{"pageNumber":"883","pageRowStart":"22050","pageSize":"25","recordCount":184904,"records":[{"id":70196384,"text":"70196384 - 2018 - Convergent validity between willingness to pay elicitation methods: An application to Grand Canyon whitewater boaters","interactions":[],"lastModifiedDate":"2019-08-16T06:33:18","indexId":"70196384","displayToPublicDate":"2018-04-04T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2261,"text":"Journal of Environmental Planning and Management","active":true,"publicationSubtype":{"id":10}},"title":"Convergent validity between willingness to pay elicitation methods: An application to Grand Canyon whitewater boaters","docAbstract":"<p><span>We directly compare trip willingness to pay (WTP) values between dichotomous choice contingent valuation (DCCV) and discrete choice experiment (DCE) stated preference surveys of private party Grand Canyon whitewater boaters. The consistency of DCCV and DCE estimates is debated in the literature, and this study contributes to the body of work comparing the methods. Comparisons were made of mean WTP estimates for four hypothetical Colorado River flow-level scenarios. Boaters were found to most highly value mid-range flows, with very low and very high flows eliciting lower WTP estimates across both DCE and DCCV surveys. Mean WTP precision was estimated through simulation. No statistically significant differences were detected between the two methods at three of the four hypothetical flow levels.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/09640568.2018.1435411","usgsCitation":"Neher, C., Bair, L.S., Duffield, J., Patterson, D.A., and Neher, K., 2018, Convergent validity between willingness to pay elicitation methods: An application to Grand Canyon whitewater boaters: Journal of Environmental Planning and Management, v. 62, no. 4, p. 611-625, https://doi.org/10.1080/09640568.2018.1435411.","productDescription":"15 p.","startPage":"611","endPage":"625","ipdsId":"IP-088671","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":437963,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DZ07HM","text":"USGS data release","linkHelpText":"Grand Canyon Whitewater Boater Data, Convergent Validity between Willingness to Pay Elicitation Methods"},{"id":353155,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Grand Canyon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.3621826171875,\n              35.357696204467516\n            ],\n            [\n              -111.22558593749999,\n              35.357696204467516\n            ],\n            [\n              -111.22558593749999,\n              37.08585785263673\n            ],\n            [\n              -114.3621826171875,\n              37.08585785263673\n            ],\n            [\n              -114.3621826171875,\n              35.357696204467516\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"62","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-13","publicationStatus":"PW","scienceBaseUri":"5afee6e8e4b0da30c1bfbf2b","contributors":{"authors":[{"text":"Neher, Christopher","contributorId":175085,"corporation":false,"usgs":false,"family":"Neher","given":"Christopher","email":"","affiliations":[{"id":27528,"text":"Uni. of Montana, Dept. of Mathematical Sciences","active":true,"usgs":false}],"preferred":false,"id":732703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bair, Lucas S. 0000-0002-9911-3624 lbair@usgs.gov","orcid":"https://orcid.org/0000-0002-9911-3624","contributorId":5270,"corporation":false,"usgs":true,"family":"Bair","given":"Lucas","email":"lbair@usgs.gov","middleInitial":"S.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":732702,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duffield, John","contributorId":202570,"corporation":false,"usgs":false,"family":"Duffield","given":"John","email":"","affiliations":[{"id":36482,"text":"Department of Mathematical Sciences, University of Montana","active":true,"usgs":false}],"preferred":false,"id":732704,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patterson, David A.","contributorId":175326,"corporation":false,"usgs":false,"family":"Patterson","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":36482,"text":"Department of Mathematical Sciences, University of Montana","active":true,"usgs":false}],"preferred":false,"id":732705,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neher, Katherine","contributorId":202571,"corporation":false,"usgs":false,"family":"Neher","given":"Katherine","email":"","affiliations":[{"id":36483,"text":"Bioeconomics, Inc. Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":732706,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196377,"text":"70196377 - 2018 - Distribution and seasonal differences in Pacific Lamprey and Lampetra spp eDNA across 18 Puget Sound watersheds","interactions":[],"lastModifiedDate":"2018-04-04T11:17:32","indexId":"70196377","displayToPublicDate":"2018-04-04T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Distribution and seasonal differences in Pacific Lamprey and <i>Lampetra spp</i> eDNA across 18 Puget Sound watersheds","title":"Distribution and seasonal differences in Pacific Lamprey and Lampetra spp eDNA across 18 Puget Sound watersheds","docAbstract":"<p><span>Lampreys have a worldwide distribution, are functionally important to ecological communities and serve significant roles in many cultures. In Pacific coast drainages of North America, lamprey populations have suffered large declines. However, lamprey population status and trends within many areas of this region are unknown and such information is needed for advancing conservation goals. We developed two quantitative PCR-based, aquatic environmental DNA (eDNA) assays for detection of Pacific Lamprey (</span><i>Entosphenus tridentatus</i><span>) and<span>&nbsp;</span></span><i>Lampetra</i><span><span>&nbsp;</span>spp, using locked nucleic acids (LNAs) in the probe design. We used these assays to characterize the spatial distribution of lamprey in 18 watersheds of Puget Sound, Washington, by collecting water samples in spring and fall. Pacific Lamprey and<span>&nbsp;</span></span><i>Lampetra</i><span>spp were each detected in 14 watersheds and co-occurred in 10 watersheds. Lamprey eDNA detection rates were much higher in spring compared to fall. Specifically, the Pacific Lamprey eDNA detection rate was 3.5 times higher in spring and the<span>&nbsp;</span></span><i>Lampetra</i><span><span>&nbsp;</span>spp eDNA detection rate was 1.5 times higher in spring even though larval lamprey are present in streams year-round. This significant finding highlights the importance of seasonality on eDNA detection. Higher stream discharge in the fall likely contributed to reduced eDNA detection rates, although seasonal life history events may have also contributed. These eDNA assays differentiate Pacific Lamprey and<span>&nbsp;</span></span><i>Lampetra</i><span><span>&nbsp;</span>spp across much of their range along the west coast of North America. Sequence analysis indicates the Pacific Lamprey assay also targets other<span>&nbsp;</span></span><i>Entosphenus</i><span><span>&nbsp;</span>spp and indicates the<span>&nbsp;</span></span><i>Lampetra</i><span><span>&nbsp;</span>spp assay may have limited or no capability of detecting<span>&nbsp;</span></span><i>Lampetra</i><span><span>&nbsp;</span>in some locations south of the Columbia River Basin. Nevertheless, these assays will serve as a valuable tool for resource managers and have direct application to lamprey conservation efforts, such as mapping species distributions, occupancy modeling, and monitoring translocations and reintroductions.</span></p>","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.4496","usgsCitation":"Ostberg, C.O., Chase, D.M., Hayes, M.C., and Duda, J.J., 2018, Distribution and seasonal differences in Pacific Lamprey and Lampetra spp eDNA across 18 Puget Sound watersheds: PeerJ, v. 6, p. 1-25, https://doi.org/10.7717/peerj.4496.","productDescription":"e4496; 25 p.","startPage":"1","endPage":"25","ipdsId":"IP-090879","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468852,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.4496","text":"Publisher Index Page"},{"id":437962,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H994DT","text":"USGS data release","linkHelpText":"Distribution and seasonal differences in Pacific Lamprey and Lampetra spp eDNA across 18 Puget Sound watersheds, 2014 and 2015"},{"id":353142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puget Sound","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.61267089843751,\n              46.882723010671945\n            ],\n            [\n              -121.7340087890625,\n              46.882723010671945\n            ],\n            [\n              -121.7340087890625,\n              49.05227025601607\n            ],\n            [\n              -123.61267089843751,\n              49.05227025601607\n            ],\n            [\n              -123.61267089843751,\n              46.882723010671945\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-16","publicationStatus":"PW","scienceBaseUri":"5afee6e8e4b0da30c1bfbf2d","contributors":{"authors":[{"text":"Ostberg, Carl O. 0000-0003-1479-8458 costberg@usgs.gov","orcid":"https://orcid.org/0000-0003-1479-8458","contributorId":3031,"corporation":false,"usgs":true,"family":"Ostberg","given":"Carl","email":"costberg@usgs.gov","middleInitial":"O.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chase, Dorothy M. 0000-0002-7759-2687","orcid":"https://orcid.org/0000-0002-7759-2687","contributorId":203926,"corporation":false,"usgs":true,"family":"Chase","given":"Dorothy","email":"","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Michael C. 0000-0002-9060-0565 mhayes@usgs.gov","orcid":"https://orcid.org/0000-0002-9060-0565","contributorId":3017,"corporation":false,"usgs":true,"family":"Hayes","given":"Michael","email":"mhayes@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732669,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":145486,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":732670,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196365,"text":"70196365 - 2018 - Herbivory and eutrophication mediate grassland plant nutrient responses across a global climatic gradient","interactions":[],"lastModifiedDate":"2018-04-04T11:12:57","indexId":"70196365","displayToPublicDate":"2018-04-04T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Herbivory and eutrophication mediate grassland plant nutrient responses across a global climatic gradient","docAbstract":"<p><span>Plant stoichiometry, the relative concentration of elements, is a key regulator of ecosystem functioning and is also being altered by human activities. In this paper we sought to understand the global drivers of plant stoichiometry and compare the relative contribution of climatic vs. anthropogenic effects. We addressed this goal by measuring plant elemental (C, N, P and K) responses to eutrophication and vertebrate herbivore exclusion at eighteen sites on six continents. Across sites, climate and atmospheric N deposition emerged as strong predictors of plot‐level tissue nutrients, mediated by biomass and plant chemistry. Within sites, fertilization increased total plant nutrient pools, but results were contingent on soil fertility and the proportion of grass biomass relative to other functional types. Total plant nutrient pools diverged strongly in response to herbivore exclusion when fertilized; responses were largest in ungrazed plots at low rainfall, whereas herbivore grazing dampened the plant community nutrient responses to fertilization. Our study highlights (1) the importance of climate in determining plant nutrient concentrations mediated through effects on plant biomass, (2) that eutrophication affects grassland nutrient pools via both soil and atmospheric pathways and (3) that interactions among soils, herbivores and eutrophication drive plant nutrient responses at small scales, especially at water‐limited sites.</span></p>","language":"English","publisher":"Ecology Society of America","doi":"10.1002/ecy.2175","usgsCitation":"Anderson, T.M., Griffith, D.M., Grace, J.B., Lind, E., Adler, P.B., Biederman, L.A., Blumenthal, D.M., Daleo, P., Firn, J., Hagenah, N., Harpole, W.S., MacDougall, A.S., McCulley, R.L., Prober, S.M., Risch, A.C., Sankaran, M., Schutz, M., Seabloom, E.W., Stevens, C.J., Sullivan, L., Wragg, P., and Borer, E.T., 2018, Herbivory and eutrophication mediate grassland plant nutrient responses across a global climatic gradient: Ecology, v. 99, no. 4, p. 822-831, https://doi.org/10.1002/ecy.2175.","productDescription":"10 p.","startPage":"822","endPage":"831","ipdsId":"IP-084236","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468853,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecy.2175","text":"External Repository"},{"id":353140,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"4","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-31","publicationStatus":"PW","scienceBaseUri":"5afee6e8e4b0da30c1bfbf35","contributors":{"authors":[{"text":"Anderson, T. Michael","contributorId":203893,"corporation":false,"usgs":false,"family":"Anderson","given":"T.","email":"","middleInitial":"Michael","affiliations":[{"id":36744,"text":"Wake Forest University","active":true,"usgs":false}],"preferred":false,"id":732600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffith, Daniel M.","contributorId":203894,"corporation":false,"usgs":false,"family":"Griffith","given":"Daniel","email":"","middleInitial":"M.","affiliations":[{"id":36744,"text":"Wake Forest University","active":true,"usgs":false}],"preferred":false,"id":732601,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":732599,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lind, Eric M.","contributorId":44828,"corporation":false,"usgs":false,"family":"Lind","given":"Eric M.","affiliations":[],"preferred":false,"id":732602,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adler, Peter B.","contributorId":64789,"corporation":false,"usgs":false,"family":"Adler","given":"Peter","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":732603,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Biederman, Lori A.","contributorId":203895,"corporation":false,"usgs":false,"family":"Biederman","given":"Lori","email":"","middleInitial":"A.