Over the last several decades, many lakes globally have increased in dissolved organic carbon (DOC), calling into question how lake functions may respond to increasing DOC. Unfortunately, our basis for making predictions is limited to spatial surveys, modeling, and laboratory experiments, which may not accurately capture important whole-ecosystem processes. In this article, we present data on metabolic and physiochemical responses of a multiyear experimental whole-lake increase in DOC concentration. Unexpectedly, we observed an increase in pelagic gross primary production, likely due to a small increase in phosphorus as well as a surprising lack of change in epilimnetic light climate. We also speculate on the importance of lake size modifying the relationship between light climate and elevated DOC. A larger increase in ecosystem respiration resulted in an increased heterotrophy for the treatment basin. The magnitude of the increase in heterotrophy was extremely close to the excess DOC load to the treatment basin, indicating that changes in heterotrophy may be predictable if allochthonous carbon loads are well-constrained. Elevated DOC concentration also reduced thermocline and mixed layer depth and reduced whole-lake temperature. Results from this experiment were quantitatively different, and sometimes even in the opposite direction, from expectations based on cross-system surveys and bottle experiments, emphasizing the importance of whole-ecosystem experiments in understanding ecosystem response to environmental change.
","language":"English","publisher":"American Society of Limnology and Oceanography","publisherLocation":"Waco, TX","doi":"10.1002/lno.10248","usgsCitation":"Zwart, J., Craig, N., Kelly, P., Sebestyen, S.D., Solomon, C.T., Weidel, B., and Jones, S., 2016, Metabolic and physiochemical responses to a whole-lake experimental increase in dissolved organic carbon in a north-temperate lake: Limnology and Oceanography, v. 61, no. 2, p. 723-734, https://doi.org/10.1002/lno.10248.","startPage":"723","endPage":"734","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068470","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":471400,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://figshare.com/articles/journal_contribution/Metabolic_and_physiochemical_responses_to_a_whole-lake_experimental_increase_in_dissolved_organic_carbon_in_a_north-temperate_lake/24733230","text":"Publisher Index Page"},{"id":325984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-21","publicationStatus":"PW","scienceBaseUri":"57a1c430e4b006cb45552c2b","contributors":{"authors":[{"text":"Zwart, Jacob A.","contributorId":173345,"corporation":false,"usgs":false,"family":"Zwart","given":"Jacob A.","affiliations":[{"id":16905,"text":"University of Notre Dame, Dept. of Biological Sciences, Notre Dame, IN, 46556, USA","active":true,"usgs":false}],"preferred":false,"id":644342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Craig, Nicola","contributorId":150803,"corporation":false,"usgs":false,"family":"Craig","given":"Nicola","email":"","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":644343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelly, Patrick T.","contributorId":69059,"corporation":false,"usgs":true,"family":"Kelly","given":"Patrick T.","affiliations":[],"preferred":false,"id":644344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sebestyen, Stephen D.","contributorId":107562,"corporation":false,"usgs":true,"family":"Sebestyen","given":"Stephen","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":644347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Solomon, Christopher T.","contributorId":34014,"corporation":false,"usgs":false,"family":"Solomon","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":644345,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":644341,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Stuart E.","contributorId":22222,"corporation":false,"usgs":false,"family":"Jones","given":"Stuart E.","affiliations":[{"id":6966,"text":"Department of Biological Sciences, University of Notre Dame","active":true,"usgs":false}],"preferred":false,"id":644346,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70156787,"text":"70156787 - 2016 - Multi-scale predictions of massive conifer mortality due to chronic temperature rise","interactions":[],"lastModifiedDate":"2018-01-12T15:44:21","indexId":"70156787","displayToPublicDate":"2015-12-21T16:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale predictions of massive conifer mortality due to chronic temperature rise","docAbstract":"Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April–August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted ≥50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.
","language":"English","publisher":"Nature Publishing Group","publisherLocation":"London, UK","doi":"10.1038/nclimate2873","usgsCitation":"McDowell, N., Williams, A., Xu, C., Pockman, W., Dickman, L., Sevanto, S., Pangle, R., Limousin, J., Plaut, J., Mackay, D., Ogee, J., Domec, J., Allen, C.D., Fisher, R.A., Jiang, X., Muss, J., Breshears, D., Rauscher, S.A., and Koven, C., 2016, Multi-scale predictions of massive conifer mortality due to chronic temperature rise: Nature Climate Change, v. 6, p. 295-300, https://doi.org/10.1038/nclimate2873.","productDescription":"6 p.","startPage":"295","endPage":"300","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058464","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471401,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1492529","text":"External Repository"},{"id":312936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-21","publicationStatus":"PW","scienceBaseUri":"56826b46e4b0a04ef4925b86","contributors":{"authors":[{"text":"McDowell, Nathan G.","contributorId":9176,"corporation":false,"usgs":true,"family":"McDowell","given":"Nathan G.","affiliations":[],"preferred":false,"id":583294,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, A.P.","contributorId":70226,"corporation":false,"usgs":true,"family":"Williams","given":"A.P.","email":"","affiliations":[],"preferred":false,"id":583295,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xu, C.","contributorId":9781,"corporation":false,"usgs":true,"family":"Xu","given":"C.","email":"","affiliations":[],"preferred":false,"id":583296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pockman, W. 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A detailed reconstruction of this time interval is critical for understanding the nature of biotic and environmental changes preceding the end-Cretaceous Mass Extinction event and for deciphering the likely extinction mechanism (i.e., bolide impact versus volcanism). Eight sections encompassing the K/Pg succession across the Mississippi Embayment were analyzed using biostratigraphic sampling of ammonites, dinoflagellates, and nannofossils. An upper Maastrichtian ammonite zonation is proposed as follows, from oldest to youngest:Discoscaphites conradi Zone, D. minardi Zone, and D. iris Zone. Our study documents that the ammonite zonation established in the Atlantic Coastal Plain (ACP) extends to the GCP. This zonation is integrated with nannofossil and dinoflagellate biostratigraphy to provide a framework to more accurately determine the age relationships in this region. We demonstrate that ammonites and dinoflagellates are more reliable stratigraphic indicators in this area than nannofossils because age-diagnostic nannofossils are not consistently present within the upper Maastrichtian in the GCP. This biostratigraphic framework has the potential to become a useful tool for correlation of strata both within the GCP and between the GCP, Western Interior, and ACP. The presence of the uppermost Maastrichtian ammonite D. iris, calcareous nannofossil Micula prinsii, and dinoflagellates Palynodinium grallator and Disphaerogena carposphaeropsis suggests that the K/Pg succession in the GCP is nearly complete. Consequently, the GCP is an excellent setting for investigating fine scale temporal changes across the K/Pg boundary and ultimately elucidating the mechanisms causing extinction.
","language":"English","publisher":"Academic Press","doi":"10.1016/j.cretres.2015.11.010","usgsCitation":"Larina, E., Garb, M., Landman, N.H., Dastas, N., Thibault, N., Edwards, L.E., Phillips, G., Rovelli, R., Myers, C., and Naujokaityte, J., 2016, Upper Maastrichtian ammonite biostratigraphy of the Gulf Coastal Plain (Mississippi Embayment, southern USA): Cretaceous Research, v. 60, p. 128-151, https://doi.org/10.1016/j.cretres.2015.11.010.","productDescription":"24 p.","startPage":"128","endPage":"151","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070686","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":316738,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Arkansas, Missouri, Mississippi","county":"Chickasaw County, Hot Springs County, Oktibbeha County, Stoddard County, Summer County, Tippah County, Union County, Wilcox County","otherGeospatial":"Gulf Coastal Plain, Mississippi Embayment","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.8671875,\n 31.653381399664\n ],\n [\n -93.8671875,\n 37.666429212090605\n ],\n [\n -86.37451171875,\n 37.666429212090605\n ],\n [\n -86.37451171875,\n 31.653381399664\n ],\n [\n -93.8671875,\n 31.653381399664\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"60","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56bb1bd2e4b08d617f654e81","contributors":{"authors":[{"text":"Larina, Ekaterina","contributorId":156370,"corporation":false,"usgs":false,"family":"Larina","given":"Ekaterina","email":"","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":597690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garb, Matthew P.","contributorId":6355,"corporation":false,"usgs":true,"family":"Garb","given":"Matthew P.","affiliations":[],"preferred":false,"id":597689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landman, Neil H.","contributorId":95779,"corporation":false,"usgs":true,"family":"Landman","given":"Neil","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":597691,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dastas, Natalie","contributorId":156371,"corporation":false,"usgs":false,"family":"Dastas","given":"Natalie","email":"","affiliations":[{"id":20331,"text":"Brooklyn College","active":true,"usgs":false}],"preferred":false,"id":597692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thibault, Nicolas","contributorId":156372,"corporation":false,"usgs":false,"family":"Thibault","given":"Nicolas","email":"","affiliations":[{"id":12672,"text":"University of Copenhagen","active":true,"usgs":false}],"preferred":false,"id":597693,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Edwards, Lucy E. 0000-0003-4075-3317 leedward@usgs.gov","orcid":"https://orcid.org/0000-0003-4075-3317","contributorId":2647,"corporation":false,"usgs":true,"family":"Edwards","given":"Lucy","email":"leedward@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":597688,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Phillips, George","contributorId":156373,"corporation":false,"usgs":false,"family":"Phillips","given":"George","email":"","affiliations":[{"id":20332,"text":"Museum of Natural Science","active":true,"usgs":false}],"preferred":false,"id":597694,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rovelli, Remy","contributorId":99447,"corporation":false,"usgs":true,"family":"Rovelli","given":"Remy","affiliations":[],"preferred":false,"id":597695,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Myers, Corinne","contributorId":156374,"corporation":false,"usgs":false,"family":"Myers","given":"Corinne","email":"","affiliations":[{"id":20333,"text":"The University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":597696,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Naujokaityte, Jone","contributorId":156375,"corporation":false,"usgs":false,"family":"Naujokaityte","given":"Jone","email":"","affiliations":[{"id":20331,"text":"Brooklyn College","active":true,"usgs":false}],"preferred":false,"id":597697,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70160659,"text":"70160659 - 2016 - Soil amplification with a strong impedance contrast: Boston, Massachusetts","interactions":[],"lastModifiedDate":"2016-06-13T10:49:56","indexId":"70160659","displayToPublicDate":"2015-12-19T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1517,"text":"Engineering Geology","active":true,"publicationSubtype":{"id":10}},"title":"Soil amplification with a strong impedance contrast: Boston, Massachusetts","docAbstract":"In this study, we evaluate the effect of strong sediment/bedrock impedance contrasts on soil amplification in Boston, Massachusetts, for typical sites along the Charles and Mystic Rivers. These sites can be characterized by artificial fill overlying marine sediments overlying glacial till and bedrock, where the depth to bedrock ranges from 20 to 80 m. The marine sediments generally consist of organic silts, sand, and Boston Blue Clay. We chose these sites because they represent typical foundation conditions in the city of Boston, and the soil conditions are similar to other high impedance contrast environments. The sediment/bedrock interface in this region results in an impedance ratio on the order of ten, which in turn results in a significant amplification of the ground motion. Using stratigraphic information derived from numerous boreholes across the region paired with geologic and geomorphologic constraints, we develop a depth-to-bedrock model for the greater Boston region. Using shear-wave velocity profiles from 30 locations, we develop average velocity profiles for sites mapped as artificial fill, glaciofluvial deposits, and bedrock. By pairing the depth-to-bedrock model with the surficial geology and the average shear-wave velocity profiles, we can predict soil amplification in Boston. We compare linear and equivalent-linear site response predictions for a soil layer of varying thickness over bedrock, and assess the effects of varying the bedrock shear-wave velocity (VSb) and quality factor (Q). In a moderate seismicity region like Boston, many earthquakes will result in ground motions that can be modeled with linear site response methods. We also assess the effect of bedrock depth on soil amplification for a generic soil profile in artificial fill, using both linear and equivalent-linear site response models. Finally, we assess the accuracy of the model results by comparing the predicted (linear site response) and observed site response at the Northeastern University (NEU) vertical seismometer array during the 2011 M 5.8 Mineral, Virginia, earthquake. Site response at the NEU vertical array results in amplification on the order of 10 times at a period between 0.7-0.8 s. The results from this study provide evidence that the mean short-period and mean intermediate-period amplification used in design codes (i.e., from the Fa and Fv site coefficients) may underpredict soil amplification in strong impedance contrast environments such as Boston.