{"pageNumber":"261","pageRowStart":"6500","pageSize":"25","recordCount":46679,"records":[{"id":70260098,"text":"70260098 - 2020 - Goals and development of the Alaska Volcano Observatory Seismic Network and application to forecasting and detecting volcanic eruptions","interactions":[],"lastModifiedDate":"2024-10-30T22:23:31.538975","indexId":"70260098","displayToPublicDate":"2020-01-02T07:06:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Goals and development of the Alaska Volcano Observatory Seismic Network and application to forecasting and detecting volcanic eruptions","docAbstract":"<p>The Alaska Volcano Observatory (AVO) seismic network has been in operation since 1988 and during this time has grown from 29 to 217 seismic stations providing real-time monitoring of 32 active volcanoes in Alaska, as well as useful data for regional earthquake monitoring. Since 1988, AVO has detected 59 volcanic eruptions at Aleutian arc volcanoes, and 31 of these have been captured by local seismic instrumentation. As part of this monitoring effort, AVO has cataloged more than 120,000 earthquake hypocenters and magnitudes associated with volcanic processes throughout the arc. This high rate of volcanic activity provides an excellent opportunity to study seismicity associated with magmatic and eruptive processes and develop and refine analytical techniques to track volcanic seismicity and warn of hazardous eruptions. The network is currently undergoing an extensive upgrade, replacing aging short-period analog seismometers with digital broadband instruments. These are expected to improve AVO’s seismic capability and further facilitate other geophysical instrumentation such as continuous Global Positioning System receivers, infrasound sensors, and web cams.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190216","usgsCitation":"Power, J., Haney, M.M., Botnick, S.M., Dixon, J.P., Fee, D., Kaufman, M., Ketner, D.M., Lyons, J.J., Parker, T., Paskievitch, J.F., Read, C., Searcy, C., Stihler, S.D., Tepp, G., and Wech, A., 2020, Goals and development of the Alaska Volcano Observatory Seismic Network and application to forecasting and detecting volcanic eruptions: Seismological Research Letters, v. 91, no. 2A, p. 647-659, https://doi.org/10.1785/0220190216.","productDescription":"13 p.","startPage":"647","endPage":"659","ipdsId":"IP-111065","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":463242,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","issue":"2A","noUsgsAuthors":false,"publicationDate":"2020-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Power, John 0000-0002-7233-4398","orcid":"https://orcid.org/0000-0002-7233-4398","contributorId":215240,"corporation":false,"usgs":true,"family":"Power","given":"John","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":916975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Botnick, Steven M 0000-0002-3284-9127","orcid":"https://orcid.org/0000-0002-3284-9127","contributorId":344718,"corporation":false,"usgs":true,"family":"Botnick","given":"Steven","email":"","middleInitial":"M","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dixon, James P. 0000-0002-8478-9971 jpdixon@usgs.gov","orcid":"https://orcid.org/0000-0002-8478-9971","contributorId":3163,"corporation":false,"usgs":true,"family":"Dixon","given":"James","email":"jpdixon@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fee, David 0000-0002-0936-9977","orcid":"https://orcid.org/0000-0002-0936-9977","contributorId":267231,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":13097,"text":"Geophysical Institute, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":916978,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kaufman, Max","contributorId":140427,"corporation":false,"usgs":false,"family":"Kaufman","given":"Max","email":"","affiliations":[{"id":13493,"text":"UAFGI","active":true,"usgs":false}],"preferred":false,"id":916979,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ketner, Dane M. 0000-0002-1610-0773","orcid":"https://orcid.org/0000-0002-1610-0773","contributorId":217809,"corporation":false,"usgs":true,"family":"Ketner","given":"Dane","email":"","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916980,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":916981,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Parker, Thomas 0000-0002-3006-5652 tparker@usgs.gov","orcid":"https://orcid.org/0000-0002-3006-5652","contributorId":215241,"corporation":false,"usgs":true,"family":"Parker","given":"Thomas","email":"tparker@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":916982,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Paskievitch, John F. 0000-0003-3500-0177 jpaskie@usgs.gov","orcid":"https://orcid.org/0000-0003-3500-0177","contributorId":345580,"corporation":false,"usgs":true,"family":"Paskievitch","given":"John","email":"jpaskie@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916983,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Read, Cyrus 0000-0003-3259-4723 cread@usgs.gov","orcid":"https://orcid.org/0000-0003-3259-4723","contributorId":345581,"corporation":false,"usgs":true,"family":"Read","given":"Cyrus","email":"cread@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916984,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Searcy, Cheryl 0000-0002-9474-5754 csearcy@usgs.gov","orcid":"https://orcid.org/0000-0002-9474-5754","contributorId":345582,"corporation":false,"usgs":true,"family":"Searcy","given":"Cheryl","email":"csearcy@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916985,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stihler, Scott D. 0000-0002-3585-7050","orcid":"https://orcid.org/0000-0002-3585-7050","contributorId":215242,"corporation":false,"usgs":false,"family":"Stihler","given":"Scott","email":"","middleInitial":"D.","affiliations":[{"id":39214,"text":"Alaska Volcano Observatory, UAFGI.","active":true,"usgs":false}],"preferred":false,"id":916986,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Tepp, Gabrielle 0000-0001-5388-5138","orcid":"https://orcid.org/0000-0001-5388-5138","contributorId":206305,"corporation":false,"usgs":true,"family":"Tepp","given":"Gabrielle","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916987,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wech, Aaron 0000-0003-4983-1991","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":202561,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916988,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70208758,"text":"70208758 - 2020 - Evaluating social vulnerability indicators: Criteria and their application to the Social Vulnerability Index","interactions":[],"lastModifiedDate":"2020-03-02T06:24:10","indexId":"70208758","displayToPublicDate":"2020-01-02T06:40:23","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating social vulnerability indicators: Criteria and their application to the Social Vulnerability Index","docAbstract":"As a concept, social vulnerability describes combinations of social, cultural, economic,\npolitical, and institutional processes that shape socioeconomic differentials in the experience\nof and recovery from hazards. Quantitative measures of social vulnerability are\nwidely used in research and practice. In this paper, we establish criteria for the evaluation\nof social vulnerability indicators and apply those criteria to the most widely used measure\nof social vulnerability, the Social Vulnerability Index (SoVI). SoVI is a single quantitative\nindicator that purports to measure a place’s social vulnerability. We show that SoVI\nhas some critical shortcomings regarding theoretical and internal consistency. Specifically,\nmultiple SoVI-based measurements of the vulnerability of the same place, using the same\ndata, can yield strikingly different results. We also show that the SoVI is often misaligned\nwith theory; increases in variables that contribute to vulnerability, like the unemployment\nrate, often decrease vulnerability as measured by the SoVI. We caution against the use of\nthe index in policy making or other risk-reduction efforts, and we suggest ways to more\nreliably assess social vulnerability in practice.","language":"English","publisher":"Springer","doi":"10.1007/s11069-019-03820-z","usgsCitation":"Spielman, S., Tuccillo, J., Folch, D., Schweikert, A., Davies, R., Wood, N.J., and Tate, E., 2020, Evaluating social vulnerability indicators: Criteria and their application to the Social Vulnerability Index: Natural Hazards, v. 100, no. 1, p. 417-436, https://doi.org/10.1007/s11069-019-03820-z.","productDescription":"20 p.","startPage":"417","endPage":"436","ipdsId":"IP-113587","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":372721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Spielman, Seth","contributorId":146151,"corporation":false,"usgs":false,"family":"Spielman","given":"Seth","email":"","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":783286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tuccillo, Joseph","contributorId":222828,"corporation":false,"usgs":false,"family":"Tuccillo","given":"Joseph","email":"","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":783287,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Folch, David","contributorId":222829,"corporation":false,"usgs":false,"family":"Folch","given":"David","email":"","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":783288,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schweikert, Amy","contributorId":204479,"corporation":false,"usgs":false,"family":"Schweikert","given":"Amy","email":"","affiliations":[],"preferred":false,"id":783289,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davies, Rebecca","contributorId":222830,"corporation":false,"usgs":false,"family":"Davies","given":"Rebecca","email":"","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":783290,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":783285,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tate, Eric","contributorId":222831,"corporation":false,"usgs":false,"family":"Tate","given":"Eric","email":"","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":783291,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"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 <i>Mallotus catervarius</i> 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":"<p><span>Pacific capelin&nbsp;</span><i>Mallotus catervarius</i><span>&nbsp;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.</span></p>","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. McGowan","contributorId":222299,"corporation":false,"usgs":false,"family":"David W. McGowan","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":781827,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldstein, Esther","contributorId":222300,"corporation":false,"usgs":false,"family":"Goldstein","given":"Esther","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":781826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dreary, Alison","contributorId":222301,"corporation":false,"usgs":false,"family":"Dreary","given":"Alison","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ormseth, Olav","contributorId":222302,"corporation":false,"usgs":false,"family":"Ormseth","given":"Olav","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781830,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeRobertis, Alex","contributorId":222303,"corporation":false,"usgs":false,"family":"DeRobertis","given":"Alex","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781831,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Horne, John","contributorId":222304,"corporation":false,"usgs":false,"family":"Horne","given":"John","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":781832,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lauren Rogers","contributorId":222305,"corporation":false,"usgs":false,"family":"Lauren Rogers","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781833,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wilson, Matt","contributorId":222306,"corporation":false,"usgs":false,"family":"Wilson","given":"Matt","email":"","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781834,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Coyle, Kenneth","contributorId":222307,"corporation":false,"usgs":false,"family":"Coyle","given":"Kenneth","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":781835,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Holderied, Kris","contributorId":222308,"corporation":false,"usgs":false,"family":"Holderied","given":"Kris","affiliations":[{"id":40515,"text":"NOAA Kasitsna Bay Lab","active":true,"usgs":false}],"preferred":false,"id":781836,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":781837,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stockhausen, W.T.","contributorId":31952,"corporation":false,"usgs":true,"family":"Stockhausen","given":"W.T.","email":"","affiliations":[],"preferred":false,"id":781987,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Stephani Zador","contributorId":222309,"corporation":false,"usgs":false,"family":"Stephani Zador","affiliations":[{"id":40514,"text":"NOAA NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":781838,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"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":"<div class=\"article-section__content en main\"><p>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 (<i>Anser caerulescens caerulescens</i>) and Ross's goose (<i>Anser rossii</i>). 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.</p></div>","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":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":"<p><span>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 (</span><i>δ</i><sup>34</sup><span>S = 6.3–29.2‰;&nbsp;</span><i>δ</i><sup>18</sup><span>OSO</span><sub>4</sub><span>&nbsp;= –0.1 to 9.8‰;&nbsp;</span><i>δ</i><sup>18</sup><span>O</span><sub>OH</sub><span>&nbsp;= –15.3 to –3.4‰;&nbsp;</span><i>δ</i><span>D = –102 to –79‰) and pyrite (</span><i>δ</i><sup>34</sup><span>S = –8.8 to –2.7‰), and void-filling anhydrite (</span><i>δ</i><sup>34</sup><span>S = 17.2–19.2‰;&nbsp;</span><i>δ</i><sup>18</sup><span>O</span><sub>SO4</sub><span>&nbsp;= 1.8–5.7‰), suggest that early advanced argillic alteration formed within a magmatic-hydrothermal system. The ascending magmatic vapor (</span><i>δ</i><sup>34</sup><span>S</span><sub>ΣS</sub><span>&nbsp;≈ –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 (</span><i>δ</i><sup>34</sup><span>S = 0.4– 7.0‰;&nbsp;</span><i>δ</i><sup>18</sup><span>O</span><sub>SO4</sub><span>&nbsp;= 2.3–6.0‰;&nbsp;</span><i>δ</i><sup>18</sup><span>O</span><sub>OH</sub><span>&nbsp;= –10.3 to –2.9‰;&nbsp;</span><i>δ</i><span>D = –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 (</span><i>δ</i><sup>34</sup><span>S = –15.0 to –3.0‰) and barite (</span><i>δ</i><sup>34</sup><span>S = 22.3–23.8‰;&nbsp;</span><i>δ</i><sup>18</sup><span>O</span><sub>SO4</sub><span>&nbsp;= –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 (</span><i>δ</i><sup>18</sup><span>O = –1.1 to 2.1‰;&nbsp;</span><i>δ</i><span>D = –121 to –103‰) with pyrite was deposited from an increasingly diluted magmatic-hydrothermal liquid (≥70% meteoric component) exsolved from a progressively degassed magma. Gypsum (</span><i>δ</i><sup>34</sup><span>S = 11.4–19.2‰;&nbsp;</span><i>δ</i><sup>18</sup><span>O</span><sub>SO4</sub><span>&nbsp;= 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.</span></p>","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":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":"<p>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. </p><p>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 <sup>13</sup>C/<sup>12</sup>C (δ<sup>13</sup>C), 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 <sup>37</sup>Cl/<sup>35</sup>Cl (δ<sup>37</sup>Cl) also have been used with carbon isotopes, collectively known as 2-D CSIA, and most recently isotopes of hydrogen <sup>2</sup>H/<sup>1</sup>H (δ<sup>2</sup>H) 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.</p>","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}]}}
