{"pageNumber":"505","pageRowStart":"12600","pageSize":"25","recordCount":40783,"records":[{"id":70200465,"text":"70200465 - 2016 - Demographic modeling for reintroduction decision-making","interactions":[],"lastModifiedDate":"2018-10-24T10:37:37","indexId":"70200465","displayToPublicDate":"2016-01-01T14:27:02","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Demographic modeling for reintroduction decision-making","docAbstract":"In this chapter we consider the construction and use of population models to support reintroduction decision making. We begin by reviewing the decision-analytic process, also known as structured decision making. The material on structured decision making builds on the chapter by Chauvenet et al. (This Volume) who focus their attention on the objective setting step of structured decision making. In a decision-analytic setting, modeling cannot commence before objective setting, because the purpose of models is to provide predictions about how different management alternatives will influence the attainment of management objectives. After the introductory section on structured decision making, we turn our attention to the construction and use of population models. We discuss the steps in modeling, including structuring and planning models, obtaining parameter estimates from data, filling information gaps using expert judgment, constructing models, and using models to evaluate action alternatives. We close the chapter with a discussion of research and development needs that we believe will advance the use of population models to support the effective management of reintroduced populations.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reintroduction of fish and wildlife populations","language":"English","publisher":"University of California Press","usgsCitation":"Converse, S.J., and Armstrong, D.P., 2016, Demographic modeling for reintroduction decision-making, chap. <i>of</i> Reintroduction of fish and wildlife populations, p. 123-146.","productDescription":"24 p.","startPage":"123","endPage":"146","ipdsId":"IP-069447","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":358689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":358524,"type":{"id":15,"text":"Index Page"},"url":"https://www.ucpress.edu/book/9780520284616/reintroduction-of-fish-and-wildlife-populations"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10af84e4b034bf6a7e89da","contributors":{"authors":[{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":748992,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Armstrong, Doug P.","contributorId":209868,"corporation":false,"usgs":false,"family":"Armstrong","given":"Doug","email":"","middleInitial":"P.","affiliations":[{"id":13571,"text":"Massey University","active":true,"usgs":false}],"preferred":false,"id":748993,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70178823,"text":"70178823 - 2016 - Silicic lunar volcanism: Testing the crustal melting model","interactions":[],"lastModifiedDate":"2019-02-18T09:56:49","indexId":"70178823","displayToPublicDate":"2016-01-01T14:22:49","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"Silicic lunar volcanism: Testing the crustal melting model","docAbstract":"<p>Lunar silicic rocks were first identified by granitic fragments found in samples brought to Earth by the Apollo missions, followed by the discovery of silicic domes on the lunar surface through remote sensing. Although these silicic lithologies are thought to make up a small portion of the lunar crust, their presence indicates that lunar crustal evolution is more complex than originally thought. Models currently used to describe the formation of silicic lithologies on the Moon include in situ differentiation of a magma, magma differentiation with silicate liquid immiscibility, and partial melting of the crust. This study focuses on testing a crustal melting model through partial melting experiments on compositions representing lithologies spatially associated with the silicic domes. The experiments were guided by the results of modeling melting temperatures and residual melt compositions of possible protoliths for lunar silicic rocks using the thermodynamic modeling software, rhyolite-MELTS.</p><p>Rhyolite-MELTS simulations predict liquidus temperatures of 950–1040 °C for lunar granites under anhydrous conditions, which guided the temperature range for the experiments. Monzogabbro, alkali gabbronorite, and KREEP basalt were identified as potential protoliths due to their ages, locations on the Moon (i.e., located near observed silicic domes), chemically evolved compositions, and the results from rhyolite-MELTS modeling. Partial melting experiments, using mixtures of reagent grade oxide powders representing bulk rock compositions of these rock types, were carried out at atmospheric pressure over the temperature range of 900–1100 °C. Because all lunar granite samples and remotely sensed domes have an elevated abundance of Th, some of the mixtures were doped with Th to observe its partitioning behavior.</p><p>Run products show that at temperatures of 1050 and 1100 °C, melts of the three protoliths are not silicic in nature (i.e., they have &lt;63 wt% SiO<sub>2</sub>). By 1000 °C, melts of both monzogabbro and alkali gabbronorite approach the composition of granite, but are also characterized by immiscible Si-rich and Fe-rich liquids. Furthermore, Th strongly partitions into the Fe-rich, and not the Si-rich glass in all experimental runs.</p><p>Our work provides important constraints on the mechanism of silicic melt formation on the Moon. The observed high-Th content of lunar granite is difficult to explain by silicate liquid immiscibility, because through this process, Th is not fractionated into the Si-rich phase. Results of our experiments and modeling suggests that silicic lunar rocks could be produced from monzogabbro and alkali gabbronorite protoliths by partial melting at<span>&nbsp;</span><i>T</i><span>&nbsp;</span>&lt; 1000 °C. Additionally, we speculate that at higher pressures (<i>P</i><span>&nbsp;</span>≥ 0.005 GPa), the observed immiscibility in the partial melting experiments would be suppressed.</p>","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/am-2016-5619","usgsCitation":"Gullikson, A., Hagerty, J., Reid, M.R., Rapp, J., and Draper, D.S., 2016, Silicic lunar volcanism: Testing the crustal melting model: American Mineralogist, v. 101, no. 10, p. 2312-2321, https://doi.org/10.2138/am-2016-5619.","productDescription":"10 p.","startPage":"2312","endPage":"2321","ipdsId":"IP-066882","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":488778,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2138/am-2016-5619","text":"Publisher Index Page"},{"id":356294,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"101","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-01","publicationStatus":"PW","scienceBaseUri":"5b6fca0ee4b0f5d57878ec86","contributors":{"authors":[{"text":"Gullikson, Amber","contributorId":177311,"corporation":false,"usgs":false,"family":"Gullikson","given":"Amber","affiliations":[],"preferred":false,"id":741899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hagerty, Justin 0000-0003-3800-7948 jhagerty@usgs.gov","orcid":"https://orcid.org/0000-0003-3800-7948","contributorId":911,"corporation":false,"usgs":true,"family":"Hagerty","given":"Justin","email":"jhagerty@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":741900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reid, Mary R.","contributorId":11925,"corporation":false,"usgs":true,"family":"Reid","given":"Mary","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":741901,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rapp, Jennifer F.","contributorId":206830,"corporation":false,"usgs":false,"family":"Rapp","given":"Jennifer F.","affiliations":[],"preferred":false,"id":741902,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Draper, David S.","contributorId":206831,"corporation":false,"usgs":false,"family":"Draper","given":"David","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":741903,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70162270,"text":"70162270 - 2016 - Understanding environmental DNA detection probabilities: A case study using a stream-dwelling char <i>Salvelinus fontinalis</i>","interactions":[],"lastModifiedDate":"2016-01-20T12:26:57","indexId":"70162270","displayToPublicDate":"2016-01-01T13:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Understanding environmental DNA detection probabilities: A case study using a stream-dwelling char <i>Salvelinus fontinalis</i>","docAbstract":"<p>Environmental DNA sampling (eDNA) has emerged as a powerful tool for detecting aquatic animals. Previous research suggests that eDNA methods are substantially more sensitive than traditional sampling. However, the factors influencing eDNA detection and the resulting sampling costs are still not well understood. Here we use multiple experiments to derive independent estimates of eDNA production rates and downstream persistence from brook trout (<i>Salvelinus fontinalis</i>) in streams. We use these estimates to parameterize models comparing the false negative detection rates of eDNA sampling and traditional backpack electrofishing. We find that using the protocols in this study eDNA had reasonable detection probabilities at extremely low animal densities (e.g., probability of detection 0.18 at densities of one fish per stream kilometer) and very high detection probabilities at population-level densities (e.g., probability of detection &gt; 0.99 at densities of &ge; 3 fish per 100 m). This is substantially more sensitive than traditional electrofishing for determining the presence of brook trout and may translate into important cost savings when animals are rare. Our findings are consistent with a growing body of literature showing that eDNA sampling is a powerful tool for the detection of aquatic species, particularly those that are rare and difficult to sample using traditional methods.</p>","language":"English","publisher":"Elsevier","publisherLocation":"Kidlington, Oxford","doi":"10.1016/j.biocon.2015.12.023","usgsCitation":"Wilcox, T., Mckelvey, K.S., Young, M.K., Sepulveda, A.J., Shepard, B.B., Jane, S., Whiteley, A.R., Lowe, W.H., and Schwartz, M.K., 2016, Understanding environmental DNA detection probabilities: A case study using a stream-dwelling char <i>Salvelinus fontinalis</i>: Biological Conservation, v. 194, p. 209-216, https://doi.org/10.1016/j.biocon.2015.12.023.","productDescription":"8 p.","startPage":"209","endPage":"216","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066118","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471355,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2015.12.023","text":"Publisher Index Page"},{"id":314525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Shields River and Blackfoot River watersheds","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104.08447265624999,\n              48.99463598353405\n            ],\n            [\n              -104.08447265624999,\n              44.99588261816546\n            ],\n            [\n              -111.11572265625,\n              45.01141864227728\n            ],\n            [\n              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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56a0bdd9e4b0961cf280dc30","contributors":{"authors":[{"text":"Wilcox, Taylor","contributorId":152363,"corporation":false,"usgs":false,"family":"Wilcox","given":"Taylor","email":"","affiliations":[{"id":18916,"text":"U.S. Department of Agriculture, Forest Service, National Genomics Center for Wildlife and Fish Conservation, Rocky Mountain Research Station, Missoula, MT 59801 USA","active":true,"usgs":false}],"preferred":false,"id":589054,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mckelvey, Kevin S.","contributorId":22617,"corporation":false,"usgs":true,"family":"Mckelvey","given":"Kevin","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":589055,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Michael K.","contributorId":34253,"corporation":false,"usgs":true,"family":"Young","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":589056,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sepulveda, Adam J. 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":150628,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":589053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shepard, Bradley B.","contributorId":57327,"corporation":false,"usgs":true,"family":"Shepard","given":"Bradley","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":589057,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jane, Stephen F","contributorId":152365,"corporation":false,"usgs":false,"family":"Jane","given":"Stephen F","affiliations":[{"id":18918,"text":"Department of Environmental Conservation, University of Massachusetts, Amherst, MA, 01003, USA","active":true,"usgs":false}],"preferred":false,"id":589058,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Whiteley, Andrew R.","contributorId":150155,"corporation":false,"usgs":false,"family":"Whiteley","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":589059,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lowe, Winsor H.","contributorId":126722,"corporation":false,"usgs":false,"family":"Lowe","given":"Winsor","email":"","middleInitial":"H.","affiliations":[{"id":6577,"text":"University of Montana, Division of Biological Sciences, Missoula, MT, 59812, USA.","active":true,"usgs":false}],"preferred":false,"id":589060,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schwartz, Michael K.","contributorId":102326,"corporation":false,"usgs":true,"family":"Schwartz","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":589061,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70159817,"text":"70159817 - 2016 - Moss and vascular plant indices in Ohio wetlands have similar environmental predictors","interactions":[],"lastModifiedDate":"2016-01-06T12:12:51","indexId":"70159817","displayToPublicDate":"2016-01-01T13:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Moss and vascular plant indices in Ohio wetlands have similar environmental predictors","docAbstract":"<p>Mosses and vascular plants have been shown to be reliable indicators of wetland habitat delineation and environmental quality. Knowledge of the best ecological predictors of the quality of wetland moss and vascular plant communities may determine if similar management practices would simultaneously enhance both populations. We used Akaike's Information Criterion to identify models predicting a moss quality assessment index (MQAI) and a vascular plant index of biological integrity based on floristic quality (VIBI-FQ) from 27 emergent and 13 forested wetlands in Ohio, USA. The set of predictors included the six metrics from a wetlands disturbance index (ORAM) and two landscape development intensity indices (LDIs). The best single predictor of MQAI and one of the predictors of VIBI-FQ was an ORAM metric that assesses habitat alteration and disturbance within the wetland, such as mowing, grazing, and agricultural practices. However, the best single predictor of VIBI-FQ was an ORAM metric that assessed wetland vascular plant communities, interspersion, and microtopography. LDIs better predicted MQAI than VIBI-FQ, suggesting that mosses may either respond more rapidly to, or recover more slowly from, anthropogenic disturbance in the surrounding landscape than vascular plants. These results supported previous predictive studies on amphibian indices and metrics and a separate vegetation index, indicating that similar wetland management practices may result in qualitatively the same ecological response for three vastly different wetland biological communities (amphibians, vascular plants, and mosses).