The construction of impassable dams severely affected many Pacific salmon Oncorhynchus spp. populations, resulting in reintroduction efforts that are now focused on returning anadromous fish to areas located upstream of these dams. A primary strategy for moving adult salmon and steelhead O. mykiss around a dam or multiple dams involves trapping fish downstream and transporting them to upstream areas (“trap and haul”) for spawning. We conducted a 4‐year radiotelemetry study to evaluate behavior and movement patterns of hatchery‐ and natural‐origin adult spring Chinook Salmon O. tshawytscha after a trap‐and‐haul program was implemented around three dams on the Cowlitz River, Washington. A multistate model was used to describe how factors such as origin, sex, release site location, and discharge affected transition rates to riverine areas where spawning habitat was located. Natural‐origin Chinook Salmon moved upstream from a reservoir release site and entered one of two rivers more quickly and in greater proportions than hatchery‐origin fish. Results from the multistate model indicated that transition rates from the reservoir to the Cowlitz River were 2.2 times higher for natural‐origin Chinook Salmon than for hatchery‐origin fish. About one‐half (49.6%) of the reservoir‐released hatchery‐origin Chinook Salmon moved upstream into the Cowlitz River or the Cispus River during the spawning period. The release of hatchery‐origin Chinook Salmon directly into these rivers increased the percentage of fish with river fates during the spawning period to 72.3–75.4%. Results from the multistate model showed that factors such as release site location, origin, day of year, and discharge were important predictors of transition intensities between specific locations in the study area. These findings illustrate the need to evaluate how salmon and steelhead respond to trap‐and‐haul methods, allowing for better management of reintroduction efforts in the future.
","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10199","usgsCitation":"Kock, T.J., Perry, R.W., Pope, A.C., Serl, J.D., Kohn, M., and Liedtke, T.L., 2018, Responses of hatchery‐ and natural‐origin adult spring Chinook Salmon to a trap‐and‐haul reintroduction program: North American Journal of Fisheries Management, v. 38, no. 5, p. 1004-1016, https://doi.org/10.1002/nafm.10199.","productDescription":"13 p.","startPage":"1004","endPage":"1016","ipdsId":"IP-090272","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":356524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Cowlitz River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.22290039062499,\n 46.3886223381617\n ],\n [\n -121.453857421875,\n 46.3886223381617\n ],\n [\n -121.453857421875,\n 46.66263249079177\n ],\n [\n -122.22290039062499,\n 46.66263249079177\n ],\n [\n -122.22290039062499,\n 46.3886223381617\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-13","publicationStatus":"PW","scienceBaseUri":"5b98a285e4b0702d0e842f2f","contributors":{"authors":[{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":742550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":742551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pope, Adam C. 0000-0002-7253-2247 apope@usgs.gov","orcid":"https://orcid.org/0000-0002-7253-2247","contributorId":5664,"corporation":false,"usgs":true,"family":"Pope","given":"Adam","email":"apope@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":742552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Serl, John D.","contributorId":207057,"corporation":false,"usgs":false,"family":"Serl","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":37444,"text":"Washington Department of Fish and Wildlife, Cowlitz Falls Fish Facility, Randle, WA","active":true,"usgs":false}],"preferred":false,"id":742553,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kohn, Mike","contributorId":207058,"corporation":false,"usgs":false,"family":"Kohn","given":"Mike","email":"","affiliations":[{"id":37445,"text":"Public Utility District Number 1 of Lewis County, Cowlitz Falls Project, Morton, WA","active":true,"usgs":false}],"preferred":false,"id":742554,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":742555,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198671,"text":"70198671 - 2018 - Evaluating the waterfowl breeding population and habitat survey for scaup","interactions":[],"lastModifiedDate":"2018-08-15T13:42:15","indexId":"70198671","displayToPublicDate":"2018-08-15T13:42:09","publicationYear":"2018","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":"Evaluating the waterfowl breeding population and habitat survey for scaup","docAbstract":"Potential bias in breeding population estimates of certain duck species from the Waterfowl Breeding Population and Habitat Survey (WBPHS) has been a concern for decades. The WBPHS does not differentiate between lesser (Aythya affinis) and greater (A. marila) scaup, but lesser scaup comprise 89% of the combined scaup population and their population estimates are suspected to be biased. We marked female lesser scaup (i.e., marked scaup) in the Mississippi and Atlantic Flyways, Canada and United States, with implantable satellite transmitters to track their spring migration through the traditional and eastern survey areas of the WBPHS, 2005–2010. Our goal was to use data independent of the WBPHS to evaluate whether breeding population estimates for scaup were biased and identify variables that might be used in the future to refine population estimates. We found that the WBPHS estimates of breeding scaup are biased because, across years, only 30% of our marked scaup had settled for the breeding period when the strata in which they settled were surveyed, 43% were available to be counted in multiple survey strata as their migration continued during the WBPHS, 32% settled outside the WBPHS area, the number of times a marked scaup was available to be counted by survey crews varied positively with the latitude that a marked scaup settled on breeding areas, the probability of a marked scaup being in a stratum while it was surveyed varied among years, and these probabilities were positively correlated with the traditional and eastern breeding population estimates for scaup. Annual population estimates derived from banding data provide a less biased and preferable method of monitoring scaup population status and trend. Development of models that include metrics such as survey stratum latitude and annual spring environmental conditions might potentially be used to improve scaup breeding population estimates derived from the WBPHS, but independent estimates from banding data would be important to evaluate such models.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21478","usgsCitation":"Schummer, M.L., Afton, A.D., Badzinski, S.S., Petrie, S.A., Olsen, G.H., and Mitchell, M.A., 2018, Evaluating the waterfowl breeding population and habitat survey for scaup: Journal of Wildlife Management, v. 82, no. 6, p. 1252-1262, https://doi.org/10.1002/jwmg.21478.","productDescription":"11 p.","startPage":"1252","endPage":"1262","ipdsId":"IP-092640","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":356513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"82","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-25","publicationStatus":"PW","scienceBaseUri":"5b98a286e4b0702d0e842f35","contributors":{"authors":[{"text":"Schummer, Michael L.","contributorId":176347,"corporation":false,"usgs":false,"family":"Schummer","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":742504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Afton, Alan D. 0000-0002-0436-8588 aafton@usgs.gov","orcid":"https://orcid.org/0000-0002-0436-8588","contributorId":139582,"corporation":false,"usgs":false,"family":"Afton","given":"Alan","email":"aafton@usgs.gov","middleInitial":"D.","affiliations":[{"id":368,"text":"Louisiana Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":742505,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Badzinski, Shannon S.","contributorId":176348,"corporation":false,"usgs":false,"family":"Badzinski","given":"Shannon","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":742506,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Petrie, Scott A.","contributorId":141223,"corporation":false,"usgs":false,"family":"Petrie","given":"Scott","email":"","middleInitial":"A.","affiliations":[{"id":13717,"text":"Long Point Waterfowl","active":true,"usgs":false}],"preferred":false,"id":742507,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olsen, Glenn H. 0000-0002-7188-6203 golsen@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":40918,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"golsen@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":742503,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mitchell, Mark A.","contributorId":207036,"corporation":false,"usgs":false,"family":"Mitchell","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":37433,"text":"Department of Veterinary Clinical Medicine, University of Illinois, Urbana, IL 61802","active":true,"usgs":false}],"preferred":false,"id":742508,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198438,"text":"ofr20181126 - 2018 - An individual-based model for predicting dynamics of a newly established Mexican wolf (Canis lupus baileyi) population—Final report","interactions":[],"lastModifiedDate":"2018-08-24T14:08:04","indexId":"ofr20181126","displayToPublicDate":"2018-08-15T12:26:01","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1126","displayTitle":"An individual-based model for predicting dynamics of a newly established Mexican wolf (Canis lupus baileyi) population—Final report","title":"An individual-based model for predicting dynamics of a newly established Mexican wolf (Canis lupus baileyi) population—Final report","docAbstract":"The Mexican wolf recovery team proposed to establish other populations of Mexican wolves (Canis lupus baileyi) in the Southwest (U.S. Fish and Wildlife Service, 1982). We were tasked to conduct an extensive simulation modeling exercise to determine release strategies (in conjunction with management actions) that best predict establishment of a new Mexican wolf population. Our objectives were to determine optimal release and management strategies for population establishment and growth. This is a retrospective analysis utilizing data from 1998 to 2014, and during this period, we divided management strategies into two phases; (1) 1998–2008, where nuisance wolves (i.e., wolves that exhibit nuisance behavior or depredate livestock) were managed primarily through lethal removals and removals to captivity, and (2) 2009–2014, when lethal removals ceased and diversionary feeding was provided to denning packs to dissuade wolves from conflict with humans. Management strategies from the second phase are being used for management of the current Mexican wolf population, and demographic rates derived from alternate population modeling in Vortex incorporating post-2008 wolf data are being used to guide future recovery efforts. Therefore, demographic rates estimated from our retrospective analysis will differ (i.e., due to our unique approach to the analyses and the demographic rates being derived from a different dataset), and are intended solely to address the objectives of this report, and are not intended as basis for the development of management recommendations for the current Mexican wolf population. Using individual-based models, we tested dozens of scenarios and derived an optimal release strategy that had the highest probability of establishing a new population and which maximized subsequent post-release growth, and in this report, we present these model results. Findings from this research will improve our understanding of release strategies that yield growing populations, advance our understanding of the demands of reintroducing large carnivores, and provide insight into beneficial strategies that could aid other species reintroduction programs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181126","collaboration":"Prepared for U.S. Fish and Wildlife Service, Agreement: G12AC20098","usgsCitation":"Gedir, J.V., and Cain, J.W., III, 2018, An individual-based model for predicting dynamics of a newly established Mexican wolf (Canis lupus baileyi) population—Final report: U.S. Geological Survey Open-File Report 2018-1126, 16 p., https://doi.org/10.3133/ofr20181126.","productDescription":"iv, 16 p.","onlineOnly":"Y","ipdsId":"IP-085609","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":356548,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1126/ofr20181126.pdf","text":"Report","size":"904 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1126"},{"id":356547,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1126/coverthb.jpg"}],"country":"United States","state":"Arizona, New Mexico","contact":"Leader, Washington Cooperative Fish and Wildlife Research Unit
U.S. Geological Survey
Fishery Sciences Building, Box 355020
University of Washington
Seattle, Washington, 98195
https://www.coopunits.org/Washington/