,{"id":70244010,"text":"70244010 - 2020 - Using advanced population genomics to better understand the relationship between offshore and spawning habitat use for Atlantic Sturgeon","interactions":[],"lastModifiedDate":"2023-05-31T14:05:38.468729","indexId":"70244010","displayToPublicDate":"2020-01-01T08:58:09","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5709,"text":"OCS Study","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"2020-062","title":"Using advanced population genomics to better understand the relationship between offshore and spawning habitat use for Atlantic Sturgeon","docAbstract":"<p>Atlantic Sturgeon (<i>Acipenser oxyrinchus oxyrinchus</i>) are a large-bodied anadromous fish that historically supported important fisheries along the east coast of the United States. Following years of overharvest and habitat degradation, populations experienced severe declines. In 2012, the National Marine Fisheries Service listed Atlantic Sturgeon under the Endangered Species Act (ESA; 61 FR 4722). Their listing named five Distinct Population Segments (DPSs), predicated on genetic groups composed of geographically proximate populations. </p><p>Federal management of Atlantic Sturgeon presents challenges, as sturgeon from each of the five DPSs mix extensively in coastal and marine habitats yet take and recovery progress must be evaluated separately for each unit. Genetic assignment testing based on mitochondrial and microsatellite markers allows individuals to be assigned back to their natal river and DPS. However, this approach is not perfect and some individuals may be incorrectly assigned. Recent advances in genomics offer the potential of a higher resolution approach to genetic assignment testing, and thus may reduce uncertainty associated with assignment testing. In addition, genomics allows a greater number of markers to be examined from across a broader portion of the sturgeon genome, thus may provide an enhanced perspective of population structure for the species, and potentially allow other previously intractable questions to be addressed (Bernatchez et al. 2017, Supple and Shapiro 2018). </p><p>We used next-generation sequencing to develop a draft genome for Atlantic Sturgeon and identify single nucleotide polymorphisms (SNPs) that could be used to resolve the natal river and DPS of individual Atlantic Sturgeon. We identified 1,210 candidate SNPs within the nuclear genome as well as 49 SNPs within the mitochondrial genome. After filtering and review, we selected 161 nuclear SNPs and 39 mitochondrial SNPs for further testing and evaluation. We used genotyping-in-thousands by sequencing (GT-seq) to simultaneously sequence nuclear SNP loci, mitochondrial SNP loci, and the existing panel of twelve microsatellite loci. This effort required a pilot sequencing run on a single sturgeon sample to test marker amplification and refine primer strengths, followed by a series of sequencing runs to generate baseline data for 288 individuals representing nine populations of Atlantic Sturgeon in four DPSs. </p><p>Using baseline data from the nine populations, we ran a series of genomic analyses to characterize diversity within and among populations, providing a benchmark for this species using the new SNP markers. Allelic richness was similar for all populations, although there was a general trend of more northern population containing greater levels of allelic richness. Interestingly, we observed linkage disequilibrium among many pairs of loci within many populations. This might be the result of physical linkage but could also suggest these populations are recovering from genetic bottlenecks and/or are effectively small, leading to specific haplotypes to be favored by chance. Pairwise differentiation among populations varied among the populations (<i>F</i><sub>ST</sub> range: 0.010-0.098) and was significantly correlated (<i>r</i> = 0.771; <i>P</i> &lt; 0.001) to pairwise <i>F</i><sub>ST</sub> observed using microsatellite markers). Population clustering and ordination techniques using the new genomic data both support an overall population structure that is similar to the current DPS management units (which were developed primarily based on microsatellite genetic data). Overall, this suggests that existing microsatellite markers and the panel of SNP markers developed in this study provide similar information about the populations structure and ecology of Atlantic Sturgeon. Given the observed differences in allele frequencies among populations, our genomic baseline supports previous assertations that Atlantic Sturgeon show natal homing, despite mixing extensively in marine waters during non-breeding periods. Lower levels of differentiation between populations in the South Atlantic DPS suggest that populations in this region may have greater levels of gene flow relative to their more northerly conspecifics, which has also previously been suggested based on microsatellite data. The observed differentiation among populations provides the necessary foundation for determining the natal river and DPS of Atlantic Sturgeon using assignment testing. </p><p>We tested the utility of our new genomic baseline for resolving the population and DPS of Atlantic Sturgeon. Our nuclear SNP markers showed utility for identifying the origin of unknown Atlantic Sturgeon samples, as 86.5% were assigned to the correct DPS and 66.3% were assigned to the correct natal river. However, since this study was funded the Conservation Genetics and Genomics Laboratory at Leetown Science Center has made significant improvements to their microsatellite genetic baseline, which now performs more effectively than our new genomic approach (the genetic baseline includes 12 populations and 5 DPSs, and correctly assigns 95.8% of individuals to DPS and 84.9% of individuals to their natal population using 12 microsatellite loci). We conducted an ad hoc exploration of how additional microsatellite or nuclear SNP loci may further improve the accuracy of assignment testing. We found that additional microsatellite markers are likely to result in greater improvements in assignment efficiency than additional nuclear SNPs. However, a much larger number of SNP loci (which if identified could be sequenced using other methods that are now available; e.g., the RAD-capture approach published by Ali et al. 2016) could produce assignment efficiencies that are greater than what is currently feasible using microsatellites. In the absence of further research and development of additional SNP markers for Atlantic Sturgeon (possibly using an approach other than GT-seq), the existing microsatellite loci are the most effective means available to determine the natal river and DPS of Atlantic Sturgeon encountered in offshore waters. </p><p>Because our new genomic markers were less effective than the existing panel of 12 microsatellite markers, we chose to use the existing microsatellite markers to assign Atlantic Sturgeon captured in another BOEM-funded study (cooperative agreement M16AC00003; Monitoring endangered Atlantic Sturgeon and commercial finfish habitat use offshore New York) following consultation with our project officer. Using this approach, we genotyped and assigned 186 Atlantic Sturgeon captured in coastal waters off the Rockaway Peninsula, New York. The vast majority of these sturgeon were assigned to the New York Bight DPS (94.62%), and most appear to belong to the Hudson River population (87.10%) with smaller contributions from the Delaware River population (7.53%). Smaller contributions (2.15%) were observed from six other populations, including those from the James, York, Kennebec, Ogeechee, and Edisto rivers. Although most of the fish we assigned were assigned to the nearest spawning rivers (Hudson and Delaware), the contributions from distant rivers is consistent with the propensity of this species to move long distances and form mixed stock aggregations along the continental shelf. This finding indicates that spawning populations (and their corresponding DPS) from distant locations may potentially be impacted by offshore activities. In fact, activities in this region of the New York Bight could negatively impact Atlantic Sturgeon population from at least four different DPSs. Genetic or genomic assignment testing remains an essential tool to characterize potential impacts to Atlantic Sturgeon populations and should be applied more broadly to better characterize potential impacts of activities in other locations.</p>","language":"English","publisher":"Bureau of Ocean Energy Management","usgsCitation":"Kazyak, D.C., Aunins, A.W., Johnson, R.L., Lubinski, B.A., Eackles, M.S., and King, T.L., 2020, Using advanced population genomics to better understand the relationship between offshore and spawning habitat use for Atlantic Sturgeon: OCS Study 2020-062, vi, 70 p.","productDescription":"vi, 70 p.","ipdsId":"IP-106640","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":417577,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417553,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://espis.boem.gov/final%20reports/BOEM_2020-062.pdf"}],"country":"United States","otherGeospatial":"Atlantic Coast","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -81.78806562180561,\n              30.580780235117913\n            ],\n            [\n              -77.30336432135029,\n              29.69193789019691\n            ],\n            [\n              -64.22711779996946,\n              41.900389189548946\n            ],\n            [\n              -67.3512701866663,\n              45.015746962117504\n            ],\n            [\n              -69.19972084180974,\n              45.07365899620572\n            ],\n            [\n              -71.17441845739293,\n              43.73099181927631\n            ],\n            [\n              -71.83104405363528,\n              41.84410310133748\n            ],\n            [\n              -74.31268565149895,\n              41.0826339553866\n            ],\n            [\n              -77.28914013501216,\n              39.074309300310176\n            ],\n            [\n              -76.84797677722777,\n              36.18896372481389\n            ],\n            [\n              -80.79266974786641,\n              32.79868499554179\n            ],\n            [\n              -82.1343310450048,\n              31.38292965735748\n            ],\n            [\n              -81.78806562180561,\n              30.580780235117913\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":140409,"corporation":false,"usgs":true,"family":"Kazyak","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":874141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aunins, Aaron W. 0000-0001-5240-1453 aaunins@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-1453","contributorId":5863,"corporation":false,"usgs":true,"family":"Aunins","given":"Aaron","email":"aaunins@usgs.gov","middleInitial":"W.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":874142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Robin L. 0000-0003-4314-3792 rjohnson1@usgs.gov","orcid":"https://orcid.org/0000-0003-4314-3792","contributorId":224717,"corporation":false,"usgs":true,"family":"Johnson","given":"Robin","email":"rjohnson1@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":874143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lubinski, Barbara A. 0000-0003-3568-2569","orcid":"https://orcid.org/0000-0003-3568-2569","contributorId":202483,"corporation":false,"usgs":true,"family":"Lubinski","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":874144,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eackles, Michael S. 0000-0001-5624-5769 meackles@usgs.gov","orcid":"https://orcid.org/0000-0001-5624-5769","contributorId":218936,"corporation":false,"usgs":true,"family":"Eackles","given":"Michael","email":"meackles@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":874145,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"King, Tim L. tlking@usgs.gov","contributorId":3520,"corporation":false,"usgs":true,"family":"King","given":"Tim","email":"tlking@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":874258,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70248462,"text":"70248462 - 2020 - Geologic map of the Patrick quadrangle, Chesterfield County, South Carolina","interactions":[],"lastModifiedDate":"2023-09-15T13:25:41.276194","indexId":"70248462","displayToPublicDate":"2020-01-01T08:54:20","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":16711,"text":"Geologic Quadrangle Map","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"GQM-57","title":"Geologic map of the Patrick quadrangle, Chesterfield County, South Carolina","docAbstract":"<p>The Patrick 7.5 minute quadrangle, located in Chesterfield County, South Carolina, lies entirely within the upper Atlantic Coastal Plain province. Directly to the southeast in the Dovesville quadrangle, the Pliocene Orangeburg Scarp marks the western edge of marine terraces that characterize the upper limit of the middle Atlantic Coastal Plain. The geologic mapping for this quadrangle was done from 2013-2015 by Bradley A. Fitzwater at Old Dominion University as part of a Master’s thesis supervised by G. Richard Whittecar. Christopher S. Swezey (U.S. Geological Survey) and Fitzwater collaborated in the geologic mapping of both the Patrick quadrangle and the adjacent Middendorf quadrangle (Swezey et al., 2021). The geologic mapping was conducted using a lidar base from 2013, whereas this published product shows the geologic data on a USGS topographic map base from 1968. As a result of differences in resolution, the published map may display a few minor discrepancies with respect to alignment of geologic data with topographic and hydrologic features.