{"pageNumber":"669","pageRowStart":"16700","pageSize":"25","recordCount":184617,"records":[{"id":70206074,"text":"70206074 - 2020 - Historical changes in fish communities in urban streams of the southeastern U.S. and the relative importance of water-quality stressors","interactions":[],"lastModifiedDate":"2020-01-05T14:01:25","indexId":"70206074","displayToPublicDate":"2019-09-04T10:54:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Historical changes in fish communities in urban streams of the southeastern U.S. and the relative importance of water-quality stressors","docAbstract":"A total of 71 stream sites representing a gradient of urban land use was sampled across the Piedmont of the southeastern U.S. in 2014.  Fish data collected (observed) at each site were compared to an expected community based on georeferenced historical (~1950 - ~1990) species occurrence records for stream segments (1:100,000 scale) containing the sampled stream sites.  Loss of expected fish species (percent of fish species expected to occur but not observed) and homogenization (difference in Jaccard’s similarity of the fish community among sites observed and expected) were determined.  On average, there was a 13.2% increase in the similarity of fish communities across sites, demonstrating evidence of community homogenization.  Occurrence of Redbreast Sunfish (Lepomis auritus), Green Sunfish (L. cyanellus), and Bluegill (L. macrochirus) increased more than 50% over time (between observed and expected).  Species loss increased significantly with urbanization whereas homogenization was not related to urbanization.  Random forest analysis indicated that herbicides, insecticides, and centrarchid species richness were significant predictors of species loss.  Of these, generalized additive model regression indicated that herbicides represented the most parsimonious model based on a single predictor.  Stream base flow, elevation, and total nitrogen were significant predictors of homogenization.  Generalized additive model regression indicated that decreased stream base flow was the single most important factor associated with increased homogenization.  Chemical contaminants and associated ecosystem alteration and changes in stream flow may represent important regional influences on changes in fish communities in urban streams in the southeastern U.S.","language":"English","publisher":"Wiley","doi":"10.1111/eff.12503","usgsCitation":"Meador, M.R., 2020, Historical changes in fish communities in urban streams of the southeastern U.S. and the relative importance of water-quality stressors: Ecology of Freshwater Fish, v. 29, no. 1, p. 156-169, https://doi.org/10.1111/eff.12503.","productDescription":"14 p.","startPage":"156","endPage":"169","ipdsId":"IP-092961","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":368448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States ","state":"Alabama, Georgia, North Carolina, South Carolina, Tennessee, Virginia, Washington DC.","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -78.431396484375,\n              39.487084981687495\n            ],\n            [\n              -79.266357421875,\n              38.70265930723801\n            ],\n            [\n              -79.771728515625,\n              38.634036452919226\n            ],\n            [\n              -80.343017578125,\n              37.90953361677018\n            ],\n            [\n              -80.628662109375,\n              37.58811876638322\n            ],\n            [\n              -81.090087890625,\n              37.49229399862877\n            ],\n            [\n              -81.89208984375,\n              37.52715361723378\n            ],\n            [\n              -84.1552734375,\n              36.65079252503471\n            ],\n            [\n              -85.60546875,\n              34.994003757575776\n            ],\n            [\n              -86.5283203125,\n              33.137551192346145\n            ],\n            [\n              -87.29736328125,\n              32.0639555946604\n            ],\n            [\n              -85.10009765625,\n              31.690781806136822\n            ],\n            [\n              -83.78173828125,\n              32.1570124860701\n            ],\n            [\n              -81.9580078125,\n              33.46810795527896\n            ],\n            [\n              -80.947265625,\n              33.797408767572485\n            ],\n            [\n              -80.04638671875,\n              34.17999758688084\n            ],\n            [\n              -79.60693359375,\n              34.867904962568716\n            ],\n            [\n              -78.22265625,\n              35.7286770448517\n            ],\n            [\n              -77.113037109375,\n              36.54494944148322\n            ],\n            [\n              -77.16796875,\n              37.96152331396614\n            ],\n            [\n              -76.849365234375,\n              38.92522904714054\n            ],\n            [\n              -77.18994140625,\n              39.06184913429154\n            ],\n            [\n              -77.991943359375,\n              38.496593518947584\n            ],\n            [\n              -77.82714843749999,\n              39.13006024213511\n            ],\n            [\n              -78.431396484375,\n              39.487084981687495\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"29","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Meador, Michael R. 0000-0001-5956-3340 mrmeador@usgs.gov","orcid":"https://orcid.org/0000-0001-5956-3340","contributorId":219878,"corporation":false,"usgs":true,"family":"Meador","given":"Michael","email":"mrmeador@usgs.gov","middleInitial":"R.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":773484,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70263567,"text":"70263567 - 2020 - Regional Global Navigation Satellite System networks for crustal deformation monitoring","interactions":[],"lastModifiedDate":"2025-02-13T16:47:47.502631","indexId":"70263567","displayToPublicDate":"2019-09-04T10:45:18","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Regional Global Navigation Satellite System networks for crustal deformation monitoring","docAbstract":"<p><span>Regional networks of Global Navigation Satellite System (GNSS) stations cover seismically and volcanically active areas throughout the United States. Data from these networks have been used to produce high‐precision, three‐component velocity fields covering broad geographic regions as well as position time series that track time‐varying crustal deformation. This information has contributed to assessing interseismic strain accumulation and related seismic hazard, revealed previously unknown occurrences of aseismic fault slip, constrained coseismic slip estimates, and enabled monitoring of volcanic unrest and postseismic deformation. In addition, real‐time GNSS data are now widely available. Such observations proved invaluable for tracking the rapidly evolving eruption of Kīlauea in 2018. Real‐time earthquake source modeling using GNSS data is being incorporated into tsunami warning systems, and a vigorous research effort is focused on quantifying the contribution that real‐time GNSS can make to improve earthquake early warnings as part of the Advanced National Seismic System ShakeAlert system. Real‐time GNSS data can also aid in the tracking of ionospheric disturbances and precipitable water vapor for weather forecasting. Although regional GNSS and seismic networks generally have been established independently, their spatial footprints often overlap, and in some cases the same institution operates both types of networks. Further integration of GNSS and seismic networks would promote joint use of the two data types to better characterize earthquake sources and ground motion as well as offer opportunities for more efficient network operations. Looking ahead, upgrading network stations to leverage new GNSS technology could enable more precise positioning and robust real‐time operations. New computational approaches such as machine learning have the potential to enable full utilization of the large amounts of data generated by continuous GNSS networks. Development of seafloor Global Positioning System‐acoustic networks would provide unique information for fundamental and applied research on subduction zone seismic hazard and, potentially, monitoring.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190113","usgsCitation":"Murray, J.R., Bartlow, N., Bock, Y., Brooks, B.A., Foster, J.H., Freymueller, J.T., Hammond, W.C., Hodgkinson, K., Johanson, I.A., Lopez-Venegas, A., Mann, D., Mattioli, G., Melbourne, T., Mencin, D., Montgomery-Brown, E.K., Murray, M.H., Smalley, R., and Thomas, V., 2020, Regional Global Navigation Satellite System networks for crustal deformation monitoring: Seismological Research Letters, v. 91, no. 2A, p. 552-572, https://doi.org/10.1785/0220190113.","productDescription":"21 p.","startPage":"552","endPage":"572","ipdsId":"IP-108083","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","issue":"2A","noUsgsAuthors":false,"publicationDate":"2019-09-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Murray, Jessica R. 0000-0002-6144-1681 jrmurray@usgs.gov","orcid":"https://orcid.org/0000-0002-6144-1681","contributorId":2759,"corporation":false,"usgs":true,"family":"Murray","given":"Jessica","email":"jrmurray@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927348,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartlow, Noel 0000-0002-9961-5608","orcid":"https://orcid.org/0000-0002-9961-5608","contributorId":242895,"corporation":false,"usgs":false,"family":"Bartlow","given":"Noel","email":"","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":927349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bock, Yehuda 0000-0001-8296-6623","orcid":"https://orcid.org/0000-0001-8296-6623","contributorId":350938,"corporation":false,"usgs":false,"family":"Bock","given":"Yehuda","affiliations":[{"id":83883,"text":"University of California San Diego Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":927350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brooks, Benjamin A. 0000-0001-7954-6281 bbrooks@usgs.gov","orcid":"https://orcid.org/0000-0001-7954-6281","contributorId":5237,"corporation":false,"usgs":true,"family":"Brooks","given":"Benjamin","email":"bbrooks@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927351,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Foster, James H.","contributorId":244553,"corporation":false,"usgs":false,"family":"Foster","given":"James","email":"","middleInitial":"H.","affiliations":[{"id":48939,"text":"Hawaii Institute of Geophysics and Planetology, University of Hawaii at Manoa, HI, USA","active":true,"usgs":false}],"preferred":false,"id":927352,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Freymueller, Jeffery T. 0000-0003-0614-0306","orcid":"https://orcid.org/0000-0003-0614-0306","contributorId":244609,"corporation":false,"usgs":false,"family":"Freymueller","given":"Jeffery","email":"","middleInitial":"T.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":927353,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hammond, William C.","contributorId":73735,"corporation":false,"usgs":true,"family":"Hammond","given":"William","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":927354,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hodgkinson, Kathleen 0000-0001-8529-0913","orcid":"https://orcid.org/0000-0001-8529-0913","contributorId":209915,"corporation":false,"usgs":false,"family":"Hodgkinson","given":"Kathleen","email":"","affiliations":[{"id":38024,"text":"UNAVCO Inc.","active":true,"usgs":false}],"preferred":false,"id":927355,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Johanson, Ingrid A. 0000-0002-6049-2225","orcid":"https://orcid.org/0000-0002-6049-2225","contributorId":215613,"corporation":false,"usgs":true,"family":"Johanson","given":"Ingrid","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science 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0000-0002-9117-7471","orcid":"https://orcid.org/0000-0002-9117-7471","contributorId":350941,"corporation":false,"usgs":false,"family":"Mattioli","given":"Glen","affiliations":[{"id":83886,"text":"UNAVCO, Inc.","active":true,"usgs":false}],"preferred":false,"id":927359,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Melbourne, Timothy 0000-0003-1870-3962","orcid":"https://orcid.org/0000-0003-1870-3962","contributorId":209916,"corporation":false,"usgs":false,"family":"Melbourne","given":"Timothy","email":"","affiliations":[{"id":26935,"text":"Central Washington University","active":true,"usgs":false}],"preferred":false,"id":927360,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Mencin, David 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Science Center","active":true,"usgs":true}],"preferred":true,"id":927363,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Smalley, Robert Jr.","contributorId":244558,"corporation":false,"usgs":false,"family":"Smalley","given":"Robert","suffix":"Jr.","email":"","affiliations":[{"id":48941,"text":"Center for Earthquake Research and Information, University of Memphis, Memphis, TN, USA","active":true,"usgs":false}],"preferred":false,"id":927364,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Thomas, Valerie 0000-0001-6170-5563","orcid":"https://orcid.org/0000-0001-6170-5563","contributorId":222022,"corporation":false,"usgs":true,"family":"Thomas","given":"Valerie","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927365,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70206562,"text":"70206562 - 2020 - De facto water reuse: Bioassay suite approach delivers depth and breadth in endocrine active compound detection","interactions":[],"lastModifiedDate":"2019-11-08T08:48:22","indexId":"70206562","displayToPublicDate":"2019-09-04T08:44:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"De facto water reuse: Bioassay suite approach delivers depth and breadth in endocrine active compound detection","docAbstract":"Although endocrine disrupting compounds (EDCs) have been detected in wastewater and surface waters worldwide using a variety of in vitro effects-based screening tools, e.g. bioassays, few have examined potential attenuation of environmental contaminants by both natural (sorption, degradation, etc) and anthropogenic (water treatment practices) processes. This study used several bioassays and quantitative chemical analyses to assess residence-time weighted samples at six sites along a river in the northeastern United States beginning upstream of a waste water treatment plant (WWTP) outfall and proceeding downstream along the stream reach to a drinking water treatment plant (DWTP). Known steroidal estrogens were quantified and changes in signaling pathway molecular initiating events (activation of estrogen, androgen, glucocorticoid, peroxisome proliferator-activated, pregnane X receptor, and aryl hydrocarbon receptor signaling networks) were identified in water extracts. In initial multi-endpoint assays geographic and receptor-specific endocrine activity patterns in transcription factor signatures and nuclear receptor activation were discovered. In subsequent single endpoint receptor-specific bioassays, estrogen (16 of 18 samples; 0.01 to 28 ng estradiol equivalents [E2Eqs]/L) glucocorticoid (3 of 18 samples; 1.8 to 21 ng dexamethasone equivalents [DexEqs]/L), and androgen (2 of 18 samples; 0.95 to 2.1 ng dihydrotestosterone equivalents [DHTEqs]/L) receptor transcriptional activation occurred above respective assay method detection limits (0.04 ng E2Eqs/L, 1.2 ng DexEqs/L, and 0.77 ng DHTEqs/L) in multiple sampling events. Estrogen activity, the most often detected, correlated well with measured concentrations of known steroidal estrogens (R2 = 0.890). Overall, activity indicative of multiple types of endocrine active compounds was highest in wastewater effluent samples, while activity downstream was progressively lower, and negligible in (unfinished) treated water. This multiple bioassay approach, in conjunction with targeted analytical chemistry methods, has gained acceptance among water quality screening programs. Not only was estrogenic and glucocorticoid activity confirmed in the effluent by utilizing multiple methods concurrently, but other activated signaling networks that historically received less attention (i.e. peroxisome proliferator-activated receptor) were also detected.