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":70198371,"text":"fs20183049 - 2018 - Landsat Collections","interactions":[],"lastModifiedDate":"2018-09-20T07:56:32","indexId":"fs20183049","displayToPublicDate":"2018-08-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3049","title":"Landsat Collections","docAbstract":"In 2016, the U.S. Geological Survey reorganized the Landsat archive into a tiered collection structure, which ensures that Landsat Level-1 products provide a consistent archive of known data quality to support time-series analyses and data “stacking” while controlling continuous improvement of the archive and access to all data as they are acquired. Landsat Collection 1 required the reprocessing of all archived Landsat data to achieve radiometric and geometric consistency of Level-1 products through time and across all Landsat sensors.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183049","usgsCitation":"U.S. Geological Survey, 2018, Landsat collections: U.S. Geological Survey Fact Sheet 2018–3049, 2 p., https://doi.org/10.3133/fs20183049.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-097436","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":356418,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3049/fs20183049.pdf","text":"Report","size":"743 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018–3049"},{"id":356417,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3049/coverthb2.jpg"}],"contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
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":70198644,"text":"70198644 - 2018 - Flushing of the deep Pacific Ocean and the deglacial rise of atmospheric CO2 concentrations","interactions":[],"lastModifiedDate":"2018-10-04T13:23:52","indexId":"70198644","displayToPublicDate":"2018-08-14T13:56:43","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Flushing of the deep Pacific Ocean and the deglacial rise of atmospheric CO2 concentrations","title":"Flushing of the deep Pacific Ocean and the deglacial rise of atmospheric CO2 concentrations","docAbstract":"During the last deglaciation (19,000–9,000 years ago), atmospheric CO2increased by about 80 ppm. Understanding the mechanisms responsible for this change is a central theme of palaeoclimatology, relevant for predicting future CO2 transfers in a warming world. Deglacial CO2 rise hypothetically tapped an accumulated deep Pacific carbon reservoir, but the processes remain elusive as they are underconstrained by existing tracers. Here we report high-resolution authigenic neodymium isotope data in North Pacific sediment cores and infer abyssal Pacific overturning weaker than today during the Last Glacial Maximum but intermittently stronger during steps of deglacial CO2 rise. Radiocarbon evidence suggestive of relatively ‘old’ deglacial deep Pacific water is reinterpreted here as an increase in preformed 14C age of subsurface waters sourced near Antarctica, consistent with movement of aged carbon out of the deep ocean and release of CO2 to the atmosphere during the abyssal flushing events. The timing of neodymium isotope changes suggests that deglacial acceleration of Pacific abyssal circulation tracked Southern Hemisphere warming, sea-ice retreat and increase of mean ocean temperature. The inferred magnitude of circulation changes is consistent with deep Pacific flushing as a significant, and perhaps dominant, control of the deglacial rise of atmospheric CO2.
","language":"English","publisher":"Nature","doi":"10.1038/s41561-018-0205-6","usgsCitation":"Du, J., Haley, B., Mix, A., Walczak, M., and Praetorius, S.K., 2018, Flushing of the deep Pacific Ocean and the deglacial rise of atmospheric CO2 concentrations: Nature Geoscience, v. 11, p. 749-755, https://doi.org/10.1038/s41561-018-0205-6.","productDescription":"7 p.","startPage":"749","endPage":"755","ipdsId":"IP-091496","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":356442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-13","publicationStatus":"PW","scienceBaseUri":"5b98a289e4b0702d0e842f43","contributors":{"authors":[{"text":"Du, Jianghui 0000-0002-3386-9314","orcid":"https://orcid.org/0000-0002-3386-9314","contributorId":206970,"corporation":false,"usgs":false,"family":"Du","given":"Jianghui","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":742336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haley, Brian","contributorId":206971,"corporation":false,"usgs":false,"family":"Haley","given":"Brian","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":742337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mix, Alan","contributorId":184163,"corporation":false,"usgs":false,"family":"Mix","given":"Alan","affiliations":[],"preferred":false,"id":742338,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walczak, Maureen 0000-0002-4123-6998","orcid":"https://orcid.org/0000-0002-4123-6998","contributorId":206972,"corporation":false,"usgs":false,"family":"Walczak","given":"Maureen","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":742339,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":742335,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"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":70198893,"text":"70198893 - 2018 - Lake sediment fecal and biomass burning biomarkers provide direct evidence for prehistoric human-lit fires in New Zealand","interactions":[],"lastModifiedDate":"2018-08-27T12:31:21","indexId":"70198893","displayToPublicDate":"2018-08-14T12:31:16","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":"Lake