We evaluated the interacting influences of river flows and tides on travel time, routing, and survival of juvenile late-fall Chinook salmon (Oncorhynchus tshawytscha) migrating through the Sacramento–San Joaquin River Delta. To quantify these effects, we jointly modeled the travel time, survival, and migration routing in relation to individual time-varying covariates of acoustic-tagged salmon within a Bayesian framework. We used observed arrival times for detected individuals and imputed arrival times for undetected individuals to assign covariate values in each reach. We found travel time was inversely related to river inflow in all reaches, yet survival was positively related to inflow only in reaches that transitioned from bidirectional tidal flows to unidirectional flow with increasing inflows. We also found that the probability of fish entering the interior Delta, a low-survival reach, declined as inflow increased. Our study illustrates how river inflows interact with tides to influence fish survival during the critical transition between freshwater and ocean environments. Furthermore, our analytical framework introduces new techniques to integrate formally over missing covariate values to quantify effects of time-varying covariates.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2017-0310","usgsCitation":"Perry, R.W., Pope, A.C., Romine, J., Brandes, P.L., Burau, J.R., Blake, A.R., Ammann, A.J., and Michel, C.J., 2018, Flow-mediated effects on travel time, routing, and survival of juvenile Chinook salmon in a spatially complex, tidally forced river delta: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 11, p. 1886-1901, https://doi.org/10.1139/cjfas-2017-0310.","productDescription":"16 p.","startPage":"1886","endPage":"1901","ipdsId":"IP-090251","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":437784,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OG5NX7","text":"USGS data release","linkHelpText":"The North Delta Routing and Survival Management Tool"},{"id":356577,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin River Delta","volume":"75","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a287e4b0702d0e842f3b","contributors":{"authors":[{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":742735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pope, Adam C. 0000-0002-7253-2247 apope@usgs.gov","orcid":"https://orcid.org/0000-0002-7253-2247","contributorId":5664,"corporation":false,"usgs":true,"family":"Pope","given":"Adam","email":"apope@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":742736,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romine, Jason G.","contributorId":207092,"corporation":false,"usgs":false,"family":"Romine","given":"Jason G.","affiliations":[{"id":37451,"text":"U.S. Fish & Wildlife Service, Mid-Columbia River National Wildlife Refuge Complex, 64 Maple St., Burbank, WA 99323","active":true,"usgs":false}],"preferred":false,"id":742737,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brandes, Patricia L.","contributorId":196879,"corporation":false,"usgs":false,"family":"Brandes","given":"Patricia","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":742738,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":742739,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blake, Aaron R. 0000-0001-7348-2336 ablake@usgs.gov","orcid":"https://orcid.org/0000-0001-7348-2336","contributorId":5059,"corporation":false,"usgs":true,"family":"Blake","given":"Aaron","email":"ablake@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":742740,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ammann, Arnold J.","contributorId":207095,"corporation":false,"usgs":false,"family":"Ammann","given":"Arnold","email":"","middleInitial":"J.","affiliations":[{"id":37452,"text":"National Marine Fisheries Service, Southwest Fisheries Science Center, 110 Shaffer Rd., Santa Cruz, CA 95060","active":true,"usgs":false}],"preferred":false,"id":742741,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Michel, Cyril J.","contributorId":207096,"corporation":false,"usgs":false,"family":"Michel","given":"Cyril","email":"","middleInitial":"J.","affiliations":[{"id":37452,"text":"National Marine Fisheries Service, Southwest Fisheries Science Center, 110 Shaffer Rd., Santa Cruz, CA 95060","active":true,"usgs":false}],"preferred":false,"id":742742,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70228065,"text":"70228065 - 2018 - A review of Bayesian belief network models as decision-support tools for wetland conservation: Are water birds potential umbrella taxa?","interactions":[],"lastModifiedDate":"2022-02-03T15:10:27.723944","indexId":"70228065","displayToPublicDate":"2018-08-15T09:06:57","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"A review of Bayesian belief network models as decision-support tools for wetland conservation: Are water birds potential umbrella taxa?","docAbstract":"Creative approaches to identifying umbrella species hold promise for devising effective surrogates of ecological communities or ecosystems. However, mechanistic niche models that predict range or habitat overlap among species may yet lack development. We reviewed literature on taxon-centered Bayesian belief network (BBN) models to explore a novel approach to identify umbrella taxa identifying taxonomic groups that share the largest proportion of habitat requirements (i.e., states of important habitat variables) with other wetland-dependent taxa. We reviewed and compiled published literature to provide a comprehensive and reproducible account of the current understanding of habitat requirements for freshwater, wetland-dependent taxa using BBNs. We found that wetland birds had the highest degree of shared habitat requirements with other taxa, and consequently may be suitable umbrella taxa in freshwater wetlands. Comparing habitat requirements using a BBN approach to build species distribution models, this review also identified taxa that may not benefit from conservation actions targeted at umbrella taxa by identifying taxa with unique habitat requirements not shared with umbrellas. Using a standard node set that accurately and comprehensively represents the ecosystem in question, BBNs could be designed to improve identification of umbrella taxa. In wetlands, expert knowledge about hydrology, geomorphology and soils could add important information regarding physical landscape characteristics relevant to species. Thus, a systems-oriented framework may improve overarching inferences from BBNs and subsequent utility to conservation planning and management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2018.08.001","usgsCitation":"MacPherson, M.P., Webb, E.B., Raedeke, A., Mengel, D.C., and Nelson, F., 2018, A review of Bayesian belief network models as decision-support tools for wetland conservation: Are water birds potential umbrella taxa?: Biological Conservation, v. 226, p. 215-223, https://doi.org/10.1016/j.biocon.2018.08.001.","productDescription":"9 p.","startPage":"215","endPage":"223","ipdsId":"IP-097201","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468496,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.biocon.2018.08.001","text":"External Repository"},{"id":395349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"226","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"MacPherson, Maggie P.","contributorId":274459,"corporation":false,"usgs":false,"family":"MacPherson","given":"Maggie","email":"","middleInitial":"P.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":833002,"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":833003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Raedeke, Andy","contributorId":274460,"corporation":false,"usgs":false,"family":"Raedeke","given":"Andy","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":833004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mengel, Doreen C.","contributorId":203619,"corporation":false,"usgs":false,"family":"Mengel","given":"Doreen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":833065,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, Frank","contributorId":274461,"corporation":false,"usgs":false,"family":"Nelson","given":"Frank","email":"","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":833005,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198666,"text":"70198666 - 2018 - Estimating distemper virus dynamics among wolves and grizzly bears using serology and Bayesian state‐space models","interactions":[],"lastModifiedDate":"2018-09-28T09:07:15","indexId":"70198666","displayToPublicDate":"2018-08-14T14:12:42","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Estimating distemper virus dynamics among wolves and grizzly bears using serology and Bayesian state‐space models","docAbstract":"Many parasites infect multiple hosts, but estimating the transmission across host species remains a key challenge in disease ecology. We investigated the within and across host species dynamics of canine distemper virus (CDV) in grizzly bears (Ursus arctos) and wolves (Canis lupus) of the Greater Yellowstone Ecosystem (GYE). We hypothesized that grizzly bears may be more likely to be exposed to CDV during outbreaks in the wolf population because grizzly bears often displace wolves while scavenging carcasses. We used serological data collected from 1984 to 2014 in conjunction with Bayesian state‐space models to infer the temporal dynamics of CDV. These models accounted for the unknown timing of pathogen exposure, and we assessed how different testing thresholds and the potential for testing errors affected our conclusions. We identified three main CDV outbreaks (1999, 2005, and 2008) in wolves, which were more obvious when we used higher diagnostic thresholds to qualify as seropositive. There was some evidence for increased exposure rates in grizzly bears in 2005, but the magnitude of the wolf effect on bear exposures was poorly estimated and depended upon our prior distributions. Grizzly bears were exposed to CDV prior to wolf reintroduction and during time periods outside of known wolf outbreaks, thus wolves are only one of several potential routes for grizzly bear exposures. Our modeling approach accounts for several of the shortcomings of serological data and is applicable to many wildlife disease systems, but is most informative when testing intervals are short. CDV circulates in a wide range of carnivore species, but it remains unclear whether the disease persists locally within the GYE carnivore community or is periodically reintroduced from distant regions with larger host populations.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4396","usgsCitation":"Cross, P.C., van Manen, F.T., Viana, M., Almberg, E.S., Bachen, D., Brandell, E.E., Haroldson, M.A., Hudson, P.J., Stahler, D.R., and Smith, D.W., 2018, Estimating distemper virus dynamics among wolves and grizzly bears using serology and Bayesian state‐space models: Ecology and Evolution, v. 8, no. 17, p. 8726-8735, https://doi.org/10.1002/ece3.4396.","productDescription":"10 p.","startPage":"8726","endPage":"8735","ipdsId":"IP-094527","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":468497,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4396","text":"Publisher Index Page"},{"id":356446,"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 -112.137451171875,\n 42.147114459220994\n ],\n [\n -108.6328125,\n 42.147114459220994\n ],\n [\n -108.6328125,\n 45.65244828675087\n ],\n [\n -112.137451171875,\n 45.65244828675087\n ],\n [\n -112.137451171875,\n 42.147114459220994\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"17","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-05","publicationStatus":"PW","scienceBaseUri":"5b98a287e4b0702d0e842f3f","contributors":{"authors":[{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":742402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":742403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Viana, Mafalda 0000-0001-5975-6505","orcid":"https://orcid.org/0000-0001-5975-6505","contributorId":207013,"corporation":false,"usgs":false,"family":"Viana","given":"Mafalda","email":"","affiliations":[{"id":37430,"text":"Glasgow University","active":true,"usgs":false}],"preferred":false,"id":742404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Almberg, Emily S.","contributorId":207014,"corporation":false,"usgs":false,"family":"Almberg","given":"Emily","email":"","middleInitial":"S.","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":742405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bachen, Daniel","contributorId":207015,"corporation":false,"usgs":false,"family":"Bachen","given":"Daniel","email":"","affiliations":[{"id":36895,"text":"Montana Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":742406,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brandell, Ellen E. 0000-0002-2698-7013","orcid":"https://orcid.org/0000-0002-2698-7013","contributorId":207016,"corporation":false,"usgs":false,"family":"Brandell","given":"Ellen","email":"","middleInitial":"E.","affiliations":[{"id":25381,"text":"Penn State Univ.","active":true,"usgs":false}],"preferred":false,"id":742407,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":742408,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hudson, Peter