{"pageNumber":"867","pageRowStart":"21650","pageSize":"25","recordCount":184606,"records":[{"id":70203196,"text":"70203196 - 2018 - Using regional scale flow–ecology modeling to identify catchments where fish assemblages are most vulnerable to changes in water availability","interactions":[],"lastModifiedDate":"2019-04-26T16:44:27","indexId":"70203196","displayToPublicDate":"2018-04-26T16:33:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Using regional scale flow–ecology modeling to identify catchments where fish assemblages are most vulnerable to changes in water availability","docAbstract":"<ol><li>Streamflow is essential for maintaining healthy aquatic ecosystems and for supporting human water supply needs. Changes in climate, land use and water use practices may alter water availability. Understanding the potential effect of these changes on aquatic ecosystems is critical for long-term water management to maintain a balance between water for human consumption and ecosystem needs.</li><li>Fish species data and streamflow estimates from a rainfall-runoff and flow routing model were used to develop boosted regression tree models to predict the relationship between streamflow and fish species richness (FSR) under plausible scenarios of (1) water withdrawal, (2) climate change and (3) increases in impervious surfaces in the Piedmont ecoregion of North Carolina, U.S.A. Maximum monthly flow, the fraction of total flow originating from impervious surface runoff, coefficient of monthly streamflow variability, and the specific river basin accounted for 50% of the variability in FSR. This model was used to predict FSR values for all twelve-digit Hydrological Unit Code catchments (HUC-12s) in the North Carolina Piedmont under current flow conditions and under water withdrawal, climate change and impervious surface scenarios.</li><li>Flow–ecology modeling results indicate that predicted FSR declined significantly with increased water withdrawals. However, the magnitude of decline varied geographically. A “hot-spot” analysis was conducted based on predicted changes in FSR under each scenario to understand which HUC-12s were most likely to be affected by changes in water withdrawals, climate and impervious surfaces. Under the 20% withdrawal increase scenario, 413 of 886 (47%) HUC-12s in the study area were predicted to lose one or more species. HUC-12s in the Broad, Catawba, Yadkin and Cape Fear river basins were most susceptible to species loss.</li><li>These findings may help decision making efforts by identifying catchments most vulnerable to changing water availability. Additionally, FSR-discharge modeling results can assist resource agencies, water managers and stakeholders in assessing the effect of water withdrawals in catchments to better support the protection and long-term conservation of species.</li></ol>","language":"English","doi":"10.1111/fwb.13048","usgsCitation":"Hain;, E.F., Kennen, J., Caldwell, P.V., Nelson, S.A., Ge Sun, and McNulty, S.G., 2018, Using regional scale flow–ecology modeling to identify catchments where fish assemblages are most vulnerable to changes in water availability: Freshwater Biology, v. 63, p. 928-945, https://doi.org/10.1111/fwb.13048.","productDescription":"17 p.","startPage":"928","endPage":"945","ipdsId":"IP-084804","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":363277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.936279296875,\n              33.797408767572485\n            ],\n            [\n              -76.893310546875,\n              33.797408767572485\n            ],\n            [\n              -76.893310546875,\n              36.53612263184686\n            ],\n            [\n              -80.936279296875,\n              36.53612263184686\n            ],\n            [\n              -80.936279296875,\n              33.797408767572485\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"63","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Hain;, Ernie F.","contributorId":215083,"corporation":false,"usgs":false,"family":"Hain;","given":"Ernie","email":"","middleInitial":"F.","affiliations":[{"id":39171,"text":"Center for Geospatial Analytics, Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, 27695, USA","active":true,"usgs":false}],"preferred":false,"id":761593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":761592,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Peter V.","contributorId":215084,"corporation":false,"usgs":false,"family":"Caldwell","given":"Peter","email":"","middleInitial":"V.","affiliations":[{"id":39172,"text":"USDA Forest Service, Center for Forest Watershed Science, Coweeta Hydrologic Laboratory, Otto, NC, USA","active":true,"usgs":false}],"preferred":false,"id":761594,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Stacy A.C.","contributorId":215085,"corporation":false,"usgs":false,"family":"Nelson","given":"Stacy","email":"","middleInitial":"A.C.","affiliations":[{"id":39171,"text":"Center for Geospatial Analytics, Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, 27695, USA","active":true,"usgs":false}],"preferred":false,"id":761595,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ge Sun","contributorId":215086,"corporation":false,"usgs":false,"family":"Ge Sun","affiliations":[{"id":39173,"text":"USDA Forest Service, Eastern Forest Environmental Threat Assessment Center, Raleigh, NC, USA","active":true,"usgs":false}],"preferred":false,"id":761596,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McNulty, Steven G.","contributorId":215087,"corporation":false,"usgs":false,"family":"McNulty","given":"Steven","email":"","middleInitial":"G.","affiliations":[{"id":39173,"text":"USDA Forest Service, Eastern Forest Environmental Threat Assessment Center, Raleigh, NC, USA","active":true,"usgs":false}],"preferred":false,"id":761597,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70265444,"text":"70265444 - 2018 - Dissipation of polyoxyethylene tallow amine (POEA) and glyphosate in an agricultural field and their co-occurrence on streambed sediments","interactions":[],"lastModifiedDate":"2025-04-07T14:24:03.688416","indexId":"70265444","displayToPublicDate":"2018-04-26T09:19:57","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Dissipation of polyoxyethylene tallow amine (POEA) and glyphosate in an agricultural field and their co-occurrence on streambed sediments","docAbstract":"<p><span>The&nbsp;environmental fate&nbsp;of&nbsp;polyoxyethylene&nbsp;tallow&nbsp;amine (POEA), an additive in&nbsp;glyphosate&nbsp;herbicide formulations, has not been studied. This study examined the dissipation of POEA;&nbsp;glyphosate; and aminomethylphosphonic acid (AMPA), a&nbsp;</span>degradation product<span>&nbsp;of glyphosate, in the top 45 cm of soil from an agricultural field where glyphosate was applied. The concentration of these compounds was also analyzed in bed sediment samples from watersheds in agricultural and urban areas from six states (Georgia, Hawaii, Iowa, Mississippi, North Carolina, South Carolina). The field studies show that POEA, glyphosate, and AMPA persist on the soil from planting season to planting season but dissipate over time with little migration into deeper soil. POEA, glyphosate, and AMPA were found on the bed sediment samples in urban and&nbsp;agricultural watersheds.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.04.246","usgsCitation":"Tush, D.L., Maksimowicz, M.M., and Meyer, M., 2018, Dissipation of polyoxyethylene tallow amine (POEA) and glyphosate in an agricultural field and their co-occurrence on streambed sediments: Science of the Total Environment, v. 636, p. 212-219, https://doi.org/10.1016/j.scitotenv.2018.04.246.","productDescription":"8 p.","startPage":"212","endPage":"219","ipdsId":"IP-079506","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":488908,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.04.246","text":"Publisher Index Page"},{"id":484240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia, Hawaii, Iowa, Mississippi, North Carolina, South 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T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":932739,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196719,"text":"70196719 - 2018 - Profiles of digestive enzymes of two competing planktivores, silver carp and gizzard shad, differ","interactions":[],"lastModifiedDate":"2018-04-26T16:23:33","indexId":"70196719","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5680,"text":"Ichthyological Research","active":true,"publicationSubtype":{"id":10}},"title":"Profiles of digestive enzymes of two competing planktivores, silver carp and gizzard shad, differ","docAbstract":"<p><span>Typically, studies in digestive physiology in fish focus on a few enzymes and provide insight into the specific processes of the enzyme in a targeted species. Comparative studies assessing a wide number of digestive enzymes on fishes that compete for food resources are lacking, especially in the context of an introduced species. It is generally thought that the invasive silver carp (SVC;&nbsp;</span><i class=\"EmphasisTypeItalic \">Hypophthalmichthys molitrix</i><span>) directly compete for food resources with the native gizzard shad (GZS;<span>&nbsp;</span></span><i class=\"EmphasisTypeItalic \">Dorosoma cepedianum</i><span>) in waters where they coexist. We compared 19 digestive enzymes between SVC and GZS throughout a year and in two rivers in the Midwestern United States: Illinois River and Wabash River. All digestive enzymes analyzed were detected in both SVC and GZS in both rivers. However, the profiles of the digestive enzymes varied by species. Alkaline phosphatase, valine arylamidase, acid phosphatase, naphthol-AS-BI-phosphohydrolase and N-acetyl-β-glucosaminidase were all much higher in SVC than in GZS. Differences between digestive enzyme profiles were also observed between rivers and months. This study demonstrates the utility of using an ecological approach to compare physiological features in fishes.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10228-018-0615-x","usgsCitation":"Amberg, J., Jensen, N., Erickson, R.A., Sauey, B.W., and Jackson, C., 2018, Profiles of digestive enzymes of two competing planktivores, silver carp and gizzard shad, differ: Ichthyological Research, v. 65, no. 2, p. 245-251, https://doi.org/10.1007/s10228-018-0615-x.","productDescription":"7 p.","startPage":"245","endPage":"251","ipdsId":"IP-076712","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":353749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"65","issue":"2","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-01","publicationStatus":"PW","scienceBaseUri":"5afee6cde4b0da30c1bfbe32","contributors":{"authors":[{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jensen, Nathan R.","contributorId":201065,"corporation":false,"usgs":false,"family":"Jensen","given":"Nathan R.","affiliations":[],"preferred":false,"id":734092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734093,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sauey, Blake W. 0000-0003-2819-0814 bsauey@usgs.gov","orcid":"https://orcid.org/0000-0003-2819-0814","contributorId":202175,"corporation":false,"usgs":true,"family":"Sauey","given":"Blake","email":"bsauey@usgs.gov","middleInitial":"W.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734094,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, Craig 0000-0003-4023-0276 cjackson@usgs.gov","orcid":"https://orcid.org/0000-0003-4023-0276","contributorId":192276,"corporation":false,"usgs":true,"family":"Jackson","given":"Craig","email":"cjackson@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734095,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196709,"text":"70196709 - 2018 - Mechanisms of wave‐driven water level variability on reef‐fringed coastlines","interactions":[],"lastModifiedDate":"2018-07-03T11:25:32","indexId":"70196709","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Mechanisms of wave‐driven water level variability on reef‐fringed coastlines","docAbstract":"<p><span>Wave‐driven water level variability (and runup at the shoreline) is a significant cause of coastal flooding induced by storms. Wave runup is challenging to predict, particularly along tropical coral reef‐fringed coastlines due to the steep bathymetric profiles and large bottom roughness generated by reef organisms, which can violate assumptions in conventional models applied to open sandy coastlines. To investigate the mechanisms of wave‐driven water level variability on a reef‐fringed coastline, we performed a set of laboratory flume experiments on an along‐shore uniform bathymetric profile with and without bottom roughness. Wave setup and waves at frequencies lower than the incident sea‐swell forcing (infragravity waves) were found to be the dominant components of runup. These infragravity waves were positively correlated with offshore wave groups, signifying they were generated in the surf zone by the oscillation of the breakpoint. On the reef flat and at the shoreline, the low‐frequency waves formed a standing wave pattern with energy concentrated at the natural frequencies of the reef flat, indicating resonant amplification. Roughness elements used in the flume to mimic large reef bottom roughness reduced low frequency motions on the reef flat and reduced wave run up by 30% on average, compared to the runs over a smooth bed. These results provide insight into sea‐swell and infragravity wave transformation and wave setup dynamics on steep‐sloped coastlines, and the effect that future losses of reef bottom roughness may have on coastal flooding along reef‐fringed coasts.</span></p>","language":"English","publisher":"Wiley","doi":"10.1029/2018JC013933","usgsCitation":"Buckley, M.L., Lowe, R.J., Hansen, J.E., van Dongeren, A.R., and Storlazzi, C.D., 2018, Mechanisms of wave‐driven water level variability on reef‐fringed coastlines: Journal of Geophysical Research C: Oceans, v. 123, no. 5, p. 3811-3831, https://doi.org/10.1029/2018JC013933.","productDescription":"21 p.","startPage":"3811","endPage":"3831","ipdsId":"IP-092740","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468807,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://admin.research-repository.uwa.edu.au/en/publications/db5339a2-0de9-4c15-9798-f5eaddf31687","text":"Publisher Index Page"},{"id":437931,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71V5D7J","text":"USGS data release","linkHelpText":"Water level and velocity measurements from the 2012 University of Western Australia Fringing Reef Experiment (UWAFRE)"},{"id":353758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-26","publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe3e","contributors":{"authors":[{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":734068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, Ryan J.","contributorId":152265,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":734069,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Jeff E.","contributorId":204340,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff","email":"","middleInitial":"E.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":true,"id":734070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Dongeren, Ap R.","contributorId":203482,"corporation":false,"usgs":false,"family":"van Dongeren","given":"Ap","email":"","middleInitial":"R.