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.134297","usgsCitation":"Medlock Kakaley, E.K., Blackwell, B., Cardon, M.C., Conley, J.M., Evans, N., Feifarek, D.J., Furlong, E., Glassmeyer, S.T., Gray, L.E., Hartig, P.C., Kolpin, D., Mills, M.A., Rosenblum, L., Villeneuve, D.L., and Wilson, V.S., 2020, De facto water reuse: Bioassay suite approach delivers depth and breadth in endocrine active compound detection: Science of the Total Environment, v. 699, https://doi.org/10.1016/j.scitotenv.2019.134297.","productDescription":"134297, 12 p.","startPage":"1-12","ipdsId":"IP-111008","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":458674,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1703348","text":"Publisher Index Page"},{"id":369079,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"699","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Medlock Kakaley, Elizabeth K","contributorId":220449,"corporation":false,"usgs":false,"family":"Medlock Kakaley","given":"Elizabeth","email":"","middleInitial":"K","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":774944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":774945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cardon, Mary C.","contributorId":190792,"corporation":false,"usgs":false,"family":"Cardon","given":"Mary","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":774946,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conley, Justin M.","contributorId":184086,"corporation":false,"usgs":false,"family":"Conley","given":"Justin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":774947,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Evans, Nicola","contributorId":184087,"corporation":false,"usgs":false,"family":"Evans","given":"Nicola","email":"","affiliations":[],"preferred":false,"id":774948,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Feifarek, David J.","contributorId":198057,"corporation":false,"usgs":false,"family":"Feifarek","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":774949,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Furlong, Edward 0000-0002-7305-4603","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":213730,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":774950,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Glassmeyer, Susan T.","contributorId":184135,"corporation":false,"usgs":false,"family":"Glassmeyer","given":"Susan","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":774951,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gray, L. Earl","contributorId":220450,"corporation":false,"usgs":false,"family":"Gray","given":"L.","email":"","middleInitial":"Earl","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":774952,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hartig, Phillip C.","contributorId":190793,"corporation":false,"usgs":false,"family":"Hartig","given":"Phillip","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":774953,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":205652,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":774943,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mills, Marc A.","contributorId":141085,"corporation":false,"usgs":false,"family":"Mills","given":"Marc","email":"","middleInitial":"A.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":774954,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rosenblum, Laura","contributorId":184089,"corporation":false,"usgs":false,"family":"Rosenblum","given":"Laura","email":"","affiliations":[],"preferred":false,"id":774955,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Villeneuve, Daniel L.","contributorId":141084,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Daniel","email":"","middleInitial":"L.","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":774956,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wilson, Vickie S. 0000-0003-1661-8481","orcid":"https://orcid.org/0000-0003-1661-8481","contributorId":184092,"corporation":false,"usgs":false,"family":"Wilson","given":"Vickie","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":774957,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70208108,"text":"70208108 - 2020 - A range-wide model of contemporary, omnidirectional connectivity for the threatened Mojave desert tortoise","interactions":[],"lastModifiedDate":"2020-01-27T19:26:20","indexId":"70208108","displayToPublicDate":"2019-09-03T19:22:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"A range-wide model of contemporary, omnidirectional connectivity for the threatened Mojave desert tortoise","docAbstract":"As habitat destruction leads to species extinctions globally, conservation planning that accounts for population-level connectivity and gene flow is an urgent priority. Models that only approximate habitat potential are incomplete because areas of high habitat potential may be isolated, whereas intermixed areas of lower habitat potential may still be critical for maintaining connectivity between and among populations. We developed a range-wide, omnidirectional (‘coreless’) connectivity model and map for the threatened Mojave desert tortoise at a high spatial resolution (30 m), based on empirical movement data and a circuit-theoretic approach to estimating connectivity. Specifically, we first estimated habitat potential (i.e., quality) for tortoise movement (as distinct from habitat potential more generally) across its range using hypotheses based on the published literature, linear mixed models, multiple environmental factors derived from remotely sensed data, and recent solar and wind development footprints. The resultant raster output was used to represent landscape conductance in a circuit-theoretic model of connectivity, which relates the flow of electrical current through a circuit to the movement of tortoises through the landscape. We then modeled potential connectivity across the range of the tortoise using Circuitscape software and the Julia numerical programming language. Intermediate distances from minor roads, intermediate values of annual average maximum temperature, and increasing density of desert washes were among the strongest predictors of movement habitat quality. There was also strong evidence for increased habitat quality for movement with increasing amounts of vegetation cover. The resulting connectivity model and map was determined to accurately reflect important areas for tortoise movement, but we encourage others to do their own evaluation of the model within local areas of interest and as more data become available.  Accordingly, the map can provide an important component to improve management decisions that have the potential to influence the conservation of connected desert tortoise populations throughout the range.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2847","usgsCitation":"Gray, M.E., Dickson, B.G., Nussear, K., Esque, T., and Chang, T., 2020, A range-wide model of contemporary, omnidirectional connectivity for the threatened Mojave desert tortoise: Ecosphere, v. 10, no. 9, e02847, https://doi.org/10.1002/ecs2.2847.","productDescription":"e02847","ipdsId":"IP-109686","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458676,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2847","text":"Publisher Index Page"},{"id":371617,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Desert ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.3946533203125,\n              33.65578083204094\n            ],\n            [\n              -114.70275878906249,\n              33.280027811732154\n            ],\n            [\n              -114.40612792968749,\n              35.14686290675633\n            ],\n            [\n              -115.77941894531249,\n              35.92464453144099\n            ],\n            [\n              -116.70227050781249,\n              35.420391545750746\n            ],\n            [\n              -117.32299804687499,\n              34.985003130171066\n            ],\n            [\n              -116.83959960937499,\n              34.347971491244955\n            ],\n            [\n              -116.3946533203125,\n              33.65578083204094\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"9","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Gray, Miranda E","contributorId":221848,"corporation":false,"usgs":false,"family":"Gray","given":"Miranda","email":"","middleInitial":"E","affiliations":[{"id":40441,"text":"Conservation Science Partners, Truckee, CA","active":true,"usgs":false}],"preferred":false,"id":780491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dickson, Brett G.","contributorId":221849,"corporation":false,"usgs":false,"family":"Dickson","given":"Brett","email":"","middleInitial":"G.","affiliations":[{"id":40442,"text":"Conservation Science Partners, Truckee, CA; Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":780492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nussear, Kenneth","contributorId":194538,"corporation":false,"usgs":false,"family":"Nussear","given":"Kenneth","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":780493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780490,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chang, Tony","contributorId":191992,"corporation":false,"usgs":false,"family":"Chang","given":"Tony","email":"","affiliations":[],"preferred":false,"id":780494,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70211191,"text":"70211191 - 2020 - Permafrost hydrology drives the assimilation of old carbon by stream food webs in the Arctic","interactions":[],"lastModifiedDate":"2020-07-16T18:49:40.296564","indexId":"70211191","displayToPublicDate":"2019-09-03T13:44:11","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Permafrost hydrology drives the assimilation of old carbon by stream food webs in the Arctic","docAbstract":"<p><span>Permafrost thaw in the Arctic is mobilizing old carbon (C) from soils to aquatic ecosystems and the atmosphere. Little is known, however, about the assimilation of old C by aquatic food webs in Arctic watersheds. Here, we used C isotopes (δ</span><sup>13</sup><span>C, Δ</span><sup>14</sup><span>C) to quantify C assimilation by biota across 12 streams in arctic Alaska. Streams spanned watersheds with varying permafrost hydrology, from ice-poor bedrock to ice-rich loess (that is, yedoma). We measured isotopic content of (1) C sources including dissolved organic C (DOC), dissolved inorganic C (DIC), and soil C, and (2) stream biota, including benthic biofilm and macroinvertebrates, and resident fish species (Arctic Grayling (</span><i>Thymallus arcticus</i><span>) and Dolly Varden (</span><i>Salvelinus malma</i><span>)). Findings document the assimilation of old C by stream biota, with depleted Δ</span><sup>14</sup><span>C values observed at multiple trophic levels, including benthic biofilm (</span><sup>14</sup><span>C ages = 5255 to 265&nbsp;years before present (y BP)), macroinvertebrates (4490 y BP to modern), and fish (3195 y BP to modern). Mixing model results indicate that DOC and DIC contribute to benthic biofilm composition, with relative contributions differing across streams draining ice-poor and ice-rich terrain. DOC originates primarily from old terrestrial C sources, including deep peat horizons (39–47%; 530 y BP) and near-surface permafrost (12–19%; 5490 y BP). DOC also accounts for approximately half of fish isotopic composition. Analyses suggest that as the contribution of old C to fish increases, fish growth and nutritional status decline. We anticipate increases in old DOC delivery to streams under projected warming, which may further alter food web function in Arctic watersheds.