{"pageNumber":"371","pageRowStart":"9250","pageSize":"25","recordCount":46619,"records":[{"id":70196235,"text":"70196235 - 2017 - Autonomous acoustic recorders reveal complex patterns in avian detection probability","interactions":[],"lastModifiedDate":"2018-03-27T16:20:59","indexId":"70196235","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Autonomous acoustic recorders reveal complex patterns in avian detection probability","docAbstract":"<p><span>Avian point‐count surveys are typically designed to occur during periods when birds are consistently active and singing, but seasonal and diurnal patterns of detection probability are often not well understood and may vary regionally or between years. We deployed autonomous acoustic recorders to assess how avian availability for detection (i.e., the probability that a bird signals its presence during a recording) varied during the breeding season with time of day, date, and weather‐related variables at multiple subarctic tundra sites in Alaska, USA, 2013–2014. A single observer processed 2,692 10‐minute recordings across 11 site‐years. We used time‐removal methods to assess availability and used generalized additive models to examine patterns of detectability (joint probability of presence, availability, and detection) for 16 common species. Despite lack of distinct dawn or dusk, most species displayed circadian vocalization patterns, with detection rates generally peaking between 0800 hours and 1200 hours but remaining high as late as 2000 hours for some species. Between 2200 hours and 0500 hours, most species’ detection rates dropped to near 0, signaling a distinctive rest period. Detectability dropped sharply for most species in early July. For all species considered, time‐removal analysis indicated nearly 100% likelihood of detection during a 10‐minute recording conducted in June, between 0500 hours and 2000 hours. This indicates that non‐detections during appropriate survey times and dates were attributable to the species’ absence or that silent birds were unlikely to initiate singing during a 10‐minute interval, whereas vocally active birds were singing very frequently. Systematic recordings revealed a gradient of species’ presence at each site, from ubiquitous to incidental. Although the total number of species detected at a site ranged from 16 to 27, we detected only 4 to 15 species on ≥5% of the site's recordings. Recordings provided an unusually detailed and consistent dataset that allowed us to identify, among other things, appropriate survey dates and times for species breeding at northern latitudes. Our results also indicated that more recordings of shorter duration (1–4 min) may be most efficient for detecting passerines.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21285","usgsCitation":"Thompson, S.J., Handel, C.M., and McNew, L.B., 2017, Autonomous acoustic recorders reveal complex patterns in avian detection probability: Journal of Wildlife Management, v. 81, no. 7, p. 1228-1241, https://doi.org/10.1002/jwmg.21285.","productDescription":"14 p.","startPage":"1228","endPage":"1241","ipdsId":"IP-078782","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":461465,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarworks.montana.edu/xmlui/handle/1/14475","text":"External Repository"},{"id":438277,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7B856KG","text":"USGS data release","linkHelpText":"Audio Recording Device Data for Assessing Avian Detectability, Seward Peninsula, Alaska, 2013-2014"},{"id":352803,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"81","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-07","publicationStatus":"PW","scienceBaseUri":"5afee845e4b0da30c1bfc40f","contributors":{"authors":[{"text":"Thompson, Sarah J. 0000-0002-5733-8198 sjthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-5733-8198","contributorId":5434,"corporation":false,"usgs":true,"family":"Thompson","given":"Sarah","email":"sjthompson@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"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":731788,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Handel, Colleen M. 0000-0002-0267-7408 cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":731789,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McNew, Lance B. lmcnew@usgs.gov","contributorId":5086,"corporation":false,"usgs":true,"family":"McNew","given":"Lance","email":"lmcnew@usgs.gov","middleInitial":"B.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":731804,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196229,"text":"70196229 - 2017 - Genetic assessment of the effects of streamscape succession on coho salmon Oncorhynchus kisutch colonization in recently deglaciated streams","interactions":[],"lastModifiedDate":"2018-08-19T10:06:42","indexId":"70196229","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Genetic assessment of the effects of streamscape succession on coho salmon <i>Oncorhynchus kisutch</i> colonization in recently deglaciated streams","title":"Genetic assessment of the effects of streamscape succession on coho salmon Oncorhynchus kisutch colonization in recently deglaciated streams","docAbstract":"<p><span>Measures of genetic diversity within and among populations and historical geomorphological data on stream landscapes were used in model simulations based on approximate Bayesian computation (ABC) to examine hypotheses of the relative importance of stream features (geomorphology and age) associated with colonization events and gene flow for coho salmon&nbsp;</span><i>Oncorhynchus kisutch</i><span><span>&nbsp;</span>breeding in recently deglaciated streams (50–240 years<span>&nbsp;</span></span><span class=\"smallCaps\">b.p</span><span>.) in Glacier Bay National Park (GBNP), Alaska. Population estimates of genetic diversity including heterozygosity and allelic richness declined significantly and monotonically from the oldest and largest to youngest and smallest GBNP streams. Interpopulation variance in allele frequency increased with increasing distance between streams (</span><i>r</i><span><span>&nbsp;</span>= 0·435,<span>&nbsp;</span></span><i>P</i><span><span>&nbsp;</span>&lt; 0·01) and was inversely related to stream age (</span><i>r</i><span><span>&nbsp;</span>= –0·281,<span>&nbsp;</span></span><i>P</i><span><span>&nbsp;</span>&lt; 0·01). The most supported model of colonization involved ongoing or recent (&lt;10 generations before sampling) colonization originating from large populations outside Glacier Bay proper into all other GBNP streams sampled. Results here show that sustained gene flow from large source populations is important to recently established<span>&nbsp;</span></span><i>O. kisutch</i><span><span>&nbsp;</span>metapopulations. Studies that document how genetic and demographic characteristics of newly founded populations vary associated with successional changes in stream habitat are of particular importance to and have significant implications for, restoration of declining or repatriation of extirpated populations in other regions of the species' native range.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/jfb.13337","usgsCitation":"Scribner, K.T., Soiseth, C., McGuire, J.J., Sage, G.K., Thorsteinson, L.K., Nielsen, J.L., and Knudsen, E., 2017, Genetic assessment of the effects of streamscape succession on coho salmon Oncorhynchus kisutch colonization in recently deglaciated streams: Journal of Fish Biology, v. 91, no. 1, p. 195-218, https://doi.org/10.1111/jfb.13337.","productDescription":"24 p.","startPage":"195","endPage":"218","ipdsId":"IP-074390","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":438278,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7V98657","text":"USGS data release","linkHelpText":"Coho Salmon (Oncorhynchus kisutch) Genetic Data, Glacier Bay National Park, Alaska (1994-1999)"},{"id":353006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Glacier Bay National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -137.24395751953125,\n              58.33545085930665\n            ],\n            [\n              -135.3570556640625,\n              58.33545085930665\n            ],\n            [\n              -135.3570556640625,\n              59.08714961054985\n            ],\n            [\n              -137.24395751953125,\n              59.08714961054985\n            ],\n            [\n              -137.24395751953125,\n              58.33545085930665\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"91","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-19","publicationStatus":"PW","scienceBaseUri":"5afee845e4b0da30c1bfc411","contributors":{"authors":[{"text":"Scribner, Kim T.","contributorId":146113,"corporation":false,"usgs":false,"family":"Scribner","given":"Kim","email":"","middleInitial":"T.","affiliations":[{"id":135,"text":"Biological Resources Division","active":false,"usgs":true},{"id":16582,"text":"Department of Fisheries and Wildlife and Department of Zoology, 480 Wilson Rd. 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824","active":true,"usgs":false}],"preferred":false,"id":731759,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soiseth, Chad","contributorId":179804,"corporation":false,"usgs":false,"family":"Soiseth","given":"Chad","email":"","affiliations":[],"preferred":false,"id":731760,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166 jmcguire@whoi.edu","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":177447,"corporation":false,"usgs":false,"family":"McGuire","given":"Jeffrey","email":"jmcguire@whoi.edu","middleInitial":"J.","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":731761,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sage, G. Kevin 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":4348,"corporation":false,"usgs":true,"family":"Sage","given":"G.","email":"ksage@usgs.gov","middleInitial":"Kevin","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":731762,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thorsteinson, Lyman K. lthorsteinson@usgs.gov","contributorId":3000,"corporation":false,"usgs":true,"family":"Thorsteinson","given":"Lyman","email":"lthorsteinson@usgs.gov","middleInitial":"K.","affiliations":[{"id":113,"text":"Alaska Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":731765,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nielsen, J. L.","contributorId":203548,"corporation":false,"usgs":false,"family":"Nielsen","given":"J.","email":"","middleInitial":"L.","affiliations":[{"id":27774,"text":"formerly with USGS","active":true,"usgs":false}],"preferred":false,"id":731763,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Knudsen, E.","contributorId":98264,"corporation":false,"usgs":true,"family":"Knudsen","given":"E.","affiliations":[],"preferred":false,"id":731764,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70191486,"text":"70191486 - 2017 - Novel, continuous monitoring of fine‐scale movement using fixed‐position radiotelemetry arrays and random forest location fingerprinting","interactions":[],"lastModifiedDate":"2018-03-29T13:11:53","indexId":"70191486","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Novel, continuous monitoring of fine‐scale movement using fixed‐position radiotelemetry arrays and random forest location fingerprinting","docAbstract":"<ol class=\"\"><li>Radio‐tag signals from fixed‐position antennas are most often used to indicate presence or absence of individuals, or to estimate individual activity levels from signal strength variation within an antenna's detection zone. The potential of such systems to provide more precise information on tag location and movement has not been explored in great detail in an ecological setting.</li><li>By reversing the roles that transmitters and receivers play in localization methods common to the telecommunications industry, we present a new telemetric tool for accurately estimating the location of tagged individuals from received signal strength values. The methods used to characterize the study area in terms of received signal strength are described, as is the random forest model used for localization. The resulting method is then validated using test data before being applied to true data collected from tagged individuals in the study site.</li><li>Application of the localization method to test data withheld from the learning dataset indicated a low average error over the entire study area (&lt;1&nbsp;m), whereas application of the localization method to real data produced highly probable results consistent with field observations.</li><li>This telemetric approach provided detailed movement data for tagged fish along a single axis (a migratory path) and is particularly useful for monitoring passage along migratory routes. The new methods applied in this study can also be expanded to include multiple axes (<i>x</i>,<i><span>&nbsp;</span>y</i>,<i><span>&nbsp;</span>z</i>) and multiple environments (aquatic and terrestrial) for remotely monitoring wildlife movement.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.12745","usgsCitation":"Harbicht, A.B., Castro-Santos, T.R., Ardren, W.R., Gorsky, D., and Fraser, D., 2017, Novel, continuous monitoring of fine‐scale movement using fixed‐position radiotelemetry arrays and random forest location fingerprinting: Methods in Ecology and Evolution, v. 8, no. 7, p. 850-859, https://doi.org/10.1111/2041-210X.12745.","productDescription":"10 p.","startPage":"850","endPage":"859","ipdsId":"IP-079687","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":469781,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.12745","text":"Publisher Index Page"},{"id":352942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Boquet River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.394,\n              44.366\n            ],\n            [\n              -73.388,\n              44.366\n            ],\n            [\n              -73.388,\n              44.370\n            ],\n            [\n              -73.394,\n              44.370\n            ],\n            [\n              -73.394,\n              44.366\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"7","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-07","publicationStatus":"PW","scienceBaseUri":"5afee854e4b0da30c1bfc424","contributors":{"authors":[{"text":"Harbicht, Andrew B.","contributorId":197056,"corporation":false,"usgs":false,"family":"Harbicht","given":"Andrew","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":712407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":712406,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ardren, William R.","contributorId":184180,"corporation":false,"usgs":false,"family":"Ardren","given":"William","email":"","middleInitial":"R.