sediment fecal and biomass burning biomarkers provide direct evidence for prehistoric human-lit fires in New Zealand","docAbstract":"Deforestation associated with the initial settlement of New Zealand is a dramatic example of how humans can alter landscapes through fire. However, evidence linking early human presence and land-cover change is inferential in most continental sites. We employed a multi-proxy approach to reconstruct anthropogenic land use in New Zealand’s South Island over the last millennium using fecal and plant sterols as indicators of human activity and monosaccharide anhydrides, polycyclic aromatic hydrocarbons, charcoal and pollen as tracers of fire and vegetation change in lake-sediment cores. Our data provide a direct record of local human presence in Lake Kirkpatrick and Lake Diamond watersheds at the time of deforestation and a new and stronger case of human agency linked with forest clearance. The first detection of human presence matches charcoal and biomarker evidence for initial burning at c. AD 1350. Sterols decreased shortly after to values suggesting the sporadic presence of people and then rose to unprecedented levels after the European settlement. Our results confirm that initial human arrival in New Zealand was associated with brief and intense burning activities. Testing our approach in a context of well-established fire history provides a new tool for understanding cause-effect relationships in more complex continental reconstructions.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-018-30606-3","usgsCitation":"Argiriadis, E., Battistel, D., McWethy, D.B., Vecchiato, M., Kirchgeorg, T., Kehrwald, N.M., Whitlock, C., Wilmshurst, J.M., and Barbante, C., 2018, Lake sediment fecal and biomass burning biomarkers provide direct evidence for prehistoric human-lit fires in New Zealand: Scientific Reports, v. 8, Article number: 12113; 9 p., https://doi.org/10.1038/s41598-018-30606-3.","productDescription":"Article number: 12113; 9 p.","ipdsId":"IP-094661","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468499,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-30606-3","text":"Publisher Index Page"},{"id":356784,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 168.96069288253784,\n -44.649497959678556\n ],\n [\n 168.96600365638733,\n -44.649497959678556\n ],\n [\n 168.96600365638733,\n -44.64600207780289\n ],\n [\n 168.96069288253784,\n -44.64600207780289\n ],\n [\n 168.96069288253784,\n -44.649497959678556\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 168.5570526123047,\n -45.03956694724903\n ],\n [\n 168.59962463378906,\n -45.03956694724903\n ],\n [\n 168.59962463378906,\n -45.01433117775014\n ],\n [\n 168.5570526123047,\n -45.01433117775014\n ],\n [\n 168.5570526123047,\n -45.03956694724903\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-14","publicationStatus":"PW","scienceBaseUri":"5b98a289e4b0702d0e842f49","contributors":{"authors":[{"text":"Argiriadis, Elena","contributorId":207231,"corporation":false,"usgs":false,"family":"Argiriadis","given":"Elena","affiliations":[{"id":37489,"text":"University of Venice, Ca' Foscari","active":true,"usgs":false}],"preferred":false,"id":743285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Battistel, Dario","contributorId":205865,"corporation":false,"usgs":false,"family":"Battistel","given":"Dario","email":"","affiliations":[{"id":37181,"text":"Department of Environmental Science, Informatics and Statistics, Ca' Foscari University of Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":743286,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McWethy, David B.","contributorId":207232,"corporation":false,"usgs":false,"family":"McWethy","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":743287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vecchiato, Marco","contributorId":207233,"corporation":false,"usgs":false,"family":"Vecchiato","given":"Marco","email":"","affiliations":[{"id":37489,"text":"University of Venice, Ca' Foscari","active":true,"usgs":false}],"preferred":false,"id":743288,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kirchgeorg, Torben","contributorId":207234,"corporation":false,"usgs":false,"family":"Kirchgeorg","given":"Torben","email":"","affiliations":[{"id":37489,"text":"University of Venice, Ca' Foscari","active":true,"usgs":false}],"preferred":false,"id":743289,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kehrwald, Natalie M. 0000-0002-9160-2239 nkehrwald@usgs.gov","orcid":"https://orcid.org/0000-0002-9160-2239","contributorId":168918,"corporation":false,"usgs":true,"family":"Kehrwald","given":"Natalie","email":"nkehrwald@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":743284,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Whitlock, Cathy","contributorId":79745,"corporation":false,"usgs":false,"family":"Whitlock","given":"Cathy","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":743290,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wilmshurst, Janet M.","contributorId":207235,"corporation":false,"usgs":false,"family":"Wilmshurst","given":"Janet","email":"","middleInitial":"M.","affiliations":[{"id":37490,"text":"University of Aukland","active":true,"usgs":false}],"preferred":false,"id":743291,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barbante, Carlo","contributorId":202632,"corporation":false,"usgs":false,"family":"Barbante","given":"Carlo","email":"","affiliations":[{"id":36503,"text":"Department of Environmental Sciences, Infomatics, and