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":734071,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":734072,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196708,"text":"70196708 - 2018 - Pharmaceutical manufacturing facility discharges can substantially increase the pharmaceutical load to U.S. wastewaters","interactions":[],"lastModifiedDate":"2021-05-28T14:06:57.742111","indexId":"70196708","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Pharmaceutical manufacturing facility discharges can substantially increase the pharmaceutical load to U.S. wastewaters","docAbstract":"<p><span>Discharges from pharmaceutical manufacturing facilities (PMFs) previously have been identified as important sources of pharmaceuticals to the environment. Yet few studies are available to establish the influence of PMFs on the pharmaceutical source contribution to wastewater treatment plants (WWTPs) and waterways at the national scale. Consequently, a national network of 13 WWTPs receiving PMF discharges, six WWTPs with no PMF input, and one WWTP that transitioned through a PMF closure were selected from across the United States to assess the influence of PMF inputs on pharmaceutical loading to WWTPs. Effluent samples were analyzed for 120 pharmaceuticals and pharmaceutical degradates. Of these, 33 pharmaceuticals had concentrations substantially higher in PMF-influenced effluent (maximum 555,000 ng/L) compared to effluent from control sites (maximum 175 ng/L). Concentrations in WWTP receiving PMF input are variable, as discharges from PMFs are episodic, indicating that production activities can vary substantially over relatively short (several months) periods and have the potential to rapidly transition to other pharmaceutical products. Results show that PMFs are an important, national-scale source of pharmaceuticals to the environment.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.04.160","usgsCitation":"Scott, T., Phillips, P.J., Kolpin, D., Finkelstein, K.M., Furlong, E., Foreman, W.T., and Gray, J., 2018, Pharmaceutical manufacturing facility discharges can substantially increase the pharmaceutical load to U.S. wastewaters: Science of the Total Environment, v. 636, p. 69-79, https://doi.org/10.1016/j.scitotenv.2018.04.160.","productDescription":"11 p.","startPage":"69","endPage":"79","ipdsId":"IP-095342","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":468809,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.04.160","text":"Publisher Index Page"},{"id":353759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"636","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe40","contributors":{"authors":[{"text":"Scott, Tia-Marie 0000-0002-5677-0544 tia-mariescott@usgs.gov","orcid":"https://orcid.org/0000-0002-5677-0544","contributorId":5122,"corporation":false,"usgs":true,"family":"Scott","given":"Tia-Marie","email":"tia-mariescott@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Patrick J. 0000-0001-5915-2015 pjphilli@usgs.gov","orcid":"https://orcid.org/0000-0001-5915-2015","contributorId":172757,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick","email":"pjphilli@usgs.gov","middleInitial":"J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734062,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":734063,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Finkelstein, Kaitlyn M. 0000-0003-1588-3312","orcid":"https://orcid.org/0000-0003-1588-3312","contributorId":202727,"corporation":false,"usgs":true,"family":"Finkelstein","given":"Kaitlyn","email":"","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734067,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Furlong, Edward T. 0000-0002-7305-4603","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":204151,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward T.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":734064,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foreman, William T. 0000-0002-2530-3310 wforeman@usgs.gov","orcid":"https://orcid.org/0000-0002-2530-3310","contributorId":190786,"corporation":false,"usgs":true,"family":"Foreman","given":"William","email":"wforeman@usgs.gov","middleInitial":"T.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":734065,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gray, James L. 0000-0002-0807-5635","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":202726,"corporation":false,"usgs":true,"family":"Gray","given":"James L.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":734066,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70196702,"text":"70196702 - 2018 - Reproductive success and contaminant associations in tree swallows (Tachycineta bicolor) used to assess a Beneficial Use Impairment in U.S. and Binational Great Lakes’ Areas of Concern","interactions":[],"lastModifiedDate":"2018-04-26T11:21:22","indexId":"70196702","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Reproductive success and contaminant associations in tree swallows (<i>Tachycineta bicolor</i>) used to assess a Beneficial Use Impairment in U.S. and Binational Great Lakes’ Areas of Concern","title":"Reproductive success and contaminant associations in tree swallows (Tachycineta bicolor) used to assess a Beneficial Use Impairment in U.S. and Binational Great Lakes’ Areas of Concern","docAbstract":"During 2010-2014, tree swallow (Tachycineta bicolor) reproductive success was monitored at 68 sites across all 5 Great Lakes, including 58 sites located within Great Lakes Areas of Concern (AOCs) and 10 non-AOCs. Sample eggs were collected from tree swallow clutches and analyzed for contaminants including polychlorinated biphenyls (PCBs), dioxins and furans, polybrominated diphenyl ethers, and 34 other organic compounds. Contaminant data were available for 360 of the clutches monitored. Markov chain multistate modeling was used to assess the importance of 5 ecological variables and 11 of the dominant contaminants in explaining the pattern of egg and nestling failure rates. Four of 5 ecological variables (Female Age, Date within season, Year, and Site) were important explanatory variables. Of the 11 contaminants, only total dioxin and furan toxic equivalents (TEQs) explained a significant amount of the egg failure probabilities. Neither total PCBs nor PCB TEQs explained the variation in egg failure rates. In a separate analysis, polycyclic aromatic hydrocarbon exposure in nestling diet, used as a proxy for female diet during egg laying, was significantly correlated with the daily probability of egg failure. The 8 sites within AOCs which had poorer reproduction when compared to 10 non-AOC sites, the measure of impaired reproduction as defined by the Great Lakes Restoration Initiative, were associated with exposure to dioxins and furan TEQs, PAHs, or depredation. Only 2 sites had poorer reproduction than the poorest performing non-AOC. Using a classic (non-modeling) approach to estimating reproductive success, 82% of nests hatched at least 1 egg, and 75% of eggs laid, excluding those collected for contaminant analyses, hatched.","language":"English","publisher":"Springer","doi":"10.1007/s10646-018-1913-9","usgsCitation":"Custer, C.M., Custer, T.W., Etterson, M.A., Dummer, P.M., Goldberg, D., and Franson, J.C., 2018, Reproductive success and contaminant associations in tree swallows (Tachycineta bicolor) used to assess a Beneficial Use Impairment in U.S. and Binational Great Lakes’ Areas of Concern: Ecotoxicology, v. 27, no. 4, p. 457-476, https://doi.org/10.1007/s10646-018-1913-9.","productDescription":"20 p.","startPage":"457","endPage":"476","ipdsId":"IP-086919","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":353728,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes","volume":"27","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-09","publicationStatus":"PW","scienceBaseUri":"5afee6cfe4b0da30c1bfbe46","contributors":{"authors":[{"text":"Custer, Christine M. 0000-0003-0500-1582 ccuster@usgs.gov","orcid":"https://orcid.org/0000-0003-0500-1582","contributorId":1143,"corporation":false,"usgs":true,"family":"Custer","given":"Christine","email":"ccuster@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Custer, Thomas W. 0000-0003-3170-6519 tcuster@usgs.gov","orcid":"https://orcid.org/0000-0003-3170-6519","contributorId":2835,"corporation":false,"usgs":true,"family":"Custer","given":"Thomas","email":"tcuster@usgs.gov","middleInitial":"W.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734044,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Etterson, Matthew A.","contributorId":108012,"corporation":false,"usgs":false,"family":"Etterson","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":734045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dummer, Paul M. 0000-0002-2055-9480 pdummer@usgs.gov","orcid":"https://orcid.org/0000-0002-2055-9480","contributorId":3015,"corporation":false,"usgs":true,"family":"Dummer","given":"Paul","email":"pdummer@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734046,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldberg, Diana R. 0000-0001-8540-8512","orcid":"https://orcid.org/0000-0001-8540-8512","contributorId":82252,"corporation":false,"usgs":true,"family":"Goldberg","given":"Diana R.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":734047,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Franson, J. Christian 0000-0002-0251-4238 jfranson@usgs.gov","orcid":"https://orcid.org/0000-0002-0251-4238","contributorId":177499,"corporation":false,"usgs":true,"family":"Franson","given":"J.","email":"jfranson@usgs.gov","middleInitial":"Christian","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":734048,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70196703,"text":"70196703 - 2018 - Assessing the efficacy of corn-based bait containing antimycin-a to control common carp populations using laboratory and pond experiments","interactions":[],"lastModifiedDate":"2018-06-04T16:02:11","indexId":"70196703","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","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":"Assessing the efficacy of corn-based bait containing antimycin-a to control common carp populations using laboratory and pond experiments","docAbstract":"<p><span>Strategic use of oral toxicants could allow for practical and sustainable control schemes for the invasive common carp (</span><i class=\"EmphasisTypeItalic \">Cyprinus carpio,</i><span><span>&nbsp;</span>or ‘carp’) if a toxicant selectively targeted carp and not native species. In this study, we incorporated antimycin-a (ANT-A), a known fish toxicant, into a corn-based bait and conducted a series of experiments to determine its toxicity, leaching rate, and species-specificity. Our results showed that ANT-A was lethal to carp at doses ≥&nbsp;4&nbsp;mg/kg and that the amount of ANT-A that leached out of the bait in 72&nbsp;h was not lethal to carp or bluegill (</span><i class=\"EmphasisTypeItalic \">Lepomis macrochirus</i><span>). Species-specificity trials were conducted in 227 L tanks, in which carp were stocked with three native species representing families that occur sympatrically with carp in our study region: the fathead minnow (</span><i class=\"EmphasisTypeItalic \">Pimephales promelas</i><span>), yellow perch (</span><i class=\"EmphasisTypeItalic \">Perca flavescens</i><span>) and bluegill. These trials showed high mortality of carp (46%) and fathead minnows (76%) but no significant mortality of perch or bluegill. Finally, a pond study, which used the same species composition except for fathead minnows, resulted in 37% morality among adult carp and no mortality among perch or bluegill. Our results suggest that corn-based bait that contains ANT-A could be used to selectively control carp in ecosystems dominated by percids or centrarchids, such as lakes across the Great Plains ecoregion of North America, where carp are especially problematic.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10530-018-1662-y","usgsCitation":"Poole, J.R., Sauey, B.W., Amberg, J., and Bajer, P.G., 2018, Assessing the efficacy of corn-based bait containing antimycin-a to control common carp populations using laboratory and pond experiments: Biological Invasions, v. 20, no. 7, p. 1809-1820, https://doi.org/10.1007/s10530-018-1662-y.","productDescription":"12 p.","startPage":"1809","endPage":"1820","ipdsId":"IP-085875","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":353729,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"7","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-15","publicationStatus":"PW","scienceBaseUri":"5afee6cfe4b0da30c1bfbe44","contributors":{"authors":[{"text":"Poole, Joshua R.","contributorId":204465,"corporation":false,"usgs":false,"family":"Poole","given":"Joshua","email":"","middleInitial":"R.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":734050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sauey, Blake W. 0000-0003-2819-0814 bsauey@usgs.gov","orcid":"https://orcid.org/0000-0003-2819-0814","contributorId":202175,"corporation":false,"usgs":true,"family":"Sauey","given":"Blake","email":"bsauey@usgs.gov","middleInitial":"W.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734051,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bajer, Przemyslaw G.","contributorId":204466,"corporation":false,"usgs":false,"family":"Bajer","given":"Przemyslaw","email":"","middleInitial":"G.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":734052,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196707,"text":"70196707 - 2018 - Open hydrology courseware using the United States Geological Survey’s National Water Census Data Portal","interactions":[],"lastModifiedDate":"2018-04-26T11:32:22","indexId":"70196707","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5679,"text":"Open Water Journal","active":true,"publicationSubtype":{"id":10}},"title":"Open hydrology courseware using the United States Geological Survey’s National Water Census Data Portal","docAbstract":"<p><span>The U.S. Geological Survey (USGS) is the primary U.S. Government agency for water data collection and dissemination. In this role, the USGS has recently created and deployed a National Water Census Data Portal (NWC-DP) which provides access to streamflow, evapotransporation, precipitation, aquatic biology and other data at the national level. Recognizing the value of these data sets for hydrologic science education, this paper presents an effort to bridge the gap between pencil–and-paper-based hydrology curriculum and the USGS NWC-DP resource. Specifically, we have developed an R package, National Water Census Education (NWCEd), and five associated laboratory exercises that integrate R- and web-services-based access to the NWC-DP data sets. Using custom functions built into the NWCEd, students are able to access unprecedented amounts of hydrologic data from the NWC-DP, which can be applied to current hydrology curriculum and analyzed using NWCEd and a number of other open-source R tools.