</p>","language":"English","publisher":"South Carolina Geological Survey","usgsCitation":"Fitzwater, B.A., Whittecar, G., and Swezey, C.S., 2020, Geologic map of the Patrick quadrangle, Chesterfield County, South Carolina: Geologic Quadrangle Map GQM-57, 1 Plate: 42.00 x 32.00 inches.","productDescription":"1 Plate: 42.00 x 32.00 inches","ipdsId":"IP-082620","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":420827,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115090.htm"},{"id":420784,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.dnr.sc.gov/geology/publications.html"},{"id":420789,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"scale":"24000","country":"United States","state":"South Carolina","county":"Chesterfield County","otherGeospatial":"Patrick quadrangle","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.125,\n              34.625\n            ],\n            [\n              -80.125,\n              34.5\n            ],\n            [\n              -80,\n              34.5\n            ],\n            [\n              -80,\n              34.625\n            ],\n            [\n              -80.125,\n              34.625\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzwater, Bradley A.","contributorId":177211,"corporation":false,"usgs":false,"family":"Fitzwater","given":"Bradley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":883006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whittecar, G. Richard","contributorId":313541,"corporation":false,"usgs":false,"family":"Whittecar","given":"G. Richard","affiliations":[{"id":36518,"text":"Old Dominion University","active":true,"usgs":false}],"preferred":false,"id":883007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swezey, Christopher S. 0000-0003-4019-9264 cswezey@usgs.gov","orcid":"https://orcid.org/0000-0003-4019-9264","contributorId":173033,"corporation":false,"usgs":true,"family":"Swezey","given":"Christopher","email":"cswezey@usgs.gov","middleInitial":"S.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":883008,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70223305,"text":"70223305 - 2020 - Use of museum specimens to refine historical pronghorn subspecies boundaries","interactions":[],"lastModifiedDate":"2021-08-20T12:56:15.157091","indexId":"70223305","displayToPublicDate":"2020-01-01T07:52:03","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":"Use of museum specimens to refine historical pronghorn subspecies boundaries","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Endangered Sonoran (<i>Antilocapra americana sonoriensis</i>) and Peninsular (<i>A. a. peninsularis</i>) pronghorn persist largely because of captive breeding and reintroduction efforts. Recovery team managers want to re-establish pronghorn in their native range, but there is currently uncertainty regarding the subspecies status of extinct pronghorn populations that historically inhabited southern California, USA, and northern Baja California, Mexico. To address this uncertainty, we genotyped museum specimens and conducted phylogenetic and population genetic analyses of historical data in the context of 3 contemporary pronghorn populations. The historical northern Baja California pronghorn share the most ancestry with contemporary Peninsular pronghorn, whereas pronghorn in southern California share more ancestry with contemporary American (<i>A. a. americana</i>) pronghorn. For reintroductions into northern Baja California, the Peninsular subspecies is more appropriate based on museum genetic data. For reintroductions into Southern California, ecological and genetic factors are both important, as the subspecies most genetically related to historical populations (American) may not be well-adapted to the hot, low-elevation deserts of the reintroduction area. © 2019 The Wildlife Society.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21810","usgsCitation":"Hahn, E.E., Klimova, A., Munguia-Vega, A., Clark, K.B., and Culver, M., 2020, Use of museum specimens to refine historical pronghorn subspecies boundaries: Journal of Wildlife Management, v. 64, no. 3, p. 524-533, https://doi.org/10.1002/jwmg.21810.","productDescription":"10 p.","startPage":"524","endPage":"533","ipdsId":"IP-101758","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":388222,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"California","otherGeospatial":"Baja California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.69628906249999,\n              29.99300228455108\n            ],\n            [\n              -112.67578124999999,\n              29.99300228455108\n            ],\n            [\n              -112.67578124999999,\n              35.02999636902566\n            ],\n            [\n              -118.69628906249999,\n              35.02999636902566\n            ],\n            [\n              -118.69628906249999,\n              29.99300228455108\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"64","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hahn, Erin E.","contributorId":264557,"corporation":false,"usgs":false,"family":"Hahn","given":"Erin","email":"","middleInitial":"E.","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":821672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Klimova, Anastasia","contributorId":264558,"corporation":false,"usgs":false,"family":"Klimova","given":"Anastasia","affiliations":[{"id":54500,"text":"actg","active":true,"usgs":false}],"preferred":false,"id":821673,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munguia-Vega, Adrian","contributorId":264559,"corporation":false,"usgs":false,"family":"Munguia-Vega","given":"Adrian","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":821674,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clark, Kevin B.","contributorId":264560,"corporation":false,"usgs":false,"family":"Clark","given":"Kevin","email":"","middleInitial":"B.","affiliations":[{"id":54501,"text":"sdnhm","active":true,"usgs":false}],"preferred":false,"id":821675,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Culver, Melanie 0000-0001-5380-3059 mculver@usgs.gov","orcid":"https://orcid.org/0000-0001-5380-3059","contributorId":197693,"corporation":false,"usgs":true,"family":"Culver","given":"Melanie","email":"mculver@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":821671,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70222101,"text":"70222101 - 2020 - Patterns and drivers of atmospheric river precipitation and hydrologic impacts across the western United States","interactions":[],"lastModifiedDate":"2021-07-21T11:56:46.001135","indexId":"70222101","displayToPublicDate":"2020-01-01T07:07:22","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Patterns and drivers of atmospheric river precipitation and hydrologic impacts across the western United States","docAbstract":"<p><span>Atmospheric rivers (ARs) significantly influence precipitation and hydrologic variability in many areas of the world, including the western United States. As ARs are increasingly recognized by the research community and the public, there is a need to more precisely quantify and communicate their hydrologic impacts, which can vary from hazardous to beneficial depending on location and on the atmospheric and land surface conditions prior to and during the AR. This study leverages 33 years of atmospheric and hydrologic data for the western United States to 1) identify how water vapor amount, wind direction and speed, temperature, and antecedent soil moisture conditions influence precipitation and hydrologic responses (runoff, recharge, and snowpack) using quantile regression and 2) identify differences in hydrologic response types and magnitudes across the study region. Results indicate that water vapor amount serves as a primary control on precipitation amounts. Holding water vapor constant, precipitation amounts vary with wind direction, depending on location, and are consistently greater at colder temperatures. Runoff efficiencies further covary with temperature and antecedent soil moisture, with precipitation falling as snow and greater available water storage in the soil column mitigating flood impacts of large AR events. This study identifies the coastal and maritime mountain ranges as areas with the greatest potential for hazardous flooding and snowfall impacts. This spatially explicit information can lead to better understanding of the conditions under which ARs of different precipitation amounts are likely to be hazardous at a given location.</span></p>","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-19-0119.1","usgsCitation":"Albano, C.M., Dettinger, M.D., and Harpold, A., 2020, Patterns and drivers of atmospheric river precipitation and hydrologic impacts across the western United States: Journal of Hydrometeorology, v. 21, p. 143-159, https://doi.org/10.1175/JHM-D-19-0119.1.","productDescription":"17 p.","startPage":"143","endPage":"159","ipdsId":"IP-108504","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":458275,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-19-0119.1","text":"Publisher Index Page"},{"id":387290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -127.3095703125,\n              31.541089879585808\n            ],\n            [\n              -108.9404296875,\n              31.541089879585808\n            ],\n            [\n              -108.9404296875,\n              49.26780455063753\n            ],\n            [\n              -127.3095703125,\n              49.26780455063753\n            ],\n            [\n              -127.3095703125,\n              31.541089879585808\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"21","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Albano, Christine M.","contributorId":169455,"corporation":false,"usgs":false,"family":"Albano","given":"Christine","email":"","middleInitial":"M.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":819519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dettinger, Michael D. 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":149896,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael","email":"mddettin@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":819520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harpold, Adrian","contributorId":184147,"corporation":false,"usgs":false,"family":"Harpold","given":"Adrian","affiliations":[],"preferred":false,"id":819521,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70212124,"text":"70212124 - 2020 - Semiautomated process for enumeration of fishes from recreational-grade side-scan sonar imagery","interactions":[],"lastModifiedDate":"2020-08-14T13:40:27.721905","indexId":"70212124","displayToPublicDate":"2020-01-01T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Semiautomated process for enumeration of fishes from recreational-grade side-scan sonar imagery","docAbstract":"The use of hydroacoustic techniques is increasing as scientists search for less invasive ways to monitor fish populations, and using recreational side‐scan sonar (SSS) imagery for monitoring has become more common in aquatic resource management over the last 15 years due in part to its low cost and user‐friendly interface. The time‐consuming nature of manually counting fish targets has limited the use of the data that is collected by these systems in research or management contexts. To reduce the time and effort that is required to enumerate acoustic targets that are presumed to be fish, we developed a semiautomated process that rapidly quantifies targets from recreational SSS imagery by using an open‐source image processing software. Perceived fish targets were enumerated using a set of macroinstructions that performed similarly to manual enumeration by three experienced assessors. This method reduced variation that arises from individual assessors and eliminated the prohibitive time constraints that are associated with manual processing. Herein, we describe how our semiautomated process could be used in fisheries management contexts after further research and development of sampling methods. Future research will focus on field validation, quantifying relative abundance, testing across a broader range of environmental conditions, and exploring other applications for fisheries management.N","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10373","usgsCitation":"Lawson, K.M., Ridgway, J.L., Mueller, A.T., Faulkner, J., and Calfee, R.D., 2020, Semiautomated process for enumeration of fishes from recreational-grade side-scan sonar imagery: North American Journal of Fisheries Management, v. 40, no. 1, p. 75-83, https://doi.org/10.1002/nafm.10373.","productDescription":"9 p.","startPage":"75","endPage":"83","ipdsId":"IP-104107","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":458278,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10373","text":"Publisher Index Page"},{"id":437181,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AKBIK9","text":"USGS data release","linkHelpText":"Semi-automated and manual enumeration of bigheaded carps from recreational-grade side-scan sonar imagery, Perche Creek, MO, 2018"},{"id":377504,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Lawson, Katelyn M 0000-0002-8017-3352","orcid":"https://orcid.org/0000-0002-8017-3352","contributorId":238276,"corporation":false,"usgs":true,"family":"Lawson","given":"Katelyn","email":"","middleInitial":"M","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":796232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ridgway, Josey Lee 0000-0003-4157-7255","orcid":"https://orcid.org/0000-0003-4157-7255","contributorId":238277,"corporation":false,"usgs":true,"family":"Ridgway","given":"Josey","email":"","middleInitial":"Lee","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":796233,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueller, Andrew T. 0000-0001-8566-8023","orcid":"https://orcid.org/0000-0001-8566-8023","contributorId":238278,"corporation":false,"usgs":true,"family":"Mueller","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":796234,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Faulkner, Jacob 0000-0002-8109-9107","orcid":"https://orcid.org/0000-0002-8109-9107","contributorId":238279,"corporation":false,"usgs":true,"family":"Faulkner","given":"Jacob","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":796235,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":796236,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70208625,"text":"70208625 - 2020 - Temporospatial shifts in Sandhill Crane staging in the Central Platte River Valley in response to climatic variation and habitat change","interactions":[],"lastModifiedDate":"2020-12-15T20:16:16.059853","indexId":"70208625","displayToPublicDate":"2019-12-31T14:44:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2785,"text":"Monographs of the Western North American Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Temporospatial shifts in Sandhill Crane staging in the Central Platte River Valley in response to climatic variation and habitat change","docAbstract":"<p><span>Over 80% of the Mid-Continent Sandhill Crane (</span><i>Antigone canadensis</i><span>) Population (MCP), estimated at over 660,000 individuals, stops in the Central Platte River Valley (CPRV) during spring migration from mid-February through mid-April. Research suggests that the MCP may be shifting its distribution spatially and temporally within the CPRV. From 2002 to 2017, we conducted weekly aerial surveys of Sandhill Cranes staging in the CPRV to examine temporal and spatial trends in their abundance and distribution. Then, we used winter temperature and drought severity measures from key wintering and early migratory stopover locations to assess the impacts of weather patterns on annual migration chronology in the CPRV. We also evaluated channel width and land cover characteristics using aerial imagery from 1938, 1998, and 2016 to assess the relationship between habitat change and the spatial distribution of the MCP in the CPRV. We used generalized linear models, cumulative link models, and Akaike’s information criterion corrected for small sample sizes (AICc) to compare temporal and spatial models. Temperatures and drought conditions at wintering and migration locations that are heavily used by Greater Sandhill Cranes (</span><i>A. c. tabida</i><span>) best predicted migration chronology of the MCP to the CPRV. The spatial distribution of roosting Sandhill Cranes from 2015 to 2017 was best predicted by the proportion of width reduction in the main channel since 1938 (rather than its width in 2016) and the proportion of land cover as prairie-meadow habitat within 800 m of the Platte River. Our data suggest that Sandhill Cranes advanced their migration by an average of just over 1 day per year from 2002 to 2017, and that they continued to shift eastward, concentrating at eastern reaches of the CPRV. Climate change, land use change, and habitat loss have all likely contributed to Sandhill Cranes coming earlier and staying longer in fewer reaches of the CPRV, increasing their site use intensity. These historically unprecedented densities may present a disease risk to Sandhill Cranes and other waterbirds, including Whooping Cranes (</span><i>Grus americana</i><span>). Our models suggest that conservation actions may be maintaining Sandhill Crane densities in areas that would otherwise be declining in use. We suggest that management actions intended to mitigate trends in the distribution of Sandhill Cranes, including wet meadow restoration, may similarly benefit prairie- and braided river–endemic species of concern.