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":732604,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Blumenthal, Dana M.","contributorId":203896,"corporation":false,"usgs":false,"family":"Blumenthal","given":"Dana","email":"","middleInitial":"M.","affiliations":[{"id":36745,"text":"USDA-ARS Rangeland Resources Research Unit","active":true,"usgs":false}],"preferred":false,"id":732605,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Daleo, Pedro","contributorId":203897,"corporation":false,"usgs":false,"family":"Daleo","given":"Pedro","email":"","affiliations":[{"id":36746,"text":"Universidad Nacional de Mar del Plata","active":true,"usgs":false}],"preferred":false,"id":732607,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Firn, Jennifer","contributorId":66405,"corporation":false,"usgs":false,"family":"Firn","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":732608,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hagenah, Nicole","contributorId":203898,"corporation":false,"usgs":false,"family":"Hagenah","given":"Nicole","email":"","affiliations":[{"id":28213,"text":"University of KwaZulu-Natal","active":true,"usgs":false}],"preferred":false,"id":732609,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Harpole, W. Stanley","contributorId":131024,"corporation":false,"usgs":false,"family":"Harpole","given":"W.","email":"","middleInitial":"Stanley","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":732610,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"MacDougall, Andrew S.","contributorId":203899,"corporation":false,"usgs":false,"family":"MacDougall","given":"Andrew","email":"","middleInitial":"S.","affiliations":[{"id":12660,"text":"University of Guelph","active":true,"usgs":false}],"preferred":false,"id":732611,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McCulley, Rebecca L.","contributorId":203900,"corporation":false,"usgs":false,"family":"McCulley","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":732612,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Prober, Suzanne M.","contributorId":74498,"corporation":false,"usgs":false,"family":"Prober","given":"Suzanne","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":732613,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Risch, Anita C.","contributorId":203901,"corporation":false,"usgs":false,"family":"Risch","given":"Anita","email":"","middleInitial":"C.","affiliations":[{"id":36747,"text":"Swiss Federal Institute for Forest, Snow and Landscape Research, Community Ecology","active":true,"usgs":false}],"preferred":false,"id":732614,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Sankaran, Mahesh","contributorId":203902,"corporation":false,"usgs":false,"family":"Sankaran","given":"Mahesh","email":"","affiliations":[{"id":36748,"text":"National Centre for Biological Sciences, Bangalor, India","active":true,"usgs":false}],"preferred":false,"id":732615,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Schutz, Martin","contributorId":203903,"corporation":false,"usgs":false,"family":"Schutz","given":"Martin","email":"","affiliations":[{"id":36747,"text":"Swiss Federal Institute for Forest, Snow and Landscape Research, Community Ecology","active":true,"usgs":false}],"preferred":false,"id":732616,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Seabloom, Eric W.","contributorId":60762,"corporation":false,"usgs":false,"family":"Seabloom","given":"Eric","email":"","middleInitial":"W.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":732617,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Stevens, Carly J.","contributorId":203904,"corporation":false,"usgs":false,"family":"Stevens","given":"Carly","email":"","middleInitial":"J.","affiliations":[{"id":36749,"text":"Lancaster Environment Centre, Lancaster University","active":true,"usgs":false}],"preferred":false,"id":732618,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Sullivan, Lauren","contributorId":203905,"corporation":false,"usgs":false,"family":"Sullivan","given":"Lauren","affiliations":[{"id":25341,"text":"Department of Ecology, Evolution, and Organismal Biology, Iowa State University","active":true,"usgs":false}],"preferred":false,"id":732619,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Wragg, Peter","contributorId":203906,"corporation":false,"usgs":false,"family":"Wragg","given":"Peter","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":732620,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Borer, Elizabeth T.","contributorId":45049,"corporation":false,"usgs":false,"family":"Borer","given":"Elizabeth","email":"","middleInitial":"T.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":732606,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}}
,{"id":70196367,"text":"70196367 - 2018 - Relating river discharge and water temperature to the recruitment of age‐0 White Sturgeon (Acipenser transmontanus Richardson, 1836) in the Columbia River using over‐dispersed catch data","interactions":[],"lastModifiedDate":"2018-04-04T11:04:31","indexId":"70196367","displayToPublicDate":"2018-04-04T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2166,"text":"Journal of Applied Ichthyology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Relating river discharge and water temperature to the recruitment of age‐0 White Sturgeon (<i>Acipenser transmontanus</i> Richardson, 1836) in the Columbia River using over‐dispersed catch data","title":"Relating river discharge and water temperature to the recruitment of age‐0 White Sturgeon (Acipenser transmontanus Richardson, 1836) in the Columbia River using over‐dispersed catch data","docAbstract":"<p><span>The goals were to (i) determine if river discharge and water temperature during various early life history stages were predictors of age‐0 White Sturgeon,&nbsp;</span><i>Acipenser transmontanus</i><span>, recruitment, and (ii) provide an example of how over‐dispersed catch data, including data with many zero observations, can be used to better understand the effects of regulated rivers on the productivity of depressed sturgeon populations. An information theoretic approach was used to develop and select negative binomial and zero‐inflated negative binomial models that model the relation of age‐0 White Sturgeon survey data from three contiguous Columbia River reservoirs to river discharge and water temperature during spawning, egg incubation, larval, and post‐larval phases. Age‐0 White Sturgeon were collected with small mesh gill nets in The Dalles and John Day reservoirs from 1997 to 2014 and a bottom trawl in Bonneville Reservoir from 1989 to 2006. Results suggest that seasonal river discharge was positively correlated with age‐0 recruitment; notably that discharge, 16 June–31 July was positively correlated to age‐0 recruitment in all three reservoirs. The best approximating models for two of the three reservoirs also suggest that seasonal water temperature may be a determinant of age‐0 recruitment. Our research demonstrates how over‐dispersed catch data can be used to better understand the effects of environmental conditions on sturgeon populations caused by the construction and operation of dams.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/jai.13570","usgsCitation":"Counihan, T.D., and Chapman, C.G., 2018, Relating river discharge and water temperature to the recruitment of age‐0 White Sturgeon (Acipenser transmontanus Richardson, 1836) in the Columbia River using over‐dispersed catch data: Journal of Applied Ichthyology, v. 34, no. 2, p. 279-289, https://doi.org/10.1111/jai.13570.","productDescription":"11 p.","startPage":"279","endPage":"289","ipdsId":"IP-074421","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":460965,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jai.13570","text":"Publisher Index Page"},{"id":353138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Columbia River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.12353515624999,\n              45.213003555993964\n            ],\n            [\n              -117.12524414062501,\n              45.213003555993964\n            ],\n            [\n              -117.12524414062501,\n              46.800059446787316\n            ],\n            [\n              -124.12353515624999,\n              46.800059446787316\n            ],\n            [\n              -124.12353515624999,\n              45.213003555993964\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"34","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-23","publicationStatus":"PW","scienceBaseUri":"5afee6e8e4b0da30c1bfbf33","contributors":{"authors":[{"text":"Counihan, Timothy D. 0000-0003-4967-6514 tcounihan@usgs.gov","orcid":"https://orcid.org/0000-0003-4967-6514","contributorId":4211,"corporation":false,"usgs":true,"family":"Counihan","given":"Timothy","email":"tcounihan@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Colin G.","contributorId":197963,"corporation":false,"usgs":false,"family":"Chapman","given":"Colin","email":"","middleInitial":"G.","affiliations":[{"id":36223,"text":"Oregon Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":732627,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70196387,"text":"70196387 - 2018 - China, the United States, and competition for resources that enable emerging technologies","interactions":[],"lastModifiedDate":"2018-04-24T14:16:01","indexId":"70196387","displayToPublicDate":"2018-04-04T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3165,"text":"Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"title":"China, the United States, and competition for resources that enable emerging technologies","docAbstract":"<p><span>Historically, resource conflicts have often centered on fuel minerals (particularly oil). Future resource conflicts may, however, focus more on competition for nonfuel minerals that enable emerging technologies. Whether it is rhenium in jet engines, indium in flat panel displays, or gallium in smart phones, obscure elements empower smarter, smaller, and faster technologies, and nations seek stable supplies of these and other nonfuel minerals for their industries. No nation has all of the resources it needs domestically. International trade may lead to international competition for these resources if supplies are deemed at risk or insufficient to satisfy growing demand, especially for minerals used in technologies important to economic development and national security. Here, we compare the net import reliance of China and the United States to inform mineral resource competition and foreign supply risk. Our analysis indicates that China relies on imports for over half of its consumption for 19 of 42 nonfuel minerals, compared with 24 for the United States—11 of which are common to both. It is for these 11 nonfuel minerals that competition between the United States and China may become the most contentious, especially for those with highly concentrated production that prove irreplaceable in pivotal emerging technologies.</span></p>","language":"English","publisher":"National Academy of Sciences of the United States of America","doi":"10.1073/pnas.1717152115","usgsCitation":"Gulley, A.L., Nassar, N., and Xun, S., 2018, China, the United States, and competition for resources that enable emerging technologies: Proceedings of the National Academy of Sciences of the United States of America, v. 115, no. 16, p. 4111-4115, https://doi.org/10.1073/pnas.1717152115.","productDescription":"5 p.","startPage":"4111","endPage":"4115","ipdsId":"IP-090411","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":468851,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.1073/pnas.1717152115","text":"Publisher Index Page"},{"id":353162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","issue":"16","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-02","publicationStatus":"PW","scienceBaseUri":"5afee6e8e4b0da30c1bfbf29","contributors":{"authors":[{"text":"Gulley, Andrew L. 0000-0003-4717-2080","orcid":"https://orcid.org/0000-0003-4717-2080","contributorId":203953,"corporation":false,"usgs":true,"family":"Gulley","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":732714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":177175,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal T.","email":"nnassar@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":732715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xun, Sean 0000-0002-5784-7048","orcid":"https://orcid.org/0000-0002-5784-7048","contributorId":203954,"corporation":false,"usgs":true,"family":"Xun","given":"Sean","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":732716,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70195823,"text":"fs20183012 - 2018 - Biological and ecological science for Michigan—The Great Lakes State","interactions":[],"lastModifiedDate":"2018-04-05T11:03:43","indexId":"fs20183012","displayToPublicDate":"2018-04-04T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3012","title":"Biological and ecological science for Michigan—The Great Lakes State","docAbstract":"<p>Michigan is rich in lakes, rivers, dune and rocky shorelines, forests, fish and wildlife, and has the longest freshwater coastline in the United States, 3,224 miles. Many enterprises critical to Michigan’s economy and cultural heritage are based on natural resources including commercial and sport fishing, hunting, and other outdoor recreation. Overall, outdoor recreation is enjoyed by more than 63 percent of Michigan residents, and has been estimated to generate <span>$18.7</span> billion in consumer spending, create 194,000 jobs, and raise $1.4 billion in State and local tax revenue annually.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183012","usgsCitation":"U.S. Geological Survey, 2018, Biological and ecological science for Michigan—The Great Lakes State: U.S. Geological Survey Fact Sheet 2018-3012, 2 p., https://doi.org/10.3133/fs20183012.","productDescription":"2 p.","onlineOnly":"Y","ipdsId":"IP-091846","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":353164,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3012/coverthb.jpg"},{"id":353165,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3012/fs20183012.pdf","text":"Report","size":"7.