</span></p>","language":"English","publisher":"BYU","usgsCitation":"Nelson, J., Ames, D.P., and Blodgett, D.L., 2018, Open hydrology courseware using the United States Geological Survey’s National Water Census Data Portal: Open Water Journal, v. 5, no. 1, p. 1-14.","productDescription":"Article 1; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-086854","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"links":[{"id":353730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":353724,"type":{"id":15,"text":"Index Page"},"url":"https://scholarsarchive.byu.edu/openwater/vol5/iss1/1/"}],"volume":"5","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cfe4b0da30c1bfbe42","contributors":{"authors":[{"text":"Nelson, Jake","contributorId":204467,"corporation":false,"usgs":false,"family":"Nelson","given":"Jake","email":"","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":734059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ames, Daniel P.","contributorId":204468,"corporation":false,"usgs":false,"family":"Ames","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":734060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blodgett, David L. 0000-0001-9489-1710 dblodgett@usgs.gov","orcid":"https://orcid.org/0000-0001-9489-1710","contributorId":3868,"corporation":false,"usgs":true,"family":"Blodgett","given":"David","email":"dblodgett@usgs.gov","middleInitial":"L.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":734058,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196713,"text":"70196713 - 2018 - Effect of dynamical phase on the resonant interaction among tsunami edge wave modes","interactions":[],"lastModifiedDate":"2018-04-26T16:21:37","indexId":"70196713","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Effect of dynamical phase on the resonant interaction among tsunami edge wave modes","docAbstract":"<p><span>Different modes of tsunami edge waves can interact through nonlinear resonance. During this process, edge waves that have very small initial amplitude can grow to be as large or larger than the initially dominant edge wave modes. In this study, the effects of dynamical phase are established for a single triad of edge waves that participate in resonant interactions. In previous studies, Jacobi elliptic functions were used to describe the slow variation in amplitude associated with the interaction. This analytical approach assumes that one of the edge waves in the triad has zero initial amplitude and that the combined phase of the three waves&nbsp;</span><i class=\"EmphasisTypeItalic \">φ</i><span>&nbsp;=&nbsp;</span><i class=\"EmphasisTypeItalic \">θ</i><sub>1</sub><span>&nbsp;+&nbsp;</span><i class=\"EmphasisTypeItalic \">θ</i><sub>2</sub><span>&nbsp;−&nbsp;</span><i class=\"EmphasisTypeItalic \">θ</i><sub>3</sub><span><span>&nbsp;</span>is constant at the value for maximum energy exchange (</span><i class=\"EmphasisTypeItalic \">φ</i><span>&nbsp;=&nbsp;0). To obtain a more general solution, dynamical phase effects and non-zero initial amplitudes for all three waves are incorporated using numerical methods for the governing differential equations. Results were obtained using initial conditions calculated from a subduction zone, inter-plate thrust fault geometry and a stochastic earthquake slip model. The effect of dynamical phase is most apparent when the initial amplitudes and frequencies of the three waves are within an order of magnitude. In this case, non-zero initial phase results in a marked decrease in energy exchange and a slight decrease in the period of the interaction. When there are large differences in frequency and/or initial amplitude, dynamical phase has less of an effect and typically one wave of the triad has very little energy exchange with the other two waves. Results from this study help elucidate under what conditions edge waves might be implicated in late, large-amplitude arrivals.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00024-018-1796-y","usgsCitation":"Geist, E.L., 2018, Effect of dynamical phase on the resonant interaction among tsunami edge wave modes: Pure and Applied Geophysics, v. 175, no. 4, p. 1341-1354, https://doi.org/10.1007/s00024-018-1796-y.","productDescription":"14 p.","startPage":"1341","endPage":"1354","ipdsId":"IP-093470","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":353755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"175","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-12","publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe3a","contributors":{"authors":[{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":734080,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70196715,"text":"70196715 - 2018 - Pedestrian evacuation modeling to reduce vehicle use for distant tsunami evacuations in Hawaiʻi","interactions":[],"lastModifiedDate":"2018-04-26T16:17:10","indexId":"70196715","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2036,"text":"International Journal of Disaster Risk Reduction","active":true,"publicationSubtype":{"id":10}},"title":"Pedestrian evacuation modeling to reduce vehicle use for distant tsunami evacuations in Hawaiʻi","docAbstract":"<p><span>Tsunami waves that arrive hours after generation elsewhere pose logistical challenges to emergency managers due to the perceived abundance of time and inclination of evacuees to use vehicles. We use coastal communities on the island of Oʻahu (Hawaiʻi, USA) to demonstrate regional evacuation modeling that can identify where successful pedestrian-based evacuations are plausible and where vehicle use could be discouraged. The island of Oʻahu has two tsunami-evacuation zones (standard and extreme), which provides the opportunity to examine if recommended travel modes vary based on zone. Geospatial path distance models are applied to estimate population exposure a</span><span>s a function of pedestrian travel time and speed out of evacuation zones. The use of the extreme zone triples the number of residents, employees, and facilities serving at-risk populations that would be encouraged to evacuate and slightly reduces the percentage of residents (98–76%) that could evacuate in less than 15 min at a plausible speed (with similar percentages for employees). Areas with lengthy evacuations are concentrated in the North Shore region for the standard zone but found all around the Oʻahu coastline for the extreme zone. The use of the extreme zone results in a 26% increase in the number of hotel visitors that would be encouraged to evacuate, and a 76% increase in the number of them that may require more than 15 min. Modeling can identify where pedestrian evacuations are plausible; however, there are logistical and behavioral issues that warrant attention before localized evacuation procedures may be realistic.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijdrr.2018.03.009","usgsCitation":"Wood, N.J., Jones, J., Peters, J., and Richards, K., 2018, Pedestrian evacuation modeling to reduce vehicle use for distant tsunami evacuations in Hawaiʻi: International Journal of Disaster Risk Reduction, v. 28, p. 271-283, https://doi.org/10.1016/j.ijdrr.2018.03.009.","productDescription":"13 p.","startPage":"271","endPage":"283","ipdsId":"IP-092793","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":468805,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijdrr.2018.03.009","text":"Publisher Index Page"},{"id":437932,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7862FNT","text":"USGS data release","linkHelpText":"Pedestrian tsunami evacuation results for two tsunami-evacuation zones (standard and extreme) and three travel speeds (impaired, slow, and fast walk) for O'ahu, HI"},{"id":353753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -158.31573486328125,\n              21.235622362422877\n            ],\n            [\n              -157.6153564453125,\n              21.235622362422877\n            ],\n            [\n              -157.6153564453125,\n              21.73717777095988\n            ],\n            [\n              -158.31573486328125,\n              21.73717777095988\n            ],\n            [\n              -158.31573486328125,\n              21.235622362422877\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"28","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe36","contributors":{"authors":[{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":734084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Jamie 0000-0002-9967-3314","orcid":"https://orcid.org/0000-0002-9967-3314","contributorId":204480,"corporation":false,"usgs":true,"family":"Jones","given":"Jamie","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":734085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peters, Jeff 0000-0003-4312-0590 jpeters@usgs.gov","orcid":"https://orcid.org/0000-0003-4312-0590","contributorId":4711,"corporation":false,"usgs":true,"family":"Peters","given":"Jeff","email":"jpeters@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":734086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richards, Kevin krichard@usgs.gov","contributorId":204475,"corporation":false,"usgs":false,"family":"Richards","given":"Kevin","email":"krichard@usgs.gov","affiliations":[{"id":36945,"text":"Hawaii Emergency Management Agency","active":true,"usgs":false}],"preferred":false,"id":734087,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196546,"text":"ofr20181063 - 2018 - Distribution and demography of San Francisco gartersnakes (Thamnophis sirtalis tetrataenia) at Mindego Ranch, Russian Ridge Open Space Preserve, San Mateo County, California","interactions":[],"lastModifiedDate":"2018-05-29T15:45:09","indexId":"ofr20181063","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1063","displayTitle":"Distribution and demography of San Francisco gartersnakes (<em>Thamnophis sirtalis tetrataenia</em>) at Mindego Ranch, Russian Ridge Open Space Preserve, San Mateo County, California","title":"Distribution and demography of San Francisco gartersnakes (Thamnophis sirtalis tetrataenia) at Mindego Ranch, Russian Ridge Open Space Preserve, San Mateo County, California","docAbstract":"<p class=\"p1\">San Francisco gartersnakes (<i>Thamnophis sirtalis tetrataenia</i>) are a subspecies of common gartersnakes endemic to the San Francisco Peninsula of northern California. Because of habitat loss and collection for the pet trade, San Francisco gartersnakes were listed as endangered under the precursor to the Federal Endangered Species Act. A population of San Francisco gartersnakes resides at Mindego Ranch, San Mateo County, which is part of the Russian Ridge Open Space Preserve owned and managed by the Midpeninsula Regional Open Space District (MROSD). Because the site contained non-native fishes and American bullfrogs (<i>Lithobates catesbeianus</i>), MROSD implemented management to eliminate or reduce the abundance of these non-native species in 2014. We monitored the population using capture-mark-recapture techniques to document changes in the population during and following management actions. Although drought confounded some aspects of inference about the effects of management, prey and San Francisco gartersnake populations generally increased following draining of Aquatic Feature 3. Continued management of the site to keep invasive aquatic predators from recolonizing or increasing in abundance, as well as vegetation management that promotes heterogeneous grassland/shrubland near wetlands, likely would benefit this population of San Francisco gartersnakes.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181063","collaboration":"Prepared in cooperation with the Midpeninsula Regional Open Space District","usgsCitation":"Kim, R., Halstead, B.J., Wylie, G.D., and Casazza, M.L., 2018, Distribution and demography of San Francisco gartersnakes (<em>Thamnophis sirtalis tetrataenia</em>) at Mindego Ranch, Russian Ridge Open Space Preserve, San Mateo County, California: U.S. Geological Survey Open-File Report 2018-1063, 80 p., https://doi.org/10.3133/ofr20181063.","productDescription":"viii, 80 p.","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-093147","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":353746,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1063/coverthb.jpg"},{"id":353747,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1063/ofr20181063.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1063"}],"country":"United States","state":"California","county":"San Mateo","otherGeospatial":"Mindego Ranch, Russian Ridge Open Space Preserve","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.25543022155762,\n              37.2960420634488\n            ],\n            [\n              -122.22109794616699,\n              37.2960420634488\n            ],\n            [\n              -122.22109794616699,\n              37.33065186897204\n            ],\n            [\n              -122.25543022155762,\n              37.33065186897204\n            ],\n            [\n              -122.25543022155762,\n              37.2960420634488\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.werc.usgs.gov/\" target=\"blank\" data-mce-href=\"https://www.werc.usgs.gov/\">Western Ecological Research Center</a><br> U.S. Geological Survey<br> 3020 State University Drive East<br> Sacramento, California 95819</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Study Area<br></li><li>Methods<br></li><li>Results<br></li><li>Discussion<br></li><li>Summary<br></li><li>Acknowledgments<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2018-04-26","noUsgsAuthors":false,"publicationDate":"2018-04-26","publicationStatus":"PW","scienceBaseUri":"5afee6d0e4b0da30c1bfbe4c","contributors":{"authors":[{"text":"Kim, Richard 0000-0001-5891-0582 rkim@usgs.gov","orcid":"https://orcid.org/0000-0001-5891-0582","contributorId":204478,"corporation":false,"usgs":true,"family":"Kim","given":"Richard","email":"rkim@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":734101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":733530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Glenn D. 0000-0002-7061-6658 glenn_wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7061-6658","contributorId":3052,"corporation":false,"usgs":true,"family":"Wylie","given":"Glenn","email":"glenn_wylie@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":734102,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":734103,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196005,"text":"sir20185009 - 2018 - Public-supply water use and self-supplied industrial water use in Tennessee, 2010","interactions":[],"lastModifiedDate":"2018-09-25T05:58:29","indexId":"sir20185009","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5009","title":"Public-supply water use and self-supplied industrial water use in Tennessee, 2010","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with the Tennessee Department of Environment and Conservation, Division of Water Resources, prepared this report and displayed and analyzed water use by self-supplied industrial and public-supply water systems in Tennessee for 2010. Public-supply water systems in Tennessee provide water for domestic, industrial, and commercial uses and for municipal services. In 2010, 474 public-supply water systems distributed 917 million gallons per day (Mgal/d) of surface water (67 percent, 617 Mgal/d) and groundwater (33 percent, 300 Mgal/d) to a population of 5.7 million in Tennessee. Gross per capita water use in Tennessee during 2010 was 162 gallons per day.