</p>","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.ecolind.2015.11.036","usgsCitation":"Stapanian, M.A., Schumacher, W., Gara, B., Adams, J.V., and Viau, N., 2016, Moss and vascular plant indices in Ohio wetlands have similar environmental predictors: Ecological Indicators, v. 62, p. 138-146, https://doi.org/10.1016/j.ecolind.2015.11.036.","productDescription":"9 p.","startPage":"138","endPage":"146","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066410","costCenters":[{"id":324,"text":"Great Lakes Science 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,{"id":70169240,"text":"70169240 - 2016 - Toward more realistic projections of soil carbon dynamics by Earth system models","interactions":[],"lastModifiedDate":"2016-05-17T16:11:58","indexId":"70169240","displayToPublicDate":"2016-01-01T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Toward more realistic projections of soil carbon dynamics by Earth system models","docAbstract":"<p><span>Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015GB005239","usgsCitation":"Luo, Y., Ahlstrom, A., Allison, S.D., Batjes, N.H., Brovkin, V., Carvalhais, N., Chappell, A., Ciais, P., Davidson, E.A., Finzi, A., Georgiou, K., Guenet, B., Hararuk, O., Harden, J., He, Y., Hopkins, F., Jiang, L., Koven, C., Jackson, R.B., Jones, C.D., Lara, M., Liang, J., McGuire, A.D., Parton, W., Peng, C., Randerson, J., Salazar, A., Sierra, C., Smith, M.J., Tian, H., Todd-Brown, K.E., Torn, M.S., van Groenigen, K.J., Wang, Y., West, T.O., Wei, Y., Wieder, W.R., Xia, J., Xu, X., Xu, X., and Zhou, T., 2016, Toward more realistic projections of soil carbon dynamics by Earth system models: Global Biogeochemical Cycles, v. 30, no. 1, p. 40-56, https://doi.org/10.1002/2015GB005239.","productDescription":"17 p.","startPage":"40","endPage":"56","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067379","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471356,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gb005239","text":"Publisher Index Page"},{"id":319354,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-21","publicationStatus":"PW","scienceBaseUri":"56f50fd4e4b0f59b85e1ebec","contributors":{"authors":[{"text":"Luo, Y.","contributorId":28417,"corporation":false,"usgs":true,"family":"Luo","given":"Y.","email":"","affiliations":[],"preferred":false,"id":623545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ahlstrom, Anders","contributorId":167793,"corporation":false,"usgs":false,"family":"Ahlstrom","given":"Anders","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":623546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allison, Steven D.","contributorId":167794,"corporation":false,"usgs":false,"family":"Allison","given":"Steven","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":623547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Batjes, Niels H.","contributorId":167795,"corporation":false,"usgs":false,"family":"Batjes","given":"Niels","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":623548,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brovkin, V.","contributorId":94188,"corporation":false,"usgs":false,"family":"Brovkin","given":"V.","affiliations":[],"preferred":false,"id":623549,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carvalhais, Nuno","contributorId":167796,"corporation":false,"usgs":false,"family":"Carvalhais","given":"Nuno","email":"","affiliations":[],"preferred":false,"id":623550,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chappell, Adrian","contributorId":167797,"corporation":false,"usgs":false,"family":"Chappell","given":"Adrian","email":"","affiliations":[],"preferred":false,"id":623551,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ciais, Philippe","contributorId":40719,"corporation":false,"usgs":true,"family":"Ciais","given":"Philippe","affiliations":[],"preferred":false,"id":623552,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Davidson, Eric A.","contributorId":7983,"corporation":false,"usgs":true,"family":"Davidson","given":"Eric","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":623553,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Finzi, Adien","contributorId":167798,"corporation":false,"usgs":false,"family":"Finzi","given":"Adien","affiliations":[],"preferred":false,"id":623554,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Georgiou, Katerina 0000-0002-2819-3292","orcid":"https://orcid.org/0000-0002-2819-3292","contributorId":167799,"corporation":false,"usgs":false,"family":"Georgiou","given":"Katerina","email":"","affiliations":[],"preferred":false,"id":623555,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Guenet, Bertrand","contributorId":167800,"corporation":false,"usgs":false,"family":"Guenet","given":"Bertrand","email":"","affiliations":[],"preferred":false,"id":623556,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hararuk, Oleksandra","contributorId":167801,"corporation":false,"usgs":false,"family":"Hararuk","given":"Oleksandra","email":"","affiliations":[],"preferred":false,"id":623561,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Harden, Jennifer","contributorId":46190,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","affiliations":[],"preferred":false,"id":623562,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"He, Yujie","contributorId":32444,"corporation":false,"usgs":true,"family":"He","given":"Yujie","affiliations":[],"preferred":false,"id":623563,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Hopkins, 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University","active":true,"usgs":false}],"preferred":false,"id":623570,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Jones, Chris D.","contributorId":167803,"corporation":false,"usgs":false,"family":"Jones","given":"Chris","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":623571,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Lara, M.","contributorId":17167,"corporation":false,"usgs":true,"family":"Lara","given":"M.","email":"","affiliations":[],"preferred":false,"id":623572,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Liang, J.","contributorId":80069,"corporation":false,"usgs":true,"family":"Liang","given":"J.","email":"","affiliations":[],"preferred":false,"id":623573,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":623378,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Parton, William","contributorId":75175,"corporation":false,"usgs":true,"family":"Parton","given":"William","affiliations":[],"preferred":false,"id":623574,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Peng, Changhui","contributorId":8357,"corporation":false,"usgs":true,"family":"Peng","given":"Changhui","affiliations":[],"preferred":false,"id":623575,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Randerson, J.","contributorId":94458,"corporation":false,"usgs":true,"family":"Randerson","given":"J.","affiliations":[],"preferred":false,"id":623576,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Salazar, Alejandro","contributorId":167804,"corporation":false,"usgs":false,"family":"Salazar","given":"Alejandro","email":"","affiliations":[],"preferred":false,"id":623577,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Sierra, Carlos A.","contributorId":30521,"corporation":false,"usgs":true,"family":"Sierra","given":"Carlos A.","affiliations":[],"preferred":false,"id":623578,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Smith, Matthew J.","contributorId":61701,"corporation":false,"usgs":true,"family":"Smith","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":623579,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Tian, Hanqin","contributorId":117981,"corporation":false,"usgs":true,"family":"Tian","given":"Hanqin","email":"","affiliations":[],"preferred":false,"id":623580,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Todd-Brown, Katherine E. O","contributorId":167805,"corporation":false,"usgs":false,"family":"Todd-Brown","given":"Katherine","email":"","middleInitial":"E. O","affiliations":[],"preferred":false,"id":623581,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Torn, Margaret S.","contributorId":28179,"corporation":false,"usgs":false,"family":"Torn","given":"Margaret","email":"","middleInitial":"S.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false},{"id":6670,"text":"Lawrence Berkeley National Laboratory, Berkeley, CA","active":true,"usgs":false}],"preferred":false,"id":623582,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"van Groenigen, Kees Jan","contributorId":167806,"corporation":false,"usgs":false,"family":"van Groenigen","given":"Kees","email":"","middleInitial":"Jan","affiliations":[],"preferred":false,"id":623583,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Wang, Ying","contributorId":76237,"corporation":false,"usgs":true,"family":"Wang","given":"Ying","email":"","affiliations":[],"preferred":false,"id":623584,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"West, Tristram O.","contributorId":39230,"corporation":false,"usgs":true,"family":"West","given":"Tristram","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":623585,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Wei, Yaxing","contributorId":79347,"corporation":false,"usgs":true,"family":"Wei","given":"Yaxing","email":"","affiliations":[],"preferred":false,"id":623586,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Wieder, William R.","contributorId":75792,"corporation":false,"usgs":true,"family":"Wieder","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":623587,"contributorType":{"id":1,"text":"Authors"},"rank":37},{"text":"Xia, Jianyang","contributorId":167809,"corporation":false,"usgs":false,"family":"Xia","given":"Jianyang","email":"","affiliations":[],"preferred":false,"id":623588,"contributorType":{"id":1,"text":"Authors"},"rank":38},{"text":"Xu, Xia","contributorId":167810,"corporation":false,"usgs":false,"family":"Xu","given":"Xia","email":"","affiliations":[],"preferred":false,"id":623589,"contributorType":{"id":1,"text":"Authors"},"rank":39},{"text":"Xu, Xiaofeng","contributorId":167811,"corporation":false,"usgs":false,"family":"Xu","given":"Xiaofeng","email":"","affiliations":[],"preferred":false,"id":623590,"contributorType":{"id":1,"text":"Authors"},"rank":40},{"text":"Zhou, T.","contributorId":93248,"corporation":false,"usgs":true,"family":"Zhou","given":"T.","email":"","affiliations":[],"preferred":false,"id":623591,"contributorType":{"id":1,"text":"Authors"},"rank":41}]}}
,{"id":70199655,"text":"70199655 - 2016 - Pre-Mississippian tectonic affinity across the Canada Basin–Arctic margins of Alaska and Canada","interactions":[],"lastModifiedDate":"2018-09-24T11:48:21","indexId":"70199655","displayToPublicDate":"2016-01-01T11:48:10","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Pre-Mississippian tectonic affinity across the Canada Basin–Arctic margins of Alaska and Canada","docAbstract":"<p><span>New and reprocessed seismic reflection data on the Alaskan and Canadian Arctic margins of the Canada Basin, together with geologic constraints from exploration wells and outcrops, reveal structural and stratigraphic relationships in pre-Mississippian rocks that constrain models of Canada Basin opening. Lithostratigraphic age and acoustic character indicate that the Devonian and older passive-margin to foreland-basin succession in the Canadian M’Clure Strait is also found on the central Alaska margin. This succession also displays similar structural geometry and relief as well as deformational age on both margins. Moreover, Middle Devonian to Early Mississippian tectonic vergence—north directed on the central Alaska margin and east directed in the Canadian M’Clure Strait—indicates a common direction of tectonic transport if the two margins were conjugate. All of these observations demonstrate that pre-Mississippian rocks of the Alaskan and Canadian Arctic margins share a common tectonic history of uplift and exhumation and that the two margins were conjugates prior to opening of the Canada Basin.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/G37862.1","usgsCitation":"Houseknecht, D.W., and Connors, C., 2016, Pre-Mississippian tectonic affinity across the Canada Basin–Arctic margins of Alaska and Canada: Geology, v. 44, no. 7, p. 507-510, https://doi.org/10.1130/G37862.1.","productDescription":"4 p.","startPage":"507","endPage":"510","ipdsId":"IP-073852","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":471357,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g37862.1","text":"Publisher Index Page"},{"id":357672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -160,\n              69\n            ],\n            [\n              -144,\n              69\n            ],\n            [\n              -144,\n              72\n            ],\n            [\n              -160,\n              72\n            ],\n            [\n              -160,\n              69\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"44","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-01","publicationStatus":"PW","scienceBaseUri":"5bc03402e4b0fc368eb53a92","contributors":{"authors":[{"text":"Houseknecht, David W. 0000-0002-9633-6910 dhouse@usgs.gov","orcid":"https://orcid.org/0000-0002-9633-6910","contributorId":645,"corporation":false,"usgs":true,"family":"Houseknecht","given":"David","email":"dhouse@usgs.gov","middleInitial":"W.