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.enggeo.2015.12.016","usgsCitation":"Baise, L.G., Kaklamanos, J., Berry, B.M., and Thompson, E.M., 2016, Soil amplification with a strong impedance contrast: Boston, Massachusetts: Engineering Geology, v. 202, 13 p., https://doi.org/10.1016/j.enggeo.2015.12.016.","productDescription":"13 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071386","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471402,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.enggeo.2015.12.016","text":"Publisher Index Page"},{"id":313151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Boston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.03193283081055,\n 42.38644427600168\n ],\n [\n -71.14574432373045,\n 42.43828063778991\n ],\n [\n -71.1665153503418,\n 42.42561066758352\n ],\n [\n -71.18385314941406,\n 42.36666166373274\n ],\n [\n -71.1697769165039,\n 42.345984712768576\n ],\n [\n -71.06986999511719,\n 42.3477609142747\n ],\n [\n -71.03382110595703,\n 42.3853031408436\n ],\n [\n -71.03193283081055,\n 42.38644427600168\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"202","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56865fc9e4b0e7594ee74cd5","chorus":{"doi":"10.1016/j.enggeo.2015.12.016","url":"http://dx.doi.org/10.1016/j.enggeo.2015.12.016","publisher":"Elsevier BV","authors":"Baise Laurie G., Kaklamanos James, Berry Bradford M., Thompson Eric M.","journalName":"Engineering Geology","publicationDate":"3/2016"},"contributors":{"authors":[{"text":"Baise, Laurie G.","contributorId":127395,"corporation":false,"usgs":false,"family":"Baise","given":"Laurie","email":"","middleInitial":"G.","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":583496,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaklamanos, James","contributorId":35053,"corporation":false,"usgs":true,"family":"Kaklamanos","given":"James","affiliations":[],"preferred":false,"id":583497,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berry, Bradford M","contributorId":150894,"corporation":false,"usgs":false,"family":"Berry","given":"Bradford","email":"","middleInitial":"M","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":583498,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":146592,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":583495,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160356,"text":"70160356 - 2016 - A guide for establishing restoration goals for contaminated ecosystems","interactions":[],"lastModifiedDate":"2016-12-14T12:40:08","indexId":"70160356","displayToPublicDate":"2015-12-18T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"A guide for establishing restoration goals for contaminated ecosystems","docAbstract":"As natural resources become increasingly limited, the value of restoring contaminated sites, both terrestrial and aquatic, becomes increasingly apparent. Traditionally, goals for remediation have been set before any consideration of goals for ecological restoration. The goals for remediation have focused on removing or limiting contamination whereas restoration goals have targeted the ultimate end use. Here, we present a framework for developing a comprehensive set of achievable goals for ecological restoration of contaminated sites to be used in concert with determining goals for remediation. This framework was developed during a Society of Environmental Toxicology and Chemistry (SETAC) and Society of Ecological Restoration (SER) cosponsored workshop that brought together experts from multiple countries. Although most members were from North America, this framework is designed for use internationally. We discuss the integration of establishing goals for both contaminant remediation and overall restoration, and the need to include both the restoration of ecological and socio-cultural-economic value in the context of contaminated sites. Although recognizing that in some countries there may be regulatory issues associated with contaminants and clean up, landscape setting and social drivers can inform the restoration goals. We provide a decision tree support tool to guide the establishment of restoration goals for contaminated ecosystems. The overall intent of this decision tree is to provide a framework for goal setting and to identify outcomes achievable given the contamination present at a site.
","language":"English","publisher":"SETAC","publisherLocation":"Pensacola, FL","doi":"10.1002/ieam.1709","usgsCitation":"Wagner, A.M., Larson, D.L., DalSoglio, J.A., Harris, J.A., Labus, P., Rosi-Marshall, E.J., and Skarbis, K.E., 2016, A guide for establishing restoration goals for contaminated ecosystems: Integrated Environmental Assessment and Management, v. 12, no. 2, p. 264-272, https://doi.org/10.1002/ieam.1709.","productDescription":"9 p.","startPage":"264","endPage":"272","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062120","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471403,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ieam.1709","text":"Publisher Index Page"},{"id":312546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-01","publicationStatus":"PW","scienceBaseUri":"56752e2de4b0da412f4f8bb5","contributors":{"authors":[{"text":"Wagner, Anne M.","contributorId":150713,"corporation":false,"usgs":false,"family":"Wagner","given":"Anne","email":"","middleInitial":"M.","affiliations":[{"id":18075,"text":"Chevron Energy Technology Company","active":true,"usgs":false}],"preferred":false,"id":582739,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":2120,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":582738,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DalSoglio, Julie A.","contributorId":150714,"corporation":false,"usgs":false,"family":"DalSoglio","given":"Julie","email":"","middleInitial":"A.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":582740,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, James A.","contributorId":150715,"corporation":false,"usgs":false,"family":"Harris","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":18076,"text":"Cranfield University, Bedfordshire, U.K","active":true,"usgs":false}],"preferred":false,"id":582741,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Labus, Paul","contributorId":35266,"corporation":false,"usgs":true,"family":"Labus","given":"Paul","email":"","affiliations":[],"preferred":false,"id":582742,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosi-Marshall, Emma J.","contributorId":17722,"corporation":false,"usgs":true,"family":"Rosi-Marshall","given":"Emma","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":582743,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Skarbis, Krisin E.","contributorId":150716,"corporation":false,"usgs":false,"family":"Skarbis","given":"Krisin","email":"","middleInitial":"E.","affiliations":[{"id":7188,"text":"Cary Institute of Ecosystem Studies, Millbrook, NY, USA","active":true,"usgs":false}],"preferred":false,"id":582744,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70160330,"text":"70160330 - 2016 - Structure and spatial patterns of macrobenthic community in Tai Lake, a large shallow lake, China","interactions":[],"lastModifiedDate":"2015-12-17T14:23:38","indexId":"70160330","displayToPublicDate":"2015-12-17T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Structure and spatial patterns of macrobenthic community in Tai Lake, a large shallow lake, China","docAbstract":"Tai Lake (Chinese: Taihu), the third-largest freshwater lake in China, suffers from harmful cyanobacteria blooms that are caused by economic development and population growth near the lake. Several studies have focused on phytoplankton in Tai Lake after a drinking water crisis in 2007; however, these studies primarily focused on microcystin bioaccumulation and toxicity to individual species without examining the effects of microcystin on macrobenthic community diversity. In this study, we conducted a survey of the lake to examine the effects of microcystine and other pollutants on marcobenthic community diversity. A totally of forty-nine species of macroinvertebrates were found in Tai Lake. Limnodrilus hoffmeisteri and Corbicula fluminea were the most abundant species. Cluster-analysis and one-way analysis of similarity (ANOSIM) identified three significantly different macrobenthic communities among the sample sites. More specifically, sites in the eastern bays, where aquatic macrophytes were abundant, had the highest diversity of macrobenthic communities, which were dominated by Bellamya aeruginosa, Bellamya purificata, L. hoffmeisteri, and Alocinma longicornis. Sites in Zhushan Bay contained relatively diverse communities, mainly composed of L. hoffmeisteri, C. fluminea, L. claparederanus, R. sinicus, and Cythura sp. Sites in the western region, Meiliang Bay and Wuli Bay had the lowest diversity, mainly composed ofL. hoffmeisteri, C. fluminea, Branchiura sowerbyi, and Rhyacodrilus sinicus. In addition, the relationships between macrobenthic metrics (Shannon–Wiener, Margalef, and Pielou) and environmental variables showed that community structure and spatial patterns of macrobenthos in Tai Lake were significantly influenced by chemical oxygen demand (CODCr), biochemical oxygen demand (BOD5), lead (Pb), and microcystin-LR (L for leucine and R for arginine). Our findings provide critical information that could help managers and policymakers assess and modify ecological restoration practices.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2015.08.043","usgsCitation":"Li, D., Erickson, R.A., Song Tang, Li, X., Niu, Z., Wang, X., Liu, H., and Yu, H., 2016, Structure and spatial patterns of macrobenthic community in Tai Lake, a large shallow lake, China: Ecological Indicators, v. 61, no. 2, p. 170-187, https://doi.org/10.1016/j.ecolind.2015.08.043.","productDescription":"18 p.","startPage":"170","endPage":"187","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062777","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":312468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Tai Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 119.89105224609375,\n 30.935212690426727\n ],\n [\n 119.89105224609375,\n 31.54460103811182\n ],\n [\n 120.59280395507812,\n 31.54460103811182\n ],\n [\n 120.59280395507812,\n 30.935212690426727\n ],\n [\n 119.89105224609375,\n 30.935212690426727\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"61","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5673dcb4e4b0da412f4f8201","contributors":{"authors":[{"text":"Li, Di","contributorId":150650,"corporation":false,"usgs":false,"family":"Li","given":"Di","email":"","affiliations":[{"id":18059,"text":"State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":582573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":582572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Song Tang","contributorId":150651,"corporation":false,"usgs":false,"family":"Song Tang","affiliations":[{"id":18060,"text":"School of Environment and Sustainability, University of Saskatchewan, Canada","active":true,"usgs":false}],"preferred":false,"id":582574,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Li, Xuwen","contributorId":150652,"corporation":false,"usgs":false,"family":"Li","given":"Xuwen","email":"","affiliations":[{"id":18061,"text":"Jiangsu Environmental Monitoring Center, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":582575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Niu, Zhichun","contributorId":150653,"corporation":false,"usgs":false,"family":"Niu","given":"Zhichun","email":"","affiliations":[{"id":18061,"text":"Jiangsu Environmental Monitoring Center, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":582576,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Xia","contributorId":150654,"corporation":false,"usgs":false,"family":"Wang","given":"Xia","email":"","affiliations":[{"id":18061,"text":"Jiangsu Environmental Monitoring Center, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":582577,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liu, Hongling","contributorId":150655,"corporation":false,"usgs":false,"family":"Liu","given":"Hongling","email":"","affiliations":[{"id":18059,"text":"State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":582578,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yu, Hongxia","contributorId":150656,"corporation":false,"usgs":false,"family":"Yu","given":"Hongxia","email":"","affiliations":[{"id":18059,"text":"State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":582579,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70160337,"text":"70160337 - 2016 - Spatial capture-recapture models allowing Markovian transience or dispersal","interactions":[],"lastModifiedDate":"2016-01-11T11:10:49","indexId":"70160337","displayToPublicDate":"2015-12-17T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3103,"text":"Population Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Spatial capture-recapture models allowing Markovian transience or dispersal","docAbstract":"Spatial capture–recapture (SCR) models are a relatively recent development in quantitative ecology, and they are becoming widely used to model density in studies of animal populations using camera traps, DNA sampling and other methods which produce spatially explicit individual encounter information. One of the core assumptions of SCR models is that individuals possess home ranges that are spatially stationary during the sampling period. For many species, this assumption is unlikely to be met and, even for species that are typically territorial, individuals may disperse or exhibit transience at some life stages. In this paper we first conduct a simulation study to evaluate the robustness of estimators of density under ordinary SCR models when dispersal or transience is present in the population. Then, using both simulated and real data, we demonstrate that such models can easily be described in the BUGS language providing a practical framework for their analysis, which allows us to evaluate movement dynamics of species using capture–recapture data. We find that while estimators of density are extremely robust, even to pathological levels of movement (e.g., complete transience), the estimator of the spatial scale parameter of the encounter probability model is confounded with the dispersal/transience scale parameter. Thus, use of ordinary SCR models to make inferences about density is feasible, but interpretation of SCR model parameters in relation to movement should be avoided. Instead, when movement dynamics are of interest, such dynamics should be parameterized explicitly in the model.