</p><p>Since 1950, water withdrawals by public-supply water systems in Tennessee have increased from 160 Mgal/d to 917 Mgal/d in 2010. Each of the 95 counties in Tennessee was served by at least 1 public-supply water system in 2010. Tennessee public-supply water systems withdraw less groundwater than surface water, and surface-water use has increased at a faster rate than groundwater use. Since 2005, surface-water withdrawals have increased by 26 Mgal/d, and groundwater withdrawals have decreased by 29 Mgal/d, which is the first decrease in groundwater withdrawals since 1950; however, 29 systems reported increased groundwater withdrawals during 2010, and 12 of these 29 systems reported increases of 1 Mgal/d or more. Davidson County had the largest surface-water withdrawal rate (136 Mgal/d) in 2010. The largest groundwater withdrawal rate (151 Mgal/d) by a single public-supply water system was reported by Memphis Light, Gas and Water, which served more than 669,000 people in Shelby County in 2010.</p><p>Self-supplied industrial water use includes water for such purposes as fabrication, processing, washing, diluting, cooling, or transporting a product; incorporating water into a product; or for sanitation needs in facilities that manufacture various products. Water withdrawals for self-supplied industrial water use during 2010 were about 776 Mgal/d. This quantity represented a decrease of 7 Mgal/d since 2005. In Tennessee, self-supplied industrial water withdrawals were primarily for&nbsp;chemical and allied products (555 Mgal/d), paper and allied products (107 Mgal/d), aeronautical products (71.5 Mgal/d), concrete and glass products (9.74 Mgal/d), and primary metal products (4.49 Mgal/d); and these products accounted for 96 percent (747 Mgal/d) of the self-supplied industrial water withdrawals in 2010. Surface water supplied 94 percent of the water (728 Mgal/d) for self-supplied industrial purposes, and groundwater supplied 6 percent (47.6 Mgal/d). Self-supplied industrial water withdrawals in Sullivan County were 488 Mgal/d and accounted for 61 percent of the self-supplied industrial water withdrawals. The largest groundwater withdrawal, 14.9 Mgal/d, by a single self-supplied industry was in Memphis, Tennessee, for the production of chemicals and allied products.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185009","collaboration":"Prepared in cooperation with the Tennessee Department of Environment and Conservation, Division of Water Resources","usgsCitation":"Robinson, J.A., 2018, Public-supply water use and self-supplied industrial water use in Tennessee, 2010: U.S. Geological Survey Scientific Investigation Report 2018–5009, 30 p., https://doi.org/10.3133/sir20185009.","productDescription":"Report: v, 29 p.; 7 Appendixes; Data Release","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059935","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science 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 \"}}]}","contact":"<p><a href=\"mailto: dc_tn@usgs.gov\" data-mce-href=\"mailto: dc_tn@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/lmg-water/\" data-mce-href=\"https://www.usgs.gov/centers/lmg-water/\">Lower Mississippi Gulf Water Science Center</a>, Tennessee Office <br>U.S. Geological Survey<br>640 Grassmere Park, Suite 100 <br>Nashville, TN 37211</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Approach and Methods<br></li><li>Public-Supply Water Use During 2010<br></li><li>Self-Supplied Industrial Water Use During 2010<br></li><li>Summary<br></li><li>References Cited<br></li><li>Glossary<br></li><li>Appendix 1. Public-Supply Water Systems and Associated Water Use in the Tennessee Hydrologic Region, 2010<br></li><li>Appendix 2. Public-Supply Water Systems and Associated Water Use in the Ohio Hydrologic Region, 2010<br></li><li>Appendix 3. Public-Supply Water Systems and Associated Water Use in the Lower-Mississippi Hydrologic Region, 2010<br></li><li>Appendix 4. Self-Supplied Industrial Water Use in the Tennessee Hydrologic Region, 2010<br></li><li>Appendix 5. Self-Supplied Industrial Water Use in the Ohio Hydrologic Region, 2010<br></li><li>Appendix 6. Self-Supplied Industrial Water Use in the Lower Mississippi Hydrologic Region, 2010<br></li><li>Appendix 7. Public-Supply Water Systems in Tennessee, 2010<br></li></ul>","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"publishedDate":"2018-04-26","noUsgsAuthors":false,"publicationDate":"2018-04-26","publicationStatus":"PW","scienceBaseUri":"5afee6d0e4b0da30c1bfbe4e","contributors":{"authors":[{"text":"Robinson, John A. 0000-0001-8002-4237 jarobin@usgs.gov","orcid":"https://orcid.org/0000-0001-8002-4237","contributorId":1105,"corporation":false,"usgs":true,"family":"Robinson","given":"John","email":"jarobin@usgs.gov","middleInitial":"A.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":730885,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70196699,"text":"70196699 - 2018 - Most atolls will be uninhabitable by the mid-21st century because of sea-level rise exacerbating wave-driven flooding","interactions":[],"lastModifiedDate":"2018-04-26T11:08:10","indexId":"70196699","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Most atolls will be uninhabitable by the mid-21st century because of sea-level rise exacerbating wave-driven flooding","docAbstract":"<p><span>Sea levels are rising, with the highest rates in the tropics, where thousands of low-lying coral atoll islands are located. Most studies on the resilience of these islands to sea-level rise have projected that they will experience minimal inundation impacts until at least the end of the 21st century. However, these have not taken into account the additional hazard of wave-driven overwash or its impact on freshwater availability. We project the impact of sea-level rise and wave-driven flooding on atoll infrastructure and freshwater availability under a variety of climate change scenarios. We show that, on the basis of current greenhouse gas emission rates, the nonlinear interactions between sea-level rise and wave dynamics over reefs will lead to the annual wave-driven overwash of most atoll islands by the mid-21st century. This annual flooding will result in the islands becoming uninhabitable because of frequent damage to infrastructure and the inability of their freshwater aquifers to recover between overwash events. This study provides critical information for understanding the timing and magnitude of climate change impacts on atoll islands that will result in significant, unavoidable geopolitical issues if it becomes necessary to abandon and relocate low-lying island states.</span></p>","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.aap9741","usgsCitation":"Storlazzi, C.D., Gingerich, S.B., van Dongeren, A., Cheriton, O.M., Swarzenski, P.W., Quataert, E., Voss, C.I., Field, D.W., Annamalai, H., Piniak, G.A., and McCall, R.T., 2018, Most atolls will be uninhabitable by the mid-21st century because of sea-level rise exacerbating wave-driven flooding: Science Advances, v. 4, no. 4, p. 1-9, https://doi.org/10.1126/sciadv.aap9741.","productDescription":"eaap9741; 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-091317","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468808,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.aap9741","text":"Publisher Index Page"},{"id":437933,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VD6XDB","text":"USGS data release","linkHelpText":"Projected flood water depths on Roi-Namur, Kwajalein Atoll, Republic of the Marshall Islands"},{"id":353726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d0e4b0da30c1bfbe4a","contributors":{"authors":[{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":734021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gingerich, Stephen B. 0000-0002-4381-0746 sbginger@usgs.gov","orcid":"https://orcid.org/0000-0002-4381-0746","contributorId":1426,"corporation":false,"usgs":true,"family":"Gingerich","given":"Stephen","email":"sbginger@usgs.gov","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Dongeren, Ap","contributorId":149002,"corporation":false,"usgs":false,"family":"van Dongeren","given":"Ap","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":734023,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":204459,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":734024,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":189823,"corporation":false,"usgs":false,"family":"Swarzenski","given":"Peter","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":734025,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Quataert, Ellen","contributorId":193834,"corporation":false,"usgs":false,"family":"Quataert","given":"Ellen","email":"","affiliations":[],"preferred":false,"id":734026,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":734027,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Field, Donald W.","contributorId":204460,"corporation":false,"usgs":false,"family":"Field","given":"Donald","email":"","middleInitial":"W.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":734028,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Annamalai, Hariharasubramanian","contributorId":204461,"corporation":false,"usgs":false,"family":"Annamalai","given":"Hariharasubramanian","email":"","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":734029,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Piniak, Greg A.","contributorId":204462,"corporation":false,"usgs":false,"family":"Piniak","given":"Greg","email":"","middleInitial":"A.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":734030,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McCall, Robert T.","contributorId":148986,"corporation":false,"usgs":false,"family":"McCall","given":"Robert","email":"","middleInitial":"T.","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":734031,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70196712,"text":"70196712 - 2018 - Introduction to “Global tsunami science: Past and future, Volume III”","interactions":[],"lastModifiedDate":"2018-04-26T16:50:23","indexId":"70196712","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Introduction to “Global tsunami science: Past and future, Volume III”","docAbstract":"<p><span>Twenty papers on the study of tsunamis are included in Volume III of the PAGEOPH topical issue “Global Tsunami Science: Past and Future”. Volume I of this topical issue was published as PAGEOPH, vol. 173, No. 12, 2016 and Volume II as PAGEOPH, vol. 174, No. 8, 2017. Two papers in Volume III focus on specific details of the 2009 Samoa and the 1923 northern Kamchatka tsunamis; they are followed by three papers related to tsunami hazard assessment for three different regions of the world oceans: South Africa, Pacific coast of Mexico and the northwestern part of the Indian Ocean. The next six papers are on various aspects of tsunami hydrodynamics and numerical modelling, including tsunami edge waves, resonant behaviour of compressible water layer during tsunamigenic earthquakes, dispersive properties of seismic and volcanically generated tsunami waves, tsunami runup on a vertical wall and influence of earthquake rupture velocity on maximum tsunami runup. Four papers discuss problems of tsunami warning and real-time forecasting for Central America, the Mediterranean coast of France, the coast of Peru, and some general problems regarding the optimum use of the DART buoy network for effective real-time tsunami warning in the Pacific Ocean. Two papers describe historical and paleotsunami studies in the Russian Far East. The final set of three papers importantly investigates tsunamis generated by non-seismic sources: asteroid airburst and meteorological disturbances. Collectively, this volume highlights contemporary trends in global tsunami research, both fundamental and applied toward hazard assessment and mitigation.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00024-018-1851-8","usgsCitation":"Rabinovich, A.B., Fritz, H.M., Tanioka, Y., and Geist, E.L., 2018, Introduction to “Global tsunami science: Past and future, Volume III”: Pure and Applied Geophysics, v. 175, no. 4, p. 1231-1237, https://doi.org/10.1007/s00024-018-1851-8.","productDescription":"7 p.","startPage":"1231","endPage":"1237","ipdsId":"IP-096461","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":353757,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"175","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-19","publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe3c","contributors":{"authors":[{"text":"Rabinovich, Alexander B.","contributorId":177506,"corporation":false,"usgs":false,"family":"Rabinovich","given":"Alexander","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":734130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fritz, Hermann M.","contributorId":194830,"corporation":false,"usgs":false,"family":"Fritz","given":"Hermann","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":734131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tanioka, Yuichiro","contributorId":177507,"corporation":false,"usgs":false,"family":"Tanioka","given":"Yuichiro","email":"","affiliations":[],"preferred":false,"id":734132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":734133,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196701,"text":"70196701 - 2018 - Slow and steady wins the race? Future climate and land use change leaves the imperiled Blanding's turtle (Emydoidea blandingii) behind","interactions":[],"lastModifiedDate":"2018-04-26T11:15:01","indexId":"70196701","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Slow and steady wins the race? Future climate and land use change leaves the imperiled Blanding's turtle (<i>Emydoidea blandingii</i>) behind","title":"Slow and steady wins the race? Future climate and land use change leaves the imperiled Blanding's turtle (Emydoidea blandingii) behind","docAbstract":"<p><span>Climate change is accompanied by shifts in species distributions, as portions of current ranges become less suitable. Maintaining or improving landscape connectivity to facilitate species movements is a primary approach to mitigate the effects of climate change on biodiversity. However, it is not clear how ongoing changes in land use and climate may affect the existing connectivity of landscapes. We evaluated shifts in habitat suitability and connectivity for the imperiled Blanding's turtle (</span><i>Emydoidea blandingii</i><span>) in Wisconsin using species distribution modeling in combination with different future scenarios of both<span> land use change</span><span>&nbsp;</span>and climate change for the 2050s. We found that climate change had significant effects on both habitat suitability and connectivity, however, there was little difference in the magnitude of effects among different economic scenarios. Under both our low- and high-CO</span><sub>2</sub><span><span><span>&nbsp;</span>emissions scenarios, suitable habitat for the Blanding's turtle shifted northward. In the high-emissions scenario, almost no suitable habitat remained for Blanding's turtle in Wisconsin by the 2050s and there was up to a 100,000-fold increase in landscape resistance to turtle movement, suggesting the landscape essentially becomes impassable.