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10021-019-00413-6","usgsCitation":"O'Donnell, J., Carey, M.P., Koch, J.C., Xu, X., Poulin, B., Walker, J., and Zimmerman, C.E., 2020, Permafrost hydrology drives the assimilation of old carbon by stream food webs in the Arctic: Ecosystems, v. 23, p. 435-453, https://doi.org/10.1007/s10021-019-00413-6.","productDescription":"19 p.","startPage":"435","endPage":"453","ipdsId":"IP-102831","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":437218,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NAUIQR","text":"USGS data release","linkHelpText":"Carbon Isotope Concentrations in Stream Food Webs of the Arctic Network National Parks, Alaska, 2014-2016"},{"id":376449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bering Land Bridge and Noatak National Preserves","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -165.58593749999997,\n              65.4217295985527\n            ],\n            [\n              -156.09375,\n              65.4217295985527\n            ],\n            [\n              -156.09375,\n              68.12248241161676\n            ],\n            [\n              -165.58593749999997,\n              68.12248241161676\n            ],\n            [\n              -165.58593749999997,\n              65.4217295985527\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2019-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"O'Donnell, Jonathon A 0000-0001-7031-9808","orcid":"https://orcid.org/0000-0001-7031-9808","contributorId":222968,"corporation":false,"usgs":false,"family":"O'Donnell","given":"Jonathon A","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":793044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":793045,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":793046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xu, Xiaomei","contributorId":139915,"corporation":false,"usgs":false,"family":"Xu","given":"Xiaomei","email":"","affiliations":[{"id":13312,"text":"University of California-Irvine","active":true,"usgs":false}],"preferred":false,"id":793047,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poulin, Brett 0000-0002-5555-7733 bpoulin@usgs.gov","orcid":"https://orcid.org/0000-0002-5555-7733","contributorId":194253,"corporation":false,"usgs":true,"family":"Poulin","given":"Brett","email":"bpoulin@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":793048,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walker, Jennifer","contributorId":201558,"corporation":false,"usgs":false,"family":"Walker","given":"Jennifer","affiliations":[],"preferred":false,"id":793049,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":793050,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70227104,"text":"70227104 - 2020 - Attack of the PCR clones: Rates of clonality have little effect on RAD-seq genotype calls","interactions":[],"lastModifiedDate":"2021-12-29T14:00:37.386552","indexId":"70227104","displayToPublicDate":"2019-09-03T07:57:16","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2776,"text":"Molecular Ecology Resources","active":true,"publicationSubtype":{"id":10}},"title":"Attack of the PCR clones: Rates of clonality have little effect on RAD-seq genotype calls","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Interpretation of high-throughput sequence data requires an understanding of how decisions made during bioinformatic data processing can influence results. One source of bias that is often cited is PCR clones (or PCR duplicates). PCR clones are common in restriction site-associated sequencing (RAD-seq) data sets, which are increasingly being used for molecular ecology. To determine the influence PCR clones and the bioinformatic handling of clones have on genotyping, we evaluate four RAD-seq data sets. Data sets were compared before and after clones were removed to estimate the number of clones present in RAD-seq data, quantify how often the presence of clones in a data set causes genotype calls to change compared to when clones were removed, investigate the mechanisms that lead to genotype call changes and test whether clones bias heterozygosity estimates. Our RAD-seq data sets contained 30%–60% PCR clones, but 95% of RAD-tags had five or fewer clones. Relatively few genotypes changed once clones were removed (5%–10%), and the vast majority of these changes (98%) were associated with genotypes switching from a called to no-call state or vice versa. PCR clones had a larger influence on genotype calls in individuals with low read depth but appeared to influence genotype calls at all loci similarly. Removal of PCR clones reduced the number of called genotypes by 2% but had almost no influence on estimates of heterozygosity. As such, while steps should be taken to limit PCR clones during library preparation, PCR clones are likely not a substantial source of bias for most RAD-seq studies.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/1755-0998.13087","usgsCitation":"Euclide, P.T., McKinney, G., Bootsma, M., Tarsa, C., Meek, M., and Larson, W., 2020, Attack of the PCR clones: Rates of clonality have little effect on RAD-seq genotype calls: Molecular Ecology Resources, v. 20, no. 1, p. 66-78, https://doi.org/10.1111/1755-0998.13087.","productDescription":"13 p.","startPage":"66","endPage":"78","ipdsId":"IP-107066","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":393570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Euclide, Peter T.","contributorId":270640,"corporation":false,"usgs":false,"family":"Euclide","given":"Peter","email":"","middleInitial":"T.","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":829639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKinney, Garrett","contributorId":270641,"corporation":false,"usgs":false,"family":"McKinney","given":"Garrett","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":829640,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bootsma, Matthew","contributorId":270643,"corporation":false,"usgs":false,"family":"Bootsma","given":"Matthew","email":"","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":829641,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tarsa, Charlene","contributorId":270644,"corporation":false,"usgs":false,"family":"Tarsa","given":"Charlene","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":829642,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meek, Mariah","contributorId":270645,"corporation":false,"usgs":false,"family":"Meek","given":"Mariah","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":829643,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Larson, Wesley 0000-0003-4473-3401 wlarson@usgs.gov","orcid":"https://orcid.org/0000-0003-4473-3401","contributorId":199509,"corporation":false,"usgs":true,"family":"Larson","given":"Wesley","email":"wlarson@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":829638,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70208375,"text":"70208375 - 2020 - Influence of a high-head dam as a dispersal barrier to fish community structure of the Upper Mississippi River","interactions":[],"lastModifiedDate":"2020-02-05T15:56:21","indexId":"70208375","displayToPublicDate":"2019-09-01T15:50:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Influence of a high-head dam as a dispersal barrier to fish community structure of the Upper Mississippi River","docAbstract":"<p><span>In river systems, high‐head dams may increase the distance‐decay of fish community similarity by creating nearly impermeable dispersal barriers to certain species from upstream reaches. Substantial evidence suggests that migratory species are impacted by dams, and most previous studies in stream/river networks have focused on small streams and headwaters. Here, we assess whether a high‐head dam (Lock and Dam 19; LD 19) on a large river, the Upper Mississippi River (UMR), substantially alters fish community structure relative to variability expected to occur independent of the dam's effect as a fish dispersal barrier. Using fish catch per unit effort data, we modelled the distance‐decay function for the UMR fish community and then estimated the similarity that would be expected to occur across LD19 and compared it with measured similarity. Measured similarity in the fish community above and below LD19 was close to the expected value based on the distance‐decay function, suggesting LD19 does not create an abrupt transition in the fish community. Although some migratory fish species no longer occur above LD19 (e.g., skipjack herring,&nbsp;</span><i>Alosa chrysochloris</i><span>), these species do not occur in high abundance below the dam and so do not drive variation in fish community structure. Instead, much of the variation in species structure is driven by the loss/gain of species across the latitudinal gradient. Lock and Dam 19 does not appear to be a clear transition point in the river's fish community, although it may function as a meaningful barrier for particular species (e.g., invasive species) and warrant future attention from a management perspective.</span></p>","language":"English","publisher":"John Wiley and Sons, Inc.","doi":"10.1002/rra.3534","usgsCitation":"Anderson, R.L., Anderson, C.A., Larson, J.H., Knights, B.C., Vallazza, J.M., Jenkins, S.E., and Lamer, J.T., 2020, Influence of a high-head dam as a dispersal barrier to fish community structure of the Upper Mississippi River: River Research and Applications, v. 36, no. 1, p. 47-56, https://doi.org/10.1002/rra.3534.","productDescription":"10 p.","startPage":"47","endPage":"56","ipdsId":"IP-095942","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":458682,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.3534","text":"Publisher Index Page"},{"id":372095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92.8125,\n              37.52715361723378\n            ],\n            [\n              -88.79150390625,\n              37.52715361723378\n            ],\n            [\n              -88.79150390625,\n              44.68427737181225\n            ],\n            [\n              -92.8125,\n              44.68427737181225\n            ],\n            [\n              -92.8125,\n              37.52715361723378\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Rebekah L.","contributorId":218832,"corporation":false,"usgs":false,"family":"Anderson","given":"Rebekah","email":"","middleInitial":"L.","affiliations":[{"id":39921,"text":"Illinois Deptment of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":781660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Cory A.","contributorId":196305,"corporation":false,"usgs":false,"family":"Anderson","given":"Cory","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":781661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":781659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":781662,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vallazza, Jonathan M. 0000-0003-2367-4887 jvallazza@usgs.gov","orcid":"https://orcid.org/0000-0003-2367-4887","contributorId":149362,"corporation":false,"usgs":true,"family":"Vallazza","given":"Jonathan","email":"jvallazza@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":781663,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jenkins, Sean E.","contributorId":199666,"corporation":false,"usgs":false,"family":"Jenkins","given":"Sean","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":781665,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lamer, James T. 0000-0003-1155-1548","orcid":"https://orcid.org/0000-0003-1155-1548","contributorId":196307,"corporation":false,"usgs":false,"family":"Lamer","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":48847,"text":"Illinois River Biological Station, Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":781664,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70212604,"text":"70212604 - 2020 - Porphyry copper potential of the U.S. Southern Basin and Range using  ASTER data integrated with geochemical and geologic datasets to  assess potential near-surface deposits in well-explored permissive tracts","interactions":[],"lastModifiedDate":"2020-08-24T12:21:59.418909","indexId":"70212604","displayToPublicDate":"2019-09-01T15:21:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Porphyry copper potential of the U.S. Southern Basin and Range using  ASTER data integrated with geochemical and geologic datasets to  assess potential near-surface deposits in well-explored permissive tracts","docAbstract":"<p><span>ArcGIS was used to spatially assess and rank potential porphyry copper deposits using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data together with geochemical and geologic datasets in order to estimate undiscovered deposits in the southern Basin and Range Province in the southwestern United States. The assessment was done using a traditional expert opinion three-part method and a prospectivity model developed using weights of evidence and logistic regression techniques to determine if ASTER data integrated with other geologic datasets can be used to find additional areas of prospectivity in well-explored permissive tracts. ASTER hydrothermal alteration data were expressed as 457 alteration polygons defined from a low-pass filtered alteration density map of combined argillic, phyllic, and propylitic rock units. Sediment stream samples were plotted as map grid data and used as spatial information in ASTER polygons. Gravity and magnetic data were also used to define basins greater than 1 km in depth. Each ASTER alteration polygon was ranked for porphyry copper potential using alteration types, spatial amounts of alteration, stream sediment geochemistry, lithology, polygon shape, proximity to other alteration polygons, and deposit and prospects data. Permissive tracts defined for the assessment in the southern Basin and Range Province include the Laramide Northwest, Laramide Southeast, Jurassic, and Tertiary tracts. Expert opinion estimates using the three-part assessment method resulted in a mean estimate of 17 undiscovered porphyry copper deposits, whereas the prospectivity modeling predicted a mean estimate of nine undiscovered deposits. In the well-explored Laramide Southeast tract, which contains the most deposits and has been explored for over 100 years, an average of 4.3 undiscovered deposits was estimated using ASTER alteration polygon data versus 2.8 undiscovered deposits without ASTER data. The Tertiary tract, which contains the largest number of ASTER alteration polygons not associated with known Tertiary deposits, was predicted to contain the most undiscovered resources in the southern Basin and Range Province.</span></p>","language":"English","publisher":"Economic Geology","doi":"10.5382/econgeo.4675","usgsCitation":"Mars, J.C., Robinson, Hammarstrom, J.M., Zurcher, L., Whitney, H.A., Solano, F., Gettings, M.E., and Ludington, S., 2020, Porphyry copper potential of the U.S. Southern Basin and Range using  ASTER data integrated with geochemical and geologic datasets to  assess potential near-surface deposits in well-explored permissive tracts: Economic Geology, v. 114, no. 6, p. 1095-1121, https://doi.org/10.5382/econgeo.4675.","productDescription":"27 p.","startPage":"1095","endPage":"1121","ipdsId":"IP-096385","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":458683,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5382/econgeo.4675","text":"Publisher Index Page"},{"id":377769,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.50146484374999,\n              31.82156451492074\n            ],\n            [\n              -106.787109375,\n              32.34284135639302\n            ],\n            [\n              -107.11669921875,\n              32.713355353177555\n            ],\n            [\n              -107.51220703125,\n              32.95336814579932\n            ],\n            [\n           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Center","active":true,"usgs":true}],"preferred":true,"id":797004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Jr. 0000-0002-9676-9564","orcid":"https://orcid.org/0000-0002-9676-9564","contributorId":8479,"corporation":false,"usgs":true,"family":"Robinson","suffix":"Jr.","email":"","affiliations":[{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":797005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hammarstrom, Jane M. 0000-0003-2742-3460 jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":797006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zurcher, Lukas 0000-0001-5575-1192 lzurcher@usgs.gov","orcid":"https://orcid.org/0000-0001-5575-1192","contributorId":172674,"corporation":false,"usgs":true,"family":"Zurcher","given":"Lukas","email":"lzurcher@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":797007,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whitney, Helen A. 0000-0003-0137-8729","orcid":"https://orcid.org/0000-0003-0137-8729","contributorId":239285,"corporation":false,"usgs":true,"family":"Whitney","given":"Helen","email":"","middleInitial":"A.