Statistics, Ca'Foscari University of Venice, Via Torino 155, 30172 Mestre (VE), Italy","active":true,"usgs":false}],"preferred":false,"id":743292,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70216177,"text":"70216177 - 2018 - Efficiency of sampling sunfishes using snorkeling in clear, warmwater streams of the south-central United States","interactions":[],"lastModifiedDate":"2020-11-09T15:03:52.637067","indexId":"70216177","displayToPublicDate":"2018-08-14T08:58:34","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":"Efficiency of sampling sunfishes using snorkeling in clear, warmwater streams of the south-central United States","docAbstract":"The continued evaluation of fish-sampling gears and methods is essential to identify their applicability across environmental conditions and among species. Although limited by visibility, snorkeling has potential advantages relative to other fish-sampling gears in wadeable streams (e.g., minimally intrusive, cost effective, and appropriate in deeper areas). Clear water is common to warm-water streams; however, the use of snorkeling for monitoring stream-fish populations has largely focused on cold-water systems. To assess relative snorkeling efficiency in warm-water streams, we compared standardized single-pass snorkel counts to tow-barge electrofishing abundance estimates for six sunfishes (Centrarchidae) in the Ozark Highlands ecoregion of northwest Oklahoma and southwest Missouri under relatively similar environmental conditions (i.e., clear water, cobble substrates, low-flow conditions). Snorkeling efficiency was variable among sunfishes and consistently low for species with cryptic traits and habitat use. We also did not detect cryptic sunfishes (i.e., a single individual was not encountered) using snorkeling at multiple stream reaches where estimated abundance was > 50 within a 0.5- to 1.0-km stream reach. Our findings indicate that snorkeling has applications for monitoring sunfish populations and assemblages when using an abundance estimator or accounting for imperfect detection; however, it is inappropriate for estimating population size of cryptic sunfishes. We encourage continued research into the applicability of snorkeling to estimate warm-water stream fish abundance.
","language":"English","publisher":"Allen Press","doi":"10.3996/032018-JFWM-027","usgsCitation":"Mollenhauer, R., and Brewer, S.K., 2018, Efficiency of sampling sunfishes using snorkeling in clear, warmwater streams of the south-central United States: Journal of Fish and Wildlife Management, v. 9, no. 2, p. 602-609, https://doi.org/10.3996/032018-JFWM-027.","productDescription":"8 p.","startPage":"602","endPage":"609","ipdsId":"IP-091999","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468500,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/032018-jfwm-027","text":"Publisher Index Page"},{"id":380296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri, Oklahoma","otherGeospatial":"Ozark Highlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.3668212890625,\n 36.46988944681576\n ],\n [\n -94.21875,\n 36.46988944681576\n ],\n [\n -94.21875,\n 37.020098201368114\n ],\n [\n -95.3668212890625,\n 37.020098201368114\n ],\n [\n -95.3668212890625,\n 36.46988944681576\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"2","noUsgsAuthors":false,"publicationDate":"2018-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Mollenhauer, Robert","contributorId":242899,"corporation":false,"usgs":false,"family":"Mollenhauer","given":"Robert","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":804362,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":804363,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"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":70202468,"text":"70202468 - 2018 - Liverworts from Attu Island, Near Islands, Aleutian Islands, Alaska (USA) with comparison to the Commander Islands (Russia)","interactions":[],"lastModifiedDate":"2019-03-04T15:35:36","indexId":"70202468","displayToPublicDate":"2018-08-13T15:35:29","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5810,"text":"Botanica Pacifica","active":true,"publicationSubtype":{"id":10}},"title":"Liverworts from Attu Island, Near Islands, Aleutian Islands, Alaska (USA) with comparison to the Commander Islands (Russia)","docAbstract":"The liverwort flora of Attu Island, the westernmost Aleutian Island in the United States, was studied to assess species diversity in the hyperoceanic sector of the northern boreal subzone. The field study was undertaken in sites selected to represent a spectrum of environmental variation, primarily within the eastern part of the island. Data were analyzed using our own collections on Attu Island, supplemented with information from published reports to compare bryophyte distribution patterns at three levels, the Northern Hemisphere, North America, the Commander Islands of Russia, and Alaska. A total of 112 liverworts were identified and a substantial number, 34 species (30%), were new reports from Attu Island and one was new to Alaska. Geographic elements dominating the flora included arctomontane (26%), arctoboreomontane (23%), montane (20%), and boreal (14%) species, while arctic species were almost absent (1%). The liverworts of the Attu Island-Commander Islands region were widespread species with over 70% circumpolar, or nearly circumpolar; nevertheless large gaps were present in some of their distributions with a floristic depression in liverwort distribution between Attu and the Commander Islands.