<span> Habitat loss</span><span>&nbsp;</span>and landscape resistance were exponentially greater in southern versus northern Wisconsin, indicating a strong<span> trailing edge</span></span><span>&nbsp;</span>effect. Thus, populations at the southern edge of the range are likely to “fall behind” shifts in suitable habitat faster than northern populations. Given its limited dispersal capability, loss of suitable habitat may occur at a rate far faster than the Blanding's turtle can adjust to changing conditions via shifts in range.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2018.03.026","usgsCitation":"Hamilton, C.M., Bateman, B.L., Gorzo, J.M., Reid, B., Thogmartin, W.E., Peery, M.Z., Heglund, P.J., Radeloff, V.C., and Pidgeon, A.M., 2018, Slow and steady wins the race? Future climate and land use change leaves the imperiled Blanding's turtle (Emydoidea blandingii) behind: Biological Conservation, v. 222, p. 75-85, https://doi.org/10.1016/j.biocon.2018.03.026.","productDescription":"11 p.","startPage":"75","endPage":"85","ipdsId":"IP-088117","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468804,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2018.03.026","text":"Publisher Index Page"},{"id":353727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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M.","contributorId":204463,"corporation":false,"usgs":false,"family":"Gorzo","given":"Jessica","email":"","middleInitial":"M.","affiliations":[{"id":34699,"text":"University of Minnesota-Duluth","active":true,"usgs":false}],"preferred":false,"id":734037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reid, Brendan","contributorId":204464,"corporation":false,"usgs":false,"family":"Reid","given":"Brendan","affiliations":[],"preferred":false,"id":734038,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":734034,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peery, M. Zachariah","contributorId":171534,"corporation":false,"usgs":false,"family":"Peery","given":"M.","email":"","middleInitial":"Zachariah","affiliations":[],"preferred":false,"id":734039,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heglund, Patricia J.","contributorId":149499,"corporation":false,"usgs":false,"family":"Heglund","given":"Patricia","email":"","middleInitial":"J.","affiliations":[{"id":17755,"text":"U.S. Fish and Wildlife Service, Upper Midwest Environmental Sciences Center","active":true,"usgs":false}],"preferred":false,"id":734040,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Radeloff, Volker C.","contributorId":141124,"corporation":false,"usgs":false,"family":"Radeloff","given":"Volker","email":"","middleInitial":"C.","affiliations":[{"id":13679,"text":"SILVIS Lab, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":734041,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pidgeon, Anna M.","contributorId":141123,"corporation":false,"usgs":false,"family":"Pidgeon","given":"Anna","email":"","middleInitial":"M.","affiliations":[{"id":13679,"text":"SILVIS Lab, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":734042,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70196714,"text":"70196714 - 2018 - Temperature-influenced energetics model for migrating waterfowl","interactions":[],"lastModifiedDate":"2018-04-26T16:18:45","indexId":"70196714","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Temperature-influenced energetics model for migrating waterfowl","docAbstract":"<p><span>Climate and weather affect avian migration by influencing when and where birds fly, the energy costs and risks of flight, and the ability to sense cues necessary for proper navigation. We review the literature of the physiology of avian migration and the influence of climate, specifically temperature, on avian migration dynamics. We use waterfowl as a model guild because of the ready availability of empirical physiological data and their enormous economic value, but our discussion and expectations are broadly generalizable to migratory birds in general. We detail potential consequences of an increasingly warm climate on avian migration, including the possibility of the cessation of migration by some populations and species. Our intent is to lay the groundwork for including temperature effects on energetic gains and losses of migratory birds with the expected consequences of increasing temperatures into a predictive modeling framework. To this end, we provide a simulation of migration progression exclusively focused on the influence of temperature on the physiological determinants of migration. This simulation produced comparable results to empirically derived and observed values for different migratory factors (e.g., body fat content, flight range, departure date). By merging knowledge from the arenas of avian physiology and migratory theory we have identified a clear need for research and have developed hypotheses for a path forward.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2018.04.001","usgsCitation":"Aagaard, K., Thogmartin, W.E., and Lonsdorg, E.V., 2018, Temperature-influenced energetics model for migrating waterfowl: Ecological Modelling, v. 378, p. 46-58, https://doi.org/10.1016/j.ecolmodel.2018.04.001.","productDescription":"13 p.","startPage":"46","endPage":"58","ipdsId":"IP-084841","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468806,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2018.04.001","text":"Publisher Index Page"},{"id":353754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"378","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe38","contributors":{"authors":[{"text":"Aagaard, Kevin 0000-0003-0756-2172 kaagaard@usgs.gov","orcid":"https://orcid.org/0000-0003-0756-2172","contributorId":147393,"corporation":false,"usgs":true,"family":"Aagaard","given":"Kevin","email":"kaagaard@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lonsdorg, Eric V.","contributorId":204474,"corporation":false,"usgs":false,"family":"Lonsdorg","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":734083,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196718,"text":"70196718 - 2018 - Clusters of community exposure to coastal flooding hazards based on storm and sea level rise scenarios—implications for adaptation networks in the San Francisco Bay region","interactions":[],"lastModifiedDate":"2018-05-21T13:07:34","indexId":"70196718","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3242,"text":"Regional Environmental Change","active":true,"publicationSubtype":{"id":10}},"title":"Clusters of community exposure to coastal flooding hazards based on storm and sea level rise scenarios—implications for adaptation networks in the San Francisco Bay region","docAbstract":"<p><span>Sea level is projected to rise over the coming decades, further increasing the extent of flooding hazards in coastal communities. Efforts to address potential impacts from climate-driven coastal hazards have called for collaboration among communities to strengthen the application of best practices. However, communities currently lack practical tools for identifying potential partner communities based on similar hazard exposure characteristics. This study uses statistical cluster analysis to identify similarities in community exposure to flooding hazards for a suite of sea level rise and storm scenarios. We demonstrate this approach using 63 jurisdictions in the San Francisco Bay region of California (USA) and compare 21 distinct exposure variables related to residents, employees, and structures for six hazard scenario combinations of sea level rise and storms. Results indicate that cluster analysis can provide an effective mechanism for identifying community groupings. Cluster compositions changed based on the selected societal variables and sea level rise scenarios, suggesting that a community could participate in multiple networks to target specific issues or policy interventions. The proposed clustering approach can serve as a data-driven foundation to help communities identify other communities with similar adaptation challenges and to enhance regional efforts that aim to facilitate adaptation planning and investment prioritization.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10113-017-1267-5","usgsCitation":"Hummel, M., Wood, N.J., Schweikert, A., Stacey, M., Jones, J., Barnard, P.L., and Erikson, L., 2018, Clusters of community exposure to coastal flooding hazards based on storm and sea level rise scenarios—implications for adaptation networks in the San Francisco Bay region: Regional Environmental Change, v. 18, no. 5, p. 1343-1355, https://doi.org/10.1007/s10113-017-1267-5.","productDescription":"13 p.","startPage":"1343","endPage":"1355","ipdsId":"IP-084260","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":353750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.61016845703124,\n              37.385435182627226\n            ],\n            [\n              -121.58569335937501,\n              37.385435182627226\n            ],\n            [\n              -121.58569335937501,\n              38.25974980039479\n            ],\n            [\n              -122.61016845703124,\n              38.25974980039479\n            ],\n            [\n              -122.61016845703124,\n              37.385435182627226\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"18","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-07","publicationStatus":"PW","scienceBaseUri":"5afee6cde4b0da30c1bfbe34","contributors":{"authors":[{"text":"Hummel, Michelle","contributorId":204476,"corporation":false,"usgs":false,"family":"Hummel","given":"Michelle","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":734104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":734105,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schweikert, Amy","contributorId":204479,"corporation":false,"usgs":false,"family":"Schweikert","given":"Amy","email":"","affiliations":[],"preferred":false,"id":734106,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stacey, Mark T.","contributorId":13367,"corporation":false,"usgs":true,"family":"Stacey","given":"Mark T.","affiliations":[],"preferred":false,"id":734107,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Jeanne","contributorId":50444,"corporation":false,"usgs":true,"family":"Jones","given":"Jeanne","affiliations":[],"preferred":false,"id":734108,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":2880,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":734109,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":147149,"corporation":false,"usgs":true,"family":"Erikson","given":"Li H.","email":"lerikson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":734110,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70195642,"text":"sir20185010 - 2018 - Characterization of water quality in Bushy Park Reservoir, South Carolina, 2013–15","interactions":[],"lastModifiedDate":"2018-04-25T16:19:05","indexId":"sir20185010","displayToPublicDate":"2018-04-25T15:15:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5010","title":"Characterization of water quality in Bushy Park Reservoir, South Carolina, 2013–15","docAbstract":"<p>The Bushy Park Reservoir is the principal water supply for 400,000 people in the greater Charleston, South Carolina, area, which includes homes as well as businesses and industries in the Bushy Park Industrial Complex. Charleston Water System and the U.S. Geological Survey conducted a cooperative study during 2013–15 to assess the circulation of Bushy Park Reservoir and its effects on water-quality conditions, specifically, recurring taste-and-odor episodes. This report describes the water-quality data collected for the study that included a combination of discrete water-column sampling at seven locations in the reservoir and longitudinal water-quality profiling surveys of the reservoir and tributaries to characterize the temporal and spatial water-quality dynamics of Bushy Park Reservoir. Water-quality profiling surveys were conducted with an autonomous underwater vehicle equipped with a multiparameter water-quality-sonde bulkhead. Data collected by the autonomous underwater vehicle included water temperature, dissolved oxygen, pH, specific conductance, turbidity, total chlorophyll as fluorescence (estimate of algal biomass), and phycocyanin as fluorescence (estimate of cyanobacteria biomass) data.</p><p>Characterization of the water-quality conditions in the reservoir included comparison to established State nutrient guidelines, identification of any spatial and seasonal variation in water-quality conditions and phytoplankton community structures, and assessment of the degree of influence of water-quality conditions related to Foster Creek and Durham Canal inflows, especially during periods of elevated taste-and-odor concentrations. Depth-profile and autonomous underwater vehicle survey data were used to identify areas within the reservoir where greater phytoplankton and cyanobacteria densities were most likely occurring.</p><p>Water-quality survey results indicated that Bushy Park Reservoir tended to stratify thermally at a depth of about 20 feet from June to early October. The stratification was limited to the deeper portions of the reservoir near the dam and often dissipated within the reservoir near the CWS intake less than a mile upstream from the dam. Where thermally stratified, a corresponding depletion of dissolved oxygen also occurred at about the same depth and resulted in an anoxic hypolimnion below the 25-foot depth and an increase in specific conductance, likely due to re-mobilized metals and phosphorus under reducing conditions. In general, chlorophyll estimated from fluorescence exhibited some spatial variation, but no strong consistent pattern or “hot spot” was observed. Phycocyanin, estimated from relative fluorescence unit output as blue-green algae cell density, periodically seemed to be greater in the upper portion of the reservoir, but those differences may be attributed to increased turbidity and the potential change in phytoplankton community structure that affects fluorescence. Increased phycocyanin was observed at about the 10-foot depth during the summer months.</p><p>A constant production of 2-methylisoborneol (MIB) near the dam and geosmin in the middle and upper portions of the reservoir appears to be occurring during the summer and early fall in the reservoir, but concentrations of these compounds tend to be between 10 and 15 nanograms per liter, which is at the Charleston Water System treatment threshold. At the Bushy Park Reservoir intake, the dominant taste-and-odor compound tended to be MIB, measured at a 2- or 3-to-1 ratio with geosmin during the summer and fall. During springtime episodes, however, when taste-and-odor compound concentrations typically are elevated above the Charleston Water System treatment threshold, the spatial distribution of geosmin concentrations greater than 15 nanograms per liter (28 to 38 nanograms per liter) was best explained by in situ production in the lower portion of the Bushy Park Reservoir near the dam rather than transport from Foster Creek. This pattern seems to indicate a possible shift in phytoplankton communities (or, at least, cyanobacteria communities) from MIB producers to geosmin producers.