{"pageNumber":"260","pageRowStart":"6475","pageSize":"25","recordCount":68827,"records":[{"id":70227653,"text":"70227653 - 2020 - Resilience management for conservation of inland recreational fisheries","interactions":[],"lastModifiedDate":"2022-01-25T14:28:09.045933","indexId":"70227653","displayToPublicDate":"2020-01-10T08:22:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Resilience management for conservation of inland recreational fisheries","docAbstract":"

Resilience thinking has generated much interest among scientific communities, yet most resilience concepts have not materialized into management applications. We believe that using resilience concepts to characterize systems and the social and ecological processes affecting them is a way to integrate resilience into better management decisions. This situation is exemplified by inland recreational fisheries, which represent complex socioecological systems that face unpredictable and unavoidable change. Making management decisions in the context of resilience is increasingly important given mounting environmental and anthropogenic perturbations to inland systems. Herein, we propose a framework that allows resilience concepts to be better incorporated into management by (i) recognizing how current constraints and management objectives focus on desired or undesired systems (specific fish and anglers), (ii) evaluating the state of a system in terms of how both social and ecological forces enforce or erode the desired or undesired system, (iii) identifying the resilience-stage cycles a system state may undergo, and (iv) determining the broad management strategies that may be viable given the system state and resilience stage. We use examples from inland recreational fisheries to illustrate different system state and resilience stages and synthesize several key results. Across all combinations of socioecological forces, five common types of viable management strategies emerge: (i) adopt a different management preference or focus, (ii) change stakeholder attitudes or behaviors via stakeholder outreach, (iii) engage in (sometimes extreme) biological intervention, (iv) engage in fishery intervention, and (v) adopt landscape-level management approaches focusing on achieving different systems in different waters. We then discuss the challenges and weaknesses of our approach, including specifically the cases in which there are multiple strong social forces (i.e., stakeholders holding competing objectives or values) and situations where waters are not readily divisible, such as rivers or great lakes, and in which spatial separation of competing objectives will be difficult. We end with our vision of how we believe these types of operationalized resilience approaches could improve or transform inland recreational fisheries management.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2019.00498","usgsCitation":"Camp, E.V., Kaemingk, M.A., Ahrens, R.N., Potts, W.M., Pine, W.E., Weyl, O.L., and Pope, K.L., 2020, Resilience management for conservation of inland recreational fisheries: Frontiers in Ecology and Evolution, v. 7, 498, 17 p., https://doi.org/10.3389/fevo.2019.00498.","productDescription":"498, 17 p.","ipdsId":"IP-108306","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":458164,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2019.00498","text":"Publisher Index Page"},{"id":394818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","noUsgsAuthors":false,"publicationDate":"2020-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Camp, E. V.","contributorId":272121,"corporation":false,"usgs":false,"family":"Camp","given":"E.","email":"","middleInitial":"V.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":831557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaemingk, M. A.","contributorId":271091,"corporation":false,"usgs":false,"family":"Kaemingk","given":"M.","email":"","middleInitial":"A.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":831558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ahrens, R. N. M.","contributorId":272122,"corporation":false,"usgs":false,"family":"Ahrens","given":"R.","email":"","middleInitial":"N. M.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":831559,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Potts, W. M.","contributorId":268289,"corporation":false,"usgs":false,"family":"Potts","given":"W.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":831560,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pine, W. E. III","contributorId":272123,"corporation":false,"usgs":false,"family":"Pine","given":"W.","suffix":"III","email":"","middleInitial":"E.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":831561,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weyl, O. L. F","contributorId":272124,"corporation":false,"usgs":false,"family":"Weyl","given":"O.","email":"","middleInitial":"L. F","affiliations":[{"id":48725,"text":"South African Institute for Aquatic Biodiversity","active":true,"usgs":false}],"preferred":false,"id":831562,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":831563,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70211640,"text":"70211640 - 2020 - Co-occurence of Chiricahua leopard frogs (Lithobates chiricahuensis) with sunfish (Lepomis)","interactions":[],"lastModifiedDate":"2020-08-06T19:55:59.712564","indexId":"70211640","displayToPublicDate":"2020-01-09T09:25:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5991,"text":"The Southwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Co-occurence of Chiricahua leopard frogs (Lithobates chiricahuensis) with sunfish (Lepomis)","title":"Co-occurence of Chiricahua leopard frogs (Lithobates chiricahuensis) with sunfish (Lepomis)","docAbstract":"

Invasive species are a major threat to the persistence of native species, particularly in systems where ephemeral aquatic habitats have been replaced by permanent water and predators, such as fish, have been introduced. Within the Altar Valley, Arizona, the invasive American bullfrog, Lithobates catesbeianus (formerly Rana catesbeianus), has been successfully eradicated to help recover Chiricahua leopard frogs (Lithobates chiricahuensis). However, other nonnative predators including sunfish (Lepomis) are present in some permanent water bodies. During four consecutive years (2014–2017), we detected both the federally threatened Chiricahua leopard frog and sunfish at one permanent water body in the Altar Valley. This suggests that despite the potential negative effect of predatory fish on amphibians, there may be conditions where the Chiricahua leopard frog can co-occur with this nonnative predator. A better understanding of rare situations of co-occurrence with nonnative predators may contribute to our understanding of why co-occurrence happens in some, but not all, systems and whether conservation strategies can be developed in situations where eradication of nonnative predators is infeasible.

","language":"English","publisher":"BioOne","doi":"10.1894/0038-4909-64-1-69","usgsCitation":"Howell, P., Sigafus, B.H., Hossack, B.R., and Muths, E.L., 2020, Co-occurence of Chiricahua leopard frogs (Lithobates chiricahuensis) with sunfish (Lepomis): The Southwestern Naturalist, v. 64, no. 1, p. 69-72, https://doi.org/10.1894/0038-4909-64-1-69.","productDescription":"4 p.","startPage":"69","endPage":"72","numberOfPages":"4","ipdsId":"IP-091934","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":377105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Alter Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.785888671875,\n 31.51767878128718\n ],\n [\n -111.19537353515624,\n 31.51767878128718\n ],\n [\n -111.19537353515624,\n 32.16631295696736\n ],\n [\n -111.785888671875,\n 32.16631295696736\n ],\n [\n -111.785888671875,\n 31.51767878128718\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"64","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Howell, Paige E.","contributorId":173495,"corporation":false,"usgs":false,"family":"Howell","given":"Paige E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":794900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sigafus, Brent H. 0000-0002-7422-8927 bsigafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":4534,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent","email":"bsigafus@usgs.gov","middleInitial":"H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":794901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":794902,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muths, Erin L. 0000-0002-5498-3121 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3121","contributorId":236995,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":794903,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207244,"text":"sir20195141 - 2020 - Water-balance techniques for determining available soil-water storage for selected sandy and clay soil study sites in Cass County, North Dakota, 2016–17","interactions":[],"lastModifiedDate":"2022-04-25T20:16:09.086144","indexId":"sir20195141","displayToPublicDate":"2020-01-08T16:45:00","publicationYear":"2020","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":"2019-5141","displayTitle":"Water-Balance Techniques for Determining Available Soil-Water Storage for Selected Sandy and Clay Soil Study Sites in Cass County, North Dakota, 2016–17","title":"Water-balance techniques for determining available soil-water storage for selected sandy and clay soil study sites in Cass County, North Dakota, 2016–17","docAbstract":"

The U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service, collected field and remotely sensed data on precipitation, evapotranspiration (ET), and soil-water content to determine available soil-water storage (AWS) at six study sites on sandy and clay soils in Cass County, North Dakota. Data were collected at all the study sites from May 1–October 31, 2016, and from May 1–October 24, 2017. Estimated daily AWS was determined using daily meteorological and potential evapotranspiration (PET) data obtained from various climate stations, and estimated monthly AWS was determined using monthly meteorological and PET data and monthly ET data determined using the Operational Simplified Surface Energy Balance model. AWS during 2016 and 2017 was determined at daily and monthly time steps because of data availability and to assess results using varying time steps. Comparisons of measured and estimated daily values of AWS at the Brewer Lake site indicated poor agreement during May–October 2016 and May–October 2017. Comparisons of measured and estimated daily values of AWS at the Embden East and Embden West sites indicated poor and fair agreement respectively. At the Lynchburg Crop and Lynchburg Grass sites, comparisons of measured and estimated daily values of AWS indicated fair and good relations, respectively, even with the possible effects of soil cracks. Mean estimated values of daily runoff plus soil percolation for the four sandy soil sites indicated that a maximum of about 19 percent of the estimated runoff plus soil percolation could be considered runoff and that the remaining 81 percent could be considered soil percolation, and for the two clay soil sites about 13 percent of the runoff plus soil percolation could have been considered runoff and about 87 percent could have been considered soil percolation. Results indicated little difference between using monthly PET or monthly ET in water-balance equations to estimate monthly AWS for the grouped sandy soil sites, and only slightly better results were obtained using monthly PET than monthly ET to estimate monthly AWS for the grouped clay soil study sites. Overall, the monthly water-balance models did not perform as well as the daily water-balance models for determining AWS at the six study sites. Additional data collection from a longer-period study and adjustments to the models may improve results from the monthly water-balance techniques.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195141","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service","usgsCitation":"Vining, K.C., 2020, Water-balance techniques for determining available soil-water storage for selected sandy and clay soil study sites in Cass County, North Dakota, 2016–17: U.S. Geological Survey Scientific Investigations Report 2019–5141, 39 p., https://doi.org/10.3133/sir20195141.","productDescription":"Report: vii, 39 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-098347","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":399616,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109584.htm"},{"id":371052,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GG2ILI","text":"USGS data 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Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-01-08","noUsgsAuthors":false,"publicationDate":"2020-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Vining, Kevin C. 0000-0001-5738-3872","orcid":"https://orcid.org/0000-0001-5738-3872","contributorId":221225,"corporation":false,"usgs":true,"family":"Vining","given":"Kevin","email":"","middleInitial":"C.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777428,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70231788,"text":"70231788 - 2020 - Bioaccumulation and toxicity of cadmium, copper, nickel, and zinc and their mixtures to aquatic insect communities","interactions":[],"lastModifiedDate":"2022-05-26T15:05:00.261268","indexId":"70231788","displayToPublicDate":"2020-01-08T10:01:54","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Bioaccumulation and toxicity of cadmium, copper, nickel, and zinc and their mixtures to aquatic insect communities","docAbstract":"

We describe 2 artificial stream experiments that exposed aquatic insect communities to zinc (Zn), copper (Cu), and cadmium (year 2014) and to Zn, Cu, and nickel (year 2015). The testing strategy was to concurrently expose insect communities to single metals and mixtures. Single-metal tests were repeated to evaluate the reproducibility of the methods and year-to-year variability. Metals were strongly accumulated in sediments, periphyton, and insect (caddisfly) tissues, with the highest concentrations occurring in periphyton. Sensitive mayflies declined in metal treatments, and effect concentrations could be predicted effectively from metal concentrations in either periphyton or water. Most responses were similar in the replicated tests, but median effect concentration values for the mayfly Rhithrogena sp. varied 20-fold between the tests, emphasizing the difficulty comparing sensitivities across studies and the value of repeated testing. Relative to the single-metal responses, the toxicity of the mixtures was either approximately additive or less than additive when calculated as the product of individual responses (response addition). However, even less-than-additive relative responses were sometimes greater than responses to similar concentrations tested singly. The ternary mixtures resulted in mayfly declines at concentrations that caused no declines in the concurrent single-metal tests. When updating species-sensitivity distributions (SSDs) with these results, the mayfly responses were among the most sensitive 10th percentile of available data for all 4 metals, refuting older literature placing mayflies in the insensitive portion of metal SSDs. Testing translocated aquatic insect communities in 30-d artificial streams is an efficient approach to generate multiple species effect values under quasi-natural conditions that are relevant to natural streams.