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":797008,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Solano, Federico 0000-0002-0308-5850","orcid":"https://orcid.org/0000-0002-0308-5850","contributorId":213145,"corporation":false,"usgs":true,"family":"Solano","given":"Federico","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":797009,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gettings, Mark E. 0000-0002-2910-2321 mgetting@usgs.gov","orcid":"https://orcid.org/0000-0002-2910-2321","contributorId":602,"corporation":false,"usgs":true,"family":"Gettings","given":"Mark","email":"mgetting@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":797010,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ludington, Stephen 0000-0002-6265-4996 slud@usgs.gov","orcid":"https://orcid.org/0000-0002-6265-4996","contributorId":172672,"corporation":false,"usgs":true,"family":"Ludington","given":"Stephen","email":"slud@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":797011,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70211499,"text":"70211499 - 2020 - Incorporating climate change into invasive species management: Insights from managers","interactions":[],"lastModifiedDate":"2020-07-29T00:01:06.006358","indexId":"70211499","displayToPublicDate":"2019-08-31T18:54:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating climate change into invasive species management: Insights from managers","docAbstract":"<p><span>Invasive alien species are likely to interact with climate change, thus necessitating management that proactively addresses both global changes. However, invasive species managers’ concerns about the effects of climate change, the degree to which they incorporate climate change into their management, and what stops them from doing so remain unknown. Therefore, we surveyed natural resource managers addressing invasive species across the U.S. about their priorities, concerns, and management strategies in a changing climate. Of the 211 managers we surveyed, most were very concerned about the influence of climate change on invasive species management, but their organizations were significantly less so. Managers reported that lack of funding and personnel limited their ability to effectively manage invasive species, while lack of information limited their consideration of climate change in decision-making. Additionally, managers prioritized research that identifies range-shifting invasive species and native communities resilient to invasions and climate change. Managers also reported that this information would be most effectively communicated through conversations, research summaries, and meetings/symposia. Despite the need for more information, 65% of managers incorporate climate change into their invasive species management through strategic planning, preventative management, changing treatment and control, and increasing education and outreach. These results show the potential for incorporating climate change into management, but also highlight a clear and pressing need for more targeted research, accessible science communication, and two-way dialogue between researchers and managers focused on invasive species and climate change.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10530-019-02087-6","usgsCitation":"Beaury, E.M., Fusco, E.J., Jackson, M.R., Laginhas, B.B., Morelli, T.L., Allen, J.M., Pasquarella, V.J., and Bradley, B.A., 2020, Incorporating climate change into invasive species management: Insights from managers: Biological Invasions, v. 22, p. 233-252, https://doi.org/10.1007/s10530-019-02087-6.","productDescription":"20 p.","startPage":"233","endPage":"252","ipdsId":"IP-109690","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":458686,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10530-019-02087-6","text":"Publisher Index Page"},{"id":376816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","noUsgsAuthors":false,"publicationDate":"2019-08-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Beaury, Evelyn M.","contributorId":236820,"corporation":false,"usgs":false,"family":"Beaury","given":"Evelyn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":794354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fusco, Emily J.","contributorId":236821,"corporation":false,"usgs":false,"family":"Fusco","given":"Emily","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":794355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, Michelle R.","contributorId":236822,"corporation":false,"usgs":false,"family":"Jackson","given":"Michelle","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":794356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laginhas, Brittany B.","contributorId":236823,"corporation":false,"usgs":false,"family":"Laginhas","given":"Brittany","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":794357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":794358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allen, Jenica M.","contributorId":146420,"corporation":false,"usgs":false,"family":"Allen","given":"Jenica","email":"","middleInitial":"M.","affiliations":[{"id":13006,"text":"Department of Ecology and Evolutionary Biology, University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":794359,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pasquarella, Valerie J.","contributorId":236824,"corporation":false,"usgs":false,"family":"Pasquarella","given":"Valerie","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":794360,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bradley, Bethany A.","contributorId":40117,"corporation":false,"usgs":true,"family":"Bradley","given":"Bethany","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":794361,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70211842,"text":"70211842 - 2020 - The influence of sample matrix on the accuracy of nitrite N and O isotope ratio analyses with the azide method","interactions":[],"lastModifiedDate":"2020-08-07T20:58:04.651731","indexId":"70211842","displayToPublicDate":"2019-08-31T15:55:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3233,"text":"Rapid Communications in Mass Spectrometry","active":true,"publicationSubtype":{"id":10}},"title":"The influence of sample matrix on the accuracy of nitrite N and O isotope ratio analyses with the azide method","docAbstract":"<h3 id=\"rcm8569-sec-0001-title\" class=\"article-section__sub-title section1\">Rationale</h3><p>The isotope ratios of nitrogen (<sup>15</sup>N/<sup>14</sup>N) and oxygen (<sup>18</sup>O/<sup>16</sup>O) in nitrite (NO<sub>2</sub><sup>−</sup>) can be measured by conversion of the nitrite into nitrous oxide (N<sub>2</sub>O) with azide, followed by mass spectrometric analysis of N<sub>2</sub>O by gas chromatography isotope ratio mass spectrometry (GC/IRMS). While applying this method to brackish samples, we noticed that the N and O isotope ratio measurements of NO<sub>2</sub><sup>−</sup><span>&nbsp;</span>are highly sensitive to sample salinity and to the pH at which samples are preserved.</p><h3 id=\"rcm8569-sec-0002-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We investigated the influence of sample salinity and sample preservation pH on the N and O isotope ratios of the N<sub>2</sub>O produced from the reaction of NO<sub>2</sub><sup>−</sup><span>&nbsp;</span>with azide. The N<sub>2</sub>O isotope ratios were measured by GC/IRMS.</p><h3 id=\"rcm8569-sec-0003-title\" class=\"article-section__sub-title section1\">Results</h3><p>Under the experimental reaction conditions, the conversion of NO<sub>2</sub><sup>−</sup><span>&nbsp;</span>into N<sub>2</sub>O was less complete in lower salinity solutions, resulting in respective N and O isotopic offsets of +2.5‰ and −14.0‰ compared with seawater solutions. Differences in salinity were also associated with differences in the fraction of O atoms exchanged between NO<sub>2</sub><sup>−</sup><span>&nbsp;</span>and water during the reaction. Similarly, aqueous NO<sub>2</sub><sup>−</sup><span>&nbsp;</span>samples preserved at elevated pH values resulted in the incomplete conversion of NO<sub>2</sub><sup>−</sup><span>&nbsp;</span>into N<sub>2</sub>O by azide, and consequent pH‐dependent isotopic offsets, as well as differences in the fraction of O atoms exchanged with water. The addition of sodium chloride to the reaction matrix of samples and standards largely mitigated salinity‐dependent isotopic offsets in the N<sub>2</sub>O product, and nearly homogenized the fraction of O atom exchange among samples of different salinity. A test of the hypobromite–azide method to measure N isotope ratios of ammonium by conversion into NO<sub>2</sub><sup>−</sup><span>&nbsp;</span>then N<sub>2</sub>O revealed no influence of sample salinity on the N isotope ratios of the N<sub>2</sub>O product.</p><h3 id=\"rcm8569-sec-0004-title\" class=\"article-section__sub-title section1\">Conclusions</h3><p>We outline recommendations to mitigate potential matrix effects among samples and standards, to improve the accuracy of N and O isotope ratios in NO<sub>2</sub><sup>−</sup><span>&nbsp;</span>measured with the azide method.</p>","language":"English","publisher":"Wiley","doi":"10.1002/rcm.8569","usgsCitation":"Granger, J., Boshers, D.S., Bohlke, J., Yu, D., Chen, N., and Tobias, C.R., 2020, The influence of sample matrix on the accuracy of nitrite N and O isotope ratio analyses with the azide method: Rapid Communications in Mass Spectrometry, v. 34, e8569, 12 p., https://doi.org/10.1002/rcm.8569.","productDescription":"e8569, 12 p.","ipdsId":"IP-110163","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":377206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","noUsgsAuthors":false,"publicationDate":"2020-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Granger, Julie","contributorId":214194,"corporation":false,"usgs":false,"family":"Granger","given":"Julie","email":"","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":795339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boshers, Danielle S.","contributorId":214193,"corporation":false,"usgs":false,"family":"Boshers","given":"Danielle","email":"","middleInitial":"S.","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":795340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":795341,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yu, Dan","contributorId":237802,"corporation":false,"usgs":false,"family":"Yu","given":"Dan","email":"","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":795342,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chen, Nengwang","contributorId":237803,"corporation":false,"usgs":false,"family":"Chen","given":"Nengwang","email":"","affiliations":[{"id":47617,"text":"Xiamen University, China","active":true,"usgs":false}],"preferred":false,"id":795343,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tobias, Craig R.","contributorId":191283,"corporation":false,"usgs":false,"family":"Tobias","given":"Craig","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":795344,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70206109,"text":"70206109 - 2020 - Temporal patterns of induced seismicity in Oklahoma revealed from multi-station template matching","interactions":[],"lastModifiedDate":"2020-10-13T22:50:25.42041","indexId":"70206109","displayToPublicDate":"2019-08-29T08:05:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2453,"text":"Journal of Seismology","active":true,"publicationSubtype":{"id":10}},"title":"Temporal patterns of induced seismicity in Oklahoma revealed from multi-station template matching","docAbstract":"<p><span>Over the past decade, Oklahoma became the most seismically active region of the mid-Continental USA as a result of industry operations. However, seismic network limitations and completeness of earthquake catalogs have restricted the types of analyses that can be performed. By applying multi-station template matching on the 23,889 cataloged earthquakes in Oklahoma and Southern Kansas between late-2008 and 2016, we increased the number of detected earthquakes to 209,409 events. While the improved catalog produced an order of magnitude events than the original catalog, the frequency-magnitude distribution remains similar to the original catalog. We found that the coefficient of variation of interevent times in small spatial bins tends to spatially correlate with the location of&nbsp;</span><i>M</i><span>&nbsp;≥ 4 earthquakes. The improved catalog reveals the pervasiveness of swarm-like patterns in seismicity across the entire study region. The rapid increase in seismicity rate of these swarms in 2013 coincided with a reduction in the calculated&nbsp;</span><i>p</i><span>&nbsp;values (power law decay rates) before and after larger events. We also used the catalog to revisit the temporal patterns in the four&nbsp;</span><i>M</i><span>&nbsp;≥ 5 sequences, finding more active foreshock behavior than previously recognized and variations in aftershock behavior. When compared against poroelastic stress models for the Pawnee and Fairview sequences, the catalog shows an improved correlation with stress that accounts for variable-rate injection, supporting the conclusion that injection rate is an important contributor to seismic hazard.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10950-019-09864-9","usgsCitation":"Skoumal, R.J., Brudzinski, M.R., Currie, B.S., and Ries, R., 2020, Temporal patterns of induced seismicity in Oklahoma revealed from multi-station template matching: Journal of Seismology, v. 24, p. 921-935, https://doi.org/10.1007/s10950-019-09864-9.","productDescription":"15 p.","startPage":"921","endPage":"935","ipdsId":"IP-090908","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":368504,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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University","active":true,"usgs":false}],"preferred":false,"id":773611,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Currie, Brian S.","contributorId":207881,"corporation":false,"usgs":false,"family":"Currie","given":"Brian","email":"","middleInitial":"S.