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3012"}],"country":"United 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 \"}}]}","contact":"<p><a href=\"https://www.usgs.gov/science/mission-areas/ecosystems\" target=\"blank\" data-mce-href=\"https://www.usgs.gov/science/mission-areas/ecosystems\">Ecosystems Mission Area</a><br> <a href=\"https://www.usgs.gov/ask/\" data-mce-href=\"https://www.usgs.gov/ask/\">https://www.usgs.gov/ask/</a><br> 1-800-ASK-USGS (1-800-275-8747)</p>","tableOfContents":"<ul><li>The USGS Ecosystems The USGS Ecosystems Mission Area<br></li><li>Sustaining the Michigan Great Lakes Fishery<br></li><li>Fighting a Damaging Invader<br></li><li>Bringing Back Lake Sturgeon<br></li><li>Restoration Science for Urban Revitalization<br></li><li>Sharing Information about Wildlife Diseases<br></li><li>Surveillance and Control Techniques for Unwelcome Invaders<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2018-04-04","noUsgsAuthors":false,"publicationDate":"2018-04-04","publicationStatus":"PW","scienceBaseUri":"5afee6e8e4b0da30c1bfbf37","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":730174,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70196313,"text":"ofr20171157 - 2018 - Barrier-island and estuarine-wetland physical-change assessment after Hurricane Sandy","interactions":[],"lastModifiedDate":"2025-05-13T16:22:30.827212","indexId":"ofr20171157","displayToPublicDate":"2018-04-03T10:15:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1157","title":"Barrier-island and estuarine-wetland physical-change assessment after Hurricane Sandy","docAbstract":"<h1>Introduction</h1><p>The Nation’s eastern coast is fringed by beaches, dunes, barrier islands, wetlands, and bluffs. These natural coastal barriers provide critical benefits and services, and can mitigate the impact of storms, erosion, and sea-level rise on our coastal communities. Waves and storm surge resulting from Hurricane Sandy, which made landfall along the New Jersey coast on October 29, 2012, impacted the U.S. coastline from North Carolina to Massachusetts, including Assateague Island, Maryland and Virginia, and the Delmarva coastal system. The storm impacts included changes in topography, coastal morphology, geology, hydrology, environmental quality, and ecosystems.</p><p>In the immediate aftermath of the storm, light detection and ranging (lidar) surveys from North Carolina to New York documented storm impacts to coastal barriers, providing a baseline to assess vulnerability of the reconfigured coast. The focus of much of the existing coastal change assessment is along the ocean-facing coastline; however, much of the coastline affected by Hurricane Sandy includes the estuarine-facing coastlines of barrier-island systems. Specifically, the wetland and back-barrier shorelines experienced substantial change as a result of wave action and storm surge that occurred during Hurricane Sandy (see also USGS photograph, <a href=\"http://coastal.er.usgs.gov/hurricanes/sandy/photo-comparisons/virginia.php\" data-mce-href=\"http://coastal.er.usgs.gov/hurricanes/sandy/photo-comparisons/virginia.php\">http://coastal.er.usgs.gov/hurricanes/sandy/photo-comparisons/virginia.php</a>). Assessing physical shoreline and wetland change (land loss as well as land gains) can help to determine the resiliency of wetland systems that protect adjacent habitat, shorelines, and communities.</p><p>To address storm impacts to wetlands, a vulnerability assessment should describe both long-term (for example, several decades) and short-term (for example, Sandy’s landfall) extent and character of the interior wetlands and the back-barrier-shoreline changes. The objective of this report is to describe several new wetland vulnerability assessments based on the detailed physical changes estimated from observations. The scope includes understanding changes caused by both short- and long-term processes using both remotely sensed and in situ observations to characterize changes to the wetland in terms of accretion/expansion and erosion/contraction. Accretion may be due to net vertical and (or) horizontal deposition, including estuarine-shoreline change due to overwash. Wetland erosion may be due to elevated waves and water levels in the estuary itself. We included additional information based on wave runup and storm-surge elevations based on models and elevation data. We then developed a predictive assessment for wetland vulnerability that describes the likelihood of changes of the estuarine shoreline and the landward extent of sand overwash driven by processes occurring on the ocean-facing shoreline. This assessment is intended to be linked to the beach and dune vulnerability assessments that have been developed previously.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171157","usgsCitation":"Plant, N.G., Smith, K.E.L., Passeri, D.L., Smith, C.G., and Bernier, J.C., 2018, Barrier-island and estuarine-wetland physical-change assessment after Hurricane Sandy: U.S. Geological Survey Open-File Report 2017–1157, 36 p.,  https://doi.org/10.3133/ofr20171157.","productDescription":"viii, 36 p.","numberOfPages":"45","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073468","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":353051,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1157/coverthb.jpg"},{"id":353052,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1157/ofr20171157.pdf","text":"Report","size":"7.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1157"}],"contact":"<p>Director, <a href=\"https://coastal.er.usgs.gov\" data-mce-href=\"https://coastal.er.usgs.gov\">St. Petersburg Coastal and Marine Science </a>Center<br> U.S. Geological Survey<br> 600 4th Street South<br> St. Petersburg, FL 33701</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Introduction</li><li>Methods</li><li>Results&nbsp;</li><li>Discussion</li><li>Conclusions&nbsp;</li><li>References Cited</li><li>Appendix 1. BN Models</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2018-04-03","noUsgsAuthors":false,"publicationDate":"2018-04-03","publicationStatus":"PW","scienceBaseUri":"5afee6e8e4b0da30c1bfbf39","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":732281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Kathryn E.L. 0000-0002-7521-7875 kelsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-7521-7875","contributorId":173264,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E.L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":732282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Passeri, Davina 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":732283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Christopher G. 0000-0002-8075-4763 cgsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":3410,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":732284,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bernier, Julie 0000-0002-9918-5353 jbernier@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-5353","contributorId":3549,"corporation":false,"usgs":true,"family":"Bernier","given":"Julie","email":"jbernier@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":732285,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196228,"text":"ofr20181050 - 2018 - Passage survival of juvenile steelhead, coho salmon, and Chinook salmon in Lake Scanewa and at Cowlitz Falls Dam, Cowlitz River, Washington, 2010–16","interactions":[],"lastModifiedDate":"2018-04-04T10:20:34","indexId":"ofr20181050","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1050","title":"Passage survival of juvenile steelhead, coho salmon, and Chinook salmon in Lake Scanewa and at Cowlitz Falls Dam, Cowlitz River, Washington, 2010–16","docAbstract":"<p class=\"p1\">A multi-year evaluation was conducted during 2010–16 to evaluate passage survival of juvenile steelhead (<i>Oncorhynchus mykiss</i>), Chinook salmon (<i>O. tshawytscha</i>), and coho salmon (<i>O. kisutch</i>) in Lake Scanewa, and at Cowlitz Falls Dam in the upper Cowlitz River Basin, Washington. Reservoir passage survival was evaluated in 2010, 2011, and 2016, and included the tagging and release of 1,127 juvenile salmonids. Tagged fish were released directly into the Cowlitz and Cispus Rivers, 22.3 and 8.9 km, respectively, upstream of the reservoir, and were monitored as they moved downstream into, and through the reservoir. A single release-recapture survival model was used to analyze detection records and estimate reservoir passage survival, which was defined as successful passage from reservoir entry to arrival at Cowlitz Falls Dam. Tagged fish generally moved quickly downstream of the release sites and, on average, arrived in the dam forebay within 2 d of release. Median travel time from release to first detection at the dam ranged from 0.23 to 0.96 d for juvenile steelhead, from 0.15 to 1.11 d for juvenile coho salmon, and from 0.18 to 1.89 d for juvenile Chinook salmon. Minimum reservoir passage survival probabilities were 0.960 for steelhead, 0.855 for coho salmon and 0.900 for Chinook salmon.</p><p class=\"p1\">Dam passage survival was evaluated at the pilot-study level during 2013–16 and included the tagging and release of 2,512 juvenile salmonids. Juvenile Chinook salmon were evaluated during 2013–14, and juvenile steelhead and coho salmon were evaluated during 2015–16. A paired-release study design was used that included release sites located upstream and downstream of Cowlitz Falls Dam. The downstream release site was positioned at the downstream margin of the dam’s tailrace, which allowed dam passage survival to be measured in a manner that included mortality that occurred in the passage route and in the dam tailrace. More than one-half of the tagged Chinook salmon (52 percent) released upstream of Cowlitz Falls Dam moved downstream and passed the project; the remaining fish either remained upstream of the dam (37 percent) or were collected (11 percent). In 2015 and 2016, collection efficiencies at Cowlitz Falls Dam were abnormally high for juvenile steelhead and coho salmon, which resulted in few fish passing the dam. Seven percent of the tagged steelhead (40 fish) and 4 percent of the tagged coho salmon (18 fish) released upstream of the dam eventually passed the project, but these low numbers of fish precluded the estimation of meaningful survival estimates. Dam passage survival probability estimates for juvenile Chinook salmon were 0.828 in 2013 and 0.861 in 2014, lower than previously reported for turbine-specific passage Cowlitz Falls Dam.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181050","collaboration":"Prepared in cooperation with the Lewis County Public Utility District, Washington","usgsCitation":"Liedtke, T.L., Kock, T.J., and Hurst, W., 2018, Passage survival of juvenile steelhead, coho salmon, and Chinook salmon in Lake Scanewa and at Cowlitz Falls Dam, Cowlitz River, Washington, 2010–16: U.S. Geological Survey Open-File Report 2018-1050, 44 p., https://doi.org/10.3133/ofr20181050.","productDescription":"viii, 44 p.","numberOfPages":"56","onlineOnly":"Y","ipdsId":"IP-094272","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":353112,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1050/ofr20181050.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1050"},{"id":353111,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1050/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Cowlitz Falls Dam, Cowlitz River, Lake Scanewa","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.1844482421875,\n              46.42129253514276\n            ],\n            [\n              -121.94549560546875,\n              46.42129253514276\n            ],\n            [\n              -121.94549560546875,\n              46.53477563383562\n            ],\n            [\n              -122.1844482421875,\n              46.53477563383562\n            ],\n            [\n              -122.1844482421875,\n              46.42129253514276\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://wfrc.usgs.gov/\" target=\"blank\" data-mce-href=\"https://wfrc.usgs.gov/\">Western Fisheries Research Center</a><br> U.S. Geological Survey<br> 6505 NE 65th Street<br> Seattle, Washington 98115</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Chapter A. Reservoir Passage Survival of Juvenile Steelhead, Coho Salmon, and Chinook Salmon in Lake Scanewa, Upper Cowlitz River, Washington, 2010, 2011, and 2016&nbsp;<br></li><li>Chapter B. Dam Passage Survival of Juvenile Steelhead, Coho Salmon, and Chinook Salmon at Cowlitz Falls Dam, Cowlitz River, Washington, 2013-16<br></li><li>Appendix 1. Summary of Radio Transmitter Failures Associated with the 2016 Cowlitz River Evaluations<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2018-04-03","noUsgsAuthors":false,"publicationDate":"2018-04-03","publicationStatus":"PW","scienceBaseUri":"5afee6eae4b0da30c1bfbf53","contributors":{"authors":[{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":731754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":731755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hurst, William 0000-0001-5758-8210 whurst@usgs.gov","orcid":"https://orcid.org/0000-0001-5758-8210","contributorId":139838,"corporation":false,"usgs":true,"family":"Hurst","given":"William","email":"whurst@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":731756,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196338,"text":"70196338 - 2018 - The GFDL global atmosphere and land model AM4.0/LM4.0: 1. Simulation characteristics with prescribed SSTs","interactions":[],"lastModifiedDate":"2018-04-24T14:18:31","indexId":"70196338","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5407,"text":"Journal of Advances in Modeling Earth Systems","active":true,"publicationSubtype":{"id":10}},"title":"The GFDL global atmosphere and land model AM4.0/LM4.0: 1. Simulation characteristics with prescribed SSTs","docAbstract":"<p><span>In this two‐part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100 km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part 1, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode—with prescribed sea surface temperatures (SSTs) and sea‐ice distribution—is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. The model's Cess sensitivity (response in the top‐of‐atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part 2, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017MS001208","usgsCitation":"Zhao, M., Golaz, J., Held, I.M., Guo, H., Balaji, V., Benson, R., Chen, J., Chen, X., Donner, L.J., Dunne, J.P., Dunne, K.A., Durachta, J., Fan, S., Freidenreich, S., Garner, S.T., Ginoux, P., Harris, L.M., Horowitz, L.W., Krasting, J., Langenhorst, A.R., Liang, Z., Lin, P., Lin, S., Malyshev, S.L., Mason, E., Milly, P., Ming, Y., Naik, V., Paulot, F., Paynter, D., Phillipps, P., Radhakrishnan, A., Ramaswamy, V., Robinson, T., Schwarzkopf, D., Seman, C., Shevliakova, E., Shen, Z., Shin, H., Silvers, L., Wilson, J.R., Winton, M., Wittenberg, A.T., Wyman, B., and Xiang, B., 2018, The GFDL global atmosphere and land model AM4.0/LM4.0: 1. Simulation characteristics with prescribed SSTs: Journal of Advances in Modeling Earth Systems, v. 10, no. 3, p. 735-769, https://doi.org/10.1002/2017MS001208.","productDescription":"35 p.","startPage":"735","endPage":"769","ipdsId":"IP-090444","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468858,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017ms001208","text":"Publisher Index Page"},{"id":353088,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-15","publicationStatus":"PW","scienceBaseUri":"5afee6eae4b0da30c1bfbf4b","contributors":{"authors":[{"text":"Zhao, M.","contributorId":203806,"corporation":false,"usgs":false,"family":"Zhao","given":"M.","email":"","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":732386,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Golaz, J.