</span></p>","language":"English","publisher":"BioOne","doi":"10.3398/042.011.0104","usgsCitation":"Caven, A.J., Brinley Buckley, E.M., King, K.C., Wiese, J.D., Baasch, D.M., Wright, G.D., Harner, M.J., Pearse, A.T., Rabbe, M., Varner, D., Krohn, B., Arcilla, N., Schroeder, K.D., and Dinan, K.F., 2020, Temporospatial shifts in Sandhill Crane staging in the Central Platte River Valley in response to climatic variation and habitat change: Monographs of the Western North American Naturalist, v. 11, p. 33-76, https://doi.org/10.3398/042.011.0104.","productDescription":"44 p.","startPage":"33","endPage":"76","ipdsId":"IP-102357","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":458279,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3398/042.011.0104","text":"Publisher Index Page"},{"id":372957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Platte River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.03237915039062,\n              41.024981358869915\n            ],\n            [\n              -98.06465148925781,\n              41.055537533528636\n            ],\n            [\n              -98.27957153320312,\n              40.954492756949186\n            ],\n            [\n              -98.40934753417967,\n              40.88029480552824\n            ],\n            [\n              -98.81515502929688,\n              40.73112880602221\n            ],\n            [\n              -98.99642944335938,\n              40.69938133866613\n            ],\n            [\n              -99.55535888671874,\n              40.73321007823572\n            ],\n            [\n              -99.60548400878906,\n              40.66293116628907\n            ],\n            [\n              -99.1845703125,\n              40.63740418690266\n            ],\n            [\n              -98.86459350585938,\n              40.64469860601899\n            ],\n            [\n              -98.55491638183594,\n              40.72540497175607\n            ],\n            [\n              -98.28781127929688,\n              40.805493843894155\n            ],\n            [\n              -98.16970825195312,\n              40.91039911873504\n            ],\n            [\n              -98.03237915039062,\n              41.024981358869915\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Caven, Andrew J.","contributorId":177586,"corporation":false,"usgs":false,"family":"Caven","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":782798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brinley Buckley, Emma M.","contributorId":198370,"corporation":false,"usgs":false,"family":"Brinley Buckley","given":"Emma","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":782799,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"King, Kelsey C","contributorId":222650,"corporation":false,"usgs":false,"family":"King","given":"Kelsey","email":"","middleInitial":"C","affiliations":[{"id":40581,"text":"Platte River Whooping Crane Maintenance Trust","active":true,"usgs":false}],"preferred":false,"id":782800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiese, Joshua D","contributorId":222651,"corporation":false,"usgs":false,"family":"Wiese","given":"Joshua","email":"","middleInitial":"D","affiliations":[{"id":40581,"text":"Platte River Whooping Crane Maintenance Trust","active":true,"usgs":false}],"preferred":false,"id":782801,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baasch, David M.","contributorId":147145,"corporation":false,"usgs":false,"family":"Baasch","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":16795,"text":"Headwaters Corp, Kearney, NE","active":true,"usgs":false}],"preferred":false,"id":782802,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wright, Greg D.","contributorId":177585,"corporation":false,"usgs":false,"family":"Wright","given":"Greg","email":"","middleInitial":"D.","affiliations":[{"id":12957,"text":"Chippewa Ottawa Resource Authority","active":true,"usgs":false}],"preferred":false,"id":782803,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harner, Mary J.","contributorId":177584,"corporation":false,"usgs":false,"family":"Harner","given":"Mary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":782804,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":782797,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rabbe, Matt","contributorId":202597,"corporation":false,"usgs":false,"family":"Rabbe","given":"Matt","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":782805,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Varner, Dana","contributorId":222652,"corporation":false,"usgs":false,"family":"Varner","given":"Dana","affiliations":[{"id":40582,"text":"Rainwater Basin Joint Venture","active":true,"usgs":false}],"preferred":false,"id":782806,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Krohn, Brice","contributorId":222653,"corporation":false,"usgs":false,"family":"Krohn","given":"Brice","email":"","affiliations":[{"id":40581,"text":"Platte River Whooping Crane Maintenance Trust","active":true,"usgs":false}],"preferred":false,"id":782807,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Arcilla, Nicole","contributorId":223085,"corporation":false,"usgs":false,"family":"Arcilla","given":"Nicole","email":"","affiliations":[],"preferred":false,"id":782808,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Schroeder, Kirk D","contributorId":222655,"corporation":false,"usgs":false,"family":"Schroeder","given":"Kirk","email":"","middleInitial":"D","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":782809,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Dinan, Kenneth F","contributorId":222656,"corporation":false,"usgs":false,"family":"Dinan","given":"Kenneth","email":"","middleInitial":"F","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":782810,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70209290,"text":"70209290 - 2020 - Envisioning a national invasive species information framework","interactions":[],"lastModifiedDate":"2020-03-31T12:51:15","indexId":"70209290","displayToPublicDate":"2019-12-31T12:48:40","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Envisioning a national invasive species information framework","docAbstract":"<p><span>With a view toward creating a national Early Detection and Rapid Response Program (EDRR) program, the United States&nbsp;</span><i>National Invasive Species Council Management Plan</i><span>&nbsp;for 2016–2018 calls for a series of assessments of federal EDRR capacities, including the evaluation of “relevant federal information systems to provide the data and other information necessary for risk analyses/horizon scanning, rapid specimen identification, and rapid response planning.” This paper is a response to that directive. We provide an overview of information management needs for enacting EDRR and discuss challenges to meeting these needs. We then review the history of relevant US policy directives for advancing invasive species information systems and provide an overview of federal invasive species information system capacities, including current gaps and inconsistencies. We conclude with a summary of key principles and needs for establishing a national invasive species information framework. Our findings are consistent with earlier studies and, thus, emphasize the need to act on long-recognized needs. As a supplement to this paper, we have cataloged federal invasive species databases and information tools identified through this work.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10530-019-02141-3","usgsCitation":"Reaser, J.K., Simpson, A., Guala, G., Morisette, J., and Fuller, P., 2020, Envisioning a national invasive species information framework: Biological Invasions, v. 22, no. 1, p. 21-36, https://doi.org/10.1007/s10530-019-02141-3.","productDescription":"16 p.","startPage":"21","endPage":"36","ipdsId":"IP-103628","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":458280,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10530-019-02141-3","text":"Publisher Index Page"},{"id":373661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Reaser, Jamie K","contributorId":223683,"corporation":false,"usgs":false,"family":"Reaser","given":"Jamie","email":"","middleInitial":"K","affiliations":[{"id":39207,"text":"Department of the Interior","active":true,"usgs":false}],"preferred":false,"id":785903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simpson, Annie 0000-0001-8338-5134","orcid":"https://orcid.org/0000-0001-8338-5134","contributorId":206062,"corporation":false,"usgs":true,"family":"Simpson","given":"Annie","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":785902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guala, Gerald","contributorId":223684,"corporation":false,"usgs":true,"family":"Guala","given":"Gerald","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":785904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morisette, Jeffrey 0000-0002-0483-0082","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":212187,"corporation":false,"usgs":false,"family":"Morisette","given":"Jeffrey","affiliations":[{"id":38451,"text":"U.S. Department of the Interior, National Invasive Species Council Secretariat","active":true,"usgs":false}],"preferred":false,"id":785905,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuller, Pam 0000-0002-9389-9144 pfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9389-9144","contributorId":223685,"corporation":false,"usgs":true,"family":"Fuller","given":"Pam","email":"pfuller@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":785906,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70208091,"text":"70208091 - 2020 - Establishing high-frequency noise baselines to 100 Hz based on millions of power spectra from IRIS MUSTANG","interactions":[],"lastModifiedDate":"2020-02-06T11:42:11","indexId":"70208091","displayToPublicDate":"2019-12-31T07:16:23","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Establishing high-frequency noise baselines to 100 Hz based on millions of power spectra from IRIS MUSTANG","docAbstract":"Advances in seismic instrumentation have enabled data to be recorded at increasing sample rates.  This has in turn created a need to establish higher-frequency baselines for assessing data quality, as the widely-used New High (NHNM) and Low Noise Models (NLNM) of Peterson (1993) do not extend to frequencies above 10 Hz.  To provide a baseline for higher frequencies (10-100 Hz), we examine power spectral density probability density functions (PSDPDFs) for high-sample-rate stations available from the Incorporated Research Institutions for Seismology Data Services (IRIS DS) MUSTANG quality control system. We compute high-frequency high and low noise baselines by matching the appropriate composite PSDPDF percentile points to NHNM and NLNM power levels at overlapping frequencies (1-10 Hz) and then extending to higher frequencies (10-100 Hz) with piecewise linear fits to the matching PSDPDF percentile.\n\nWe find that the Peterson NLNM remains an accurate representation of the lower bound of global ambient Earth noise since it is matched by only 0.1% of Global Seismographic Network (GSN) PSDs.  We present high-frequency high and low noise baselines intended primarily for use by temporary networks targeting high-frequency signals (e.g. monitoring of aftershocks or induced seismicity) based on statistics of PSDPDFs from all publicly available high-sample-rate data.  \n\nMost publicly-available high-sample-rate data is recorded by temporary deployments, and the experiment design and scientific targets of these deployments strongly influence the observed statistical distribution of high-frequency noise. We anticipate that the noise baselines presented here will be useful in automated quality control of high-sample-rate seismic data.   However, we note that establishing a low noise model that accurately represents the lowest possible ambient Earth noise at frequencies up to 100 Hz will require additional continuous high-sample-rate data from high-quality permanent stations in low-noise environments.