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":712408,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gorsky, Dimitry","contributorId":169691,"corporation":false,"usgs":false,"family":"Gorsky","given":"Dimitry","affiliations":[],"preferred":false,"id":712409,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fraser, Dylan","contributorId":197057,"corporation":false,"usgs":false,"family":"Fraser","given":"Dylan","affiliations":[],"preferred":false,"id":712410,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70189131,"text":"70189131 - 2017 - Monitoring water content dynamics of biological soil crusts","interactions":[],"lastModifiedDate":"2018-03-29T11:39:58","indexId":"70189131","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring water content dynamics of biological soil crusts","docAbstract":"<p><span>Biological soil crusts (hereafter, “biocrusts”) dominate soil surfaces in nearly all dryland environments. To better understand the influence of water content on carbon (C) exchange, we assessed the ability of dual-probe heat-pulse (DPHP) sensors, installed vertically and angled, to measure changes in near-surface water content. Four DPHP sensors were installed in each of two research plots (eight sensors total) that differed by temperature treatment (control and heated). Responses were compared to horizontally installed water content measurements made with three frequency-domain reflectometry (FDR) sensors in each plot at 5-cm depth. The study was conducted near Moab, Utah, from April through September 2009. Results showed significant differences between sensor technologies: peak water content differences from the DPHP sensors were approximately three times higher than those from the FDR sensors; some of the differences can be explained by the targeted monitoring of biocrust material in the shorter DPHP sensor and by potential signal loss from horizontally installed FDR sensors, or by an oversampling of deeper soil. C-exchange estimates using the DPHP sensors showed a net C loss of 69 and 76&nbsp;g&nbsp;C m</span><sup>−2</sup><span><span>&nbsp;</span>in control and heated plots, respectively. The study illustrates the potential for using the more sensitive data from shallow installations for estimating C exchange in biocrusts.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2017.03.004","usgsCitation":"Young, M.H., Fenstermaker, L.F., and Belnap, J., 2017, Monitoring water content dynamics of biological soil crusts: Journal of Arid Environments, v. 142, p. 41-49, https://doi.org/10.1016/j.jaridenv.2017.03.004.","productDescription":"9 p.","startPage":"41","endPage":"49","ipdsId":"IP-079049","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469728,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1413765","text":"Publisher Index Page"},{"id":352934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"142","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee854e4b0da30c1bfc428","contributors":{"authors":[{"text":"Young, Michael H.","contributorId":203634,"corporation":false,"usgs":false,"family":"Young","given":"Michael","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":703101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fenstermaker, Lynn F.","contributorId":194059,"corporation":false,"usgs":false,"family":"Fenstermaker","given":"Lynn","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":703102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":703100,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191078,"text":"70191078 - 2017 - Short-term ecological consequences of collaborative restoration treatments in ponderosa pine forests of Colorado","interactions":[],"lastModifiedDate":"2017-09-25T11:38:59","indexId":"70191078","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Short-term ecological consequences of collaborative restoration treatments in ponderosa pine forests of Colorado","docAbstract":"<p><span>Ecological restoration treatments are being implemented at an increasing rate in ponderosa pine and other dry conifer forests across the western United States, via the USDA Forest Service’s Collaborative Forest Landscape Restoration (CFLR) program. In this program, collaborative stakeholder groups work with National Forests (NFs) to adaptively implement and monitor ecological restoration treatments intended to offset the effects of many decades of anthropogenic stressors. We initiated a novel study to expand the scope of treatment effectiveness monitoring efforts in one of the first CFLR landscapes, Colorado’s Front Range. We used a Before/After/Control/Impact framework to evaluate the short-term consequences of treatments on numerous ecological properties. We collected pre-treatment and one year post-treatment data on NF and partner agencies’ lands, in 66 plots distributed across seven treatment units and nearby untreated areas. Our results reflected progress toward several treatment objectives: treated areas had lower tree density and basal area, greater openness, no increase in exotic understory plants, no decrease in native understory plants, and no decrease in use by tree squirrels and ungulates. However, some findings suggested the need for adaptive modification of both treatment prescriptions and monitoring protocols: treatments did not promote heterogeneity of stand structure, and monitoring methods may not have been robust enough to detect changes in surface fuels. Our study highlights both the effective aspects of these restoration treatments, and the importance of initiating and continuing collaborative science-based monitoring to improve the outcomes of broad-scale forest restoration efforts.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2017.03.008","collaboration":"Paula Fornwalt; Jonas Feinstein","usgsCitation":"Briggs, J.S., Fornwalt, P.J., and Feinstein, J.A., 2017, Short-term ecological consequences of collaborative restoration treatments in ponderosa pine forests of Colorado: Forest Ecology and Management, v. 395, p. 69-80, https://doi.org/10.1016/j.foreco.2017.03.008.","productDescription":"12 p.","startPage":"69","endPage":"80","ipdsId":"IP-079089","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":469769,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2017.03.008","text":"Publisher Index Page"},{"id":346044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","volume":"395","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59ca15ade4b017cf314041c3","contributors":{"authors":[{"text":"Briggs, Jenny S. 0000-0001-7454-6928 jsbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-7454-6928","contributorId":3087,"corporation":false,"usgs":true,"family":"Briggs","given":"Jenny","email":"jsbriggs@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":711089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fornwalt, Paula J.","contributorId":196676,"corporation":false,"usgs":false,"family":"Fornwalt","given":"Paula","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":711090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feinstein, Jonas A.","contributorId":196677,"corporation":false,"usgs":false,"family":"Feinstein","given":"Jonas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":711091,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192522,"text":"70192522 - 2017 - Species distribution models for a migratory bird based on citizen science and satellite tracking data","interactions":[],"lastModifiedDate":"2017-10-26T13:33:14","indexId":"70192522","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Species distribution models for a migratory bird based on citizen science and satellite tracking data","docAbstract":"<p><span>Species distribution models can provide critical baseline distribution information for the conservation of poorly understood species. Here, we compared the performance of band-tailed pigeon (</span><i>Patagioenas fasciata)</i><span><span>&nbsp;</span>species distribution models created using Maxent and derived from two separate presence-only occurrence data sources in New Mexico: 1) satellite tracked birds and 2) observations reported in eBird basic data set. Both models had good accuracy (test AUC&nbsp;&gt;&nbsp;0.8 and True Skill Statistic&nbsp;&gt;&nbsp;0.4), and high overlap between suitability scores (</span><i>I</i><span><span>&nbsp;</span>statistic 0.786) and suitable habitat patches (relative rank 0.639). Our results suggest that, at the state-wide level, eBird occurrence data can effectively model similar species distributions as satellite tracking data. Climate change models for the band-tailed pigeon predict a 35% loss in area of suitable climate by 2070 if CO</span><sub>2</sub><span><span>&nbsp;</span>emissions drop to 1990 levels by 2100, and a 45% loss by 2070 if we continue current CO</span><sub>2</sub><span><span>&nbsp;</span>emission levels through the end of the century. These numbers may be conservative given the predicted increase in drought, wildfire, and forest pest impacts to the coniferous forests the species inhabits in New Mexico. The northern portion of the species’ range in New Mexico is predicted to be the most viable through time.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2017.08.001","usgsCitation":"Coxen, C.L., Frey, J.K., Carleton, S.A., and Collins, D.P., 2017, Species distribution models for a migratory bird based on citizen science and satellite tracking data: Global Ecology and Conservation, v. 11, p. 298-311, https://doi.org/10.1016/j.gecco.2017.08.001.","productDescription":"14 p.","startPage":"298","endPage":"311","ipdsId":"IP-087235","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469720,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2017.08.001","text":"Publisher Index Page"},{"id":347476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New 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scarleton@usgs.gov","orcid":"https://orcid.org/0000-0001-9609-650X","contributorId":4060,"corporation":false,"usgs":true,"family":"Carleton","given":"Scott","email":"scarleton@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collins, Daniel P.","contributorId":198065,"corporation":false,"usgs":false,"family":"Collins","given":"Daniel","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":716380,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70195361,"text":"70195361 - 2017 - Geomorphology of comet 67P/Churyumov–Gerasimenko","interactions":[],"lastModifiedDate":"2018-02-12T11:10:36","indexId":"70195361","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5624,"text":"Monthly Notices of the Royal Astronomical Society","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphology of comet 67P/Churyumov–Gerasimenko","docAbstract":"<p><span>We present a global geomorphological map of comet 67P/Churyumov–Gerasimenko (67P/C-G) using data acquired by the&nbsp;</span><i>Rosetta</i><span><span>&nbsp;</span>Orbiter’s OSIRIS Narrow Angle Camera. The images used in our study were acquired between 2014 August and 2015 May, before 67P/C-G passed through perihelion. Imagery of the Southern hemisphere was included in our study, allowing us to compare the contrasting hemispheres of 67P/C-G in a single study. Our work also puts into greater context the morphologies studied in previous works, and also the morphologies observed on previously visited cometary nuclei. Relative to other nuclei, 67P/C-G appears most similar to 81P/Wild 2, with a topographically heterogeneous surface dominated by smooth-floored pits. Our mapping describes the landscapes of 67P/C-G when they were first observed by<span>&nbsp;</span></span><i>Rosetta</i><span>, and our map can be used to detect changes in surface morphologies after its perihelion passage. Our mapping reveals strong latitudinal dependences for emplaced units and a highly heterogeneous surface. Layered bedrock units that represent the exposed nucleus of 67P/C-G are dominant at southern latitudes, while topographically smooth, dust covered regions dominate the Northern hemisphere. Equatorial latitudes are dominated by smooth terrain units that show evidence for flow structures. We observe no obvious differences between the comet’s two lobes, with the only longitudinal variations being the Imhotep and Hatmehit basins. These correlations suggest a strong seasonal forcing on the surface evolution of 67P/C-G, where materials are transported from the Southern hemisphere to Northern hemisphere basins over multiple orbital time-scales.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/mnras/stx1096","usgsCitation":"Birch, S.P., Tang, Y., Hayes, A.G., Kirk, R.L., Bodewitz, D., Campins, H., Fernandez, Y., de Freitas Bart, R., Kutsop, N.W., Sierks, H., Soderblom, J.M., Squyres, S.W., and Vincent, J., 2017, Geomorphology of comet 67P/Churyumov–Gerasimenko: Monthly Notices of the Royal Astronomical Society, v. 469, no. Suppl_2, p. S50-S67, https://doi.org/10.1093/mnras/stx1096.","productDescription":"18 p.","startPage":"S50","endPage":"S67","ipdsId":"IP-083959","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":469705,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/mnras/stx1096","text":"Publisher Index Page"},{"id":351464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"469","issue":"Suppl_2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-06","publicationStatus":"PW","scienceBaseUri":"5afee845e4b0da30c1bfc415","contributors":{"authors":[{"text":"Birch, Samuel P. D.","contributorId":202322,"corporation":false,"usgs":false,"family":"Birch","given":"Samuel","email":"","middleInitial":"P. D.