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":773612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ries, Rosamiel","contributorId":211773,"corporation":false,"usgs":false,"family":"Ries","given":"Rosamiel","email":"","affiliations":[{"id":38316,"text":"Miami University, Oxford, Ohio","active":true,"usgs":false}],"preferred":false,"id":773613,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70206445,"text":"70206445 - 2020 - A meta-analysis of global crop water productivity of three leading world crops (wheat, corn, and rice) in the irrigated areas over three decades","interactions":[],"lastModifiedDate":"2020-08-05T13:58:56.739844","indexId":"70206445","displayToPublicDate":"2019-08-28T15:41:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2035,"text":"International Journal of Digital Earth","active":true,"publicationSubtype":{"id":10}},"title":"A meta-analysis of global crop water productivity of three leading world crops (wheat, corn, and rice) in the irrigated areas over three decades","docAbstract":"<p><span>The overarching goal of this study was to perform a comprehensive meta-analysis of irrigated agricultural Crop Water Productivity (CWP) of the world’s three leading crops: wheat, corn, and rice based on three decades of remote sensing and non-remote sensing-based studies. Overall, CWP data from 148 crop growing study sites (60 wheat, 43 corn, and 45 rice) spread across the world were gathered from published articles spanning 31 different countries. There was overwhelming evidence of a significant increase in CWP with an increase in latitude for predominately northern hemisphere datasets. For example, corn grown in latitude 40–50° had much higher mean CWP (2.45 kg/m³) compared to mean CWP of corn grown in other latitudes such as 30–40° (1.67 kg/m³) or 20–30° (0.94 kg/m³). The same trend existed for wheat and rice as well. For soils, none of the CWP values, for any of the three crops, were statistically different. However, mean CWP in higher latitudes for the same soil was significantly higher than the mean CWP for the same soil in lower latitudes. This applied for all three crops studied. For wheat, the global CWP categories were low (≤0.75 kg/m³), medium (&gt;0.75 to &lt;1.10 kg/m³), and high CWP (≥1.10 kg/m³). For corn the global CWP categories were low (≤1.25 kg/m³), medium (&gt;1.25 to ≤1.75 kg/m³), and high (&gt;1.75 kg/m³). For rice the global CWP categories were low (≤0.70 kg/m³), medium (&gt;0.70 to ≤1.25 kg/m³), and high (&gt;1.25 kg/m³). USA and China are the only two countries that have consistently high CWP for wheat, corn, and rice. Australia and India have medium CWP for wheat and rice. India’s corn, however, has low CWP. Egypt, Turkey, Netherlands, Mexico, and Israel have high CWP for wheat. Romania, Argentina, and Hungary have high CWP for corn, and Philippines has high CWP for rice. All other countries have either low or medium CWP for all three crops. Based on data in this study, the highest consumers of water for crop production also have the most potential for water savings. These countries are USA, India, and China for wheat; USA, China, and Brazil for corn; India, China, and Pakistan for rice. For example, even just a 10% increase in CWP of wheat grown in India can save 6974 billion liters of water. This is equivalent to creating 6974 lakes each of 100 m³ in volume that leads to many benefits such as acting as ‘water banks’ for lean season, recreation, and numerous ecological services. This study establishes the volume of water that can be saved for each crop in each country when there is an increase in CWP by 10%, 20%, and 30%.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/17538947.2019.1651912","usgsCitation":"Daniel J. Foley, Thenkabail, P., Aneece, I., Pardhasaradhi Teluguntla, and Oliphant, A., 2020, A meta-analysis of global crop water productivity of three leading world crops (wheat, corn, and rice) in the irrigated areas over three decades: International Journal of Digital Earth, v. 13, no. 8, p. 939-975, https://doi.org/10.1080/17538947.2019.1651912.","productDescription":"37 p.","startPage":"939","endPage":"975","ipdsId":"IP-105160","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":458691,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17538947.2019.1651912","text":"Publisher Index Page"},{"id":368938,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Daniel J. Foley 0000-0002-2051-6325","orcid":"https://orcid.org/0000-0002-2051-6325","contributorId":220240,"corporation":false,"usgs":false,"family":"Daniel J. Foley","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":774571,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad 0000-0002-2182-8822","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":220239,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":774570,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aneece, Itiya 0000-0002-1201-5459","orcid":"https://orcid.org/0000-0002-1201-5459","contributorId":220241,"corporation":false,"usgs":true,"family":"Aneece","given":"Itiya","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":774572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pardhasaradhi Teluguntla 0000-0001-8060-9841","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":214457,"corporation":false,"usgs":false,"family":"Pardhasaradhi Teluguntla","affiliations":[{"id":39046,"text":"Bay Area Environmental Research Institute at USGS","active":true,"usgs":false}],"preferred":false,"id":774573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oliphant, Adam 0000-0001-8622-7932 aoliphant@usgs.gov","orcid":"https://orcid.org/0000-0001-8622-7932","contributorId":192325,"corporation":false,"usgs":true,"family":"Oliphant","given":"Adam","email":"aoliphant@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":774574,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70215204,"text":"70215204 - 2020 - Understanding melt evolution and eruption dynamics of the 1666 C.E. eruption of Cinder Cone, Lassen Volcanic National Park, California: Insights from olivine-hosted melt inclusions","interactions":[],"lastModifiedDate":"2020-10-12T14:39:09.465819","indexId":"70215204","displayToPublicDate":"2019-08-27T09:33:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Understanding melt evolution and eruption dynamics of the 1666 C.E. eruption of Cinder Cone, Lassen Volcanic National Park, California: Insights from olivine-hosted melt inclusions","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0090\">Cinder Cone is the youngest scoria cone volcano in the continental United States. Erupted in 1666 C.E. within what is now Lassen Volcanic National Park, Cinder Cone is an un-vegetated scoria cone with well-preserved lava flows and tephra deposits that display complex geochemical variability. In this study, we utilize the volatile (H<sub>2</sub>O, CO<sub>2,</sub><span>&nbsp;</span>Cl), major, and trace element chemistry of olivine-hosted melt inclusions from the tephra deposit of Cinder Cone to better understand the sub-surface evolution of magmas that erupt to produce scoria cones. High-Fo olivine phenocrysts from all erupted units contain melt inclusions that are more primitive in composition than the erupted material. The evolved compositions of the lava and bulk tephra and the abundance of quartz xenocrysts within the deposits suggest the basaltic parental magmas were rapidly contaminated by granitic material in the middle to upper crust, after melt inclusion entrapment. Distinct compositional variability between early and late erupted units suggests two different mantle-derived basaltic magmas were tapped and erupted sequentially as two distinct eruptive phases. The CO<sub>2</sub><span>&nbsp;</span>concentrations in the melt inclusions, after correction for the presence of vapor bubbles, suggest minimum entrapment depths of ~9.5–20&nbsp;km and show no resolvable differences between early and late erupted units at the time of olivine crystallization. Diffusion modeling of Ni and Fo gradients in olivine rims indicates that olivine residence times in an evolving magma were on the order of weeks to years, similar to those calculated for longer-lived scoria cone eruptions, such as Jorullo, in Mexico. Additionally, geochemical evidence suggests that the evolution of parental magmas was likely driven by the partial melting, disaggregation, and assimilation of granitic material in the upper crust. Our combined results provide new insight into the complexities of short-lived monogenetic eruptions.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2019.106665","usgsCitation":"Walowski, K., Wallace, P., Cashman, K., Marks, J., Clynne, M.A., and Ruprecht, P., 2020, Understanding melt evolution and eruption dynamics of the 1666 C.E. eruption of Cinder Cone, Lassen Volcanic National Park, California: Insights from olivine-hosted melt inclusions: Journal of Volcanology and Geothermal Research, v. 387, 106665, 16 p., https://doi.org/10.1016/j.jvolgeores.2019.106665.","productDescription":"106665, 16 p.","ipdsId":"IP-109342","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":379305,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Lassen Volcano National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.8438720703125,\n              39.90973623453719\n            ],\n            [\n              -120.60241699218751,\n              39.90973623453719\n            ],\n            [\n              -120.60241699218751,\n              40.967455873296714\n            ],\n            [\n              -121.8438720703125,\n              40.967455873296714\n            ],\n            [\n              -121.8438720703125,\n              39.90973623453719\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"387","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walowski, Kristina J","contributorId":150156,"corporation":false,"usgs":false,"family":"Walowski","given":"Kristina J","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":801180,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wallace, P.J.","contributorId":242951,"corporation":false,"usgs":false,"family":"Wallace","given":"P.J.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":801181,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cashman, K.V.","contributorId":242952,"corporation":false,"usgs":false,"family":"Cashman","given":"K.V.","email":"","affiliations":[{"id":48591,"text":"University of Bristol, Bristol, U.K.","active":true,"usgs":false}],"preferred":false,"id":801182,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marks, J.K.","contributorId":242953,"corporation":false,"usgs":false,"family":"Marks","given":"J.K.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":801183,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":801184,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ruprecht, P.","contributorId":242954,"corporation":false,"usgs":false,"family":"Ruprecht","given":"P.","email":"","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":801185,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70206262,"text":"70206262 - 2020 - Species-specific responses to wetland mitigation among amphibians in the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2020-02-06T10:56:46","indexId":"70206262","displayToPublicDate":"2019-08-26T06:49:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Species-specific responses to wetland mitigation among amphibians in the Greater Yellowstone Ecosystem","docAbstract":"<p><span>Habitat loss and degradation are leading causes of biodiversity declines, therefore assessing the capacity of created mitigation wetlands to replace habitat for wildlife has become a management priority. We used single season occupancy models to compare the occurrence of larvae of four species of pond‐breeding amphibians in wetlands created for mitigation, wetlands impacted by road construction, and unimpacted reference wetlands along a highway corridor in the Greater Yellowstone Ecosystem, United States. Created wetlands were shallow and had less aquatic vegetation and surface area than impacted and reference wetlands. Occupancy of barred tiger salamander (</span><i>Ambystoma mavortium</i><span>) and boreal chorus frog (</span><i>Pseudacris maculata</i><span>) larvae was similar across wetland types, whereas boreal toads (</span><i>Anaxyrus boreas</i><span>) occurred more often in created wetlands than reference and impacted wetlands. However, the majority of created wetlands (&gt;80%) dried partially or completely before amphibian metamorphosis occurred in both years of our study, resulting in heavy mortality of larvae and, we suspect, little to no recruitment. Columbia spotted frogs (</span><i>Rana luteiventris</i><span>), which require emergent vegetation that is not common in newly created wetlands, occurred commonly in impacted and reference wetlands but were found in only one created wetland. Our results show that shallow created wetlands with little aquatic vegetation may be attractive breeding areas for some amphibians, but may result in high mortality and little recruitment if they fail to hold water for the entire larval period.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/rec.13031","usgsCitation":"Swartz, L., Lowe, W., Muths, E.L., and Hossack, B.R., 2020, Species-specific responses to wetland mitigation among amphibians in the Greater Yellowstone Ecosystem: Restoration Ecology, v. 28, no. 1, p. 206-214, https://doi.org/10.1111/rec.13031.","productDescription":"9 p.","startPage":"206","endPage":"214","ipdsId":"IP-103888","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":368638,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Yellowstone","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.7694091796875,\n              43.40903821777055\n            ],\n            [\n              -108.9129638671875,\n              43.40903821777055\n            ],\n            [\n              -108.9129638671875,\n              45.32897866218559\n            ],\n            [\n              -111.7694091796875,\n              45.32897866218559\n            ],\n            [\n              -111.7694091796875,\n              43.40903821777055\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"28","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Swartz, LK","contributorId":220046,"corporation":false,"usgs":false,"family":"Swartz","given":"LK","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":773968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, WH","contributorId":220047,"corporation":false,"usgs":false,"family":"Lowe","given":"WH","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":773969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":773970,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":773967,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70204933,"text":"70204933 - 2020 - Maximum entropy derived statistics of sound speed structure in a fine-grained sediment inferred from sparse broadband acoustic measurements on the New England continental shelf","interactions":[],"lastModifiedDate":"2020-01-20T12:25:57","indexId":"70204933","displayToPublicDate":"2019-08-23T10:55:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1941,"text":"IEEE Journal of Oceanic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Maximum entropy derived statistics of sound speed structure in a fine-grained sediment inferred from sparse broadband acoustic measurements on the New England continental shelf","docAbstract":"Marginal probability distributions for parameters representing an effective sound-speed structure of a fine-grained sediment are inferred from a data ensemble maximum entropy method that utilizes a sparse spatially distributed set of received pressure time series resulting from multiple explosive sources in a shallow-water ocean environment possessing significant spatial variability of the seabed. A remote sensing seabed acoustics experiment undertaken in March 2017 off the New England Shelf was designed so that multiple independent analyses could infer the statistical properties of the seabed. The current analysis incorporates the measured horizontal variability from interpretations of a subbottom profiling survey of the experimental area. An idealized range- and azimuth-dependent parameterization of the seabed is derived from identification of horizons within the seabed that define multiple sediment layers. A sparse set of explosive charges were deployed on circular tracks with radii of about 2, 4, and 6.5 km with an acoustic array at the center to correlate a set of random measurements to physical acoustic processes that characterize the seabed. The mean values of a surface sound speed ratio and a linear sound speed gradient for the fine-grained sediment layer derived from 12 data samples processed in the 25–275-Hz band provide an estimate of the effective sound-speed structure in a 130-km $^2$ area. The inferred sediment sound speed values are evaluated by predicting measured time series data not used in the statistical inference, and are also compared to historical measurements. Finally, the low-frequency maximum entropy estimate of the sediment sound speed along with physical measurements derived from piston core measurements are utilized to estimate the sediment grain bulk modulus.