J.","contributorId":192149,"corporation":false,"usgs":false,"family":"Hudson","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":742409,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stahler, Daniel R.","contributorId":179180,"corporation":false,"usgs":false,"family":"Stahler","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":742410,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Douglas W.","contributorId":207018,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas","email":"","middleInitial":"W.","affiliations":[{"id":37432,"text":"Yellowstone National Park","active":true,"usgs":false}],"preferred":false,"id":742411,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70198643,"text":"70198643 - 2018 - Global and Arctic climate sensitivity enhanced by changes in North Pacific heat flux","interactions":[],"lastModifiedDate":"2018-08-14T13:54:10","indexId":"70198643","displayToPublicDate":"2018-08-14T13:54:07","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Global and Arctic climate sensitivity enhanced by changes in North Pacific heat flux","docAbstract":"Arctic amplification is a consequence of surface albedo, cloud, and temperature feedbacks, as well as poleward oceanic and atmospheric heat transport. However, the relative impact of changes in sea surface temperature (SST) patterns and ocean heat flux sourced from different regions on Arctic temperatures are not well constrained. We modify ocean-to-atmosphere heat fluxes in the North Pacific and North Atlantic in a climate model to determine the sensitivity of Arctic temperatures to zonal heterogeneities in northern hemisphere SST patterns. Both positive and negative ocean heat flux perturbations from the North Pacific result in greater global and Arctic surface air temperature anomalies than equivalent magnitude perturbations from the North Atlantic; a response we primarily attribute to greater moisture flux from the subpolar extratropics to Arctic. Enhanced poleward latent heat and moisture transport drive sea-ice retreat and low-cloud formation in the Arctic, amplifying Arctic surface warming through the ice-albedo feedback and infrared warming effect of low clouds. Our results imply that global climate sensitivity may be dependent on patterns of ocean heat flux in the northern hemisphere.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-018-05337-8","usgsCitation":"Praetorius, S.K., Rugenstein, M.A., Persad, G., and Caldeira, K., 2018, Global and Arctic climate sensitivity enhanced by changes in North Pacific heat flux: Nature Communications, v. 9, p. 1-12, https://doi.org/10.1038/s41467-018-05337-8.","productDescription":"Article number 3124; 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-087593","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":468498,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-018-05337-8","text":"Publisher Index Page"},{"id":356441,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-07","publicationStatus":"PW","scienceBaseUri":"5b98a289e4b0702d0e842f45","contributors":{"authors":[{"text":"Praetorius, Summer K. 0000-0003-2683-3652","orcid":"https://orcid.org/0000-0003-2683-3652","contributorId":206966,"corporation":false,"usgs":true,"family":"Praetorius","given":"Summer","email":"","middleInitial":"K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":742331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rugenstein, Maria A.","contributorId":206967,"corporation":false,"usgs":false,"family":"Rugenstein","given":"Maria","email":"","middleInitial":"A.","affiliations":[{"id":32389,"text":"Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland","active":true,"usgs":false}],"preferred":false,"id":742332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Persad, Geeta","contributorId":206968,"corporation":false,"usgs":false,"family":"Persad","given":"Geeta","email":"","affiliations":[{"id":30217,"text":"Carnegie Institution for Science","active":true,"usgs":false}],"preferred":false,"id":742333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caldeira, Ken","contributorId":206969,"corporation":false,"usgs":false,"family":"Caldeira","given":"Ken","email":"","affiliations":[{"id":30217,"text":"Carnegie Institution for Science","active":true,"usgs":false}],"preferred":false,"id":742334,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198637,"text":"70198637 - 2018 - Spatial relationships of levees and wetland systems within floodplains of the Wabash Basin, USA","interactions":[],"lastModifiedDate":"2018-08-14T13:40:53","indexId":"70198637","displayToPublicDate":"2018-08-14T13:40:50","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Spatial relationships of levees and wetland systems within floodplains of the Wabash Basin, USA","docAbstract":"Given the unique biogeochemical, physical, and hydrologic services provided by floodplain wetlands, proper management of river systems should include an understanding of how floodplain modifications influence wetland ecosystems. The construction of levees can reduce river–floodplain connectivity, yet it is unclear how levees affect wetlands within floodplains, let alone the cumulative impacts within an entire watershed. This paper explores spatial relationships between levee and floodplain wetland systems in the Wabash Basin, United States. We used a hydrogeomorphic floodplain delineation technique to map floodplain extents and identify wetlands that may be hydrologically connected to river networks. We then spatially examined the relationship between levee presence, wetland area, and other river network attributes within discrete subbasins. Our results show that cumulative wetland area is relatively constant in subbasins that contain levees, regardless of maximum stream order within the subbasin. In subbasins that do not contain levees, cumulative wetland area increases with maximum stream order. However, we found that wetland distributions around levees can be complex, and further studies on the influence of levees on wetland habitat may need to consider finer resolution spatial scales.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12652","usgsCitation":"Morrison, R.R., Bray, E., Nardi, F., Annis, A., and Dong, Q., 2018, Spatial relationships of levees and wetland systems within floodplains of the Wabash Basin, USA: Journal of the American Water Resources Association, v. 54, no. 4, p. 934-948, https://doi.org/10.1111/1752-1688.12652.","productDescription":"15 p.","startPage":"934","endPage":"948","ipdsId":"IP-089450","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":356438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Wabash Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89,\n 38\n ],\n [\n -85,\n 38\n ],\n [\n -85,\n 41.5\n ],\n [\n -89,\n 41.5\n ],\n [\n -89,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-25","publicationStatus":"PW","scienceBaseUri":"5b98a289e4b0702d0e842f47","contributors":{"authors":[{"text":"Morrison, Ryan R.","contributorId":198245,"corporation":false,"usgs":false,"family":"Morrison","given":"Ryan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":742443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bray, Erin N.","contributorId":92906,"corporation":false,"usgs":true,"family":"Bray","given":"Erin N.","affiliations":[],"preferred":false,"id":742444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nardi, Fernando","contributorId":207032,"corporation":false,"usgs":false,"family":"Nardi","given":"Fernando","email":"","affiliations":[],"preferred":false,"id":742445,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Annis, Antonio","contributorId":207033,"corporation":false,"usgs":false,"family":"Annis","given":"Antonio","email":"","affiliations":[],"preferred":false,"id":742446,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dong, Quan 0000-0003-0571-5884 qdong@usgs.gov","orcid":"https://orcid.org/0000-0003-0571-5884","contributorId":4506,"corporation":false,"usgs":true,"family":"Dong","given":"Quan","email":"qdong@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":742447,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198608,"text":"70198608 - 2018 - Probabilistic models of seafloor composition using multispectral acoustic backscatter: The benthic detectorists","interactions":[],"lastModifiedDate":"2018-08-14T09:48:19","indexId":"70198608","displayToPublicDate":"2018-08-13T16:06:34","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Probabilistic models of seafloor composition using multispectral acoustic backscatter: The benthic detectorists","docAbstract":"We describe and compare two probabilistic models\nfor task-specific seafloor characterization based on multispectral\nbackscatter. We examine whether generative or discriminative\napproaches to supervised seafloor characterization do better\nat harnessing the greatly increased information about seafloor\nsubstrate composition that is encoded in the backscattering\nresponse across multiple frequencies. A Gaussian mixture model\n(GMM) is proposed as a generative model, and a fully-connected\nconditional random field (CRF) is proposed as a discriminative\nmodel. Either model uses input data derived from monospectral\nor multispectral backscatter without modification. The CRF\napproach considers both the relative backscatter magnitudes of\ndifferent substrates as well as their relative proximity, and can\nbe optimized using parameters. The GMM model, in contrast,\nincludes no spatial information in its estimates, being based solely\non relative backscatter magnitudes. Both GMM and CRF modeling\napproaches perform better with multispectral backscatter\ncompared to monospectral, significantly outperforming all three\nmonospectral frequencies. With multispectral backscatter inputs,\nbased on average classification accuracies alone, there was little\nto choose between the two modeling approaches (classification\naccuracy of 81% and 83% for GMM and CRF models, respectively,\nevaluated using 50% of available bed observations to\ntrain and 50% to test the models). However, a CRF model that\nhas been optimized with respect to its tunable parameters tends\nto produce higher posterior probabilities (i.e. greater certainty)\nfor its classifications. Using monospectral backscatter inputs, the\nCRF model significantly outperformed the GMM model in terms\nof average classification accuracy. On balance, therefore, based\non the evidence presented here, the CRF is suggested to be\nthe superior approach for task-specific seafloor classification.\nAlthough further work using additional data is required to\nfurther examine this conclusion, the work presented here will\nguide and focus subsequent research efforts as more areas of\nthe seafloor are mapped with the new technology. In order to\nfacilitate these efforts, the algorithms presented here are encoded\nin a freely available python toolbox for Probabilistic acoustic\nSediment Mapping, called PriSM , that can be used for both\nmonospectral and multispectral backscatter. Finally, we show that\napplication of the CRF model to the outputs of a geoacoustical\nmodel of seafloor scattering results in realistic substrate classification\nboundaries. This hybrid CRF and physics-based approach\ncan predict the physical properties of the seafloor at a finer spatial\nresolution than is possible using the geoacoustical model alone.","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkSubtype":{"id":19,"text":"Conference Paper"},"conferenceTitle":"GeoHab 2018","conferenceDate":"May 8, 2018","conferenceLocation":"Santa Barbara, California","language":"English","publisher":"GeoHab Conference Proceedings","usgsCitation":"Buscombe, D.D., Grams, P.E., and Kaplinski, M., 2018, Probabilistic models of seafloor composition using multispectral acoustic backscatter: The benthic detectorists, GeoHab 2018, Santa Barbara, California, May 8, 2018, 30 p.","productDescription":"30 p.","ipdsId":"IP-097322","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":356427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":356420,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.r2sonic.com/geohab2018-success/"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a289e4b0702d0e842f4b","contributors":{"authors":[{"text":"Buscombe, Daniel D. 0000-0001-6217-5584","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":198817,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","middleInitial":"D.","affiliations":[],"preferred":false,"id":742135,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":742136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaplinski, Matthew","contributorId":198818,"corporation":false,"usgs":false,"family":"Kaplinski","given":"Matthew","affiliations":[],"preferred":false,"id":742137,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197949,"text":"ofr20181104 - 2018 - Promoting synergy in the innovative use of environmental data—Workshop summary","interactions":[],"lastModifiedDate":"2019-06-03T11:13:38","indexId":"ofr20181104","displayToPublicDate":"2018-08-13T14:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1104","displayTitle":"Promoting synergy in the innovative use of environmentalFrom December 2 to 4, 2015, NatureServe and the U.S. Geological Survey organized and hosted a biodiversity and ecological informatics workshop at the U.S. Department of the Interior in Washington, D.C. The workshop objective was to identify user-driven future directions and areas of collaboration in advanced applications of environmental data applied to forecasting and decision making for the sustainability of biodiversity and ecosystem services. Substantial effort to recruit attendees from diverse Federal, State, and private sector organizations successfully attracted participants from 20 Federal agencies and 48 different institutions in the academic, nonprofit, State government, and commercial sectors; the total number of attendees ranged from 100 to 144 during the 3-day workshop. The first one-half of the workshop was divided into 7 plenary sessions and 3 sets of lightning talk sessions organized by sector, providing 48 oral and visual plenary presentations that shared diverse perspectives on biodiversity and ecological informatics, including original biospatial analyses from 6 graduate student map contest winners. The second one-half of the workshop focused on 10 breakout sessions with participant-driven themes from the environmental data sphere and concluded with an address by the Director of the U.S. Fish and Wildlife Service. The workshop was structured to encourage interactivity. About 80–90 percent of attendees provided direct feedback using clicker devices for specific questions related to biodiversity and ecological data uses and needs, and 10 breakout session leaders shared the highlights of their group discussions during the final workshop plenary sessions. Participants were encouraged to use the Twitter hashtag #ShareUrData. Over lunch on day 2 there were 20 simultaneous presentations of tools and apps during a special “Tools Café” session.