","language":"English","publisher":"Springer","doi":"10.1007/s10144-015-0524-z","usgsCitation":"Royle, J., Fuller, A.K., and Sutherland, C., 2016, Spatial capture-recapture models allowing Markovian transience or dispersal: Population Ecology, v. 58, no. 1, p. 53-62, https://doi.org/10.1007/s10144-015-0524-z.","productDescription":"10 p.","startPage":"53","endPage":"62","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069359","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471404,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1007/s10144-015-0524-z","text":"External Repository"},{"id":312465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-21","publicationStatus":"PW","scienceBaseUri":"5673dcb3e4b0da412f4f81fd","contributors":{"authors":[{"text":"Royle, J. Andrew aroyle@usgs.gov","contributorId":138860,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":582604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":582623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sutherland, Chris","contributorId":150670,"corporation":false,"usgs":false,"family":"Sutherland","given":"Chris","affiliations":[],"preferred":false,"id":582624,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159869,"text":"ofr20151230 - 2016 - Water use in Georgia by county for 2010 and water-use trends, 1985–2010","interactions":[],"lastModifiedDate":"2016-12-08T17:04:41","indexId":"ofr20151230","displayToPublicDate":"2015-12-16T13:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1230","title":"Water use in Georgia by county for 2010 and water-use trends, 1985–2010","docAbstract":"Water use and water withdrawals and returns in 2010 are estimated for each major river basin, principal aquifer, water-planning region, and county in Georgia using data obtained from various Federal and State agencies and local sources. Offstream water use in 2010 is estimated for the categories of public supply, domestic, commercial, industrial, mining, irrigation, livestock, aquaculture, and thermoelectric power. Water-use trends for 1985 to 2010 are also shown.
\nThe period between 2007 and 2010 was a challenging time economically and climatologically in Georgia. During that period, the United States was in the midst of a major recession, resulting in decreases in the manufacturing and construction industries and large increases in unemployment. During 2007, 2008, and the latter half of 2010, precipitation in Georgia was substantially below the 30-year norm.
\nAccording to the 2010 Census of Population and Housing, nearly 9.7 million people lived in Georgia. The water for about 85 percent of that population was provided by public water suppliers. Estimated total water withdrawals from ground-water and surface-water sources were about 4,670 million gallons per day (Mgal/d) in 2010, about a 15-percent reduction from 2005 (5,471 Mgal/d). In 2010, thermoelectric-power facilities (2,046 Mgal/d) and public-supply uses (1,121 Mgal/d) accounted for 68 percent of all water withdrawn in Georgia. Surface-water withdrawals were greatest for thermoelectric-power generation (2,043 Mgal/d), whereas irrigation used the largest amount of groundwater (599 Mgal/d). Surface water provided 78 percent of the 1,121 Mgal/day withdrawn for public supply in 2010. Typically, counties in northern Georgia withdraw a larger percentage of water from surface water than groundwater sources; whereas, counties in the southern part of the State withdraw more water from groundwater sources.
\nHistorically, water withdrawals in Georgia were highest in 1980 (6,725 Mgal/d). By 1990, water use had decreased by 20 percent to 5,353 Mgal/d, but increased to 6,487 Mgal/d in 2000. By 2005, water use had decreased to an estimated 5,471 Mgal/d, and declined further to 4,670 Mgal/d in 2010—a 30-percent decrease since 1980. This decline was evident across all water-use categories, but was greatest for surface-water withdrawals by thermoelectric-power facilities. The estimated total water use per capita in 1985 (total withdrawals for all categories divided by total population) was about 850 gallons per day (gal/d), steadily decreasing to about 798 gal/d in 2000, and decreasing further to 460 gal/d in 2010. Although water use declined among all use categories during that 10-year period, most of the decline in per capita water use was caused by the large decrease in water used for thermoelectric-power generation.
\nThroughout 1985–2010 water withdrawn for thermoelectric-power generation has constituted the largest volume of offstream water use in Georgia. Total withdrawals for thermoelectric-power generation declined about 37 percent between 2000 and 2010, mostly due to the decommissioning of power plants in the State. Also during this period, several power plants were shut down and re-tooled to use natural gas-powered generators; thus, water withdrawals for cooling were substantially reduced.
\nThe decline in water withdrawals and use between 2005 and 2010 can probably be attributed to several factors working together during this period: (1) water conservation laws and policies along with advances in water-conservation technology; (2) the onset of a major recession in 2007; and (3) below average rainfall in 2007, 2008, and the latter half of 2010. Because of these factors, water withdrawn by public suppliers decreased by 4.8 percent (despite a nearly 11-percent increase in population served) and per capita use decreased by 19 percent between 2005 and 2010.
\nAbout 2,225 Mgal/d of water was returned to Georgia streams and lakes in 2010 under the National Pollutant Discharge Elimination System program administered by the Georgia Environmental Protection Division. This amount is about 48 percent of the total water withdrawn from all sources in 2010. Water returns declined 39 percent between 1995 and 2010, mirroring the decline in water withdrawals during that period. In addition, land applications of treated wastewater increased steadily between 1995 and 2010.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151230","collaboration":"Prepared in cooperation with the Georgia Department of Natural Resources, Environmental Protection Division","usgsCitation":"Lawrence, S.J., 2016, Water use in Georgia by county for 2010 and water-use trends, 1985–2010 (ver. 1.1, January 2016): U.S. Geological Survey Open-File Report 2015–1230, 206 p., https://dx.doi.org/10.3133/ofr20151230.","productDescription":"viii, 206 p.","numberOfPages":"218","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2010-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-037442","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":312330,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1230/ofr20151230.pdf","text":"Report","size":"19.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1230"},{"id":312329,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1230/coverthbn.jpg"},{"id":314402,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2015/1230/verHist.txt","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2015-1230"}],"country":"United States","state":"Georgia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.594482421875,\n 34.994003757575776\n ],\n [\n -84.990234375,\n 32.222095840502334\n ],\n [\n -85.166015625,\n 31.83089906339438\n ],\n [\n -85.05615234375,\n 31.541089879585808\n ],\n [\n -85.1220703125,\n 31.21280145833882\n ],\n [\n -84.91333007812499,\n 30.72294882477251\n ],\n [\n -82.24365234375,\n 30.5717205651999\n ],\n [\n -82.188720703125,\n 30.363396239603716\n ],\n [\n -82.0458984375,\n 30.334953881988564\n ],\n [\n -82.034912109375,\n 30.732392734006083\n ],\n [\n -81.89208984375,\n 30.86451022625836\n ],\n [\n -81.45263671875,\n 30.62845887475364\n ],\n [\n -81.10107421874999,\n 31.690781806136822\n ],\n [\n -80.9033203125,\n 31.942839972853083\n ],\n [\n -81.27685546875,\n 32.55607364492029\n ],\n [\n -81.5625,\n 33.08233672856376\n ],\n [\n -81.9580078125,\n 33.46810795527896\n ],\n [\n -82.518310546875,\n 33.93424531117312\n ],\n [\n -82.880859375,\n 34.4793919710481\n ],\n [\n -83.045654296875,\n 34.470335121217495\n ],\n [\n -83.375244140625,\n 34.732584206123626\n ],\n [\n -83.08959960937499,\n 35.0120020431607\n ],\n [\n -85.594482421875,\n 34.994003757575776\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted December 16, 2015; Version 1.1: January 15, 2016","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Many tropical islands have limited water resources with historically increasing demand, all potentially affected by a changing climate. The effects of climate change on island hydrology are difficult to model due to steep local precipitation gradients and sparse data. This work uses 10 statistically downscaled general circulation models (GCMs) under two greenhouse gas emission scenarios to evaluate the uncertainty propagated from GCMs in projecting the effects of climate change on water resources in a tropical island system. The assessment is conducted using a previously configured hydrologic model, the Precipitation Runoff Modelling System (PRMS) for Puerto Rico. Projected climate data and their modelled hydrologic variables versus historical measurements and their modelled hydrologic variables are found to have empirical distribution functions that are statistically different with less than 1 year of daily data aggregation. Thus, only annual averages of the projected hydrologic variables are employed as completely bias‐corrected model outputs. The magnitude of the projected total flow decreases in the four regions covering Puerto Rico, but with a large range of uncertainty depending on the makeup of the GCM ensemble. The multi‐model mean projected total flow decreases by 49–88% of historical amounts from the 1960s to the 2090s for the high emissions scenarios and by 39–79% for the low emissions scenarios. Subsurface flow contributions decreased the least and groundwater flow contributions decreased the most across the island. At locations critical to water supply for human use, projected streamflow is shown to decrease substantially below projected withdrawals by 2099.