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":746083,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connors, Christopher D.","contributorId":11950,"corporation":false,"usgs":true,"family":"Connors","given":"Christopher D.","affiliations":[],"preferred":false,"id":746084,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70198530,"text":"70198530 - 2016 - Slab-rollback ignimbrite flareups in the southern Great Basin and other Cenozoic American arcs: A distinct style of arc volcanism","interactions":[],"lastModifiedDate":"2018-08-07T11:47:45","indexId":"70198530","displayToPublicDate":"2016-01-01T11:45:02","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Slab-rollback ignimbrite flareups in the southern Great Basin and other Cenozoic American arcs: A distinct style of arc volcanism","docAbstract":"<p>In continental-margin subduction zones, basalt magmas spawned in the mantle interact with the crust to produce a broad spectrum of volcanic arc associations. A distinct style of very voluminous arc volcanism develops far inland on thick crust over periods of 10–20 m.y. and involves relatively infrequent caldera-forming explosive eruptions of dominantly calc-alkaline rhyolite, dacite, and trachydacite with repose times of 10<sup>4</sup>–10<sup>6</sup><span>&nbsp;</span>yr. Volumes of individual eruptions are large (10<sup>2</sup>–10<sup>3</sup><span>&nbsp;</span>km<sup>3</sup>), and nested super-eruptions of thousands of cubic kilometers are common. Calderas are as much as 60–75 km in diameter, and surrounding individual ignimbrite outflow sheets extend outward as much as 150 km, blanketing upwards of 10<sup>5</sup><span>&nbsp;</span>km<sup>2</sup>. Little or no basalt is extruded, whereas andesitic differentiates coeval with silicic ignimbrites range from minor to dominant in relative volume. A common feature in these flareups is essentially nonextending, thick, inland crust overlying a subducting oceanic plate with transverse tears that rolled back to a steeper dip from a previously flat configuration. Lithospheric delamination is locally possible. Large volumes of basalt that provide heat and mass for silicic magma generation in the crust form by fluid fluxing of the growing mantle wedge overlying the steepening dehydrating slab and from asthenospheric decompression. Variations in the mantle input, together with variations in crustal thickness, temperature, and composition, modulate the expression of the flareups. As a consequence of the high flux of mantle-derived magma into the thick crust, geotherms become elevated, and the brittle-ductile transition can rise to depths as shallow as 7 km. At this transition, diapirically rising magmas from a melting, assimilation, storage, and homogenization (MASH) zone are blocked and spread laterally into discoid chambers that grow until a thermomechanical threshold is attained, triggering climactic eruption and caldera collapse.</p><p>This ignimbrite flareup style of continental arc volcanism is exemplified by the mid-Cenozoic southern Great Basin ignimbrite province; other examples include the contemporaneous Southern Rocky Mountain, Mogollon-Datil, vast Sierra Madre Occidental volcanic fields, and the late Cenozoic Altiplano-Puna volcanic complex in the Central Andes. Rhyolitic and trachydacitic ignimbrites typically have erupted, but where the crust was predominantly felsic, prewarmed, and orogenically thickened, well-developed MASH zones have spawned multiple super-eruptions of phenocryst-rich dacite, or monotonous intermediates, and smaller volumes of calc-alkaline rhyolite ignimbrite. In the Great Basin, eruptions of dry, hot trachydacite magma followed the monotonous intermediates. Partial melting in thinner crust with a major mafic component yielded more alkalic rhyolite and related trachydacite.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01285.1","usgsCitation":"Best, M.G., Christiansen, E.H., de Silva, S., and Lipman, P.W., 2016, Slab-rollback ignimbrite flareups in the southern Great Basin and other Cenozoic American arcs: A distinct style of arc volcanism: Geosphere, v. 12, no. 4, p. 1097-1135, https://doi.org/10.1130/GES01285.1.","productDescription":"39 p.","startPage":"1097","endPage":"1135","ipdsId":"IP-099383","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":471358,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01285.1","text":"Publisher Index Page"},{"id":356276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Utah","otherGeospatial":"Great Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121,\n              36\n            ],\n            [\n              -111,\n              36\n            ],\n            [\n              -111,\n              42\n            ],\n            [\n              -121,\n              42\n            ],\n            [\n              -121,\n              36\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-27","publicationStatus":"PW","scienceBaseUri":"5b6fca0fe4b0f5d57878ec8a","contributors":{"authors":[{"text":"Best, Myron G.","contributorId":206800,"corporation":false,"usgs":false,"family":"Best","given":"Myron","email":"","middleInitial":"G.","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":741801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christiansen, Eric H.","contributorId":206801,"corporation":false,"usgs":false,"family":"Christiansen","given":"Eric","email":"","middleInitial":"H.","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":741802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"de Silva, Shanaka","contributorId":206802,"corporation":false,"usgs":false,"family":"de Silva","given":"Shanaka","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":741803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lipman, Peter W. 0000-0001-9175-6118","orcid":"https://orcid.org/0000-0001-9175-6118","contributorId":203612,"corporation":false,"usgs":true,"family":"Lipman","given":"Peter","email":"","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":741800,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70200941,"text":"70200941 - 2016 - Invasive pythons, not anthropogenic stressors, explain the distribution of a keystone species","interactions":[],"lastModifiedDate":"2018-11-16T11:18:13","indexId":"70200941","displayToPublicDate":"2016-01-01T11:18:04","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Invasive pythons, not anthropogenic stressors, explain the distribution of a keystone species","docAbstract":"<p><span>Untangling the causes of native species loss in human-modified systems is difficult and often controversial. Evaluating the impact of non-native species in these systems is particularly challenging, as additional human perturbations often precede or accompany introductions. One example is the ongoing debate over whether mammal declines within Everglades National Park (ENP) were caused by either the establishment of non-native Burmese pythons (</span><i class=\"EmphasisTypeItalic \">Python molurus bivittatus</i><span>) or the effects of other anthropogenic stressors. We examined the influence of both pythons and a host of alternative stressors—altered hydrology and habitat characteristics, mercury contamination and development—on the distribution of the marsh rabbit (</span><i class=\"EmphasisTypeItalic \">Sylvilagus palustris</i><span>), a once common mammal in ENP. Distance from the epicenter of the python invasion best explained marsh rabbit occurrence in suitable habitat patches, whereas none of the alternative stressors considered could explain marsh rabbit distribution. Estimates of the probability of marsh rabbit occurrence ranged from 0 at the python invasion epicenter to nearly 1.0 150&nbsp;km from the invasion epicenter. These results support the hypothesis that invasive pythons shape the distribution of marsh rabbits in southern Florida. The loss of marsh rabbits and similar species will likely alter trophic interactions and ecosystem function within the Everglades, an internationally important hotspot of biodiversity. Further, our results suggest that non-native species can have profound impacts on mainland biodiversity.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10530-016-1221-3","usgsCitation":"Sovie, A.R., McCleery, R.A., Fletcher, R.J., and Hart, K.M., 2016, Invasive pythons, not anthropogenic stressors, explain the distribution of a keystone species: Biological Invasions, v. 18, no. 11, p. 3309-3318, https://doi.org/10.1007/s10530-016-1221-3.","productDescription":"10 p.","startPage":"3309","endPage":"3318","ipdsId":"IP-065121","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":359512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades Ecosystem","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.012939453125,\n              24.407137917727667\n            ],\n            [\n              -79.991455078125,\n              24.407137917727667\n            ],\n            [\n              -79.991455078125,\n              27.254629577800063\n            ],\n            [\n              -82.012939453125,\n              27.254629577800063\n            ],\n            [\n              -82.012939453125,\n              24.407137917727667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"18","issue":"11","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-09","publicationStatus":"PW","scienceBaseUri":"5befe5bde4b045bfcadf7f4e","contributors":{"authors":[{"text":"Sovie, Adia R.","contributorId":197424,"corporation":false,"usgs":false,"family":"Sovie","given":"Adia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":751411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCleery, Robert A.","contributorId":139849,"corporation":false,"usgs":false,"family":"McCleery","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":751412,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fletcher, Robert J. 0000-0003-1717-5707","orcid":"https://orcid.org/0000-0003-1717-5707","contributorId":195795,"corporation":false,"usgs":false,"family":"Fletcher","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":751413,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":751410,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70164444,"text":"70164444 - 2016 - Along-strike variations in fault frictional properties along the San Andreas Fault near Cholame, California from joint earthquake and low-frequency earthquake relocations","interactions":[],"lastModifiedDate":"2017-01-03T15:56:54","indexId":"70164444","displayToPublicDate":"2016-01-01T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Along-strike variations in fault frictional properties along the San Andreas Fault near Cholame, California from joint earthquake and low-frequency earthquake relocations","docAbstract":"<p>Recent observations of low‐frequency earthquakes (LFEs) and tectonic tremor along the Parkfield&ndash;Cholame segment of the San Andreas fault suggest slow‐slip earthquakes occur in a transition zone between the shallow fault, which accommodates slip by a combination of aseismic creep and earthquakes (&lt;15&thinsp;&thinsp;km depth), and the deep fault, which accommodates slip by stable sliding (&gt;35&thinsp;&thinsp;km depth). However, the spatial relationship between shallow earthquakes and LFEs remains unclear. Here, we present precise relocations of 34 earthquakes and 34 LFEs recorded during a temporary deployment of 13 broadband seismic stations from May 2010 to July 2011. We use the temporary array waveform data, along with data from permanent seismic stations and a new high‐resolution 3D velocity model, to illuminate the fine‐scale details of the seismicity distribution near Cholame and the relation to the distribution of LFEs. The depth of the boundary between earthquakes and LFE hypocenters changes along strike and roughly follows the 350&deg;C isotherm, suggesting frictional behavior may be, in part, thermally controlled. We observe no overlap in the depth of earthquakes and LFEs, with an &sim;5&thinsp;&thinsp;km separation between the deepest earthquakes and shallowest LFEs. In addition, clustering in the relocated seismicity near the 2004 <i>M</i><sub>w</sub> 6.0 Parkfield earthquake hypocenter and near the northern boundary of the 1857 <i>M</i><sub>w</sub> 7.8 Fort Tejon rupture may highlight areas of frictional heterogeneities on the fault where earthquakes tend to nucleate.</p>","language":"English","publisher":"Seismological Society of Amercia","doi":"10.1785/0120150171","usgsCitation":"Harrington, R., Cochran, E.S., Griffiths, E.M., Zeng, X., and Thurber, C.H., 2016, Along-strike variations in fault frictional properties along the San Andreas Fault near Cholame, California from joint earthquake and low-frequency earthquake relocations: Bulletin of the Seismological Society of America, v. 106, no. 2, p. 319-326, https://doi.org/10.1785/0120150171.","productDescription":"8 p.","startPage":"319","endPage":"326","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066396","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":316595,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70202285,"text":"70202285 - 2016 - Management-driven science synthesis: An evaluation of Everglades restoration trajectories","interactions":[],"lastModifiedDate":"2019-02-20T11:02:00","indexId":"70202285","displayToPublicDate":"2016-01-01T10:59:43","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Management-driven science synthesis: An evaluation of Everglades restoration trajectories","docAbstract":"The Synthesis of Everglades Restoration andEcosystem Services (SERES) Project was funded in 2010 by the U.S. Department of Interior (DOI) through the Critical Ecosystem Studies Initiative (CESI) and established to synthesize the ever-growing body of Everglades scientific information with the goal of addressing topics that have hampered restoration since the Comprehensive Everglades Restoration Plan (CERP) was passed in 2000. A distinguishing characteristic of this synthesis effort was that the target end-user was a management/\ndecision-maker audience. Specifically, the aim was to address the questions of the water managers and other decision leaders in a way that would illuminate and inform but not constrain or specify decisions. Since its inception, the SERES Project has been managed by the Everglades Foundation; however, a core group of scientifc experts from agencies, academic institutions, and the private sector have contributed to the project (see list on page 4). We\nbegan the project by interviewing key officials, including resource managers, decision-makers, and heads of agencies and environmental organizations. The objective of these interviews was to establish the Key Science Management Questions that needed to be addressed in order to advance restoration of the Everglades. The resulting questions led to the organization of project teams focused on Hydrology, Water Quality, Soils, Trophic Dynamics, and Landscape\nPattern. In order to establish the technical basis for the project, we conducted in depth reviews of the recent scientifc literature, evaluation tools and models, and available data in each of these core areas. Finally, we developed a suite of restoration options that would aid us in addressing the Key Questions and evaluated their relative performance from hydrological, ecological, and economic perspectives. General fndings of the SERES Project are described in subsequent sections, and technical reviews and results of analyses supporting this