The 10 participant-defined breakout session topics are listed below:
Numerous common themes that emerged from the workshop include the following:
Director, Core Science Analytics Synthesis and Libraries Program
U.S. Geological Survey
W 6th Ave Kipling Street
Lakewood, CO 80225
Land management practices often directly alter vegetation structure and composition, but the degree to which ecological processes such as herbivory interact with management to influence biodiversity is less well understood. We hypothesized that large herbivores compound the effects of intensive forest management on early seral plant communities and plantation establishment (i.e., tree survival and growth), and the degree of such effects is dependent on the intensity of management practices. We established 225 m2 wild‐ungulate (deer and elk) exclosures, nested within a manipulated gradient of management intensity (no‐herbicide Control, Light herbicide, Moderate herbicide and Intensive herbicide treatments), replicated at the scale of whole harvest units (10‐19 ha). Vegetation structure, composition and crop‐tree responses to herbivory varied across the gradient of herbicide application during the first two years of stand establishment, with herbivory effects most evident at intermediate herbicide treatments. In the Moderate herbicide treatment – which approximates treatments applied to > 2.5 million hectares in Pacific Northwest U.S.A. – foraging by deer and elk resulted in simplified, low‐cover plant communities more closely resembling the Intensive herbicide treatment. Herbivory further suppressed the growth of competing vegetation in the Light herbicide treatment, improving crop‐tree survival, and providing early evidence of an ecosystem service. By changing community composition and vegetation structure, intensive forest management alters foraging selectivity and subsequent plant‐herbivore interactions; initial shifts in early seral communities are likely to influence understory plant communities and tree growth in later stages of forest development.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1777","usgsCitation":"Stokely, T.D., Verschuyl, J., Hagar, J., and Betts, M.G., 2018, Herbicides and herbivory interact to drive plant community and crop‐tree establishment: Ecological Applications, v. 28, no. 8, p. 2011-2023, https://doi.org/10.1002/eap.1777.","productDescription":"13 p.","startPage":"2011","endPage":"2023","ipdsId":"IP-073976","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":468501,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.1777","text":"Publisher Index Page"},{"id":437787,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H1307W","text":"USGS data release","linkHelpText":"Forest management and cervid herbivory data from Western Oregon, USA, 2012"},{"id":356410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.09057617187499,\n 44.750634493861064\n ],\n [\n -123.21441650390625,\n 44.750634493861064\n ],\n [\n -123.21441650390625,\n 45.673563046842524\n ],\n [\n -124.09057617187499,\n 45.673563046842524\n ],\n [\n -124.09057617187499,\n 44.750634493861064\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"8","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-24","publicationStatus":"PW","scienceBaseUri":"5b98a289e4b0702d0e842f4f","contributors":{"authors":[{"text":"Stokely, Thomas D.","contributorId":206929,"corporation":false,"usgs":false,"family":"Stokely","given":"Thomas","email":"","middleInitial":"D.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":742164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verschuyl, Jake","contributorId":206930,"corporation":false,"usgs":false,"family":"Verschuyl","given":"Jake","affiliations":[{"id":37426,"text":"National Council for Air & Stream Improvement, Inc.","active":true,"usgs":false}],"preferred":false,"id":742165,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagar, Joan 0000-0002-3044-6607 joan_hagar@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-6607","contributorId":3369,"corporation":false,"usgs":true,"family":"Hagar","given":"Joan","email":"joan_hagar@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":742163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Betts, Matthew G.","contributorId":206931,"corporation":false,"usgs":false,"family":"Betts","given":"Matthew","email":"","middleInitial":"G.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":742166,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228306,"text":"70228306 - 2018 - An interferometric synthetic aperture radar (InSAR) habitat suitability model to identify overwinter conditions for coregonine whitefishes in Arctic lagoons","interactions":[],"lastModifiedDate":"2022-02-08T17:36:12.932625","indexId":"70228306","displayToPublicDate":"2018-08-12T11:29:59","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"An interferometric synthetic aperture radar (InSAR) habitat suitability model to identify overwinter conditions for coregonine whitefishes in Arctic lagoons","docAbstract":"Lagoons provide critical habitats for many fishes, including coregonine whitefishes, which are a mainstay in many subsistence fisheries of rural communities in Arctic Alaska. Despite their importance, little is known about the overwintering habits of whitefishes in Arctic Alaska due to the challenges associated with sampling during winter. We developed a habitat suitability (HS) model to understand the potential range of physical conditions that whitefishes experience during the Arctic winter, using three indicator lagoons that represent a range of environmental characteristics. The HS model was built using a three-step approach. First, remote sensing that uses interferometric synthetic aperture radar (InSAR) identified areas of floating and bottomfast ice. Second, through in-field ground-truthing, we confirmed the presence and quality of liquid water (water depth, temperature, and dissolved oxygen) beneath the ice cover. Third, we assessed the suitability of that liquid water as habitat for whitefishes based on published literature and expert interpretation of water quality parameters. InSAR determined that 0, 65.4, and 88.2% of the three lagoons were composed of floating ice corresponding with areas of liquid water beneath a layer of ice. The HS model indicated that all three lagoons had reduced suitability as whitefish habitat in winter than in summer due to the loss of habitat because of the presence of bottomfast ice and a reduction in the quality of liquid water due to cold temperatures, high salinities, and low dissolved oxygen levels. However, only the shallowest lagoon had lethal conditions and zero suitability as whitefish habitat. The methods outlined here provide a simple, cost-effective method to identify habitats that consistently provide critical winter habitat and integrate remote sensing in a HS model framework.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10111","usgsCitation":"Tibbles, M., Falke, J.A., Mahoney, A.R., Robards, M., and Seitz, A.C., 2018, An interferometric synthetic aperture radar (InSAR) habitat suitability model to identify overwinter conditions for coregonine whitefishes in Arctic lagoons: Transactions of the American Fisheries Society, v. 147, no. 6, p. 1167-1178, https://doi.org/10.1002/tafs.10111.","productDescription":"12 p.","startPage":"1167","endPage":"1178","ipdsId":"IP-097751","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468503,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10686345","text":"External Repository"},{"id":395635,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Cape Krusenstern National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.6416015625,\n 67.08455048507471\n ],\n [\n -162.960205078125,\n 67.26779766322973\n ],\n [\n -163.19091796875,\n 67.4285812540874\n ],\n [\n -163.135986328125,\n 67.80924450600011\n ],\n [\n -164.05883789062497,\n 67.80509469602548\n ],\n [\n -164.278564453125,\n 67.64267630796034\n ],\n [\n -163.916015625,\n 67.09738040223989\n ],\n [\n -163.2568359375,\n 66.99884379185184\n ],\n [\n -162.6416015625,\n 67.08455048507471\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"147","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Tibbles, Marguerite","contributorId":275096,"corporation":false,"usgs":false,"family":"Tibbles","given":"Marguerite","email":"","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":833643,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":833644,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mahoney, Andrew R.","contributorId":275097,"corporation":false,"usgs":false,"family":"Mahoney","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":833645,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robards, Martin D.","contributorId":275099,"corporation":false,"usgs":false,"family":"Robards","given":"Martin D.","affiliations":[{"id":56701,"text":"wsc","active":true,"usgs":false}],"preferred":false,"id":833646,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seitz, Andrew C.","contributorId":275102,"corporation":false,"usgs":false,"family":"Seitz","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":833647,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223132,"text":"70223132 - 2018 - An evaluation of three fish surveys in the San Francisco Estuary, 1995–2015","interactions":[],"lastModifiedDate":"2021-08-12T13:11:35.596364","indexId":"70223132","displayToPublicDate":"2018-08-12T08:09:14","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"An evaluation of three fish surveys in the San Francisco Estuary, 1995–2015","docAbstract":"Resource managers rely on long-term monitoring surveys conducted in the San Francisco Estuary to evaluate the status and trends of resident fish populations in this important region. These surveys are potentially confounded because of the incomplete detection of individuals and species, the magnitude of which is often related to the same factors that affect fish populations. We used multistate occupancy estimators to evaluate the distribution, abundance, and detection probability of four fish species collected during 1995–2015 with three long-term surveys. Detection probabilities varied positively with fish abundance and negatively with Secchi depth. Detection varied among species and was greatest for the 20-mm Survey and least for the midwater trawl used for the midwater trawl used in the San Francisco Bay Study. Incomplete detection resulted in underestimates of occupancy and abundance across species and surveys and were greatest for the Bay Study. However, trends in occupancy and abundance of the study period appeared to be unbiased. Fish occupancy and abundance were generally related to salinity or specific conductance, day-of-the year, and water temperature, but the nature of the relations varied among surveys and species. There also was strong spatial and temporal dependence in species-specific occupancy and abundance that changed through time and were unrelated to the covariates considered. Our results suggest that managers consider incorporating methods for estimating detection and adjusting data to ensure data quality. Additionally, the strong spatio-temporal patterns in the monitoring data suggest that existing protocols may need to be modified to ensure that data and inferences reflect system-wide changes rather than changes at a specific set of non-randomly selected locations.
