{"pageNumber":"298","pageRowStart":"7425","pageSize":"25","recordCount":40783,"records":[{"id":70210920,"text":"70210920 - 2020 - Applying spatially explicit capture–recapture models to estimate black bear density in South Carolina","interactions":[],"lastModifiedDate":"2020-07-03T14:02:08.90055","indexId":"70210920","displayToPublicDate":"2019-09-05T08:59:28","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Applying spatially explicit capture–recapture models to estimate black bear density in South Carolina","docAbstract":"<p><span>Population density is an important component of wildlife management decisions, but can be difficult to estimate directly for an itinerant, wide‐ranging species such as the American black bear (</span><i>Ursus americanus<span>&nbsp;</span></i><span>). In South Carolina, USA, where there has been growth in black bear populations and bear–human‐conflict reports during the past several decades, managers need robust estimates of population size to inform management strategies. We used maximum‐likelihood capture–recapture models, using hair snares to collect DNA samples, to estimate density and abundance for a harvested population of black bear in northwestern South Carolina during 2013 to 2014. Models were tested in a spatially explicit framework using the&nbsp;</span><i>secr<span>&nbsp;</span></i><span>package in Program R. Black bear density was estimated at 0.133 bears/km</span><sup>2</sup><span>&nbsp;(SE = 0.034) in 2013 and 0.179 bears/km</span><sup>2</sup><span>&nbsp;(SE = 0.043) in 2014. Black bear abundance in our study area was estimated to be 586 bears (SE = 95) in 2013 and 680 bears (SE = 128) in 2014, which are 2–3‐fold lower than previous estimates. We suggest that these estimates be considered a baseline for state biologists to employ in the population's management and in developing future harvest‐regulation strategies. Overall our study highlighted the potential for model choice to influence density estimates, and we concluded that spatially explicit models were appropriate for this study because geographic closure could not be assumed.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1007","usgsCitation":"Azad, S., McFadden, K., Clark, J.D., Wactor, T., and Jachowski, D., 2020, Applying spatially explicit capture–recapture models to estimate black bear density in South Carolina: Wildlife Society Bulletin, v. 43, no. 3, p. 500-507, https://doi.org/10.1002/wsb.1007.","productDescription":"8 p.","startPage":"500","endPage":"507","ipdsId":"IP-108028","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":499857,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/1934029e1d5c411d8e18f9f7abaa7f57","text":"External Repository"},{"id":376120,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"south Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.936279296875,\n              35.10193405724606\n            ],\n            [\n              -82.430419921875,\n              35.191766965947394\n            ],\n            [\n              -83.1005859375,\n              35.003003395276714\n            ],\n            [\n              -83.353271484375,\n              34.71452466170392\n            ],\n            [\n              -83.023681640625,\n              34.49750272138159\n            ],\n            [\n              -82.7490234375,\n              34.27083595165\n            ],\n            [\n              -81.23291015625,\n              34.31621838080741\n            ],\n            [\n              -81.03515625,\n              34.334364487026306\n            ],\n            [\n              -80.936279296875,\n              35.10193405724606\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"43","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Azad, Shefali","contributorId":228811,"corporation":false,"usgs":false,"family":"Azad","given":"Shefali","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":792137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McFadden, Katherine kwmcfadden@usgs.gov","contributorId":228812,"corporation":false,"usgs":false,"family":"McFadden","given":"Katherine","email":"kwmcfadden@usgs.gov","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":792138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Joseph D. 0000-0002-8547-8112 jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":792139,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wactor, Tammy","contributorId":228813,"corporation":false,"usgs":false,"family":"Wactor","given":"Tammy","email":"","affiliations":[{"id":35670,"text":"South Carolina Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":792140,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jachowski, David S.","contributorId":228814,"corporation":false,"usgs":false,"family":"Jachowski","given":"David S.