","language":"English","publisher":"Botanica Pacifica","doi":"10.17581/bp.2018.07203","usgsCitation":"Talbot, S.S., Schofield, W.B., Vana, J., and Talbot, S.L., 2018, Liverworts from Attu Island, Near Islands, Aleutian Islands, Alaska (USA) with comparison to the Commander Islands (Russia): Botanica Pacifica, v. 7, no. 2, p. 127-141, https://doi.org/10.17581/bp.2018.07203.","productDescription":"15 p.","startPage":"127","endPage":"141","ipdsId":"IP-092332","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":460863,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.17581/bp.2018.07203","text":"Publisher Index Page"},{"id":437786,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92H3W9D","text":"USGS data release","linkHelpText":"Frullania nisquallensis Species Confirmation, Attu Island, Alaska, 2018"},{"id":361715,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","state":"Alaska","otherGeospatial":"Aleutian Islands, Attu Island, Commander Islands, Near Islands","volume":"7","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Talbot, Stephen S.","contributorId":213927,"corporation":false,"usgs":false,"family":"Talbot","given":"Stephen","email":"","middleInitial":"S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":758709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schofield, Wilfred B.","contributorId":213928,"corporation":false,"usgs":false,"family":"Schofield","given":"Wilfred","email":"","middleInitial":"B.","affiliations":[{"id":38932,"text":"Department of Botany, University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":758710,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vana, Jiri","contributorId":213929,"corporation":false,"usgs":false,"family":"Vana","given":"Jiri","email":"","affiliations":[{"id":38933,"text":"Department of Botany, Charles University","active":true,"usgs":false}],"preferred":false,"id":758711,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":758708,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"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":70199797,"text":"70199797 - 2018 - Field evaluation of carbon dioxide as a fish deterrent at a water management structure along the Illinois River","interactions":[],"lastModifiedDate":"2018-09-28T12:44:44","indexId":"70199797","displayToPublicDate":"2018-08-13T12:44:39","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Field evaluation of carbon dioxide as a fish deterrent at a water management structure along the Illinois River","docAbstract":"Construction of a water management structure (WMS) in the levee surrounding The Nature Conservancy’s Emiquon Preserve (Havana, Illinois, USA) created a new hydrological connection and potential aquatic invasive species pathway between the Illinois River and a large conservation wetland complex. Site managers need a control tool that deters the upstream passage of non-native fishes into the wetland lakes, but does not interfere with normal gate operation and water discharge. This short field study evaluated carbon dioxide (CO2) injected into water as a non-obstructive method to reduce fish abundance near the WMS culverts. We quantified relative fish abundance using underwater sonar with and without injection of CO2 into culverts during three discharge events: no flow (0 m3/s), restricted flow (0.9 m3/s), and unrestricted flow (3.2 m3/s). Overall, CO2 reached or exceeded our target concentration of 100 mg/L during no flow and restricted flow, and fish abundance was 70–95% lower at culvert entrances relative to untreated control days. The target CO2 level was not reached during unrestricted flow and fish abundance was not reduced during CO2 injection. Atmospheric CO2 concentrations were inconsequential and unaffected by CO2 treatments throughout testing. Results from this initial field study provide several considerations for CO2 as a fish deterrent in natural environments.