","language":"English","publisher":"University of California","doi":"10.15447/sfews.2018v16iss4art2","usgsCitation":"Peterson, J., and Barajas, M.F., 2018, An evaluation of three fish surveys in the San Francisco Estuary, 1995–2015: San Francisco Estuary and Watershed Science, v. 16, no. 4, 2, 28 p., https://doi.org/10.15447/sfews.2018v16iss4art2.","productDescription":"2, 28 p.","ipdsId":"IP-100488","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468504,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2018v16iss4art2","text":"Publisher Index Page"},{"id":387901,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.9644775390625,\n 37.36142550190517\n ],\n [\n -120.82214355468749,\n 37.36142550190517\n ],\n [\n -120.82214355468749,\n 38.42777351132905\n ],\n [\n -122.9644775390625,\n 38.42777351132905\n ],\n [\n -122.9644775390625,\n 37.36142550190517\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"4","noUsgsAuthors":false,"publicationDate":"2018-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":821080,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barajas, Miguel F.","contributorId":264181,"corporation":false,"usgs":false,"family":"Barajas","given":"Miguel","email":"","middleInitial":"F.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":821081,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70256212,"text":"70256212 - 2018 - Near-solidus melts of MORB + 4 wt% H2O at 0.8 – 2.8 GPa applied to issues of subduction magmatism and continent formation","interactions":[],"lastModifiedDate":"2024-07-29T15:44:51.510322","indexId":"70256212","displayToPublicDate":"2018-08-11T10:38:28","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1336,"text":"Contributions to Mineralogy and Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Near-solidus melts of MORB + 4 wt% H2O at 0.8 – 2.8 GPa applied to issues of subduction magmatism and continent formation","docAbstract":"Experiments on MORB + 4 wt% H2O at 0.8–2.8 GPa and 700–950 °C (Liu in High pressure phase equilibria involving the amphibolite–eclogite transformation. PhD dissertation, Stanford University, Stanford, California, 1997; Liu et al. in Earth Planet Sci Lett 143:161–171, 1996) were reexamined for their major and trace element melt compositions and melting relations. Degree of melting diminishes at greater pressures, with corresponding evolution of melt from andesitic at the lowest pressures and hottest temperatures to high-silica rhyolitic at the greatest pressure and coolest temperature. Quartz contributes greatly to the production of near-solidus melts of basaltic eclogite, with the result that melt productivity falls markedly following quartz exhaustion. This limits the extent of melting attainable in the basaltic eclogite portions of sub-arc subducting plates to no more than ~ 2 × the modal wt% quartz in the mafic eclogite protolith. Synthesized residual mineral assemblages lack an epidote-series mineral at temperatures > 750 °C, and as a result, melts from the rutile eclogite and rutile-amphibole eclogite facies have elevated concentrations of light rare earth elements, U, Th, have elevated Ba, K, and Sr, high Sr/Y, and are strongly depleted in Nb, Y, and the heavy rare earth elements. Models of eclogite partial melt reacting with peridotite of the mantle wedge reproduce major and trace element characteristics of parental arc magmas so long as the proportions of infiltrating melt to peridotite are relatively high, consistent with channelized ascent. Melt mass is estimated to increase roughly three- to ten-fold, consistent with H2O concentrations of 3–7 wt% in the magmas produced by reaction. Partial melts of subducting basaltic eclogite are predicted to have positive Sr concentration anomalies, relative to Ce and Nd, that persist through melt-peridotite reactions. Primitive arc magmas commonly have positive Sr anomalies, whereas such anomalies are smaller in estimates of the bulk continental crust. Overall, Sr anomalies diminish passing from primitive to more evolved arc volcanic rocks, consistent with extensive mineral-melt differentiation (crystallization, partial remelting) involving plagioclase. On the order of 50 wt% differentiation would be necessary to eliminate Sr positive anomalies, based on geochemical variations in the Cascade and western Aleutian magmatic arcs. Loss to the mantle of cumulates and restites with high Sr anomalies, in abundances broadly equal to the mass of the preserved crust, would be required to form the continents via processes similar to present-day subduction magmatism.
","language":"English","publisher":"Springer","doi":"10.1007/s00410-018-1494-x","usgsCitation":"Sisson, T.W., and Kelemen, P.B., 2018, Near-solidus melts of MORB + 4 wt% H2O at 0.8 – 2.8 GPa applied to issues of subduction magmatism and continent formation: Contributions to Mineralogy and Petrology, v. 173, 70, 23 p., https://doi.org/10.1007/s00410-018-1494-x.","productDescription":"70, 23 p.","ipdsId":"IP-099283","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":431568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"173","noUsgsAuthors":false,"publicationDate":"2018-08-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Sisson, Thomas W. 0000-0003-3380-6425 tsisson@usgs.gov","orcid":"https://orcid.org/0000-0003-3380-6425","contributorId":2341,"corporation":false,"usgs":true,"family":"Sisson","given":"Thomas","email":"tsisson@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":907119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelemen, Peter B. 0000-0003-4757-0855","orcid":"https://orcid.org/0000-0003-4757-0855","contributorId":340411,"corporation":false,"usgs":false,"family":"Kelemen","given":"Peter","email":"","middleInitial":"B.","affiliations":[{"id":40291,"text":"Lamont-Doherty Earth Observatory of Columbia University","active":true,"usgs":false}],"preferred":false,"id":907120,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70202566,"text":"70202566 - 2018 - Millennial soil retention of terrestrial organic matter deposited in the Bengal Fan","interactions":[],"lastModifiedDate":"2019-03-11T14:34:36","indexId":"70202566","displayToPublicDate":"2018-08-10T14:33:42","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Millennial soil retention of terrestrial organic matter deposited in the Bengal Fan","docAbstract":"The abundance of organic carbon (OC) in vegetation and soils (~2,600 PgC) compared to carbon in the atmosphere (~830 PgC) highlights the importance of terrestrial OC in global carbon budgets. The residence time of OC in continental reservoirs, which sets the rates of carbon exchange between land and atmosphere, represents a key uncertainty in global carbon cycle dynamics. Retention of terrestrial OC can also distort bulk OC- and biomarker-based paleorecords, yet continental storage timescales remain poorly quantified. Using “bomb” radiocarbon (14C) from thermonuclear weapons testing as a tracer, we model leaf-wax fatty acid and bulk OC 14C signatures in a river-proximal marine sediment core from the Bay of Bengal in order to constrain OC storage timescales within the Ganges-Brahmaputra (G-B) watershed. Our model shows that 79-83% of the leaf-waxes in this core were stored in continental reservoirs for an average of 1,000-1,200 calendar years, while the remainder was stored for an average of 15 years. This age structure distorts high-resolution organic paleorecords across geologically rapid events, highlighting that compound-specific proxy approaches must consider storage timescales. Furthermore, these results show that future environmental change could destabilize large stores of old - yet reactive - OC currently stored in tropical basins.","language":"English","publisher":"SpringerNature","doi":"10.1038/s41598-018-30091-8","usgsCitation":"French, K.L., Hein, C., Haghipour, N., Wacker, L., Kudrass, H., Eglinton, T., and Galy, V., 2018, Millennial soil retention of terrestrial organic matter deposited in the Bengal Fan: Scientific Reports, v. 8, p. 1-8, https://doi.org/10.1038/s41598-018-30091-8.","productDescription":"Article 11997, 8 p.","startPage":"1","endPage":"8","ipdsId":"IP-090571","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":468505,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-30091-8","text":"Publisher Index Page"},{"id":361979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Bay of Bengal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 88.857421875,\n 20.612219573881042\n ],\n [\n 91.97753906249999,\n 20.612219573881042\n ],\n [\n 91.97753906249999,\n 23.543845136505844\n ],\n [\n 88.857421875,\n 23.543845136505844\n ],\n [\n 88.857421875,\n 20.612219573881042\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-10","publicationStatus":"PW","contributors":{"authors":[{"text":"French, Katherine L. 0000-0002-0153-8035","orcid":"https://orcid.org/0000-0002-0153-8035","contributorId":205462,"corporation":false,"usgs":true,"family":"French","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":false,"id":759122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hein, Christopher","contributorId":214093,"corporation":false,"usgs":false,"family":"Hein","given":"Christopher","affiliations":[{"id":18865,"text":"VIMS","active":true,"usgs":false}],"preferred":false,"id":759123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haghipour, Negar","contributorId":214094,"corporation":false,"usgs":false,"family":"Haghipour","given":"Negar","email":"","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":759124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wacker, Lukas","contributorId":214095,"corporation":false,"usgs":false,"family":"Wacker","given":"Lukas","email":"","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":759125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kudrass, Hermann","contributorId":214096,"corporation":false,"usgs":false,"family":"Kudrass","given":"Hermann","email":"","affiliations":[{"id":38980,"text":"MARUM