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":728126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tang, Y.","contributorId":202323,"corporation":false,"usgs":false,"family":"Tang","given":"Y.","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":728127,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, A. G.","contributorId":202325,"corporation":false,"usgs":false,"family":"Hayes","given":"A.","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":728129,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kirk, Randolph L. 0000-0003-0842-9226 rkirk@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-9226","contributorId":2765,"corporation":false,"usgs":true,"family":"Kirk","given":"Randolph","email":"rkirk@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":728125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bodewitz, D.","contributorId":202332,"corporation":false,"usgs":false,"family":"Bodewitz","given":"D.","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":728137,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Campins, H.","contributorId":202330,"corporation":false,"usgs":false,"family":"Campins","given":"H.","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":728135,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fernandez, Y.","contributorId":202331,"corporation":false,"usgs":false,"family":"Fernandez","given":"Y.","email":"","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":728136,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"de Freitas Bart, R.","contributorId":202326,"corporation":false,"usgs":false,"family":"de Freitas Bart","given":"R.","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":728131,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kutsop, N. W.","contributorId":202324,"corporation":false,"usgs":false,"family":"Kutsop","given":"N.","email":"","middleInitial":"W.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":728128,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sierks, H.","contributorId":202327,"corporation":false,"usgs":false,"family":"Sierks","given":"H.","email":"","affiliations":[{"id":36389,"text":"Max Planck Institute","active":true,"usgs":false}],"preferred":false,"id":728132,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Soderblom, J. M.","contributorId":202329,"corporation":false,"usgs":false,"family":"Soderblom","given":"J.","email":"","middleInitial":"M.","affiliations":[{"id":36390,"text":"Massachussets Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":728134,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Squyres, S. W.","contributorId":172124,"corporation":false,"usgs":false,"family":"Squyres","given":"S.","email":"","middleInitial":"W.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":728130,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Vincent, J.-B.","contributorId":202328,"corporation":false,"usgs":false,"family":"Vincent","given":"J.-B.","email":"","affiliations":[{"id":36389,"text":"Max Planck Institute","active":true,"usgs":false}],"preferred":false,"id":728133,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70192800,"text":"70192800 - 2017 - A database and probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention in the United States","interactions":[],"lastModifiedDate":"2018-07-31T14:02:18","indexId":"70192800","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5215,"text":"Energy Procedia","onlineIssn":"1876-6102","active":true,"publicationSubtype":{"id":10}},"title":"A database and probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention in the United States","docAbstract":"<p><span>The U.S. Geological Survey (USGS) has developed an assessment methodology for estimating the potential incremental technically recoverable oil resources resulting from carbon dioxide-enhanced oil recovery (CO</span><sub>2</sub><span>-EOR) in reservoirs with appropriate depth, pressure, and oil composition. The methodology also includes a procedure for estimating the CO</span><sub>2</sub><span><span>&nbsp;</span>that remains in the reservoir after the CO</span><sub>2</sub><span>-EOR process is complete. The methodology relies on a reservoir-level database that incorporates commercially available geologic and engineering data. The mathematical calculations of this assessment methodology were tested and produced realistic results for the Permian Basin Horseshoe Atoll, Upper Pennsylvanian-Wolfcampian Play (Texas, USA). The USGS plans to use the new methodology to conduct an assessment of technically recoverable hydrocarbons and associated CO</span><sub>2&nbsp;</sub><span>sequestration resulting from CO</span><sub>2</sub><span>-EOR in the United States.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.egypro.2017.03.1847","usgsCitation":"Warwick, P.D., Verma, M., Attanasi, E., Olea, R.A., Blondes, M., Freeman, P., Brennan, S.T., Merrill, M., Jahediesfanjani, H., Roueche, J., and Lohr, C., 2017, A database and probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention in the United States: Energy Procedia, v. 114, p. 7055-7059, https://doi.org/10.1016/j.egypro.2017.03.1847.","productDescription":"5 p.","startPage":"7055","endPage":"7059","ipdsId":"IP-079968","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":469711,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.egypro.2017.03.1847","text":"Publisher Index Page"},{"id":350441,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"114","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb8fe4b06e28e9c2328e","contributors":{"authors":[{"text":"Warwick, Peter D. 0000-0002-3152-7783 pwarwick@usgs.gov","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":762,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter","email":"pwarwick@usgs.gov","middleInitial":"D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":716978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verma, Mahendra K. mverma@usgs.gov","contributorId":1027,"corporation":false,"usgs":true,"family":"Verma","given":"Mahendra 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,{"id":70194501,"text":"70194501 - 2017 - Heat as a groundwater tracer in shallow and deep heterogeneous media: Analytical solution, spreadsheet tool, and field applications","interactions":[],"lastModifiedDate":"2018-03-29T15:54:42","indexId":"70194501","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Heat as a groundwater tracer in shallow and deep heterogeneous media: Analytical solution, spreadsheet tool, and field applications","docAbstract":"<p><span>Groundwater flow advects heat, and thus, the deviation of subsurface temperatures from an expected conduction‐dominated regime can be analysed to estimate vertical water fluxes. A number of analytical approaches have been proposed for using heat as a groundwater tracer, and these have typically assumed a homogeneous medium. However, heterogeneous thermal properties are ubiquitous in subsurface environments, both at the scale of geologic strata and at finer scales in streambeds. Herein, we apply the analytical solution of Shan and Bodvarsson (2004), developed for estimating vertical water fluxes in layered systems, in 2 new environments distinct from previous vadose zone applications. The utility of the solution for studying groundwater‐surface water exchange is demonstrated using temperature</span><span>&nbsp;data collected from an upwelling streambed with sediment layers, and a simple sensitivity analysis using these data indicates the solution is relatively robust. Also, a deeper temperature profile recorded in a borehole in South Australia is analysed to estimate deeper water fluxes. The analytical solution is able to match observed thermal gradients, including the change in slope at sediment interfaces. Results indicate that not accounting for layering can yield errors in the magnitude and even direction of the inferred Darcy fluxes. A simple automated spreadsheet tool (Flux‐LM) is presented to allow users to input temperature and layer data and solve the inverse problem to estimate groundwater flux rates from shallow (e.g., &lt;1&nbsp;m) or deep (e.g., up to 100&nbsp;m) profiles. The solution is not transient, and thus, it should be cautiously applied where diel signals propagate or in deeper zones where multi‐decadal surface signals have disturbed subsurface thermal regimes.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11216","usgsCitation":"Kurylyk, B.L., Irvine, D.J., Carey, S.K., Briggs, M.A., Werkema, D.D., and Bonham, M., 2017, Heat as a groundwater tracer in shallow and deep heterogeneous media: Analytical solution, spreadsheet tool, and field applications: Hydrological Processes, v. 31, no. 14, p. 2648-2661, https://doi.org/10.1002/hyp.11216.","productDescription":"14 p.","startPage":"2648","endPage":"2661","ipdsId":"IP-083382","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"links":[{"id":469721,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6260938","text":"External Repository"},{"id":438279,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NZ85VG","text":"USGS data release","linkHelpText":"Streambed temperature data for the manuscript: Heat as a hydrologic tracer in shallow and deep heterogeneous media: analytical solution, spreadsheet tool, and field applications"},{"id":352969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"14","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee845e4b0da30c1bfc417","contributors":{"authors":[{"text":"Kurylyk, Barret L.","contributorId":176296,"corporation":false,"usgs":false,"family":"Kurylyk","given":"Barret","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":724119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irvine, Dylan J.","contributorId":190404,"corporation":false,"usgs":false,"family":"Irvine","given":"Dylan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":724120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carey, Sean K.","contributorId":201022,"corporation":false,"usgs":false,"family":"Carey","given":"Sean","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":724121,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":724118,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Werkema, Dale D.","contributorId":40488,"corporation":false,"usgs":false,"family":"Werkema","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":724122,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bonham, Mariah","contributorId":199839,"corporation":false,"usgs":false,"family":"Bonham","given":"Mariah","email":"","affiliations":[],"preferred":false,"id":724123,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192089,"text":"70192089 - 2017 - Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic time series from Landsat and the MODIS BRDF/NBAR/albedo product","interactions":[],"lastModifiedDate":"2017-10-23T15:52:11","indexId":"70192089","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2027,"text":"International Journal of Applied Earth Observation and Geoinformation","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic time series from Landsat and the MODIS BRDF/NBAR/albedo product","docAbstract":"<p><span>Seasonal vegetation phenology can significantly alter surface albedo which in turn affects the global energy balance and the albedo warming/cooling feedbacks that impact climate change. To monitor and quantify the surface dynamics of heterogeneous landscapes, high temporal and spatial resolution synthetic time series of albedo and the enhanced vegetation index (EVI) were generated from the 500</span><span>&nbsp;</span><span>m Moderate Resolution Imaging Spectroradiometer (MODIS) operational Collection V006 daily BRDF/NBAR/albedo products and 30</span><span>&nbsp;</span><span>m Landsat 5 albedo and near-nadir reflectance data through the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The traditional Landsat Albedo (Shuai et al., 2011) makes use of the MODIS BRDF/Albedo products (MCD43) by assigning appropriate BRDFs from coincident MODIS products to each Landsat image to generate a 30</span><span>&nbsp;</span><span>m Landsat albedo product for that acquisition date. The available cloud free Landsat 5 albedos (due to clouds, generated every 16</span><span>&nbsp;</span><span>days at best) were used in conjunction with the daily MODIS albedos to determine the appropriate 30</span><span>&nbsp;</span><span>m albedos for the intervening daily time steps in this study. These enhanced daily 30</span><span>&nbsp;</span><span>m spatial resolution synthetic time series were then used to track albedo and vegetation phenology dynamics over three Ameriflux tower sites (Harvard Forest in 2007, Santa Rita in 2011 and Walker Branch in 2005). These Ameriflux sites were chosen as they are all quite nearby new towers coming on line for the National Ecological Observatory Network (NEON), and thus represent locations which will be served by spatially paired albedo measures in the near future. The availability of data from the NEON towers will greatly expand the sources of tower albedometer data available for evaluation of satellite products. At these three Ameriflux tower sites the synthetic time series of broadband shortwave albedos were evaluated using the tower albedo measurements with a Root Mean Square Error (RMSE) less than 0.013 and a bias within the range of ±0.006. These synthetic time series provide much greater spatial detail than the 500</span><span>&nbsp;</span><span>m gridded MODIS data, especially over more heterogeneous surfaces, which improves the efforts to characterize and monitor the spatial variation across species and communities. The mean of the difference between maximum and minimum synthetic time series of albedo within the MODIS pixels over a subset of satellite data of Harvard Forest (16</span><span>&nbsp;</span><span>km by 14</span><span>&nbsp;</span><span>km) was as high as 0.2 during the snow-covered period and reduced to around 0.1 during the snow-free period. Similarly, we have used STARFM to also couple MODIS Nadir BRDF Adjusted Reflectances (NBAR) values with Landsat 5 reflectances to generate daily synthetic times series of NBAR and thus Enhanced Vegetation Index (NBAR-EVI) at a 30</span><span>&nbsp;</span><span>m resolution. While normally STARFM is used with directional reflectances, the use of the view angle corrected daily MODIS NBAR values will provide more consistent time series. These synthetic times series of EVI are shown to capture seasonal vegetation dynamics with finer spatial and temporal details, especially over heterogeneous land surfaces.