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":792141,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"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 Center","active":true,"usgs":true}],"preferred":true,"id":927356,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lopez-Venegas, Alberto 0000-0002-3413-0546","orcid":"https://orcid.org/0000-0002-3413-0546","contributorId":350939,"corporation":false,"usgs":false,"family":"Lopez-Venegas","given":"Alberto","affiliations":[{"id":34129,"text":"University of Puerto Rico Mayaguez","active":true,"usgs":false}],"preferred":false,"id":927357,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mann, Doerte 0000-0002-8789-5219","orcid":"https://orcid.org/0000-0002-8789-5219","contributorId":350940,"corporation":false,"usgs":false,"family":"Mann","given":"Doerte","affiliations":[{"id":83886,"text":"UNAVCO, Inc.","active":true,"usgs":false}],"preferred":false,"id":927358,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mattioli, Glen 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 0000-0001-9984-6724","orcid":"https://orcid.org/0000-0001-9984-6724","contributorId":328836,"corporation":false,"usgs":false,"family":"Mencin","given":"David","email":"","affiliations":[{"id":5114,"text":"UNAVCO","active":true,"usgs":false}],"preferred":false,"id":927361,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Montgomery-Brown, Emily K. 0000-0001-6787-2055","orcid":"https://orcid.org/0000-0001-6787-2055","contributorId":214074,"corporation":false,"usgs":true,"family":"Montgomery-Brown","given":"Emily","email":"","middleInitial":"K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":927362,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Murray, Mark Hunter 0000-0003-4862-5547","orcid":"https://orcid.org/0000-0003-4862-5547","contributorId":300982,"corporation":false,"usgs":true,"family":"Murray","given":"Mark","email":"","middleInitial":"Hunter","affiliations":[{"id":237,"text":"Earthquake 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":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":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":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":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":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":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes 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":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":793050,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"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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,{"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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,{"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 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 \"}}]}","volume":"45","issue":"1","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Knobles, David P.","contributorId":218392,"corporation":false,"usgs":false,"family":"Knobles","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":769154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Preston S.","contributorId":139561,"corporation":false,"usgs":false,"family":"Wilson","given":"Preston","email":"","middleInitial":"S.","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address:  TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":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":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science 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":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":70206828,"text":"70206828 - 2020 - Using full and partial unmixing algorithms to estimate the inundation extent of small, isolated stock ponds in an arid landscape","interactions":[],"lastModifiedDate":"2020-08-27T15:29:37.417951","indexId":"70206828","displayToPublicDate":"2019-07-30T06:48:22","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Using full and partial unmixing algorithms to estimate the inundation extent of small, isolated stock ponds in an arid landscape","docAbstract":"<p><span>Many natural wetlands around the world have disappeared or been replaced, resulting in the dependence of many wildlife species on small, artificial earthen stock ponds. These ponds provide critical wildlife habitat, such that the accurate detection of water and assessment of inundation extent is required. We applied a full (linear spectral mixture analysis; LSMA) and partial (matched filtering; MF) spectral unmixing algorithm to a 2007 Landsat 5 and a 2014 Landsat 8 satellite image to determine the ability of a time-intensive (i.e., more spectral input; LSMA) vs. a more efficient (less spectral input; MF) spectral unmixing approach to detect and estimate surface water area of stock ponds in southern Arizona, USA and northern Sonora, Mexico. Spearman rank correlations (</span><i>r</i><sub>s</sub><span>) between modeled and actual inundation areas less than a single Landsat pixel (&lt; 900 m</span><sup>2</sup><span>) were low for both techniques (</span><i>r</i><sub>s</sub><span>&nbsp;range = 0.22 to 0.62), but improved for inundation areas &gt;900&nbsp;m</span><sup>2</sup><span>&nbsp;(</span><i>r</i><sub>s</sub><span>&nbsp;range = 0.34 to 0.70). Our results demonstrate that the MF approach can model ranked inundation extent of known pond locations with results comparable to or better than LSMA, but further refinement is required for estimating absolute inundation areas and mapping wetlands &lt;1 Landsat pixel.