","language":"English","publisher":"Royal Meteorological Society","doi":"10.1002/joc.4560","usgsCitation":"Van Beusekom, A.E., Gould, W.A., Terando, A.J., and Collazo, J.A., 2016, Climate change and water resources in a tropical island system: Propagation of uncertainty from statistically downscaled climate models to hydrologic models: International Journal of Climatology, v. 36, no. 9, p. 3370-3383, https://doi.org/10.1002/joc.4560.","productDescription":"14 p.","startPage":"3370","endPage":"3383","ipdsId":"IP-062479","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":369912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.4066162109375,\n 17.814071002942764\n ],\n [\n -65.56915283203125,\n 17.814071002942764\n ],\n [\n -65.56915283203125,\n 18.609807415471877\n ],\n [\n -67.4066162109375,\n 18.609807415471877\n ],\n [\n -67.4066162109375,\n 17.814071002942764\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"9","noUsgsAuthors":false,"publicationDate":"2015-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Beusekom, Ashley E. 0000-0002-6996-978X beusekom@usgs.gov","orcid":"https://orcid.org/0000-0002-6996-978X","contributorId":3992,"corporation":false,"usgs":true,"family":"Van Beusekom","given":"Ashley","email":"beusekom@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":776637,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gould, William A.","contributorId":103535,"corporation":false,"usgs":true,"family":"Gould","given":"William","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":776638,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terando, Adam J. 0000-0002-9280-043X aterando@usgs.gov","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":173447,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","email":"aterando@usgs.gov","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":776639,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collazo, Jaime A. 0000-0002-1816-7744","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":217287,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime","email":"","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":776640,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160380,"text":"70160380 - 2016 - Acute and chronic toxicity of sodium sulfate to four freshwater organisms in water-only exposures","interactions":[],"lastModifiedDate":"2016-10-17T10:36:14","indexId":"70160380","displayToPublicDate":"2015-12-15T12:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Acute and chronic toxicity of sodium sulfate to four freshwater organisms in water-only exposures","docAbstract":"The acute and chronic toxicity of sulfate (tested as sodium sulfate) was determined in diluted well water (hardness of 100 mg/L and pH 8.2) with a cladoceran (Ceriodaphnia dubia; 2-d and 7-d exposures), a midge (Chironomus dilutus; 4-d and 41-d exposures), a unionid mussel (pink mucket, Lampsilis abrupta; 4-d and 28-d exposures), and a fish (fathead minnow, Pimephales promelas; 4-d and 34-d exposures). Among the 4 species, the cladoceran and mussel were acutely more sensitive to sulfate than the midge and fathead minnow, whereas the fathead minnow was chronically more sensitive than the other 3 species. Acute-to-chronic ratios ranged from 2.34 to 5.68 for the 3 invertebrates but were as high as 12.69 for the fish. The fathead minnow was highly sensitive to sulfate during the transitional period from embryo development to hatching in the diluted well water, and thus, additional short-term (7- to 14-d) sulfate toxicity tests were conducted starting with embryonic fathead minnow in test waters with different ionic compositions at a water hardness of 100 mg/L. Increasing chloride in test water from 10 mg Cl/L to 25 mg Cl/L did not influence sulfate toxicity to the fish, whereas increasing potassium in test water from 1mg K/L to 3mg K/L substantially reduced the toxicity of sulfate. The results indicate that both acute and chronic sulfate toxicity data, and the influence of potassium on sulfate toxicity to fish embryos, need to be considered when environmental guidance values for sulfate are developed or refined.
","language":"English","publisher":"Elsevier","doi":"10.1002/etc.3148","usgsCitation":"Wang, N., Consbrock, R.A., Ingersoll, C.G., Hardesty, D., Brumbaugh, W.G., Hammer, E.J., Bauer, C.R., and Mount, D.R., 2016, Acute and chronic toxicity of sodium sulfate to four freshwater organisms in water-only exposures: Environmental Toxicology and Chemistry, v. 35, no. 1, p. 115-127, https://doi.org/10.1002/etc.3148.","productDescription":"13 p.","startPage":"115","endPage":"127","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064762","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":312505,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-02","publicationStatus":"PW","scienceBaseUri":"56753c39e4b0da412f4f8bc5","contributors":{"authors":[{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":582797,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Consbrock, Rebecca A. 0000-0002-5748-7046 rconsbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5748-7046","contributorId":3095,"corporation":false,"usgs":true,"family":"Consbrock","given":"Rebecca","email":"rconsbrock@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":582798,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":582799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hardesty, Douglas K. dhardesty@usgs.gov","contributorId":3281,"corporation":false,"usgs":true,"family":"Hardesty","given":"Douglas K.","email":"dhardesty@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":582800,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":582801,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hammer, Edward J.","contributorId":150723,"corporation":false,"usgs":false,"family":"Hammer","given":"Edward","email":"","middleInitial":"J.","affiliations":[{"id":18077,"text":"U. S. Environmental Protection Agency, Region 5, Water Quality Branch, Chicago, Illinois","active":true,"usgs":false}],"preferred":false,"id":582802,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bauer, Candice R.","contributorId":150724,"corporation":false,"usgs":false,"family":"Bauer","given":"Candice","email":"","middleInitial":"R.","affiliations":[{"id":18077,"text":"U. S. Environmental Protection Agency, Region 5, Water Quality Branch, Chicago, Illinois","active":true,"usgs":false}],"preferred":false,"id":582803,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mount, David R.","contributorId":150725,"corporation":false,"usgs":false,"family":"Mount","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":18078,"text":"U. S. Environmental Protection Agency, Environmental Effects Research Laboratory, Duluth, Minnesota","active":true,"usgs":false}],"preferred":false,"id":582804,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70160100,"text":"70160100 - 2016 - The effects of habitat, climate, and Barred Owls on long-term demography of Northern Spotted Owls","interactions":[],"lastModifiedDate":"2017-10-07T08:55:53","indexId":"70160100","displayToPublicDate":"2015-12-15T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"The effects of habitat, climate, and Barred Owls on long-term demography of Northern Spotted Owls","docAbstract":"Estimates of species' vital rates and an understanding of the factors affecting those parameters over time and space can provide crucial information for management and conservation. We used mark–recapture, reproductive output, and territory occupancy data collected during 1985–2013 to evaluate population processes of Northern Spotted Owls (Strix occidentalis caurina) in 11 study areas in Washington, Oregon, and northern California, USA. We estimated apparent survival, fecundity, recruitment, rate of population change, and local extinction and colonization rates, and investigated relationships between these parameters and the amount of suitable habitat, local and regional variation in meteorological conditions, and competition with Barred Owls (Strix varia). Data were analyzed for each area separately and in a meta-analysis of all areas combined, following a strict protocol for data collection, preparation, and analysis. We used mixed effects linear models for analyses of fecundity, Cormack-Jolly-Seber open population models for analyses of apparent annual survival (ϕ), and a reparameterization of the Jolly-Seber capture–recapture model (i.e. reverse Jolly-Seber; RJS) to estimate annual rates of population change (λRJS) and recruitment. We also modeled territory occupancy dynamics of Northern Spotted Owls and Barred Owls in each study area using 2-species occupancy models. Estimated mean annual rates of population change (λ) suggested that Spotted Owl populations declined from 1.2% to 8.4% per year depending on the study area. The weighted mean estimate of λ for all study areas was 0.962 (± 0.019 SE; 95% CI: 0.925–0.999), indicating an estimated range-wide decline of 3.8% per year from 1985 to 2013. Variation in recruitment rates across the range of the Spotted Owl was best explained by an interaction between total winter precipitation and mean minimum winter temperature. Thus, recruitment rates were highest when both total precipitation (29 cm) and minimum winter temperature (−9.5°C) were lowest. Barred Owl presence was associated with increased local extinction rates of Spotted Owl pairs for all 11 study areas. Habitat covariates were related to extinction rates for Spotted Owl pairs in 8 of 11 study areas, and a greater amount of suitable owl habitat was generally associated with decreased extinction rates. We observed negative effects of Barred Owl presence on colonization rates of Spotted Owl pairs in 5 of 11 study areas. The total amount of suitable Spotted Owl habitat was positively associated with colonization rates in 5 areas, and more habitat disturbance was associated with lower colonization rates in 2 areas. We observed strong declines in derived estimates of occupancy in all study areas. Mean fecundity of females was highest for adults (0.309 ± 0.027 SE), intermediate for 2-yr-olds (0.179 ± 0.040 SE), and lowest for 1-yr-olds (0.065 ± 0.022 SE). The presence of Barred Owls and habitat covariates explained little of the temporal variation in fecundity in most study areas. Climate covariates occurred in competitive fecundity models in 8 of 11 study areas, but support for these relationships was generally weak. The fecundity meta-analysis resulted in 6 competitive models, all of which included the additive effects of geographic region and annual time variation. The 2 top-ranked models also weakly supported the additive negative effects of the amount of suitable core area habitat, Barred Owl presence, and the amount of edge habitat on fecundity. We found strong support for a negative effect of Barred Owl presence on apparent survival of Spotted Owls in 10 of 11 study areas, but found few strong effects of habitat on survival at the study area scale. Climate covariates occurred in top or competitive survival models for 10 of 11 study areas, and in most cases the relationships were as predicted; however, there was little consistency among areas regarding the relative importance of specific climate covariates. In contrast, meta-analysis results suggested that Spotted Owl survival was higher across all study areas when the Pacific Decadal Oscillation (PDO) was in a warming phase and the Southern Oscillation Index (SOI) was negative, with a strongly negative SOI indicative of El Niño events. The best model that included the Barred Owl covariate (BO) was ranked 4th and also included the PDO covariate, but the BO effect was strongly negative. Our results indicated that Northern Spotted Owl populations were declining throughout the range of the subspecies and that annual rates of decline were accelerating in many areas. We observed strong evidence that Barred Owls negatively affected Spotted Owl populations, primarily by decreasing apparent survival and increasing local territory extinction rates. However, the amount of suitable owl habitat, local weather, and regional climatic patterns also were related to survival, occupancy (via colonization rate), recruitment, and, to a lesser extent, fecundity, although there was inconsistency in regard to which covariates were important for particular demographic parameters or across study areas. In the study areas where habitat was an important source of variation for Spotted Owl demographics, vital rates were generally positively associated with a greater amount of suitable owl habitat. However, Barred Owl densities may now be high enough across the range of the Northern Spotted Owl that, despite the continued management and conservation of suitable owl habitat on federal lands, the long-term prognosis for the persistence of Northern Spotted Owls may be in question without additional management intervention. Based on our study, the removal of Barred Owls from the Green Diamond Resources (GDR) study area had rapid, positive effects on Northern Spotted Owl survival and the rate of population change, supporting the hypothesis that, along with habitat conservation and management, Barred Owl removal may be able to slow or reverse Northern Spotted Owl population declines on at least a localized scale.