","language":"English","publisher":"REABIC","doi":"10.3391/mbi.2018.9.3.12","usgsCitation":"Cupp, A.R., Smerud, J.R., Tix, J., Schleis, S.M., Fredricks, K.T., Erickson, R.A., Amberg, J., Morrow, W.S., Koebel, C.M., Murphy, E.A., Vishy, C., and Blodgett, K.D., 2018, Field evaluation of carbon dioxide as a fish deterrent at a water management structure along the Illinois River: Management of Biological Invasions, v. 9, no. 3, p. 299-308, https://doi.org/10.3391/mbi.2018.9.3.12.","productDescription":"10 p.","startPage":"299","endPage":"308","ipdsId":"IP-093338","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468502,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2018.9.3.12","text":"Publisher Index Page"},{"id":437788,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GS2P5E","text":"USGS data release","linkHelpText":"Field evaluation of carbon dioxide as a fish deterrent at a water management structure along the Illinois River: Data"},{"id":357899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois River","volume":"9","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02fc0e4b0fc368eb5396d","contributors":{"authors":[{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":746651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smerud, Justin R. 0000-0003-4385-7437 jrsmerud@usgs.gov","orcid":"https://orcid.org/0000-0003-4385-7437","contributorId":5031,"corporation":false,"usgs":true,"family":"Smerud","given":"Justin","email":"jrsmerud@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":746652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tix, John 0000-0002-9531-5624 jtix@usgs.gov","orcid":"https://orcid.org/0000-0002-9531-5624","contributorId":197014,"corporation":false,"usgs":true,"family":"Tix","given":"John","email":"jtix@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":746653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schleis, Susan M. 0000-0002-9396-7856 sschleis@usgs.gov","orcid":"https://orcid.org/0000-0002-9396-7856","contributorId":2858,"corporation":false,"usgs":true,"family":"Schleis","given":"Susan","email":"sschleis@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":746654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fredricks, Kim T. 0000-0003-2363-7891 kfredricks@usgs.gov","orcid":"https://orcid.org/0000-0003-2363-7891","contributorId":173994,"corporation":false,"usgs":true,"family":"Fredricks","given":"Kim","email":"kfredricks@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":746655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":746659,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":746656,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morrow, William S. 0000-0002-2250-3165 wsmorrow@usgs.gov","orcid":"https://orcid.org/0000-0002-2250-3165","contributorId":1886,"corporation":false,"usgs":true,"family":"Morrow","given":"William","email":"wsmorrow@usgs.gov","middleInitial":"S.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746657,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Koebel, Carolyn M. 0000-0003-0501-2572 ckoebel@usgs.gov","orcid":"https://orcid.org/0000-0003-0501-2572","contributorId":173836,"corporation":false,"usgs":true,"family":"Koebel","given":"Carolyn","email":"ckoebel@usgs.gov","middleInitial":"M.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746658,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Murphy, Elizabeth A. 0000-0002-8939-7678 emurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-8939-7678","contributorId":196368,"corporation":false,"usgs":true,"family":"Murphy","given":"Elizabeth","email":"emurphy@usgs.gov","middleInitial":"A.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746660,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Vishy, Chad 0000-0001-5242-0363","orcid":"https://orcid.org/0000-0001-5242-0363","contributorId":208276,"corporation":false,"usgs":true,"family":"Vishy","given":"Chad","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":746661,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Blodgett, K. Douglas","contributorId":208277,"corporation":false,"usgs":false,"family":"Blodgett","given":"K.","email":"","middleInitial":"Douglas","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":746662,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"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":70197858,"text":"fs20183034 - 2018 - Biological and ecological science for Ohio—The Buckeye State","interactions":[],"lastModifiedDate":"2018-08-13T10:34:02","indexId":"fs20183034","displayToPublicDate":"2018-08-10T11:56:12","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3034","title":"Biological and ecological science for Ohio—The Buckeye State","docAbstract":"Ohio is home to lakes, rivers, streams, wetlands, forests, prairies, and 312 miles of Lake Erie shoreline. These resources sustain Ohio’s communities by supporting vital sectors of the economy and cultural heritage such as fishing, hunting, and other outdoor recreation. Lake Erie provides drinking water for 3 million Ohioans, supports 124,000 Ohio jobs, and generates \\$1.8 billion in tourism revenue to the State. Outdoor recreation is enjoyed by nearly 60 percent of Ohio residents. Annually, it is estimated that outdoor recreation generates \\$24.3 billion in consumer spending across the State, creates 215,000 jobs, and raises \\$1.5 billion in State and local tax revenue.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183034","usgsCitation":"U.S. Geological Survey, 2018, Biological and ecological science for Ohio—The Buckeye State: U.S. Geological Survey Fact Sheet 2018-3034, 2 p., https://doi.org/10.3133/fs20183034.","productDescription":"2 p.","onlineOnly":"Y","ipdsId":"IP-091847","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":356390,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3034/coverthb.jpg"},{"id":356383,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3034/fs20183034.pdf","text":"Report","size":"560 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3034"}],"country":"United 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\"}}]}","contact":"Ecosystems Mission Area