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jag.2017.03.008","usgsCitation":"Wang, Z., Schaaf, C.B., Sun, Q., Kim, J., Erb, A.M., Gao, F., Roman, M.O., Yang, Y., Petroy, S., Taylor, J., Masek, J.G., Morisette, J.T., Zhang, X., and Papuga, S.A., 2017, Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic time series from Landsat and the MODIS BRDF/NBAR/albedo product: International Journal of Applied Earth Observation and Geoinformation, v. 59, p. 104-117, https://doi.org/10.1016/j.jag.2017.03.008.","productDescription":"14 p.","startPage":"104","endPage":"117","ipdsId":"IP-083678","costCenters":[{"id":477,"text":"North Central Climate Science 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Qingson","contributorId":197719,"corporation":false,"usgs":false,"family":"Sun","given":"Qingson","email":"","affiliations":[],"preferred":false,"id":714134,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kim, JiHyun","contributorId":197720,"corporation":false,"usgs":false,"family":"Kim","given":"JiHyun","email":"","affiliations":[],"preferred":false,"id":714135,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erb, Angela M.","contributorId":197721,"corporation":false,"usgs":false,"family":"Erb","given":"Angela","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":714136,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gao, Feng 0000-0002-1865-2846","orcid":"https://orcid.org/0000-0002-1865-2846","contributorId":70671,"corporation":false,"usgs":false,"family":"Gao","given":"Feng","email":"","affiliations":[{"id":6622,"text":"US Department of 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Jeffrey","contributorId":197724,"corporation":false,"usgs":false,"family":"Taylor","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":714141,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Masek, Jeffrey G.","contributorId":197725,"corporation":false,"usgs":false,"family":"Masek","given":"Jeffrey","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":714142,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":714131,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Zhang, Xiaoyang","contributorId":197726,"corporation":false,"usgs":false,"family":"Zhang","given":"Xiaoyang","email":"","affiliations":[],"preferred":false,"id":714143,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Papuga, Shirley A.","contributorId":197727,"corporation":false,"usgs":false,"family":"Papuga","given":"Shirley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":714144,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70191873,"text":"70191873 - 2017 - An “EAR” on environmental surveillance and monitoring: A case study on the use of Exposure–Activity Ratios (EARs) to prioritize sites, chemicals, and bioactivities of concern in Great Lakes waters","interactions":[],"lastModifiedDate":"2017-10-18T15:17:45","indexId":"70191873","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"An “EAR” on environmental surveillance and monitoring: A case study on the use of Exposure–Activity Ratios (EARs) to prioritize sites, chemicals, and bioactivities of concern in Great Lakes waters","docAbstract":"<p><span>Current environmental monitoring approaches focus primarily on chemical occurrence. However, based on concentration alone, it can be difficult to identify which compounds may be of toxicological concern and should be prioritized for further monitoring, in-depth testing, or management. This can be problematic because toxicological characterization is lacking for many emerging contaminants. New sources of high-throughput screening (HTS) data, such as the ToxCast database, which contains information for over 9000 compounds screened through up to 1100 bioassays, are now available. Integrated analysis of chemical occurrence data with HTS data offers new opportunities to prioritize chemicals, sites, or biological effects for further investigation based on concentrations detected in the environment linked to relative potencies in pathway-based bioassays. As a case study, chemical occurrence data from a 2012 study in the Great Lakes Basin along with the ToxCast effects database were used to calculate exposure–activity ratios (EARs) as a prioritization tool. Technical considerations of data processing and use of the ToxCast database are presented and discussed. EAR prioritization identified multiple sites, biological pathways, and chemicals that warrant further investigation. Prioritized bioactivities from the EAR analysis were linked to discrete adverse outcome pathways to identify potential adverse outcomes and biomarkers for use in subsequent monitoring efforts.</span></p>","language":"English","publisher":"ACS","doi":"10.1021/acs.est.7b01613","usgsCitation":"Blackwell, B., Ankley, G., Corsi, S., DeCicco, L.A., Houck, K., Judson, R.S., Li, S., Martin, M.T., Murphy, E., Schroeder, A.L., Smith, E., Swintek, J., and Villeneuve, D.L., 2017, An “EAR” on environmental surveillance and monitoring: A case study on the use of Exposure–Activity Ratios (EARs) to prioritize sites, chemicals, and bioactivities of concern in Great Lakes waters: Environmental Science & Technology, v. 51, no. 15, p. 8713-8724, https://doi.org/10.1021/acs.est.7b01613.","productDescription":"12 p.","startPage":"8713","endPage":"8724","ipdsId":"IP-088064","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":469709,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6132252","text":"External Repository"},{"id":346899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes","volume":"51","issue":"15","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-18","publicationStatus":"PW","scienceBaseUri":"59e86835e4b05fe04cd4d1f0","contributors":{"authors":[{"text":"Blackwell, Brett R.","contributorId":173601,"corporation":false,"usgs":false,"family":"Blackwell","given":"Brett R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":713482,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ankley, Gerald T.","contributorId":177970,"corporation":false,"usgs":false,"family":"Ankley","given":"Gerald T.","affiliations":[{"id":13485,"text":"U.S. Environmental Protection Agency, Duluth, MN","active":true,"usgs":false}],"preferred":false,"id":713483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713481,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeCicco, Laura A. 0000-0002-3915-9487 ldecicco@usgs.gov","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":174716,"corporation":false,"usgs":true,"family":"DeCicco","given":"Laura","email":"ldecicco@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":713484,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Houck, Kieth A.","contributorId":197428,"corporation":false,"usgs":false,"family":"Houck","given":"Kieth A.","affiliations":[],"preferred":false,"id":713485,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Judson, Richard S.","contributorId":197429,"corporation":false,"usgs":false,"family":"Judson","given":"Richard","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":713486,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Li, Shibin","contributorId":197430,"corporation":false,"usgs":false,"family":"Li","given":"Shibin","email":"","affiliations":[],"preferred":false,"id":713487,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Martin, Matthew T.","contributorId":197431,"corporation":false,"usgs":false,"family":"Martin","given":"Matthew","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":713488,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Murphy, Elizabeth","contributorId":197432,"corporation":false,"usgs":false,"family":"Murphy","given":"Elizabeth","affiliations":[],"preferred":false,"id":713489,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Schroeder, Anthony L.","contributorId":173596,"corporation":false,"usgs":false,"family":"Schroeder","given":"Anthony","email":"","middleInitial":"L.","affiliations":[{"id":12503,"text":"University of Minnesota - Saint Paul","active":true,"usgs":false},{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":713490,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Smith, Edwin R.","contributorId":197434,"corporation":false,"usgs":false,"family":"Smith","given":"Edwin R.","affiliations":[],"preferred":false,"id":713491,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Swintek, Joe","contributorId":197435,"corporation":false,"usgs":false,"family":"Swintek","given":"Joe","email":"","affiliations":[],"preferred":false,"id":713492,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Villeneuve, Daniel L.","contributorId":32091,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Daniel","email":"","middleInitial":"L.","affiliations":[{"id":13485,"text":"U.S. Environmental Protection Agency, Duluth, MN","active":true,"usgs":false}],"preferred":false,"id":713493,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70190050,"text":"70190050 - 2017 - Integration of vegetation community spatial data into a prescribed fire planning process at Shenandoah National Park, Virginia (USA)","interactions":[],"lastModifiedDate":"2018-03-28T14:27:13","indexId":"70190050","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2821,"text":"Natural Areas Journal","active":true,"publicationSubtype":{"id":10}},"title":"Integration of vegetation community spatial data into a prescribed fire planning process at Shenandoah National Park, Virginia (USA)","docAbstract":"<p><span>Many eastern forest communities depend on fire for regeneration or are enhanced by fire as a restoration practice. However, the use of prescribed fire in the mesic forested environments and the densely populated regions of the eastern United States has been limited. The objective of our research was to develop a science-based approach to prioritizing the use of prescribed fire in appropriate forest types in the eastern United States based on a set of desired management outcomes. Through a process of expert elicitation and data analysis, we assessed and integrated recent vegetation community mapping results along with other available spatial data layers into a spatial prioritization tool for prescribed fire planning at Shenandoah National Park (Virginia, USA). The integration of vegetation spatial data allowed for development of per-pixel priority rankings and exclusion areas enabling precise targeting of fire management activities on the ground, as well as a park-wide ranking of fire planning compartments. We demonstrate the use and evaluation of this approach through implementation and monitoring of a prescribed burn and show that progress is being made toward desired conditions. Integration of spatial data into the fire planning process has served as a collaborative tool for the implementation of prescribed fire projects, which assures projects will be planned in the most appropriate areas to meet objectives that are supported by current science.</span></p>","language":"English","publisher":"Natural Areas Association","doi":"10.3375/043.037.0312","usgsCitation":"Young, J.A., Mahan, C.G., and Forder, M., 2017, Integration of vegetation community spatial data into a prescribed fire planning process at Shenandoah National Park, Virginia (USA): Natural Areas Journal, v. 37, no. 3, p. 394-405, https://doi.org/10.3375/043.037.0312.","productDescription":"12 p.","startPage":"394","endPage":"405","ipdsId":"IP-066214","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":352864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah National Park","volume":"37","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee854e4b0da30c1bfc426","contributors":{"authors":[{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":707326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahan, Carolyn G.","contributorId":146582,"corporation":false,"usgs":false,"family":"Mahan","given":"Carolyn","email":"","middleInitial":"G.","affiliations":[{"id":12754,"text":"Penn State University Altoona","active":true,"usgs":false}],"preferred":false,"id":707327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forder, Melissa","contributorId":195517,"corporation":false,"usgs":false,"family":"Forder","given":"Melissa","email":"","affiliations":[],"preferred":false,"id":707328,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191900,"text":"70191900 - 2017 - Spatiotemporal analysis of changes in lode mining claims around the McDermitt Caldera, northern Nevada and southern Oregon","interactions":[],"lastModifiedDate":"2018-02-15T14:29:28","indexId":"70191900","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2832,"text":"Natural Resources Research","onlineIssn":"1573-8981","printIssn":"1520-7439","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal analysis of changes in lode mining claims around the McDermitt Caldera, northern Nevada and southern Oregon","docAbstract":"<p><span>Resource managers and agencies involved with planning for future federal land needs are required to complete an assessment of and forecast for future land use every ten years. Predicting mining activities on federal lands is difficult as current regulations do not require disclosure of exploration results. In these cases, historic mining claims may serve as a useful proxy for determining where mining-related activities may occur. We assess the utility of using a space–time cube (STC) and associated analyses to evaluate and characterize mining claim activities around the McDermitt Caldera in northern Nevada and southern Oregon. The most significant advantage of arranging the mining claim data into a STC is the ability to visualize and compare the data, which allows scientists to better understand patterns and results. Additional analyses of the STC (i.e., Trend, Emerging Hot Spot, Hot Spot, and Cluster and Outlier Analyses) provide extra insights into the data and may aid in predicting future mining claim activities.