-C.","contributorId":203807,"corporation":false,"usgs":false,"family":"Golaz","given":"J.-C.","email":"","affiliations":[{"id":36725,"text":"GFDL/NOAA; Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":732387,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Held, I. 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,{"id":70196336,"text":"70196336 - 2018 - The aerosphere as a network connector of organisms and their diseases","interactions":[],"lastModifiedDate":"2018-04-03T11:45:55","indexId":"70196336","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"The aerosphere as a network connector of organisms and their diseases","docAbstract":"<p><span>Aeroecological processes, especially powered flight of animals, can rapidly connect biological communities across the globe. This can have profound consequences for evolutionary diversification, energy and nutrient transfers, and the spread of infectious diseases. The latter is of particular consequence for human populations, since migratory birds are known to host diseases which have a history of transmission into domestic poultry or even jumping to human hosts. In this chapter, we present a scenario under which a highly pathogenic avian influenza (HPAI) strain enters North America from East Asia via post-molting waterfowl migration. We use an agent-based model (ABM) to simulate the movement and disease transmission among 10</span><sup>6</sup><span><span>&nbsp;</span>generalized waterfowl agents originating from ten molting locations in eastern Siberia, with the HPAI seeded in only ~10</span><sup>2</sup><span><span>&nbsp;</span>agents at one of these locations. Our ABM tracked the disease dynamics across a very large grid of sites as well as individual agents, allowing us to examine the spatiotemporal patterns of change in virulence of the HPAI infection as well as waterfowl host susceptibility to the disease. We concurrently simulated a 12-station disease monitoring network in the northwest USA and Canada in order to assess the potential efficacy of these sites to detect and confirm the arrival of HPAI. Our findings indicated that HPAI spread was initially facilitated but eventually subdued by the migration of host agents. Yet, during the 90-day simulation, selective pressures appeared to have distilled the HPAI strain to its most virulent form (i.e., through natural selection), which was counterbalanced by the host susceptibility being conversely reduced (i.e., through genetic predisposition and acquired immunity). The monitoring network demonstrated wide variation in the utility of sites; some were clearly better at providing early warnings of HPAI arrival, while sites further from the disease origin exposed the selective dynamics which slowed the spread of the disease albeit with the result of passing highly virulent strains into southern wintering locales (where human impacts are more likely). Though the ABM presented had generalized waterfowl migration and HPAI disease dynamics, this exercise demonstrates the power of such simulations to examine the extremely large and complex processes which comprise aeroecology. We offer insights into how such models could be further parameterized to represent HPAI transmission risks as well as how ABMs could be applied to other aeroecological questions pertaining to individual-based connectivity.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Aeroecology","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-68576-2_17","usgsCitation":"Ross, J.D., Bridge, E.S., Prosser, D.J., and Takekawa, J., 2018, The aerosphere as a network connector of organisms and their diseases, chap. <i>of</i> Aeroecology, p. 427-464, https://doi.org/10.1007/978-3-319-68576-2_17.","productDescription":"38 p.","startPage":"427","endPage":"464","ipdsId":"IP-072061","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":353096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-24","publicationStatus":"PW","scienceBaseUri":"5afee6eae4b0da30c1bfbf4d","contributors":{"authors":[{"text":"Ross, Jeremy D.","contributorId":189958,"corporation":false,"usgs":false,"family":"Ross","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":732378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bridge, Eli S.","contributorId":203804,"corporation":false,"usgs":false,"family":"Bridge","given":"Eli","email":"","middleInitial":"S.","affiliations":[{"id":36723,"text":"Oklahoma Biological Survey, University of Oklahoma, Norman, OK","active":true,"usgs":false}],"preferred":false,"id":732379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":732377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takekawa, John Y. 0000-0003-0217-5907","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":203805,"corporation":false,"usgs":false,"family":"Takekawa","given":"John Y.","affiliations":[{"id":36724,"text":"Audubon California, Richardson Bay Audubon Center and Sanctuary, Tiburon, CA","active":true,"usgs":false}],"preferred":false,"id":732380,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196339,"text":"70196339 - 2018 - The GFDL global atmosphere and land model AM4.0/LM4.0: 2. Model description, sensitivity studies, and tuning strategies","interactions":[],"lastModifiedDate":"2018-04-27T16:34:43","indexId":"70196339","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5407,"text":"Journal of Advances in Modeling Earth Systems","active":true,"publicationSubtype":{"id":10}},"title":"The GFDL global atmosphere and land model AM4.0/LM4.0: 2. Model description, sensitivity studies, and tuning strategies","docAbstract":"<p><span>In Part 2 of this two‐part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part 1. Part 2 provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017MS001209","usgsCitation":"Zhao, M., Golaz, J., Held, I.M., Guo, H., Balaji, V., Benson, R., Chen, J., Chen, X., Donner, L.J., Dunne, J.P., Dunne, K.A., Durachta, J., Fan, S., Freidenreich, S., Garner, S.T., Ginoux, P., Harris, L.M., Horowitz, L.W., Krasting, J., Langenhorst, A.R., Liang, Z., Lin, P., Lin, S., Malyshev, S., Mason, E., Milly, P., Ming, Y., Naik, V., Paulot, F., Paynter, D., Phillipps, P., Radhakrishnan, A., Ramaswamy, V., Robinson, T., Schwarzkopf, D., Seman, C., Shevliakova, E., Shen, Z., Shin, H., Silvers, L., Wilson, J.R., Winton, M., Wittenberg, A.T., Wyman, B., and Xiang, B., 2018, The GFDL global atmosphere and land model AM4.0/LM4.0: 2. Model description, sensitivity studies, and tuning strategies: Journal of Advances in Modeling Earth Systems, v. 10, no. 3, p. 691-734, https://doi.org/10.1002/2017MS001209.","productDescription":"44 p.","startPage":"691","endPage":"734","ipdsId":"IP-090445","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468856,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017ms001209","text":"Publisher Index Page"},{"id":353087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-15","publicationStatus":"PW","scienceBaseUri":"5afee6eae4b0da30c1bfbf49","contributors":{"authors":[{"text":"Zhao, M.","contributorId":203806,"corporation":false,"usgs":false,"family":"Zhao","given":"M.","email":"","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":732431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Golaz, J.-C.","contributorId":203807,"corporation":false,"usgs":false,"family":"Golaz","given":"J.-C.","email":"","affiliations":[{"id":36725,"text":"GFDL/NOAA; Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":732432,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Held, I. 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,{"id":70196325,"text":"70196325 - 2018 - Size‐assortative choice and mate availability influences hybridization between red wolves (Canis rufus) and coyotes (Canis latrans)","interactions":[],"lastModifiedDate":"2018-04-27T16:33:54","indexId":"70196325","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Size‐assortative choice and mate availability influences hybridization between red wolves (<i>Canis rufus</i>) and coyotes (<i>Canis latrans</i>)","title":"Size‐assortative choice and mate availability influences hybridization between red wolves (Canis rufus) and coyotes (Canis latrans)","docAbstract":"<p><span>Anthropogenic hybridization of historically isolated taxa has become a primary conservation challenge for many imperiled species. Indeed, hybridization between red wolves (</span><i>Canis rufus</i><span>) and coyotes (</span><i>Canis latrans</i><span>) poses a significant challenge to red wolf recovery. We considered seven hypotheses to assess factors influencing hybridization between red wolves and coyotes via pair‐bonding between the two species. Because long‐term monogamy and defense of all‐purpose territories are core characteristics of both species, mate choice has long‐term consequences. Therefore, red wolves may choose similar‐sized mates to acquire partners that behave similarly to themselves in the use of space and diet. We observed multiple factors influencing breeding pair formation by red wolves and found that most wolves paired with similar‐sized conspecifics and wolves that formed congeneric pairs with nonwolves (coyotes and hybrids) were mostly female wolves, the smaller of the two sexes. Additionally, we observed that lower red wolf abundance relative to nonwolves and the absence of helpers increased the probability that wolves consorted with nonwolves. However, successful pairings between red wolves and nonwolves were associated with wolves that maintained small home ranges. Behaviors associated with territoriality are energetically demanding and behaviors (e.g., aggressive interactions, foraging, and space use) involved in maintaining territories are influenced by body size. Consequently, we propose the hypothesis that size disparities between consorting red wolves and coyotes influence positive assortative mating and may represent a reproductive barrier between the two species. We offer that it may be possible to maintain wild populations of red wolves in the presence of coyotes if management strategies increase red wolf abundance on the landscape by mitigating key threats, such as human‐caused mortality and hybridization with coyotes. Increasing red wolf abundance would likely restore selection pressures that increase mean body and home‐range sizes of red wolves and decrease hybridization rates via reduced occurrence of congeneric pairs.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3950","usgsCitation":"Hinton, J.W., Gittleman, J.L., van Manen, F.T., and Chamberlain, M.J., 2018, Size‐assortative choice and mate availability influences hybridization between red wolves (Canis rufus) and coyotes (Canis latrans): Ecology and Evolution, v. 8, no. 8, p. 3927-3940, https://doi.org/10.1002/ece3.3950.","productDescription":"14 p.","startPage":"3927","endPage":"3940","ipdsId":"IP-082308","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":460968,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3950","text":"Publisher Index Page"},{"id":353090,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-23","publicationStatus":"PW","scienceBaseUri":"5afee6eae4b0da30c1bfbf51","contributors":{"authors":[{"text":"Hinton, Joseph W.","contributorId":179346,"corporation":false,"usgs":false,"family":"Hinton","given":"Joseph","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":732328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gittleman, John L.","contributorId":190533,"corporation":false,"usgs":false,"family":"Gittleman","given":"John","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":732330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":732327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chamberlain, Michael J.","contributorId":179350,"corporation":false,"usgs":false,"family":"Chamberlain","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":732329,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196345,"text":"70196345 - 2018 - Rising synchrony controls western North American ecosystems","interactions":[],"lastModifiedDate":"2018-05-21T13:13:21","indexId":"70196345","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","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":"Rising synchrony controls western North American ecosystems","docAbstract":"<p><span>Along the western margin of North America, the winter expression of the North Pacific High (NPH) strongly influences interannual variability in coastal upwelling, storm track position, precipitation, and river discharge. Coherence among these factors induces covariance among physical and biological processes across adjacent marine and terrestrial ecosystems. Here, we show that over the past century the degree and spatial extent of this covariance (synchrony) has substantially increased, and is coincident with rising variance in the winter NPH. Furthermore, centuries‐long blue oak (</span><i>Quercus douglasii</i><span>) growth chronologies sensitive to the winter NPH provide robust evidence that modern levels of synchrony are among the highest observed in the context of the last 250 years. These trends may ultimately be linked to changing impacts of the El Niño Southern Oscillation on mid‐latitude ecosystems of North America. Such a rise in synchrony may destabilize ecosystems, expose populations to higher risks of extinction, and is thus a concern given the broad biological relevance of winter climate to biological systems.