</p><p>The spatial and seasonal assessment of water-quality conditions in Bushy Park Reservoir identified seasonal differences in water chemistry and spatial differences between the upper and lower portions of the reservoir that correspond to the location of elevated geosmin concentrations. On the basis of the spatial and seasonal assessment of actinomycetes concentrations compared to taste-and-odor compound concentrations, cyanobacteria production likely was the dominant source of the taste-and-odor episodes rather than actinomycetes. The lack of spatial and seasonal patterns in actinomycetes concentrations did not correspond to the springtime geosmin concentrations that were elevated above the Charleston Water System treatment threshold in the lower portion of the reservoir. Additionally, actinomycetes concentrations, although ubiquitous, had a median of about 9 and maximum of about 20 colonies per milliliter, which can be considered low for elevated taste-and-odor compound production. Nonetheless, the potential exists for actinomycetes to be a secondary source of taste-and-odor production and could explain some of the ubiquitous occurrence of low-level taste-and-odor production, such as MIB concentrations, observed throughout the summer and early fall months.</p><p>When evaluated by biovolume, cyanobacteria were not the dominant phytoplankton group in Bushy Park Reservoir during the study period. <i>Dolichospermum planctonicum</i> (previously <i>Anabaena planktonica </i>) was the dominant genera of the cyanobacteria group during spring periods. The geosmin-producing genera that were identified in the 2014 and 2015 spring communities in Bushy Park Reservoir were not observed in the 1999 and 2000 algal taxonomic data.</p><p>A more robust examination of phytoplankton species was conducted by using a multivariate analysis that identified seasonal changes in phytoplankton community structure. These seasonal phytoplankton communities appeared to be explained by seasonal changes in water chemistry and may be responsible for episodes of taste-and-odor occurrence, especially geosmin. The most probable source of geosmin identified during the study was <i>D. planctonicum</i>.</p><p>In a synoptic sampling event during a taste-and-odor episode in April 2015, cyanobacteria, not acinomycetes, also was indicated to be the more prevalent source of the geosmin. Although the Edisto River intake and its associated supply tunnel to the treatment facility had relatively high actinomycetes concentrations (130 and 140 colonies per milliliter, respectively) compared to the Bushy Park intake and tunnel (2 colonies per milliliter), corresponding geosmin concentrations were below 5 nanograms per liter for source water from the Edisto River intake and tunnel. Elevated geosmin concentrations above the Charleston Water System treatment threshold were identified in source waters from the Bushy Park Reservoir. The cyanobacteria community at the sampled sites in April 2015 was statistically similar to the community in the Bushy Park Reservoir in April 2014, when geosmin concentrations also were elevated. The only geosmin-producing genus identified at the Bushy Park intake, however, was <i>D. planctonicum</i>.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185010","collaboration":"Prepared in cooperation with Charleston Water System","usgsCitation":"Conrads, P.A., Journey, C.A., Petkewich, M.D., Lanier, T.H., and Clark, J.M., 2018, Characterization of water quality in Bushy Park Reservoir, South Carolina, 2013–15: U.S. Geological Survey Scientific Investigations Report 2018–5010,  175 p., https://doi.org/10.3133/sir20185010. ","productDescription":"xi, 175 p.","numberOfPages":"192","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087952","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":437934,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z7YOXC","text":"USGS data release","linkHelpText":"Phycocyanin, Velocity, AUV, and Profile Data for William Station Shutdown in Bushy Park Reservoir, South Carolina, 2017"},{"id":353632,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5010/sir20185010.pdf","text":"Report","size":"27.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5010"},{"id":353631,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5010/coverthb.jpg"},{"id":353639,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NG4NVX","text":"USGS data release","description":"USGS data release","linkHelpText":"Water Quality Data for Bushy Park Reservoir, South Carolina 2013–2015"}],"country":"United States","state":"South Carolina","otherGeospatial":"Bushy Park Reservoir","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.364990234375,\n              32.816132537537115\n            ],\n            [\n              -79.43939208984375,\n              32.816132537537115\n            ],\n            [\n              -79.43939208984375,\n              33.51162942617925\n            ],\n            [\n              -80.364990234375,\n              33.51162942617925\n            ],\n            [\n              -80.364990234375,\n              32.816132537537115\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"dc_sc@usgs.gov\" data-mce-href=\"dc_sc@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/water/southatlantic/\" data-mce-href=\"https://www.usgs.gov/water/southatlantic/\">South Altantic Water Science Center</a><br> U.S. Geological Survey <br> 720 Gracern Road <br> Stephenson Center, Suite 129 <br> Columbia, SC 29210</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Approach and Methods</li><li>Characterization of Reservoir Water Quality</li><li>Summary</li><li>References Cited</li><li>Appendix 1.&nbsp;Operation and data processing of the EcoMapper Iver2 autonomous&nbsp;underwater vehicle</li><li>Appendix 2.&nbsp;Plots showing 2D longitudinal profiles for seven parameters for&nbsp;16 autonomous underwater vehicle water-quality surveys&nbsp;</li><li>Appendix 3.&nbsp;Water-quality profile data collected from the Bushy Park Reservoir,&nbsp;near Goose Creek, South Carolina, between September 2013 and April 2015</li><li>Appendix 4.&nbsp;Summary of the quality assurance and quality control data collected in&nbsp;Bushy Park Reservoir, near Goose Creek, South Carolina, September 2013 to&nbsp;April 2015</li><li>Appendix 5.&nbsp;Analytical results for water-column samples collected in Bushy Park&nbsp;Reservoir, near Goose Creek, South Carolina, September 2013 to April 2015</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2018-04-25","noUsgsAuthors":false,"publicationDate":"2018-04-25","publicationStatus":"PW","scienceBaseUri":"5afee6d0e4b0da30c1bfbe50","contributors":{"authors":[{"text":"Conrads, Paul A. 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":198982,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":729533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petkewich, Matthew D. 0000-0002-5749-6356 mdpetkew@usgs.gov","orcid":"https://orcid.org/0000-0002-5749-6356","contributorId":982,"corporation":false,"usgs":true,"family":"Petkewich","given":"Matthew","email":"mdpetkew@usgs.gov","middleInitial":"D.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lanier, Timothy H. 0000-0001-5104-3308 thlanier@usgs.gov","orcid":"https://orcid.org/0000-0001-5104-3308","contributorId":4171,"corporation":false,"usgs":true,"family":"Lanier","given":"Timothy","email":"thlanier@usgs.gov","middleInitial":"H.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733818,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Jimmy M. 0000-0002-3138-5738 jmclark@usgs.gov","orcid":"https://orcid.org/0000-0002-3138-5738","contributorId":4773,"corporation":false,"usgs":true,"family":"Clark","given":"Jimmy","email":"jmclark@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733819,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70227679,"text":"70227679 - 2018 - Adaptive management of animal populations with significant unknowns and uncertainties: A case study","interactions":[],"lastModifiedDate":"2022-01-26T16:37:24.221638","indexId":"70227679","displayToPublicDate":"2018-04-25T10:35:58","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Adaptive management of animal populations with significant unknowns and uncertainties: A case study","docAbstract":"<p><span>Conservation and management decision making in natural resources is challenging due to numerous uncertainties and unknowns, especially relating to understanding system dynamics. Adaptive resource management (ARM) is a formal process to making logical and transparent recurrent decisions when there are uncertainties about system dynamics. Despite wide recognition and calls for implementing adaptive natural resource management, applications remain limited. More common is a reactive approach to decision making, which ignores future system dynamics. This contrasts with ARM, which anticipates future dynamics of ecological process and management actions using a model-based framework. Practitioners may be reluctant to adopt ARM because of the dearth of comparative evaluations between ARM and more common approaches to making decisions. We compared the probability of meeting management objectives when managing a population under both types of decision frameworks, specifically in relation to typical uncertainties and unknowns. We use a population of Sandhill Cranes as our case study. We evaluate each decision process under varying levels of monitoring and ecological uncertainty, where the true underlying population dynamics followed a stochastic age-structured population model with environmentally driven vital rate density dependence. We found that the ARM framework outperformed the currently employed reactive decision framework to manage Sandhill Cranes in meeting the population objective across an array of scenarios. This was even the case when the candidate set of population models contained only naïve representations of the true population process. Under the reactive decision framework, we found little improvement in meeting the population objective even if monitoring uncertainty was eliminated. In contrast, if the population was monitored without error within the ARM framework, the population objective was always maintained, regardless of the population models considered. Contrary to expectation, we found that age-specific optimal harvest decisions are not always necessary to meet a population objective when population dynamics are age structured. Population managers can decrease risks and gain transparency and flexibility in management by adopting an ARM framework. If population monitoring data has high sampling variation and/or limited empirical knowledge is available for constructing mechanistic population models, ARM model sets should consider a range of mechanistic, descriptive, and predictive model types.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1734","usgsCitation":"Gerber, B.D., and Kendall, W.L., 2018, Adaptive management of animal populations with significant unknowns and uncertainties: A case study: Ecological Applications, v. 28, no. 5, p. 1325-1341, https://doi.org/10.1002/eap.1734.","productDescription":"17 p.","startPage":"1325","endPage":"1341","ipdsId":"IP-073120","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":489030,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/nrs_facpubs/84","text":"External Repository"},{"id":394876,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gerber, Brian D.","contributorId":187620,"corporation":false,"usgs":false,"family":"Gerber","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":831785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":831704,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70196508,"text":"ofr20181060 - 2018 - USA National Phenology Network observational data documentation","interactions":[],"lastModifiedDate":"2018-04-25T16:12:08","indexId":"ofr20181060","displayToPublicDate":"2018-04-25T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1060","title":"USA National Phenology Network observational data documentation","docAbstract":"<p><span>The goals of the USA National Phenology Network (USA-NPN,&nbsp;</span><span class=\"m_-3679835315905615095m_755557968517775349gmail-MsoHyperlink\"><a href=\"http://www.usanpn.org/\" target=\"_blank\" data-mce-href=\"http://www.usanpn.org/\">www.usanpn.org</a></span><span>) are to advance science, inform decisions, and communicate and connect with the public regarding phenology and species’ responses to environmental variation and climate change. The USA-NPN seeks to advance the science of phenology and facilitate ecosystem stewardship by providing phenological information freely and openly. To accomplish these goals, the USA-NPN National Coordinating Office (NCO) delivers observational data on plant and animal phenology in several formats, including minimally processed status and intensity datasets and derived phenometrics for individual plants, sites, and regions. This document describes the suite of observational data products delivered by the USA National Phenology Network, covering the period 2009–present for the United States and accessible via the Phenology Observation Portal (</span><span class=\"m_-3679835315905615095m_755557968517775349gmail-MsoHyperlink\"><a href=\"http://dx.doi.org/10.5066/F78S4N1V\" target=\"_blank\" data-mce-href=\"http://dx.doi.org/10.5066/F78S4N1V\">http://dx.doi.org/10.5066/F78S4N1V</a></span><span>) and via an Application Programming Interface. The data described here have been used in diverse research and management applications, including over 30 publications in fields such as remote sensing, plant evolution, and resource management.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181060","usgsCitation":"Rosemartin, A., Denny, E.G., Gerst, K.L., Marsh, R.L., Posthumus, E.E., Crimmins, T.M., and Weltzin, J.F., 2018, USA National Phenology Network observational data documentation: U.S. Geological Survey Open-File Report 2018–1060, 24 p., https://doi.org/10.3133/ofr20181060.","productDescription":"Report: vi, 24 p.; Appendix tables","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085279","costCenters":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"links":[{"id":353663,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1060/coverthb.jpg"},{"id":353665,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1060/ofr20181060_appendix1tables.zip","text":"Appendix 1 Tables","size":"67 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2018-1080 Appendix 1"},{"id":353664,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1060/ofr20181060.