document are available in reports on the project website.","language":"English","publisher":"Everglades Foundation","usgsCitation":"Davis, S.E., Beerens, J.M., Borkhataria, R.R., Childers, D.L., Choi, J., Davis, S.M., Fitz, C., Gaiser, E., Henriquez, H., Lodge, T.E., Harvey, J., Marshall, F., McCormick, B., Naja, M., Osborne, T., Ross, M.S., Sah, J., Trexler, J.C., Van Lent, T., and Wetzel, P.R., 2016, Management-driven science synthesis: An evaluation of Everglades restoration trajectories, 60 p.","productDescription":"60 p.","ipdsId":"IP-071537","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":361381,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":361370,"type":{"id":15,"text":"Index Page"},"url":"https://www.evergladesfoundation.org/our-efforts/reports-papers/"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.8753662109375,\n              25.030861410390447\n            ],\n            [\n              -79.98596191406249,\n              25.030861410390447\n            ],\n            [\n              -79.98596191406249,\n              28.38173504322308\n            ],\n            [\n              -82.8753662109375,\n              28.38173504322308\n            ],\n            [\n              -82.8753662109375,\n              25.030861410390447\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Stephen E","contributorId":213386,"corporation":false,"usgs":false,"family":"Davis","given":"Stephen","email":"","middleInitial":"E","affiliations":[{"id":17761,"text":"Everglades Foundation","active":true,"usgs":false}],"preferred":false,"id":757631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beerens, James M. 0000-0001-8143-916X jbeerens@usgs.gov","orcid":"https://orcid.org/0000-0001-8143-916X","contributorId":143722,"corporation":false,"usgs":true,"family":"Beerens","given":"James","email":"jbeerens@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":757630,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borkhataria, Rena R.","contributorId":197425,"corporation":false,"usgs":false,"family":"Borkhataria","given":"Rena","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":757632,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Childers, Daniel L.","contributorId":201937,"corporation":false,"usgs":false,"family":"Childers","given":"Daniel","email":"","middleInitial":"L.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":757633,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Choi, Jay","contributorId":213387,"corporation":false,"usgs":true,"family":"Choi","given":"Jay","affiliations":[{"id":436,"text":"National Research Program - 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,{"id":70194448,"text":"70194448 - 2016 - LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models","interactions":[],"lastModifiedDate":"2018-01-24T16:05:13","indexId":"70194448","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1999,"text":"Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models","docAbstract":"<p><span>Metabolism is a fundamental process in ecosystems that crosses multiple scales of organization from individual organisms to whole ecosystems. To improve sharing and reuse of published metabolism models, we developed LakeMetabolizer, an R package for estimating lake metabolism from&nbsp;</span><i>in situ<span>&nbsp;</span></i><span>time series of dissolved oxygen, water temperature, and, optionally, additional environmental variables. LakeMetabolizer implements 5 different metabolism models with diverse statistical underpinnings: bookkeeping, ordinary least squares, maximum likelihood, Kalman filter, and Bayesian. Each of these 5 metabolism models can be combined with 1 of 7 models for computing the coefficient of gas exchange across the air–water interface (</span><i>k</i><span>). LakeMetabolizer also features a variety of supporting functions that compute conversions and implement calculations commonly applied to raw data prior to estimating metabolism (e.g., oxygen saturation and optical conversion models). These tools have been organized into an R package that contains example data, example use-cases, and function documentation. The release package version is available on the Comprehensive R Archive Network (CRAN), and the full open-source GPL-licensed code is freely available for examination and extension online. With this unified, open-source, and freely available package, we hope to improve access and facilitate the application of metabolism in studies and management of lentic ecosystems.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/IW-6.4.883","usgsCitation":"Winslow, L., Zwart, J., Batt, R., Dugan, H., Woolway, R., Corman, J., Hanson, P.C., and Read, J.S., 2016, LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models: Inland Waters, v. 6, no. 4, p. 622-636, https://doi.org/10.1080/IW-6.4.883.","productDescription":"15 p.","startPage":"622","endPage":"636","ipdsId":"IP-065534","costCenters":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"links":[{"id":349534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-02","publicationStatus":"PW","scienceBaseUri":"5a60fd87e4b06e28e9c24fa5","contributors":{"authors":[{"text":"Winslow, Luke 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":168947,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":723877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zwart, Jacob A.","contributorId":173345,"corporation":false,"usgs":false,"family":"Zwart","given":"Jacob A.","affiliations":[{"id":16905,"text":"University of Notre Dame, Dept. of Biological Sciences, Notre Dame, IN, 46556, USA","active":true,"usgs":false}],"preferred":false,"id":723878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Batt, Ryan D.","contributorId":168948,"corporation":false,"usgs":false,"family":"Batt","given":"Ryan D.","affiliations":[{"id":25393,"text":"Department of Ecology, Evolution, and Natural Resources, Rutgers University, New Brunswick, New Jersey, USA 08901","active":true,"usgs":false}],"preferred":false,"id":723879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dugan, Hilary","contributorId":150191,"corporation":false,"usgs":false,"family":"Dugan","given":"Hilary","affiliations":[{"id":17938,"text":"Center for Limnology University of Wisconsin, Madison, WI 53706, US","active":true,"usgs":false}],"preferred":false,"id":723880,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woolway, R. Iestyn","contributorId":150345,"corporation":false,"usgs":false,"family":"Woolway","given":"R. Iestyn","affiliations":[{"id":18007,"text":"Lake Ecosystems Group, Centre for Ecology & Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster, LA1 4AP, UK.","active":true,"usgs":false}],"preferred":false,"id":723881,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corman, Jessica","contributorId":194469,"corporation":false,"usgs":false,"family":"Corman","given":"Jessica","affiliations":[],"preferred":false,"id":723882,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hanson, Paul C.","contributorId":35634,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":723883,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":723884,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70198170,"text":"70198170 - 2016 - Nutrient dynamics of the Delta: Effects on primary producers","interactions":[],"lastModifiedDate":"2018-07-18T16:03:45","indexId":"70198170","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Nutrient dynamics of the Delta: Effects on primary producers","docAbstract":"<p><span>Increasing clarity of Delta waters, the emergence of harmful algal blooms, the proliferation of aquatic water weeds, and the altered food web of the Delta have brought nutrient dynamics to the forefront. This paper focuses on the sources of nutrients, the transformation and uptake of nutrients, and the links of nutrients to primary producers. The largest loads of nutrients to the Delta come from the Sacramento River with the San Joaquin River seasonally important, especially in the summer. Nutrient concentrations reflect riverine inputs in winter and internal biological processes during periods of lower flow with internal nitrogen losses within the Delta estimated at approximately 30% annually. Light regime, grazing pressure, and nutrient availability influence rates of primary production at different times and locations within the Delta. The roles of the chemical form of dissolved inorganic nitrogen in growth rates of primary producers in the Delta and the structure of the open-water algal community are currently topics of much interest and considerable debate. Harmful algal blooms have been noted since the late 1990s, and the extent of invasive aquatic macrophytes (both submerged and free-floating forms) has increased especially during years of drought. Elevated nutrient loads must be considered in terms of their ability to support this excess biomass. Modern sensor technology and networks are now deployed that make high-frequency measurements of nitrate, ammonium, and phosphate. Data from such instruments allow a much more detailed assessment of the spatial and temporal dynamics of nutrients. Four fruitful directions for future research include utilizing continuous sensor data to estimate rates of primary production and ecosystem respiration, linking hydrodynamic models of the Delta with the transport and fate of dissolved nutrients, studying nutrient dynamics in various habitat types, and exploring the use of stable isotopes to trace the movement and fate of effluent-derived nutrients.</span></p>","language":"English","publisher":"University of California","doi":"10.15447/sfews.2016v14iss4art4","usgsCitation":"Dahm, C., Parker, A.E., Adelson, A.E., Christman, M.A., and Bergamaschi, B.A., 2016, Nutrient dynamics of the Delta: Effects on primary producers: San Francisco Estuary and Watershed Science, v. 14, no. 4, Article 4; 35 p., https://doi.org/10.15447/sfews.2016v14iss4art4.","productDescription":"Article 4; 35 p.","ipdsId":"IP-099451","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":471375,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2016v14iss4art4","text":"Publisher Index Page"},{"id":355816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.13775634765625,\n              37.73053874574077\n            ],\n            [\n              -121.25610351562499,\n              37.73053874574077\n            ],\n            [\n              -121.25610351562499,\n              38.25112269630296\n            ],\n            [\n              -122.13775634765625,\n              38.25112269630296\n            ],\n            [\n              -122.13775634765625,\n              37.73053874574077\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"14","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-28","publicationStatus":"PW","scienceBaseUri":"5b6fca10e4b0f5d57878ec8c","contributors":{"authors":[{"text":"Dahm, Clifford N.","contributorId":22730,"corporation":false,"usgs":false,"family":"Dahm","given":"Clifford N.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":740403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parker, Alexander E.","contributorId":206434,"corporation":false,"usgs":false,"family":"Parker","given":"Alexander","email":"","middleInitial":"E.","affiliations":[{"id":37328,"text":"California State University Maritime Academy Vallejo, CA","active":true,"usgs":false}],"preferred":false,"id":740404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adelson, Anne E.","contributorId":206435,"corporation":false,"usgs":false,"family":"Adelson","given":"Anne","email":"","middleInitial":"E.","affiliations":[{"id":37329,"text":"Delta Stewardship Council Sacramento, CA","active":true,"usgs":false}],"preferred":false,"id":740405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christman, Mairgareth A.","contributorId":206436,"corporation":false,"usgs":false,"family":"Christman","given":"Mairgareth","email":"","middleInitial":"A.","affiliations":[{"id":37330,"text":"Delta Stewardship Council, Sacramento, CA","active":true,"usgs":false}],"preferred":false,"id":740406,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":740402,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70176525,"text":"70176525 - 2016 - Non-linear responses of glaciated prairie wetlands to climate warming","interactions":[],"lastModifiedDate":"2017-05-03T13:11:51","indexId":"70176525","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"Non-linear responses of glaciated prairie wetlands to climate warming","docAbstract":"<p><span>The response of ecosystems to climate warming is likely to include threshold events when small changes in key environmental drivers produce large changes in an ecosystem. Wetlands of the Prairie Pothole Region (PPR) are especially sensitive to climate variability, yet the possibility that functional changes may occur more rapidly with warming than expected has not been examined or modeled. The productivity and biodiversity of these wetlands are strongly controlled by the speed and completeness of a vegetation cover cycle driven by the wet and dry extremes of climate. Two thresholds involving duration and depth of standing water must be exceeded every few decades or so to complete the cycle and to produce highly functional wetlands. Model experiments at 19 weather stations employing incremental warming scenarios determined that wetland function across most of the PPR would be diminished beyond a climate warming of about 1.5–2.0&nbsp;°C, a critical temperature threshold range identified in other climate change studies.