","language":"English","publisher":"Wiley","doi":"10.1002/etc.4663","usgsCitation":"Mebane, C.A., Schmidt, T., Miller, J.L., and Balistrieri, L.S., 2020, Bioaccumulation and toxicity of cadmium, copper, nickel, and zinc and their mixtures to aquatic insect communities: Environmental Toxicology and Chemistry, v. 39, no. 4, p. 812-833, https://doi.org/10.1002/etc.4663.","productDescription":"22 p.","startPage":"812","endPage":"833","ipdsId":"IP-110553","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":458177,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.4663","text":"Publisher Index Page"},{"id":401151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843832,"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":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Janet L.","contributorId":218842,"corporation":false,"usgs":false,"family":"Miller","given":"Janet","email":"","middleInitial":"L.","affiliations":[{"id":39922,"text":"No affilcation","active":true,"usgs":false}],"preferred":false,"id":843834,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":843835,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210164,"text":"70210164 - 2020 - Fluxes of agricultural nitrogen and metolachlor metabolites are highly correlated in a first order stream in Maryland, USA","interactions":[],"lastModifiedDate":"2020-05-19T14:55:14.610714","indexId":"70210164","displayToPublicDate":"2020-01-08T09:49:16","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Fluxes of agricultural nitrogen and metolachlor metabolites are highly correlated in a first order stream in Maryland, USA","docAbstract":"Nitrogen pollution in watersheds containing significant\ncropland area is generally problematic. Conservation practices intended\nto reduce nitrate-N (NO3--N) export from watersheds are being implemented\nby many regions without necessary tools to assess effectiveness of these\nabatement tools. A commonly used herbicide metolachlor degrades in the\nvadose zone of croplands to form two metabolites (metolachlor ethane\nsulfonic acid (MESA) and metolachlor oxanilic acid (MOXA)) which are both\nhighly soluble in soils. Study of metabolite fates in a first order\nwatershed provided evidence that transport of these metabolites to stream\nwater is highly correlated to transport of the agricultural NO3--N that\nalso forms in the cropland vadose zone. Linear models describing the\nrelationships of stream flux of MESA and MOXA to NO3--N flux generated\ngoodness of fit values of 0.93 and 0.82 respectively. These findings\nsupport a conclusion that both MESA and MOXA act as excellent transport\nanalogs of NO3- and become strongly correlated to agricultural NO3--N\nleaching from the cropland vadose zone. Moreover, their use as\nconservative tracers in agricultural watersheds can provide valuable\ninformation concerning movement and fate of agricultural nitrogen at\nwatershed scales of observation.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.136590","usgsCitation":"Rice, C., Hively, W.D., McCarty, G.W., and Hapeman, C., 2020, Fluxes of agricultural nitrogen and metolachlor metabolites are highly correlated in a first order stream in Maryland, USA: Science of the Total Environment, v. 716, 136590, 7 p., https://doi.org/10.1016/j.scitotenv.2020.136590.","productDescription":"136590, 7 p.","ipdsId":"IP-113701","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":458180,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.136590","text":"Publisher Index 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\"}}]}","volume":"716","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rice, Cliff 0000-0002-7702-9376","orcid":"https://orcid.org/0000-0002-7702-9376","contributorId":224744,"corporation":false,"usgs":false,"family":"Rice","given":"Cliff","email":"","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":789364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":210993,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":789365,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCarty, Gregory W.","contributorId":192367,"corporation":false,"usgs":false,"family":"McCarty","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":789366,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hapeman, Cathleen","contributorId":224745,"corporation":false,"usgs":false,"family":"Hapeman","given":"Cathleen","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":789367,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208607,"text":"70208607 - 2020 - Spatiotemporal variability of modeled watershed scale surface-depression storage and runoff for the conterminous United States","interactions":[],"lastModifiedDate":"2020-02-21T11:50:49","indexId":"70208607","displayToPublicDate":"2020-01-08T06:45:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal variability of modeled watershed scale surface-depression storage and runoff for the conterminous United States","docAbstract":"This study uses the explores the viability of a proxy model calibration strategy through assessment of the spatiotemporal variability of surface-depression storage and runoff generated with the U.S. Geological Survey’s National Hydrologic Model (NHM) infrastructure for hydrologic response units (HRUs; n=109,951) across the conterminous United States (CONUS). Simulated values for each HRU of daily surface-depression storage (treated as a decimal fraction of total possible volume) and monthly normalized runoff (0 to 1) values were calculated using Spearman’s rho at monthly and annual aggregations. Locations where values are correlated show where previously-developed proxy calibration strategies are likely to be effective. In addition, differences in the correlation for monthly and annual time scale aggregations show which time scale drives surface-depression storage processes in the NHM. Results show overall long-term (annual) correlation is more common than short-term (monthly) correlation over the CONUS; however, summary statistics for eighty-six ecoregions show five with higher ranges of monthly relative to annual Spearman’s rank coefficient values. This landscape-scale analysis shows simulations aggregated to an annual time scale are generally more dominant for the CONUS; however, simulations aggregated to monthly, short-term time scales are more dominant in focused areas where surface-depression storage processes are investigated.","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12826","usgsCitation":"Driscoll, J.M., Hay, L., Vanderhoof, M.K., and Viger, R.J., 2020, Spatiotemporal variability of modeled watershed scale surface-depression storage and runoff for the conterminous United States: Journal of the American Water Resources Association, v. 56, no. 1, p. 16-29, https://doi.org/10.1111/1752-1688.12826.","productDescription":"14 p.","startPage":"16","endPage":"29","ipdsId":"IP-093569","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction 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Branch","active":true,"usgs":true}],"preferred":true,"id":782704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":782706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":782707,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208745,"text":"70208745 - 2020 - Resolving small-scale forest snow patterns using an energy-balance snow model with a 1-layer canopy","interactions":[],"lastModifiedDate":"2020-02-28T06:31:32","indexId":"70208745","displayToPublicDate":"2020-01-08T06:28:52","publicationYear":"2020","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":"Resolving small-scale forest snow patterns using an energy-balance snow model with a 1-layer canopy","docAbstract":"Modelling spatiotemporal dynamics of snow in forests is challenging, as involved processes are strongly dependent on small-scale canopy properties. In this study, we explore how local canopy structure information can be integrated in a medium-complexity energy-balance snow model to replicate observed snow patterns at very high spatial resolutions. Snow depth distributions simulated with the Flexible Snow Model (FSM2) were tested against extensive experimental data acquired in discontinuous subalpine forest stands in Eastern Switzerland over three winters. While the default canopy implementation in FSM2 fails to capture the observed snow depth variability, performance is considerably improved when local canopy cover fraction and hemispherical sky view fraction are additionally accounted for (30% reduction in RMSE). However, realistic snow depth distribution patterns throughout the season are only achieved if effective temperatures of near and distant canopy elements are discerned, and if a mechanism to mimic preferential deposition of snow in canopy gaps is included. We demonstrate that by diversifying the canopy structure input in order to reflect respective portions of the canopy relevant to different processes, even a simple model based on widely used process parametrizations and canopy metrics can be applied for high-resolution simulations of the sub-canopy snow cover with just a few modifications. The presented approaches could be implemented in commonly used land surface models, allowing upscaling experiments and development of sub-grid parametrizations without necessitating complex high-resolution models.","language":"English","publisher":"Wiley","doi":"10.1029/2019WR026129","usgsCitation":"Mazzotti, G., Essery, R., Moeser, C.D., and Jonas, T., 2020, Resolving small-scale forest snow patterns using an energy-balance snow model with a 1-layer canopy: Water Resources Research, v. 56, no. 1, e2019WR026129, 22 p., https://doi.org/10.1029/2019WR026129.","productDescription":"e2019WR026129, 22 p.","ipdsId":"IP-112070","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":458191,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.research.ed.ac.uk/en/publications/941ef274-b54b-48d0-8263-ae1287bd8584","text":"External Repository"},{"id":372718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Switzerland","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[9.59423,47.52506],[9.63293,47.3476],[9.47997,47.10281],[9.93245,46.92073],[10.4427,46.89355],[10.36338,46.48357],[9.92284,46.3149],[9.18288,46.44021],[8.96631,46.03693],[8.48995,46.00515],[8.31663,46.16364],[7.75599,45.82449],[7.27385,45.77695],[6.84359,45.99115],[6.5001,46.42967],[6.02261,46.27299],[6.03739,46.72578],[6.76871,47.28771],[6.73657,47.5418],[7.1922,47.44977],[7.46676,47.62058],[8.3173,47.61358],[8.52261,47.83083],[9.59423,47.52506]]]},\"properties\":{\"name\":\"Switzerland\"}}]}","volume":"56","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Mazzotti, Giulia","contributorId":222821,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Giulia","email":"","affiliations":[{"id":40604,"text":"WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland and Laboratory of Hydraulics, Hydrology and Glaciology, ETHZ, Zurich, Switzerland","active":true,"usgs":false}],"preferred":false,"id":783256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Essery, Richard","contributorId":222822,"corporation":false,"usgs":false,"family":"Essery","given":"Richard","email":"","affiliations":[{"id":40605,"text":"School of Geosciences, University of Edinburgh, Edinburgh, UK","active":true,"usgs":false}],"preferred":false,"id":783257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moeser, C. David 0000-0003-0154-9110","orcid":"https://orcid.org/0000-0003-0154-9110","contributorId":214563,"corporation":false,"usgs":true,"family":"Moeser","given":"C.","email":"","middleInitial":"David","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jonas, Tobias","contributorId":222823,"corporation":false,"usgs":false,"family":"Jonas","given":"Tobias","email":"","affiliations":[{"id":40606,"text":"WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland","active":true,"usgs":false}],"preferred":false,"id":783258,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211192,"text":"70211192 - 2020 - Field-based method for assessing duration of infectivity for influenza A viruses in the environment","interactions":[],"lastModifiedDate":"2020-07-16T18:41:56.104549","indexId":"70211192","displayToPublicDate":"2020-01-07T13:27:15","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2496,"text":"Journal of Virological Methods","active":true,"publicationSubtype":{"id":10}},"title":"Field-based method for assessing duration of infectivity for influenza A viruses in the environment","docAbstract":"