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s11053-017-9324-9","usgsCitation":"Coyan, J.A., Zientek, M.L., and Mihalasky, M.J., 2017, Spatiotemporal analysis of changes in lode mining claims around the McDermitt Caldera, northern Nevada and southern Oregon: Natural Resources Research, v. 26, no. 3, p. 319-337, https://doi.org/10.1007/s11053-017-9324-9.","productDescription":"19 p.","startPage":"319","endPage":"337","ipdsId":"IP-081467","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":461467,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11053-017-9324-9","text":"Publisher Index Page"},{"id":346970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Oregon","otherGeospatial":"McDermitt Caldera","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.20190429687501,\n              41.64726212881368\n            ],\n            [\n              -117.81463623046875,\n              41.64726212881368\n            ],\n            [\n              -117.81463623046875,\n              42.09210825254959\n            ],\n            [\n              -118.20190429687501,\n              42.09210825254959\n            ],\n            [\n              -118.20190429687501,\n              41.64726212881368\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"26","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-08","publicationStatus":"PW","scienceBaseUri":"59e9b994e4b05fe04cd65c86","contributors":{"authors":[{"text":"Coyan, Joshua A. 0000-0002-8450-7364 jcoyan@usgs.gov","orcid":"https://orcid.org/0000-0002-8450-7364","contributorId":197481,"corporation":false,"usgs":true,"family":"Coyan","given":"Joshua","email":"jcoyan@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":713589,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zientek, Michael L. 0000-0002-8522-9626 mzientek@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":2420,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael","email":"mzientek@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":713591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mihalasky, Mark J. 0000-0002-0082-3029 mjm@usgs.gov","orcid":"https://orcid.org/0000-0002-0082-3029","contributorId":3692,"corporation":false,"usgs":true,"family":"Mihalasky","given":"Mark","email":"mjm@usgs.gov","middleInitial":"J.","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":false,"id":713590,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192997,"text":"70192997 - 2017 - Mapping informal small-scale mining features in a data-sparse tropical environment with a small UAS","interactions":[],"lastModifiedDate":"2022-12-22T17:49:02.708399","indexId":"70192997","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5559,"text":"Journal of Unmanned Vehicle Systems","active":true,"publicationSubtype":{"id":10}},"title":"Mapping informal small-scale mining features in a data-sparse tropical environment with a small UAS","docAbstract":"<p><span>This study evaluates the use of a small unmanned aerial system (UAS) to collect imagery over artisanal mining sites in West Africa. The purpose of this study is to consider how very high-resolution imagery and digital surface models (DSMs) derived from structure-from-motion (SfM) photogrammetric techniques from a small UAS can fill the gap in geospatial data collection between satellite imagery and data gathered during field work to map and monitor informal mining sites in tropical environments. The study compares both wide-angle and narrow field of view camera systems in the collection and analysis of high-resolution orthoimages and DSMs of artisanal mining pits. The results of the study indicate that UAS imagery and SfM photogrammetric techniques permit DSMs to be produced with a high degree of precision and relative accuracy, but highlight the challenges of mapping small artisanal mining pits in remote and data sparse terrain.</span></p>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/juvs-2017-0002","usgsCitation":"Chirico, P.G., and Dewitt, J., 2017, Mapping informal small-scale mining features in a data-sparse tropical environment with a small UAS: Journal of Unmanned Vehicle Systems, v. 5, no. 3, p. 69-91, https://doi.org/10.1139/juvs-2017-0002.","productDescription":"23 p.","startPage":"69","endPage":"91","ipdsId":"IP-083399","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":349228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347668,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cdnsciencepub.com/doi/full/10.1139/juvs-2017-0002"}],"country":"Guinea","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-8.4393,7.68604],[-8.72212,7.71167],[-8.92606,7.30904],[-9.20879,7.31392],[-9.40335,7.52691],[-9.33728,7.92853],[-9.75534,8.54106],[-10.01657,8.4285],[-10.23009,8.40621],[-10.50548,8.3489],[-10.49432,8.71554],[-10.65477,8.97718],[-10.6224,9.26791],[-10.83915,9.68825],[-11.11748,10.04587],[-11.91728,10.04698],[-12.15034,9.85857],[-12.42593,9.83583],[-12.59672,9.62019],[-12.71196,9.34271],[-13.24655,8.90305],[-13.68515,9.49474],[-14.07404,9.88617],[-14.33008,10.01572],[-14.5797,10.21447],[-14.69323,10.6563],[-14.83955,10.87657],[-15.13031,11.04041],[-14.68569,11.52782],[-14.38219,11.50927],[-14.12141,11.67712],[-13.9008,11.67872],[-13.74316,11.81127],[-13.82827,12.14264],[-13.71874,12.24719],[-13.70048,12.58618],[-13.21782,12.57587],[-12.49905,12.33209],[-12.2786,12.35444],[-12.20356,12.46565],[-11.6583,12.38658],[-11.51394,12.44299],[-11.45617,12.07683],[-11.29757,12.07797],[-11.03656,12.21124],[-10.87083,12.17789],[-10.59322,11.92398],[-10.16521,11.84408],[-9.89099,12.06048],[-9.56791,12.19424],[-9.32762,12.33429],[-9.12747,12.30806],[-8.90526,12.08836],[-8.7861,11.81256],[-8.3763,11.39365],[-8.58131,11.13625],[-8.62032,10.81089],[-8.40731,10.90926],[-8.28236,10.7926],[-8.33538,10.49481],[-8.02994,10.20653],[-8.22934,10.12902],[-8.30962,9.78953],[-8.07911,9.37622],[-7.8321,8.5757],[-8.2035,8.45545],[-8.29905,8.31644],[-8.22179,8.12333],[-8.2807,7.68718],[-8.4393,7.68604]]]},\"properties\":{\"name\":\"Guinea\"}}]}","volume":"5","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb8ee4b06e28e9c2328c","contributors":{"authors":[{"text":"Chirico, Peter G. 0000-0001-8375-5342 pchirico@usgs.gov","orcid":"https://orcid.org/0000-0001-8375-5342","contributorId":195555,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter","email":"pchirico@usgs.gov","middleInitial":"G.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":717564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dewitt, Jessica D. 0000-0002-8281-8134 jdewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-8134","contributorId":198894,"corporation":false,"usgs":true,"family":"Dewitt","given":"Jessica D.","email":"jdewitt@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":717565,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70196812,"text":"70196812 - 2017 - Landform features and seasonal precipitation predict shallow groundwater influence on temperature in headwater streams","interactions":[],"lastModifiedDate":"2018-05-02T11:40:36","indexId":"70196812","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","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":"Landform features and seasonal precipitation predict shallow groundwater influence on temperature in headwater streams","docAbstract":"<p><span>Headwater stream responses to climate change will depend in part on groundwater‐surface water exchanges. We used linear modeling techniques to partition likely effects of shallow groundwater seepage and air temperature on stream temperatures for 79 sites in nine focal watersheds using hourly air and water temperature measurements collected during summer months from 2012 to 2015 in Shenandoah National Park, Virginia, USA. Shallow groundwater effects exhibited more variation within watersheds than between them, indicating the importance of reach‐scale assessments and the limited capacity to extrapolate upstream groundwater influences from downstream measurements. Boosted regression tree (BRT) models revealed intricate interactions among geomorphological landform features (stream slope, elevation, network length, contributing area, and channel confinement) and seasonal precipitation patterns (winter, spring, and summer months) that together were robust predictors of spatial and temporal variation in groundwater influence on stream temperatures. The final BRT model performed well for training data and cross‐validated samples (correlation = 0.984 and 0.760, respectively). Geomorphological and precipitation predictors of groundwater influence varied in their importance between watersheds, suggesting differences in spatial and temporal controls of recharge dynamics and the depth of the groundwater source. We demonstrate an application of the final BRT model to predict groundwater effects from landform and precipitation covariates at 1075 new sites distributed at 100 m increments within focal watersheds. Our study provides a framework to estimate effects of groundwater seepage on stream temperature in unsampled locations. We discuss applications for climate change research to account for groundwater‐surface water interactions when projecting future thermal thresholds for stream biota.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2017WR020455","usgsCitation":"Johnson, Z.C., Snyder, C.D., and Hitt, N.P., 2017, Landform features and seasonal precipitation predict shallow groundwater influence on temperature in headwater streams: Water Resources Research, v. 53, no. 7, p. 5788-5812, https://doi.org/10.1002/2017WR020455.","productDescription":"25 p.","startPage":"5788","endPage":"5812","ipdsId":"IP-086899","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":469716,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr020455","text":"Publisher Index Page"},{"id":438280,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7B56H72","text":"USGS data release","linkHelpText":"Air-water temperature data for the study of groundwater influence on stream thermal regimes in Shenandoah National Park, Virginia (ver. 2.0, May 3, 2018)"},{"id":353918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -78.85986328125,\n              38.09133660751176\n            ],\n            [\n              -78.10455322265625,\n              38.09133660751176\n            ],\n            [\n              -78.10455322265625,\n              38.90172091499795\n            ],\n            [\n              -78.85986328125,\n              38.90172091499795\n            ],\n            [\n              -78.85986328125,\n              38.09133660751176\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"53","issue":"7","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-20","publicationStatus":"PW","scienceBaseUri":"5afee845e4b0da30c1bfc40b","contributors":{"authors":[{"text":"Johnson, Zachary C. 0000-0002-0149-5223","orcid":"https://orcid.org/0000-0002-0149-5223","contributorId":204647,"corporation":false,"usgs":false,"family":"Johnson","given":"Zachary","email":"","middleInitial":"C.","affiliations":[{"id":35215,"text":"Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":734560,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snyder, Craig D. 0000-0002-3448-597X csnyder@usgs.gov","orcid":"https://orcid.org/0000-0002-3448-597X","contributorId":2568,"corporation":false,"usgs":true,"family":"Snyder","given":"Craig","email":"csnyder@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":734559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568 nhitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":4435,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"nhitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":734561,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191828,"text":"70191828 - 2017 - Real-time geomagnetic monitoring for space weather-related applications: Opportunities and challenges","interactions":[],"lastModifiedDate":"2020-07-13T14:35:30.811512","indexId":"70191828","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"Real-time geomagnetic monitoring for space weather-related applications: Opportunities and challenges","docAbstract":"<p><span>An examination is made of opportunities and challenges for enhancing global, real-time geomagnetic monitoring that would be beneficial for a variety of operational projects. This enhancement in geomagnetic monitoring can be attained by expanding the geographic distribution of magnetometer stations, improving the quality of magnetometer data, increasing acquisition sampling rates, increasing the promptness of data transmission, and facilitating access to and use of the data. Progress will benefit from new partnerships to leverage existing capacities and harness multisector, cross-disciplinary, and international interests.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2017SW001665","usgsCitation":"Love, J.J., and Finn, C., 2017, Real-time geomagnetic monitoring for space weather-related applications: Opportunities and challenges: Space Weather, v. 15, no. 7, p. 820-827, https://doi.org/10.1002/2017SW001665.","productDescription":"8 p.","startPage":"820","endPage":"827","ipdsId":"IP-085207","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":347338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-24","publicationStatus":"PW","scienceBaseUri":"59f1a2a5e4b0220bbd9d9f48","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":713246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finn, Carol 0000-0003-3144-1645","orcid":"https://orcid.org/0000-0003-3144-1645","contributorId":13201,"corporation":false,"usgs":true,"family":"Finn","given":"Carol","affiliations":[],"preferred":false,"id":713247,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70192208,"text":"70192208 - 2017 - Seven recommendations to make your invasive alien species data more useful","interactions":[],"lastModifiedDate":"2018-08-10T16:25:38","indexId":"70192208","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5523,"text":"Frontiers in Applied Mathematics and Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Seven recommendations to make your invasive alien species data more useful","docAbstract":"<p><span>Science-based strategies to tackle biological invasions depend on recent, accurate, well-documented, standardized and openly accessible information on alien species. Currently and historically, biodiversity data are scattered in numerous disconnected data silos that lack interoperability. The situation is no different for alien species data, and this obstructs efficient retrieval, combination, and use of these kinds of information for research and policy-making. Standardization and interoperability are particularly important as many alien species related research and policy activities require pooling data. We describe seven ways that data on alien species can be made more accessible and useful, based on the results of a European Cooperation in Science and Technology (COST) workshop: (1) Create data management plans; (2) Increase interoperability of information sources; (3) Document data through metadata; (4) Format data using existing standards; (5) Adopt controlled vocabularies; (6) Increase data availability; and (7) Ensure long-term data preservation. We identify four properties specific and integral to alien species data (species status, introduction pathway, degree of establishment, and impact mechanism) that are either missing from existing data standards or lack a recommended controlled vocabulary. Improved access to accurate, real-time and historical data will repay the long-term investment in data management infrastructure, by providing more accurate, timely and realistic assessments and analyses. If we improve core biodiversity data standards by developing their relevance to alien species, it will allow the automation of common activities regarding data processing in support of environmental policy. Furthermore, we call for considerable effort to maintain, update, standardize, archive, and aggregate datasets, to ensure proper valorization of alien species data and information before they become obsolete or lost.