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120190123","usgsCitation":"Wolin, E., and McNamara, D., 2020, Establishing high-frequency noise baselines to 100 Hz based on millions of power spectra from IRIS MUSTANG: Bulletin of the Seismological Society of America, v. 110, no. 1, p. 270-278, https://doi.org/10.1785/0120190123.","productDescription":"9 p.","startPage":"270","endPage":"278","ipdsId":"IP-107994","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":371634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"110","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Wolin, Emily 0000-0003-1610-1191","orcid":"https://orcid.org/0000-0003-1610-1191","contributorId":221834,"corporation":false,"usgs":true,"family":"Wolin","given":"Emily","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":780442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McNamara, Daniel 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":221835,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":780443,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70208092,"text":"70208092 - 2020 - Integrating multiple data sources and multi-scale land-cover data to model the distribution of a declining amphibian","interactions":[],"lastModifiedDate":"2020-01-27T19:59:37","indexId":"70208092","displayToPublicDate":"2019-12-30T19:58:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Integrating multiple data sources and multi-scale land-cover data to model the distribution of a declining amphibian","docAbstract":"Determining the spatial scale at which landscape features influence population persistence is an important task for conservation planning. One challenge is that sampling biases confound factors that influence species occurrence and survey effort. Recent developments in Point Process Models (PPMs) enable researchers to disentangle the sampling process from ecological drivers of species' distributions. Land-cover change is a driver of decline for the western spadefoot (Spea hammondii), which has been extirpated from much of its range in California. Assessing this species' status requires information on the current distribution of suitable habitat within its historical range, but little is known about the effect of the landscape surrounding breeding ponds on spadefoot occurrence. Critically, surveys for western spadefoots often occur along roads, potentially biasing data used to fit species distribution models. We created PPMs integrating historical presence/non-detection and presence-only data for western spadefoots and land-cover data at multiple spatial scales to model the distribution of this species while removing the influence of sampling bias. There was spatial sampling bias in presence-only data; records were more likely to be reported near roads and urban centers and PPMs that removed sampling bias outperformed models that ignored sampling bias. The occurrence of western spadefoots was positively related to the proportion of grassland within a 2000 m buffer. The remaining habitat for western spadefoots is largely found in the foothills surrounding California's Central Valley. Our study illustrates how PPMs can improve projections of habitat suitability and our understanding of the drivers of species' distributions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2019.108374","usgsCitation":"Rose, J.P., Halstead, B., and Fisher, R.N., 2020, Integrating multiple data sources and multi-scale land-cover data to model the distribution of a declining amphibian: Biological Conservation, v. 241, 108374, https://doi.org/10.1016/j.biocon.2019.108374.","productDescription":"108374","ipdsId":"IP-108816","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458282,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2019.108374","text":"Publisher Index Page"},{"id":371628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.14599609375001,\n              40.96330795307353\n            ],\n            [\n              -123.06884765625,\n              41.062786068733026\n            ],\n            [\n              -123.15673828124999,\n              39.13006024213511\n            ],\n            [\n              -120.21240234375001,\n              35.06597313798418\n            ],\n            [\n              -117.83935546874999,\n              34.17999758688084\n            ],\n            [\n              -117.00439453125,\n              34.994003757575776\n            ],\n            [\n              -117.97119140625,\n              36.06686213257888\n            ],\n            [\n              -119.2236328125,\n              37.77071473849609\n            ],\n            [\n              -122.14599609375001,\n              40.96330795307353\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"241","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":780444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780446,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70211621,"text":"70211621 - 2020 - Assessment of leachable elements in volcanic ashfall: A review and evaluation of a standardized protocol for ash hazard characterization","interactions":[],"lastModifiedDate":"2020-08-10T17:01:51.255152","indexId":"70211621","displayToPublicDate":"2019-12-28T09:47:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of leachable elements in volcanic ashfall: A review and evaluation of a standardized protocol for ash hazard characterization","docAbstract":"<p><span>Volcanic ash presents a widespread and common hazard during and after eruptions. Complex interactions between solid ash surfaces and volcanic gases lead to the formation of soluble salts that may be mobilized in aqueous environments. A variety of stakeholders may be concerned about the effects of ash on human and animal health, drinking water supplies, crops, soils and surface runoff. As part of the immediate emergency response, rapid dissemination of information regarding potentially hazardous concentrations of soluble species is critical. However, substantial variability in the methods used to characterize leachable elements makes it challenging to compare datasets and eruption impacts. To address these challenges, the International Volcanic Health Hazard Network (</span><a rel=\"noreferrer noopener\" href=\"http://www.ivhhn.org/\" target=\"_blank\" data-mce-href=\"http://www.ivhhn.org/\">www.ivhhn.org</a><span>) organized a two-day workshop to define appropriate methods for hazard assessment. The outcome of this workshop was a ‘consensus protocol’ for analysis of volcanic ash samples for rapid assessment of hazards from leachable elements, which was subsequently ratified by leading volcanological organizations. The purpose of this protocol is to recommend clear, standard and reliable methods applicable to a range of purposes during eruption response, such as assessing impacts on drinking-water supplies and ingestion hazards to livestock, and also applicable to research purposes. Where possible, it is intended that the methods make use of commonly available equipment and require little training. To evaluate method transferability, an interlaboratory comparison exercise was organized among six laboratories worldwide. Each laboratory received a split of pristine ash, and independently analyzed it according to the protocol for a wide range of elements. Collated results indicate good repeatability and reproducibility for most elements, thus indicating that the development of this protocol is a useful step towards providing standardized and reliable methods for ash hazard characterization. In this article, we review recent ash leachate studies, report the outcomes of the comparison exercise and present a revised and updated protocol based on the experiences and recommendations of the exercise participants. The adoption of standardized methods will improve and facilitate the comparability of results among studies and enable the ongoing development of a global database of leachate information relevant for informing volcanic health hazards assessment.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2019.106756","usgsCitation":"Stewart, C., Damby, D., Tomasek, I., Horwell, C.J., Plumlee, G.S., Armienta, M.A., Hinojosa, M.G., Appleby, M., Delmelle, P., Cronin, S., Ottley, C.J., Oppenheimer, C., and Morman, S.A., 2020, Assessment of leachable elements in volcanic ashfall: A review and evaluation of a standardized protocol for ash hazard characterization: Journal of Volcanology and Geothermal Research, v. 392, 106756, 22 p., https://doi.org/10.1016/j.jvolgeores.2019.106756.","productDescription":"106756, 22 p.","ipdsId":"IP-112086","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":458284,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://dro.dur.ac.uk/29919/","text":"External Repository"},{"id":377039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"392","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stewart, Carol","contributorId":236960,"corporation":false,"usgs":false,"family":"Stewart","given":"Carol","email":"","affiliations":[{"id":47573,"text":"Massey University, NZ","active":true,"usgs":false}],"preferred":false,"id":794824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Damby, David 0000-0002-3238-3961","orcid":"https://orcid.org/0000-0002-3238-3961","contributorId":206614,"corporation":false,"usgs":true,"family":"Damby","given":"David","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":794825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tomasek, Ines","contributorId":205741,"corporation":false,"usgs":false,"family":"Tomasek","given":"Ines","email":"","affiliations":[{"id":37158,"text":"Institute of Hazard, Risk & Resilience, Department of Earth Sciences, Durham University, UK","active":true,"usgs":false}],"preferred":false,"id":794826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horwell, Claire J.","contributorId":177455,"corporation":false,"usgs":false,"family":"Horwell","given":"Claire","email":"","middleInitial":"J.","affiliations":[{"id":16770,"text":"Dept. Earth Sciences, Durham University, UK","active":true,"usgs":false}],"preferred":false,"id":794827,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plumlee, Geoffrey S. 0000-0002-9607-5626","orcid":"https://orcid.org/0000-0002-9607-5626","contributorId":204552,"corporation":false,"usgs":true,"family":"Plumlee","given":"Geoffrey","email":"","middleInitial":"S.","affiliations":[],"preferred":true,"id":794828,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Armienta, Maria Aurora","contributorId":236961,"corporation":false,"usgs":false,"family":"Armienta","given":"Maria","email":"","middleInitial":"Aurora","affiliations":[{"id":47574,"text":"Universidad Nacional Autónoma de México, Mexico","active":true,"usgs":false}],"preferred":false,"id":794829,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hinojosa, Maria Gabriela Ruiz","contributorId":236962,"corporation":false,"usgs":false,"family":"Hinojosa","given":"Maria","email":"","middleInitial":"Gabriela Ruiz","affiliations":[{"id":47575,"text":"UCLouvain, Belgium","active":true,"usgs":false}],"preferred":false,"id":794830,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Appleby, Moya","contributorId":236963,"corporation":false,"usgs":false,"family":"Appleby","given":"Moya","email":"","affiliations":[{"id":5111,"text":"GNS Science, New Zealand","active":true,"usgs":false}],"preferred":false,"id":794831,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Delmelle, Pierre","contributorId":236964,"corporation":false,"usgs":false,"family":"Delmelle","given":"Pierre","email":"","affiliations":[{"id":47575,"text":"UCLouvain, Belgium","active":true,"usgs":false}],"preferred":false,"id":794832,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cronin, Shane","contributorId":236965,"corporation":false,"usgs":false,"family":"Cronin","given":"Shane","affiliations":[{"id":26898,"text":"University of Auckland, New Zealand","active":true,"usgs":false}],"preferred":false,"id":794833,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ottley, Christopher J","contributorId":236967,"corporation":false,"usgs":false,"family":"Ottley","given":"Christopher","email":"","middleInitial":"J","affiliations":[{"id":40359,"text":"Durham University, UK","active":true,"usgs":false}],"preferred":false,"id":794834,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Oppenheimer, Clive","contributorId":174445,"corporation":false,"usgs":false,"family":"Oppenheimer","given":"Clive","email":"","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":794835,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Morman, Suzette A. 0000-0002-2532-1033 smorman@usgs.gov","orcid":"https://orcid.org/0000-0002-2532-1033","contributorId":996,"corporation":false,"usgs":true,"family":"Morman","given":"Suzette","email":"smorman@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}],"preferred":true,"id":794836,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70228175,"text":"70228175 - 2020 - Increasing accuracy of lake nutrient predictions in thousands of lakes by leveraging water clarity data","interactions":[],"lastModifiedDate":"2022-02-07T17:50:09.933226","indexId":"70228175","displayToPublicDate":"2019-12-27T11:39:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5456,"text":"Limnology and Oceanography Letters","active":true,"publicationSubtype":{"id":10}},"title":"Increasing accuracy of lake nutrient predictions in thousands of lakes by leveraging water clarity data","docAbstract":"<p><span>Aquatic scientists require robust, accurate information about nutrient concentrations and indicators of algal biomass in unsampled lakes in order to understand and predict the effects of global climate and land-use change. Historically, lake and landscape characteristics have been used as predictor variables in regression models to generate nutrient predictions, but often with significant uncertainty. An alternative approach to improve predictions is to leverage the observed relationship between water clarity and nutrients, which is possible because water clarity is more commonly measured than lake nutrients. We used a joint-nutrient model that conditioned predictions of total phosphorus, nitrogen, and chlorophyll </span><i>a</i><span>&nbsp;on observed water clarity. Our results demonstrated substantial reductions (8–27%; median = 23%) in prediction error when conditioning on water clarity. These models will provide new opportunities for predicting nutrient concentrations of unsampled lakes across broad spatial scales with reduced uncertainty.</span></p>","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lol2.10134","usgsCitation":"Wagner, T., Noah R., O.L., Bartley, M.L., Hanks, E., Schliep, E.M., Wikle, N.B., King, K.B., McCullough, I., Stachelek, J., Cheruvelil, K.S., Filstrup, C.T., Lapierre, J., Liu, B., Sorrano, P., Tan, P., Wang, Q., Webster, K., and Zhou, J., 2020, Increasing accuracy of lake nutrient predictions in thousands of lakes by leveraging water clarity data: Limnology and Oceanography Letters, v. 5, no. 2, p. 228-235, https://doi.org/10.1002/lol2.10134.","productDescription":"8 p.","startPage":"228","endPage":"235","ipdsId":"IP-109351","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":488957,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lol2.10134","text":"Publisher Index Page"},{"id":395550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noah R., oa Lottig Lottig","contributorId":274769,"corporation":false,"usgs":false,"family":"Noah R.","given":"oa","suffix":"Lottig","email":"","middleInitial":"Lottig","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":833308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartley, Meridith L.","contributorId":274772,"corporation":false,"usgs":false,"family":"Bartley","given":"Meridith","email":"","middleInitial":"L.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":833309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanks, Ephraim M.","contributorId":274775,"corporation":false,"usgs":false,"family":"Hanks","given":"Ephraim M.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":833310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schliep, Erin M.","contributorId":274778,"corporation":false,"usgs":false,"family":"Schliep","given":"Erin","email":"","middleInitial":"M.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":833311,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wikle, Nathan B.","contributorId":274780,"corporation":false,"usgs":false,"family":"Wikle","given":"Nathan","email":"","middleInitial":"B.