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1080"}],"contact":"<p><span size=\"2\" face=\"arial, helvetica, sans-serif\" data-mce-style=\"font-family: arial, helvetica, sans-serif; font-size: small;\" style=\"font-family: arial, helvetica, sans-serif; font-size: small;\"><a href=\"https://www2.usgs.gov/ecosystems/org_chart.html\" target=\"_blank\" data-mce-href=\"https://www2.usgs.gov/ecosystems/org_chart.html\">Director</a>,<a href=\"https://www2.usgs.gov/ecosystems/\" target=\"_blank\" data-mce-href=\"https://www2.usgs.gov/ecosystems/\"><br>Ecosystems Mission Area<br></a></span><span size=\"2\" face=\"arial, helvetica, sans-serif\" data-mce-style=\"font-family: arial, helvetica, sans-serif; font-size: small;\" style=\"font-family: arial, helvetica, sans-serif; font-size: small;\"><a href=\"https://usgs.gov/\" target=\"_blank\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey</a><br></span><span size=\"2\" face=\"arial, helvetica, sans-serif\" data-mce-style=\"font-family: arial, helvetica, sans-serif; font-size: small;\" style=\"font-family: arial, helvetica, sans-serif; font-size: small;\">12201 Sunrise Valley Dr., MS 300<br></span><span size=\"2\" face=\"arial, helvetica, sans-serif\" data-mce-style=\"font-family: arial, helvetica, sans-serif; font-size: small;\" style=\"font-family: arial, helvetica, sans-serif; font-size: small;\">Reston, VA &nbsp;20192</span></p>","tableOfContents":"<ul><li>Acknowledgements<br></li><li>Abstract<br></li><li>Introduction<br></li><li>Data Collection Protocols<br></li><li>Data Discovery, Access, Quality and Documentation<br></li><li>Data Types<br></li><li>Status and Intensity Data<br></li><li>Individual Phenometrics<br></li><li>Site Phenometrics<br></li><li>Magnitude Phenometrics<br></li><li>Applications<br></li><li>References Cited<br></li><li>Appendix 1: Datafield Definition Tables<br></li><li>Appendix 2: Quality Assurance and Quality Control Measures<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2018-04-25","noUsgsAuthors":false,"publicationDate":"2018-04-25","publicationStatus":"PW","scienceBaseUri":"5afee6d0e4b0da30c1bfbe56","contributors":{"authors":[{"text":"Rosemartin, Alyssa H.","contributorId":178239,"corporation":false,"usgs":false,"family":"Rosemartin","given":"Alyssa","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":733317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Denny, Ellen G.","contributorId":204179,"corporation":false,"usgs":false,"family":"Denny","given":"Ellen","email":"","middleInitial":"G.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":733318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerst, Katharine L.","contributorId":175227,"corporation":false,"usgs":false,"family":"Gerst","given":"Katharine","email":"","middleInitial":"L.","affiliations":[{"id":27543,"text":"National Phenology Network, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":733319,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marsh, R. Lee","contributorId":146211,"corporation":false,"usgs":false,"family":"Marsh","given":"R.","email":"","middleInitial":"Lee","affiliations":[{"id":16629,"text":"USA National Phenology Network, SNRE University of Arizona","active":true,"usgs":false}],"preferred":false,"id":733320,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Posthumus, Erin E.","contributorId":77460,"corporation":false,"usgs":true,"family":"Posthumus","given":"Erin E.","affiliations":[],"preferred":false,"id":733900,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crimmins, Theresa M.","contributorId":178236,"corporation":false,"usgs":false,"family":"Crimmins","given":"Theresa","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":733321,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weltzin, Jake 0000-0001-8641-6645 jweltzin@usgs.gov","orcid":"https://orcid.org/0000-0001-8641-6645","contributorId":196323,"corporation":false,"usgs":true,"family":"Weltzin","given":"Jake","email":"jweltzin@usgs.gov","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"preferred":true,"id":733316,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70196693,"text":"70196693 - 2018 - Remote measurement of canopy water content in giant sequoias (Sequoiadendron giganteum) during drought","interactions":[],"lastModifiedDate":"2018-04-25T10:42:11","indexId":"70196693","displayToPublicDate":"2018-04-25T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Remote measurement of canopy water content in giant sequoias (<i>Sequoiadendron giganteum</i>) during drought","title":"Remote measurement of canopy water content in giant sequoias (Sequoiadendron giganteum) during drought","docAbstract":"<div class=\"Abstracts\"><div id=\"ab010\" class=\"abstract author\" lang=\"en\"><div id=\"as010\"><p id=\"sp0010\">California experienced severe drought from 2012 to 2016, and there were visible changes in the forest canopy throughout the State. In 2014, unprecedented foliage dieback was recorded in giant sequoia (<i>Sequoiadendron giganteum</i>) trees in Sequoia National Park, in the southern California Sierra Nevada mountains. Although visible changes in sequoia canopies can be recorded, biochemical and physiological responses to drought stress in giant sequoia canopies are not well understood. Ground-based measurements provide insight into the mechanisms of drought responses in trees, but are often limited to few individuals, especially in trees of tall stature such as giant sequoia. Recent studies demonstrate that remotely measured forest canopy water content (CWC) is a general indicator of canopy response to drought, but the underpinning leaf- to canopy-level causes of observed variation in CWC remain poorly understood. We combined field and airborne remote sensing measurements taken in 2015 and 2016 to assess the biophysical responses of giant sequoias to drought. In 49 study trees, CWC was related to leaf water potential, but not to the other foliar traits, suggesting that changes in CWC were made at whole-canopy rather than leaf scales. We found a non-random, spatially varying pattern in mapped CWC, with lower CWC values at lower elevation and along the outer edges of the groves. This pattern was also observed in empirical measurements of foliage dieback from the ground, and in mapped CWC across multiple sequoia groves in this region, supporting the hypothesis that drought stress is expressed in canopy-level changes in giant sequoias. The fact that we can clearly detect a relationship between CWC and foliage dieback, even without taking into account prior variability or new leaf growth, strongly suggests that remotely sensed CWC, and changes in CWC, are a useful measure of water stress in giant sequoia, and valuable for assessing and managing these iconic forests in drought.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2017.12.002","usgsCitation":"Martin, R.E., Asner, G.P., Francis, E., Ambrose, A., Baxter, W., Das, A., Vaughn, N.R., Paz-Kagan, T., Dawson, T.E., Nydick, K.R., and Stephenson, N.L., 2018, Remote measurement of canopy water content in giant sequoias (Sequoiadendron giganteum) during drought: Forest Ecology and Management, v. 419-420, p. 279-290, https://doi.org/10.1016/j.foreco.2017.12.002.","productDescription":"12 p.","startPage":"279","endPage":"290","ipdsId":"IP-091084","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468810,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2017.12.002","text":"Publisher Index Page"},{"id":353694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sequoia National Park","volume":"419-420","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d0e4b0da30c1bfbe54","contributors":{"authors":[{"text":"Martin, Roberta E.","contributorId":201234,"corporation":false,"usgs":false,"family":"Martin","given":"Roberta","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":734001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asner, Gregory P.","contributorId":25393,"corporation":false,"usgs":false,"family":"Asner","given":"Gregory","email":"","middleInitial":"P.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":734002,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Francis, Emily","contributorId":204453,"corporation":false,"usgs":false,"family":"Francis","given":"Emily","email":"","affiliations":[{"id":30217,"text":"Carnegie Institution for Science","active":true,"usgs":false}],"preferred":false,"id":734003,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ambrose, Anthony","contributorId":204454,"corporation":false,"usgs":false,"family":"Ambrose","given":"Anthony","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":734004,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baxter, Wendy","contributorId":204455,"corporation":false,"usgs":false,"family":"Baxter","given":"Wendy","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":734005,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Das, Adrian J. 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":3842,"corporation":false,"usgs":true,"family":"Das","given":"Adrian J.","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":734006,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vaughn, Nicolas R.","contributorId":201233,"corporation":false,"usgs":false,"family":"Vaughn","given":"Nicolas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":734007,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Paz-Kagan, Tarin","contributorId":196597,"corporation":false,"usgs":false,"family":"Paz-Kagan","given":"Tarin","email":"","affiliations":[],"preferred":false,"id":734008,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dawson, Todd E.","contributorId":176594,"corporation":false,"usgs":false,"family":"Dawson","given":"Todd","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":734009,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nydick, Koren R.","contributorId":196601,"corporation":false,"usgs":false,"family":"Nydick","given":"Koren","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":734010,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Stephenson, Nathan L. 0000-0003-0208-7229 nstephenson@usgs.gov","orcid":"https://orcid.org/0000-0003-0208-7229","contributorId":2836,"corporation":false,"usgs":true,"family":"Stephenson","given":"Nathan","email":"nstephenson@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":734000,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70196696,"text":"70196696 - 2018 - A numerical model investigation of the impacts of Hurricane Sandy on water level variability in Great South Bay, New York","interactions":[],"lastModifiedDate":"2018-04-25T15:58:46","indexId":"70196696","displayToPublicDate":"2018-04-25T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"A numerical model investigation of the impacts of Hurricane Sandy on water level variability in Great South Bay, New York","docAbstract":"<p><span>Hurricane Sandy was a large and intense storm with high winds that caused total water levels from combined tides and storm surge to reach 4.0 m in the Atlantic Ocean and 2.5 m in Great South Bay (GSB), a back-barrier bay between Fire Island and Long Island, New York. In this study the impact of the hurricane winds and waves are examined in order to understand the flow of ocean water into the back-barrier bay and water level variations within the bay. To accomplish this goal, a high resolution hurricane wind field is used to drive the coupled Delft3D-SWAN hydrodynamic and wave models over a series of grids with the finest resolution in GSB. The processes that control water levels in the back-barrier bay are investigated by comparing the results of four cases that include: (i) tides only; (ii) tides, winds and waves with no overwash over Fire Island allowed; (iii) tides, winds, waves and limited overwash at the east end of the island; (iv) tides, winds, waves and extensive overwash along the island. The results indicate that strong local wind-driven storm surge along the bay axis had the largest influence on the total water level fluctuations during the hurricane. However, the simulations allowing for overwash have higher correlation with water level observations in GSB and suggest that island overwash provided a significant contribution of ocean water to eastern GSB during the storm. The computations indicate that overwash of 7500–10,000 </span><span id=\"mmlsi0143\" class=\"mathmlsrc\"><span class=\"formulatext stixSupport mathImg\" title=\"Click to view the MathML source\" data-mathurl=\"/science?_ob=MathURL&amp;_method=retrieve&amp;_eid=1-s2.0-S0278434318300396&amp;_mathId=si0143.gif&amp;_user=111111111&amp;_pii=S0278434318300396&amp;_rdoc=1&amp;_issn=02784343&amp;md5=4a2348020c5cead8081fb67bdcafb8e9\">m<sup>3</sup>s<sup>−1</sup></span></span><span><span>&nbsp;</span>was approximately the same as the inflow from the ocean through the major existing inlet. Overall, the model results indicate the complex variability in total water levels driven by tides, ocean storm surge, surge from local winds, and overwash that had a significant impact on the circulation in Great South Bay during Hurricane Sandy.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2018.04.003","usgsCitation":"Bennett, V.C., Mulligan, R.P., and Hapke, C.J., 2018, A numerical model investigation of the impacts of Hurricane Sandy on water level variability in Great South Bay, New York: Continental Shelf Research, v. 161, p. 1-11, https://doi.org/10.1016/j.csr.2018.04.003.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-082328","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468811,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2018.04.003","text":"Publisher Index Page"},{"id":353706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Great South Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.7,\n              40.55\n            ],\n            [\n              -72.7,\n              40.55\n            ],\n            [\n              -72.7,\n              40.8\n            ],\n            [\n              -73.7,\n              40.8\n            ],\n            [\n              -73.7,\n              40.55\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"161","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d0e4b0da30c1bfbe52","contributors":{"authors":[{"text":"Bennett, Vanessa C. C.","contributorId":204457,"corporation":false,"usgs":false,"family":"Bennett","given":"Vanessa","email":"","middleInitial":"C. C.","affiliations":[{"id":36943,"text":"Queens University","active":true,"usgs":false}],"preferred":false,"id":734015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mulligan, Ryan P.","contributorId":194423,"corporation":false,"usgs":false,"family":"Mulligan","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":35723,"text":"Queen's University - Kingston, Ontario","active":true,"usgs":false}],"preferred":false,"id":734016,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":734014,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196520,"text":"ofr20181064 - 2018 - Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2017","interactions":[],"lastModifiedDate":"2018-04-25T10:18:41","indexId":"ofr20181064","displayToPublicDate":"2018-04-24T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1064","displayTitle":"Status and trends of adult Lost River (<em>Deltistes luxatus</em>) and shortnose (<em>Chasmistes brevirostris</em>) sucker populations in Upper Klamath Lake, Oregon, 2017","title":"Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2017","docAbstract":"<h1>Executive Summary</h1><p class=\"p1\">Data from a long-term capture-recapture program were used to assess the status and dynamics of populations of two long-lived, federally endangered catostomids in Upper Klamath Lake, Oregon. Lost River suckers (LRS; <i>Deltistes luxatus</i>) and shortnose suckers (SNS; <i>Chasmistes brevirostris</i>) have been captured and tagged with passive integrated transponder (PIT) tags during their spawning migrations in each year since 1995. In addition, beginning in 2005, individuals that had been previously PIT-tagged were re-encountered on remote underwater antennas deployed throughout sucker spawning areas. Captures and remote encounters during the spawning season in spring 2016 were incorporated into capture-recapture analyses of population dynamics.