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10584-015-1534-8","usgsCitation":"Johnson, W., Werner, B., and Guntenspergen, G.R., 2016, Non-linear responses of glaciated prairie wetlands to climate warming: Climatic Change, v. 134, no. 1, p. 209-223, https://doi.org/10.1007/s10584-015-1534-8.","productDescription":"15 p.","startPage":"209","endPage":"223","ipdsId":"IP-066806","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":328763,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.3837890625,\n              42.35854391749705\n            ],\n            [\n              -95.2734375,\n              46.164614496897094\n            ],\n            [\n              -95.6689453125,\n              48.37084770238363\n            ],\n            [\n              -97.5146484375,\n              50.20503326494332\n            ],\n            [\n              -105.205078125,\n              52.74959372674114\n            ],\n            [\n              -111.884765625,\n              54.265224078605655\n            ],\n            [\n              -111.9287109375,\n              50.3454604086048\n            ],\n            [\n              -105.77636718749999,\n              47.931066347509784\n            ],\n            [\n              -99.36035156249999,\n              42.94033923363183\n            ],\n            [\n              -95.185546875,\n              42.16340342422401\n            ],\n            [\n              -93.3837890625,\n              42.35854391749705\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"134","issue":"1","noUsgsAuthors":false,"publicationDate":"2015-10-22","publicationStatus":"PW","scienceBaseUri":"57f7c6e6e4b0bc0bec09cbe1","contributors":{"authors":[{"text":"Johnson, W. Carter","contributorId":17548,"corporation":false,"usgs":true,"family":"Johnson","given":"W. Carter","affiliations":[],"preferred":false,"id":649099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Werner, Brett","contributorId":47073,"corporation":false,"usgs":true,"family":"Werner","given":"Brett","affiliations":[],"preferred":false,"id":649100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":649101,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70176484,"text":"70176484 - 2016 - Dispersal and spatial heterogeneity: Single species","interactions":[],"lastModifiedDate":"2016-09-19T08:59:41","indexId":"70176484","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2384,"text":"Journal of Mathematical Biology","active":true,"publicationSubtype":{"id":10}},"title":"Dispersal and spatial heterogeneity: Single species","docAbstract":"<p><span>A recent result for a reaction-diffusion equation is that a population diffusing at any rate in an environment in which resources vary spatially will reach a higher total equilibrium biomass than the population in an environment in which the same total resources are distributed homogeneously. This has so far been proven by Lou for the case in which the reaction term has only one parameter, </span><span id=\"IEq1\" class=\"InlineEquation\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi>m</mi><mo stretchy=&quot;false&quot;>(</mo><mi>x</mi><mo stretchy=&quot;false&quot;>)</mo></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"mi\">m</span><span id=\"MathJax-Span-4\" class=\"mo\">(</span><span id=\"MathJax-Span-5\" class=\"mi\">x</span><span id=\"MathJax-Span-6\" class=\"mo\">)</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">m(x)</span></span></span><span>, varying with spatial location </span><span id=\"IEq2\" class=\"InlineEquation\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi>x</mi></math>\"><span id=\"MathJax-Span-7\" class=\"math\"><span><span><span id=\"MathJax-Span-8\" class=\"mrow\"><span id=\"MathJax-Span-9\" class=\"mi\">x</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">x</span></span></span><span>, which serves as both the intrinsic growth rate coefficient and carrying capacity of the population. However, this striking result seems rather limited when applies to real populations. In order to make the model more relevant for ecologists, we consider a logistic reaction term, with two parameters, </span><span id=\"IEq3\" class=\"InlineEquation\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi>r</mi><mo stretchy=&quot;false&quot;>(</mo><mi>x</mi><mo stretchy=&quot;false&quot;>)</mo></math>\"><span id=\"MathJax-Span-10\" class=\"math\"><span><span><span id=\"MathJax-Span-11\" class=\"mrow\"><span id=\"MathJax-Span-12\" class=\"mi\">r</span><span id=\"MathJax-Span-13\" class=\"mo\">(</span><span id=\"MathJax-Span-14\" class=\"mi\">x</span><span id=\"MathJax-Span-15\" class=\"mo\">)</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">r(x)</span></span></span><span> for intrinsic growth rate, and </span><span id=\"IEq4\" class=\"InlineEquation\"><span id=\"MathJax-Element-4-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi>K</mi><mo stretchy=&quot;false&quot;>(</mo><mi>x</mi><mo stretchy=&quot;false&quot;>)</mo></math>\"><span id=\"MathJax-Span-16\" class=\"math\"><span><span><span id=\"MathJax-Span-17\" class=\"mrow\"><span id=\"MathJax-Span-18\" class=\"mi\">K</span><span id=\"MathJax-Span-19\" class=\"mo\">(</span><span id=\"MathJax-Span-20\" class=\"mi\">x</span><span id=\"MathJax-Span-21\" class=\"mo\">)</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">K(x)</span></span></span><span> for carrying capacity. When </span><span id=\"IEq5\" class=\"InlineEquation\"><span id=\"MathJax-Element-5-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi>r</mi><mo stretchy=&quot;false&quot;>(</mo><mi>x</mi><mo stretchy=&quot;false&quot;>)</mo></math>\"><span id=\"MathJax-Span-22\" class=\"math\"><span><span><span id=\"MathJax-Span-23\" class=\"mrow\"><span id=\"MathJax-Span-24\" class=\"mi\">r</span><span id=\"MathJax-Span-25\" class=\"mo\">(</span><span id=\"MathJax-Span-26\" class=\"mi\">x</span><span id=\"MathJax-Span-27\" class=\"mo\">)</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">r(x)</span></span></span><span> and </span><span id=\"IEq6\" class=\"InlineEquation\"><span id=\"MathJax-Element-6-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi>K</mi><mo stretchy=&quot;false&quot;>(</mo><mi>x</mi><mo stretchy=&quot;false&quot;>)</mo></math>\"><span id=\"MathJax-Span-28\" class=\"math\"><span><span><span id=\"MathJax-Span-29\" class=\"mrow\"><span id=\"MathJax-Span-30\" class=\"mi\">K</span><span id=\"MathJax-Span-31\" class=\"mo\">(</span><span id=\"MathJax-Span-32\" class=\"mi\">x</span><span id=\"MathJax-Span-33\" class=\"mo\">)</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">K(x)</span></span></span><span> are proportional, the logistic equation takes a particularly simple form, and the earlier result still holds. In this paper we have established the result for the more general case of a positive correlation between </span><span id=\"IEq7\" class=\"InlineEquation\"><span id=\"MathJax-Element-7-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi>r</mi><mo stretchy=&quot;false&quot;>(</mo><mi>x</mi><mo stretchy=&quot;false&quot;>)</mo></math>\"><span id=\"MathJax-Span-34\" class=\"math\"><span><span><span id=\"MathJax-Span-35\" class=\"mrow\"><span id=\"MathJax-Span-36\" class=\"mi\">r</span><span id=\"MathJax-Span-37\" class=\"mo\">(</span><span id=\"MathJax-Span-38\" class=\"mi\">x</span><span id=\"MathJax-Span-39\" class=\"mo\">)</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">r(x)</span></span></span><span> and </span><span id=\"IEq8\" class=\"InlineEquation\"><span id=\"MathJax-Element-8-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi>K</mi><mo stretchy=&quot;false&quot;>(</mo><mi>x</mi><mo stretchy=&quot;false&quot;>)</mo></math>\"><span id=\"MathJax-Span-40\" class=\"math\"><span><span><span id=\"MathJax-Span-41\" class=\"mrow\"><span id=\"MathJax-Span-42\" class=\"mi\">K</span><span id=\"MathJax-Span-43\" class=\"mo\">(</span><span id=\"MathJax-Span-44\" class=\"mi\">x</span><span id=\"MathJax-Span-45\" class=\"mo\">)</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">K(x)</span></span></span><span> when dispersal rate is small. We review natural and laboratory systems to which these results are relevant and discuss the implications of the results to population theory and conservation ecology.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00285-015-0879-y","usgsCitation":"DeAngelis, D.L., Ni, W., and Zhang, B., 2016, Dispersal and spatial heterogeneity: Single species: Journal of Mathematical Biology, v. 72, no. 1, p. 239-254, https://doi.org/10.1007/s00285-015-0879-y.","productDescription":"16 p.","startPage":"239","endPage":"254","ipdsId":"IP-068977","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":328702,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-11","publicationStatus":"PW","scienceBaseUri":"57f7c6e6e4b0bc0bec09cbe3","contributors":{"authors":[{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":648911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ni, Wei-Ming","contributorId":146528,"corporation":false,"usgs":false,"family":"Ni","given":"Wei-Ming","email":"","affiliations":[{"id":16716,"text":"University of Minnesota : East China Normal University","active":true,"usgs":false}],"preferred":false,"id":648912,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Bo","contributorId":146526,"corporation":false,"usgs":false,"family":"Zhang","given":"Bo","email":"","affiliations":[{"id":16714,"text":"Dept. of Biology, University of Miami","active":true,"usgs":false}],"preferred":false,"id":648913,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70173732,"text":"70173732 - 2016 - Predictive habitat models derived from nest-box occupancy for the endangered Carolina northern flying squirrel in the southern Appalachians","interactions":[],"lastModifiedDate":"2022-11-01T16:37:34.298687","indexId":"70173732","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Predictive habitat models derived from nest-box occupancy for the endangered Carolina northern flying squirrel in the southern Appalachians","docAbstract":"<p><span>In the southern Appalachians, artificial nest-boxes are used to survey for the endangered Carolina northern flying squirrel (CNFS;&nbsp;</span><i>Glaucomys sabrinus coloratus</i><span>), a disjunct subspecies associated with high elevation (&gt;1385 m) forests. Using environmental parameters diagnostic of squirrel habitat, we created 35&nbsp;</span><i>a priori</i><span>&nbsp;occupancy models in the program PRESENCE for boxes surveyed in western North Carolina, 1996-2011. Our best approximating model showed CNFS denning associated with sheltered landforms and montane conifers, primarily red spruce&nbsp;</span><i>Picea rubens</i><span>. As sheltering decreased, decreasing distance to conifers was important. Area with a high probability (&gt;0.5) of occupancy was distributed over 18662 ha of habitat, mostly across 10 mountain ranges. Because nest-box surveys underrepresented areas &gt;1750 m and CNFS forage in conifers, we combined areas of high occupancy with conifer GIS coverages to create an additional distribution model of likely habitat. Regionally, above 1385 m, we determined that 31795 ha could be occupied by CNFS. Known occupied patches ranged from </span></p>","language":"English","publisher":"Inter-Research","doi":"10.3354/esr00662","usgsCitation":"Ford, W.M., Evans, A., Odom, R.H., Rodrigue, J.L., Kelly, C., Abaid, N., Diggins, C.A., and Newcomb, D., 2016, Predictive habitat models derived from nest-box occupancy for the endangered Carolina northern flying squirrel in the southern Appalachians: Endangered Species Research, v. 27, p. 131-140, https://doi.org/10.3354/esr00662.","productDescription":"10 p.","startPage":"131","endPage":"140","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059397","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471393,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00662","text":"Publisher Index Page"},{"id":323393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Tennessee, Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.7466335932305,\n              34.995648624137246\n            ],\n            [\n              -78.94333487363758,\n              34.995648624137246\n            ],\n            [\n              -78.94333487363758,\n              37.285370946434895\n            ],\n            [\n              -84.7466335932305,\n              37.285370946434895\n            ],\n            [\n              -84.7466335932305,\n              34.995648624137246\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"27","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"575a9335e4b04f417c275176","contributors":{"authors":[{"text":"Ford, W. Mark wford@usgs.gov","contributorId":3858,"corporation":false,"usgs":true,"family":"Ford","given":"W.","email":"wford@usgs.gov","middleInitial":"Mark","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":638024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, A.M.","contributorId":20117,"corporation":false,"usgs":true,"family":"Evans","given":"A.M.","email":"","affiliations":[],"preferred":false,"id":638236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Odom, Richard H.","contributorId":171659,"corporation":false,"usgs":false,"family":"Odom","given":"Richard","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":638237,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodrigue, Jane L.","contributorId":150352,"corporation":false,"usgs":false,"family":"Rodrigue","given":"Jane","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":638238,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelly, C.A.","contributorId":72564,"corporation":false,"usgs":true,"family":"Kelly","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":638239,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Abaid, Nicole","contributorId":171663,"corporation":false,"usgs":false,"family":"Abaid","given":"Nicole","email":"","affiliations":[],"preferred":false,"id":638240,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Diggins, Corinne A.","contributorId":171667,"corporation":false,"usgs":false,"family":"Diggins","given":"Corinne","email":"","middleInitial":"A.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":638241,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Newcomb, Doug","contributorId":150080,"corporation":false,"usgs":false,"family":"Newcomb","given":"Doug","email":"","affiliations":[{"id":17902,"text":"US Fish and Wildlife Service, Raleigh, NC","active":true,"usgs":false}],"preferred":false,"id":638242,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70171558,"text":"70171558 - 2016 - Acadia National Park Climate Change Scenario Planning Workshop summary","interactions":[],"lastModifiedDate":"2020-07-27T18:57:50.841175","indexId":"70171558","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Acadia National Park Climate Change Scenario Planning Workshop summary","docAbstract":"<p>This report summarizes outcomes from a two-day scenario planning workshop for Acadia National Park, Maine (ACAD). The primary objective of the workshop was to help ACAD senior leadership make management and planning decisions based on up-to-date climate science and assessments of future uncertainty. The workshop was also designed as a training program, helping build participants' capabilities to develop and use scenarios. The details of the workshop are given in later sections. The climate scenarios presented here are based on published global climate model output. The scenario implications for resources and management decisions are based on expert knowledge distilled through scientist-manager interaction during workgroup break-out sessions at the workshop. Thus, the descriptions below are from these small-group discussions in a workshop setting and should not be taken as vetted research statements of responses to the climate scenarios, but rather as insights and examinations of possible futures (Martin et al. 2011, McBride et al. 2012).