","language":"English","publisher":"Cooper Ornithological Society","doi":"10.1650/CONDOR-15-24.1","usgsCitation":"Dugger, K., Forsman, E.D., Franklin, A.B., Davis, R.J., White, G.C., Schwarz, C.J., Burnham, K.P., Nichols, J., Hines, J., Yackulic, C.B., Doherty, P., Bailey, L., Clark, D.A., Ackers, S.H., Andrews, L.S., Augustine, B., Biswell, B.L., Blakesley, J., Carlson, P., Clement, M.J., Diller, L.V., Glenn, E.M., Green, A., Gremel, S.A., Herter, D.R., Higley, J.M., Hobson, J., Horn, R.B., Huyvaert, K., McCafferty, C., McDonald, T., McDonnell, K., Olson, G.S., Reid, J.A., Rockweit, J., Ruiz, V., Saenz, J., and Sovern, S.G., 2016, The effects of habitat, climate, and Barred Owls on long-term demography of Northern Spotted Owls: Condor, v. 118, no. 1, p. 57-116, https://doi.org/10.1650/CONDOR-15-24.1.","productDescription":"59 p.","startPage":"57","endPage":"116","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063590","costCenters":[{"id":200,"text":"Coop Res Unit 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This analysis was performed to determine if the expression of this immuno-regulator could be used as a component of a larger health evaluation intended to identify potential risk-factors that may help to explain why very few of these fish survive to age-1. Potential associations between TGF-β1 expression, histopathological findings, meristic data as well as temporal and spatial data were evaluated using analysis-of-variance. In this analysis, the absence or presence of opercula deformity and hepatic cell necrosis were identified as significant factors in accounting for the variance in TGF-β1 expression observed in age-0 shortnose suckers (n = 122, squared multiple R = 0.989). Location of sample collection and the absence or presence of anchor worms (Lernaea spp.) were identified as significant cofactors. The actual mechanisms involved with these relationships have yet to be determined. The strength, however, of our findings support the concept of using TGF-β1 expression as part of a broader fish health assessment and suggests the potential for using additional immunologic measures in future studies. Specifically, our results indicate that the measure of TGF-β1 expression in age-0 shortnose sucker health assessments can facilitate the process of identifying disease risks that are associated with the documented lack of recruitment into the adult population.
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Almost all 50 States within the United States (excluding Delaware and Rhode Island) have karst areas, with sinkhole damage highest in Florida, Texas, Alabama, Missouri, Kentucky, Tennessee, and Pennsylvania. A conservative estimate of losses to all types of ground subsidence was $125 million per year in 1997. This estimate may now be low, as review of cost reports from the last 15 years indicates that the cost of karst collapses in the United States averages more than $300 million per year. Knowing when a catastrophic event will occur is not possible; however, understanding where such occurrences are likely is possible. The US Geological Survey has developed and maintains national-scale maps of karst areas and areas prone to sinkhole formation. 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dweary@usgs.gov","orcid":"https://orcid.org/0000-0002-6115-6397","contributorId":545,"corporation":false,"usgs":true,"family":"Weary","given":"David","email":"dweary@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":582104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaufmann, James E. jkaufmann@usgs.gov","contributorId":2312,"corporation":false,"usgs":true,"family":"Kaufmann","given":"James","email":"jkaufmann@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":582105,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70171366,"text":"70171366 - 2016 - Seasonal Distribution and Movements of Atlantic and Shortnose Sturgeon in the Penobscot River Estuary, Maine","interactions":[],"lastModifiedDate":"2016-05-27T13:28:42","indexId":"70171366","displayToPublicDate":"2015-12-15T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal Distribution and Movements of Atlantic and Shortnose Sturgeon in the Penobscot River Estuary, Maine","docAbstract":"Relatively little is known about the distribution and seasonal movement patterns of shortnose sturgeon Acipenser brevirostrum and Atlantic sturgeon Acipenser oxyrinchus oxyrinchus occupying rivers in the northern part of their range. During 2006 and 2007, 40 shortnose sturgeon (66–113.4 cm fork length [FL]) and 8 Atlantic sturgeon (76.2–166.2 cm FL) were captured in the Penobscot River, Maine, implanted with acoustic transmitters, and monitored using an array of acoustic receivers in the Penobscot River estuary and Penobscot Bay. Shortnose sturgeon were present year round in the estuary and overwintered from fall (mid-October) to spring (mid-April) in the upper estuary. In early spring, all individuals moved downstream to the middle estuary. Over the course of the summer, many individuals moved upstream to approximately 2 km of the downstream-most dam (46 river kilometers [rkm] from the Penobscot River mouth [rkm 0]) by August. Most aggregated into an overwintering site (rkm 36.5) in mid- to late fall. As many as 50% of the tagged shortnose sturgeon moved into and out of the Penobscot River system during 2007, and 83% were subsequently detected by an acoustic array in the Kennebec River, located 150 km from the Penobscot River estuary. Atlantic sturgeon moved into the estuary from the ocean in the summer and concentrated into a 1.5-km reach. All Atlantic sturgeon moved to the ocean by fall, and two of these were detected in the Kennebec River. Although these behaviors are common for Atlantic sturgeon, regular coastal migrations of shortnose sturgeon have not been documented previously in this region. These results have important implications for future dam removals as well as for rangewide and river-specific shortnose sturgeon management.
","language":"English","publisher":"Taylor and Francis","doi":"10.1577/T09-122.1","usgsCitation":"Zydlewski, J.D., Fernandes, S.J., Zydlewski, G.B., Wippelhauser, G.S., and Kinnison, M.T., 2016, Seasonal Distribution and Movements of Atlantic and Shortnose Sturgeon in the Penobscot River Estuary, Maine: Transactions of the American Fisheries Society, v. 139, no. 5, p. 1436-1449, https://doi.org/10.1577/T09-122.1.","productDescription":"13 p.","startPage":"1436","endPage":"1449","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-013820","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":321830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Penobscot River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -69.521484375,\n 43.866218006556394\n ],\n [\n -69.521484375,\n 45.213003555993964\n ],\n [\n -68.15917968749999,\n 45.213003555993964\n ],\n [\n -68.15917968749999,\n 43.866218006556394\n ],\n [\n -69.521484375,\n 43.866218006556394\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"139","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2011-01-09","publicationStatus":"PW","scienceBaseUri":"57496fb4e4b07e28b665cca4","contributors":{"authors":[{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":630721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fernandes, Stephen J.","contributorId":169689,"corporation":false,"usgs":false,"family":"Fernandes","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":630727,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Gayle B.","contributorId":169688,"corporation":false,"usgs":false,"family":"Zydlewski","given":"Gayle","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":630728,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wippelhauser, Gail S.","contributorId":169680,"corporation":false,"usgs":false,"family":"Wippelhauser","given":"Gail","email":"","middleInitial":"S.","affiliations":[{"id":25571,"text":"Maine Department of Marine Resources, Augusta, ME","active":true,"usgs":false}],"preferred":false,"id":630729,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kinnison, Michael T.","contributorId":169617,"corporation":false,"usgs":false,"family":"Kinnison","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":630730,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70164524,"text":"70164524 - 2016 - Radiometric dating of marine-influenced coal using Re–Os geochronology","interactions":[],"lastModifiedDate":"2016-02-09T13:23:41","indexId":"70164524","displayToPublicDate":"2015-12-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Radiometric dating of marine-influenced coal using Re–Os geochronology","docAbstract":"Coal deposits are integral to understanding the structural evolution and thermal history of sedimentary basins and correlating contemporeous estuarine and fluvial delatic strata with marine sections. While marine shales may readily lend themselves to Re–Os dating due to the dominance of hydrogenous Re and Os, the lack of a chronometer for near-shore sedimentary environments hampers basinwide correlations in absolute time. Here, we employ the Re–Os geochronometer, along with total organic carbon (TOC) and Rock–Eval data, to determine the timing and conditions of a marine incursion at the top of the Matewan coal bed, Kanawha Formation, Pottsville Group, West Virginia, USA. The observed range for hydrogen index (HI: 267–290 mg hydrocarbon/gram total organic carbon) for these coal samples suggests dominance of aliphatic hydrocarbons with low carbon (<C19) chain length. Average Re (107.6±16.4 ng/g) and Os (0.52±0.09 ng/g) concentrations of the marine-influenced Matewan coal are higher by few orders of magnitude than published data for terrestrial coal. A Re–Os isochron for the Matewan coal provides an age of 325±14 Ma (Model 3; MSWD = 12; n=19; 2σ ). This is the first Re–Os age derived from coal samples; the age overlaps a new composite Re–Os age of 317±2 Ma for the immediately overlying Betsie Shale Member.
\nExternal precision for replicate Os analyses carried out for several Matewan coal samples shows a positive correlation with their HI. The HI, which is low in terrestrial organic matter, reflects the degree of marine influence. Thus, samples with the most profound marine influence also have the best analytical reproducibility. Equilibration of Os isotopes with seawater under marine conditions overwhelms variability inherited from terrestrial plant debris, decreasing scatter on the isochron. The 187Re/188Os ratios of the Matewan coal (∼3300–5135) are higher than most of those previously published for Phanerozoic black shale (mostly <2000). Mass balance calculations based on Re/TOC and Os/TOC ratios for the Matewan coal indicate that both Re and Os are primarily marine in origin, and their high 187Re/188Os ratios confirm efficient removal of both elements from a sulfidic water column into the coal. We show that Re–Os geochronology of marine-influenced coal can be a viable tool for constraining depositional ages.