Understanding influenza A virus (IAV) persistence in wetlands is limited by a paucity of field studies relating to the maintenance of infectivity over time. The duration of IAV infectivity in water has been assessed under variable laboratory conditions, but results are difficult to translate to more complex field conditions. We tested a field-based method to assess the viability of IAVs in an Alaska wetland during fall and winter which incorporated physical and chemical properties of the waterbody in which samples were held. Filtered pond water was inoculated with avian fecal samples collected from the environment, aliquoted into a series of duplicate sealed vials and submerged back in the wetland for up to 132 days (October 2018–March 2019). Sample aliquots were sequentially recovered and tested for IAVs by rRT-PCR and virus isolation. One sample remained rRT-PCR positive for the duration of the study and virus isolation positive for 118 days. The surrounding water temperature was 1°–6 °C with near neutral pH (6.6–7.3) for the duration of the study. This proof of concept study demonstrates a protocol for testing the persistence of infectious IAV naturally shed from waterfowl under ambient environmental conditions.

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This review of life history, physiology, and behavior of white sturgeon, along with data from recent toxicological studies, suggest that trace metals, especially Cu, affect survival and behavior of early life stage fish. Sturgeon free embryos, first feeding embryos, and mixed feeding embryos utilize interstitial \nspaces between gravel. Although concentrations of Cu in the water column of the Upper Columbia River are typically less than US water quality criteria defined to protect aquatic life, samples at the sediment–water interface were as large as 24 µg/L and exceed the criteria. Toxicological studies reviewed here demonstrate mortality, loss of equilibrium, and immobility at Cu concentrations of 1.5 to <16 µg/L and reduced swimming activity was documented at 0.88 to 7 μg/L. Contaminated invertebrates and slag particles provide other routes of exposure. These additional routes of exposure can cause indirect effects from starvation due to potential lack of prey items and ingestion of contaminated prey or slag particles. The lack of food in stomachs during these critical early life stages may coincide with a threshold “point of no return” at which sturgeon will be unable to survive even if food becomes available following that early time frame. These findings become especially important as work progresses to enhance white sturgeon recruitment in the Upper Columbia River. To date, decisions against including trace metals as a factor in sturgeon recovery have focused on surface‐water concentrations and measurements of lethality (LC50) to establish threshold concentrations for sturgeon sensitivity. However, information provided here suggests that measurements from the sediment–water interface and effect concentrations (EC50) be considered with white sturgeon life history characteristics. These data support minimizing Cu exposure risk to enhance a successful white sturgeon recovery effort.","language":"English","publisher":"SETAC","doi":"10.1002/ieam.4240","collaboration":"","usgsCitation":"Puglis, H.J., Farag, A., and Mebane, C.A., 2020, Copper concentrations in the upper Columbia River as a limiting factor in White Sturgeon recruitment and recovery: Integrated Environmental Assessment and Management, v. 16, no. 3, p. 378-391, https://doi.org/10.1002/ieam.4240.","productDescription":"14 p.","startPage":"378","endPage":"391","ipdsId":"IP-098467","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":374050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","state":"Washington, British Columbia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.71850585937501,\n 49.23194729854554\n ],\n [\n -117.784423828125,\n 49.75287993415023\n ],\n [\n -118.828125,\n 49.78835749241399\n ],\n [\n -118.89404296875,\n 49.01625665778159\n ],\n [\n -120.73974609374999,\n 49.01625665778159\n ],\n [\n -120.62988281249999,\n 48.23199134320962\n ],\n [\n -120.421142578125,\n 46.475699386607516\n ],\n [\n -117.7734375,\n 46.66451741754235\n ],\n [\n -117.71850585937501,\n 49.23194729854554\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Puglis, Holly J. 0000-0002-3090-6597 hpuglis@usgs.gov","orcid":"https://orcid.org/0000-0002-3090-6597","contributorId":4686,"corporation":false,"usgs":true,"family":"Puglis","given":"Holly","email":"hpuglis@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":787190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farag, Aida 0000-0003-4247-6763 aida_farag@usgs.gov","orcid":"https://orcid.org/0000-0003-4247-6763","contributorId":200690,"corporation":false,"usgs":true,"family":"Farag","given":"Aida","email":"aida_farag@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":787191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787192,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70239440,"text":"70239440 - 2020 - Introduction to this special section: Geothermal energy","interactions":[],"lastModifiedDate":"2023-01-13T12:49:12.91956","indexId":"70239440","displayToPublicDate":"2020-01-07T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3568,"text":"The Leading Edge","active":true,"publicationSubtype":{"id":10}},"title":"Introduction to this special section: Geothermal energy","docAbstract":"

Geothermal energy is a global renewable resource that has the potential to provide a significant portion of baseload energy in many regions. In the United States, it has the potential to provide 8.5% of the electric generation capacity by the middle of the century. In general, geothermal systems require heat, permeability, and water to be viable for energy generation. However, with current technologies, only heat is strictly necessary in a native system. Engineered geothermal systems (EGS) introduce water into the subsurface at elevated pressures and reduced temperatures and enhance permeability through hydraulic and/or shear fracturing. Additionally, although moderate- to high-temperature resources currently dominate geothermal energy production, low-temperature resources have been utilized for direct-use cases. When well balanced and maintained, geothermal resources can produce significant amounts of heat and achieve long-term sustainability on the order of an estimated tens to hundreds of years.

","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/tle39120855.1","usgsCitation":"Kaven, J., Templeton, D., and Bathija, A.P., 2020, Introduction to this special section: Geothermal energy: The Leading Edge, v. 39, no. 12, p. 855-856, https://doi.org/10.1190/tle39120855.1.","productDescription":"2 p.","startPage":"855","endPage":"856","ipdsId":"IP-123786","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":458209,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1772306","text":"External Repository"},{"id":411838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kaven, Joern 0000-0003-2625-2786","orcid":"https://orcid.org/0000-0003-2625-2786","contributorId":217694,"corporation":false,"usgs":true,"family":"Kaven","given":"Joern","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":861578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Templeton, Dennise","contributorId":300819,"corporation":false,"usgs":false,"family":"Templeton","given":"Dennise","email":"","affiliations":[{"id":65265,"text":"Lawrence Livermore National Lab","active":true,"usgs":false}],"preferred":false,"id":861579,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bathija, Arpita P.","contributorId":300831,"corporation":false,"usgs":false,"family":"Bathija","given":"Arpita","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":861598,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70213244,"text":"70213244 - 2020 - An open source database for the synthesis of soil radiocarbon data: ISRaD version 1.0","interactions":[],"lastModifiedDate":"2020-09-16T13:28:46.247242","indexId":"70213244","displayToPublicDate":"2020-01-06T13:58:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1426,"text":"Earth System Science Data","active":true,"publicationSubtype":{"id":10}},"title":"An open source database for the synthesis of soil radiocarbon data: ISRaD version 1.0","docAbstract":"

Radiocarbon is a critical constraint on our estimates of the timescales of soil carbon cycling that can aid in identifying mechanisms of carbon stabilization and destabilization and improve the forecast of soil carbon response to management or environmental change. Despite the wealth of soil radiocarbon data that have been reported over the past 75 years, the ability to apply these data to global-scale questions is limited by our capacity to synthesize and compare measurements generated using a variety of methods. Here, we present the International Soil Radiocarbon Database (ISRaD; http://soilradiocarbon.org, last access: 16 December 2019), an open-source archive of soil data that include reported measurements from bulk soils, distinct soil carbon pools isolated in the laboratory by a variety of soil fractionation methods, samples of soil gas or water collected interstitially from within an intact soil profile, CO2 gas isolated from laboratory soil incubations, and fluxes collected in situ from a soil profile. The core of ISRaD is a relational database structured around individual datasets (entries) and organized hierarchically to report soil radiocarbon data, measured at different physical and temporal scales as well as other soil or environmental properties that may also be measured and may assist with interpretation and context. Anyone may contribute their own data to the database by entering it into the ISRaD template and subjecting it to quality assurance protocols. ISRaD can be accessed through (1) a web-based interface, (2) an R package (ISRaD), or (3) direct access to code and data through the GitHub repository, which hosts both code and data. The design of ISRaD allows for participants to become directly involved in the management, design, and application of ISRaD data. The synthesized dataset is available in two forms: the original data as reported by the authors of the datasets and an enhanced dataset that includes ancillary geospatial data calculated within the ISRaD framework. ISRaD also provides data management tools in the ISRaD-R package that provide a starting point for data analysis; as an open-source project, the broader soil community is invited and encouraged to add data, tools, and ideas for improvement. As a whole, ISRaD provides resources to aid our evaluation of soil dynamics across a range of spatial and temporal scales. The ISRaD v1.0 dataset is archived and freely available at https://doi.org/10.5281/zenodo.2613911 (Lawrence et al., 2019).