Bremen","active":true,"usgs":false}],"preferred":false,"id":759126,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eglinton, Timothy","contributorId":214097,"corporation":false,"usgs":false,"family":"Eglinton","given":"Timothy","email":"","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":759127,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Galy, Valier","contributorId":150226,"corporation":false,"usgs":false,"family":"Galy","given":"Valier","email":"","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":759128,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70198576,"text":"70198576 - 2018 - Effect of spatial and temporal scale on simulated groundwater recharge investigations","interactions":[],"lastModifiedDate":"2018-08-10T11:25:15","indexId":"70198576","displayToPublicDate":"2018-08-10T11:21:51","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"Effect of spatial and temporal scale on simulated groundwater recharge investigations","docAbstract":"Hydrologic model input datasets such as climate, land use, elevation, soil, and geology information are available in a range of scales for use in water resources investigations. Smaller spatial and temporal scale input data allow groundwater recharge models to simulate more physically realistic processes and presumably result in more accurate estimates of groundwater recharge. Projected climate data are, therefore, often downscaled to smaller spatial and temporal scales for use in these models. It is unknown, however, if increasingly smaller-scale climate data produce substantially different simulated recharge results, either in magnitude or trend. Also, even if simulated recharge results are different at a higher space and time resolution, simulation at coarser resolution might be adequate to provide recharge information at decision scales (e.g., meeting Colorado River compact requirements on a ten-year moving average basis). Historical climate datasets at three spatial (∼800 m, ∼4 km, and ∼12 km) and two temporal (daily and monthly) scales were used in a Soil Water Balance (SWB) model of the upper Colorado River basin (UCRB) to simulate groundwater recharge over the water-year 1982–2014 time period. The magnitude of annual and moving ten-year annual average recharge results for daily climate data were within 5% and 7% of ∼4 km results for ∼800 m and ∼12 km climate data, respectively, with deviations from 1982 to 2014 means within 1% and 3% (median), respectively. Comparison of simulated recharge results using the coarsest spatial and temporal climate data with results from the finest scale data indicated similar small differences over ten-year moving annual averages, over water years, and during high recharge months. While differences in simulated groundwater recharge magnitude, which may be important for groundwater-flow simulations, were substantial during some seasonal comparisons, trends in recharge were almost identical across scales, leading to similar conclusions about change from “normal”. Considering the uncertainty inherent in projected climate data, coarser spatial and longer temporal scale input data may be sufficient for water resources managers who need to understand changes in trends in groundwater recharge over water-year or longer time periods.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2018.07.014","usgsCitation":"Tillman, F.D., Pruitt, T., and Gangopadhyay, S., 2018, Effect of spatial and temporal scale on simulated groundwater recharge investigations: Advances in Water Resources, v. 119, p. 257-270, https://doi.org/10.1016/j.advwatres.2018.07.014.","productDescription":"14 p.","startPage":"257","endPage":"270","ipdsId":"IP-087425","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":356384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.77490234375,\n 36.66841891894786\n ],\n [\n -105.62255859375,\n 36.66841891894786\n ],\n [\n -105.62255859375,\n 43.35713822211053\n ],\n [\n -111.77490234375,\n 43.35713822211053\n ],\n [\n -111.77490234375,\n 36.66841891894786\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"119","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc3c5e4b0f5d57878e8db","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":741994,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pruitt, Tom 0000-0002-3543-1324","orcid":"https://orcid.org/0000-0002-3543-1324","contributorId":173440,"corporation":false,"usgs":false,"family":"Pruitt","given":"Tom","email":"","affiliations":[{"id":27228,"text":"Reclamation","active":true,"usgs":false}],"preferred":false,"id":741996,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":741995,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224920,"text":"70224920 - 2018 - Implications of spatially variable costs and habitat conversion risk in landscape-scale conservation planning","interactions":[],"lastModifiedDate":"2021-10-05T12:39:18.922599","indexId":"70224920","displayToPublicDate":"2018-08-10T07:36:40","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Implications of spatially variable costs and habitat conversion risk in landscape-scale conservation planning","docAbstract":"“Strategic habitat conservation” refers to a process used by the U.S. Fish and Wildlife Service to develop cost-efficient strategies for conserving wildlife populations and their habitats. Strategic habitat conservation focuses on resolving uncertainties surrounding habitat conservation to meet specific wildlife population objectives (i.e., targets) and developing tools to guide where conservation actions should be focused on the landscape. Although there are examples of using optimization models to highlight where conservation should be delivered, such methods often do not explicitly account for spatial variation in the costs of conservation actions. Furthermore, many planning approaches assume that habitat protection is a preferred option, but they do not assess its value relative to other actions, such as restoration. We developed a case study to assess the implications of accounting for and ignoring spatial variation in conservation costs in optimizing conservation targets. We included assumptions about habitat loss to determine the extent to which protection or restoration would be necessary to meet an established population target. Our case study focused on optimal placement of grassland protection or restoration actions to influence bobolink Dolichonyx oryzivorus populations in the tallgrass prairie ecoregion of the north central United States. Our results show that not accounting for spatially variable costs doubled or tripled the cost of meeting the population target. Furthermore, our results suggest that one should not assume that protecting existing habitat is always a preferred option. Rather, our results show that the balance between protection and restoration can be influenced by a combination of desired targets, assumptions about habitat loss, and the relative cost of the two actions. Our analysis also points out how difficult it may be to reach targets, given the expense to meet them. We suggest that a full accounting of expected costs and benefits will help to guide development of viable management actions and meaningful conservation plans.
New mapping, geochemistry, and argon geochronology illuminate a brief, remarkably silicic episode set in a mafic segment of the Cascade arc. Middle Sister was constructed during a 35-k.y. episode in the late Pleistocene from mafic, intermediate, and silicic eruptions adjacent to the primarily rhyolitic South Sister. Eruptions in the Three Sisters volcanic cluster prior to 50 ka were exclusively mafic (<57 wt% SiO2), and several basaltic andesite lava flows can be traced to Middle Sister or a predecessor volcano (prior to 150 ka). Lava flows erupted 50–37 ka at Middle Sister and on its periphery were chemically diverse, with abundant basaltic andesite, a high-silica rhyolite flow, and an andesite produced from mixing of a rhyolite and mafic magma. Abundant rhyolite and rhyodacite erupted in this interval also at South Sister. Eruptive activity paused at Middle Sister 37–27 ka but continued at South Sister with large volumes of dacite and andesite lavas. Middle Sister erupted mafic, intermediate, and silicic lava flows 27–15 ka and then ceased to erupt. Calculated eruptive rates for the entire Three Sisters volcanic cluster quadrupled from ∼0.2 to ∼0.8 km3/k.y. between 50 and 15 ka, largely owing to the eruptions focused at Middle and South Sisters, and the cluster has now returned to its modest eruptive output, mainly away from the stratovolcanoes. Time–volume results for the volcanic cluster are compared to studies of other well-mapped, well-dated stratovolcanoes. Nearly all centers record similar eruptive-volume behavior with long histories of relatively constant output punctuated by short episodes of voluminous eruptions. In addition to the Three Sisters, two of these centers (Mt. Mazama, Crater Lake, Oregon, and Puyehue/Cordon Caule in the southern Andes) record significant compositional changes associated with the voluminous eruptive episodes.