\n\n
Soil moisture in seasonally snow-covered environments fluctuates seasonally between wet and dry states. Climate warming is advancing the onset of spring snowmelt and may lengthen the summer-dry state and ultimately cause drier soil conditions. The magnitude of either response may vary across elevation and vegetation types. We situated our study at the lower boundary of persistent snow cover and the upper boundary of subalpine forest with paired treatment blocks in aspen forest and open meadow. In treatments plots, we advanced snowmelt timing by an average of 14 days by adding dust to the snow surface during spring melt. We specifically wanted to know whether early snowmelt would increase the duration of the summer-dry period and cause soils to be drier in the early-snowmelt treatments compared with control plots. We found no difference in the onset of the summer-dry state and no significant differences in soil moisture between treatments. To better understand the reasons soil moisture did not respond to early snowmelt as expected, we examined the mediating influences of soil organic matter, texture, temperature, and the presence or absence of forest. In our study, late-spring precipitation may have moderated the effects of early snowmelt on soil moisture. We conclude that landscape characteristics, including soil, vegetation, and regional weather patterns, may supersede the effects of snowmelt timing in determining growing season soil moisture, and efforts to anticipate the impacts of climate change on seasonally snow-covered ecosystems should take into account these mediating factors.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1002/eco.1697","usgsCitation":"Conner, L.G., Gill, R.A., and Belnap, J., 2016, Soil moisture response to experimentally altered snowmelt timing is mediated by soil, vegetation, and regional climate patterns: Ecohydrology, v. 9, no. 6, p. 1006-1016, https://doi.org/10.1002/eco.1697.","productDescription":"11 p.","startPage":"1006","endPage":"1016","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066535","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":314784,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Fairview Canyon, Wasatch Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.25,\n 39.6\n ],\n [\n -111.25,\n 39.7\n ],\n [\n -111.35,\n 39.7\n ],\n [\n -111.35,\n 39.6\n ],\n [\n -111.25,\n 39.6\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-15","publicationStatus":"PW","scienceBaseUri":"56a7556be4b0b28f1184d883","contributors":{"authors":[{"text":"Conner, Lafe G","contributorId":152512,"corporation":false,"usgs":false,"family":"Conner","given":"Lafe","email":"","middleInitial":"G","affiliations":[{"id":18936,"text":"Department of Biology, Brigham Young University, 4102 LSB, Provo, UT 84602, USA","active":true,"usgs":false}],"preferred":false,"id":589592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gill, Richard A.","contributorId":85508,"corporation":false,"usgs":true,"family":"Gill","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":589593,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":589591,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170964,"text":"70170964 - 2016 - Impacts of climatic variation on trout: A global synthesis and path forward","interactions":[],"lastModifiedDate":"2017-11-27T10:28:22","indexId":"70170964","displayToPublicDate":"2015-12-10T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3278,"text":"Reviews in Fish Biology and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of climatic variation on trout: A global synthesis and path forward","docAbstract":"Despite increasing concern that climate change may negatively impact trout—a globally distributed group of fish with major economic, ecological, and cultural value—a synthetic assessment of empirical data quantifying relationships between climatic variation and trout ecology does not exist. We conducted a systematic review to describe how temporal variation in temperature and streamflow influences trout ecology in freshwater ecosystems. Few studies (n = 42) have quantified relationships between temperature or streamflow and trout demography, growth, or phenology, and nearly all estimates (96 %) were for Salvelinus fontinalis and Salmo trutta. Only seven studies used temporal data to quantify climate-driven changes in trout ecology. Results from these studies were beset with limitations that prohibited quantitatively rigorous meta-analysis, a concerning inadequacy given major investment in trout conservation and management worldwide. Nevertheless, consistent patterns emerged from our synthesis, particularly a positive effect of summer streamflow on trout demography and growth; 64 % of estimates were positive and significant across studies, age classes, species, and locations, highlighting that climate-induced changes in hydrology may have numerous consequences for trout. To a lesser degree, summer and fall temperatures were negatively related to population demography (51 and 53 % of estimates, respectively), but temperature was rarely related to growth. To address limitations and uncertainties, we recommend: (1) systematically improving data collection, description, and sharing; (2) appropriately integrating climate impacts with other intrinsic and extrinsic drivers over the entire lifecycle; (3) describing indirect consequences of climate change; and (4) acknowledging and describing intrinsic resiliency.
","language":"English","publisher":"Chapman & Hall","publisherLocation":"Andover, UK","doi":"10.1007/s11160-015-9414-x","usgsCitation":"Kovach, R., Muhlfeld, C.C., Al-Chokhachy, R.K., Dunham, J.B., Letcher, B., and Kershner, J.L., 2016, Impacts of climatic variation on trout: A global synthesis and path forward: Reviews in Fish Biology and Fisheries, v. 26, no. 2, p. 135-151, https://doi.org/10.1007/s11160-015-9414-x.","productDescription":"17 p.","startPage":"135","endPage":"151","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064125","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":321217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-10","publicationStatus":"PW","scienceBaseUri":"5736fad0e4b0dae0d5e03dde","contributors":{"authors":[{"text":"Kovach, Ryan 0000-0001-5402-2123 rkovach@usgs.gov","orcid":"https://orcid.org/0000-0001-5402-2123","contributorId":145914,"corporation":false,"usgs":true,"family":"Kovach","given":"Ryan","email":"rkovach@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":629259,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":629260,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098 ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":629261,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":629262,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Letcher, Benjamin 0000-0003-0191-5678 bletcher@usgs.gov","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":169305,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin","email":"bletcher@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":629263,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kershner, Jeffrey L. 0000-0002-7093-9860 jkershner@usgs.gov","orcid":"https://orcid.org/0000-0002-7093-9860","contributorId":310,"corporation":false,"usgs":true,"family":"Kershner","given":"Jeffrey","email":"jkershner@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":629264,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70160054,"text":"70160054 - 2016 - A systematic survey of the integration of animal behavior into conservation","interactions":[],"lastModifiedDate":"2016-07-15T14:44:05","indexId":"70160054","displayToPublicDate":"2015-12-10T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"A systematic survey of the integration of animal behavior into conservation","docAbstract":"The role of behavioral ecology in improving wildlife conservation and management has been the subject of much recent debate. We aim to answer two foundational questions about the current use of behavioral knowledge in conservation: 1. To what extent is behavioral knowledge used in wildlife conservation and management? 2. How does the use of behavior differ among conservation fields in both frequency and types of use? To answer these questions, we searched the literature for intersections between key fields of animal behavior and conservation biology and created a systematic ‘heat’ map to visualize relative efforts. Our analysis challenges previous suggestions that there is little association between the fields of behavioral ecology and conservation and reveals tremendous variation in the use of different behaviors in conservation. For instance, some behaviors, such as foraging and dispersal, are commonly considered, but other behaviors such as learning, social or anti-predatory behaviors are hardly considered. Our analysis suggests that in many cases awareness of the importance of behavior does not translate into applicable management tools. We recommend that researchers should focus on developing research in underutilized intersections of behavior and conservation themes for which preliminary work show a potential for improving conservation and management, on translating behavioral theory into applicable and testable predictions, and on creating systematic reviews to summarize the behavioral evidence within the behavior-conservation intersections for which many studies exist.
","language":"English","publisher":"Wiley","doi":"10.1111/cobi.12654","usgsCitation":"Berger-Tal, O., Blumstein, D.T., Carroll, S., Fisher, R.N., Mesnick, S.L., Owen, M.A., Saltz, D., St. Claire, C.C., and Swaisgood, R.R., 2016, A systematic survey of the integration of animal behavior into conservation: Conservation Biology, v. 30, no. 4, p. 744-753, https://doi.org/10.1111/cobi.12654.","productDescription":"10 p.","startPage":"744","endPage":"753","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066474","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471409,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/cobi.12654","text":"Publisher Index Page"},{"id":312096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-03","publicationStatus":"PW","scienceBaseUri":"566aa238e4b09cfe53ca44d7","contributors":{"authors":[{"text":"Berger-Tal, Oded","contributorId":150452,"corporation":false,"usgs":false,"family":"Berger-Tal","given":"Oded","email":"","affiliations":[{"id":18023,"text":"Ecology and Evolutionary Biology, UCLA","active":true,"usgs":false}],"preferred":false,"id":581724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blumstein, Daniel T.","contributorId":150453,"corporation":false,"usgs":false,"family":"Blumstein","given":"Daniel","email":"","middleInitial":"T.","affiliations":[{"id":18023,"text":"Ecology and Evolutionary Biology, UCLA","active":true,"usgs":false}],"preferred":false,"id":581725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carroll, Scott","contributorId":150454,"corporation":false,"usgs":false,"family":"Carroll","given":"Scott","email":"","affiliations":[{"id":18024,"text":"Entomology Department, UC Davis","active":true,"usgs":false}],"preferred":false,"id":581726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":581723,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mesnick, Sarah L.","contributorId":150455,"corporation":false,"usgs":false,"family":"Mesnick","given":"Sarah","email":"","middleInitial":"L.","affiliations":[{"id":18025,"text":"Southwest Fisheries Science Center, NMFS, La Jolla","active":true,"usgs":false}],"preferred":false,"id":581727,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Owen, Megan A.","contributorId":138918,"corporation":false,"usgs":false,"family":"Owen","given":"Megan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":581728,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Saltz, David","contributorId":150456,"corporation":false,"usgs":false,"family":"Saltz","given":"David","email":"","affiliations":[{"id":18026,"text":"Mitrani Dep't of Desert Ecology, Ben-Gurion University of the Negev, Israel","active":true,"usgs":false}],"preferred":false,"id":581729,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"St. Claire, Colleen Cassady","contributorId":150457,"corporation":false,"usgs":false,"family":"St. Claire","given":"Colleen","email":"","middleInitial":"Cassady","affiliations":[{"id":18027,"text":"Biology Dep't, U of Alberta, Edmonton, Canada","active":true,"usgs":false}],"preferred":false,"id":581730,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Swaisgood, Ronald R.","contributorId":69490,"corporation":false,"usgs":false,"family":"Swaisgood","given":"Ronald","email":"","middleInitial":"R.","affiliations":[{"id":12762,"text":"San Diego Zoo Institure for Conservation Research","active":true,"usgs":false}],"preferred":false,"id":581731,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70160057,"text":"70160057 - 2016 - Human activities and climate variability drive fast-paced change across the world's estuarine-coastal ecosystems","interactions":[],"lastModifiedDate":"2016-02-01T13:29:58","indexId":"70160057","displayToPublicDate":"2015-12-10T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Human activities and climate variability drive fast-paced change across the world's estuarine-coastal ecosystems","docAbstract":"Time series of environmental measurements are essential for detecting, measuring and understanding changes in the Earth system and its biological communities. Observational series have accumulated over the past 2–5 decades from measurements across the world's estuaries, bays, lagoons, inland seas and shelf waters influenced by runoff. We synthesize information contained in these time series to develop a global view of changes occurring in marine systems influenced by connectivity to land. Our review is organized around four themes: (i) human activities as drivers of change; (ii) variability of the climate system as a driver of change; (iii) successes, disappointments and challenges of managing change at the sea-land interface; and (iv) discoveries made from observations over time. Multidecadal time series reveal that many of the world's estuarine–coastal ecosystems are in a continuing state of change, and the pace of change is faster than we could have imagined a decade ago. Some have been transformed into novel ecosystems with habitats, biogeochemistry and biological communities outside the natural range of variability. Change takes many forms including linear and nonlinear trends, abrupt state changes and oscillations. The challenge of managing change is daunting in the coastal zone where diverse human pressures are concentrated and intersect with different responses to climate variability over land and over ocean basins. The pace of change in estuarine–coastal ecosystems will likely accelerate as the human population and economies continue to grow and as global climate change accelerates. Wise stewardship of the resources upon which we depend is critically dependent upon a continuing flow of information from observations to measure, understand and anticipate future changes along the world's coastlines.