","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-12-61-2020","usgsCitation":"Lawrence, C.R., Beem-Miller, J., Hoyt, A., Monroe, G., Sierra, C., Stoner, S., Heckman, K., Blankinship, J., Crow, S., McNichol, G., Trumbore, S., Levine, P., Vinduskova, O., Todd-Brown, K., Rasmussen, C., Hicks Pries, C., Schadel, C., McFarlane, K., Doetterl, S., Hatte, C., He, Y., Treat, C.C., Harden, J.W., Torn, M.S., Estop-Aragonés, C., Berhe, A.A., Keiluweit, M., Kuhnen, A.D., Marin-Spiotta, E., Plante, A.F., Thompson, A., Shi, Z., Schimel, J.P., Vaughn, L., von Fromm, S.F., and Wagai, R., 2020, An open source database for the synthesis of soil radiocarbon data: ISRaD version 1.0: Earth System Science Data, v. 12, no. 1, p. 61-76, https://doi.org/10.5194/essd-12-61-2020.","productDescription":"16 p.","startPage":"61","endPage":"76","ipdsId":"IP-105138","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science 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Federal agencies need credible scientific information to determine the production and value of ecosystem services in an efficient and timely manner. The U.S. Geological Survey addresses this scientific information need through the Sustaining Environmental Capital Initiative project. The project has relied on U.S. Geological Survey expertise related to water, fisheries, advanced modeling, and economics and other social sciences to conduct eight case studies across a range of environment types, including water-based environments, deserts, sagebrush ecosystems, floodplains, and forests. The Sustaining Environmental Capital Initiative also supported the development and expansion of four tools with the intent of adding content and usability for partners’ decision-making needs. The tools are the Natural Value Resource Center, Benefit Transfer Toolkit, Riverine Environmental Flow Decision Support System, and Artificial Intelligence for Ecosystem Services modeling platform.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191117","usgsCitation":"Huber, C., Meldrum, J.R., Schuster, R.M., Ancona, Z.H., Bagstad, K.J., Beck, S.M., Carlisle, D.M., Claggett, P.R., Franco, F., Galbraith, H.S., Haefele, M., Hoelting, K.R., Hogan, D.M., Hopkins, K.G., Kern, T., Lawrence, C.B., Lischka, S., Loomis, J.B., Mueller, J.M., Noe, G.B., Pindilli, E.J., Quay, B., Semmens, D.J., Sinclair, W., Spooner, D.E., Voigt, B., and St. John White, B., 2020, Sustaining Environmental Capital Initiative summary report: U.S. Geological Survey Open-File Report 2019–1117, 23 p., https://doi.org/10.3133/ofr20191117.","productDescription":"v, 23 p.","onlineOnly":"Y","ipdsId":"IP-099772","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":370958,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1117/ofr20191117.pdf","text":"Report","size":"348 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1117"},{"id":370957,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1117/coverthb.jpg"}],"contact":"

Director, Eastern Ecological Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118

","tableOfContents":"","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2020-01-06","noUsgsAuthors":false,"publicationDate":"2020-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Huber, Christopher 0000-0001-8446-8134 chuber@usgs.gov","orcid":"https://orcid.org/0000-0001-8446-8134","contributorId":127600,"corporation":false,"usgs":true,"family":"Huber","given":"Christopher","email":"chuber@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":778796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science 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Majuro Atoll in the central Pacific has high coastal vulnerability due to low-lying islands, rising sea level, high wave events, eroding shorelines, a dense population center, and limited freshwater resources. Land elevation is the primary geophysical variable that determines exposure to inundation in coastal settings. Accordingly, coastal elevation data (with accuracy information) are critical for assessments of inundation exposure. Previous research has demonstrated the importance of using high-accuracy elevation data and rigorously accounting for uncertainty in inundation assessments. A quantitative analysis of inundation exposure was conducted for Majuro Atoll, including accounting for the cumulative vertical uncertainty from the input digital elevation model (DEM) and datum transformation. The project employed a recently produced and validated DEM derived from structure-from-motion processing of very-high-resolution aerial imagery. Areas subject to marine inundation (direct hydrologic connection to the ocean) and low-lying lands (disconnected hydrologically from the ocean) were mapped and characterized for three inundation levels using deterministic and probabilistic methods. At the highest water level modeled (3.75 ft, or 1.143 m), more than 34% of the atoll study area is likely to be exposed to inundation (68% chance or greater), while more than 20% of the atoll is extremely likely to be exposed (95% chance or greater). The study demonstrates the substantial value of a high-accuracy DEM for assessing inundation exposure of low-relief islands and the enhanced information from accounting for vertical uncertainty.

","language":"English","publisher":"MDPI","doi":"10.3390/rs12010154","usgsCitation":"Gesch, D.B., Palaseanu-Lovejoy, M., Danielson, J.J., Fletcher, C., Kottermair, M., Barbee, M., and Jalandoni, A., 2020, Inundation exposure assessment for Majuro Atoll, Republic of the Marshall Islands using a high-accuracy digital elevation model: Remote Sensing, v. 12, no. 1, Article: 154, 20 p.; Data Release, https://doi.org/10.3390/rs12010154.","productDescription":"Article: 154, 20 p.; Data Release","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":458218,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12010154","text":"Publisher Index Page"},{"id":372951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":373335,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5ba9511ee4b08583a5ca09fe","text":"USGS data release","description":"USGS data release","linkHelpText":"Inundation exposure assessment for Majuro Atoll, Republic of the Marshall Islands"}],"country":"Republic of the Marshall Islands","otherGeospatial":"Majuro Atoll","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 170.98777770996094,\n 6.976183516197836\n ],\n [\n 171.43203735351562,\n 6.976183516197836\n ],\n [\n 171.43203735351562,\n 7.198319490613516\n ],\n [\n 170.98777770996094,\n 7.198319490613516\n ],\n [\n 170.98777770996094,\n 6.976183516197836\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":784036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":784037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":784038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fletcher, Charles","contributorId":192304,"corporation":false,"usgs":false,"family":"Fletcher","given":"Charles","affiliations":[],"preferred":false,"id":784039,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kottermair, Maria","contributorId":119958,"corporation":false,"usgs":true,"family":"Kottermair","given":"Maria","email":"","affiliations":[],"preferred":false,"id":784040,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barbee, Matthew 0000-0002-8929-7255","orcid":"https://orcid.org/0000-0002-8929-7255","contributorId":196651,"corporation":false,"usgs":false,"family":"Barbee","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":784041,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jalandoni, Andrea 0000-0002-4821-7183","orcid":"https://orcid.org/0000-0002-4821-7183","contributorId":196653,"corporation":false,"usgs":false,"family":"Jalandoni","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":784042,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224539,"text":"70224539 - 2020 - Nest site selection influences cinnamon teal nest survival in Colorado","interactions":[],"lastModifiedDate":"2021-09-27T14:46:51.635435","indexId":"70224539","displayToPublicDate":"2020-01-06T09:40:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Nest site selection influences cinnamon teal nest survival in Colorado","docAbstract":"

Nest survival of ducks is partially a function of the spatiotemporal characteristics of the site at which a bird chooses to nest. Nest survival is also a fundamental component of population growth in waterfowl but is relatively unstudied for cinnamon teal (Spatula cyanoptera). We investigated cinnamon teal nest survival in a managed wetland complex in southern Colorado, USA, and assessed nest site selection to determine whether nest site characteristics were adaptive. We monitored 85 nests in 2015–2017 on Monte Vista National Wildlife Refuge, Colorado and did not detect a difference in nest survival across years. Based on nest site selection data from 2017, cinnamon teal selected nest sites characterized by a lower proportion of forbs than available sites. The relationships between habitat characteristics and nest survival were variable. Microhabitat characteristics exhibited only weak effects on nest survival during the laying stage. Nest survival during incubation was negatively related to the proportion of forbs at the nest site and, to a lesser extent, the proportion of grasses. Nest site selection was predictive of future nest survival based on the percent of forbs and grasses around the nest site, suggesting teal select nest locations to benefit reproductive success. These results have the potential to guide local habitat management actions for breeding waterfowl. 

","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21818","usgsCitation":"Kendall, W.L., Setash, C.M., and Olson, D., 2020, Nest site selection influences cinnamon teal nest survival in Colorado: Journal of Wildlife Management, v. 84, no. 3, p. 542-552, https://doi.org/10.1002/jwmg.21818.","productDescription":"11 p.","startPage":"542","endPage":"552","ipdsId":"IP-105687","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":389811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Monte Vista National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.18011474609375,\n 37.45687303762862\n ],\n [\n -106.01394653320312,\n 37.45687303762862\n ],\n [\n -106.01394653320312,\n 37.53477698849112\n ],\n [\n -106.18011474609375,\n 37.53477698849112\n ],\n [\n -106.18011474609375,\n 37.45687303762862\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"84","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":823982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Setash, Casey M.","contributorId":265282,"corporation":false,"usgs":false,"family":"Setash","given":"Casey","email":"","middleInitial":"M.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":823983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olson, David","contributorId":265284,"corporation":false,"usgs":false,"family":"Olson","given":"David","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":823984,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216735,"text":"70216735 - 2020 - Wetland water-management may influence mercury bioaccumulation in songbirds and ducks at a mercury hotspot","interactions":[],"lastModifiedDate":"2020-12-03T14:02:51.380232","indexId":"70216735","displayToPublicDate":"2020-01-04T08:00:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Wetland water-management may influence mercury bioaccumulation in songbirds and ducks at a mercury hotspot","docAbstract":"

Mercury is a persistent, biomagnifying contaminant that can cause negative behavioral, immunological, and reproductive effects in wildlife and human populations. We examined the role of wetland water-management on mercury bioaccumulation in songbirds and ducks at Kellys Slough National Wildlife Refuge Complex, near Grand Forks, North Dakota USA. We assessed mercury concentrations in blood of wetland-foraging songbirds (80 common yellowthroats [Geothlypis trichas] and 14 Nelson’s sparrows [Ammospiza nelsoni]) and eggs of upland-nesting ducks (28 gadwall [Mareca strepera], 19 blue-winged teal [Spatula discors], and 13 northern shoveler [S. clypeta]) across four wetland water-management classifications. Nelson’s sparrow blood mercury concentrations were elevated (mean: 1.00 µg/g ww; 95% CL: 0.76–1.31) and similar to those reported 6 years previously. Mercury in songbird blood and duck eggs varied among wetland water-management classifications. Songbirds and ducks had 67% and 49% lower mercury concentrations, respectively, when occupying wetlands that were drawn down with water flow compared to individuals occupying isolated-depressional wetlands with no outflow. Additionally, songbirds within impounded and partially drawn-down wetland units with water flow had mercury concentrations that were 26–28% lower, respectively, than individuals within isolated-depressional wetlands with no outflow. Our results confirm that mercury concentrations in songbirds at Kellys Slough continue to be elevated and suggest that water-management could be an important tool for wetland managers to reduce bioaccumulation of mercury in birds.