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.14128","usgsCitation":"Black, B.A., van der Sleen, P., Di Lorenzo, E., Griffin, D., Sydeman, W., Dunham, J.B., Rykaczewski, R.R., Garcia-Reyes, M., Safeeq, M., Arismendi, I., and Bograd, S.J., 2018, Rising synchrony controls western North American ecosystems: Global Change Biology, v. 24, no. 6, p. 2305-2314, https://doi.org/10.1111/gcb.14128.","productDescription":"10 p.","startPage":"2305","endPage":"2314","ipdsId":"IP-091880","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":468855,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gcb.14128","text":"External 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J.","affiliations":[],"preferred":false,"id":732504,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":365,"text":"Leetown Science Center","active":true,"usgs":true},{"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}],"preferred":true,"id":732499,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rykaczewski, Ryan R.","contributorId":203863,"corporation":false,"usgs":false,"family":"Rykaczewski","given":"Ryan","email":"","middleInitial":"R.","affiliations":[{"id":36734,"text":"Department of Biological Sciences and Marine Science Program, University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":732505,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Garcia-Reyes, Marisol","contributorId":201043,"corporation":false,"usgs":false,"family":"Garcia-Reyes","given":"Marisol","affiliations":[],"preferred":false,"id":732506,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Safeeq, Mohammad 0000-0003-0529-3925","orcid":"https://orcid.org/0000-0003-0529-3925","contributorId":77814,"corporation":false,"usgs":false,"family":"Safeeq","given":"Mohammad","email":"","affiliations":[{"id":6641,"text":"University of California at Merced","active":true,"usgs":false}],"preferred":false,"id":732507,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Arismendi, Ivan 0000-0002-8774-9350","orcid":"https://orcid.org/0000-0002-8774-9350","contributorId":202207,"corporation":false,"usgs":false,"family":"Arismendi","given":"Ivan","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":732508,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bograd, Steven J.","contributorId":203864,"corporation":false,"usgs":false,"family":"Bograd","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":36735,"text":"NOAA, Southwest Fisheries Science Center, Environmental Research Division","active":true,"usgs":false}],"preferred":false,"id":732509,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70196335,"text":"70196335 - 2018 - An epidemiological model of virus transmission in salmonid fishes of the Columbia River Basin","interactions":[],"lastModifiedDate":"2018-04-03T11:10:18","indexId":"70196335","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"An epidemiological model of virus transmission in salmonid fishes of the Columbia River Basin","docAbstract":"<p><span>We have developed a dynamic epidemiological model informed by records of viral presence and genotypes to evaluate potential transmission routes maintaining a viral pathogen in economically and culturally important anadromous fish populations. In the Columbia River Basin, infectious hematopoietic necrosis virus (IHNV) causes severe disease, predominantly in juvenile steelhead trout (</span><i>Oncorhynchus mykiss</i><span>) and less frequently in Chinook salmon (</span><i>O. tshawytscha</i><span>). Mortality events following IHNV infection can be devastating for individual hatchery programs. Despite reports of high local mortality and extensive surveillance efforts, there are questions about how viral transmission is maintained. Modeling this system offers important insights into disease transmission in natural aquatic systems, as well as about the data requirements for generating accurate estimates about transmission routes and infection probabilities. We simulated six scenarios in which testing rates and the relative importance of different transmission routes varied. The simulations demonstrated that the model accurately identified routes of transmission and inferred infection probabilities accurately when there was testing of all cohort-sites. When testing records were incomplete, the model accurately inferred which transmission routes exposed particular cohort-sites but generated biased infection probabilities given exposure. After validating the model and generating guidelines for result interpretation, we applied the model to data from 14 annual cohorts (2000–2013) at 24 focal sites in a sub-region of the Columbia River Basin, the lower Columbia River (LCR), to quantify the relative importance of potential transmission routes in this focal sub-region. We demonstrate that exposure to IHNV via the return migration of adult fish is an important route for maintaining IHNV in the LCR sub-region, and the probability of infection following this exposure was relatively high at 0.16. Although only 1% of cohort-sites experienced self-exposure by infected juvenile fish, this transmission route had the greatest probability of infection (0.22). Increased testing and/or determining whether transmission can occur from cohort-sites without testing records (e.g., determining there was no testing record because there were no fish at the cohort-site) are expected to improve inference about infection probabilities. Increased use of secure water supplies and continued use of biosecurity protocols may reduce IHNV transmission from adult fish and juvenile fish within the site, respectively, to juvenile salmonids at hatcheries. Models and conclusions from this study are potentially relevant to understanding the relative importance of transmission routes for other important aquatic pathogens in salmonids, including the agents of bacterial kidney disease and coldwater disease, and the basic approach may be useful for other pathogens and hosts in other geographic regions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2018.03.002","usgsCitation":"Ferguson, P.F., Breyta, R., Brito, I.L., Kurath, G., and LaDeau, S.L., 2018, An epidemiological model of virus transmission in salmonid fishes of the Columbia River Basin: Ecological Modelling, v. 377, p. 1-15, https://doi.org/10.1016/j.ecolmodel.2018.03.002.","productDescription":"15 p.","startPage":"1","endPage":"15","ipdsId":"IP-091422","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468859,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2018.03.002","text":"Publisher Index Page"},{"id":353082,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"377","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6eae4b0da30c1bfbf4f","contributors":{"authors":[{"text":"Ferguson, Paige F. B.","contributorId":203803,"corporation":false,"usgs":false,"family":"Ferguson","given":"Paige","email":"","middleInitial":"F. B.","affiliations":[{"id":36722,"text":"Department of Biological Sciences, University of Alabama, Box 870344, Tuscaloosa, AL 35487","active":true,"usgs":false}],"preferred":false,"id":732373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breyta, Rachel","contributorId":150355,"corporation":false,"usgs":false,"family":"Breyta","given":"Rachel","affiliations":[],"preferred":false,"id":732374,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brito, Ilana L.","contributorId":177102,"corporation":false,"usgs":false,"family":"Brito","given":"Ilana","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":732375,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kurath, Gael 0000-0003-3294-560X gkurath@usgs.gov","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":2629,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","email":"gkurath@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LaDeau, Shannon L.","contributorId":172640,"corporation":false,"usgs":false,"family":"LaDeau","given":"Shannon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":732376,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196349,"text":"70196349 - 2018 - Linking animals aloft with the terrestrial landscape","interactions":[],"lastModifiedDate":"2018-04-03T12:01:24","indexId":"70196349","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Linking animals aloft with the terrestrial landscape","docAbstract":"<p><span>Despite using the aerosphere for many facets of their life, most flying animals (i.e., birds, bats, some insects) are still bound to terrestrial habitats for resting, feeding, and reproduction. Comprehensive broad-scale observations by weather surveillance radars of animals as they leave terrestrial habitats for migration or feeding flights can be used to map their terrestrial distributions either as point locations (e.g., communal roosts) or as continuous surface layers (e.g., animal densities in habitats across a landscape). We discuss some of the technical challenges to reducing measurement biases related to how radars sample the aerosphere and the flight behavior of animals. We highlight a recently developed methodological approach that precisely and quantitatively links the horizontal spatial structure of birds aloft to their terrestrial distributions and provides novel insights into avian ecology and conservation across broad landscapes. Specifically, we present case studies that (1) elucidate how migrating birds contend with crossing ecological barriers and extreme weather events, (2) identify important stopover areas and habitat use patterns of birds along their migration routes, and (3) assess waterfowl response to wetland habitat management and restoration. These studies aid our understanding of how anthropogenic modification of the terrestrial landscape (e.g., urbanization, habitat management), natural geographic features, and weather (e.g., hurricanes) can affect the terrestrial distributions of flying animals.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Aeroecology","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-68576-2_14","usgsCitation":"Buler, J.J., Barrow, W., Boone, M., Dawson, D.K., Diehl, R.H., Moore, F.R., Randall, L.A., Schreckengost, T., and Smolinsky, J.A., 2018, Linking animals aloft with the terrestrial landscape, chap. <i>of</i> Aeroecology, p. 347-378, https://doi.org/10.1007/978-3-319-68576-2_14.","productDescription":"32 p.","startPage":"347","endPage":"378","ipdsId":"IP-072437","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":353099,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-24","publicationStatus":"PW","scienceBaseUri":"5afee6e9e4b0da30c1bfbf43","contributors":{"authors":[{"text":"Buler, Jeffrey J.","contributorId":194648,"corporation":false,"usgs":false,"family":"Buler","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":732526,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barrow, Wylie C. Jr. 0000-0003-4671-2823 barroww@usgs.gov","orcid":"https://orcid.org/0000-0003-4671-2823","contributorId":168953,"corporation":false,"usgs":true,"family":"Barrow","given":"Wylie C.","suffix":"Jr.","email":"barroww@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":732528,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boone, Matthew","contributorId":202724,"corporation":false,"usgs":false,"family":"Boone","given":"Matthew","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":732527,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dawson, Deanna K. 0000-0001-7531-212X ddawson@usgs.gov","orcid":"https://orcid.org/0000-0001-7531-212X","contributorId":202720,"corporation":false,"usgs":true,"family":"Dawson","given":"Deanna","email":"ddawson@usgs.gov","middleInitial":"K.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":732525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diehl, Robert H. 0000-0001-9141-1734 rhdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9141-1734","contributorId":3396,"corporation":false,"usgs":true,"family":"Diehl","given":"Robert","email":"rhdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":732529,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moore, Frank R.","contributorId":54582,"corporation":false,"usgs":false,"family":"Moore","given":"Frank","email":"","middleInitial":"R.","affiliations":[{"id":12981,"text":"Department of Biological Sciences, University of Southern Mississippi","active":true,"usgs":false}],"preferred":false,"id":732530,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Randall, Lori A. 0000-0003-0100-994X randalll@usgs.gov","orcid":"https://orcid.org/0000-0003-0100-994X","contributorId":2678,"corporation":false,"usgs":true,"family":"Randall","given":"Lori","email":"randalll@usgs.gov","middleInitial":"A.","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":732531,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schreckengost, Timothy","contributorId":203867,"corporation":false,"usgs":false,"family":"Schreckengost","given":"Timothy","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":732532,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smolinsky, Jaclyn A.","contributorId":202723,"corporation":false,"usgs":false,"family":"Smolinsky","given":"Jaclyn","email":"","middleInitial":"A.