</span></p>","language":"English","publisher":"Frontiers","doi":"10.3389/fams.2017.00013","usgsCitation":"Groom, Q.J., Adriaens, T., Desmet, P., Simpson, A., De Wever, A., Bazos, I., Cardoso, A.C., Charles, L., Christopoulou, A., Gazda, A., Helmisaari, H., Hobern, D., Josefsson, M., Lucy, F., Marisavljevic, D., Oszako, T., Pergl, J., Petrovic-Obradovic, O., Prevot, C., Ravn, H.P., Richards, G., Roques, A., Roy, H., Rozenberg, M.A., Scalera, R., Tricarico, E., Trichkova, T., Vercayie, D., Zenetos, A., and Vanderhoeven, S., 2017, Seven recommendations to make your invasive alien species data more useful: Frontiers in Applied Mathematics and Statistics, v. 3, p. 1-8, https://doi.org/10.3389/fams.2017.00013.","productDescription":"Article 13; 8 p.","startPage":"1","endPage":"8","ipdsId":"IP-083846","costCenters":[{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":469762,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fams.2017.00013","text":"Publisher Index Page"},{"id":347107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-30","publicationStatus":"PW","scienceBaseUri":"59eeffa6e4b0220bbd988f8e","contributors":{"authors":[{"text":"Groom, Quentin J.","contributorId":171401,"corporation":false,"usgs":false,"family":"Groom","given":"Quentin","email":"","middleInitial":"J.","affiliations":[{"id":26893,"text":"Botanic Garden Meise, Belgium","active":true,"usgs":false}],"preferred":false,"id":714786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adriaens, Tim","contributorId":171412,"corporation":false,"usgs":false,"family":"Adriaens","given":"Tim","email":"","affiliations":[{"id":26902,"text":"Research Institute for Nature and Forest, Belgium","active":true,"usgs":false}],"preferred":false,"id":714787,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Desmet, Peter","contributorId":197999,"corporation":false,"usgs":false,"family":"Desmet","given":"Peter","email":"","affiliations":[],"preferred":false,"id":714788,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simpson, Annie 0000-0001-8338-5134 asimpson@usgs.gov","orcid":"https://orcid.org/0000-0001-8338-5134","contributorId":127,"corporation":false,"usgs":true,"family":"Simpson","given":"Annie","email":"asimpson@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and 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Finland","active":true,"usgs":false}],"preferred":false,"id":714795,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hobern, Donald","contributorId":198004,"corporation":false,"usgs":false,"family":"Hobern","given":"Donald","email":"","affiliations":[],"preferred":false,"id":714796,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Josefsson, Melanie","contributorId":198005,"corporation":false,"usgs":false,"family":"Josefsson","given":"Melanie","email":"","affiliations":[],"preferred":false,"id":714797,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Lucy, Frances","contributorId":171393,"corporation":false,"usgs":false,"family":"Lucy","given":"Frances","email":"","affiliations":[{"id":26886,"text":"Institute of Technology Sligo, Ireland","active":true,"usgs":false}],"preferred":false,"id":714798,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Marisavljevic, 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Italy","active":true,"usgs":false}],"preferred":false,"id":714810,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Trichkova, Teodora","contributorId":198015,"corporation":false,"usgs":false,"family":"Trichkova","given":"Teodora","email":"","affiliations":[],"preferred":false,"id":714811,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Vercayie, Diemer","contributorId":198016,"corporation":false,"usgs":false,"family":"Vercayie","given":"Diemer","email":"","affiliations":[],"preferred":false,"id":714812,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Zenetos, Argyro","contributorId":171410,"corporation":false,"usgs":false,"family":"Zenetos","given":"Argyro","email":"","affiliations":[{"id":26900,"text":"Hellenic Centre for Marine Research, Greece","active":true,"usgs":false}],"preferred":false,"id":714813,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Vanderhoeven, Sonia","contributorId":171413,"corporation":false,"usgs":false,"family":"Vanderhoeven","given":"Sonia","email":"","affiliations":[{"id":26903,"text":"Belgian Biodiversity Platform, Belgium","active":true,"usgs":false}],"preferred":false,"id":714814,"contributorType":{"id":1,"text":"Authors"},"rank":30}]}}
,{"id":70194506,"text":"70194506 - 2017 - Puffins reveal contrasting relationships between forage fish and ocean climate in the North Pacific","interactions":[],"lastModifiedDate":"2018-03-26T14:44:53","indexId":"70194506","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1660,"text":"Fisheries Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Puffins reveal contrasting relationships between forage fish and ocean climate in the North Pacific","docAbstract":"<p><span>Long-term studies of predator food habits (i.e., ‘predator-based sampling’) are useful for identifying patterns of spatial and temporal variability of forage nekton in marine ecosystems. We investigated temporal changes in forage fish availability and relationships to ocean climate by analyzing diet composition of three puffin species (horned puffin&nbsp;</span><i>Fratercula corniculata</i><span>, tufted puffin<span>&nbsp;</span></span><i>Fratercula cirrhata</i><span>, and rhinoceros auklet<span>&nbsp;</span></span><i>Cerorhinca monocerata</i><span>) from five sites in the North Pacific from 1978–2012. Dominant forage species included squids and hexagrammids in the western Aleutians, gadids and Pacific sand lance (</span><i>Ammodytes personatus</i><span>) in the eastern Aleutians and western Gulf of Alaska (GoA), and sand lance and capelin (</span><i>Mallotus villosus</i><span>) in the northern and eastern GoA. Interannual fluctuations in forage availability dominated variability in the western Aleutians, whereas lower-frequency shifts in forage fish availability dominated elsewhere. We produced regional multivariate indicators of sand lance, capelin, and age-0 gadid availability by combining data across species and sites using Principal Component Analysis, and related these indices to environmental factors including sea level pressure (SPL), winds, and sea surface temperature (SST). There was coherence in the availability of sand lance and capelin across the study area. Sand lance availability increased linearly with environmental conditions leading to warmer ocean temperatures, whereas capelin availability increased in a non-linear manner when environmental changes led to lower ocean temperatures. Long-term studies of puffin diet composition appear to be a promising tool for understanding the availability of these difficult-to-survey forage nekton in remote regions of the North Pacific.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/fog.12204","usgsCitation":"Sydeman, W., Piatt, J.F., Thompson, S.A., Garcia-Reyes, M., Hatch, S., Arimitsu, M.L., Slater, L., Williams, J.C., Rojek, N.A., Zador, S.G., and Renner, H.M., 2017, Puffins reveal contrasting relationships between forage fish and ocean climate in the North Pacific: Fisheries Oceanography, v. 26, no. 4, p. 379-395, https://doi.org/10.1111/fog.12204.","productDescription":"17 p.","startPage":"379","endPage":"395","ipdsId":"IP-063216","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":469714,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/fog.12204","text":"External Repository"},{"id":349629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-13","publicationStatus":"PW","scienceBaseUri":"5a60fb8de4b06e28e9c23274","contributors":{"authors":[{"text":"Sydeman, William J.","contributorId":172574,"corporation":false,"usgs":false,"family":"Sydeman","given":"William J.","affiliations":[],"preferred":false,"id":724160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":724159,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Sarah Ann","contributorId":198394,"corporation":false,"usgs":false,"family":"Thompson","given":"Sarah","email":"","middleInitial":"Ann","affiliations":[],"preferred":false,"id":724161,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garcia-Reyes, Marisol","contributorId":201043,"corporation":false,"usgs":false,"family":"Garcia-Reyes","given":"Marisol","affiliations":[],"preferred":false,"id":724162,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hatch, Scott A.","contributorId":201044,"corporation":false,"usgs":false,"family":"Hatch","given":"Scott A.","affiliations":[],"preferred":false,"id":724163,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":724164,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Slater, Leslie","contributorId":201045,"corporation":false,"usgs":false,"family":"Slater","given":"Leslie","email":"","affiliations":[],"preferred":false,"id":724165,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, Jeffrey C.","contributorId":126882,"corporation":false,"usgs":false,"family":"Williams","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":724166,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rojek, Nora A.","contributorId":201046,"corporation":false,"usgs":false,"family":"Rojek","given":"Nora","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":724167,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zador, Stephani G.","contributorId":201047,"corporation":false,"usgs":false,"family":"Zador","given":"Stephani","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":724168,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Renner, Heather M.","contributorId":201048,"corporation":false,"usgs":false,"family":"Renner","given":"Heather","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":724169,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70189472,"text":"70189472 - 2017 - PeRL: A circum-Arctic Permafrost Region Pond and Lake database","interactions":[],"lastModifiedDate":"2018-06-16T18:26:58","indexId":"70189472","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1426,"text":"Earth System Science Data","active":true,"publicationSubtype":{"id":10}},"title":"PeRL: A circum-Arctic Permafrost Region Pond and Lake database","docAbstract":"<p><span>Ponds and lakes are abundant in Arctic permafrost lowlands. They play an important role in Arctic wetland ecosystems by regulating carbon, water, and energy fluxes and providing freshwater habitats. However, ponds, i.e., waterbodies with surface areas smaller than 1. 0 × 10</span><sup>4</sup><span> m</span><sup>2</sup><span>, have not been inventoried on global and regional scales. The Permafrost Region Pond and Lake (PeRL) database presents the results of a circum-Arctic effort to map ponds and lakes from modern (2002–2013) high-resolution aerial and satellite imagery with a resolution of 5 m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6 m or better. PeRL includes 69 maps covering a wide range of environmental conditions from tundra to boreal regions and from continuous to discontinuous permafrost zones. Waterbody maps are linked to regional permafrost landscape maps which provide information on permafrost extent, ground ice volume, geology, and lithology. This paper describes waterbody classification and accuracy, and presents statistics of waterbody distribution for each site. Maps of permafrost landscapes in Alaska, Canada, and Russia are used to extrapolate waterbody statistics from the site level to regional landscape units. PeRL presents pond and lake estimates for a total area of 1. 4 × 10</span><sup>6</sup><span> km</span><sup>2</sup><span><span>&nbsp;</span>across the Arctic, about 17 % of the Arctic lowland ( &lt;  300 m a.s.l.) land surface area. PeRL waterbodies with sizes of 1. 0 × 10</span><sup>6</sup><span> m</span><sup>2</sup><span><span>&nbsp;</span>down to 1. 0 × 10</span><sup>2</sup><span> m</span><sup>2</sup><span><span>&nbsp;</span>contributed up to 21 % to the total water fraction. Waterbody density ranged from 1. 0 × 10 to 9. 4 × 10</span><sup>1</sup><span> km</span><sup>−2</sup><span>. Ponds are the dominant waterbody type by number in all landscapes representing 45–99 % of the total waterbody number. The implementation of PeRL size distributions in land surface models will greatly improve the investigation and projection of surface inundation and carbon fluxes in permafrost lowlands. Waterbody maps, study area boundaries, and maps of regional permafrost landscapes including detailed metadata are available at<span>&nbsp;</span></span><a href=\"https://doi.pangaea.de/10.1594/PANGAEA.868349\" target=\"_blank\" data-mce-href=\"https://doi.pangaea.de/10.1594/PANGAEA.868349\">https://doi.pangaea.de/10.1594/PANGAEA.868349</a><span>.