</p>","conferenceTitle":"Acadia National Park Climate Change Scenario Planning Workshop","conferenceDate":"October 5-6, 2015","conferenceLocation":"Acadia National Park, ME","language":"English","publisher":"National Park Service","usgsCitation":"Star, J., Fisichelli, N., Bryan, A., Babson, A., Cole-Will, R., and Miller-Rushing, A., 2016, Acadia National Park Climate Change Scenario Planning Workshop summary, Acadia National Park Climate Change Scenario Planning Workshop, Acadia National Park, ME, October 5-6, 2015, 50 p.","productDescription":"50 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075377","costCenters":[{"id":41705,"text":"Northeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":324103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324102,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.nps.gov/subjects/climatechange/acadiaworkshop.htm"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576a652fe4b07657d1a11ceb","contributors":{"authors":[{"text":"Star, Jonathan","contributorId":168823,"corporation":false,"usgs":false,"family":"Star","given":"Jonathan","email":"","affiliations":[{"id":25365,"text":"Scenario Insight","active":true,"usgs":false}],"preferred":false,"id":631780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisichelli, Nicholas","contributorId":168824,"corporation":false,"usgs":false,"family":"Fisichelli","given":"Nicholas","affiliations":[{"id":25366,"text":"National Park Service, Climate Change Response Program","active":true,"usgs":false}],"preferred":false,"id":631781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bryan, Alexander 0000-0003-2040-7636 abryan@usgs.gov","orcid":"https://orcid.org/0000-0003-2040-7636","contributorId":168822,"corporation":false,"usgs":true,"family":"Bryan","given":"Alexander","email":"abryan@usgs.gov","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":631779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Babson, Amanda","contributorId":168825,"corporation":false,"usgs":false,"family":"Babson","given":"Amanda","email":"","affiliations":[{"id":25367,"text":"National Park Service, Northeast Region","active":true,"usgs":false}],"preferred":false,"id":631782,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cole-Will, Rebecca","contributorId":168826,"corporation":false,"usgs":false,"family":"Cole-Will","given":"Rebecca","email":"","affiliations":[{"id":25368,"text":"National Park Service, Acadia National Park","active":true,"usgs":false}],"preferred":false,"id":631783,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller-Rushing, Abraham J.","contributorId":103561,"corporation":false,"usgs":true,"family":"Miller-Rushing","given":"Abraham J.","affiliations":[],"preferred":false,"id":631784,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70176420,"text":"70176420 - 2016 - Seasonal electrical resistivity surveys of a coastal bluff, Barter Island, North Slope Alaska","interactions":[],"lastModifiedDate":"2017-04-11T12:45:05","indexId":"70176420","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3928,"text":"Journal of Environmental & Engineering Geophysics","printIssn":"1083-1363","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal electrical resistivity surveys of a coastal bluff, Barter Island, North Slope Alaska","docAbstract":"<p><span>Select coastal regions of the North Slope of Alaska are experiencing high erosion rates that can be attributed in part to recent warming trends and associated increased storm intensity and frequency. The upper sediment column of the coastal North Slope of Alaska can be described as continuous permafrost underlying a thin (typically less than 1–2 m) active layer that responds variably to seasonal thaw cycles. Assessing the temporal and spatial variability of the active layer and underlying permafrost is essential to better constrain how heightened erosion may impact material fluxes to the atmosphere and the coastal ocean, and how enhanced thaw cycles may impact the stability of the coastal bluffs. In this study, multi-channel electrical resistivity tomography (ERT) was used to image shallow subsurface features of a coastal bluff west of Kaktovik, on Barter Island, northeast Alaska. A comparison of a suite of paired resistivity surveys conducted in early and late summer 2014 provided detailed information on how the active layer and permafrost are impacted during the short Arctic summer. Such results are useful in the development of coastal resilience models that tie together fluvial, terrestrial, climatic, geologic, and oceanographic forcings on shoreline stability.</span></p>","language":"English","publisher":"Environmental & Engineering Geophysical Society","doi":"10.2113/JEEG21.1.37","usgsCitation":"Swarzenski, P.W., Johnson, C., Lorenson, T., Conaway, C.H., Gibbs, A.E., Erikson, L.H., Richmond, B.M., and Waldrop, M.P., 2016, Seasonal electrical resistivity surveys of a coastal bluff, Barter Island, North Slope Alaska: Journal of Environmental & Engineering Geophysics, v. 21, no. 1, p. 37-42, https://doi.org/10.2113/JEEG21.1.37.","productDescription":"6 p.","startPage":"37","endPage":"42","ipdsId":"IP-063158","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":339571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Barter Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -143.84811401367188,\n              70.07354279874802\n            ],\n            [\n              -143.4100341796875,\n              70.07354279874802\n            ],\n            [\n              -143.4100341796875,\n              70.16321163823721\n            ],\n            [\n              -143.84811401367188,\n              70.16321163823721\n            ],\n            [\n              -143.84811401367188,\n              70.07354279874802\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"21","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58edba76e4b0eed1ab8c6f33","contributors":{"authors":[{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648696,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Cordell 0000-0001-8353-8030 cordell_johnson@usgs.gov","orcid":"https://orcid.org/0000-0001-8353-8030","contributorId":147437,"corporation":false,"usgs":true,"family":"Johnson","given":"Cordell","email":"cordell_johnson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648697,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorenson, Thomas 0000-0001-7669-2873 tlorenson@usgs.gov","orcid":"https://orcid.org/0000-0001-7669-2873","contributorId":174599,"corporation":false,"usgs":true,"family":"Lorenson","given":"Thomas","email":"tlorenson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648698,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conaway, Christopher H. 0000-0002-0991-033X cconaway@usgs.gov","orcid":"https://orcid.org/0000-0002-0991-033X","contributorId":5074,"corporation":false,"usgs":true,"family":"Conaway","given":"Christopher","email":"cconaway@usgs.gov","middleInitial":"H.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":648699,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648700,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648701,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Richmond, Bruce M. 0000-0002-0056-5832 brichmond@usgs.gov","orcid":"https://orcid.org/0000-0002-0056-5832","contributorId":2459,"corporation":false,"usgs":true,"family":"Richmond","given":"Bruce","email":"brichmond@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648702,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Waldrop, Mark P. 0000-0003-1829-7140 mwaldrop@usgs.gov","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":1599,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","email":"mwaldrop@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":648703,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70180405,"text":"70180405 - 2016 - Conservation planning for the Colorado River in Utah","interactions":[],"lastModifiedDate":"2019-06-03T13:23:59","indexId":"70180405","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Conservation planning for the Colorado River in Utah","docAbstract":"<p>Strategic planning is increasingly recognized as necessary for providing the greatest possible conservation benefits for restoration efforts. Rigorous, science-based resource assessment, combined with acknowledgement of broader basin trends, provides a solid foundation for determining effective projects. It is equally important that methods used to prioritize conservation investments are simple and practical enough that they can be implemented in a timely manner and by a variety of resource managers. With the help of local and regional natural resource professionals, we have developed a broad-scale, spatially-explicit assessment of 146 miles (~20,000 acres) of the Colorado River mainstem in Grand and San Juan Counties, Utah that will function as the basis for a systematic, practical approach to conservation planning and riparian restoration prioritization. For the assessment we have: 1) acquired, modified or created spatial datasets of Colorado River bottomland conditions; 2) synthesized those datasets into habitat suitability models and estimates of natural recovery potential, fire risk and relative cost; 3) investigated and described dominant ecosystem trends and human uses, and; 4) suggested site selection and prioritization approaches. Partner organizations (The Nature Conservancy, National Park Service, Bureau of Land Management and Utah Forestry Fire and State Lands) are using the assessment and datasets to identify and prioritize a suite of restoration actions to increase ecosystem resilience and improve habitat for bottomland species. Primary datasets include maps of bottomland cover types, bottomland extent, maps of areas inundated during high and low flow events, as well as locations of campgrounds, roads, fires, invasive vegetation treatment areas and other features. Assessment of conditions and trends in the project area entailed: 1) assemblage of existing data on geology, changes in stream flow, and predictions of future conditions; 2) identification of fish and wildlife species present and grouping species into Conservation Elements (CEs) based on habitat needs, and: 3) acquisition, review and creation of spatial datasets characterizing vegetation, fluvial geomorphic and human features within the bottomland. Interpretation of aerial imagery and assimilation of pre-existing spatial data were central to our efforts in characterizing resources conditions. Detailed maps of vegetation and channel habitat features in the project area were generated from true color, high resolution (0.3m) imagery flown September 16, 2010. We also mapped channel habitat features at high flow on 1.0-m resolution, publicly available, true color imagery. We obtained additional layers such as land ownership, roads, fire history, non-native vegetation treatment areas, and recreational use features from public sources and project partners. Habitat suitability models were created for groups of terrestrial species by combining spatial datasets with the habitat needs of conservation elements, guided by literature, where available, and extensive use of expert knowledge. Conservation elements for endangered fish species life stages were identified but not modeled. Terrestrial CE’s included: • Riparian Overstory -yellow-billed cuckoo, Bullock’s oriole, black-headed grosbeak, blue grosbeak, warbling vireo, Cooper's hawk, screech owl, saw-whet owl, and bald eagle, (best: tall trees, dense canopy, diverse shrub understory, no tamarisk); • Riparian Understory - southwestern willow flycatcher, common yellowthroat, yellow warbler, yellow-breasted chat, beaver, northern river otter, black-necked garter snake, (best: dense mesic shrubs near still water, no tamarisk); • Bat Feeding - Allen's big-eared bat, Townsend's big-eared bat, fringed myotis, Yuma myotis, big free-tailed bat, spotted bat (best: diverse vegetation, close to still water); • Bat Watering - big free-tailed and spotted bats (best: still water with no tall vegetation); •</p>","language":"English","publisher":"Colorado Mesa University","usgsCitation":"Christine Rasmussen, and Shafroth, P.B., 2016, Conservation planning for the Colorado River in Utah, 94 p. .","productDescription":"94 p. ","ipdsId":"IP-079063","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":335787,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":334302,"type":{"id":15,"text":"Index Page"},"url":"https://www.coloradomesa.edu/water-center/documents/rasmussen_shaftroth_2016_watercenter_cmu.pdf"}],"country":"United States","state":"Utah","otherGeospatial":"Colorado River ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -109.06677246093749,\n              39.15136267949029\n            ],\n            [\n              -109.3304443359375,\n              38.94659331893374\n            ],\n            [\n              -109.79187011718749,\n              38.49229419236133\n            ],\n            [\n              -110.489501953125,\n              37.913867495923746\n            ],\n            [\n              -110.93994140625,\n              37.37015718405753\n            ],\n            [\n              -110.89599609375,\n              37.17782559332976\n            ],\n            [\n              -110.269775390625,\n              37.735969208590504\n            ],\n            [\n              -109.44580078125,\n              38.453588708941375\n            ],\n            [\n              -109.05029296875,\n              39.11301365149975\n            ],\n            [\n              -109.06677246093749,\n              39.15136267949029\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58a6c833e4b025c464286292","contributors":{"authors":[{"text":"Christine Rasmussen","contributorId":178920,"corporation":false,"usgs":false,"family":"Christine Rasmussen","affiliations":[],"preferred":false,"id":661589,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":661588,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70170556,"text":"70170556 - 2016 - Hydropedology: Synergistic integration of soil science and hydrology in the Critical Zone","interactions":[],"lastModifiedDate":"2016-04-27T09:35:34","indexId":"70170556","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Hydropedology: Synergistic integration of soil science and hydrology in the Critical Zone","docAbstract":"<div class=\"t m0 x16 h6 y12 ff2 fs5 fc0 sc0 ls0 ws0\">Soil and water are the two critical components of theEarth&rsquo;s Critical Zone (Figure 1): Soil modulates the connection between bedrock and the atmospheric boundary layer and water is a major driving force and transport agent between these two zones. The interactions between soil and water are so intimate and complex that they cannot be effectively studied in a piecemeal manner; they require a systems approach. In this spirit, hydropedology has emerged in recent years as a synergistic integration of soil science and hydrology that offers a renewed perspective and an integrated approach to understanding interactive pedologic and hydrologic processes and their properties in the Critical Zone.