https://www.usgs.gov/ask/
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There are thousands of seeps in the deep ocean worldwide; however, many questions remain about their contributions to global biodiversity and the surrounding deep‐sea environment. In addition to being globally distributed, seeps provide several benefits to humans such as unique habitats, organisms with novel genes, and carbon regulation. The purpose of this study is to determine whether there are unique seep macrobenthic assemblages, by comparing seep and nonseep environments, different seep habitats, and seeps at different depths and locations. Infaunal community composition, diversity, and abundance were examined between seep and nonseep background environments and among three seep habitats (i.e., microbial mats, tubeworms, and soft‐bottom seeps). Abundances were higher at seep sites compared to background areas. Abundance and diversity also differed among microbial mat, tubeworm, and soft‐bottom seep habitats. Although seeps contained different macrobenthic assemblages than nonseep areas, infaunal communities were also generally unique for each seep. Variability was 75% greater within communities near seeps compared to communities in background areas. Thus, high variability in community structure characterized seep communities rather than specific taxa. The lack of similarity among seep sites supports the idea that there are no specific infauna that can be used as indicators of seepage throughout the northern Gulf of Mexico, at least at higher taxonomic levels.
","language":"English","publisher":"Wiley","doi":"10.1111/maec.12508","usgsCitation":"Washburn, T.W., Demopoulos, A.W., and Montagna, P.A., 2018, Macrobenthic infaunal communities associated with deep‐sea hydrocarbon seeps in the northern Gulf of Mexico: Marine Ecology, v. 39, no. 3, e12508, https://doi.org/10.1111/maec.12508.","productDescription":"e12508","ipdsId":"IP-091463","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468506,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/56958","text":"External Repository"},{"id":437789,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FN155W","text":"USGS data release","linkHelpText":"Macrobenthic infaunal communities associated with deep-sea hydrocarbon seeps in the Gulf of Mexico, 2009-2010"},{"id":356388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-25","publicationStatus":"PW","scienceBaseUri":"5b6fc3c3e4b0f5d57878e8d3","contributors":{"authors":[{"text":"Washburn, Travis W.","contributorId":206920,"corporation":false,"usgs":false,"family":"Washburn","given":"Travis","email":"","middleInitial":"W.","affiliations":[{"id":37423,"text":"TAMU-CC","active":true,"usgs":false}],"preferred":false,"id":742108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":196216,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":742107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Montagna, Paul A.","contributorId":177033,"corporation":false,"usgs":false,"family":"Montagna","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":742109,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198597,"text":"70198597 - 2018 - State-level freshwater mussel programs: Current status and a research framework to aid in mussel management and conservation","interactions":[],"lastModifiedDate":"2018-08-10T11:36:27","indexId":"70198597","displayToPublicDate":"2018-08-10T11:36:25","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"State-level freshwater mussel programs: Current status and a research framework to aid in mussel management and conservation","docAbstract":"Despite increased focus on their ecology and conservation, freshwater mussels remain one of the most imperiled groups of aquatic organisms. We documented current management actions, resources, and challenges in managing freshwater mussels in the United States through a survey of state natural resource agencies. Approximately 85% of surveyed states (N = 40) actively managed mussel populations. Common challenges to mussel conservation included limited funding, lack of public awareness, and poor understanding of habitat needs and risks. We present a research framework, currently underway in Missouri, to support a regional mussel conservation assessment whereby habitat needs are identified, risks are assessed, and standardized protocols are developed to monitor and detect trends in mussel assemblages and threats. The research framework conforms to the National Strategy for the Conservation of Native Freshwater Mollusks and is adaptable to other states. With full consideration of resource limitations, we explore how this framework can improve the effectiveness of mussel conservation efforts.