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":833312,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"King, Katelyn B. S.","contributorId":274782,"corporation":false,"usgs":false,"family":"King","given":"Katelyn","email":"","middleInitial":"B. S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833313,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCullough, Ian","contributorId":274784,"corporation":false,"usgs":false,"family":"McCullough","given":"Ian","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833314,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stachelek, Jemma","contributorId":274864,"corporation":false,"usgs":false,"family":"Stachelek","given":"Jemma","email":"","affiliations":[],"preferred":false,"id":833315,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cheruvelil, Kendra S.","contributorId":172029,"corporation":false,"usgs":false,"family":"Cheruvelil","given":"Kendra","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":833316,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Filstrup, Christopher T.","contributorId":169032,"corporation":false,"usgs":false,"family":"Filstrup","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":833440,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lapierre, Jean-Francois","contributorId":264522,"corporation":false,"usgs":false,"family":"Lapierre","given":"Jean-Francois","affiliations":[{"id":54487,"text":"University of Montreal","active":true,"usgs":false}],"preferred":false,"id":833441,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Liu, Boyang","contributorId":274865,"corporation":false,"usgs":false,"family":"Liu","given":"Boyang","email":"","affiliations":[],"preferred":false,"id":833442,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sorrano, Patricia","contributorId":204929,"corporation":false,"usgs":false,"family":"Sorrano","given":"Patricia","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833443,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tan, Pang-Ning","contributorId":172193,"corporation":false,"usgs":false,"family":"Tan","given":"Pang-Ning","affiliations":[],"preferred":false,"id":833444,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wang, Q.","contributorId":83761,"corporation":false,"usgs":true,"family":"Wang","given":"Q.","affiliations":[],"preferred":false,"id":833445,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Webster, Katherine","contributorId":274866,"corporation":false,"usgs":false,"family":"Webster","given":"Katherine","affiliations":[],"preferred":false,"id":833446,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Zhou, Jiayu","contributorId":204926,"corporation":false,"usgs":false,"family":"Zhou","given":"Jiayu","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833447,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70222540,"text":"70222540 - 2020 - Metal bioavailability models: Current status, lessons learned, considerations for regulatory use, and the path forward","interactions":[],"lastModifiedDate":"2021-08-03T13:47:20.331188","indexId":"70222540","displayToPublicDate":"2019-12-27T08:45:36","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":"Metal bioavailability models: Current status, lessons learned, considerations for regulatory use, and the path forward","docAbstract":"<p><span>Since the early 2000s, biotic ligand models and related constructs have been a dominant paradigm for risk assessment of aqueous metals in the environment. We critically review 1) the evidence for the mechanistic approach underlying metal bioavailability models; 2) considerations for the use and refinement of bioavailability-based toxicity models; 3) considerations for the incorporation of metal bioavailability models into environmental quality standards; and 4) some consensus recommendations for developing or applying metal bioavailability models. We note that models developed to date have been particularly challenged to accurately incorporate pH effects because they are unique with multiple possible mechanisms. As such, we doubt it is ever appropriate to lump algae/plant and animal bioavailability models; however, it is often reasonable to lump bioavailability models for animals, although aquatic insects may be an exception. Other recommendations include that data generated for model development should consider equilibrium conditions in exposure designs, including food items in combined waterborne–dietary matched chronic exposures. Some potentially important toxicity-modifying factors are currently not represented in bioavailability models and have received insufficient attention in toxicity testing. Temperature is probably of foremost importance; phosphate is likely important in plant and algae models. Acclimation may result in predictions that err on the side of protection. Striking a balance between comprehensive, mechanistically sound models and simplified approaches is a challenge. If empirical bioavailability tools such as multiple-linear regression models and look-up tables are employed in criteria, they should always be informed qualitatively and quantitatively by mechanistic models. If bioavailability models are to be used in environmental regulation, ongoing support and availability for use of the models in the public domain are essential.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/etc.4560","usgsCitation":"Mebane, C.A., Chowdhury, M., De Schamphelaere, K.A., Lofts, S., Paquin, P.R., Santore, R.C., and Wood, C.M., 2020, Metal bioavailability models: Current status, lessons learned, considerations for regulatory use, and the path forward: Environmental Toxicology and Chemistry, v. 39, no. 1, p. 60-84, https://doi.org/10.1002/etc.4560.","productDescription":"25 p.","startPage":"60","endPage":"84","ipdsId":"IP-110208","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":458289,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.4560","text":"Publisher Index Page"},{"id":387661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-01","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":820503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chowdhury, M. Jasim","contributorId":261730,"corporation":false,"usgs":false,"family":"Chowdhury","given":"M. Jasim","affiliations":[{"id":52970,"text":"International Lead Association, Durham, North Carolina, USA","active":true,"usgs":false}],"preferred":false,"id":820504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Schamphelaere, Karel A.C.","contributorId":261731,"corporation":false,"usgs":false,"family":"De Schamphelaere","given":"Karel","email":"","middleInitial":"A.C.","affiliations":[{"id":52971,"text":"Ghent University, Gent, Belgium","active":true,"usgs":false}],"preferred":false,"id":820505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lofts, Stephen","contributorId":261732,"corporation":false,"usgs":false,"family":"Lofts","given":"Stephen","email":"","affiliations":[{"id":52972,"text":"Centre for Ecology and Hydrology, Bailrigg, Lancaster, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":820506,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paquin, Paul R.","contributorId":261733,"corporation":false,"usgs":false,"family":"Paquin","given":"Paul","email":"","middleInitial":"R.","affiliations":[{"id":52973,"text":"HDR, New York, New York, USA","active":true,"usgs":false}],"preferred":false,"id":820507,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Santore, Robert C.","contributorId":202449,"corporation":false,"usgs":false,"family":"Santore","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":36447,"text":"Windward Environmental LLC, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":820508,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wood, Chris M.","contributorId":261734,"corporation":false,"usgs":false,"family":"Wood","given":"Chris","email":"","middleInitial":"M.","affiliations":[{"id":52974,"text":"University of British Columbia, Vancouver, British Columbia, Canada.","active":true,"usgs":false}],"preferred":false,"id":820509,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70208100,"text":"70208100 - 2020 - Thresholds for post-wildfire debris flows: Insights from the Pinal Fire, Arizona, USA","interactions":[],"lastModifiedDate":"2020-06-04T16:48:14.988077","indexId":"70208100","displayToPublicDate":"2019-12-27T07:11:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Thresholds for post-wildfire debris flows: Insights from the Pinal Fire, Arizona, USA","docAbstract":"Wildfire significantly alters the hydrologic properties of a burned area, leading to increases in overland flow, erosion, and the potential for runoff-generated debris flows. The initiation of debris flows in recently burned areas is well-characterized by rainfall intensity-duration (ID) thresholds. However, there is currently a paucity of data quantifying the rainfall intensities required to trigger post-wildfire debris flows, which limits our understanding of how and why rainfall ID thresholds vary in different climatic and geologic settings. In this study, we monitored debris-flow activity following the Pinal Fire in central Arizona, which differs from both a climatic and hydrogeomorphic perspective from other regions in the western U.S. where ID thresholds for post-wildfire debris flows are well-established, namely the Transverse Ranges of southern CA. Since the peak rainfall intensity within a rainstorm may exceed the rainfall intensity required to trigger a debris flow, the development of robust rainfall ID thresholds requires knowledge of the timing of debris flows within rainstorms. Existing post-wildfire debris-flow studies in Arizona only constrain the peak rainfall intensity within debris-flow-producing storms, which may far exceed the intensity that actually triggered the observed debris flow. In this study, we used pressure transducers within 5 burned drainage basins to constrain the timing of debris flows within rainstorms. Rainfall ID thresholds derived here from triggering rainfall intensities are, on average, 22 mm/h lower than ID thresholds derived under the assumption that the triggering intensity is equal to the maximum rainfall intensity recorded during a rainstorm. We then use a hydrologic model to demonstrate that the magnitude of the 15-minute rainfall ID threshold at the Pinal Fire site is associated with the rainfall intensity required to exceed a recently proposed dimensionless discharge threshold for debris-flow initiation. Model results further suggest that previously observed differences in regional ID thresholds between Arizona and the San Gabriel Mountains of southern CA may be attributed, in large part, to differences in the hydraulic properties of burned soils.","language":"English","publisher":"Wiley","doi":"10.1002/esp.4805","usgsCitation":"Raymond, C.A., McGuire, L.A., Youberg, A.M., Staley, D.M., and Kean, J.W., 2020, Thresholds for post-wildfire debris flows: Insights from the Pinal Fire, Arizona, USA: Earth Surface Processes and Landforms, v. 45, no. 6, p. 1349-1360, https://doi.org/10.1002/esp.4805.","productDescription":"12 p.","startPage":"1349","endPage":"1360","ipdsId":"IP-112967","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":371633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.994873046875,\n              33.25936011503665\n            ],\n            [\n              -110.60348510742188,\n              33.25936011503665\n            ],\n            [\n              -110.60348510742188,\n              33.543683878655926\n            ],\n            [\n              -110.994873046875,\n              33.543683878655926\n            ],\n            [\n              -110.994873046875,\n              33.25936011503665\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"45","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Raymond, Carissa A","contributorId":221837,"corporation":false,"usgs":false,"family":"Raymond","given":"Carissa","email":"","middleInitial":"A","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":780463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Luke A. 0000-0001-8178-7922 lmcguire@usgs.gov","orcid":"https://orcid.org/0000-0001-8178-7922","contributorId":203420,"corporation":false,"usgs":false,"family":"McGuire","given":"Luke","email":"lmcguire@usgs.gov","middleInitial":"A.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":780464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Youberg, Ann M. 0000-0002-2005-3674","orcid":"https://orcid.org/0000-0002-2005-3674","contributorId":172609,"corporation":false,"usgs":false,"family":"Youberg","given":"Ann","email":"","middleInitial":"M.","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address:  TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":true,"id":780465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":780466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":780462,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70211487,"text":"70211487 - 2020 - Local climate determines vulnerability to camouflage mismatch in snowshoe hares","interactions":[],"lastModifiedDate":"2020-07-29T00:55:17.688689","indexId":"70211487","displayToPublicDate":"2019-12-26T19:45:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Local climate determines vulnerability to camouflage mismatch in snowshoe hares","docAbstract":"<h3 id=\"geb13049-sec-0001-title\" class=\"article-section__sub-title section1\">Aim</h3><p>Phenological mismatches, when life‐events become mistimed with optimal environmental conditions, have become increasingly common under climate change. Population‐level susceptibility to mismatches depends on how phenology and phenotypic plasticity vary across a species’ distributional range. Here, we quantify the environmental drivers of colour moult phenology, phenotypic plasticity, and the extent of phenological mismatch in seasonal camouflage to assess vulnerability to mismatch in a common North American mammal.</p><h3 id=\"geb13049-sec-0002-title\" class=\"article-section__sub-title section1\">Location</h3><p>North America.</p><h3 id=\"geb13049-sec-0003-title\" class=\"article-section__sub-title section1\">Time period</h3><p>2010–2017.</p><h3 id=\"geb13049-sec-0004-title\" class=\"article-section__sub-title section1\">Major taxa studied</h3><p>Snowshoe hare (<i>Lepus americanus<span>&nbsp;</span></i>).</p><h3 id=\"geb13049-sec-0005-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We used &gt;&nbsp;5,500 by‐catch photographs of snowshoe hares from 448 remote camera trap sites at three independent study areas. To quantify moult phenology and phenotypic plasticity, we used multinomial logistic regression models that incorporated geospatial and high‐resolution climate data. We estimated occurrence of camouflage mismatch between hares’ coat colour and the presence and absence of snow over 7&nbsp;years of monitoring.</p><h3 id=\"geb13049-sec-0006-title\" class=\"article-section__sub-title section1\">Results</h3><p>Spatial and temporal variation in moult phenology depended on local climate conditions more so than on latitude. First, hares in colder, snowier areas moulted earlier in the fall and later in the spring. Next, hares exhibited phenotypic plasticity in moult phenology in response to annual variation in temperature and snow duration, especially in the spring. Finally, the occurrence of camouflage mismatch varied in space and time; white hares on dark, snowless background occurred primarily during low‐snow years in regions characterized by shallow, short‐lasting snowpack.</p><h3 id=\"geb13049-sec-0007-title\" class=\"article-section__sub-title section1\">Main conclusions</h3><p>Long‐term climate and annual variation in snow and temperature determine coat colour moult phenology in snowshoe hares. In most areas, climate change leads to shorter snow seasons, but the occurrence of camouflage mismatch varies across the species’ range. Our results underscore the population‐specific susceptibility to climate change‐induced stressors and the necessity to understand this variation to prioritize the populations most vulnerable under global environmental change.