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13059","usgsCitation":"Cloern, J.E., Abreu, P.C., Carstensen, J., Chauvaud, L., Elmgren, R., Grall, J., Greening, H., Johansson, J.O., Kahru, M., Sherwood, E.T., Xu, J., and Yin, K., 2016, Human activities and climate variability drive fast-paced change across the world's estuarine-coastal ecosystems: Global Change Biology, v. 22, no. 2, p. 513-529, https://doi.org/10.1111/gcb.13059.","productDescription":"17 p.","startPage":"513","endPage":"529","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064246","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471410,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.13059","text":"Publisher Index Page"},{"id":312094,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-20","publicationStatus":"PW","scienceBaseUri":"566aa23be4b09cfe53ca44db","contributors":{"authors":[{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":581740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abreu, Paulo C.","contributorId":150467,"corporation":false,"usgs":false,"family":"Abreu","given":"Paulo","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":581748,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carstensen, Jacob","contributorId":79367,"corporation":false,"usgs":false,"family":"Carstensen","given":"Jacob","email":"","affiliations":[{"id":7177,"text":"Dept of Bioscience, Aahus Univ, Denmark","active":true,"usgs":false}],"preferred":false,"id":581749,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chauvaud, Laurent","contributorId":72982,"corporation":false,"usgs":true,"family":"Chauvaud","given":"Laurent","email":"","affiliations":[],"preferred":false,"id":581750,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elmgren, Ragnar","contributorId":89008,"corporation":false,"usgs":true,"family":"Elmgren","given":"Ragnar","email":"","affiliations":[],"preferred":false,"id":581751,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grall, Jacques","contributorId":150468,"corporation":false,"usgs":false,"family":"Grall","given":"Jacques","email":"","affiliations":[],"preferred":false,"id":581752,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Greening, Holly","contributorId":64299,"corporation":false,"usgs":true,"family":"Greening","given":"Holly","email":"","affiliations":[],"preferred":false,"id":581753,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johansson, John O.R.","contributorId":150470,"corporation":false,"usgs":false,"family":"Johansson","given":"John","email":"","middleInitial":"O.R.","affiliations":[],"preferred":false,"id":581754,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kahru, Mati","contributorId":150471,"corporation":false,"usgs":false,"family":"Kahru","given":"Mati","email":"","affiliations":[],"preferred":false,"id":581755,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sherwood, Edward T. 0000-0001-5330-302X","orcid":"https://orcid.org/0000-0001-5330-302X","contributorId":150472,"corporation":false,"usgs":false,"family":"Sherwood","given":"Edward","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":581756,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Xu, J.","contributorId":25324,"corporation":false,"usgs":true,"family":"Xu","given":"J.","affiliations":[],"preferred":false,"id":581757,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Yin, Kedong","contributorId":94879,"corporation":false,"usgs":true,"family":"Yin","given":"Kedong","email":"","affiliations":[],"preferred":false,"id":581758,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70160011,"text":"70160011 - 2016 - High and dry: high elevations disproportionately exposed to regional climate change in Mediterranean-climate landscapes","interactions":[],"lastModifiedDate":"2016-04-28T12:59:29","indexId":"70160011","displayToPublicDate":"2015-12-08T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"High and dry: high elevations disproportionately exposed to regional climate change in Mediterranean-climate landscapes","docAbstract":"Predicting climate-driven species’ range shifts depends substantially on species’ exposure to climate change. Mountain landscapes contain a wide range of topoclimates and soil characteristics that are thought to mediate range shifts and buffer species’ exposure. Quantifying fine-scale patterns of exposure across mountainous terrain is a key step in understanding vulnerability of species to regional climate change.
\nWe demonstrated a transferable, flexible approach for mapping climate change exposure in a moisture-limited, mountainous California landscape across 4 climate change projections under phase 5 of the Coupled Model Intercomparison Project (CMIP5) for mid-(2040–2069) and end-of-century (2070–2099).
\nWe produced a 149-year dataset (1951–2099) of modeled climatic water deficit (CWD), which is strongly associated with plant distributions, at 30-m resolution to map climate change exposure in the Tehachapi Mountains, California, USA. We defined climate change exposure in terms of departure from the 1951–1980 mean and historical range of variability in CWD in individual years and 3-year moving windows.
\nClimate change exposure was generally greatest at high elevations across all future projections, though we encountered moderate topographic buffering on poleward-facing slopes. Historically dry lowlands demonstrated the least exposure to climate change.
\nIn moisture-limited, Mediterranean-climate landscapes, high elevations may experience the greatest exposure to climate change in the 21st century. High elevation species may thus be especially vulnerable to continued climate change as habitats shrink and historically energy-limited locations become increasingly moisture-limited in the future.
\nIntersex as the manifestation of testicular oocytes (TO) in male gonochoristic fishes has been used as an indicator of estrogenic exposure. Here we evaluated largemouth bass (Micropterus salmoides) or smallmouth bass (Micropterus dolomieu) form 19 National Wildlife Refuges (NWRs) in the Northeast U.S. inhabiting waters on or near NWR lands for evidence of estrogenic endocrine disruption. Waterbodies sampled included rivers, lakes, impoundments, ponds, and reservoirs. Here we focus on evidence of endocrine disruption in male bass evidenced by gonad histopathology including intersex or abnormal plasma vitellogenin (Vtg) concentrations. During the fall seasons of 2008–2010, we collected male smallmouth bass (n=118) from 12 sites and largemouth bass (n=173) from 27 sites. Intersex in male smallmouth bass was observed at all sites and ranged from 60% to 100%; in male largemouth bass the range was 0–100%. Estrogenicity, as measured using a bioluminescent yeast reporter, was detected above the probable no effects concentration (0.73 ng/L) in ambient water samples from 79% of the NWR sites. Additionally, the presence of androgen receptor and glucocorticoid receptor ligands were noted as measured via novel nuclear receptor translocation assays. Mean plasma Vtg was elevated (>0.2 mg/ml) in male smallmouth bass at four sites and in male largemouth bass at one site. This is the first reconnaissance survey of this scope conducted on US National Wildlife Refuges. The baseline data collected here provide a necessary benchmark for future monitoring and justify more comprehensive NWR-specific studies.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.ecoenv.2015.09.035","usgsCitation":"Iwanowicz, L., Blazer, V., Pinkney, A., Guy, C., Major, A., Munney, K., Mierzykowski, S., Lingenfelser, S., Secord, A., Patnode, K., Kubiak, T., Stern, C., Hahn, C.M., Iwanowicz, D.D., Walsh, H.L., and Sperry, A.J., 2016, Evidence of estrogenic endocrine disruption in smallmouth and largemouth bass inhabiting Northeast U.S. National Wildlife Refuge waters: A reconnaissance study: Ecotoxicology and Environmental Safety, v. 124, p. 50-59, https://doi.org/10.1016/j.ecoenv.2015.09.035.","productDescription":"10 p.","startPage":"50","endPage":"59","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059732","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":312035,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Ohio, Pennsylvannia, Vermont, Virginia, West Virginia","otherGeospatial":"Assabet River, Back Bay, Blackwater, Cherry Valley, Erie, Great Bay, Great Meadows, Great Swamp, John Heinzat Tinicum, Mason Neck, Missisquoi, Montezuma, Moosehorn, Ohio River Islands, Patuxent, Rappahannock, Sunkhaze, Umbagog, Wallkill","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.103515625,\n 45.321254361171476\n ],\n [\n -67.43408203124999,\n 45.583289756006316\n ],\n [\n -67.39013671875,\n 45.321254361171476\n ],\n [\n -67.1044921875,\n 45.182036837015886\n ],\n [\n -66.8408203125,\n 44.66865287227321\n ],\n [\n -68.48876953125,\n 44.10336537791152\n ],\n [\n -69.76318359375,\n 43.67581809328344\n ],\n [\n -70.46630859375,\n 43.42100882994726\n ],\n [\n -70.7080078125,\n 42.553080288955826\n ],\n [\n -71.103515625,\n 42.04929263868686\n ],\n [\n -71.8505859375,\n 41.27780646738183\n ],\n [\n -74.02587890625,\n 40.58058466412764\n ],\n [\n -75.5419921875,\n 39.436192999314095\n ],\n [\n -75.95947265625,\n 38.993572058209466\n ],\n [\n -75.87158203125,\n 37.996162679728116\n ],\n [\n -75.65185546874999,\n 36.82687474287728\n ],\n [\n -75.89355468749999,\n 36.38591277287651\n ],\n [\n -77.36572265625,\n 36.56260003738548\n ],\n [\n -79.0576171875,\n 38.993572058209466\n ],\n [\n -80.79345703125,\n 39.67337039176558\n ],\n [\n -81.49658203125,\n 40.27952566881291\n ],\n [\n -81.32080078125,\n 41.492120839687786\n ],\n [\n -80.61767578124999,\n 42.04929263868686\n ],\n [\n -77.49755859375,\n 43.34116005412307\n ],\n [\n -76.13525390624999,\n 43.50075243569041\n ],\n [\n -73.32275390625,\n 45.213003555993964\n ],\n [\n -71.103515625,\n 45.321254361171476\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5667ff39e4b06a3ea36c8e0a","contributors":{"authors":[{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":150383,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R. 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survival and reproductive success are critical for guiding management efforts focused on species of conservation concern. Unfortunately, reliable demographic parameters are difficult to obtain for any species, but especially for rare or endangered species. Here we derived estimates of adult survival and recruitment in a community of Hawaiian forest birds, including eight native species (of which three are endangered) and two introduced species at Hakalau Forest National Wildlife Refuge, Hawaiʻi. Integrated population models (IPM) were used to link mark–recapture data (1994–1999) with long-term population surveys (1987–2008). To our knowledge, this is the first time that IPM have been used to characterize demographic parameters of a whole avian community, and provides important insights into the life history strategies of the community. The demographic data were used to test two hypotheses: 1) arthropod specialists, such as the ‘Akiapōlā‘au Hemignathus munroi, are ‘slower’ species characterized by a greater relative contribution of adult survival to population growth, i.e. lower fecundity and increased adult survival; and 2) a species’ susceptibility to environmental change, as reflected by its conservation status, can be predicted by its life history traits. We found that all species were characterized by a similar population growth rate around one, independently of conservation status, origin (native vs non-native), feeding guild, or life history strategy (as measured by ‘slowness’), which suggested that the community had reached an equilibrium. However, such stable dynamics were achieved differently across feeding guilds, as demonstrated by a significant increase of adult survival and a significant decrease of recruitment along a gradient of increased insectivory, in support of hypothesis 1. Supporting our second hypothesis, we found that slower species were more vulnerable species at the global scale than faster ones. The possible causes and conservation implications of these patterns are discussed.