","language":"English","publisher":"Springer","doi":"10.1007/s10646-019-02143-w","usgsCitation":"Winder, V.L., Anteau, M.J., Fisher, M.R., Wilcox, M.K., Igl, L., and Ackerman, J.T., 2020, Wetland water-management may influence mercury bioaccumulation in songbirds and ducks at a mercury hotspot: Ecotoxicology, v. 29, p. 1229-1239, https://doi.org/10.1007/s10646-019-02143-w.","productDescription":"11 p.","startPage":"1229","endPage":"1239","ipdsId":"IP-095797","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":380948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.1513671875,\n 47.57652571374621\n ],\n [\n -96.844482421875,\n 47.57652571374621\n ],\n [\n -96.844482421875,\n 49.009050809382046\n ],\n [\n -100.1513671875,\n 49.009050809382046\n ],\n [\n -100.1513671875,\n 47.57652571374621\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","noUsgsAuthors":false,"publicationDate":"2020-01-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Winder, Virginia L. 0000-0002-5756-3993","orcid":"https://orcid.org/0000-0002-5756-3993","contributorId":245355,"corporation":false,"usgs":false,"family":"Winder","given":"Virginia","email":"","middleInitial":"L.","affiliations":[{"id":49158,"text":"Department of Biology, Benedictine College, Atchison, KS, 66002 USA, vwinder@benedictine.edu","active":true,"usgs":false}],"preferred":false,"id":806014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":806013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Mark R","contributorId":245356,"corporation":false,"usgs":false,"family":"Fisher","given":"Mark","email":"","middleInitial":"R","affiliations":[{"id":49159,"text":"U.S. Fish and Wildlife Service, Devils Lake Wetland Management District, Devils Lake, ND, 58301 USA, mark_fisher@fws.gov","active":true,"usgs":false}],"preferred":false,"id":806015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilcox, Mary Kate","contributorId":245357,"corporation":false,"usgs":false,"family":"Wilcox","given":"Mary","email":"","middleInitial":"Kate","affiliations":[{"id":49160,"text":"Division of Biology, Kansas State University, Manhattan, KS 66502 USA, mkwilcox@ksu.edu","active":true,"usgs":false}],"preferred":false,"id":806016,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Igl, Lawrence 0000-0003-0530-7266","orcid":"https://orcid.org/0000-0003-0530-7266","contributorId":218901,"corporation":false,"usgs":true,"family":"Igl","given":"Lawrence","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":806017,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":806018,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208716,"text":"70208716 - 2020 - Formation and prevention of pipe scale from acid mine drainage at Iron Mountain and Leviathan Mines, California, USA","interactions":[],"lastModifiedDate":"2020-02-25T15:17:36","indexId":"70208716","displayToPublicDate":"2020-01-03T15:14:46","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Formation and prevention of pipe scale from acid mine drainage at Iron Mountain and Leviathan Mines, California, USA","docAbstract":"Pipelines carrying acid mine drainage (AMD) to treatment plants commonly form pipe scale, an Fe(III)-rich precipitate that forms inside the pipelines and requires periodic and costly cleanout and maintenance. Pipelines at Iron Mountain Mine (IMM) and Leviathan Mine (LM) in California carry acidic water from mine sources to a treatment plant and have developed pipe scale. Samples of scale and AMD were collected from both mine sites for mineralogical, microbiological, and chemical analysis. The scale mineralogy was primarily schwertmannite with minor amounts of poorly crystalline goethite. Although the bulk composition of the scale was similar along the length of the pipeline at IMM, the number of iron-oxidizing bacteria and concentrations of associated trace elements decreased along the flow-path inside the pipeline. Laboratory batch experiments with unfiltered AMD from IMM and LM showed that Fe(II) oxidation was driven by microbial activity when the pH was <5. A remediation strategy of decreasing the pH to <2.2 was tested through geochemical modeling and laboratory experiments. These experiments indicated that scale formation could be prevented by decreasing the pH, which could be achieved at IMM by mixing source waters. However, the presence of Fe(III)-rich scale in a pipeline buffers the pH to higher values that may affect the efficacy of this remedial approach.","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2020.104521","usgsCitation":"Campbell, K.M., Alpers, C.N., and Nordstrom, D.K., 2020, Formation and prevention of pipe scale from acid mine drainage at Iron Mountain and Leviathan Mines, California, USA: Applied Geochemistry, v. 115, 104521, 14 p. , https://doi.org/10.1016/j.apgeochem.2020.104521.","productDescription":"104521, 14 p. ","ipdsId":"IP-105776","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":458240,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2020.104521","text":"Publisher Index Page"},{"id":372639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Iron Mountain and Leviathan Mines","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.10455322265625,\n 40.065460682065535\n ],\n [\n -122.53875732421875,\n 40.065460682065535\n ],\n [\n -122.53875732421875,\n 40.6723059714534\n ],\n [\n -123.10455322265625,\n 40.6723059714534\n ],\n [\n -123.10455322265625,\n 40.065460682065535\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.16296386718749,\n 38.03078569382294\n ],\n [\n -118.9215087890625,\n 38.03078569382294\n ],\n [\n -118.9215087890625,\n 38.6897975322717\n ],\n [\n -120.16296386718749,\n 38.6897975322717\n ],\n [\n -120.16296386718749,\n 38.03078569382294\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"115","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":783148,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783149,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":783150,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211922,"text":"70211922 - 2020 - Estimating bedload from suspended load and water discharge in sand bed rivers","interactions":[],"lastModifiedDate":"2020-08-11T20:13:57.981854","indexId":"70211922","displayToPublicDate":"2020-01-03T15:10:09","publicationYear":"2020","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":"Estimating bedload from suspended load and water discharge in sand bed rivers","docAbstract":"

Estimates of fluvial sediment discharge from in situ instruments are an important component of large‐scale sediment budgets that track long‐term geomorphic change. Suspended sediment load can be reliably estimated using acoustic or physical sampling techniques; however, bedload is difficult to measure directly and can consequently be one of the largest sources of uncertainty in estimates of total load. We propose a physically informed predictive empirical model for bedload sand flux as a function of variables that are measured using existing acoustic or physical sampling techniques. This model depends on the assumption that concentration and grain size in suspension are in equilibrium with reach‐averaged boundary conditions. Bayesian inference is used to fit model parameters to data from eight sand‐bed rivers and to simulate bedload flux over the available gage record at one site on the Colorado River in Grand Canyon National Park. We find that the cumulative bedload flux during the 9 year period from 2008 to 2016 was 5% of the cumulative suspended sand load; however, instantaneous bedload flux ranged from as little as 1% of instantaneous suspended sand load to as much as 75% of instantaneous suspended sand load due to fluctuations in flow strength and sediment supply. Changes in bedload flux at a constant discharge are indicative of short‐term sediment supply enrichment and depletion. Long‐term average bedload flux cannot be expected to remain constant in the future as the river adjusts to changes in sediment runoff and the dam‐regulated discharge regime.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019WR025883","usgsCitation":"Ashley, T., McElroy, B., Buscombe, D., Grams, P.E., and Kaplinski, M., 2020, Estimating bedload from suspended load and water discharge in sand bed rivers: Water Resources Research, v. 56, no. 2, e2019WR025883, 25 p., https://doi.org/10.1029/2019WR025883.","productDescription":"e2019WR025883, 25 p.","ipdsId":"IP-108262","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":458242,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/essoar.10503756.1","text":"External Repository"},{"id":377386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.005126953125,\n 35.71083783530009\n ],\n [\n -111.37390136718749,\n 35.71083783530009\n ],\n [\n -111.37390136718749,\n 36.92793899776678\n ],\n [\n -114.005126953125,\n 36.92793899776678\n ],\n [\n -114.005126953125,\n 35.71083783530009\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Ashley, T.C.","contributorId":238017,"corporation":false,"usgs":false,"family":"Ashley","given":"T.C.","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":795824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McElroy, B.","contributorId":23797,"corporation":false,"usgs":true,"family":"McElroy","given":"B.","email":"","affiliations":[],"preferred":false,"id":795825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buscombe, D.","contributorId":44020,"corporation":false,"usgs":true,"family":"Buscombe","given":"D.","email":"","affiliations":[],"preferred":false,"id":795826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grams, Paul E. 0000-0002-0873-0708","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":216115,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":795827,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaplinski, M.","contributorId":31576,"corporation":false,"usgs":true,"family":"Kaplinski","given":"M.","email":"","affiliations":[],"preferred":false,"id":795828,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208492,"text":"70208492 - 2020 - Geographic and oceanographic influences on ferromanganese crust composition along a Pacific Ocean meridional transect, 14N to 14S","interactions":[],"lastModifiedDate":"2020-02-12T06:37:54","indexId":"70208492","displayToPublicDate":"2020-01-02T06:34:40","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Geographic and oceanographic influences on ferromanganese crust composition along a Pacific Ocean meridional transect, 14N to 14S","docAbstract":"The major controls on the variability of ferromanganese (FeMn) crust composition have been generally described over the past 40 years; however, most compilation studies lack quantitative statistics and are limited to a small region of several seamounts or compare FeMn crusts from disparate areas of the global oceans. This study provides the first detailed research to address the geographic and oceanographic controls of FeMn crust composition from a line of seamounts across 30° of latitude in the west central Pacific. Element concentrations from the uppermost layer (<15 mm) of 57 FeMn crusts were evaluated for statistically significant variance and correlation with a variety of oceanographic and geographic parameters. Manganese, Co, Ni, Mo, and Zn concentrations in crusts in this region are highly anticorrelated with seawater oxygen concentrations, suggesting oxygen as the dominant controlling factor for these elements. Iron instead correlates with water depth, which we attribute to increased carbonate ion concentration with increasing water depth. Silicon and Al content in crusts demonstrate a potential meridional variance of detrital inputs and sources in the region. Iron, Ba, and Mg are enriched in FeMn crusts below the equatorial upwelling zone which is related to biological productivity. Fluctuations in the four oceanographic and geographic parameters, seawater oxygen content, detrital input, surface productivity, and deep sources of iron, are robustly recorded by FeMn crusts. Modern measurements of these primary parameters, as well as paleoceanographic reconstructions, can be used to define regions of interest for FeMn crust exploration.","language":"English","publisher":"Wiley","doi":"10.1029/2019GC008716","usgsCitation":"Mizell, K., Hein, J.R., Lam, P.J., Koppers, A.A., and Staudigel, H., 2020, Geographic and oceanographic influences on ferromanganese crust composition along a Pacific Ocean meridional transect, 14N to 14S: Geochemistry, Geophysics, Geosystems, v. 21, no. 2, e2019GC008716, 19 p., https://doi.org/10.1029/2019GC008716.","productDescription":"e2019GC008716, 19 p.","ipdsId":"IP-111390","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":458255,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019gc008716","text":"Publisher Index Page"},{"id":437179,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93YOXHY","text":"USGS data release","linkHelpText":"Sorbed-water (H2O-) corrected chemistry for ferromanganese crust samples from the western equatorial Pacific Ocean"},{"id":372251,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Mizell, Kira 0000-0002-5066-787X kmizell@usgs.gov","orcid":"https://orcid.org/0000-0002-5066-787X","contributorId":4914,"corporation":false,"usgs":true,"family":"Mizell","given":"Kira","email":"kmizell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":782136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hein, James R. 0000-0002-5321-899X jhein@usgs.gov","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":140835,"corporation":false,"usgs":true,"family":"Hein","given":"James","email":"jhein@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":782137,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lam, Phoebe J. 0000-0001-6609-698X","orcid":"https://orcid.org/0000-0001-6609-698X","contributorId":222434,"corporation":false,"usgs":false,"family":"Lam","given":"Phoebe","email":"","middleInitial":"J.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":782138,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koppers, Anthony A.P. 0000-0002-8136-5372","orcid":"https://orcid.org/0000-0002-8136-5372","contributorId":222435,"corporation":false,"usgs":false,"family":"Koppers","given":"Anthony","email":"","middleInitial":"A.P.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":782141,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Staudigel, Hubert","contributorId":213217,"corporation":false,"usgs":false,"family":"Staudigel","given":"Hubert","email":"","affiliations":[{"id":38724,"text":"Scripps Institution of Oceanography, University of California San Diego","active":true,"usgs":false}],"preferred":false,"id":782142,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208425,"text":"70208425 - 2020 - Spatial and temporal dynamics of Pacific capelin Mallotus catervarius in the Gulf of Alaska: Implications for ecosystem-based fisheries management","interactions":[],"lastModifiedDate":"2020-03-11T15:24:50","indexId":"70208425","displayToPublicDate":"2020-01-01T18:04:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatial and temporal dynamics of Pacific capelin Mallotus catervarius in the Gulf of Alaska: Implications for ecosystem-based fisheries management","title":"Spatial and temporal dynamics of Pacific capelin Mallotus catervarius in the Gulf of Alaska: Implications for ecosystem-based fisheries management","docAbstract":"