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":732533,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70196348,"text":"70196348 - 2018 - On the sensitivity of annual streamflow to air temperature","interactions":[],"lastModifiedDate":"2018-05-29T13:33:20","indexId":"70196348","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"On the sensitivity of annual streamflow to air temperature","docAbstract":"<p><span>Although interannual streamflow variability is primarily a result of precipitation variability, temperature also plays a role. The relative weakness of the temperature effect at the annual time scale hinders understanding, but may belie substantial importance on climatic time scales. Here we develop and evaluate a simple theory relating variations of streamflow and evapotranspiration (</span><i>E</i><span>) to those of precipitation (</span><i>P</i><span>) and temperature. The theory is based on extensions of the Budyko water‐balance hypothesis, the Priestley‐Taylor theory for potential evapotranspiration (<span>&nbsp;</span></span><img class=\"section_image\" src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/7d1c7e98-ad4b-4606-94ff-30efa78ad609/wrcr23194-math-0001.png\" alt=\"urn:x-wiley:00431397:media:wrcr23194:wrcr23194-math-0001\" data-mce-src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/7d1c7e98-ad4b-4606-94ff-30efa78ad609/wrcr23194-math-0001.png\"><span>), and a linear model of interannual basin storage. The theory implies that the temperature affects streamflow by modifying evapotranspiration through a Clausius‐Clapeyron‐like relation and through the sensitivity of net radiation to temperature. We apply and test (1) a previously introduced “strong” extension of the Budyko hypothesis, which requires that the function linking temporal variations of the evapotranspiration ratio (</span><i>E</i><span>/</span><i>P</i><span>) and the index of dryness (<span>&nbsp;</span></span><img class=\"section_image\" src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/b37d04ed-1f7f-4f14-86d6-d356a5da08b9/wrcr23194-math-0002.png\" alt=\"urn:x-wiley:00431397:media:wrcr23194:wrcr23194-math-0002\" data-mce-src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/b37d04ed-1f7f-4f14-86d6-d356a5da08b9/wrcr23194-math-0002.png\"><span>/</span><i>P</i><span>) at an annual time scale is identical to that linking interbasin variations of the corresponding long‐term means, and (2) a “weak” extension, which requires only that the annual evapotranspiration ratio depends uniquely on the annual index of dryness, and that the form of that dependence need not be known a priori nor be identical across basins. In application of the weak extension, the readily observed sensitivity of streamflow to precipitation contains crucial information about the sensitivity to potential evapotranspiration and, thence, to temperature. Implementation of the strong extension is problematic, whereas the weak extension appears to capture essential controls of the temperature effect efficiently.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017WR021970","usgsCitation":"Milly, P., Kam, J., and Dunne, K.A., 2018, On the sensitivity of annual streamflow to air temperature: Water Resources Research, v. 54, no. 4, p. 2624-2641, https://doi.org/10.1002/2017WR021970.","productDescription":"18 p.","startPage":"2624","endPage":"2641","ipdsId":"IP-091187","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":437966,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7SJ1JVG","text":"USGS data release","linkHelpText":"Monthly Time Series of Streamflow, Precipitation, Air Temperature, and Net Radiation for 2,673 River Basins Worldwide, 1901-2013"},{"id":437965,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7SN085V","text":"USGS data release","linkHelpText":"Annual Streamflow Sensitivity to Air Temperature Worldwide, 1901-2013"},{"id":353101,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-02","publicationStatus":"PW","scienceBaseUri":"5afee6eae4b0da30c1bfbf45","contributors":{"authors":[{"text":"Milly, Paul C.D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":2119,"corporation":false,"usgs":true,"family":"Milly","given":"Paul C.D.","email":"cmilly@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":732522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kam, Jonghun 0000-0002-7967-7705","orcid":"https://orcid.org/0000-0002-7967-7705","contributorId":203859,"corporation":false,"usgs":false,"family":"Kam","given":"Jonghun","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":732523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunne, Krista A. 0000-0002-1220-6140 kadunne@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-6140","contributorId":203816,"corporation":false,"usgs":true,"family":"Dunne","given":"Krista","email":"kadunne@usgs.gov","middleInitial":"A.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":732524,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196360,"text":"70196360 - 2018 - Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity","interactions":[],"lastModifiedDate":"2018-04-03T14:09:14","indexId":"70196360","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity","docAbstract":"<p><span>One of the primary goals of biological assessment of streams is to identify which of a suite of chemical stressors is limiting their ecological potential. Elevated metal concentrations in streams are often associated with low pH, yet the effects of these two potentially limiting factors of freshwater biodiversity are rarely considered to interact beyond the effects of pH on metal speciation. Using a dataset from two continents, a biogeochemical model of the toxicity of metal mixtures (Al, Cd, Cu, Pb, Zn) and quantile regression, we addressed the relative importance of both pH and metals as limiting factors for macroinvertebrate communities. Current environmental quality standards for metals proved to be protective of stream macroinvertebrate communities and were used as a starting point to assess metal mixture toxicity. A model of metal mixture toxicity accounting for metal interactions was a better predictor of macroinvertebrate responses than a model considering individual metal toxicity. We showed that the direct limiting effect of pH on richness was of the same magnitude as that of chronic metal toxicity, independent of its influence on the availability and toxicity of metals. By accounting for the direct effect of pH on macroinvertebrate communities, we were able to determine that acidic streams supported less diverse communities than neutral streams even when metals were below no-effect thresholds. Through a multivariate quantile model, we untangled the limiting effect of both pH and metals and predicted the maximum diversity that could be expected at other sites as a function of these variables. This model can be used to identify which of the two stressors is more limiting to the ecological potential of running waters.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2017.12.097","usgsCitation":"Fornaroli, R., Ippolito, A., Tolkkinen, M.J., Mykra, H., Muotka, T., Balistrieri, L.S., and Schmidt, T., 2018, Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity: Environmental Pollution, v. 235, p. 889-898, https://doi.org/10.1016/j.envpol.2017.12.097.","productDescription":"10 p.","startPage":"889","endPage":"898","ipdsId":"IP-079637","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":437964,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7R20ZJW","text":"USGS data release","linkHelpText":"Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity: datasets"},{"id":353113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"235","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6e9e4b0da30c1bfbf3d","contributors":{"authors":[{"text":"Fornaroli, Riccardo","contributorId":201354,"corporation":false,"usgs":false,"family":"Fornaroli","given":"Riccardo","email":"","affiliations":[],"preferred":false,"id":732575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ippolito, Alessio","contributorId":201355,"corporation":false,"usgs":false,"family":"Ippolito","given":"Alessio","email":"","affiliations":[],"preferred":false,"id":732576,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tolkkinen, Mari J.","contributorId":201357,"corporation":false,"usgs":false,"family":"Tolkkinen","given":"Mari","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":732578,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mykra, Heikki","contributorId":201358,"corporation":false,"usgs":false,"family":"Mykra","given":"Heikki","email":"","affiliations":[],"preferred":false,"id":732579,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Muotka, Timo","contributorId":201359,"corporation":false,"usgs":false,"family":"Muotka","given":"Timo","email":"","affiliations":[],"preferred":false,"id":732580,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Balistrieri, Laurie S. 0000-0002-6359-3849 balistri@usgs.gov","orcid":"https://orcid.org/0000-0002-6359-3849","contributorId":1406,"corporation":false,"usgs":true,"family":"Balistrieri","given":"Laurie","email":"balistri@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":732574,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":1300,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis S.","email":"tschmidt@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":732577,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70194741,"text":"sir20175155 - 2018 - Hydrologic assessment and numerical simulation of groundwater flow, San Juan Mine, San Juan County, New Mexico, 2010–13","interactions":[],"lastModifiedDate":"2018-04-09T15:08:19","indexId":"sir20175155","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5155","title":"Hydrologic assessment and numerical simulation of groundwater flow, San Juan Mine, San Juan County, New Mexico, 2010–13","docAbstract":"<p>Coal combustion byproducts (CCBs), which are composed of fly ash, bottom ash, and flue gas desulfurization material, produced at the coal-fired San Juan Generating Station (SJGS), located in San Juan County, New Mexico, have been buried in former surface-mine pits at the San Juan Mine, also referred to as the San Juan Coal Mine, since operations began in the early 1970s. This report, prepared by the U.S. Geological Survey in cooperation with the Mining and Minerals Division of the New Mexico Energy, Minerals and Natural Resources Department, describes results of a hydrogeologic assessment, including numerical groundwater modeling, to identify the timing of groundwater recovery and potential pathways for groundwater transport of metals that may be leached from stored CCBs and reach hydrologic receptors after operations cease. Data collected for the hydrologic assessment indicate that groundwater in at least one centrally located reclaimed surface-mining pit has already begun to recover.</p><p>The U.S. Geological Survey numerical modeling package&nbsp;MODFLOW–NWT was used with MODPATH particle-tracking software to identify advective flow paths from CCB storage areas toward potential hydrologic receptors.&nbsp;Results indicate that groundwater at CCB storage areas will recover to the former steady state, or in some locations, groundwater may recover to a new steady state in 6,600 to 10,600 years at variable rates depending on the proximity to a residual cone-of-groundwater depression caused by mine dewatering and regional oil and gas pumping as well as on actual, rather than estimated, groundwater recharge and evapotranspirational losses. Advective particle-track modeling indicates that the number of particles and rates of advective transport will vary depending on hydraulic properties of the mine spoil, particularly hydraulic conductivity and porosity. Modeling results from the most conservative scenario indicate that particles can migrate from CCB repositories to either the Shumway Arroyo alluvium after 1,320 years and from there to the San Juan River alluvium after 1,520 years or from southernmost CCB repositories directly to the San Juan River alluvium after 2,400 years after the cessation of mining.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175155","collaboration":"Prepared in cooperation with the Mining and Minerals Division of the State of New Mexico Energy, Minerals and Natural Resources Department","usgsCitation":"Stewart, A.M., 2018, Hydrologic assessment and numerical simulation of groundwater flow, San Juan Mine, San Juan County, New Mexico, 2010–13: U.S. Geological Survey Scientific Investigations Report 2017–5155, 94 p., https://doi.org/10.3133/sir20175155.","productDescription":"Report: xi, 94 p.; Data Releases","numberOfPages":"110","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080017","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":352877,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Q81BJK","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Chemical analyses for arsenic, calcium, chloride, sodium, sulfate, sulfide and dissolved solids, August 2011 through December 2013, from groundwater sampled at or in the vicinity of the San Juan Coal Mine, New Mexico"},{"id":353249,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75719JV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW–NWT and MODPATH5 models used to identify potential flow paths from San Juan Mine to hydrologic receptors, San Juan County, New Mexico"},{"id":352876,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5155/sir20175155.pdf","text":"Report","size":"6.