\npredictions made by the viscous grain shearing model.","language":"English","publisher":"IEEE","doi":"10.1109/JOE.2019.2922717","usgsCitation":"Knobles, D.P., Wilson, P.S., Goff, J., Wan, L., Buckingham, M., Chaytor, J., and Badiey, M., 2020, Maximum entropy derived statistics of sound speed structure in a fine-grained sediment inferred from sparse broadband acoustic measurements on the New England continental shelf: IEEE Journal of Oceanic Engineering, v. 45, no. 1, p. 161-173, https://doi.org/10.1109/JOE.2019.2922717.","productDescription":"9 p.","startPage":"161","endPage":"173","ipdsId":"IP-102085","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":366851,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine, Vermont,  New Hampshire, Massachusetts, Rhode Island, 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Current address:  TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":false,"id":769155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goff, J.A.","contributorId":17004,"corporation":false,"usgs":true,"family":"Goff","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":769156,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wan, L.","contributorId":218393,"corporation":false,"usgs":false,"family":"Wan","given":"L.","email":"","affiliations":[],"preferred":false,"id":769157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buckingham, M.J.","contributorId":28772,"corporation":false,"usgs":true,"family":"Buckingham","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":769158,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chaytor, Jason 0000-0001-8135-8677 jchaytor@usgs.gov","orcid":"https://orcid.org/0000-0001-8135-8677","contributorId":140095,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason","email":"jchaytor@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":769159,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Badiey, Mohsen","contributorId":218394,"corporation":false,"usgs":false,"family":"Badiey","given":"Mohsen","email":"","affiliations":[],"preferred":false,"id":769160,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70208109,"text":"70208109 - 2020 - Social attraction used to establish Caspian tern nesting colonies in San Francisco Bay","interactions":[],"lastModifiedDate":"2020-01-27T19:22:21","indexId":"70208109","displayToPublicDate":"2019-08-14T19:21:25","publicationYear":"2020","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":"Social attraction used to establish Caspian tern nesting colonies in San Francisco Bay","docAbstract":"Conservation of colonial waterbird breeding populations often includes restoring historic nesting habitat or establishing new nesting habitat in protected areas. However, colonization of new or restored nesting habitat may be hindered by the lack of social cues from nesting conspecifics to attract prospecting birds. Social attraction, whereby decoys and colony sound recordings are used to mimic active nesting colonies, has been used successfully to establish waterbird nesting colonies throughout the world. We constructed islands, modified the substrate so that it was attractive to nesting Caspian terns (Hydroprogne caspia), and then used social attraction to establish nesting colonies within two managed ponds in San Francisco Bay, California where Caspian terns had not previously nested. During the 2015–2017 breeding seasons, we deployed decoys of adult Caspian terns, broadcasted colony sound recordings, and monitored Caspian tern response. Caspian terns formed nesting colonies within weeks of social attraction deployment at each of the two ponds in 2015, and the size of these colonies increased in each subsequent year of the study. In 2017, the final year of the study, we estimated a minimum of 501 breeding pairs between the two colonies, making them two of the three largest Caspian tern colonies in the San Francisco Bay estuary. In total, these two colonies produced 1343 nests and 531 fledglings over the three-year study period. Nest densities were low (mean: 0.29 nests/m2 of active colony area) compared to other studies, and greater than 80% of the modified island habitat remained unused by nesting Caspian terns in 2017, suggesting that there is additional space for future colony growth. The successful establishment of two of the largest Caspian tern nesting colonies in the San Francisco Bay estuary in just three years demonstrates the potential of using island construction and habitat modifications, combined with social attraction measures to establish waterbird nesting colonies.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2019.e00757","usgsCitation":"Hartman, C.A., Ackerman, J., Herzog, M.P., Strong, C., and Trachtenbarg, D.A., 2020, Social attraction used to establish Caspian tern nesting colonies in San Francisco Bay: Global Ecology and Conservation, v. 20, e00757, https://doi.org/10.1016/j.gecco.2019.e00757.","productDescription":"e00757","ipdsId":"IP-110956","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458697,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2019.e00757","text":"Publisher Index Page"},{"id":371616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California ","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.04687499999999,\n              37.21283151445594\n            ],\n            [\n              -121.6845703125,\n              37.21283151445594\n            ],\n            [\n              -121.6845703125,\n              38.30718056188316\n            ],\n            [\n              -123.04687499999999,\n              38.30718056188316\n            ],\n            [\n              -123.04687499999999,\n              37.21283151445594\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"20","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780496,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":780495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Strong, Cheryl","contributorId":149428,"corporation":false,"usgs":false,"family":"Strong","given":"Cheryl","email":"","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":780498,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trachtenbarg, David A","contributorId":146351,"corporation":false,"usgs":false,"family":"Trachtenbarg","given":"David","email":"","middleInitial":"A","affiliations":[{"id":16680,"text":"U.S. Army Corps of Engineers, Walla Walla District, Walla Walla, WA 99362","active":true,"usgs":false}],"preferred":false,"id":780499,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70211212,"text":"70211212 - 2020 - Relevance of individual and environmental drivers of movement of Golden Eagles","interactions":[],"lastModifiedDate":"2020-07-17T19:07:15.188554","indexId":"70211212","displayToPublicDate":"2019-08-13T14:04:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"title":"Relevance of individual and environmental drivers of movement of Golden Eagles","docAbstract":"<p><span>An animal's movement is expected to be governed by an interplay between goals determined by its internal state and energetic costs associated with navigating through the external environment. Understanding this ecological process is challenging when an animal moves in two dimensions and even more difficult for birds that move in a third dimension. To understand the dynamic interaction between the internal state of an animal and the variable external environment, we evaluated hypotheses explaining association of different covariates of movement and the trade‐offs birds face as they make behavioural decisions in a fluctuating landscape. We used ~870&nbsp;000 GPS telemetry data points collected from 68 Golden Eagles&nbsp;</span><i>Aquila chrysaetos<span>&nbsp;</span></i><span>to test demographic, diel, topographic and meteorological hypotheses to determine (1) the probability that&nbsp;these birds would be in motion and (2), once in motion, their flight speed. A complex and sometimes interacting set of potential internal and external factors determined movement behaviour. There was good evidence that reproductive state, manifested as age, sex and seasonal effects, had a significant influence on the probability of being in motion and, to a lesser extent, on speed of motion. Likewise, movement responses to the external environment were often unexpectedly strong. These responses, to northness of slope, strength of orographic updraft and intensity of solar radiation, were regionally and temporally variable. In contrast to previous work showing the role of a single environmental factor in determining movement decisions, our analyses support the hypothesis that multiple factors simultaneously interact to influence animal movement. In particular they highlighted how movement is influenced by the interaction between the individual's internal reproductive state and the external environment, and that, of the environmental factors, topographic influences are often more relevant than meteorological influences in determining patterns of flight behaviour. Further disentangling of how these internal and externals states jointly affect movement will provide additional insights into the&nbsp;energetic costs of movement and benefits associated with achieving process‐driven goals.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/ibi.12766","usgsCitation":"Sur, M., Duerr, A.E., Bell, D.A., Fisher, R.N., Tracey, J.A., Bloom, P.H., Miller, T., and Katzner, T., 2020, Relevance of individual and environmental drivers of movement of Golden Eagles: Ibis, v. 162, no. 2, p. 381-399, https://doi.org/10.1111/ibi.12766.","productDescription":"19 p.","startPage":"381","endPage":"399","ipdsId":"IP-100538","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":458700,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ibi.12766","text":"Publisher Index 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 \"}}]}","volume":"162","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-09-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Sur, Maitreyi","contributorId":191354,"corporation":false,"usgs":false,"family":"Sur","given":"Maitreyi","email":"","affiliations":[],"preferred":false,"id":793222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duerr, Adam E.","contributorId":190590,"corporation":false,"usgs":false,"family":"Duerr","given":"Adam","email":"","middleInitial":"E.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":793223,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bell, Doug A.","contributorId":229456,"corporation":false,"usgs":false,"family":"Bell","given":"Doug","email":"","middleInitial":"A.","affiliations":[{"id":41649,"text":"c East Bay Regional Park District","active":true,"usgs":false}],"preferred":false,"id":793224,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":793225,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tracey, Jeff A. 0000-0002-1619-1054 jatracey@usgs.gov","orcid":"https://orcid.org/0000-0002-1619-1054","contributorId":5780,"corporation":false,"usgs":true,"family":"Tracey","given":"Jeff","email":"jatracey@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":793226,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bloom, Peter H.","contributorId":191356,"corporation":false,"usgs":false,"family":"Bloom","given":"Peter","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":793227,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller, Trish","contributorId":229457,"corporation":false,"usgs":false,"family":"Miller","given":"Trish","email":"","affiliations":[{"id":41650,"text":"Conservation Science Global, Inc","active":true,"usgs":false}],"preferred":false,"id":793228,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":793229,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70217897,"text":"70217897 - 2020 - Genetic mark‐recapture analysis of winter faecal pellets allows estimation of population size in Sage Grouse Centrocercus urophasianus","interactions":[],"lastModifiedDate":"2021-02-11T17:44:33.211693","indexId":"70217897","displayToPublicDate":"2019-08-09T07:30:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Genetic mark‐recapture analysis of winter faecal pellets allows estimation of population size in Sage Grouse </>Centrocercus urophasianus</i>","title":"Genetic mark‐recapture analysis of winter faecal pellets allows estimation of population size in Sage Grouse Centrocercus urophasianus","docAbstract":"<div class=\"article-section__content en main\"><p><span>The Sage Grouse&nbsp;</span><i>Centrocercus urophasianus</i><span>&nbsp;is a species of conservation concern throughout its range in western North America. Since the 1950s, the high count of males at leks has been used as an index for monitoring populations. However, the relationship between this lek‐count index and population size is unclear, and its reliability for assessing population trends has been questioned. We used non‐invasive genetic mark‐recapture analysis of faecal and feather samples to estimate pre‐breeding population size for the Parachute‐Piceance‐Roan, a small, geographically isolated population of Sage Grouse in western Colorado, during two consecutive winters from 2012 to 2014. We estimated total pre‐breeding population size as 335 (95% confidence interval (CI): 287–382) in the first winter and 745 (95% CI: 627–864) in the second, an approximate doubling in abundance between years. Although we also observed a large increase in the spring lek‐count index between those years, high male count data poorly represented mark‐recapture estimates of male abundance in each year. Our data suggest that lek counts are useful for detecting the direction and magnitude of large changes in Sage Grouse abundance over time but they may not reliably reflect small changes in abundance that may be relevant to small populations of conservation concern.