</div>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10686","usgsCitation":"Lin, H., McDonnell, J., Nimmo, J.R., and Pachepsky, Y.A., 2016, Hydropedology: Synergistic integration of soil science and hydrology in the Critical Zone: Hydrological Processes, v. 29, no. 21, p. 4559-4561, https://doi.org/10.1002/hyp.10686.","productDescription":"3 p.","startPage":"4559","endPage":"4561","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069960","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471378,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.10686","text":"Publisher Index Page"},{"id":320588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"21","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-22","publicationStatus":"PW","scienceBaseUri":"5721e2bee4b0b13d391303b5","contributors":{"authors":[{"text":"Lin, H.S.","contributorId":168897,"corporation":false,"usgs":false,"family":"Lin","given":"H.S.","email":"","affiliations":[{"id":25381,"text":"Penn State Univ.","active":true,"usgs":false}],"preferred":false,"id":627633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDonnell, J.J.","contributorId":168898,"corporation":false,"usgs":false,"family":"McDonnell","given":"J.J.","email":"","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":627634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nimmo, John R. 0000-0001-8191-1727 jrnimmo@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":757,"corporation":false,"usgs":true,"family":"Nimmo","given":"John","email":"jrnimmo@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":627632,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pachepsky, Y. A.","contributorId":168899,"corporation":false,"usgs":false,"family":"Pachepsky","given":"Y.","email":"","middleInitial":"A.","affiliations":[{"id":25382,"text":"USDA-ARS Environmental Microbial and Food Safety Lab","active":true,"usgs":false}],"preferred":false,"id":627635,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70175033,"text":"70175033 - 2016 - Application of an extreme winter storm scenario to identify vulnerabilities, mitigation options, and science needs in the Sierra Nevada mountains, USA","interactions":[],"lastModifiedDate":"2016-07-28T10:03:33","indexId":"70175033","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Application of an extreme winter storm scenario to identify vulnerabilities, mitigation options, and science needs in the Sierra Nevada mountains, USA","docAbstract":"<p><span>In the Sierra Nevada mountains (USA), and geographically similar areas across the globe where human development is expanding, extreme winter storm and flood risks are expected to increase with changing climate, heightening the need for communities to assess risks and better prepare for such events. In this case study, we demonstrate a novel approach to examining extreme winter storm and flood risks. We incorporated high-resolution atmospheric&ndash;hydrologic modeling of the ARkStorm extreme winter storm scenario with multiple modes of engagement with practitioners, including a series of facilitated discussions and a tabletop emergency management exercise, to develop a regional assessment of extreme storm vulnerabilities, mitigation options, and science needs in the greater Lake Tahoe region of Northern Nevada and California, USA. Through this process, practitioners discussed issues of concern across all phases of the emergency management life cycle, including preparation, response, recovery, and mitigation. Interruption of transportation, communications, and interagency coordination were among the most pressing concerns, and specific approaches for addressing these issues were identified, including prepositioning resources, diversifying communications systems, and improving coordination among state, tribal, and public utility practitioners. Science needs included expanding real-time monitoring capabilities to improve the precision of meteorological models and enhance situational awareness, assessing vulnerabilities of critical infrastructure, and conducting cost&ndash;benefit analyses to assess opportunities to improve both natural and human-made infrastructure to better withstand extreme storms. Our approach and results can be used to support both land use and emergency planning activities aimed toward increasing community resilience to extreme winter storm hazards in mountainous regions.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s11069-015-2003-4","usgsCitation":"Albano, C.M., Dettinger, M.D., McCarthy, M., Schaller, K.D., Wellborn, T., and Cox, D.A., 2016, Application of an extreme winter storm scenario to identify vulnerabilities, mitigation options, and science needs in the Sierra Nevada mountains, USA: Natural Hazards, v. 80, no. 2, p. 879-900, https://doi.org/10.1007/s11069-015-2003-4.","productDescription":"22 p.","startPage":"879","endPage":"900","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068894","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":325768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-10","publicationStatus":"PW","scienceBaseUri":"579b2cace4b0589fa1c98090","contributors":{"authors":[{"text":"Albano, Christine M.","contributorId":169455,"corporation":false,"usgs":false,"family":"Albano","given":"Christine","email":"","middleInitial":"M.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":643664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dettinger, Michael D. 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":149896,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael","email":"mddettin@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":643663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCarthy, Maureen","contributorId":149897,"corporation":false,"usgs":false,"family":"McCarthy","given":"Maureen","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":643665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schaller, Kevin D.","contributorId":173217,"corporation":false,"usgs":false,"family":"Schaller","given":"Kevin","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":643775,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wellborn, Toby","contributorId":173203,"corporation":false,"usgs":false,"family":"Wellborn","given":"Toby","email":"","affiliations":[{"id":27191,"text":"USGS, NV WSC","active":true,"usgs":false}],"preferred":false,"id":643666,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cox, Dale A. dacox@usgs.gov","contributorId":165,"corporation":false,"usgs":true,"family":"Cox","given":"Dale","email":"dacox@usgs.gov","middleInitial":"A.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":643667,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70178749,"text":"70178749 - 2016 - Geology and geomorphology of the Carolina Sandhills, Chesterfield County, South Carolina","interactions":[],"lastModifiedDate":"2018-03-29T11:06:08","indexId":"70178749","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":15,"text":"Monograph"},"seriesTitle":{"id":5369,"text":"GSA Field Guides","active":true,"publicationSubtype":{"id":15}},"title":"Geology and geomorphology of the Carolina Sandhills, Chesterfield County, South Carolina","docAbstract":"<p><span>This two-day field trip focuses on the geology and geomorphology of the Carolina Sandhills in Chesterfield County, South Carolina. This area is located in the updip portion of the U.S. Atlantic Coastal Plain province, supports an ecosystem of longleaf pine (</span><i>Pinus palustris</i><span>) and wiregrass (</span><i>Aristida stricta</i><span>), and contains three major geologic map units: (1) An ~60–120-m-thick unit of weakly consolidated sand, sandstone, mud, and gravel is mapped as the Upper Cretaceous Middendorf Formation and is interpreted as a fluvial deposit. This unit is capped by an unconformity, and displays reticulate mottling, plinthite, and other paleosol features at the unconformity. The Middendorf Formation is the largest aquifer in South Carolina. (2) A 0.3–10-m-thick unit of unconsolidated sand is mapped as the Quaternary Pinehurst Formation and is interpreted as deposits of eolian sand sheets and dunes derived via remobilization of sand from the underlying Cretaceous strata. This unit displays argillic horizons and abundant evidence of bioturbation by vegetation. (3) A &lt;3-m-thick unit of sand, pebbly sand, sandy mud, and mud is mapped as Quaternary terrace deposits adjacent to modern drainages. In addition to the geologic units listed above, a prominent geomorphologic feature in the study area is a north-trending escarpment (incised by headwater streams) that forms a markedly asymmetric drainage divide. This drainage divide, as well as the Quaternary terraces deposits, are interpreted as evidence of landscape disequilibrium (possibly geomorphic responses to Quaternary climate changes).</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/2016.0042(02)","usgsCitation":"Swezey, C.S., Fitzwater, B.A., and Whittecar, G.R., 2016, Geology and geomorphology of the Carolina Sandhills, Chesterfield County, South Carolina: GSA Field Guides, v. 43, 28 p., https://doi.org/10.1130/2016.0042(02).","productDescription":"28 p.","startPage":"9","endPage":"36","ipdsId":"IP-070960","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":339728,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","otherGeospatial":"Carolina Sandhills","volume":"43","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f1e0cae4b08144348b7e01","contributors":{"authors":[{"text":"Swezey, Christopher S. 0000-0003-4019-9264 cswezey@usgs.gov","orcid":"https://orcid.org/0000-0003-4019-9264","contributorId":173033,"corporation":false,"usgs":true,"family":"Swezey","given":"Christopher","email":"cswezey@usgs.gov","middleInitial":"S.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":655035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzwater, Bradley A.","contributorId":177211,"corporation":false,"usgs":false,"family":"Fitzwater","given":"Bradley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":655036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whittecar, G. Richard","contributorId":177212,"corporation":false,"usgs":false,"family":"Whittecar","given":"G.","email":"","middleInitial":"Richard","affiliations":[],"preferred":false,"id":655037,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70175412,"text":"70175412 - 2016 - Coral calcification and ocean acidification","interactions":[],"lastModifiedDate":"2016-08-31T11:08:38","indexId":"70175412","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Coral calcification and ocean acidification","docAbstract":"<p>Over 60 years ago, the discovery that light increased calcification in the coral plant-animal symbiosis triggered interest in explaining the phenomenon and understanding the mechanisms involved. Major findings along the way include the observation that carbon fixed by photosynthesis in the zooxanthellae is translocated to animal cells throughout the colony and that corals can therefore live as autotrophs in many situations. Recent research has focused on explaining the observed reduction in calcification rate with increasing ocean acidification (OA). Experiments have shown a direct correlation between declining ocean pH, declining aragonite saturation state (&Omega;arag), declining [CO32_] and coral calcification. Nearly all previous reports on OA identify &Omega;arag or its surrogate [CO32] as the factor driving coral calcification. However, the alternate &ldquo;Proton Flux Hypothesis&rdquo; stated that coral calcification is controlled by diffusion limitation of net H+ transport through the boundary layer in relation to availability of dissolved inorganic carbon (DIC). The &ldquo;Two Compartment Proton Flux Model&rdquo; expanded this explanation and synthesized diverse observations into a universal model that explains many paradoxes of coral metabolism, morphology and plasticity of growth form in addition to observed coral skeletal growth response to OA. It is now clear that irradiance is the main driver of net photosynthesis (Pnet), which in turn drives net calcification (Gnet), and alters pH in the bulk water surrounding the coral. Pnet controls [CO32] and thus &Omega;arag of the bulk water over the diel cycle. Changes in &Omega;arag and pH lag behind Gnet throughout the daily cycle by two or more hours. The flux rate Pnet, rather than concentration-based parameters (e.g., &Omega;arag, [CO3 2], pH and [DIC]:[H+] ratio) is the primary driver of Gnet. Daytime coral metabolism rapidly removes DIC from the bulk seawater. Photosynthesis increases the bulk seawater pH while providing the energy that drives calcification and increases in Gnet. These relationships result in a correlation between Gnet and &Omega;arag, with both parameters being variables dependent on Pnet. Consequently the correlation between Gnet and &Omega;arag varies widely between different locations and times depending on the relative metabolic contributions of various calcifying and photosynthesizing organisms and local rates of carbonate dissolution. High rates of H+ efflux continue for several hours following the mid-day Gnet peak suggesting that corals have difficulty in shedding waste protons as described by the Proton Flux Model. DIC flux (uptake) tracks Pnet and Gnet and drops off rapidly after the photosynthesis-calcification maxima, indicating that corals can cope more effectively with the problem of limited DIC supply compared to the problem of eliminating H+. Predictive models of future global changes in coral and coral reef growth based on oceanic &Omega;arag must include the influence of future changes in localized Pnet on Gnet as well as changes in rates of reef carbonate dissolution. The correlation between &Omega;arag and Gnet over the diel cycle is simply the result of increasing pH due to photosynthesis that shifts the CO2-carbonate system equilibria to increase [CO32] relative to the other DIC components of [HCO3] and [CO2]. Therefore &Omega;arag closely tracks pH as an effect of Pnet, which also drives changes in Gnet. Measurements of DIC flux and H+ flux are far more useful than concentrations in describing coral metabolism dynamics. Coral reefs are systems that exist in constant disequilibrium with the water column.