</p><p class=\"p1\">Cormack-Jolly-Seber (CJS) open population capture-recapture models were used to estimate annual survival probabilities, and a reverse-time analog of the CJS model was used to estimate recruitment of new individuals into the spawning populations. In addition, data on the size composition of captured fish were examined to provide corroborating evidence of recruitment. Model estimates of survival and recruitment were used to derive estimates of changes in population size over time and to determine the status of the populations through 2015. Separate analyses were done for each species and also for each subpopulation of LRS. Shortnose suckers and one subpopulation of LRS migrate into tributary rivers to spawn, whereas the other LRS subpopulation spawns at groundwater upwelling areas along the eastern shoreline of the lake.</p><p class=\"p1\">Capture-recapture analyses indicated that with a few exceptions, the survival of males and females in both Lost River sucker subpopulations was high (greater than 0.88) from 1999 to 2015. Survival was notably lower for males from the river in 2000, 2006, and 2012, and for the shoreline areas in 2002. From 2001 to 2015, the abundance of males in the lakeshore spawning subpopulation decreased by at least 64 percent and the abundance of females decreased by at least 56 percent. Capture-recapture models suggested that the abundance of both sexes in the river spawning subpopulation of LRS had increased substantially since 2006; increases were mostly due to large estimated recruitment events in 2006 and 2008. We know that the estimates in 2006 are substantially biased in favor of recruitment because of a sampling issue. We are skeptical of the magnitude of recruitment indicated by the 2008 estimates as well because (1) few small individuals that would indicate the presence of new recruits were captured in that year, and (2) recapture probabilities in recruitment models based on just physical recaptures of fish were lower than desired for robust inferences from capture-recapture models. If we assume instead that little or no recruitment occurred for this subpopulation, the abundance of both sexes in the river spawning subpopulation likely has decreased at rates similar to the rates for the lakeshore spawning subpopulation from 2002 to 2015.</p><p class=\"p1\">Shortnose suckers experienced lower and more variable annual survival than either LRS subpopulation. Annual survival of both sexes was relatively low in 2003, 2004, 2010, and 2012. In addition, female survival was low in 1999 and 2000 while male survival was low in 2002. Survival estimate precision in early years of the study; however, are poor. Capture-recapture models and size composition data indicate that recruitment of new individuals into the SNS spawning population was trivial from 2001 to 2005. Models indicate that more than 10 percent of the population was new recruits in a number of more recent years. As a result, capture-recapture modeling suggests that the abundance of adult spawning SNS was relatively stable from 2006 to 2010. We are skeptical of the estimated recruitment in 2006 because of the known sampling issue. We also are skeptical of the estimated recruitment in other recent years because few small individuals that would indicate the presence of new recruits were captured in any of those years, and recapture probabilities in recruitment models were low. The best-case scenario for SNS, based on capture-recapture recruitment modeling, indicates that the abundance of males in the spawning population decreased by 78 percent and the abundance of females decreased by 77 percent from 2001 to 2015. Decreases in abundance for both sexes are likely greater than these estimates indicate.</p><p class=\"p1\">Despite relatively high survival in most years, we conclude that both species have experienced substantial decreases in the abundance of spawning adults because losses from mortality have not been balanced by recruitment of new individuals. Although capture-recapture data indicate substantial recruitment of new individuals into the spawning populations for SNS and river spawning LRS in some years, size data do not corroborate these estimates. As a result, the status of the endangered sucker populations in Upper Klamath Lake remains distressed, especially for SNS. Our monitoring program provides a robust platform for estimating vital population parameters, evaluating the status of the populations, and assessing the effectiveness of conservation and recovery efforts.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181064","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., Janney, E.C., Hayes, B.S., and Harris, A.C., 2018, Status and trends of adult Lost River (<em>Deltistes luxatus</em>) and shortnose (<em>Chasmistes brevirostris</em>) sucker populations in Upper Klamath Lake, Oregon, 2017: U.S. Geological Survey Open-File Report 2018-1064, 31 p., https://doi.org/10.3133/ofr20181064.","productDescription":"iv, 31 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-096959","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":437938,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97K04NO","text":"USGS data release","linkHelpText":"Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2023"},{"id":353417,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1064/coverthb.jpg"},{"id":353418,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1064/ofr20181064.pdf","text":"Report","size":"905 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1064"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.10067749023438,\n              42.21936476344714\n            ],\n            [\n              -121.79992675781249,\n              42.21936476344714\n            ],\n            [\n              -121.79992675781249,\n              42.61981257367216\n            ],\n            [\n              -122.10067749023438,\n              42.61981257367216\n            ],\n            [\n              -122.10067749023438,\n              42.21936476344714\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://wfrc.usgs.gov/\" target=\"blank\" data-mce-href=\"https://wfrc.usgs.gov/\">Western Fisheries Research Center</a><br> U.S. Geological Survey<br> 6505 NE 65th Street<br> Seattle, Washington 98115</p>","tableOfContents":"<ul><li>Executive Summary<br></li><li>Introduction<br></li><li>Methods<br></li><li>Results<br></li><li>Discussion<br></li><li>Acknowledgments<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2018-04-24","noUsgsAuthors":false,"publicationDate":"2018-04-24","publicationStatus":"PW","scienceBaseUri":"5afee6d2e4b0da30c1bfbe64","contributors":{"authors":[{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":733370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janney, Eric C. 0000-0002-0228-2174","orcid":"https://orcid.org/0000-0002-0228-2174","contributorId":83629,"corporation":false,"usgs":true,"family":"Janney","given":"Eric","email":"","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":733371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Brian S. 0000-0001-8229-4070","orcid":"https://orcid.org/0000-0001-8229-4070","contributorId":37022,"corporation":false,"usgs":true,"family":"Hayes","given":"Brian S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":733372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, Alta C. 0000-0002-2123-3028 aharris@usgs.gov","orcid":"https://orcid.org/0000-0002-2123-3028","contributorId":3490,"corporation":false,"usgs":true,"family":"Harris","given":"Alta C.","email":"aharris@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":733373,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196680,"text":"70196680 - 2018 - The role of the upper tidal estuary in wetland blue carbon storage and flux","interactions":[],"lastModifiedDate":"2018-06-12T13:51:35","indexId":"70196680","displayToPublicDate":"2018-04-24T00:00:00","publicationYear":"2018","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":"The role of the upper tidal estuary in wetland blue carbon storage and flux","docAbstract":"<p><span>Carbon (C) standing stocks, C mass balance, and soil C burial in tidal freshwater forested wetlands (TFFW) and TFFW transitioning to low‐salinity marshes along the upper estuary are not typically included in “blue carbon” accounting, but may represent a significant C sink. Results from two salinity transects along the tidal Waccamaw and Savannah rivers of the US Atlantic Coast show total C standing stocks were 321‐1264 Mg C ha</span><sup>‐1</sup><span><span>&nbsp;</span>among all sites, generally shifting to greater soil storage as salinity increased. Carbon mass balance inputs (litterfall, woody growth, herbaceous growth, root growth, surface accumulation) minus C outputs (surface litter and root decomposition, gaseous C) over a period of up to 11 years were 340‐900 g C m</span><sup>‐2</sup><span><span>&nbsp;</span>yr</span><sup>‐1</sup><span>. Soil C burial was variable (7‐337 g C m</span><sup>‐2</sup><span><span>&nbsp;</span>yr</span><sup>‐1</sup><span>), and lateral C export was estimated as C mass balance minus soil C burial as 267‐849 g C m</span><sup>‐2</sup><span>yr</span><sup>‐1</sup><span>. This represents a large amount of C export to support aquatic biogeochemical transformations. Despite reduced C persistence within emergent vegetation, decomposition of organic matter, and higher lateral C export, total C storage increased as forests converted to marsh with salinization. These tidal river wetlands exhibited high N mineralization in salinity‐stressed forested sites and considerable P mineralization in low salinity marshes. Large C standing stocks and rates of C sequestration suggest that TFFW and oligohaline marshes are considerably important globally to coastal C dynamics and in facilitating energy transformations in areas of the world in which they occur.</span></p>","language":"English","publisher":"AGU","doi":"10.1029/2018GB005897","usgsCitation":"Krauss, K.W., Noe, G.B., Duberstein, J., Conner, W.H., Stagg, C.L., Cormier, N., Jones, M.C., Bernhardt, C.E., Lockaby, B.G., From, A.S., Doyle, T.W., Day, R.H., Ensign, S., Pierfelice, K.N., Hupp, C.R., Chow, A.T., and Whitbeck, J., 2018, The role of the upper tidal estuary in wetland blue carbon storage and flux: Global Biogeochemical Cycles, v. 32, no. 5, p. 817-839, https://doi.org/10.1029/2018GB005897.","productDescription":"23 p.","startPage":"817","endPage":"839","ipdsId":"IP-091703","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468813,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gb005897","text":"Publisher Index Page"},{"id":437936,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TM7930","text":"USGS data release","linkHelpText":"Carbon budget assessment of tidal freshwater forested wetland and oligohaline marsh ecosystems along the Waccamaw and Savannah rivers, U.S.A. (2005-2016)"},{"id":437935,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73T9FCJ","text":"USGS data release","linkHelpText":"Organic matter decomposition along coastal wetland landscape gradient from tidal freshwater forested wetland to oligohaline marsh in Southeastern U.S.A. 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,{"id":70196620,"text":"70196620 - 2018 - Assessing roadway contributions to stormwater flows, concentrations, and loads with the StreamStats application","interactions":[],"lastModifiedDate":"2019-03-06T12:06:36","indexId":"70196620","displayToPublicDate":"2018-04-24T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3647,"text":"Transportation Research Record","active":true,"publicationSubtype":{"id":10}},"title":"Assessing roadway contributions to stormwater flows, concentrations, and loads with the StreamStats application","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>The Oregon Department of Transportation (ODOT) and other state departments of transportation need quantitative information about the percentages of different land cover categories above any given stream crossing in the state to assess and address roadway contributions to water-quality impairments and resulting total maximum daily loads. The U.S. Geological Survey, in cooperation with ODOT and the FHWA, added roadway and land cover information to the online StreamStats application to facilitate analysis of stormwater runoff contributions from different land covers. Analysis of 25 delineated basins with drainage areas of about 100 mi2 indicates the diversity of land covers in the Willamette Valley, Oregon. On average, agricultural, developed, and undeveloped land covers comprise 15%, 2.3%, and 82% of these basin areas. On average, these basins contained about 10 mi of state highways and 222 mi of non-state roads. The Stochastic Empirical Loading and Dilution Model was used with available water-quality data to simulate long-term yields of total phosphorus from highways, non-highway roadways, and agricultural, developed, and undeveloped areas. These yields were applied to land cover areas obtained from StreamStats for the Willamette River above Wilsonville, Oregon. This analysis indicated that highway yields were larger than yields from other land covers because highway runoff concentrations were higher than other land covers and the highway is fully impervious. However, the total highway area was a fraction of the other land covers. Accordingly, highway runoff mitigation measures can be effective for managing water quality locally, they may have limited effect on achieving basin-wide stormwater reduction goals.</p></div></div>","language":"English","publisher":"SAGE Journals","doi":"10.1177/0361198118758679","usgsCitation":"Stonewall, A., Granato, G., and Haluska, T., 2018, Assessing roadway contributions to stormwater flows, concentrations, and loads with the StreamStats application: Transportation Research Record, v. 2672, no. 39, p. 79-87, https://doi.org/10.1177/0361198118758679.","productDescription":"9 p.","startPage":"79","endPage":"87","ipdsId":"IP-089296","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":353679,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2672","issue":"39","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-11","publicationStatus":"PW","scienceBaseUri":"5afee6d2e4b0da30c1bfbe62","contributors":{"authors":[{"text":"Stonewall, Adam 0000-0002-3277-8736 stonewal@usgs.gov","orcid":"https://orcid.org/0000-0002-3277-8736","contributorId":139097,"corporation":false,"usgs":true,"family":"Stonewall","given":"Adam","email":"stonewal@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733788,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":140491,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","email":"ggranato@usgs.gov","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":false,"id":733789,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haluska, Tana 0000-0001-6307-4769 thaluska@usgs.gov","orcid":"https://orcid.org/0000-0001-6307-4769","contributorId":1708,"corporation":false,"usgs":true,"family":"Haluska","given":"Tana","email":"thaluska@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733790,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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