","language":"English","publisher":"Wiley-Blackwell","doi":"10.1111/jav.00756","usgsCitation":"Guillaumet, A., Woodworth, B., Camp, R., and Paxton, E., 2016, Comparative demographics of a Hawaiian forest bird community: Journal of Avian Biology, v. 47, no. 2, p. 185-196, https://doi.org/10.1111/jav.00756.","productDescription":"12 p.","startPage":"185","endPage":"196","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068685","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":312034,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160.46630859375,\n 21.69826549685252\n ],\n [\n -158.04931640625,\n 21.238182425982313\n ],\n [\n -156.016845703125,\n 20.004322295998723\n ],\n [\n -156.236572265625,\n 19.590844152960933\n ],\n [\n -155.797119140625,\n 18.760712758499565\n ],\n [\n -154.698486328125,\n 19.46659223220761\n ],\n [\n -155.819091796875,\n 20.80747157680652\n ],\n [\n -157.1484375,\n 21.493963563064455\n ],\n [\n -159.697265625,\n 22.411028521558706\n ],\n [\n -160.59814453125,\n 21.800308050972603\n ],\n [\n -160.46630859375,\n 21.69826549685252\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-22","publicationStatus":"PW","scienceBaseUri":"5667ff38e4b06a3ea36c8e06","chorus":{"doi":"10.1111/jav.00756","url":"http://dx.doi.org/10.1111/jav.00756","publisher":"Wiley-Blackwell","authors":"Guillaumet Alban, Woodworth Bethany L., Camp Richard J., Paxton Eben H.","journalName":"Journal of Avian Biology","publicationDate":"11/22/2015","auditedOn":"3/28/2016"},"contributors":{"authors":[{"text":"Guillaumet, Alban","contributorId":150397,"corporation":false,"usgs":false,"family":"Guillaumet","given":"Alban","email":"","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":581523,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodworth, Bethany L.","contributorId":66797,"corporation":false,"usgs":true,"family":"Woodworth","given":"Bethany L.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":581524,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Camp, Richard J.","contributorId":27392,"corporation":false,"usgs":true,"family":"Camp","given":"Richard J.","affiliations":[],"preferred":false,"id":581525,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paxton, Eben H. 0000-0001-5578-7689 epaxton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":438,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben H.","email":"epaxton@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":581522,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174956,"text":"70174956 - 2016 - A global planktic foraminifer census data set for the Pliocene ocean","interactions":[],"lastModifiedDate":"2016-07-22T16:07:40","indexId":"70174956","displayToPublicDate":"2015-12-08T05:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"A global planktic foraminifer census data set for the Pliocene ocean","docAbstract":"This article presents data derived by the USGS Pliocene Research, Interpretation and Synoptic Mapping (PRISM) Project. PRISM has generated planktic foraminifer census data from core sites and outcrops around the globe since 1988. These data form the basis of a number of paleoceanographic reconstructions focused on the mid-Piacenzian Warm Period (3.264 to 3.025 million years ago). Data are presented as counts of individuals within 64 taxonomic categories for each locality. We describe sample acquisition and processing, age dating, taxonomy and archival storage of material. These data provide a unique, stratigraphically focused opportunity to assess the effects of global warming on marine plankton.
","language":"English","publisher":"Macmillan Publishers Limited","doi":"10.1038/sdata.2015.76","usgsCitation":"Dowsett, H.J., Robinson, M.M., and Foley, K.M., 2016, A global planktic foraminifer census data set for the Pliocene ocean: Scientific Data, v. 2, Article number: 150076 ; 6 p., https://doi.org/10.1038/sdata.2015.76.","productDescription":"Article number: 150076 ; 6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069639","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":471412,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/sdata.2015.76","text":"Publisher Index Page"},{"id":325566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-08","publicationStatus":"PW","scienceBaseUri":"5793443fe4b0eb1ce79e8bd0","contributors":{"authors":[{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":643336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Marci M. 0000-0002-9200-4097 mmrobinson@usgs.gov","orcid":"https://orcid.org/0000-0002-9200-4097","contributorId":2082,"corporation":false,"usgs":true,"family":"Robinson","given":"Marci","email":"mmrobinson@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":643337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foley, Kevin M. 0000-0003-1013-462X kfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-1013-462X","contributorId":2543,"corporation":false,"usgs":true,"family":"Foley","given":"Kevin","email":"kfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":643338,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160216,"text":"70160216 - 2016 - Species and tissue type regulate long-term decomposition of brackish marsh plants grown under elevated CO2 conditions","interactions":[],"lastModifiedDate":"2021-08-24T14:59:45.425641","indexId":"70160216","displayToPublicDate":"2015-12-08T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Species and tissue type regulate long-term decomposition of brackish marsh plants grown under elevated CO2 conditions","title":"Species and tissue type regulate long-term decomposition of brackish marsh plants grown under elevated CO2 conditions","docAbstract":"Organic matter accumulation, the net effect of plant production and decomposition, contributes to vertical soil accretion in coastal wetlands, thereby playing a key role in whether they keep pace with sea-level rise. Any factor that affects decomposition may affect wetland accretion, including atmospheric CO2 concentrations. Higher CO2 can influence decomposition rates by altering plant tissue chemistry or by causing shifts in plant species composition or biomass partitioning. A combined greenhouse-field experiment examined how elevated CO2 affected plant tissue chemistry and subsequent decomposition of above- and belowground tissues of two common brackish marsh species, Schoenoplectus americanus (C3) and Spartina patens (C4). Both species were grown in monoculture and in mixture under ambient (350-385 μL L-1) or elevated (ambient + 300 μL L-1) atmospheric CO2 conditions, with all other growth conditions held constant, for one growing season. Above- and belowground tissues produced under these treatments were decomposed under ambient field conditions in a brackish marsh in the Mississippi River Delta, USA. Elevated CO2 significantly reduced nitrogen content of S. americanus, but not sufficiently to affect subsequent decomposition. Instead, long-term decomposition (percent mass remaining after 280 d) was controlled by species composition and tissue type. Shoots of S. patens had more mass remaining (41 ± 2%) than those of S. americanus (12 ± 2 %). Belowground material decomposed more slowly than that placed aboveground (62 ± 1% vs. 23 ± 3% mass remaining), but rates belowground did not differ between species. Increases in atmospheric CO2concentration will likely have a greater effect on overall decomposition in this brackish marsh community through shifts in species dominance or biomass allocation than through effects on tissue chemistry. Consequent changes in organic matter accumulation may alter marsh capacity to accommodate sea-level rise through vertical accretion.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2015.11.033","usgsCitation":"Jones, J.A., Cherry, J., and McKee, K.L., 2016, Species and tissue type regulate long-term decomposition of brackish marsh plants grown under elevated CO2 conditions: Estuarine, Coastal and Shelf Science, v. 169, p. 38-45, https://doi.org/10.1016/j.ecss.2015.11.033.","productDescription":"8 p.","startPage":"38","endPage":"45","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064638","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":312238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Big Branch Marsh National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90,\n 30.24\n ],\n [\n -90,\n 30.3\n ],\n [\n -89.9,\n 30.3\n ],\n [\n -89.9,\n 30.24\n ],\n [\n -90,\n 30.24\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"169","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"566ff657e4b09cfe53ca79ca","contributors":{"authors":[{"text":"Jones, Joshua A","contributorId":150553,"corporation":false,"usgs":false,"family":"Jones","given":"Joshua","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":582099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cherry, Julia A","contributorId":150554,"corporation":false,"usgs":false,"family":"Cherry","given":"Julia A","affiliations":[{"id":33913,"text":"Univ. of Alabama, Tuscaloosa, AL","active":true,"usgs":false}],"preferred":false,"id":582100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKee, Karen L. 0000-0001-7042-670X mckeek@usgs.gov","orcid":"https://orcid.org/0000-0001-7042-670X","contributorId":704,"corporation":false,"usgs":true,"family":"McKee","given":"Karen","email":"mckeek@usgs.gov","middleInitial":"L.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":582054,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160542,"text":"70160542 - 2016 - Non-linear resonant coupling of tsunami edge waves using stochastic earthquake source models","interactions":[],"lastModifiedDate":"2016-12-14T12:43:35","indexId":"70160542","displayToPublicDate":"2015-12-06T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Non-linear resonant coupling of tsunami edge waves using stochastic earthquake source models","docAbstract":"Non-linear resonant coupling of edge waves can occur with tsunamis generated by large-magnitude subduction zone earthquakes. Earthquake rupture zones that straddle beneath the coastline of continental margins are particularly efficient at generating tsunami edge waves. Using a stochastic model for earthquake slip, it is shown that a wide range of edge-wave modes and wavenumbers can be excited, depending on the variability of slip. If two modes are present that satisfy resonance conditions, then a third mode can gradually increase in amplitude over time, even if the earthquake did not originally excite that edge-wave mode. These three edge waves form a resonant triad that can cause unexpected variations in tsunami amplitude long after the first arrival. An M ∼ 9, 1100 km-long continental subduction zone earthquake is considered as a test case. For the least-variable slip examined involving a Gaussian random variable, the dominant resonant triad includes a high-amplitude fundamental mode wave with wavenumber associated with the along-strike dimension of rupture. The two other waves that make up this triad include subharmonic waves, one of fundamental mode and the other of mode 2 or 3. For the most variable slip examined involving a Cauchy-distributed random variable, the dominant triads involve higher wavenumbers and modes because subevents, rather than the overall rupture dimension, control the excitation of edge waves. Calculation of the resonant period for energy transfer determines which cases resonant coupling may be instrumentally observed. For low-mode triads, the maximum transfer of energy occurs approximately 20–30 wave periods after the first arrival and thus may be observed prior to the tsunami coda being completely attenuated. Therefore, under certain circumstances the necessary ingredients for resonant coupling of tsunami edge waves exist, indicating that resonant triads may be observable and implicated in late, large-amplitude tsunami arrivals.
","language":"English","publisher":"Blackwell Science","doi":"10.1093/gji/ggv489","usgsCitation":"Geist, E.L., 2016, Non-linear resonant coupling of tsunami edge waves using stochastic earthquake source models: Geophysical Journal International, v. 204, no. 2, p. 878-891, https://doi.org/10.1093/gji/ggv489.","productDescription":"14 p.","startPage":"878","endPage":"891","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066314","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471413,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggv489","text":"Publisher Index Page"},{"id":312783,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"204","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-10","publicationStatus":"PW","scienceBaseUri":"567bd3bde4b0a04ef491a209","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":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":583091,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}