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5155"},{"id":352875,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5155/coverthb.jpg"}],"country":"United States","state":"New Mexico","county":"San Juan County","otherGeospatial":"San Juan Mine","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.5,\n              36.7167\n            ],\n            [\n              -108.1,\n              36.72099868793134\n            ],\n            [\n              -108.1,\n              37\n            ],\n            [\n              -108.5,\n              37\n            ],\n            [\n              -108.5,\n              36.7167\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto: dc_nm@usgs.gov\" data-mce-href=\"mailto: dc_nm@usgs.gov\">Director</a>, <a href=\"https://nm.water.usgs.gov/\" data-mce-href=\"https://nm.water.usgs.gov/\">New Mexico Water Science Center</a><br>U.S. Geological Survey<br>6700 Edith Blvd NE<br>Albuquerque, NM 87113<br></p>","tableOfContents":"<ul><li>Acknowledgments<br></li><li>Abstract<br></li><li>Introduction<br></li><li>Purpose and Scope<br></li><li>Description of Study Area<br></li><li>Hydrologic Assessment of the San Juan Mine Study Area<br></li><li>Numerical Simulation of Groundwater Flow<br></li><li>Suggestions for Further Data Collection<br></li><li>Summary<br></li><li>References<br></li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2018-04-03","noUsgsAuthors":false,"publicationDate":"2018-04-03","publicationStatus":"PW","scienceBaseUri":"5afee6eae4b0da30c1bfbf55","contributors":{"authors":[{"text":"Stewart, Anne M. astewart@usgs.gov","contributorId":3938,"corporation":false,"usgs":true,"family":"Stewart","given":"Anne","email":"astewart@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":725092,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70196356,"text":"70196356 - 2018 - Quantifying differences in responses of aquatic insects to trace metal exposure in field studies and short-term stream mesocosm experiments","interactions":[],"lastModifiedDate":"2018-04-03T14:14:36","indexId":"70196356","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying differences in responses of aquatic insects to trace metal exposure in field studies and short-term stream mesocosm experiments","docAbstract":"<p><span>Characterizing macroinvertebrate taxa as either sensitive or tolerant is of critical importance for investigating impacts of anthropogenic stressors in aquatic ecosystems and for inferring causality. However, our understanding of relative sensitivity of aquatic insects to metals in the field and under controlled conditions in the laboratory or mesocosm experiments is limited. In this study, we compared the response of 16 lotic macroinvertebrate families to metals in short-term (10-day) stream mesocosm experiments and in a spatially extensive field study of 154 Colorado streams. Comparisons of field and mesocosm-derived EC</span><sub>20</sub><span><span>&nbsp;</span>(effect concentration of 20%) values showed that aquatic insects were generally more sensitive to metals in the field. Although the ranked sensitivity to metals was similar for many families, we observed large differences between field and mesocosm responses for some groups (e.g., Baetidae and Heptageniidae). These differences most likely resulted from the inability of short-term experiments to account for factors such as dietary exposure to metals, rapid recolonization in the field, and effects of metals on sensitive life stages. Understanding mechanisms responsible for differences among field, mesocosm, and laboratory approaches would improve our ability to predict contaminant effects and establish ecologically meaningful water-quality criteria.</span></p>","language":"English","publisher":"ACS","doi":"10.1021/acs.est.7b06628","usgsCitation":"Iwasaki, Y., Schmidt, T., and Clements, W.H., 2018, Quantifying differences in responses of aquatic insects to trace metal exposure in field studies and short-term stream mesocosm experiments: Environmental Science & Technology, v. 52, no. 7, p. 4378-4384, https://doi.org/10.1021/acs.est.7b06628.","productDescription":"7 p.","startPage":"4378","endPage":"4384","ipdsId":"IP-083029","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":353116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-22","publicationStatus":"PW","scienceBaseUri":"5afee6e9e4b0da30c1bfbf3f","contributors":{"authors":[{"text":"Iwasaki, Yuichi","contributorId":175410,"corporation":false,"usgs":false,"family":"Iwasaki","given":"Yuichi","email":"","affiliations":[{"id":27568,"text":"Tokyo Institute of Tecnology","active":true,"usgs":false}],"preferred":false,"id":732558,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":1300,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis S.","email":"tschmidt@usgs.gov","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":732557,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clements, William H.","contributorId":178714,"corporation":false,"usgs":false,"family":"Clements","given":"William","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":732559,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196362,"text":"70196362 - 2018 - Skeletal injuries in small mammals: a multispecies assessment of prevalence and location","interactions":[],"lastModifiedDate":"2018-04-03T15:22:03","indexId":"70196362","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Skeletal injuries in small mammals: a multispecies assessment of prevalence and location","docAbstract":"<p><span>Wild mammals are known to survive injuries that result in skeletal abnormalities. Quantifying and comparing skeletal injuries among species can provide insight into the factors that cause skeletal injuries and enable survival following an injury. We documented the prevalence and location of structural bone abnormalities in a community of 7 small mammal species inhabiting the White Mountains of New Hampshire. These species differ in locomotion type and levels of intraspecific aggression. Overall, the majority of injuries were to the ribs or caudal vertebrae. Incidence of skeletal injuries was highest in older animals, indicating that injuries accumulate over a lifetime. Compared to species with ambulatory locomotion, those with more specialized (semi-fossorial, saltatorial, and scansorial) locomotion exhibited fewer skeletal abnormalities in the arms and legs, which we hypothesize is a result of a lesser ability to survive limb injuries. Patterns of skeletal injuries in shrews (Soricidae) were consistent with intraspecific aggression, particularly in males, whereas skeletal injuries in rodents (Rodentia) were more likely accidental or resulting from interactions with predators. Our results demonstrate that both the incidence and pattern of skeletal injuries vary by species and suggest that the ability of an individual to survive a specific skeletal injury depends on its severity and location as well as the locomotor mode of the species involved.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyy020","usgsCitation":"Stephens, R.B., Burke, C.B., Woodman, N., Poland, L.B., and Rowe, R.J., 2018, Skeletal injuries in small mammals: a multispecies assessment of prevalence and location: Journal of Mammalogy, v. 99, no. 2, p. 486-497, https://doi.org/10.1093/jmammal/gyy020.","productDescription":"12 p.","startPage":"486","endPage":"497","ipdsId":"IP-094876","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468857,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyy020","text":"Publisher Index Page"},{"id":353122,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","scienceBaseUri":"5afee6e8e4b0da30c1bfbf3b","contributors":{"authors":[{"text":"Stephens, Ryan B.","contributorId":203881,"corporation":false,"usgs":false,"family":"Stephens","given":"Ryan","email":"","middleInitial":"B.","affiliations":[{"id":36740,"text":"Natural Resources and the Environment, University of New Hampshire, 114 James Hall, 56 College Road, Durham NH 03824-3534, USA","active":true,"usgs":false}],"preferred":false,"id":732586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burke, Christopher B.","contributorId":203882,"corporation":false,"usgs":false,"family":"Burke","given":"Christopher","email":"","middleInitial":"B.","affiliations":[{"id":36740,"text":"Natural Resources and the Environment, University of New Hampshire, 114 James Hall, 56 College Road, Durham NH 03824-3534, USA","active":true,"usgs":false}],"preferred":false,"id":732587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":732585,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poland, Lily B.","contributorId":203883,"corporation":false,"usgs":false,"family":"Poland","given":"Lily","email":"","middleInitial":"B.","affiliations":[{"id":36740,"text":"Natural Resources and the Environment, University of New Hampshire, 114 James Hall, 56 College Road, Durham NH 03824-3534, USA","active":true,"usgs":false}],"preferred":false,"id":732588,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rowe, Rebecca J.","contributorId":203884,"corporation":false,"usgs":false,"family":"Rowe","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":36740,"text":"Natural Resources and the Environment, University of New Hampshire, 114 James Hall, 56 College Road, Durham NH 03824-3534, USA","active":true,"usgs":false}],"preferred":false,"id":732589,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196352,"text":"70196352 - 2018 - Occupancy in community-level studies","interactions":[],"lastModifiedDate":"2018-04-03T15:24:32","indexId":"70196352","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Occupancy in community-level studies","docAbstract":"Another type of multi-species studies, are those focused on community-level metrics such as species richness. In this chapter we detail how some of the single-species occupancy models described in earlier chapters have been applied, or extended, for use in such studies, while accounting for imperfect detection. We highlight how Bayesian methods using MCMC are particularly useful in such settings to easily calculate relevant community-level summaries based on presence/absence data. These modeling approaches can be used to assess richness at a single point in time, or to investigate changes in the species pool over time.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Occupancy estimation and modeling (Second edition)","language":"English","publisher":"Academic Press","doi":"10.1016/B978-0-12-407197-1.00020-X","usgsCitation":"MacKenzie, D.I., Nichols, J.D., Royle, A., Pollock, K.H., Bailey, L.L., and Hines, J.E., 2018, Occupancy in community-level studies, chap. <i>of</i> Occupancy estimation and modeling (Second edition), p. 557-583, https://doi.org/10.1016/B978-0-12-407197-1.00020-X.","productDescription":"27 p.","startPage":"557","endPage":"583","ipdsId":"IP-088075","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":353123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6e9e4b0da30c1bfbf41","contributors":{"authors":[{"text":"MacKenzie, Darryl I.","contributorId":194669,"corporation":false,"usgs":false,"family":"MacKenzie","given":"Darryl","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":732545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":200533,"corporation":false,"usgs":true,"family":"Nichols","given":"James","email":"jnichols@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":732546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"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":true,"id":732544,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pollock, Kenneth H.","contributorId":8590,"corporation":false,"usgs":false,"family":"Pollock","given":"Kenneth","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":732547,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bailey, Larissa L. 0000-0002-5959-2018","orcid":"https://orcid.org/0000-0002-5959-2018","contributorId":189578,"corporation":false,"usgs":false,"family":"Bailey","given":"Larissa","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":732548,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":732549,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70194955,"text":"sir20185007 - 2018 - Data analysis considerations for pesticides determined by National Water Quality Laboratory schedule 2437","interactions":[],"lastModifiedDate":"2021-05-28T14:27:51.335925","indexId":"sir20185007","displayToPublicDate":"2018-04-02T14:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5007","title":"Data analysis considerations for pesticides determined by National Water Quality Laboratory schedule 2437","docAbstract":"In 2013, the U.S. Geological Survey National Water Quality Laboratory (NWQL) made a new method available for the analysis of pesticides in filtered water samples: laboratory schedule 2437. Schedule 2437 is an improvement on previous analytical methods because it determines the concentrations of 225 fungicides, herbicides, insecticides, and associated degradates in one method at similar or lower concentrations than previously available methods. Additionally, the pesticides included in schedule 2437 were strategically identified in a prioritization analysis that assessed likelihood of occurrence, prevalence of use, and potential toxicity.  When the NWQL reports pesticide concentrations for analytes in schedule 2437, the laboratory also provides supplemental information useful to data users for assessing method performance and understanding data quality. That supplemental information is discussed in this report, along with an initial analysis of analytical recovery of pesticides in water-quality samples analyzed by schedule 2437 during 2013–2015. A total of 523 field matrix spike samples and their paired environmental samples and 277 laboratory reagent spike samples were analyzed for this report (1,323 samples total). These samples were collected in the field as part of the U.S. Geological Survey National Water-Quality Assessment groundwater and surface-water studies and as part of the NWQL quality-control program. This report reviews how pesticide samples are processed by the NWQL, addresses how to obtain all the data necessary to interpret pesticide concentrations, explains the circumstances that result in a reporting level change or the occurrence of a raised reporting level, and describes the calculation and assessment of recovery. This report also discusses reasons why a data user might choose to exclude data in an interpretive analysis and outlines the approach used to identify the potential for decreased data quality in the assessment of method recovery. The information provided in this report is essential to understanding pesticide data determined by schedule 2437 and should be reviewed before interpretation of these data.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185007","collaboration":"National Water Quality Program","usgsCitation":"Shoda, M.E., Nowell, L.H., Stone, W.W., Sandstrom, M.W., and Bexfield, L.M., 2018, Data analysis considerations for pesticides determined by National Water Quality Laboratory schedule 2437: U.S. Geological Survey Scientific Investigations Report 2018-5007, 458 p., https://doi.org/10.3133/sir20185007.","productDescription":"Report: vi, 458 p.; 2 Data Releases; Table","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-088656","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"links":[{"id":352965,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5007/sir20185007.pdf","text":"Report","size":"7.