Pacific capelin Mallotus catervarius are planktivorous, small pelagic fish that serve an intermediate trophic role in marine food webs. Due to the lack of a directed fishery or monitoring of capelin in the Northeast Pacific, there is limited information on their distribution and abundance, and how spatio-temporal fluctuations in capelin density affects their availability as prey. To provide information on life history, spatial patterns, and population dynamics of capelin in the Gulf of Alaska (GOA), we modeled distributions of spawning habitat and larval dispersal, and synthesized spatially-indexed data from multiple, independent sources from 1996 to 2016. Potential capelin spawning areas were broadly distributed across the GOA. Models of larval drift show the GOA’s advective circulation patterns disperse capelin larvae over the continental shelf and upper slope, indicating potential connections between spawning areas and observed offshore distributions that are influenced by the location and timing of spawning. Spatial overlap in composite distributions of larval and age-1+ fish was used to identify core areas where capelin consistently occur and concentrate. Capelin primarily occupy shelf waters near the Kodiak Archipelago, and are patchily distributed across the GOA shelf and inshore waters. Interannual variations in abundance along with spatio-temporal differences in density indicates the availability of capelin to predators and monitoring surveys is highly variable in the GOA. We demonstrate that the limitations of individual data series can be compensated for by integrating multiple data sources to monitor fluctuations in distributions and abundance trends of an ecologically important species across a large marine ecosystem.

","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/meps13211","usgsCitation":"David W. McGowan, Goldstein, E., Arimitsu, M.L., Dreary, A., Ormseth, O., DeRobertis, A., Horne, J., Lauren Rogers, Wilson, M., Coyle, K., Holderied, K., Piatt, J.F., Stockhausen, W., and Stephani Zador, 2020, Spatial and temporal dynamics of Pacific capelin Mallotus catervarius in the Gulf of Alaska: Implications for ecosystem-based fisheries management: Marine Ecology Progress Series, v. 637, p. 117-140, https://doi.org/10.3354/meps13211.","productDescription":"24 p.","startPage":"117","endPage":"140","ipdsId":"IP-109292","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":458260,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/54053","text":"External Repository"},{"id":437180,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96XJDK3","text":"USGS data release","linkHelpText":"Inshore Catch Data for Capelin (Mallotus villosus) in the Gulf of Alaska 1996-2017"},{"id":372202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.017578125,\n 55.52863052257191\n ],\n [\n -134.912109375,\n 55.52863052257191\n ],\n [\n -134.912109375,\n 59.93300042374631\n ],\n [\n -153.017578125,\n 59.93300042374631\n ],\n [\n -153.017578125,\n 55.52863052257191\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"637","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"David W. 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2020 - Avian community responses to management of vegetation and water levels in restored wetlands at the Humacao Nature Reserve, Puerto Rico","interactions":[],"lastModifiedDate":"2022-02-09T17:09:57.557067","indexId":"70228335","displayToPublicDate":"2020-01-01T10:56:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5533,"text":"Caribbean Naturalist","onlineIssn":"2326-7119","active":true,"publicationSubtype":{"id":10}},"title":"Avian community responses to management of vegetation and water levels in restored wetlands at the Humacao Nature Reserve, Puerto Rico","docAbstract":"

Coastal wetlands of the Caribbean have been greatly reduced in area and quality, and information on wildlife responses to management is lacking. We applied wetland management practices (disking, control of water levels) in a site historically disturbed by Saccharum spp. (sugarcane) cultivation at the Humacao Nature Reserve, southeastern Puerto Rico, and evaluated avian community response. We conducted weekly bird surveys and nest searches on disked and non-disked plots within recently constructed impoundments. The avian community shifted from 16 upland dominated species pre-restoration, to 67 wetland-dependent species at the end of our study (2001–2002). Ordination analysis indicated avian guild use of plots varied with environmental variables. Bird species diversity was not influenced by treatment, month, or salinity levels but was influenced by water depth and vegetation cover. Bird abundance was influenced by water depth, but not by treatment, month, salinity or vegetation cover. Furthermore, water depths of 0.10–0.20 m and salinity of ≤15 ppt promoted habitat conditions suitable for a diverse wetland avian community. We located 268 nests of 8 wetland bird species and observed adults with young of various other waterbirds, including species of conservation concern such as Dendrocygna arborea (West Indian Whistling Duck) and Porzana flaviventer (Yellow-breasted Crake). Bird community responses suggest that management practices (i.e., soil disturbance and control of water levels) can improve wetland biodiversity in abandoned sugarcane fields of Puerto Rico. Moreover, these practices may benefit wetland biodiversity in other Caribbean islands with a similar history of land use and habitat degradation.

","language":"English","publisher":"Eagle Hill Foundation","usgsCitation":"Vilella, F., Cruz-Burgos, J., Kaminski, R.M., Murkin, H.R., Davis, J.B., Weitzel, S.L., and Vizcarra, F., 2020, Avian community responses to management of vegetation and water levels in restored wetlands at the Humacao Nature Reserve, Puerto Rico: Caribbean Naturalist, v. 72, p. 1-21.","productDescription":"21 p.","startPage":"1","endPage":"21","ipdsId":"IP-110559","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":395683,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.eaglehill.us/CANAonline/CANA-access-pages/CANA-regular/CANA-072-Vilella.shtml"}],"country":"Puerto Rico","otherGeospatial":"Humacao Nature Reserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n 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Atlanta","active":true,"usgs":true}],"preferred":true,"id":833812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cruz-Burgos, José A.","contributorId":275207,"corporation":false,"usgs":false,"family":"Cruz-Burgos","given":"José A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":833813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaminski, Richard M.","contributorId":78205,"corporation":false,"usgs":false,"family":"Kaminski","given":"Richard","email":"","middleInitial":"M.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":833814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murkin, Henry R.","contributorId":275209,"corporation":false,"usgs":false,"family":"Murkin","given":"Henry","email":"","middleInitial":"R.","affiliations":[{"id":7182,"text":"Ducks Unlimited Canada","active":true,"usgs":false}],"preferred":false,"id":833815,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davis, J. Brian hdavis@usgs.gov","contributorId":199997,"corporation":false,"usgs":false,"family":"Davis","given":"J.","email":"hdavis@usgs.gov","middleInitial":"Brian","affiliations":[],"preferred":false,"id":833816,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weitzel, Spencer L.","contributorId":275211,"corporation":false,"usgs":false,"family":"Weitzel","given":"Spencer","email":"","middleInitial":"L.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":833817,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vizcarra, Fernando","contributorId":275212,"corporation":false,"usgs":false,"family":"Vizcarra","given":"Fernando","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":833818,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228137,"text":"70228137 - 2020 - Condition bias of decoy-harvested light geese during the conservation order","interactions":[],"lastModifiedDate":"2022-02-07T14:24:42.891997","indexId":"70228137","displayToPublicDate":"2020-01-01T10:50:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Condition bias of decoy-harvested light geese during the conservation order","docAbstract":"

Evidence that decoy harvest techniques primarily remove individuals of poorer body condition is well established in short-lived duck species; however, there is limited support for condition bias in longer-lived waterfowl species, such as geese, where decoy harvest is considered primarily additive because of their high natural survival rates. We evaluated support for the harvest condition bias hypothesis of 2 long-lived waterfowl species, the lesser snow goose (Anser caerulescens caerulescens) and Ross's goose (Anser rossii). We used proximate analysis to quantify lipid and protein content of lesser snow and Ross's geese collected during the Light Goose Conservation Order (LGCO) in 2015 and 2016 during spring migration in Arkansas, Missouri, Nebraska, and South Dakota, USA. In each state, LGCO participants collected birds using traditional decoy techniques and we collected birds from the general population using jump-shooting tactics. Total body lipid content in both lesser snow and Ross's geese varied with age, region of harvest, and harvest type (decoy or jump-shooting). On average, adult lesser snow and Ross's geese harvested over decoys had 60 g and 41 g, respectively, fewer lipids than conspecifics collected using jump-shooting. We observed lower lipid reserves in decoy-shot geese in all 4 states sampled despite general gains in lipid reserves as migration chronology progressed. Our data support that the harvest condition bias extends to longer-lived waterfowl species and during a life-history event (spring migration) in which harvest is not normally observed. In the case of overabundant light geese, the disproportionate harvest of poorer-conditioned lesser snow and Ross's geese may serve as an additional challenge against any realized effects of harvest to reduce the population, in addition to extremely low harvest rates.