</span></p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-9-317-2017","usgsCitation":"Muster, S., Roth, K., Langer, M., Lange, S., Cresto Aleina, F., Bartsch, A., Morgenstern, A., Grosse, G., Jones, B.M., Sannel, A.B., Sjoberg, Y., Gunther, F., Andresen, C., Veremeeva, A., Lindgren, P.R., Bouchard, F., Lara, M.J., Fortier, D., Charbonneau, S., Virtanen, T.A., Hugelius, G., Palmtag, J., Siewert, M.B., Riley, W.J., Koven, C., and Boike, J., 2017, PeRL: A circum-Arctic Permafrost Region Pond and Lake database: Earth System Science Data, v. 9, p. 317-348, https://doi.org/10.5194/essd-9-317-2017.","productDescription":"32 p.","startPage":"317","endPage":"348","ipdsId":"IP-081012","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":469775,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/essd-9-317-2017","text":"Publisher Index Page"},{"id":343807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2017-06-06","publicationStatus":"PW","scienceBaseUri":"5968869de4b0d1f9f05f5965","contributors":{"authors":[{"text":"Muster, Sina","contributorId":194628,"corporation":false,"usgs":false,"family":"Muster","given":"Sina","email":"","affiliations":[],"preferred":false,"id":704818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roth, Kurt","contributorId":194629,"corporation":false,"usgs":false,"family":"Roth","given":"Kurt","email":"","affiliations":[],"preferred":false,"id":704819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langer, Moritz","contributorId":194630,"corporation":false,"usgs":false,"family":"Langer","given":"Moritz","email":"","affiliations":[],"preferred":false,"id":704820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lange, Stephan","contributorId":194631,"corporation":false,"usgs":false,"family":"Lange","given":"Stephan","email":"","affiliations":[],"preferred":false,"id":704821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cresto Aleina, Fabio","contributorId":194632,"corporation":false,"usgs":false,"family":"Cresto Aleina","given":"Fabio","email":"","affiliations":[],"preferred":false,"id":704822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bartsch, Annett","contributorId":194633,"corporation":false,"usgs":false,"family":"Bartsch","given":"Annett","email":"","affiliations":[],"preferred":false,"id":704823,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Morgenstern, Anne","contributorId":194634,"corporation":false,"usgs":false,"family":"Morgenstern","given":"Anne","email":"","affiliations":[],"preferred":false,"id":704824,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grosse, Guido","contributorId":101475,"corporation":false,"usgs":true,"family":"Grosse","given":"Guido","affiliations":[{"id":34291,"text":"University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":704825,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":704826,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sannel, A. B. K.","contributorId":38450,"corporation":false,"usgs":false,"family":"Sannel","given":"A.","email":"","middleInitial":"B. 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,{"id":70189309,"text":"70189309 - 2017 - Does bioelectrical impedance analysis accurately estimate the condition of threatened and endangered desert fish species?","interactions":[],"lastModifiedDate":"2017-07-11T09:29:00","indexId":"70189309","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","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":"Does bioelectrical impedance analysis accurately estimate the condition of threatened and endangered desert fish species?","docAbstract":"<p><span>Bioelectrical impedance analysis (BIA) is a nonlethal tool with which to estimate the physiological condition of animals that has potential value in research on endangered species. However, the effectiveness of BIA varies by species, the methodology continues to be refined, and incidental mortality rates are unknown. Under laboratory conditions we tested the value of using BIA in addition to morphological measurements such as total length and wet mass to estimate proximate composition (lipid, protein, ash, water, dry mass, energy density) in the endangered Humpback Chub&nbsp;</span><i>Gila cypha</i><span><span>&nbsp;</span>and Bonytail<span>&nbsp;</span></span><i>G. elegans</i><span><span>&nbsp;</span>and the species of concern Roundtail Chub<span>&nbsp;</span></span><i>G. robusta</i><span><span>&nbsp;</span>and conducted separate trials to estimate the mortality rates of these sensitive species. Although Humpback and Roundtail Chub exhibited no or low mortality in response to taking BIA measurements versus handling for length and wet-mass measurements, Bonytails exhibited 14% and 47% mortality in the BIA and handling experiments, respectively, indicating that survival following stress is species specific. Derived BIA measurements were included in the best models for most proximate components; however, the added value of BIA as a predictor was marginal except in the absence of accurate wet-mass data. Bioelectrical impedance analysis improved the<span>&nbsp;</span></span><i>R</i><sup>2</sup><span><span>&nbsp;</span>of the best percentage-based models by no more than 4% relative to models based on morphology. Simulated field conditions indicated that BIA models became increasingly better than morphometric models at estimating proximate composition as the observation error around wet-mass measurements increased. However, since the overall proportion of variance explained by percentage-based models was low and BIA was mostly a redundant predictor, we caution against the use of BIA in field applications for these sensitive fish species.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2017.1302993","usgsCitation":"Dibble, K.L., Yard, M.D., Ward, D.L., and Yackulic, C.B., 2017, Does bioelectrical impedance analysis accurately estimate the condition of threatened and endangered desert fish species?: Transactions of the American Fisheries Society, v. 146, no. 5, p. 888-902, https://doi.org/10.1080/00028487.2017.1302993.","productDescription":"15 p.","startPage":"888","endPage":"902","ipdsId":"IP-076886","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488591,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/dataset/Does_Bioelectrical_Impedance_Analysis_Accurately_Estimate_the_Physiological_Condition_of_Threatened_and_Endangered_Desert_Fish_Species_/5177047","text":"External Repository"},{"id":438281,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CF9NMV","text":"USGS data release","linkHelpText":"Bioelectrical impedance analysis for an endangered desert fish&amp;#151;Data"},{"id":343551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"146","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-05","publicationStatus":"PW","scienceBaseUri":"5965b1b8e4b0d1f9f05b379e","contributors":{"authors":[{"text":"Dibble, Kimberly L. 0000-0003-0799-4477 kdibble@usgs.gov","orcid":"https://orcid.org/0000-0003-0799-4477","contributorId":5174,"corporation":false,"usgs":true,"family":"Dibble","given":"Kimberly","email":"kdibble@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":704088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yard, Micheal D. myard@usgs.gov","contributorId":147386,"corporation":false,"usgs":true,"family":"Yard","given":"Micheal","email":"myard@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":704089,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ward, David L. 0000-0002-3355-0637 dlward@usgs.gov","orcid":"https://orcid.org/0000-0002-3355-0637","contributorId":3879,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dlward@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":704090,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":704091,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70189119,"text":"70189119 - 2017 - Two-step adaptive management for choosing between two management actions","interactions":[],"lastModifiedDate":"2025-01-29T15:50:41.671359","indexId":"70189119","displayToPublicDate":"2017-06-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Two-step adaptive management for choosing between two management actions","docAbstract":"<p><span>Adaptive management is widely advocated to improve environmental management. Derivations of optimal strategies for adaptive management, however, tend to be case specific and time consuming. In contrast, managers might seek relatively simple guidance, such as insight into when a new potential management action should be considered, and how much effort should be expended on trialing such an action. We constructed a two-time-step scenario where a manager is choosing between two possible management actions. The manager has a total budget that can be split between a learning phase and an implementation phase. We use this scenario to investigate when and how much a manager should invest in learning about the management actions available. The optimal investment in learning can be understood intuitively by accounting for the expected value of sample information, the benefits that accrue during learning, the direct costs of learning, and the opportunity costs of learning. We find that the optimal proportion of the budget to spend on learning is characterized by several critical thresholds that mark a jump from spending a large proportion of the budget on learning to spending nothing. For example, as sampling variance increases, it is optimal to spend a larger proportion of the budget on learning, up to a point: if the sampling variance passes a critical threshold, it is no longer beneficial to invest in learning. Similar thresholds are observed as a function of the total budget and the difference in the expected performance of the two actions. We illustrate how this model can be applied using a case study of choosing between alternative rearing diets for hihi, an endangered New Zealand passerine. Although the model presented is a simplified scenario, we believe it is relevant to many management situations. Managers often have relatively short time horizons for management, and might be reluctant to consider further investment in learning and monitoring beyond collecting data from a single time period.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1515","usgsCitation":"Moore, A.L., Walker, L., Runge, M.C., McDonald-Madden, E., and McCarthy, M.A., 2017, Two-step adaptive management for choosing between two management actions: Ecological Applications, v. 27, no. 4, p. 1210-1222, https://doi.org/10.1002/eap.1515.","productDescription":"13 p.","startPage":"1210","endPage":"1222","ipdsId":"IP-076800","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":490045,"rank":3,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-01605477","text":"External Repository"},{"id":343215,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":357277,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/ja/70189119/70189119.pdf","text":"USGS open-access version of article","linkFileType":{"id":1,"text":"pdf"}}],"volume":"27","issue":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-19","publicationStatus":"PW","scienceBaseUri":"59576334e4b0d1f9f051b4ff","contributors":{"authors":[{"text":"Moore, Alana L.","contributorId":194047,"corporation":false,"usgs":false,"family":"Moore","given":"Alana","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":703051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Leila","contributorId":194048,"corporation":false,"usgs":false,"family":"Walker","given":"Leila","email":"","affiliations":[],"preferred":false,"id":703052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":703050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDonald-Madden, Eve","contributorId":139968,"corporation":false,"usgs":false,"family":"McDonald-Madden","given":"Eve","email":"","affiliations":[{"id":13337,"text":"CSIRO Ecosystem Services, Queensland, Australia","active":true,"usgs":false}],"preferred":false,"id":703053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCarthy, Michael A","contributorId":173778,"corporation":false,"usgs":false,"family":"McCarthy","given":"Michael","email":"","middleInitial":"A","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":703054,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70189057,"text":"70189057 - 2017 - Response of deep groundwater to land use change in desert basins of the Trans-Pecos region, Texas, USA: Effects on infiltration, recharge, and nitrogen fluxes","interactions":[],"lastModifiedDate":"2025-01-29T15:48:32.30352","indexId":"70189057","displayToPublicDate":"2017-06-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Response of deep groundwater to land use change in desert basins of the Trans-Pecos region, Texas, USA: Effects on infiltration, recharge, and nitrogen fluxes","docAbstract":"<p><span>Quantifying the effects of anthropogenic processes on groundwater in arid regions can be complicated by thick unsaturated zones with long transit times. Human activities can alter water and nutrient fluxes, but their impact on groundwater is not always clear. This study of basins in the Trans-Pecos region of Texas links anthropogenic land use and vegetation change with alterations to unsaturated zone fluxes and regional increases in basin groundwater NO</span><sub>3</sub><sup>−</sup><span>concentrations. Median increases in groundwater NO</span><sub>3</sub><sup>−</sup><span><span>&nbsp;</span>(by 0.7–0.9&nbsp;mg-N/l over periods ranging from 10 to 50+&nbsp;years) occurred despite low precipitation (220–360&nbsp;mm/year), high potential evapotranspiration (~1570&nbsp;mm/year), and thick unsaturated zones (10–150+&nbsp;m). Recent model simulations indicate net infiltration and groundwater recharge can occur beneath Trans-Pecos basin floors, and may have increased due to irrigation and vegetation change. These processes were investigated further with chemical and isotopic data from groundwater and unsaturated zone cores. Some unsaturated zone solute profiles indicate flushing of natural salt accumulations has occurred. Results are consistent with human-influenced flushing of naturally accumulated unsaturated zone nitrogen as an important source of NO</span><sub>3</sub><sup>−</sup><span><span>&nbsp;</span>to the groundwater. Regional mass balance calculations indicate the mass of natural unsaturated zone NO</span><sub>3</sub><sup>−</sup><span><span>&nbsp;</span>(122–910&nbsp;kg-N/ha) was sufficient to cause the observed groundwater NO</span><sub>3</sub><sup>−</sup><span><span>&nbsp;</span>increases, especially if augmented locally with the addition of fertilizer N. Groundwater NO</span><sub>3</sub><sup>−</sup><span><span>&nbsp;</span>trends can be explained by small volumes of high NO</span><sub>3</sub><sup>−</sup><span><span>&nbsp;</span>modern recharge mixed with larger volumes of older groundwater in wells. This study illustrates the importance of combining long-term monitoring and targeted process studies to improve understanding of human impacts on recharge and nutrient cycling in arid regions, which are vulnerable to the effects of climate change and increasing human reliance on dryland ecosystems.