","language":"English","publisher":"GeoScienceWorld","doi":"10.1130/GES01638.1","usgsCitation":"Calvert, A.T., Fierstein, J., and Hildreth, W., 2018, Eruptive history of Middle Sister, Oregon Cascades-Product of a late Pleistocene eruptive episode: Geosphere, v. 14, no. 5, p. 2118-2139, https://doi.org/10.1130/GES01638.1.","productDescription":"22 p.","startPage":"2118","endPage":"2139","ipdsId":"IP-093172","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":482052,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01638.1","text":"Publisher Index Page"},{"id":480731,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Middle Sister","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.80643688201101,\n 44.160958063912176\n ],\n [\n -121.80643688201101,\n 44.1339239217734\n ],\n [\n -121.75899090216782,\n 44.1339239217734\n ],\n [\n -121.75899090216782,\n 44.160958063912176\n ],\n [\n -121.80643688201101,\n 44.160958063912176\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"5","noUsgsAuthors":false,"publicationDate":"2018-08-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":924401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fierstein, Judith E. 0000-0001-8024-1426","orcid":"https://orcid.org/0000-0001-8024-1426","contributorId":329988,"corporation":false,"usgs":true,"family":"Fierstein","given":"Judith E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":924402,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hildreth, Wes 0000-0002-7925-4251 hildreth@usgs.gov","orcid":"https://orcid.org/0000-0002-7925-4251","contributorId":2221,"corporation":false,"usgs":true,"family":"Hildreth","given":"Wes","email":"hildreth@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":924403,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199356,"text":"70199356 - 2018 - Slab2, a comprehensive subduction zone geometry model","interactions":[],"lastModifiedDate":"2018-10-04T13:15:13","indexId":"70199356","displayToPublicDate":"2018-08-09T10:57:33","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Slab2, a comprehensive subduction zone geometry model","docAbstract":"Subduction zones are home to the most seismically active faults on the planet. The shallow megathrust interfaces of subduction zones host our largest earthquakes and are likely the only faults capable of magnitude 9+ ruptures. Despite these facts, our knowledge of subduction zone geometry—which likely plays a key role in determining the spatial extent and ultimately the size of subduction zone earthquakes—is incomplete. We calculated the three-dimensional geometries of all seismically active global subduction zones. The resulting model, called Slab2, provides a uniform geometrical analysis of all currently subducting slabs.
","language":"English","publisher":"AAAS","doi":"10.1126/science.aat4723","usgsCitation":"Hayes, G.P., Moore, G., Portner, D.E., Hearne, M., Flamme, H.E., Furtney, M., and Smoczyk, G.M., 2018, Slab2, a comprehensive subduction zone geometry model: Science, v. 362, p. 58-61, https://doi.org/10.1126/science.aat4723.","productDescription":"eaat4723; 4 p.","startPage":"58","endPage":"61","ipdsId":"IP-096028","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":357326,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"362","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02fc0e4b0fc368eb5396f","contributors":{"authors":[{"text":"Hayes, Gavin P. 0000-0003-3323-0112 ghayes@usgs.gov","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":147556,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin","email":"ghayes@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":745017,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Ginevra 0000-0001-9005-7155 ginevramoore@usgs.gov","orcid":"https://orcid.org/0000-0001-9005-7155","contributorId":196528,"corporation":false,"usgs":true,"family":"Moore","given":"Ginevra","email":"ginevramoore@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":745018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Portner, Daniel E. 0000-0002-3478-6203","orcid":"https://orcid.org/0000-0002-3478-6203","contributorId":207877,"corporation":false,"usgs":false,"family":"Portner","given":"Daniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":745019,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hearne, Mike 0000-0002-8225-2396 mhearne@usgs.gov","orcid":"https://orcid.org/0000-0002-8225-2396","contributorId":4659,"corporation":false,"usgs":true,"family":"Hearne","given":"Mike","email":"mhearne@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":745020,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flamme, Hanna E. hflamme@usgs.gov","contributorId":176707,"corporation":false,"usgs":true,"family":"Flamme","given":"Hanna","email":"hflamme@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":false,"id":745021,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Furtney, Maria","contributorId":207876,"corporation":false,"usgs":false,"family":"Furtney","given":"Maria","email":"","affiliations":[],"preferred":false,"id":745022,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smoczyk, Gregory M. 0000-0002-6591-4060 gsmoczyk@usgs.gov","orcid":"https://orcid.org/0000-0002-6591-4060","contributorId":5239,"corporation":false,"usgs":true,"family":"Smoczyk","given":"Gregory","email":"gsmoczyk@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":745023,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70195604,"text":"sir20185022 - 2018 - Manure and fertilizer inputs to land in the Chesapeake Bay watershed, 1950–2012","interactions":[],"lastModifiedDate":"2018-08-24T07:48:30","indexId":"sir20185022","displayToPublicDate":"2018-08-09T08:45:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5022","title":"Manure and fertilizer inputs to land in the Chesapeake Bay watershed, 1950–2012","docAbstract":"Understanding changing nutrient concentrations in surface waters requires quantitative information on changing nutrient sources in contributing watersheds. For example, the proportion of nutrient inputs reaching streams and rivers is directly affected by when and where those nutrients enter the landscape. The goal of this report is to contribute to the U.S. Geological Survey’s efforts to describe spatial and temporal patterns in nutrient inputs to the landscape in the Chesapeake Bay watershed, thereby informing efforts to understand changes in riverine and estuarine conditions. The magnitude, spatial variability, and changes over time in nutrient inputs from manure and fertilizer were evaluated in the context of changes in land use and agricultural practices from 1950 through 2012 at three spatial scales: the entire Chesapeake Bay watershed, the 53 8-digit hydrologic units (HUC8s) that are contained within the watershed, and a set of 7 regions that were determined by aggregating geographically similar HUC8s. The expected effect of agricultural best management practices (BMPs) on agricultural nutrient inputs from 1985 through 2012 was also investigated. Nitrogen (N) and phosphorus (P) inputs from manure increased gradually over time at the scale of the entire watershed. Fertilizer-N inputs showed steeper increases, with greater inter-annual fluctuations. Fertilizer-P inputs were less variable, increasing moderately from 1950 through the mid-1970s, and declining thereafter. Nutrient inputs and farming practices varied geographically within the watershed, with implications for the potential impact of these inputs on downstream water quality and ecosystem health. Both temporal and spatial patterns in the intensity of agricultural nutrient inputs were consistent with the magnitude and concentration of livestock and poultry populations and the intensity of row crop agriculture. Reported implementation of the animal and land-use change BMPs that were evaluated were expected to have little effect on agricultural N inputs. Animal BMPs were expected to have a more measurable impact on manure-P inputs, particularly in areas with large poultry populations. Understanding these patterns is important for explaining the changes that have been observed in nutrient loads to the rivers and streams of the Chesapeake Bay watershed, and their impacts on the water quality and ecosystem health of Chesapeake Bay itself.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185022","collaboration":" ","usgsCitation":"Keisman, J.L.D., Devereux, O.H., LaMotte, A.E., Sekellick, A.J., and Blomquist, J.D., 2018, Manure and fertilizer inputs to land in the Chesapeake Bay watershed, 1950–2012: U.S. Geological Survey Scientific Investigations Report 2018–5022, 37 p., https://doi.org/10.3133/sir20185022.","productDescription":"vii, 37 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-081775","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":356307,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5022//sir20185022.pdf","text":"Report","size":"8.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5022"},{"id":356306,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5022/coverthb.jpg"}],"country":"United 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U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
Rapid population growth and declining annual recharge to aquifers in the upper Santa Cruz Basin area of southern Arizona, have increased the demand for additional groundwater resources. This demand is predicted to escalate in the future because of higher temperatures, longer droughts, less aquifer recharge, and decreased river and stream base flow. We conducted geologic studies to help evaluate and better understand groundwater resources in the basin. Results of these studies are presented in this report, which summarizes the basin geologic framework and hydrogeology, and presents a threedimensional (3D) hydrogeologic model for the Rio Rico and Nogales 7.5′ quadrangles. Three major hydrogeologic units are displayed in the 3D model; a lower basement confining unit, consisting of Jurassic, Cretaceous, and Tertiary (Paleocene and Oligocene) rocks; a middle unit composed entirely of the Miocene Nogales Formation; and an upper unit consisting of late Miocene to Holocene surficial deposits. The Nogales Formation and the late Miocene to Holocene sediments are the main aquifers in the upper Santa Cruz Basin. The 3D model integrates the hydrogeologic units and faults to define the geometry, structure, and thickness of the aquifer system that provides water to Nogales and surrounding communities of southernmost Arizona. The report includes an EarthVision 3D Viewer, consisting of software enabling the user to view data interactively in 3D space to help explain the internal complexities of the basin geometry, structure, stratigraphy, and hydrology. The 3D model is a synthesis of geologic data from geologic maps, cross sections, and lithologic descriptions and interpretations; and geophysical data including gravity, magnetic data, and airborne electromagnetic data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185062","usgsCitation":"Page, W.R., Bultman, M.W., VanSistine, D.P., Menges, C.M., Gray, Floyd, and Pantea, M.P., 2018, Geologic framework and hydrogeology of the Rio Rico and Nogales 7.5’ quadrangles, upper Santa Cruz Basin, Arizona, with three-dimensional hydrogeologic model: U.S. Geological Survey Scientific Investigations Report 2018–5062, 34 p., https://doi.org/10.3133/sir20185062.","productDescription":"Report: vi, 34 p.; Data release","onlineOnly":"Y","ipdsId":"IP-085666","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":356167,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5062/coverthb.jpg"},{"id":356184,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QJ7GHT","text":"USGS data release","linkHelpText":"Data Release for Geologic Framework and Hydrogeology of the Rico Rico and Nogales 7.5' quadrangles, Upper Santa Cruz basin, Arizona, with 3-Dimensional hydrogeologic model"},{"id":356168,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5062/sir20185062.pdf","text":"Report","size":"23.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5062"}],"country":"United States","state":"Arizona","otherGeospatial":"Rio Rico and Nogales 7.5’ Quadrangles, Upper Santa Cruz Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111,\n 31.33\n ],\n [\n -110.875,\n 31.33\n ],\n [\n -110.875,\n 31.5\n ],\n [\n -111,\n 31.5\n ],\n [\n -111,\n 31.33\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS 980
Denver, CO 80225
Digital flood-inundation maps for an 8-mile (mi) reach of the Huron River near Hamburg, Michigan (station number 04172000), from downstream of Rickett Road to Strawberry Lake, were created by the U.S. Geological Survey (USGS), in cooperation with Green Oak and Hamburg Townships, Michigan, and the U.S. Army Corps of Engineers. The flood-inundation maps also include a 1.16-mi reach of the Ore Lake Tributary until it joins the Huron River, approximately 2.22 mi downstream of Rickett Road. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Huron River near Hamburg, Michigan (station number 04172000). Near real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/. The NWS Advanced Hydrologic Prediction Service also provides forecasted flood hydrographs at this website.
Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the current stage-discharge relation at the Huron River near Hamburg, Mich., streamgage and was calibrated to water levels determined with stage sensors (pressure transducers) temporarily deployed along the stream reach. The hydraulic model was used to compute a set of water-surface profiles for flood stages ranging from 7.0 to 10.5 feet (ft). This range represents stages just above 6.0 (bankfull) to 2.04 ft above the maximum recorded stage at the USGS streamgage on the Huron River near Hamburg, Mich. (station number 04172000). The computed water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from light detection and ranging [lidar] data having a 0.49-ft vertical accuracy and 3.8-ft horizontal resolution) to delineate the area flooded at each water level.
The availability of these maps, along with Internet information regarding current stage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information critical for flood-response activities such as evacuations, road closures, and postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185048","collaboration":"Prepared in cooperation with Green Oak and Hamburg Townships, Michigan and the U.S. Army Corps of Engineers","usgsCitation":"Prokopec, J.G., 2018, Hydraulic modeling and flood-inundation mapping for the Huron River and Ore Lake Tributary, Livingston County, Michigan: U.S. Geological Survey Scientific Investigations Report 2018–5048, 13 p., https://doi.org/10.3133/sir20185048.","productDescription":"Report: vii, 13 p.; 2 Data releases","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-084641","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":437793,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H1TX91","text":"USGS data release","linkHelpText":"Geospatial data for a Flood-Inundation Mapping Study of the Huron River near Hamburg, Michigan"},{"id":362849,"rank":4,"type":{"id":30,"text":"Data Release"},"url":" https://www.sciencebase.gov/catalog/item/5c953d27e4b09388245a6d33 ","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial data for a Flood-Inundation Mapping Study of the Huron River near Hamburg, Michigan"},{"id":356059,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5048/coverthb.jpg"},{"id":356060,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5048/sir20185048.pdf","text":"Report","size":"1.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5048"},{"id":356061,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79G5M11","text":"USGS data release","description":"USGS data release","linkHelpText":"Huron River near Hamburg, Michigan, flood-inundation model and field data"}],"country":"United States","state":"Michigan","county":"Livingston County","otherGeospatial":"Huron River, Ore Lake Tributary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.84233474731445,\n 42.4333\n ],\n [\n -83.7667,\n 42.4333\n ],\n [\n -83.7667,\n 42.490960223200396\n ],\n [\n -83.84233474731445,\n 42.490960223200396\n ],\n [\n -83.84233474731445,\n 42.4333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
6520 Mercantile Way
Suite 5
Lansing, MI 48911
Review of previous investigations indicates that potential decreases in groundwater recharge and increased groundwater extraction in the vicinity of the Lower Des Plaines River Valley in Will County, Illinois, may reduce the amount of groundwater flow in the Silurian aquifer in this area. Groundwater discharge from the Silurian aquifer to wetlands in the Lower Des Plaines River Valley plays an important role in sustaining the habitat of the endangered Hine’s emerald dragonfly (Somatochlora hineana). Groundwater modeling performed by previous investigators indicates that increasing the amount of water pumped from the aquifer in support of expanded quarry operations near the Lockport Prairie Nature Preserve has the potential to reduce groundwater discharge to the most productive Hine’s emerald dragonfly habitats in Illinois, potentially degrading the habitat. Model simulations indicate that mitigation procedures designed to artificially enhance groundwater recharge in the vicinity of dragonfly habitats near the Lockport Prairie Nature Preserve are likely to offset the effects of increased pumping. Several areas with smaller, often intermittent populations of Hine’s emerald dragonflies have been identified in other parts of the Lower Des Plaines River Valley and elsewhere in Illinois. Human activities have the potential to produce changes in hydrology and water quality that can threaten all of these habitats.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185074","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Kay, R.T., Gahala, A.M., and Bailey, C., 2018, Assessment of water resources in areas that affect the habitat of the endangered Hine’s emerald dragonfly in the Lower Des Plaines River Valley, Illinois: U.S. Geological Survey Scientific Investigations Report 2018–5074, 104 p., https://doi.org/10.3133/sir20185074.","productDescription":"ix, 104 p.","numberOfPages":"118","onlineOnly":"Y","ipdsId":"IP-084365","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":356231,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5074/coverthb.jpg"},{"id":356232,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5074/sir20185074.pdf","text":"Report","size":"14.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5074"}],"country":"United States","state":"Illinois","otherGeospatial":"Lower Des Plaines River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.15,\n 41.55\n ],\n [\n -88.05,\n 41.55\n ],\n [\n -88.05,\n 41.65\n ],\n [\n -88.15,\n 41.65\n ],\n [\n -88.15,\n 41.55\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 N. Goodwin
Urbana, IL 61801
In many coastal regions throughout the world, there is increasing pressure to harden shorelines to protect human infrastructures against sea level rise, storm surge, and erosion. This study examines waterbird community integrity in relation to shoreline hardening and land use characteristics at three geospatial scales: (1) the shoreline scale characterized by seven shoreline types: bulkhead, riprap, developed, natural marsh, Phragmites-dominated marsh, sandy beach, and forest; (2) the local subestuary landscape scale including land up to 500 m inland of the shoreline; and (3) the watershed scale >500 m from the shoreline. From 2010 to 2014, we conducted waterbird surveys along the shoreline and open water within 21 subestuaries throughout the Chesapeake Bay during two seasons to encompass post-breeding shorebirds and colonial waterbirds in late summer and migrating and wintering waterfowl in late fall. We employed an Index of Waterbird Community Integrity (IWCI) derived from mean abundance of individual waterbird species and scores of six key species attributes describing each species’ sensitivity to human disturbance, and then used this index to characterize communities in each subestuary and season. IWCI scores ranged from 14.3 to 19.7. Multivariate regression model selection showed that the local shoreline scale had the strongest influence on IWCI scores. At this scale, percent coverage of bulkhead and Phragmites along shorelines were the strongest predictors of IWCI, both with negative relationships. Recursive partitioning revealed that when subestuary shoreline coverage exceeded thresholds of approximately 5% Phragmites or 8% bulkhead, IWCI scores decreased. Our results indicate that development at the shoreline scale has an important effect on waterbird community integrity, and that shoreline hardening and invasive Phragmites each have a negative effect on waterbirds using subestuarine systems.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-017-0288-0","usgsCitation":"Prosser, D.J., Nagel, J.L., Howlin, S., Marban, P., Day, D.D., and Erwin, R., 2018, Effects of local shoreline and subestuary watershed condition on waterbird community integrity: Influences of geospatial scale and season in the Chesapeake Bay: Estuaries and Coasts, v. 41, no. Supplement 1, p. 207-222, https://doi.org/10.1007/s12237-017-0288-0.","productDescription":"16 p.","startPage":"207","endPage":"222","ipdsId":"IP-080893","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":460865,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-017-0288-0","text":"Publisher Index Page"},{"id":437798,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ENV0R9","text":"USGS data release","linkHelpText":"Shoreline delineations for 21 Subestuaries in the Chesapeake Bay 2010-2014."},{"id":437797,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QR4V9M","text":"USGS data release","linkHelpText":"Effects of local shoreline and subestuary watershed condition on waterbird use: influences of geography, scale, and season in the Chesapeake Bay"},{"id":356317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.1734619140625,\n 36.90597988519294\n ],\n [\n -75.43212890625,\n 36.90597988519294\n ],\n [\n -75.43212890625,\n 39.6606850221923\n ],\n [\n -77.1734619140625,\n 39.6606850221923\n ],\n [\n -77.1734619140625,\n 36.90597988519294\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"Supplement 1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-26","publicationStatus":"PW","scienceBaseUri":"5b6fc3d0e4b0f5d57878e8f1","contributors":{"authors":[{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":741933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagel, Jessica L. 0000-0002-4437-0324 jnagel@usgs.gov","orcid":"https://orcid.org/0000-0002-4437-0324","contributorId":3976,"corporation":false,"usgs":true,"family":"Nagel","given":"Jessica","email":"jnagel@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":741934,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howlin, Shay","contributorId":206848,"corporation":false,"usgs":false,"family":"Howlin","given":"Shay","email":"","affiliations":[{"id":37415,"text":"Western EcoSystems Technology, Cheyenne, WY","active":true,"usgs":false}],"preferred":false,"id":741935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marban, Paul 0000-0002-4910-6565 pmarban@usgs.gov","orcid":"https://orcid.org/0000-0002-4910-6565","contributorId":196581,"corporation":false,"usgs":true,"family":"Marban","given":"Paul","email":"pmarban@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":741936,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Day, Daniel D. 0000-0001-9070-7170 dday@usgs.gov","orcid":"https://orcid.org/0000-0001-9070-7170","contributorId":3985,"corporation":false,"usgs":true,"family":"Day","given":"Daniel","email":"dday@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":741937,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Erwin, R. Michael 0000-0003-2108-9502","orcid":"https://orcid.org/0000-0003-2108-9502","contributorId":196583,"corporation":false,"usgs":false,"family":"Erwin","given":"R. Michael","affiliations":[],"preferred":false,"id":741938,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198559,"text":"70198559 - 2018 - Using partial aggregation in spatial capture recapture","interactions":[],"lastModifiedDate":"2018-08-07T16:23:44","indexId":"70198559","displayToPublicDate":"2018-08-07T16:23:42","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Using partial aggregation in spatial capture recapture","docAbstract":"