","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21770","usgsCitation":"Fowler, D.N., Webb, E.B., and Vrtiska, M.P., 2020, Condition bias of decoy-harvested light geese during the conservation order: Journal of Wildlife Management, v. 84, no. 1, p. 33-44, https://doi.org/10.1002/jwmg.21770.","productDescription":"12 p.","startPage":"33","endPage":"44","ipdsId":"IP-104969","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri, Nebraska, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.0654296875,\n 34.57895241036948\n ],\n [\n -90.626220703125,\n 34.57895241036948\n ],\n [\n -90.626220703125,\n 35.567980458012094\n ],\n [\n -92.0654296875,\n 35.567980458012094\n ],\n [\n -92.0654296875,\n 34.57895241036948\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.38330078125,\n 38.950865400919994\n ],\n [\n -93.50463867187499,\n 38.950865400919994\n ],\n [\n -93.50463867187499,\n 39.884450178234395\n ],\n [\n -95.38330078125,\n 39.884450178234395\n ],\n [\n -95.38330078125,\n 38.950865400919994\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.1298828125,\n 40.01078714046552\n ],\n [\n -95.943603515625,\n 40.01078714046552\n ],\n [\n -95.943603515625,\n 41.04621681452063\n ],\n [\n -98.1298828125,\n 41.04621681452063\n ],\n [\n -98.1298828125,\n 40.01078714046552\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.0966796875,\n 43.8503744993026\n ],\n [\n -97.0751953125,\n 43.8503744993026\n ],\n [\n -97.0751953125,\n 45.19752230305682\n ],\n [\n -99.0966796875,\n 45.19752230305682\n ],\n [\n -99.0966796875,\n 43.8503744993026\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"84","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-10-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Fowler, Drew N.","contributorId":205356,"corporation":false,"usgs":false,"family":"Fowler","given":"Drew","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":833195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833196,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vrtiska, Mark P.","contributorId":54008,"corporation":false,"usgs":true,"family":"Vrtiska","given":"Mark","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":833197,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228784,"text":"70228784 - 2020 - Winter carry-over effects on spring body condition driven by agricultural subsidies to Lesser Snow Geese (Anser caersulscens caerulescens)","interactions":[],"lastModifiedDate":"2022-02-21T16:30:35.783872","indexId":"70228784","displayToPublicDate":"2020-01-01T10:22:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Winter carry-over effects on spring body condition driven by agricultural subsidies to Lesser Snow Geese (Anser caersulscens caerulescens)","title":"Winter carry-over effects on spring body condition driven by agricultural subsidies to Lesser Snow Geese (Anser caersulscens caerulescens)","docAbstract":"

Anthropogenic changes to landscapes associated with intensive agriculture often have deleterious effects on avian abundance. However, some species like the Lesser Snow Goose (Anser caerulescens caerulescens), can benefit from increases in agricultural crops on both wintering and migratory stopover sites. We investigated the influence of winter habitat use on spring body condition in Lesser Snow Goose, a species that has increased in population following expansion into agriculturally based winter habitats. We used stable isotope measurements of four elements (δ2H, δ13C, δ15N, and δ34S) to determine likely prior winter habitat use of snow geese collected during spring migration across Arkansas, Missouri, and Nebraska in 2016. We evaluated differences in body size, lipid, and protein reserves from individuals with isotope values that suggested winter habitat use in traditional coastal marsh and non-coastal /agriculture habitat. Inferred winter habitat influenced total body lipid levels in snow geese collected during spring migration. Adult and juvenile individuals inferred to have overwintered in coastal marsh (n = 60) had, on average, 33.4 g (95% Confidence Interval: 0.4 g, 66.4 g) less lipid than counterparts wintering in non-coastal / agricultural habitat (n = 77). Waterfowl foods found in marshes typically have low true metabolizable energy values as a consequence of their high fiber content, which likely increases daily consumption rates. Increased energy expenditure related to greater time spent foraging, paired with lower energetic rewards, may result in lower lipid reserves among geese using coastal marsh habitats compared to birds using agricultural landscapes. Consequently, carry-over effects based on winter habitat use could explain variation in lipid reserves among individuals during spring migration and may ultimately explain differential fitness rates or susceptibility to harvest. Our results have implications for the conservation and management of this species as historic wetland landscapes become more intensively converted and used for agricultural purposes.

","language":"English","publisher":"Resilience Alliance","doi":"10.5751/ACE-01743-150221","usgsCitation":"Fowler, D.N., Webb, E.B., Vrtiska, M.P., and Hobson, K., 2020, Winter carry-over effects on spring body condition driven by agricultural subsidies to Lesser Snow Geese (Anser caersulscens caerulescens): Avian Conservation and Ecology, v. 15, no. 2, p. 1-11, https://doi.org/10.5751/ACE-01743-150221.","productDescription":"21, 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-114318","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":458267,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-01743-150221","text":"Publisher Index Page"},{"id":396226,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri, Nebraska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.52636718749999,\n 33.65120829920497\n ],\n [\n -94.0869140625,\n 33.61461929233378\n ],\n [\n -94.0869140625,\n 33.02708758002874\n ],\n [\n -91.1865234375,\n 32.99023555965106\n ],\n [\n -91.14257812499999,\n 33.578014746143985\n ],\n [\n -90.8349609375,\n 34.08906131584994\n ],\n [\n -90.04394531249999,\n 35.10193405724606\n ],\n [\n -89.4287109375,\n 36.527294814546245\n ],\n [\n -89.12109375,\n 36.63316209558658\n ],\n [\n -89.12109375,\n 37.09023980307208\n ],\n [\n -89.384765625,\n 37.26530995561875\n ],\n [\n -89.5166015625,\n 37.82280243352756\n ],\n [\n -90.263671875,\n 38.34165619279595\n ],\n [\n -90.04394531249999,\n 38.685509760012\n ],\n [\n -90.615234375,\n 39.16414104768742\n ],\n [\n -91.4501953125,\n 40.17887331434696\n ],\n [\n -91.3623046875,\n 40.51379915504413\n ],\n [\n -91.7138671875,\n 40.713955826286046\n ],\n [\n -95.8447265625,\n 40.74725696280421\n ],\n [\n -95.80078125,\n 41.244772343082076\n ],\n [\n -96.50390625,\n 42.5530802889558\n ],\n [\n -96.9873046875,\n 42.84375132629021\n ],\n [\n -97.7783203125,\n 42.94033923363181\n ],\n [\n -98.0419921875,\n 42.8115217450979\n ],\n [\n -98.61328125,\n 43.068887774169625\n ],\n [\n -104.0625,\n 43.03677585761058\n ],\n [\n -104.150390625,\n 40.97989806962013\n ],\n [\n -102.12890625,\n 41.0130657870063\n ],\n [\n -102.0849609375,\n 39.977120098439634\n ],\n [\n -95.4052734375,\n 40.01078714046552\n ],\n [\n -95.0537109375,\n 39.842286020743394\n ],\n [\n -95.1416015625,\n 39.57182223734374\n ],\n [\n -94.6142578125,\n 39.027718840211605\n ],\n [\n -94.7021484375,\n 36.63316209558658\n ],\n [\n -94.52636718749999,\n 35.53222622770337\n ],\n [\n -94.52636718749999,\n 33.65120829920497\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fowler, Drew N.","contributorId":205356,"corporation":false,"usgs":false,"family":"Fowler","given":"Drew","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":835467,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":835468,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vrtiska, Mark P.","contributorId":54008,"corporation":false,"usgs":true,"family":"Vrtiska","given":"Mark","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":835469,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hobson, Keith A.","contributorId":47306,"corporation":false,"usgs":true,"family":"Hobson","given":"Keith A.","affiliations":[],"preferred":false,"id":835470,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223693,"text":"70223693 - 2020 - Reconstruction of an early Permian, sublacustrine magmatic-hydrothermal system: Mount Carlton epithermal Au-Ag-Cu deposit, northeastern Australia","interactions":[],"lastModifiedDate":"2021-09-01T15:13:30.331799","indexId":"70223693","displayToPublicDate":"2020-01-01T10:07:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Reconstruction of an early Permian, sublacustrine magmatic-hydrothermal system: Mount Carlton epithermal Au-Ag-Cu deposit, northeastern Australia","docAbstract":"