</span></p></div>","language":"English","publisher":"Wiley","doi":"10.1111/ibi.12768","usgsCitation":"Shyvers, J., Walker, B.L., Oyler-McCance, S.J., Fike, J.A., and Noon, B.R., 2020, Genetic mark‐recapture analysis of winter faecal pellets allows estimation of population size in Sage Grouse Centrocercus urophasianus: Ibis, v. 162, no. 3, p. 749-765, https://doi.org/10.1111/ibi.12768.","productDescription":"17 p.","startPage":"749","endPage":"765","ipdsId":"IP-105765","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":458702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ibi.12768","text":"Publisher Index Page"},{"id":383194,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -109.072265625,\n              39.45316112807394\n            ],\n            [\n              -106.8310546875,\n              39.45316112807394\n            ],\n            [\n              -106.8310546875,\n              40.613952441166596\n            ],\n            [\n              -109.072265625,\n              40.613952441166596\n            ],\n            [\n              -109.072265625,\n              39.45316112807394\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"162","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Shyvers, Jessica E","contributorId":248864,"corporation":false,"usgs":false,"family":"Shyvers","given":"Jessica E","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":810103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Brett L","contributorId":248865,"corporation":false,"usgs":false,"family":"Walker","given":"Brett","email":"","middleInitial":"L","affiliations":[{"id":36246,"text":"CPW","active":true,"usgs":false}],"preferred":false,"id":810104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":810105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fike, Jennifer A. 0000-0001-8797-7823 fikej@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":140875,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer","email":"fikej@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":810169,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Noon, Barry R.","contributorId":198981,"corporation":false,"usgs":false,"family":"Noon","given":"Barry","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":810107,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70212596,"text":"70212596 - 2020 - Different management strategies are optimal for combating disease in East Texas cave versus culvert hibernating bat populations","interactions":[],"lastModifiedDate":"2020-08-24T12:36:47.547027","indexId":"70212596","displayToPublicDate":"2019-08-08T08:20:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Different management strategies are optimal for combating disease in East Texas cave versus culvert hibernating bat populations","docAbstract":"<p><span>Management decisions for species impacted by emerging infectious diseases are challenging when there are uncertainties in the effectiveness of management actions. Wildlife managers must balance trade‐offs between mitigating the effects of the disease and the associated consequences on other aspects of the managed system. An example of this challenge is exemplified in the response to white‐nose syndrome (WNS), a disease of hibernating bats. The fungal pathogen that causes WNS,&nbsp;</span><i>Pseudogymnoascus destructans</i><span>, continues to spread throughout North America. Texas, recently confirmed positive for the fungus, has documented 33 bat species in the state, with nearly half of those species naïve to the pathogen. We explicitly incorporated multiple management objectives, uncertainty, and risk in the Texas Parks and Wildlife Department decision to manage East Texas populations of the tri‐colored bat (</span><i>Perimyotis subflavus</i><span>), a species highly susceptible to WNS. Alternatives included individual actions that act against&nbsp;</span><i>P</i><span>.&nbsp;</span><i>destructans</i><span>&nbsp;or benefit bats, a no active management option, and combinations of actions. Although our main objective was to identify WNS mitigation measures for tri‐colored bats in culverts, we also considered the transferability of the decision for natural caves. In this scenario, the optimal decision differed for culverts and caves, with a “portfolio” combination of actions ranking as the best alternative for culverts and a single vaccine alternative for caves. Because the top management alternatives differed markedly between these two systems, finding treatments that have broad application is likely infeasible, given that each management decision is characterized by different mixtures of competing objectives.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/csp2.106","usgsCitation":"Bernard, R.F., Evans, J., Fuller, N.W., Reichard, J., Coleman, J., Kocer, C.J., and Campbell Grant, E.H., 2020, Different management strategies are optimal for combating disease in East Texas cave versus culvert hibernating bat populations: Conservation Science and Practice, v. 1, no. 10, e106, 14 p., https://doi.org/10.1111/csp2.106.","productDescription":"e106, 14 p.","ipdsId":"IP-106228","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":458704,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.106","text":"Publisher Index Page"},{"id":377717,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"East Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -99.0966796875,\n              27.293689224852407\n            ],\n            [\n              -93.8671875,\n              27.293689224852407\n            ],\n            [\n              -93.8671875,\n              34.23451236236987\n            ],\n            [\n              -99.0966796875,\n              34.23451236236987\n            ],\n            [\n              -99.0966796875,\n              27.293689224852407\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"1","issue":"10","noUsgsAuthors":false,"publicationDate":"2019-08-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Bernard, Riley Fehr","contributorId":238969,"corporation":false,"usgs":true,"family":"Bernard","given":"Riley","email":"","middleInitial":"Fehr","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":796956,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Jonah","contributorId":239062,"corporation":false,"usgs":false,"family":"Evans","given":"Jonah","email":"","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":796997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuller, Nathan W.","contributorId":239065,"corporation":false,"usgs":false,"family":"Fuller","given":"Nathan","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":796998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reichard, Jonathan D.","contributorId":138946,"corporation":false,"usgs":false,"family":"Reichard","given":"Jonathan D.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":796999,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coleman, Jeremy T. H.","contributorId":138948,"corporation":false,"usgs":false,"family":"Coleman","given":"Jeremy T. H.","affiliations":[{"id":6969,"text":"U.S. Fish and Wildlife Service, Division of Endangered Species","active":true,"usgs":false}],"preferred":false,"id":797000,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kocer, Christina J.","contributorId":239067,"corporation":false,"usgs":false,"family":"Kocer","given":"Christina","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":797001,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":796957,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70208318,"text":"70208318 - 2020 - Global change-driven use of onshore habitat impacts polar bear faecal microbiota","interactions":[],"lastModifiedDate":"2020-02-04T12:26:26","indexId":"70208318","displayToPublicDate":"2019-08-05T12:20:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1956,"text":"ISME Journal","active":true,"publicationSubtype":{"id":10}},"title":"Global change-driven use of onshore habitat impacts polar bear faecal microbiota","docAbstract":"The gut microbiota plays a critical role in host health, yet remains poorly studied in wild species.  Polar bears (Ursus maritimus), key indicators of Arctic ecosystem health and environmental change, are currently affected by rapid shifts in habitat that may alter gut homeostasis. Declining sea ice has led to a divide in the southern Beaufort Sea polar bear subpopulation such that an increasing proportion of individuals now inhabit onshore coastal regions during the open-water period (‘onshore bears’) while others continue to exhibit their typical behaviour of remaining on the ice (‘offshore bears’). We propose that bears that have altered their habitat selection in response to climate change will exhibit a distinct gut microbiota diversity and composition, which may ultimately have important consequences for their health. Here, we perform the first assessment of abundance and diversity in the faecal microbiota of wild polar bears using 16S rRNA Illumina technology. We find that bacterial diversity is significantly higher in onshore bears compared to offshore bears. The majority of unique bacterial taxa for onshore bears belonged to the phyla Proteobacteria (a proposed indicator of poor health in adult humans), whereas for offshore bears, Firmicutes (associated with adiposity) dominated. We conclude that climate-driven changes in polar bear land use are associated with distinct microbial communities. In doing so, we present the first case of global change mediated alterations in the gut microbiota of a free-roaming wild animal.","language":"English","publisher":"Nature","doi":"10.1038/s41396-019-0480-2","usgsCitation":"Watson, S., Hauffe, H., Bull, M., Atwood, T.C., McKinney, M., Pindo, M., and Perkins, S., 2020, Global change-driven use of onshore habitat impacts polar bear faecal microbiota: ISME Journal, v. 13, p. 2916-2926, https://doi.org/10.1038/s41396-019-0480-2.","productDescription":"11 p.","startPage":"2916","endPage":"2926","ipdsId":"IP-098794","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":458708,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41396-019-0480-2","text":"Publisher Index Page"},{"id":372013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Southern Beaufort Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -141.064453125,\n              69.09993967425089\n            ],\n            [\n              -140.888671875,\n              70.22974449563027\n            ],\n            [\n              -155.65429687499997,\n              73.09941313082075\n            ],\n            [\n              -164.443359375,\n              72.50172235139388\n            ],\n            [\n              -163.388671875,\n              69.68761843185617\n            ],\n            [\n              -158.466796875,\n              70.05059634999759\n            ],\n            [\n              -141.064453125,\n              69.09993967425089\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Watson, Sophie","contributorId":222143,"corporation":false,"usgs":false,"family":"Watson","given":"Sophie","email":"","affiliations":[{"id":17940,"text":"Cardiff University","active":true,"usgs":false}],"preferred":false,"id":781391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hauffe, Heidi","contributorId":222144,"corporation":false,"usgs":false,"family":"Hauffe","given":"Heidi","email":"","affiliations":[{"id":40495,"text":"Fondazione Edmund Mach","active":true,"usgs":false}],"preferred":false,"id":781392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bull, Matthew","contributorId":222145,"corporation":false,"usgs":false,"family":"Bull","given":"Matthew","email":"","affiliations":[{"id":17940,"text":"Cardiff University","active":true,"usgs":false}],"preferred":false,"id":781393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"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":781390,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKinney, Melissa","contributorId":222146,"corporation":false,"usgs":false,"family":"McKinney","given":"Melissa","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":781394,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pindo, Massimo","contributorId":222147,"corporation":false,"usgs":false,"family":"Pindo","given":"Massimo","email":"","affiliations":[{"id":40495,"text":"Fondazione Edmund Mach","active":true,"usgs":false}],"preferred":false,"id":781395,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Perkins, Sarah","contributorId":222148,"corporation":false,"usgs":false,"family":"Perkins","given":"Sarah","email":"","affiliations":[{"id":17940,"text":"Cardiff University","active":true,"usgs":false}],"preferred":false,"id":781396,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70219587,"text":"70219587 - 2020 - Passive restoration of vegetation and biological soil crusts following 80 years of exclusion from grazing across the Great Basin","interactions":[],"lastModifiedDate":"2021-04-15T12:49:32.901031","indexId":"70219587","displayToPublicDate":"2019-08-05T07:47:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Passive restoration of vegetation and biological soil crusts following 80 years of exclusion from grazing across the Great Basin","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Restoration targets for biological soil crusts are largely unknown. We surveyed seven 80‐year‐old grazing exclosures across northern Nevada for biocrusts to quantify reference conditions at relatively undisturbed sites. Exclosures were associated with the following plant communities: Wyoming big sagebrush, black sagebrush, and areas co‐dominated by winterfat and Wyoming big sagebrush. Cover of biocrusts and shrubs were generally higher than other plant groups at these sites, regardless of being inside or outside of the exclosures, suggesting these groups make up most of the native flora across the region. Important in forming soil structure, cyanobacteria of the order Oscillatoriales were less abundant and diverse in black sagebrush communities. Grazing had a negative effect on the abundance of Oscillatoriales but not the number of algal taxa, including cyanobacteria. Abundance of light algal crusts were not influenced by plant community or grazing. Dark algal crusts were generally less abundant on grazed sites. Influences of plant community and grazing were most apparent when accounting for reproductive rates of lichens and mosses based on establishment mechanisms. Abundance of shrubs, perennial grasses, Oscillatoriales, fast reproducing biocrusts and the number of algal and cyanobacterial taxa, varied by plant community, suggesting that restoration should be plant community specific. We demonstrate the affinity of rapidly reproducing biocrusts for winterfat‐Wyoming big sagebrush co‐dominated plant communities, regardless of grazing pressure. Across sites, the effects of grazing were most evident on the abundance of Oscillatoriales and slowly reproducing biocrusts following 80 years of cessation from grazing.