</p>","language":"English","publisher":"Wiley","doi":"10.1111/geb.13049","usgsCitation":"Zimova, M., Siren, A., Nowak, J.J., Bryan, A., Ivan, J., Morelli, T.L., Suhrer, S.L., Whittington, J., and Mills, L.S., 2020, Local climate determines vulnerability to camouflage mismatch in snowshoe hares: Global Ecology and Biogeography, v. 29, no. 3, p. 503-515, https://doi.org/10.1111/geb.13049.","productDescription":"13 p.","startPage":"503","endPage":"515","ipdsId":"IP-112695","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":467307,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/geb.13049","text":"External Repository"},{"id":376822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -77.16796875,\n              39.774769485295465\n            ],\n            [\n              -63.10546874999999,\n              43.70759350405294\n            ],\n            [\n              -50.9765625,\n              48.10743118848039\n            ],\n            [\n              -61.87499999999999,\n              57.42129439209407\n            ],\n            [\n              -74.53125,\n              59.355596110016315\n            ],\n            [\n              -78.22265625,\n              59.085738569819505\n            ],\n            [\n              -75.5859375,\n              56.17002298293205\n            ],\n            [\n              -79.1015625,\n              54.36775852406841\n            ],\n            [\n              -79.27734374999999,\n              51.069016659603896\n            ],\n            [\n              -82.6171875,\n              55.27911529201561\n            ],\n            [\n              -91.58203125,\n              57.42129439209407\n            ],\n            [\n              -94.74609375,\n              59.5343180010956\n            ],\n            [\n              -131.484375,\n              67.941650035336\n            ],\n            [\n              -154.51171875,\n              69.96043926902489\n            ],\n            [\n              -166.46484375,\n              68.52823492039876\n            ],\n            [\n              -162.24609375,\n              66.58321725728175\n            ],\n            [\n              -163.125,\n              66.16051056018838\n            ],\n            [\n              -164.35546875,\n              66.65297740055279\n            ],\n            [\n              -167.51953124999997,\n              65.58572002329473\n            ],\n            [\n              -165.76171875,\n              64.47279382008166\n            ],\n            [\n              -160.3125,\n              64.77412531292873\n            ],\n            [\n              -162.0703125,\n              63.6267446447533\n            ],\n            [\n              -164.35546875,\n              62.83508901142283\n            ],\n            [\n              -166.2890625,\n              61.438767493682825\n            ],\n            [\n              -164.00390625,\n              59.80063426102869\n            ],\n            [\n              -161.3671875,\n              58.63121664342478\n            ],\n            [\n              -156.796875,\n              58.35563036280964\n            ],\n            [\n              -169.45312499999997,\n              52.696361078274485\n            ],\n            [\n              -153.80859375,\n              56.75272287205736\n            ],\n            [\n              -149.23828125,\n              59.80063426102869\n            ],\n            [\n              -145.1953125,\n              59.977005492196\n            ],\n            [\n              -139.74609375,\n              58.26328705248601\n            ],\n            [\n              -135.35156249999997,\n              55.87531083569679\n            ],\n            [\n              -132.890625,\n              52.908902047770255\n            ],\n            [\n              -124.1015625,\n              47.635783590864854\n            ],\n            [\n              -124.98046874999999,\n              41.376808565702355\n            ],\n            [\n              -121.11328124999999,\n              46.07323062540835\n            ],\n            [\n              -111.796875,\n              36.73888412439431\n            ],\n            [\n              -107.57812499999999,\n              46.92025531537451\n            ],\n            [\n              -103.18359375,\n              47.517200697839414\n            ],\n            [\n              -89.296875,\n              44.33956524809713\n            ],\n            [\n              -83.14453125,\n              43.068887774169625\n            ],\n            [\n              -79.98046875,\n              42.032974332441405\n            ],\n            [\n              -77.16796875,\n              39.774769485295465\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-12-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Zimova, Marketa","contributorId":171704,"corporation":false,"usgs":false,"family":"Zimova","given":"Marketa","affiliations":[],"preferred":false,"id":794285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siren, Alexej P. K.","contributorId":236810,"corporation":false,"usgs":false,"family":"Siren","given":"Alexej P. K.","affiliations":[],"preferred":false,"id":794286,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nowak, Joshua J.","contributorId":236829,"corporation":false,"usgs":false,"family":"Nowak","given":"Joshua","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":794287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bryan, Alexander 0000-0003-2040-7636 abryan@usgs.gov","orcid":"https://orcid.org/0000-0003-2040-7636","contributorId":168822,"corporation":false,"usgs":true,"family":"Bryan","given":"Alexander","email":"abryan@usgs.gov","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":794290,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ivan, Jacob S.","contributorId":200243,"corporation":false,"usgs":false,"family":"Ivan","given":"Jacob S.","affiliations":[],"preferred":false,"id":794284,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":794289,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Suhrer, Skyler L.","contributorId":236830,"corporation":false,"usgs":false,"family":"Suhrer","given":"Skyler","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":794367,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Whittington, Jesse","contributorId":179372,"corporation":false,"usgs":false,"family":"Whittington","given":"Jesse","email":"","affiliations":[],"preferred":false,"id":794368,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mills, L. Scott","contributorId":236757,"corporation":false,"usgs":false,"family":"Mills","given":"L.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":794288,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70227717,"text":"70227717 - 2020 - Spatial sampling bias and model complexity in stream-based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, USA","interactions":[],"lastModifiedDate":"2022-01-27T16:55:07.591983","indexId":"70227717","displayToPublicDate":"2019-12-25T10:48:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7470,"text":"Ecology & Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatial sampling bias and model complexity in stream-based species distribution models: A case study of Paddlefish (<i>Polyodon spathula</i>) in the Arkansas River basin, USA","title":"Spatial sampling bias and model complexity in stream-based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, USA","docAbstract":"<p><span>Leveraging existing presence records and geospatial datasets, species distribution modeling has been widely applied to informing species conservation and restoration efforts. Maxent is one of the most popular modeling algorithms, yet recent research has demonstrated Maxent models are vulnerable to prediction errors related to spatial sampling bias and model complexity. Despite elevated rates of biodiversity imperilment in stream ecosystems, the application of Maxent models to stream networks has lagged, as has the availability of tools to address potential sources of error and calculate model evaluation metrics when modeling in nonraster environments (such as stream networks). Herein, we use Maxent and customized R code to estimate the potential distribution of paddlefish (</span><i>Polyodon spathula</i><span>) at a stream-segment level within the Arkansas River basin, USA, while accounting for potential spatial sampling bias and model complexity. Filtering the presence data appeared to adequately remove an eastward, large-river sampling bias that was evident within the unfiltered presence dataset. In particular, our novel riverscape filter provided a repeatable means of obtaining a relatively even coverage of presence data among watersheds and streams of varying sizes. The greatest differences in estimated distributions were observed among models constructed with default versus AIC</span><sub>C</sub><span>-selected parameterization. Although all models had similarly high performance and evaluation metrics, the AIC</span><sub>C</sub><span>-selected models were more inclusive of westward-situated and smaller, headwater streams. Overall, our results solidified the importance of accounting for model complexity and spatial sampling bias in SDMs constructed within stream networks and provided a roadmap for future paddlefish restoration efforts in the study area.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5913","usgsCitation":"Taylor, A., Hafen, T., Holley, C.T., Gonzalez, A., and Long, J.M., 2020, Spatial sampling bias and model complexity in stream-based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, USA: Ecology & Evolution, v. 10, no. 2, p. 705-717, https://doi.org/10.1002/ece3.5913.","productDescription":"13 p.","startPage":"705","endPage":"717","ipdsId":"IP-108639","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":458296,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5913","text":"Publisher Index Page"},{"id":394979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Colorado, Kansas, Missouri, Nebraska, New Mexico, Texas","otherGeospatial":"Arkansas River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.314453125,\n              34.08906131584994\n            ],\n            [\n              -91.845703125,\n              34.08906131584994\n            ],\n            [\n              -91.845703125,\n              39.30029918615029\n            ],\n            [\n              -107.314453125,\n              39.30029918615029\n            ],\n            [\n              -107.314453125,\n              34.08906131584994\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-12-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, A. T.","contributorId":264887,"corporation":false,"usgs":false,"family":"Taylor","given":"A. T.","affiliations":[{"id":54572,"text":"University of Central Oklahoma","active":true,"usgs":false}],"preferred":false,"id":831896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hafen, T.","contributorId":272271,"corporation":false,"usgs":false,"family":"Hafen","given":"T.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":831897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holley, Colt Taylor 0000-0003-4172-4331","orcid":"https://orcid.org/0000-0003-4172-4331","contributorId":272272,"corporation":false,"usgs":true,"family":"Holley","given":"Colt","email":"","middleInitial":"Taylor","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":831898,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gonzalez, A.","contributorId":272273,"corporation":false,"usgs":false,"family":"Gonzalez","given":"A.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":831899,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":831900,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70209758,"text":"70209758 - 2020 - Effect of an environmental flow on vegetation growth and health using ground and remote sensing metrics","interactions":[],"lastModifiedDate":"2020-04-28T14:24:02.273893","indexId":"70209758","displayToPublicDate":"2019-12-24T08:13:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Effect of an environmental flow on vegetation growth and health using ground and remote sensing metrics","docAbstract":"<p><span>Understanding the effectiveness of environmental flow deliveries along rivers requires monitoring vegetation. Monitoring data are often collected at multiple spatial scales. For riparian vegetation, optical remote sensing methods can estimate growth responses at the riparian corridor scale, and field‐based measures can quantify species composition; however, the extent to which these different measures are duplicative or complementary is important to understand when planning monitoring programmes with limited resources. In this study, we analysed riparian vegetation growth in the delta of the Colorado River in response to an experimental pulse flow. Our goal was to compare ground‐based measurements of vegetation structure and composition with satellite‐based Landsat radiometric variables, such as the normalized difference vegetation index (NDVI). We made this comparison in 21 transects following the delivery of 131.8 million cubic meters (mcm) of water in the stream channel during the spring of 2014 as a pulse flow and 38.4 mcm as base flows. Vegetation cover increased 14% and NDVI increased 0.02 (15%) by October 2015, and both variables returned to pre‐pulse flow values in October 2016. Observed changes in vegetation structure and composition did not persist after the second year. The highest increase in vegetation cover in October 2014 and October 2015 resulted from species that could respond rapidly to additional water such as reeds (</span><i>Arundo donax</i><span>&nbsp;and&nbsp;</span><i>Phragmites australis</i><span>), cattail (</span><i>Typha domingensis</i><span>), and herbaceous plants. Dominant shrubs, saltcedar (</span><i>Tamarix</i><span>&nbsp;spp.) and arrowweed (</span><i>Pluchea sericea</i><span>), both indicative of nonrestored habitats showed variable increases in cover, and native trees (</span><i>Salicaceae</i><span>&nbsp;family) presented low increases (1%). The strong NDVI–vegetation cover relationship indicates that NDVI is appropriate to detect changes at the riparian corridor scale but needs to be complemented with ground data to determine the contributions by different species to the observed trends.