","language":"English","publisher":"Wiley","doi":"10.1002/fsh.10106","usgsCitation":"Bouska, K.L., Rosenberger, A.E., McMurray, S.E., Lindner, G., and Key, K.N., 2018, State-level freshwater mussel programs: Current status and a research framework to aid in mussel management and conservation: Fisheries, v. 43, no. 8, p. 345-360, https://doi.org/10.1002/fsh.10106.","productDescription":"16 p.","startPage":"345","endPage":"360","ipdsId":"IP-076251","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":356387,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"43","issue":"8","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-09","publicationStatus":"PW","scienceBaseUri":"5b6fc3c3e4b0f5d57878e8d5","contributors":{"authors":[{"text":"Bouska, Kristen L. 0000-0002-4115-2313 kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":742091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberger, Amanda E.","contributorId":206917,"corporation":false,"usgs":false,"family":"Rosenberger","given":"Amanda","email":"","middleInitial":"E.","affiliations":[{"id":37422,"text":"Missouri Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":742092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McMurray, Stephen E.","contributorId":206918,"corporation":false,"usgs":false,"family":"McMurray","given":"Stephen","email":"","middleInitial":"E.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":742093,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindner, Garth A.","contributorId":143717,"corporation":false,"usgs":false,"family":"Lindner","given":"Garth A.","affiliations":[{"id":15309,"text":"University of Maryland Baltimore County","active":true,"usgs":false}],"preferred":false,"id":742094,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Key, Kayla N.","contributorId":206919,"corporation":false,"usgs":false,"family":"Key","given":"Kayla","email":"","middleInitial":"N.","affiliations":[{"id":13706,"text":"University of Missouri-Columbia","active":true,"usgs":false}],"preferred":false,"id":742095,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198582,"text":"70198582 - 2018 - Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks","interactions":[],"lastModifiedDate":"2020-02-25T07:55:59","indexId":"70198582","displayToPublicDate":"2018-08-10T11:31:17","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5728,"text":"International Journal of Cartography","active":true,"publicationSubtype":{"id":10}},"title":"Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks","docAbstract":"Automated generalization software must accommodate multi-scale representations of hydrographic networks across a variety of geographic landscapes, because scale-related hydrography differences are known to vary in different physical conditions. While generalization algorithms have been tailored to specific regions and landscape conditions by several researchers in recent years, the selection and characterization of regional conditions have not been formally defined nor statistically validated. This paper undertakes a systematic classification of landscape types in the conterminous United States to spatially subset the country into workable units, in preparation for systematic tailoring of generalization workflows that preserve hydrographic characteristics. The classification is based upon elevation, standard deviation of elevation, slope, runoff, drainage and bedrock density, soil and bedrock permeability, area of inland surface water, infiltration-excess of overland flow, and a base flow index. A seven class solution shows low misclassification rates except in areas of high landscape diversity such as the Appalachians, Rocky Mountains, and Western coastal regions.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/23729333.2018.1443759","usgsCitation":"Stanislawski, L.V., Finn, M.P., and Buttenfield, B.P., 2018, Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks: International Journal of Cartography, v. 1, p. 4-21, https://doi.org/10.1080/23729333.2018.1443759.","productDescription":"18 p.","startPage":"4","endPage":"21","ipdsId":"IP-096031","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":356386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-20","publicationStatus":"PW","scienceBaseUri":"5b6fc3c4e4b0f5d57878e8d7","contributors":{"authors":[{"text":"Stanislawski, Larry V. 0000-0002-9437-0576 lstan@usgs.gov","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":3386,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","email":"lstan@usgs.gov","middleInitial":"V.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":742028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finn, Michael P. 0000-0003-0415-2194 mfinn@usgs.gov","orcid":"https://orcid.org/0000-0003-0415-2194","contributorId":2657,"corporation":false,"usgs":true,"family":"Finn","given":"Michael","email":"mfinn@usgs.gov","middleInitial":"P.