The Mt. Carlton Au-Ag-Cu deposit, northern Bowen basin, northeastern Australia, is an uncommon example of a sublacustrine hydrothermal system containing economic high-sulfidation epithermal mineralization. The deposit formed in the early Permian and comprises vein- and hydrothermal breccia-hosted Au-Cu mineralization within a massive rhyodacite porphyry (V2 open pit) and stratabound Ag-barite mineralization within volcano-lacustrine sedimentary rocks (A39 open pit). These orebodies are all associated with extensive advanced argillic alteration of the volcanic host rocks. Stable isotope data for disseminated alunite (δ34S = 6.3–29.2‰; δ18OSO4 = –0.1 to 9.8‰; δ18OOH = –15.3 to –3.4‰; δD = –102 to –79‰) and pyrite (δ34S = –8.8 to –2.7‰), and void-filling anhydrite (δ34S = 17.2–19.2‰; δ18OSO4 = 1.8–5.7‰), suggest that early advanced argillic alteration formed within a magmatic-hydrothermal system. The ascending magmatic vapor (δ34SΣS ≈ –1.3‰) was absorbed by meteoric water (~50–60% meteoric component), producing an acidic (pH ≈ 1) condensate that formed a silicic → quartz-alunite → quartz-dickite-kaolinite zoned alteration halo with increasing distance from feeder structures. The oxygen and hydrogen isotope compositions of alunite-forming fluids at Mt. Carlton are lighter than those documented at similar deposits elsewhere, probably due to the high paleolatitude (~S60°) of northeastern Australia in the early Permian. Veins of coarse-grained, banded plumose alunite (δ34S = 0.4– 7.0‰; δ18OSO4 = 2.3–6.0‰; δ18OOH = –10.3 to –2.9‰; δD = –106 to –93‰) formed within feeder structures during the final stages of advanced argillic alteration. Epithermal mineralization was deposited subsequently, initially as fracture- and fissure-filling, Au-Cu–rich assemblages within feeder structures at depth. As the mineralizing fluids discharged into lakes, they produced syngenetic Ag-barite ore. Isotope data for ore-related sulfides and sulfosalts (δ34S = –15.0 to –3.0‰) and barite (δ34S = 22.3–23.8‰; δ18OSO4 = –0.2 to 1.3‰), and microthermometric data for primary fluid inclusions in barite (Th = 116°– 233°C; 0.0–1.7 wt % NaCl), are consistent with metal deposition at temperatures of ~200 ± 40°C (for Au-Cu mineralization in V2 pit) and ~150 ± 30°C (Ag mineralization in A39 pit) from a low-salinity, sulfur- and metal-rich magmatic-hydrothermal liquid that mixed with vapor-heated meteoric water. The mineralizing fluids initially had a high-sulfidation state, producing enargite-dominated ore with associated silicification of the early-altered wall rock. With time, the fluids evolved to an intermediate-sulfidation state, depositing sphalerite- and tennantite-dominated ore mineral assemblages. Void-filling massive dickite (δ18O = –1.1 to 2.1‰; δD = –121 to –103‰) with pyrite was deposited from an increasingly diluted magmatic-hydrothermal liquid (≥70% meteoric component) exsolved from a progressively degassed magma. Gypsum (δ34S = 11.4–19.2‰; δ18OSO4 = 0.5–3.4‰) occurs in veins within postmineralization faults and fracture networks, likely derived from early anhydrite that was dissolved by circulating meteoric water during extensional deformation. This process may explain the apparent scarcity of hypogene anhydrite in lithocaps elsewhere. While the Mt. Carlton system is similar to those that form subaerial high-sulfidation epithermal deposits, it also shares several key characteristics with magmatic-hydrothermal systems that form base and precious metal mineralization in shallow-submarine volcanic arc and back-arc settings. The lacustrine paleosurface features documented at Mt. Carlton may be useful as exploration indicators for concealed epithermal mineralization in similar extensional terranes elsewhere.

","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.4696","usgsCitation":"Sahlstrom, F., Chang, Z., Arribas , A., Dirks, P., Johnson, C.A., Huizenga, J., and Corral, I., 2020, Reconstruction of an early Permian, sublacustrine magmatic-hydrothermal system: Mount Carlton epithermal Au-Ag-Cu deposit, northeastern Australia: Economic Geology, v. 115, no. 1, p. 129-152, https://doi.org/10.5382/econgeo.4696.","productDescription":"24 p.","startPage":"129","endPage":"152","ipdsId":"IP-106958","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":458270,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/10037/19232","text":"External Repository"},{"id":388735,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 143.525390625,\n -23.362428593408826\n ],\n [\n 149.94140625,\n -23.362428593408826\n ],\n [\n 149.94140625,\n -14.221788628397585\n ],\n [\n 143.525390625,\n -14.221788628397585\n ],\n [\n 143.525390625,\n -23.362428593408826\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"115","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sahlstrom, Fredrik","contributorId":221543,"corporation":false,"usgs":false,"family":"Sahlstrom","given":"Fredrik","email":"","affiliations":[{"id":40403,"text":"James Cook University","active":true,"usgs":false}],"preferred":false,"id":822346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chang, Zhaoshan","contributorId":201393,"corporation":false,"usgs":false,"family":"Chang","given":"Zhaoshan","email":"","affiliations":[],"preferred":false,"id":822347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arribas , Antonio","contributorId":190234,"corporation":false,"usgs":false,"family":"Arribas ","given":"Antonio","affiliations":[],"preferred":false,"id":822348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dirks, Paul","contributorId":221544,"corporation":false,"usgs":false,"family":"Dirks","given":"Paul","email":"","affiliations":[{"id":40403,"text":"James Cook University","active":true,"usgs":false}],"preferred":false,"id":822349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":822350,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Huizenga, Jan M","contributorId":221545,"corporation":false,"usgs":false,"family":"Huizenga","given":"Jan M","affiliations":[{"id":40403,"text":"James Cook University","active":true,"usgs":false}],"preferred":false,"id":822351,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Corral, Isaac","contributorId":177243,"corporation":false,"usgs":false,"family":"Corral","given":"Isaac","email":"","affiliations":[],"preferred":false,"id":822352,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216693,"text":"70216693 - 2020 - Improving predictions of water supply in the Rio Grande under changing climate conditions","interactions":[],"lastModifiedDate":"2021-02-18T16:04:26.417642","indexId":"70216693","displayToPublicDate":"2020-01-01T10:02:20","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5883,"text":"Cooperator Report","active":true,"publicationSubtype":{"id":1}},"title":"Improving predictions of water supply in the Rio Grande under changing climate conditions","docAbstract":"This product is a case study summarizing the original work authored by David Gutzler, Shaleene Chavarria, and Nels Bjarke. The content will be part of a collection of Case Studies shared via the Collaborative Conservation and Adaptation Strategy Toolbox (CCAST). The research featured in this case study is an analysis of historical observations and climate models developed by the US Bureau of Reclamation. The work aims to identify changes to streamflow predictability, assess future predictability, and inform the development of more reliable water supply outlooks essential for planning purposes in the Upper Rio Grande Basin.","language":"English","publisher":"CCAST","usgsCitation":"Casarez, I.R., 2020, Improving predictions of water supply in the Rio Grande under changing climate conditions: Cooperator Report, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-123347","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":383316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383315,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://usbr.maps.arcgis.com/apps/MapSeries/index.html?appid=e1174c82d65f4124872bb1fe1efa9c3b"}],"country":"United States","state":"Colorado, New Mexico","otherGeospatial":"Upper Rio Grande River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.55639648437499,\n 36.155617833818525\n ],\n [\n -104.96337890625,\n 36.155617833818525\n ],\n [\n -104.96337890625,\n 37.75334401310656\n ],\n [\n -106.55639648437499,\n 37.75334401310656\n ],\n [\n -106.55639648437499,\n 36.155617833818525\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Casarez, Ilana Renae 0000-0001-7690-3802","orcid":"https://orcid.org/0000-0001-7690-3802","contributorId":228961,"corporation":false,"usgs":true,"family":"Casarez","given":"Ilana","email":"","middleInitial":"Renae","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":805902,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70216888,"text":"70216888 - 2020 - Technical memorandum: Compound specific isotope analysis, Oak Grove Village well site OU1, Franklin County, Missouri","interactions":[],"lastModifiedDate":"2024-03-21T14:26:25.648252","indexId":"70216888","displayToPublicDate":"2020-01-01T09:20:14","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Technical memorandum: Compound specific isotope analysis, Oak Grove Village well site OU1, Franklin County, Missouri","docAbstract":"

A study involving Compound Specific Isotope Analysis (CSIA) of trichloroethene (TCE) in groundwater at the Oak Grove Village (OGV) Well Site was conducted by the U.S. Environmental Protection Agency (EPA) in 2014 in an effort to fingerprint the source(s). This technical memorandum, written as a joint effort between HydroGeoLogic, Inc. (HGL) and the U.S. Geological Survey (USGS) Central Midwest Water Science Center (Schumacher, 2019), documents the procedures and analysis of the CSIA investigation.

CSIA is an analytical method that measures the isotopic ratios of naturally occurring stable isotopes in specific chemical compounds in environmental samples. CSIA using primarily the ratio of carbon 13C/12C (δ13C), known as 1-D CSIA, has been used for decades in evaluating degradation pathways of organic compounds, including chlorinated solvents such as TCE. Ratios of stable chlorine isotopes 37Cl/35Cl (δ37Cl) also have been used with carbon isotopes, collectively known as 2-D CSIA, and most recently isotopes of hydrogen 2H/1H (δ2H) have been added, collectively known as 3-D CSIA, in attempts to further determine source, transport, and fate of compounds such as TCE (Ertl et al., 1998; Hunkeler et al., 2011; Kuder et al., 2013; McHugh et al., 2011; Shouakar-Stash et al., 2003; EPA, 2008; and van Warmerdam et al., 1995.

","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Final data evaluation report, Oak Grove Village well site operable unit 1, Franklin County, Missouri","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"U.S. Environmental Protection Agency","usgsCitation":"Chase, P., and Schumacher, J.G., 2020, Technical memorandum: Compound specific isotope analysis, Oak Grove Village well site OU1, Franklin County, Missouri, 27 p.","productDescription":"27 p.","startPage":"815","endPage":"841","ipdsId":"IP-114566","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":426830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":426829,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://semspub.epa.gov/work/07/40561061.pdf"}],"country":"United States","state":"Missouri","city":"Oak Grove Village","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.14878655389475,\n 38.23000770114828\n ],\n [\n -91.15706332261682,\n 38.23000770114828\n ],\n [\n -91.15706332261682,\n 38.22066212844692\n ],\n [\n -91.14878655389475,\n 38.22066212844692\n ],\n [\n -91.14878655389475,\n 38.23000770114828\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chase, Phyliss","contributorId":245651,"corporation":false,"usgs":false,"family":"Chase","given":"Phyliss","email":"","affiliations":[{"id":49247,"text":"Hydrogeologic Inc. (HGL)","active":true,"usgs":false}],"preferred":false,"id":806744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schumacher, John G. 0000-0002-8840-5912 jschu@usgs.gov","orcid":"https://orcid.org/0000-0002-8840-5912","contributorId":206513,"corporation":false,"usgs":true,"family":"Schumacher","given":"John","email":"jschu@usgs.gov","middleInitial":"G.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806743,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}