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13689","collaboration":"","usgsCitation":"Gomez-Sapiens, M.M., Jarchow, C., Flessa, K.W., Shafroth, P.B., Glenn, E., and Nagler, P.L., 2020, Effect of an environmental flow on vegetation growth and health using ground and remote sensing metrics: Hydrological Processes, v. 34, no. 8, p. 1682-1696, https://doi.org/10.1002/hyp.13689.","productDescription":"15 p.","startPage":"1682","endPage":"1696","ipdsId":"IP-109952","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488909,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/659868","text":"External Repository"},{"id":374314,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Colorado River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.3070068359375,\n              31.5691754490709\n            ],\n            [\n              -114.70275878906249,\n              31.5691754490709\n            ],\n            [\n              -114.70275878906249,\n              32.708733368521585\n            ],\n            [\n              -115.3070068359375,\n              32.708733368521585\n            ],\n            [\n              -115.3070068359375,\n              31.5691754490709\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"34","issue":"8","noUsgsAuthors":false,"publicationDate":"2020-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Gomez-Sapiens, Martha M.","contributorId":58172,"corporation":false,"usgs":true,"family":"Gomez-Sapiens","given":"Martha","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":787897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarchow, Christopher 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":196069,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":787898,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flessa, Karl W.","contributorId":175308,"corporation":false,"usgs":false,"family":"Flessa","given":"Karl","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":787899,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":787900,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Glenn, Edward P.","contributorId":56542,"corporation":false,"usgs":false,"family":"Glenn","given":"Edward P.","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":787901,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":787902,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70207590,"text":"70207590 - 2020 - Colony-forming unit spreadplate assay versus liquid culture enrichment-polymerase chain reaction assay for the detection of <i>Bacillus Endospores</i> in soils","interactions":[],"lastModifiedDate":"2019-12-30T16:20:46","indexId":"70207590","displayToPublicDate":"2019-12-21T16:19:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1816,"text":"Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"Colony-forming unit spreadplate assay versus liquid culture enrichment-polymerase chain reaction assay for the detection of <i>Bacillus Endospores</i> in soils","docAbstract":"A liquid culture enrichment-polymerase chain reaction (E-PCR) assay was investigated as a potential tool to overcome inhibition by chemical component, debris, and background biological impurities in soil that were affecting detection assay performance for soil samples containing Bacillus atrophaeus subsp. globigii (a surrogate for B. anthracis). To evaluate this assay, 9 g of matched sets of three different soil types (loamy sand [sand], sandy loam [loam] and clay) was spiked with 0, ~4.5, 45, 225, 675 and 1350 endospores. One matched set was evaluated using a previously published endospore concentration and colony-forming unit spreadplate (CFU-S) assay and the other matched set was evaluated using an E-PCR assay to investigate differences in limits of detection between the two assays. Data illustrated that detection using the CFU-S assay at the 45-endospore spike level started to become sporadic whereas the E-PCR assay produced repeatable detection at the ~4.5-endospore spike concentration. The E-PCR produced an ~2-log increase in sensitivity and required slightly less time to complete than the CFU-S assay. This study also investigated differences in recovery among pure and blended sand and clay soils and found potential activation of B. anthracis in predominately clay-based soils.","language":"English","publisher":"MDPI","doi":"10.3390/geosciences10010005","usgsCitation":"Griffin, D.W., Lisle, J.T., Feldhake, D., and Silvestri, E.E., 2020, Colony-forming unit spreadplate assay versus liquid culture enrichment-polymerase chain reaction assay for the detection of <i>Bacillus Endospores</i> in soils: Geosciences, v. 1, no. 10, 5, 14 p., https://doi.org/10.3390/geosciences10010005.","productDescription":"5, 14 p.","ipdsId":"IP-105751","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":458313,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/geosciences10010005","text":"Publisher Index Page"},{"id":370875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","issue":"10","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Griffin, Dale W. 0000-0003-1719-5812 dgriffin@usgs.gov","orcid":"https://orcid.org/0000-0003-1719-5812","contributorId":2178,"corporation":false,"usgs":true,"family":"Griffin","given":"Dale","email":"dgriffin@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":778623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lisle, John T. 0000-0002-5447-2092 jlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-5447-2092","contributorId":2944,"corporation":false,"usgs":true,"family":"Lisle","given":"John","email":"jlisle@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":778624,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feldhake, David","contributorId":176367,"corporation":false,"usgs":false,"family":"Feldhake","given":"David","email":"","affiliations":[],"preferred":false,"id":778625,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Silvestri, Erin E.","contributorId":127343,"corporation":false,"usgs":false,"family":"Silvestri","given":"Erin","email":"","middleInitial":"E.","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":778626,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70206612,"text":"70206612 - 2020 - Post-12 Ma deformation of the lower Colorado River corridor, southwestern USA: Implications for diffuse transtension and the Bouse Formation","interactions":[],"lastModifiedDate":"2020-02-06T11:33:10","indexId":"70206612","displayToPublicDate":"2019-12-20T17:17:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Post-12 Ma deformation of the lower Colorado River corridor, southwestern USA: Implications for diffuse transtension and the Bouse Formation","docAbstract":"<p><span>Structural evidence presented here documents that deformation was ongoing within the lower Colorado River corridor (southwestern USA) during and after the latest Miocene Epoch, postdating large-magnitude extension and metamorphic core complex formation. Geometric and kinematic data collected on faults in key geologic units constrain the timing of deformation in relation to the age of the Bouse Formation, a unit that records the first arrival and integration of the Colorado River. North-south–striking extensional, NW-SE–striking oblique dextral, NE-SW–striking oblique sinistral, and east-west–striking contractional faults and related structures are observed to deform pre– (&gt;6 Ma), syn– (6–4.8 Ma), and post–Bouse Formation (&lt;4.8 Ma) strata. Fault displacements are typically at the centimeter to meter scale, and locally exhibit 10-m-scale displacements. Bouse Formation basalt carbonate locally exhibits outcrop-scale (tens of meters) syndepositional dips of 30°–90°, draped over and encrusted upon paleotopography, and has a basin-wide vertical distribution of as much as 500 m. We argue that part of this vertical distribution of Bouse Formation deposits represents syn- and post-Bouse deformation that enhanced north-south–trending depocenters due to combined tectonic and isostatic subsidence in a regional fault kinematic framework of east-west diffuse extension within an overall strain field of dextral transtension. Here we (1) characterize post-detachment tectonism within the corridor, (2) show that diffuse tectonism is cumulatively significant and likely modified original elevations of Bouse Formation outcrops, and (3) demonstrate that this tectonism may have played a role in the integration history of the lower Colorado River. We suggest a model whereby intracontinental transtension took place in a several hundred kilometers-wide area inboard of the San Andreas fault within a diffuse Pacific–North America plate margin since the latest Miocene.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02104.1","usgsCitation":"Thacker, J., Karlstrom, K., Crossey, L., Crow, R.S., Cassidy, C., Beard, L.S., Singleton, J., Strickland, E., Seymour, N., and Wyatt, M., 2020, Post-12 Ma deformation of the lower Colorado River corridor, southwestern USA: Implications for diffuse transtension and the Bouse Formation: Geosphere, v. 16, no. 1, p. 111-135, https://doi.org/10.1130/GES02104.1.","productDescription":"25 p.","startPage":"111","endPage":"135","ipdsId":"IP-104568","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":458319,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02104.1","text":"Publisher Index Page"},{"id":371093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Lower Colorado River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.6201171875,\n              32.7872745269555\n            ],\n            [\n              -113.51074218749999,\n              32.7872745269555\n            ],\n            [\n              -113.51074218749999,\n              35.94243575255426\n            ],\n            [\n              -115.6201171875,\n              35.94243575255426\n            ],\n            [\n              -115.6201171875,\n              32.7872745269555\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"16","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Thacker, Jacob 0000-0001-7174-6115 jthacker@usgs.gov","orcid":"https://orcid.org/0000-0001-7174-6115","contributorId":187771,"corporation":false,"usgs":false,"family":"Thacker","given":"Jacob","email":"jthacker@usgs.gov","affiliations":[],"preferred":false,"id":779160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karlstrom, Karl","contributorId":218165,"corporation":false,"usgs":false,"family":"Karlstrom","given":"Karl","affiliations":[{"id":16658,"text":"UNM","active":true,"usgs":false}],"preferred":false,"id":775174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crossey, Laura","contributorId":220554,"corporation":false,"usgs":false,"family":"Crossey","given":"Laura","affiliations":[{"id":16658,"text":"UNM","active":true,"usgs":false}],"preferred":false,"id":775175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crow, Ryan S. 0000-0002-2403-6361 rcrow@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-6361","contributorId":5792,"corporation":false,"usgs":true,"family":"Crow","given":"Ryan","email":"rcrow@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":775172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cassidy, Colleen 0000-0003-2963-9185","orcid":"https://orcid.org/0000-0003-2963-9185","contributorId":207193,"corporation":false,"usgs":true,"family":"Cassidy","given":"Colleen","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":775176,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beard, L. Sue 0000-0001-9552-1893 sbeard@usgs.gov","orcid":"https://orcid.org/0000-0001-9552-1893","contributorId":152,"corporation":false,"usgs":true,"family":"Beard","given":"L.","email":"sbeard@usgs.gov","middleInitial":"Sue","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":775177,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Singleton, John","contributorId":220555,"corporation":false,"usgs":false,"family":"Singleton","given":"John","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":775178,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Strickland, Evan","contributorId":220556,"corporation":false,"usgs":false,"family":"Strickland","given":"Evan","email":"","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":775179,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Seymour, Nikki","contributorId":220557,"corporation":false,"usgs":false,"family":"Seymour","given":"Nikki","email":"","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":775180,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wyatt, Michael","contributorId":220558,"corporation":false,"usgs":false,"family":"Wyatt","given":"Michael","email":"","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":775181,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70207543,"text":"70207543 - 2020 - Invertebrate communities of Prairie-Pothole wetlands in the age of the aquatic Homogenocene","interactions":[],"lastModifiedDate":"2020-10-12T16:29:50.24873","indexId":"70207543","displayToPublicDate":"2019-12-20T11:44:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Invertebrate communities of Prairie-Pothole wetlands in the age of the aquatic Homogenocene","docAbstract":"<p><span>Simplification of communities is a common consequence of anthropogenic modification. However, the prevalence and mechanisms of biotic homogenization among wetland systems require further examination. Biota of wetlands in the North American Prairie Pothole Region are adapted to high spatial and temporal variability in ponded-water duration and salinity. Recent climate change, however, has resulted in decreased hydrologic variability. Land-use changes have exacerbated this loss of variability. We used aquatic-macroinvertebrate data from 16 prairie-pothole wetlands sampled between 1992 and 2015 to explore homogenization of wetland communities. Macroinvertebrate communities of small wetlands that continued to cycle between wet and dry phases experienced greater turnover and supported unique taxa compared to larger wetlands that shifted towards less dynamic permanently ponded, lake-like regimes. Temporal turnover in beta-diversity was lowest in these permanently ponded wetlands. Additionally, wetlands that shifted to permanently ponded regimes also experienced a shift from palustrine to lacustrine communities. While increased pond permanence can increase species and overall beta-diversity in local areas previously lacking lake communities, homogenization of wetland communities at a larger, landscape scale can result in an overall loss of biodiversity as the diverse communities of many wetland systems become increasingly similar to those of lakes.</span></p>","language":"English","publisher":"Springer International Publishing","doi":"10.1007/s10750-019-04154-4","usgsCitation":"McLean, K., Mushet, D.M., Sweetman, J.N., Anteau, M.J., and Wiltermuth, M.T., 2020, Invertebrate communities of Prairie-Pothole wetlands in the age of the aquatic Homogenocene: Hydrobiologia, v. 847, p. 3773-3793, https://doi.org/10.1007/s10750-019-04154-4.","productDescription":"21 p.","startPage":"3773","endPage":"3793","ipdsId":"IP-111199","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":370671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","county":"Stutsman County","otherGeospatial":"Cottonwood Lake Study Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -100.77999114990234,\n              47.820762392755846\n            ],\n            [\n              -100.63407897949219,\n              47.820762392755846\n            ],\n            [\n              -100.63407897949219,\n              47.939116930322\n            ],\n            [\n              -100.77999114990234,\n              47.939116930322\n            ],\n            [\n              -100.77999114990234,\n              47.820762392755846\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"847","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"McLean, Kyle 0000-0003-3803-0136 kmclean@usgs.gov","orcid":"https://orcid.org/0000-0003-3803-0136","contributorId":168533,"corporation":false,"usgs":true,"family":"McLean","given":"Kyle","email":"kmclean@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":778407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":778408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sweetman, Jon N. 0000-0002-9849-7355","orcid":"https://orcid.org/0000-0002-9849-7355","contributorId":221489,"corporation":false,"usgs":false,"family":"Sweetman","given":"Jon","email":"","middleInitial":"N.","affiliations":[{"id":12471,"text":"North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":778409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":778410,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wiltermuth, Mark T. 0000-0002-8871-2816 mwiltermuth@usgs.gov","orcid":"https://orcid.org/0000-0002-8871-2816","contributorId":708,"corporation":false,"usgs":true,"family":"Wiltermuth","given":"Mark","email":"mwiltermuth@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":778411,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
]}