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coral reefs at the crossroads","language":"English","publisher":"Springer Netherlands","doi":"10.1007/978-94-017-7567-0","collaboration":"Paul L. Jokiel and Christopher P. Jury, Hawaii Institute of Marine Biology, University of Hawaii","usgsCitation":"Jokiel, P.L., Jury, C.P., and Kuffner, I.B., 2016, Coral calcification and ocean acidification, chap. <i>of</i> Coral reefs at the crossroads, v. 6, p. 7-45, https://doi.org/10.1007/978-94-017-7567-0.","productDescription":"29 p.","startPage":"7","endPage":"45","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049232","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":328107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c7ffb0e4b0f2f0cebfc229","contributors":{"authors":[{"text":"Jokiel, Paul L.","contributorId":131043,"corporation":false,"usgs":false,"family":"Jokiel","given":"Paul","email":"","middleInitial":"L.","affiliations":[{"id":7212,"text":"University of Hawai‘i, Hawai‘i Institute of Marine Biology","active":true,"usgs":false}],"preferred":false,"id":645113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jury, Christopher P.","contributorId":173575,"corporation":false,"usgs":false,"family":"Jury","given":"Christopher","email":"","middleInitial":"P.","affiliations":[{"id":20314,"text":"Hawaii Institute of Marine Biology, University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":645114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuffner, Ilsa B. 0000-0001-8804-7847 ikuffner@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7847","contributorId":3105,"corporation":false,"usgs":true,"family":"Kuffner","given":"Ilsa","email":"ikuffner@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":645112,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70176638,"text":"70176638 - 2016 - Seismic velocities within the sedimentary succession of the Canada Basin and southern Alpha-Mendeleev Ridge, Arctic Ocean: evidence for accelerated porosity reduction?","interactions":[],"lastModifiedDate":"2016-09-23T16:00:51","indexId":"70176638","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Seismic velocities within the sedimentary succession of the Canada Basin and southern Alpha-Mendeleev Ridge, Arctic Ocean: evidence for accelerated porosity reduction?","docAbstract":"<p><span>The Canada Basin and the southern Alpha-Mendeleev ridge complex underlie a significant proportion of the Arctic Ocean, but the geology of this undrilled and mostly ice-covered frontier is poorly known. New information is encoded in seismic wide-angle reflections and refractions recorded with expendable sonobuoys between 2007 and 2011. Velocity–depth samples within the sedimentary succession are extracted from published analyses for 142 of these records obtained at irregularly spaced stations across an area of 1.9E + 06 km</span><sup>2</sup><span>. The samples are modelled at regional, subregional and station-specific scales using an exponential function of inverse velocity versus depth with regionally representative parameters determined through numerical regression. With this approach, smooth, non-oscillatory velocity–depth profiles can be generated for any desired location in the study area, even where the measurement density is low. Practical application is demonstrated with a map of sedimentary thickness, derived from seismic reflection horizons interpreted in the time domain and depth converted using the velocity–depth profiles for each seismic trace. A thickness of 12–13&nbsp;km is present beneath both the upper Mackenzie fan and the middle slope off of Alaska, but the sedimentary prism thins more gradually outboard of the latter region. Mapping of the observed-to-predicted velocities reveals coherent geospatial trends associated with five subregions: the Mackenzie fan; the continental slopes beyond the Mackenzie fan; the abyssal plain; the southwestern Canada Basin; and, the Alpha-Mendeleev magnetic domain. Comparison of the subregional velocity–depth models with published borehole data, and interpretation of the station-specific best-fitting model parameters, suggests that sandstone is not a predominant lithology in any of the five subregions. However, the bulk sand-to-shale ratio likely increases towards the Mackenzie fan, and the model for this subregion compares favourably with borehole data for Miocene turbidites in the eastern Gulf of Mexico. The station-specific results also indicate that Quaternary sediments coarsen towards the Beaufort-Mackenzie and Banks Island margins in a manner that is consistent with the variable history of Laurentide Ice Sheet advance documented for these margins. Lithological factors do not fully account for the elevated velocity–depth trends that are associated with the southwestern Canada Basin and the Alpha-Mendeleev magnetic domain. Accelerated porosity reduction due to elevated palaeo-heat flow is inferred for these regions, which may be related to the underlying crustal types or possibly volcanic intrusion of the sedimentary succession. Beyond exploring the variation of an important physical property in the Arctic Ocean basin, this study provides comparative reference for global studies of seismic velocity, burial history, sedimentary compaction, seismic inversion and overpressure prediction, particularly in mudrock-dominated successions.</span></p>","language":"English","publisher":"Oxford Journals","doi":"10.1093/gji/ggv416","usgsCitation":"Shimeld, J., Li, Q., Chian, D., Lebedeva-Ivanova, N., Jackson, R., Mosher, D., and Hutchinson, D.R., 2016, Seismic velocities within the sedimentary succession of the Canada Basin and southern Alpha-Mendeleev Ridge, Arctic Ocean: evidence for accelerated porosity reduction?: Geophysical Journal International, v. 204, no. 1, p. 1-20, https://doi.org/10.1093/gji/ggv416.","productDescription":"20 p.","startPage":"1","endPage":"20","ipdsId":"IP-064703","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471381,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggv416","text":"Publisher Index Page"},{"id":328940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"204","issue":"1","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-09","publicationStatus":"PW","scienceBaseUri":"57f7c6e6e4b0bc0bec09cbdb","contributors":{"authors":[{"text":"Shimeld, John","contributorId":146869,"corporation":false,"usgs":false,"family":"Shimeld","given":"John","affiliations":[],"preferred":false,"id":649568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Qingmou","contributorId":174893,"corporation":false,"usgs":false,"family":"Li","given":"Qingmou","email":"","affiliations":[],"preferred":false,"id":649569,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chian, Deping","contributorId":174894,"corporation":false,"usgs":false,"family":"Chian","given":"Deping","email":"","affiliations":[],"preferred":false,"id":649570,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lebedeva-Ivanova, Nina","contributorId":146870,"corporation":false,"usgs":false,"family":"Lebedeva-Ivanova","given":"Nina","email":"","affiliations":[],"preferred":false,"id":649571,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, Ruth","contributorId":36799,"corporation":false,"usgs":true,"family":"Jackson","given":"Ruth","email":"","affiliations":[],"preferred":false,"id":649572,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mosher, David","contributorId":174895,"corporation":false,"usgs":false,"family":"Mosher","given":"David","affiliations":[],"preferred":false,"id":649573,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hutchinson, Deborah R. 0000-0002-2544-5466 dhutchinson@usgs.gov","orcid":"https://orcid.org/0000-0002-2544-5466","contributorId":521,"corporation":false,"usgs":true,"family":"Hutchinson","given":"Deborah","email":"dhutchinson@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":649574,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70170995,"text":"70170995 - 2016 - Coupling centennial-scale shoreline change to sea-level rise and coastal morphology in the Gulf of Mexico using a Bayesian network","interactions":[],"lastModifiedDate":"2016-06-20T10:25:01","indexId":"70170995","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Coupling centennial-scale shoreline change to sea-level rise and coastal morphology in the Gulf of Mexico using a Bayesian network","docAbstract":"<p>Predictions of coastal evolution driven by episodic and persistent processes associated with storms and relative sea-level rise (SLR) are required to test our understanding, evaluate our predictive capability, and to provide guidance for coastal management decisions. Previous work demonstrated that the spatial variability of long-term shoreline change can be predicted using observed SLR rates, tide range, wave height, coastal slope, and a characterization of the geomorphic setting. The shoreline is not suf- ficient to indicate which processes are important in causing shoreline change, such as overwash that depends on coastal dune elevations. Predicting dune height is intrinsically important to assess future storm vulnerability. Here, we enhance shoreline-change predictions by including dune height as a vari- able in a statistical modeling approach. Dune height can also be used as an input variable, but it does not improve the shoreline-change prediction skill. Dune-height input does help to reduce prediction uncer- tainty. That is, by including dune height, the prediction is more precise but not more accurate. Comparing hindcast evaluations, better predictive skill was found when predicting dune height (0.8) compared with shoreline change (0.6). The skill depends on the level of detail of the model and we identify an optimized model that has high skill and minimal overfitting. The predictive model can be implemented with a range of forecast scenarios, and we illustrate the impacts of a higher future sea-level. This scenario shows that the shoreline change becomes increasingly erosional and more uncertain. Predicted dune heights are lower and the dune height uncertainty decreases.</p>","language":"English","publisher":"Earth's Future","doi":"10.1002/2015EF000331","usgsCitation":"Plant, N.G., 2016, Coupling centennial-scale shoreline change to sea-level rise and coastal morphology in the Gulf of Mexico using a Bayesian network: Earth's Future, v. 4, https://doi.org/10.1002/2015EF000331.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070872","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471382,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015ef000331","text":"Publisher Index Page"},{"id":323954,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":321270,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/info:doi/10.1002/2015EF000331"}],"volume":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-02","publicationStatus":"PW","scienceBaseUri":"576913b5e4b07657d19ff006","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":629372,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70178095,"text":"70178095 - 2016 - Integrated modeling approach for fate and transport of submerged oil and oil-particle aggregates in a freshwater riverine environment","interactions":[],"lastModifiedDate":"2018-01-08T12:34:57","indexId":"70178095","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Integrated modeling approach for fate and transport of submerged oil and oil-particle aggregates in a freshwater riverine environment","docAbstract":"<p>The Enbridge Line 6B pipeline release of diluted bitumen into the Kalamazoo River downstream of Marshall, Michigan, U.S.A., in July 2010 was one of the largest oil spills into freshwater in North American history. A portion of the oil interacted with river sediment and submerged requiring the development and implementation of new approaches for detection and recovery of oil mixed with river sediment. Hydrodynamic and sediment transport modeling became an integral part of containment and recovery operations for decision support about the potential fate and migration of submerged oil and oiled sediment. Three models were developed for the U.S. Environmental Protection Agency to cover a range of spatial scales of interest to onsite operations. Two-dimensional (2D) hydrodynamic and sediment transport models from the Environmental Fluid Dynamics Code and the sediment bed model SEDZLJ1 were used to simulate potential resuspension, migration, and deposition of submerged oil and oiled sediment along a 38-mile reach of the Kalamazoo River affected by the oil from Marshall to Kalamazoo. An algorithm was added to SEDZLJ to represent three additional particle size classes of oilparticle aggregates (OPAs) with a range of sizes, specific gravities, and settling velocities. Field and laboratory experiments and flume tests were done to support the numerical modeling of OPAs. A three-dimensional hydrodynamic model was developed to simulate hydrodynamics and OPA tracking through Morrow Lake, the most downstream impoundment. This model incorporated wind and dam operations into high and low flow, lake drawdown, and containment simulations. Finally, a 2D unstructured grid model, HydroSed2D, was used to simulate flows and sediment transport along 1- to 2-mile segments of the Kalamazoo River around islands and through side channels and backwater areas that are particularly prone to submerged oil deposition.</p><p>Integrated models could be developed quickly due to the availability of information and services combined with spill response operations that included: bathymetry and topography data, fieldbased geomorphic mapping of submerged oil, and discharge measured at U.S. Geological Survey streamflow gauges. Modeling results were included in a multiple-lines-of-evidence approach that was used by the Federal On-Scene Coordinator and operations staff for decision-making related to assessment and recovery of submerged oil, as well as net environmental benefit analysis. Similar modeling approaches will likely be useful for future oil spills in riverine environments.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the joint federal interagency conference 2015","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Joint Federal Interagency Conference 2015","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, NV","language":"English","publisher":"Federal Interagency Subcommittees on Hydrology (SOH) and Sedimentation (SOS) under the Advisory Committee on Water Information (ACWI)","usgsCitation":"Fitzpatrick, F.A., Johnson, R., Zhu, Z., Waterman, D., McCulloch, R.D., Hayter, E., Garcia, M., Boufadel, M., Dekker, T., Hassan, J.S., Soong, D., Hoard, C.J., and Lee, K., 2016, Integrated modeling approach for fate and transport of submerged oil and oil-particle aggregates in a freshwater riverine environment, <i>in</i> Proceedings of the joint federal interagency conference 2015, Reno, NV, April 19-23, 2015, p. 1783-1794.","productDescription":"12 p.","startPage":"1783","endPage":"1794","ipdsId":"IP-060868","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":330649,"type":{"id":15,"text":"Index Page"},"url":"https://acwi.gov/sos/pubs/3rdJFIC/index.html"},{"id":339575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Kalamazoo River","publicComments":"Extended title: \"Proceedings of the 5th federal interagency hydrologic modeling conference and the 10th federal interagency sedimentation conference\"","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58edba76e4b0eed1ab8c6f2f","contributors":{"authors":[{"text":"Fitzpatrick, Faith A. 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