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"preferred":true,"id":742029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buttenfield, Barbara P.","contributorId":184069,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":742030,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198581,"text":"70198581 - 2018 - Stream‐centric methods for determining groundwater contributions in karst mountain watersheds","interactions":[],"lastModifiedDate":"2018-10-23T16:57:20","indexId":"70198581","displayToPublicDate":"2018-08-10T11:28:02","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Stream‐centric methods for determining groundwater contributions in karst mountain watersheds","docAbstract":"Climate change influences on mountain hydrology are uncertain, but likely to be mediated through changes in subsurface hydrologic residence times and flowpaths. The heterogeneity of karst aquifers add complexity in assessing the resiliency of these water sources to perturbation, suggesting a clear need to quantify contributions from and losses to these aquifers. Here we develop a stream centric method that combines mass and flow balances to quantify net and gross gains and losses at different spatial scales. We then extend these methods to differentiate between karst conduit and matrix contributions from the aquifer. In the Logan River watershed in Northern Utah we found significant amounts of the river water repeatedly gained and then lost through a 35 km study reach. Further, the direction and amount of water exchanged varied over space, time, and discharge. Streamflow was dominated by discharge of karst conduit groundwater after runoff with increasing, yet still small, fractions of matrix water later in the summer. These findings were combined with geologic information, prior subsurface dye tracing, and chemical sampling to provide additional lines of evidence that repeated groundwater exchanges are likely occurring and river flows are highly dependent on karst aquifer recharge and discharge. Given the large population dependent on karst aquifers throughout the world, there is a continued need to develop simple methods, like those presented here, for determining the resiliency of karst groundwater resources.
","language":"English","publisher":"AGU","doi":"10.1029/2018WR022664","usgsCitation":"Neilson, B., Tennant, H., Barnes, M., Stout, T., Miller, M.P., Gabor, R.S., Jameel, Y., Millington, M., Gelderloos, A., Bowen, G.J., and Brooks, P.D., 2018, Stream‐centric methods for determining groundwater contributions in karst mountain watersheds: Water Resources Research, v. 54, no. 9, p. 6708-6724, https://doi.org/10.1029/2018WR022664.","productDescription":"17 p.","startPage":"6708","endPage":"6724","ipdsId":"IP-094388","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":468507,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018wr022664","text":"Publisher Index Page"},{"id":356385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"9","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-22","publicationStatus":"PW","scienceBaseUri":"5b6fc3c4e4b0f5d57878e8d9","contributors":{"authors":[{"text":"Neilson, Bethany","contributorId":178798,"corporation":false,"usgs":false,"family":"Neilson","given":"Bethany","affiliations":[],"preferred":false,"id":742017,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tennant, Hyrum","contributorId":206880,"corporation":false,"usgs":false,"family":"Tennant","given":"Hyrum","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":742018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnes, Michelle","contributorId":206881,"corporation":false,"usgs":false,"family":"Barnes","given":"Michelle","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":742019,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stout, Trinity","contributorId":206882,"corporation":false,"usgs":false,"family":"Stout","given":"Trinity","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":742020,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":3919,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":742016,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gabor, Rachel S.","contributorId":177335,"corporation":false,"usgs":false,"family":"Gabor","given":"Rachel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":742021,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jameel, Yusef","contributorId":206883,"corporation":false,"usgs":false,"family":"Jameel","given":"Yusef","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":742022,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Millington, Mallory","contributorId":206884,"corporation":false,"usgs":false,"family":"Millington","given":"Mallory","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":742023,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gelderloos, Andrew","contributorId":206885,"corporation":false,"usgs":false,"family":"Gelderloos","given":"Andrew","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":742024,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bowen, Gabriel J.","contributorId":138889,"corporation":false,"usgs":false,"family":"Bowen","given":"Gabriel","email":"","middleInitial":"J.","affiliations":[{"id":12566,"text":"Department of Geology and Geophysics, Unviersity of Utah","active":true,"usgs":false}],"preferred":false,"id":742025,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Brooks, Paul D.","contributorId":139471,"corporation":false,"usgs":false,"family":"Brooks","given":"Paul","email":"","middleInitial":"D.","affiliations":[{"id":12566,"text":"Department of Geology and Geophysics, Unviersity of Utah","active":true,"usgs":false}],"preferred":false,"id":742026,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"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.