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11178","usgsCitation":"Robertson, W.M., Bohlke, J., and Sharp, J.M., 2017, Response of deep groundwater to land use change in desert basins of the Trans-Pecos region, Texas, USA: Effects on infiltration, recharge, and nitrogen fluxes: Hydrological Processes, v. 31, no. 13, p. 2349-2364, https://doi.org/10.1002/hyp.11178.","productDescription":"16 p.","startPage":"2349","endPage":"2364","ipdsId":"IP-079579","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":343208,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":357279,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/ja/70189057/70189057.pdf","text":"USGS open-access version of article","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Texas","otherGeospatial":"Trans-Pecos region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -105.5,\n              30.1\n            ],\n            [\n              -104.05,\n              30.1\n            ],\n            [\n              -104.05,\n              31.4\n            ],\n            [\n              -105.5,\n              31.4\n            ],\n            [\n              -105.5,\n              30.1\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"31","issue":"13","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-11","publicationStatus":"PW","scienceBaseUri":"59576334e4b0d1f9f051b504","contributors":{"authors":[{"text":"Robertson, Wendy Marie","contributorId":193940,"corporation":false,"usgs":false,"family":"Robertson","given":"Wendy","email":"","middleInitial":"Marie","affiliations":[],"preferred":false,"id":702677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":702676,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sharp, John M.","contributorId":149229,"corporation":false,"usgs":false,"family":"Sharp","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":702678,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70188988,"text":"ofr20171076 - 2017 - Grand challenges for integrated USGS science — A workshop report","interactions":[],"lastModifiedDate":"2022-04-22T15:47:46.396782","indexId":"ofr20171076","displayToPublicDate":"2017-06-29T15:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1076","title":"Grand challenges for integrated USGS science — A workshop report","docAbstract":"<h1>Executive Summary</h1><p>The U.S. Geological Survey (USGS) has a long history of advancing the traditional Earth science disciplines and identifying opportunities to integrate USGS science across disciplines to address complex societal problems. The USGS science strategy for 2007–2017 laid out key challenges in disciplinary and interdisciplinary arenas, culminating in a call for increased focus on a number of crosscutting science directions. Ten years on, to further the goal of integrated science and at the request of the Executive Leadership Team (ELT), a workshop with three dozen invited scientists spanning different disciplines and career stages in the Bureau convened on February 7–10, 2017, at the USGS John Wesley Powell Center for Analysis and Synthesis in Fort Collins, Colorado.</p><p>The workshop focused on identifying “grand challenges” for integrated USGS science. Individual participants identified nearly 70 potential grand challenges before the workshop and through workshop discussions. After discussion, four overarching grand challenges emerged:</p><ul><li>Natural resource security,</li><li>Societal risk from existing and emerging threats,</li><li>Smart infrastructure development, and</li><li>Anticipatory science for changing landscapes.</li></ul><p>Participants also identified a “comprehensive science challenge” that highlights the development of integrative science, data, models, and tools—all interacting in a modular framework—that can be used to address these and other future grand challenges:</p><ul><li>Earth Monitoring, Analyses, and Projections (EarthMAP)</li></ul><p>EarthMAP is our long-term vision for an integrated scientific framework that spans traditional scientific boundaries and disciplines, and integrates the full portfolio of USGS science: research, monitoring, assessment, analysis, and information delivery.</p><p>The Department of Interior, and the Nation in general, have a vast array of information needs. The USGS meets these needs by having a broadly trained and agile scientific workforce. Encouraging and supporting cross-discipline engagement would position the USGS to tackle complex and multifaceted scientific and societal challenges in the 21st Century.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171076","usgsCitation":"Jenni, K.E., Goldhaber, M.B., Betancourt, J.L., Baron, J.S., Bristol, R.S., Cantrill, Mary, Exter, P.E., Focazio, M.J., Haines, J.W., Hay, L.E., Hsu, Leslie, Labson, V.F., Lafferty, K.D., Ludwig, K.A., Milly, P.C., Morelli, T.L., Morman, S.A., Nassar, N.T., Newman, T.R., Ostroff, A.C., Read, J.S., Reed, S.C., Shapiro, C.D., Smith, R.A., Sanford, W.E., Sohl, T.L., Stets, E.G., Terando, A.J., Tillitt, D.E., Tischler, M.A., Toccalino, P.L., Wald, D.J., Waldrop, M.P., Wein, Anne, Weltzin, J.F., and Zimmerman, C.E., 2017, Grand challenges for integrated USGS science—A workshop report: U.S. Geological Survey Open-File Report 2017–1076, 94 p., https://doi.org/10.3133/ofr20171076.","productDescription":"94 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-085873","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":343080,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1076/ofr20171076.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1076"},{"id":343079,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1076/coverthbtest.jpg"}],"contact":"<p>John Wesley Powell Center<br> U.S. Geological Survey<br>2150 Centre Avenue<br>Building C<br>Fort Collins, CO 80526-8118<br><a href=\"https://powellcenter.usgs.gov/\" data-mce-href=\"https://powellcenter.usgs.gov/\">https://powellcenter.usgs.gov/</a><br data-mce-bogus=\"1\"></p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>Overarching Grand Challenges</li><li>Comprehensive Science Challenge—Earth Monitoring, Analyses, and Projections (EarthMAP)</li><li>Context to the Report</li><li>A New Science Vision for the USGS</li><li>Acknowledgments</li><li>References Cited</li><li>Appendixes</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-06-30","noUsgsAuthors":false,"publicationDate":"2017-06-30","publicationStatus":"PW","scienceBaseUri":"59576335e4b0d1f9f051b508","contributors":{"authors":[{"text":"Jenni, Karen E. 0000-0001-9927-7509 kjenni@usgs.gov","orcid":"https://orcid.org/0000-0001-9927-7509","contributorId":193824,"corporation":false,"usgs":true,"family":"Jenni","given":"Karen E.","email":"kjenni@usgs.gov","affiliations":[],"preferred":false,"id":702251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldhaber, Martin B. 0000-0002-1785-4243 mgold@usgs.gov","orcid":"https://orcid.org/0000-0002-1785-4243","contributorId":1339,"corporation":false,"usgs":true,"family":"Goldhaber","given":"Martin","email":"mgold@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Betancourt, Julio L. 0000-0002-7165-0743 jlbetanc@usgs.gov","orcid":"https://orcid.org/0000-0002-7165-0743","contributorId":3376,"corporation":false,"usgs":true,"family":"Betancourt","given":"Julio","email":"jlbetanc@usgs.gov","middleInitial":"L.","affiliations":[{"id":436,"text":"National Research Program - 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,{"id":70189106,"text":"70189106 - 2017 - Rare earth mineral potential in the southeastern U.S. Coastal Plain from integrated geophysical, geochemical, and geological approaches","interactions":[],"lastModifiedDate":"2025-01-29T15:49:31.797657","indexId":"70189106","displayToPublicDate":"2017-06-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Rare earth mineral potential in the southeastern U.S. Coastal Plain from integrated geophysical, geochemical, and geological approaches","docAbstract":"<p><span>We combined geophysical, geochemical, mineralogical, and geological data to evaluate the regional presence of rare earth element (REE)−bearing minerals in heavy mineral sand deposits of the southeastern U.S. Coastal Plain. We also analyzed regional differences in these data to determine probable sedimentary provenance. Analyses of heavy mineral separates covering the region show strong correlations between thorium, monazite, and xenotime, suggesting that radiometric equivalent thorium (eTh) can be used as a geophysical proxy for those REE-bearing minerals. Airborne radiometric data collected during the National Uranium Resource Evaluation (NURE) program cover the southeastern United States with line spacing varying from ∼2 to 10 km. These data show eTh highs over Cretaceous and Tertiary Coastal Plain sediments from the Cape Fear arch in North Carolina to eastern Alabama; these highs decrease with distance from the Piedmont. Quaternary sediments along the modern coasts show weaker eTh anomalies, except near coast-parallel ridges from South Carolina to northern Florida. Prominent eTh anomalies are also observed over large riverbeds and their floodplains, even north of the Cape Fear arch where surrounding areas are relatively low. These variations were verified using ground geophysical measurements and sample analyses, indicating that radiometric methods are a useful exploration tool at varying scales. Further analyses of heavy mineral separates showed regional differences, not only in concentrations of monazite, but also of rutile and staurolite, and in magnetic susceptibility. The combined properties suggest the presence of subregions where heavy mineral sediments are primarily sourced from high-grade metamorphic, low-grade metamorphic, or igneous terrains, or where they represent a mixing of these sources. Comparisons between interpreted sources of heavy mineral sands near the Fall Line and igneous and metamorphic Piedmont and Blue Ridge units showed a strong correspondence with rocks closest to the Fall Line and poor correspondence with rocks farther inland. This strongly suggests that the primary source of those heavy minerals, especially monazite, is the rocks that formed the rocky coast that was present during opening of the Atlantic Ocean, which in turn indicates the importance of coastal processes in forming heavy mineral sand concentrations. Furthermore, narrow radiometric eTh and K anomalies are associated with major rivers, indicating limited spatial influence of fluvial processes. Later coastal plain sediment deposition appears to have involved reworking of sediments, providing an “inheritance” of the rocky coast composition that persists for some distance from the Fall Line. However, this inheritance is reduced with distance, and sediments within ∼100 km of the coast in Georgia and Florida exhibit properties indicative of mixing from multiple sources.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31481.1","usgsCitation":"Shah, A.K., Bern, C.R., Van Gosen, B.S., Daniels, D.L., Benzel, W., Budahn, J.R., Ellefsen, K.J., Karst, A.T., and Davis, R., 2017, Rare earth mineral potential in the southeastern U.S. Coastal Plain from integrated geophysical, geochemical, and geological approaches: GSA Bulletin, v. 129, no. 9-10, p. 1140-1157, https://doi.org/10.1130/B31481.1.","productDescription":"18 p.","startPage":"1140","endPage":"1157","ipdsId":"IP-066088","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science 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,{"id":70188694,"text":"70188694 - 2017 - Daily reservoir sedimentation model: Case study from the Fena Valley Reservoir, Guam","interactions":[],"lastModifiedDate":"2018-03-27T11:17:35","indexId":"70188694","displayToPublicDate":"2017-06-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2338,"text":"Journal of Hydraulic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Daily reservoir sedimentation model: Case study from the Fena Valley Reservoir, Guam","docAbstract":"<p><span>A model to compute reservoir sedimentation rates at daily timescales is presented. The model uses streamflow and sediment load data from nearby stream gauges to obtain an initial estimate of sediment yield for the reservoir’s watershed; it is then calibrated to the total deposition calculated from repeat bathymetric surveys. Long-term changes to reservoir trapping efficiency are also taken into account. The model was applied to the Fena Valley Reservoir, a water supply reservoir on the island of Guam. This reservoir became operational in 1951 and was recently surveyed in 2014. The model results show that the highest rate of deposition occurred during two typhoons (Typhoon Alice in 1953 and Typhoon Tingting in 2004); each storm decreased reservoir capacity by approximately 2–3% in only a few days. The presented model can be used to evaluate the impact of an extreme event, or it can be coupled with a watershed runoff model to evaluate potential impacts to storage capacity as a result of climate change or other hydrologic modifications.</span></p>","language":"English","publisher":"ASCE","doi":"10.1061/(ASCE)HY.1943-7900.0001344","usgsCitation":"Marineau, M.D., and Wright, S., 2017, Daily reservoir sedimentation model: Case study from the Fena Valley Reservoir, Guam: Journal of Hydraulic Engineering, v. 143, no. 9, Article  05017003; 11 p., https://doi.org/10.1061/(ASCE)HY.1943-7900.0001344.","productDescription":"Article  05017003; 11 p.","ipdsId":"IP-082309","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":343086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"143","issue":"9","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965b1bae4b0d1f9f05b37a8","contributors":{"authors":[{"text":"Marineau, Mathieu D. 0000-0002-6568-0743 mmarineau@usgs.gov","orcid":"https://orcid.org/0000-0002-6568-0743","contributorId":4954,"corporation":false,"usgs":true,"family":"Marineau","given":"Mathieu","email":"mmarineau@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":698945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":698946,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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