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/rec.13021","usgsCitation":"Condon, L.A., Pietrasiak, N., Rosentreter, R., and Pyke, D.A., 2020, Passive restoration of vegetation and biological soil crusts following 80 years of exclusion from grazing across the Great Basin: Restoration Ecology, v. 28, no. S2, p. S75-S85, https://doi.org/10.1111/rec.13021.","productDescription":"11 p.","startPage":"S75","endPage":"S85","ipdsId":"IP-104219","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":458711,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.13021","text":"Publisher Index Page"},{"id":385120,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.13574218749999,\n              34.84987503195415\n            ],\n            [\n              -110.6103515625,\n              34.84987503195415\n            ],\n            [\n              -110.6103515625,\n              42.00032514831618\n            ],\n            [\n              -119.13574218749999,\n              42.00032514831618\n            ],\n            [\n              -119.13574218749999,\n              34.84987503195415\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"28","issue":"S2","noUsgsAuthors":false,"publicationDate":"2019-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Condon, Lea A. 0000-0002-9357-3881","orcid":"https://orcid.org/0000-0002-9357-3881","contributorId":202908,"corporation":false,"usgs":true,"family":"Condon","given":"Lea","email":"","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":814252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pietrasiak, Nicole","contributorId":174259,"corporation":false,"usgs":false,"family":"Pietrasiak","given":"Nicole","email":"","affiliations":[{"id":27402,"text":"Department of Biology, John Carroll University, University Heights, Ohio 4118","active":true,"usgs":false}],"preferred":false,"id":814253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosentreter, Roger","contributorId":257441,"corporation":false,"usgs":false,"family":"Rosentreter","given":"Roger","affiliations":[{"id":52018,"text":"Biology Department, Boise State University, Boise, Idaho","active":true,"usgs":false}],"preferred":false,"id":814254,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":814255,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70208101,"text":"70208101 - 2020 - Sampling and analysis frameworks for inference in ecology","interactions":[],"lastModifiedDate":"2020-01-27T19:43:27","indexId":"70208101","displayToPublicDate":"2019-08-02T19:41:54","publicationYear":"2020","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":"Sampling and analysis frameworks for inference in ecology","docAbstract":"<p>1. Reliable statistical inference is central to ecological research, much of which seeks to estimate population attributes and their interactions. The issue of sampling design and its relationship to inference has become increasingly important due to rapid proliferation of modeling methodology (line transect modeling, capture-recapture, estimation of occurrence, model selection procedures, hierarchical modeling) and new sampling approaches (adaptive sampling, other specialized designs). It is important for ecologists using these advanced methods to be aware of how the linkages between sample selection and data analysis can potentially affect inference. 2. We examine design-based and model-based inference frameworks for ecological data collected randomly, purposively, or opportunistically. We elucidate differences in the probability structures for data arising from these frameworks, clarify the assumptions that underlie them, and demonstrate their differences. 3. Design-based inference builds on a probability structure inherited from randomized data collection, whereas model-based inference relies on an assumed stochastic model of the data. By itself, a design-based approach is of limited value for inferences about causal hypotheses. In contrast, model-based inference is dependent on a conditionality principle that can seldom be shown to be met for an ecological system. We describe the conditions under which one can safely ignore sampling design in model-based analysis, along with inferential implications if these conditions are not met. The special case of opportunistic sampling is discussed. 4. We present a combined framework that takes advantage of both approaches to inference, and provides a robust methodology that can deal with the modeling of sampling problems such as nondetection and misclassification, as well as the exploration of causal hypotheses. The combined framework can be useful for identifying optimal sampling strategies. 5. Each approach to inference has its strengths and weaknesses, and practitioners should be aware of these in order to tailor designs and analyses to specific questions. We use the approaches and their underlying rationales to provide guidelines for choosing designs and estimators for reliable inference.</p>","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.13279","usgsCitation":"Williams, B.K., and Brown, E., 2020, Sampling and analysis frameworks for inference in ecology: Methods in Ecology and Evolution, v. 11, no. 10, p. 1832-1842, https://doi.org/10.1111/2041-210X.13279.","productDescription":"11 p.","startPage":"1832","endPage":"1842","ipdsId":"IP-105921","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":458716,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13279","text":"Publisher Index Page"},{"id":371624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"10","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":86616,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":780468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Ellie 0000-0001-7798-830X ebrown@usgs.gov","orcid":"https://orcid.org/0000-0001-7798-830X","contributorId":200491,"corporation":false,"usgs":true,"family":"Brown","given":"Ellie","email":"ebrown@usgs.gov","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":780467,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70208934,"text":"70208934 - 2020 - Planners tool up for the next big one","interactions":[],"lastModifiedDate":"2020-03-06T09:19:59","indexId":"70208934","displayToPublicDate":"2019-08-01T09:17:54","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5940,"text":"Planning","active":true,"publicationSubtype":{"id":10}},"title":"Planners tool up for the next big one","docAbstract":"Data, modeling, risk analysis, and hazard scenario resources can help put earthquake mitigation efforts on firmer ground. Article discusses general earthquake information and findings of the HayWired scenario for a planner audience.","language":"English","publisher":"American Planning Association","usgsCitation":"Johnson, L., and Wein, A.M., 2020, Planners tool up for the next big one: Planning, v. 85, p. 40-44.","productDescription":"5 p.","startPage":"40","endPage":"44","ipdsId":"IP-108944","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":372991,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372977,"type":{"id":15,"text":"Index Page"},"url":"https://www.planning.org/planning/2019/aug/"}],"volume":"85","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Laurie","contributorId":223094,"corporation":false,"usgs":false,"family":"Johnson","given":"Laurie","email":"","affiliations":[{"id":40672,"text":"Laurie Johnson Consulting/Research","active":true,"usgs":false}],"preferred":false,"id":784097,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wein, Anne M. 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":192951,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":784096,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70204664,"text":"70204664 - 2020 - Using carbon isotope ratios to verify predictions of a model simulating the interaction between coastal plant communities and their effect on ground water salinity","interactions":[],"lastModifiedDate":"2020-06-04T16:34:54.718128","indexId":"70204664","displayToPublicDate":"2019-07-31T13:28:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Using carbon isotope ratios to verify predictions of a model simulating the interaction between coastal plant communities and their effect on ground water salinity","docAbstract":"As sea level rises in low-lying coastal islands, salt-tolerant (halophytic) coastal vegetation communities may be able to migrate inland, replacing the freshwater vegetation that is unable to tolerate salt stress. The pace of such shifts may be accelerated by a self-reinforcing feedback between the halophytic vegetation and salinity, as well as by frequent and intensified salinity pulses associated with the increasing impact of storm surges as a consequence of sea-level rise. We used a modification of a previously published spatially explicit individual-based model that simulates impacts on upland freshwater hammock communities from sea-level rise and storm surge to predict the interaction between three coastal communities: mangroves, hammocks, and pinelands. The model simulation predicted two qualitative characteristics regarding the interaction between these three different coastal communities: (1) mangroves and hammock communities tend to have ground water with high salinities, while at the same time pineland ground water salinity is low, and (2) pineland located at lower elevation relative to adjacent hammock will be negatively influenced by higher ground water salinities in hammocks, as it flows toward the lower elevation pineland. We tested these predictions using foliar δ13C of Conocarpus erectus collected from Big Pine Key as a proxy for ground water salinity. Measurements of ground water salinity via this proxy confirmed the two predictions of the model. Our approach provides an approximation of the impacts of sea-level rise on terrestrial vegetation communities, including threatened pineland communities, and can be used as a tool for management decisions.","language":"English","publisher":"Springer","doi":"10.1007/s10021-019-00423-4","usgsCitation":"Subedi, S.C., Sternberg, L., DeAngelis, D.L., Ross, M.S., and Ogarcak, D., 2020, Using carbon isotope ratios to verify predictions of a model simulating the interaction between coastal plant communities and their effect on ground water salinity: Ecosystems, v. 23, p. 570-585, https://doi.org/10.1007/s10021-019-00423-4.","productDescription":"16 p.","startPage":"570","endPage":"585","ipdsId":"IP-101860","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":437219,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QO2Y7J","text":"USGS data release","linkHelpText":"Carbon-13 values in tree leaves in Florida (2018)"},{"id":366394,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Subedi, Suresh C. 0000-0001-8689-0689","orcid":"https://orcid.org/0000-0001-8689-0689","contributorId":217984,"corporation":false,"usgs":false,"family":"Subedi","given":"Suresh","email":"","middleInitial":"C.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":767973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sternberg, Leonel","contributorId":217985,"corporation":false,"usgs":false,"family":"Sternberg","given":"Leonel","affiliations":[],"preferred":false,"id":767974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":767972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ross, Michael S.","contributorId":202431,"corporation":false,"usgs":false,"family":"Ross","given":"Michael","email":"","middleInitial":"S.","affiliations":[{"id":36434,"text":"Florida International University, Miami, FL","active":true,"usgs":false}],"preferred":false,"id":767975,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ogarcak, Danielle","contributorId":217987,"corporation":false,"usgs":false,"family":"Ogarcak","given":"Danielle","email":"","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":767976,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70210904,"text":"70210904 - 2020 - Simplification of polylines by segment collapse: Minimizing areal displacement while preserving area","interactions":[],"lastModifiedDate":"2020-07-03T01:44:07.335671","indexId":"70210904","displayToPublicDate":"2019-07-30T20:39:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5728,"text":"International Journal of Cartography","active":true,"publicationSubtype":{"id":10}},"title":"Simplification of polylines by segment collapse: Minimizing areal displacement while preserving area","docAbstract":"This paper reports on a new Area Preserving Segment Collapse (APSC) algorithm for simplifying polygonal boundaries while preserving polygonal area at simplified target scales and minimizing areal displacement. A general segment collapse algorithm is defined by iteratively collapsing segments to Steiner points in priority order, guided by placement and displacement functions. The algorithm is specified by defining functions that minimize areal displacement under the constraint that the areas of adjoining polygons are preserved exactly. Self-intersections can be avoided by testing for intersections with two new line segments associated with each segment collapse operation. The paper demonstrates simplification results for a sample of 10 lakes formed from alpine, Karst, glacial and arid desert processes as well as artificial dams. APSC results are compared with three other simplification routines and evaluated for area preservation, linear and areal displacement, complexity and introduction of boundary self-intersections. Results confirm that the APSC algorithm preserves area exactly and indicate that it outperforms the other tested algorithms for minimizing areal displacement while producing reasonably low measures of linear displacement. Self-intersections can occur more commonly with APSC than other algorithms but are avoided with the proposed topology check. The APSC algorithm additionally preserves polygon complexity better than other tested algorithms.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/23729333.2019.1631535","usgsCitation":"Kronenfeld, B.J., Stanislawski, L., Buttenfield, B.P., and Brockmeyer, T., 2020, Simplification of polylines by segment collapse: Minimizing areal displacement while preserving area: International Journal of Cartography, v. 6, no. 1, p. 22-46, https://doi.org/10.1080/23729333.2019.1631535.","productDescription":"25 p.","startPage":"22","endPage":"46","ipdsId":"IP-105509","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":502439,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://works.bepress.com/kronenfeld/38/","text":"External Repository"},{"id":376111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Kronenfeld, Barry J. 0000-0002-9518-2462","orcid":"https://orcid.org/0000-0002-9518-2462","contributorId":207104,"corporation":false,"usgs":false,"family":"Kronenfeld","given":"Barry","email":"","middleInitial":"J.","affiliations":[{"id":5043,"text":"Eastern Illinois University","active":true,"usgs":false}],"preferred":false,"id":792058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanislawski, Larry 0000-0002-9437-0576","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":217849,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":792059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buttenfield, Barbara P. 0000-0001-5961-5809","orcid":"https://orcid.org/0000-0001-5961-5809","contributorId":206887,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara","email":"","middleInitial":"P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":792060,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brockmeyer, Tyler 0000-0003-4737-7203","orcid":"https://orcid.org/0000-0003-4737-7203","contributorId":228795,"corporation":false,"usgs":false,"family":"Brockmeyer","given":"Tyler","affiliations":[],"preferred":false,"id":792061,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
]}