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5007"},{"id":352964,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5007/coverthb.jpg"},{"id":352966,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5007/sir20185007_table4-v4.xlsx","text":"Table 4","size":"75.5 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Summary statistics for the recovery of schedule 2437 pesticides in lab reagent spikes, and groundwater and surface-water spike samples"},{"id":352967,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75H7DS8","text":"USGS data release","description":"USGS data release","linkHelpText":"National Water-Quality Assessment Project replicate surface water and groundwater pesticide data analyzed by the USGS National Water Quality Laboratory schedule 2437, water years 2013–15"},{"id":352968,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QZ28G4","text":"USGS data release","description":"USGS data release","linkHelpText":"Recovery data for surface water, groundwater and lab reagent samples analyzed by the USGS National Water Quality Laboratory schedule 2437, water years 2013–15"}],"contact":"<p>Program Coordinator, <a href=\"https://water.usgs.gov/nawqa/\" data-mce-href=\"https://water.usgs.gov/nawqa/\">National Water Quality Program</a><br>U.S. Geological Survey<br> 413 National Center<br> 12201 Sunrise Valley Drive<br> Reston, VA 20192</p>","tableOfContents":"<ul><li>Foreword</li><li>Abstract</li><li>Introduction</li><li>Data-Analysis Considerations</li><li>Schedule 2437 Pesticide Data Characterization</li><li>Further Analysis</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li><li>Appendix 1. Supporting Tables and Figures</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2018-04-02","noUsgsAuthors":false,"publicationDate":"2018-04-02","publicationStatus":"PW","scienceBaseUri":"5afee6eae4b0da30c1bfbf57","contributors":{"authors":[{"text":"Shoda, Megan E. 0000-0002-5343-9717 meshoda@usgs.gov","orcid":"https://orcid.org/0000-0002-5343-9717","contributorId":4352,"corporation":false,"usgs":true,"family":"Shoda","given":"Megan","email":"meshoda@usgs.gov","middleInitial":"E.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":726274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":726275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stone, Wesley W. 0000-0003-0239-2063 wwstone@usgs.gov","orcid":"https://orcid.org/0000-0003-0239-2063","contributorId":1496,"corporation":false,"usgs":true,"family":"Stone","given":"Wesley","email":"wwstone@usgs.gov","middleInitial":"W.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":726276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sandstrom, Mark W. 0000-0003-0006-5675 sandstro@usgs.gov","orcid":"https://orcid.org/0000-0003-0006-5675","contributorId":706,"corporation":false,"usgs":true,"family":"Sandstrom","given":"Mark","email":"sandstro@usgs.gov","middleInitial":"W.","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":726277,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bexfield, Laura M. 0000-0002-1789-654X bexfield@usgs.gov","orcid":"https://orcid.org/0000-0002-1789-654X","contributorId":1273,"corporation":false,"usgs":true,"family":"Bexfield","given":"Laura","email":"bexfield@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":726278,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70198730,"text":"70198730 - 2018 - Evaluating micrometeorological estimates of groundwater discharge from Great Basin desert playas","interactions":[],"lastModifiedDate":"2018-11-14T09:52:43","indexId":"70198730","displayToPublicDate":"2018-04-02T11:33:10","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating micrometeorological estimates of groundwater discharge from Great Basin desert playas","docAbstract":"<p>Groundwater availability studies in the arid southwestern United States traditionally have assumed that groundwater discharge by evapotranspiration (ETg) from desert playas is a significant component of the groundwater budget. However, desert playa ETg rates are poorly constrained by Bowen Ratio energy budget (BREB) and eddy-covariance (EC) micrometeorological measurement approaches. Best attempts by previous studies to constrain ETg from desert playas have resulted in ETg rates that are within the measurement error of micrometeorological approaches. This study uses numerical models to further constrain desert playa ETg rates that are within the measurement error of BREB and EC approaches, and to evaluate the effect of hydraulic properties and salinity-based groundwater-density contrasts on desert playa ETg rates. Numerical models simulated ETg rates from desert playas in Death Valley, California and Dixie Valley, Nevada. Results indicate that actual ETg rates from desert playas are significantly below the uncertainty thresholds of BREB- and EC-based micrometeorological measurements. Discharge from desert playas likely contributes less than 2 percent of total groundwater discharge from Dixie and Death Valleys, which suggests discharge from desert playas also is negligible in other basins. Simulation results also show that ETg from desert playas primarily is limited by differences in hydraulic properties between alluvial fan and playa sediments and, to a lesser extent, by salinity-based groundwater density contrasts. <br><br></p>","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12647","usgsCitation":"Jackson, T., Halford, K.J., Gardner, P.M., and Garcia, A., 2018, Evaluating micrometeorological estimates of groundwater discharge from Great Basin desert playas: Ground Water, v. 56, no. 6, p. 909-920, https://doi.org/10.1111/gwat.12647.","productDescription":"12 p.","startPage":"909","endPage":"920","ipdsId":"IP-067348","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":488351,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1429589","text":"External Repository"},{"id":356588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"6","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-26","publicationStatus":"PW","scienceBaseUri":"5b98a2e1e4b0702d0e843003","contributors":{"authors":[{"text":"Jackson, Tracie 0000-0001-8553-0323 tjackson@usgs.gov","orcid":"https://orcid.org/0000-0001-8553-0323","contributorId":193845,"corporation":false,"usgs":true,"family":"Jackson","given":"Tracie","email":"tjackson@usgs.gov","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":742760,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halford, Keith J. 0000-0002-7322-1846 khalford@usgs.gov","orcid":"https://orcid.org/0000-0002-7322-1846","contributorId":1374,"corporation":false,"usgs":true,"family":"Halford","given":"Keith","email":"khalford@usgs.gov","middleInitial":"J.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":742761,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gardner, Philip M. 0000-0003-3005-3587 pgardner@usgs.gov","orcid":"https://orcid.org/0000-0003-3005-3587","contributorId":962,"corporation":false,"usgs":true,"family":"Gardner","given":"Philip","email":"pgardner@usgs.gov","middleInitial":"M.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":742762,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garcia, Amanda 0000-0003-3776-3565 cgarcia@usgs.gov","orcid":"https://orcid.org/0000-0003-3776-3565","contributorId":208515,"corporation":false,"usgs":false,"family":"Garcia","given":"Amanda","email":"cgarcia@usgs.gov","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":false,"id":747519,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70200547,"text":"70200547 - 2018 - Presentation of the Dana Medal of the Mineralogical Society of America for 2017 to Thomas W. Sisson","interactions":[],"lastModifiedDate":"2018-10-24T11:32:50","indexId":"70200547","displayToPublicDate":"2018-04-02T11:32:42","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"Presentation of the Dana Medal of the Mineralogical Society of America for 2017 to Thomas W. Sisson","docAbstract":"I have the pleasure of introducing Thomas W. Sisson, the Mineralogical Society of America Dana Medalist for 2017. Tom is known for his scientific rigor and landmark publications that have contributed to a diverse spectrum of fields closely tied to the mineralogical sciences. He is particularly recognized for his work on magma differentiation and the role of water in subduction-related magmatism. Beginning with his Ph.D. research with Tim Grove, Tom's early papers showcase difficult high-temperature experiments on hydrous basalt and magmatic processes recorded by the Sierra Nevada batholith. This landmark work was soon followed by ion microprobe measurements of dissolved water concentrations in melt inclusions from a range of arc basalts and by infrared spectrometric determinations of dissolved H2O and CO2 concentrations in unusually primitive arc basalt.","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/am-2018-AP10345","usgsCitation":"Bacon, C.R., 2018, Presentation of the Dana Medal of the Mineralogical Society of America for 2017 to Thomas W. Sisson: American Mineralogist, v. 103, no. 4, p. 651-652, https://doi.org/10.2138/am-2018-AP10345.","productDescription":"2 p.","startPage":"651","endPage":"652","ipdsId":"IP-091475","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468860,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2138/am-2018-ap10345","text":"Publisher Index Page"},{"id":358737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"103","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a9e0e4b034bf6a7e54f0","contributors":{"authors":[{"text":"Bacon, Charles R. 0000-0002-2165-5618 cbacon@usgs.gov","orcid":"https://orcid.org/0000-0002-2165-5618","contributorId":2909,"corporation":false,"usgs":true,"family":"Bacon","given":"Charles","email":"cbacon@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":749480,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70248920,"text":"70248920 - 2018 - High frequency data exposes nonlinear seasonal controls on dissolved organic matter in a large watershed","interactions":[],"lastModifiedDate":"2023-09-26T12:10:32.30659","indexId":"70248920","displayToPublicDate":"2018-04-02T07:08:53","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"High frequency data exposes nonlinear seasonal controls on dissolved organic matter in a large watershed","docAbstract":"<div id=\"abstractBox\" class=\"article_abstract-content hlFld-Abstract\"><p class=\"articleBody_abstractText\">We analyzed a five year, high frequency time series generated by an in situ fluorescent dissolved organic matter (fDOM) sensor installed near the Connecticut River’s mouth, investigating high temporal resolution DOM dynamics in a larger watershed and longer time series than previously addressed. We identified a gradient between large, saturating summer fDOM responses to discharge and linear, subdued responses during colder months. Seasonal response patterns were not consistent with multiple linear regression. Alternatively, we binned measurements across the yearly cycle using environmental indices, such as temperature, and applied moving regression, a novel approach which produced superior fits to calendar day binning. Spatially averaged watershed soil temperature at 10 cm was the best overall index of discharge-fDOM response. DOM fractionation showed fDOM was primarily a surrogate for hydrophobic organic acid (HPOA) concentrations. HPOAs were highly correlated with discharge, but hydrophilics (HPIs) were not. Discharge dependent DOM concentrations driven by the HPOA fraction may be controlled by soil temperature and water table position relative to organic and mineral soil horizons. HPI concentrations were correlated with average watershed soil temperature at 10 cm but were rather stationary throughout the year, further indicating a consistent groundwater source for this nonfluorescent DOM. We present a resolved subseasonal empirical model of DOM concentrations and fluxes, showing that riverine DOM flux and quality depend heavily on seasonal terrestrial carbon dynamics and hydrologic flow paths. High frequency monitoring reveals readily discernible patterns demonstrating that upland biogeochemical signals are maintained even at this large watershed scale.</p></div>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.7b04579","usgsCitation":"Shultz, M., Pellerin, B., Aiken, G., Martin, J., and Raymond, P., 2018, High frequency data exposes nonlinear seasonal controls on dissolved organic matter in a large watershed: Environmental Science and Technology, v. 52, no. 10, p. 5644-5652, https://doi.org/10.1021/acs.est.7b04579.","productDescription":"9 p.","startPage":"5644","endPage":"5652","ipdsId":"IP-090811","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":421163,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"10","noUsgsAuthors":false,"publicationDate":"2018-04-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Shultz, Matthew","contributorId":330173,"corporation":false,"usgs":false,"family":"Shultz","given":"Matthew","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":884211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pellerin, Brian A. 0000-0003-3712-7884","orcid":"https://orcid.org/0000-0003-3712-7884","contributorId":204324,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian A.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":884212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aiken, George 0000-0001-8454-0984","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":208803,"corporation":false,"usgs":true,"family":"Aiken","given":"George","affiliations":[],"preferred":true,"id":884213,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Joseph W. 0000-0002-5995-9385","orcid":"https://orcid.org/0000-0002-5995-9385","contributorId":203256,"corporation":false,"usgs":true,"family":"Martin","given":"Joseph W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":884214,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Raymond, Peter","contributorId":330174,"corporation":false,"usgs":false,"family":"Raymond","given":"Peter","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":884215,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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