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s13157-019-01201-7","usgsCitation":"Jarchow, C., Sigafus, B.H., Muths, E.L., and Hossack, B.R., 2020, Using full and partial unmixing algorithms to estimate the inundation extent of small, isolated stock ponds in an arid landscape: Wetlands, v. 40, p. 563-575, https://doi.org/10.1007/s13157-019-01201-7.","productDescription":"13 p.","startPage":"563","endPage":"575","ipdsId":"IP-092489","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":437220,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95ZFPT1","text":"USGS data release","linkHelpText":"Surface water data for isolated stock ponds in southern Arizona, USA and northern Sonora, Mexico"},{"id":369519,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Jarchow, Christopher 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":196069,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":775953,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sigafus, Brent H. 0000-0002-7422-8927 bsigafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":4534,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent","email":"bsigafus@usgs.gov","middleInitial":"H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":775952,"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":775954,"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":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":775955,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227115,"text":"70227115 - 2020 - Harvest–release decisions in recreational fisheries","interactions":[],"lastModifiedDate":"2021-12-30T16:41:44.505518","indexId":"70227115","displayToPublicDate":"2019-07-29T10:37:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Harvest–release decisions in recreational fisheries","docAbstract":"<p><span>Most fishery regulations aim to control angler harvest. Yet, we lack a basic understanding of what actually determines the angler’s decision to harvest or release fish caught. We used XGBoost, a machine learning algorithm, to develop a predictive angler harvest–release model by taking advantage of an extensive recreational fishery data set (24 water bodies, 9 years, and 193 523 fish). We were able to successfully predict the harvest–release outcome for 99% of fish caught in the training data set and 96% of fish caught in the test data set. Unsuccessful predictions were mostly attributed to predicting harvest of fish that were released. Fish length was the most essential feature examined for predicting angler harvest. Other important predictive harvest–release features included the number of individuals of the same species caught, geographic location of an angler’s residence, distance traveled, and time spent fishing. The XGBoost algorithm was able to effectively predict the harvest–release decision and revealed hidden and intricate relationships that are often unaccounted for with classical analysis techniques. Exposing and accounting for these angler–fish intricacies is critical for fisheries conservation and management.</span></p>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2019-0119","usgsCitation":"Kaemingk, M.A., Hurley, K.L., Chizinski, C.J., and Pope, K.L., 2020, Harvest–release decisions in recreational fisheries: Canadian Journal of Fisheries and Aquatic Sciences, v. 77, no. 1, p. 194-201, https://doi.org/10.1139/cjfas-2019-0119.","productDescription":"8 p.","startPage":"194","endPage":"201","ipdsId":"IP-107097","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":500808,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/96908","text":"External Repository"},{"id":393653,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70208348,"text":"70208348 - 2020 - Light exposure along particle flowpaths in large rivers","interactions":[],"lastModifiedDate":"2020-02-05T16:23:00","indexId":"70208348","displayToPublicDate":"2019-07-26T16:06:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Light exposure along particle flowpaths in large rivers","docAbstract":"<p><span>Sunlight is a critical resource in aquatic systems driving photosynthesis, photodegradation of organic matter and contaminants, animal behavior, and the activity of human pathogens. In rivers, solutes, materials, and organisms are turbulently mixed across the water column during downstream transport and exposed to highly variable sunlight. However, there are no measurements of suspended particles' sunlight exposure during downstream transport to characterize this variability, and it is unclear if current measurement approaches and optical theory capture the light exposure of suspended particles. We deployed neutrally buoyant drifters and stationary buoys in the Upper Mississippi (WI, U.S.A.) and Neuse Rivers (NC, U.S.A.) to measure underwater sunlight from the perspective of suspended particles. In our study sites, underwater sunlight varied more along flowpaths measured by drifters than over time measured by fixed‐site buoys; sunlight exposure along flowpaths was dominated by bursts of light (sunflecks) that accounted for 62–99% of the cumulative sunlight exposure; and modeled sunlight exposure using optical theory was consistently 56–1700% higher than measured sunlight exposure along flowpaths. Our results suggested that suspended particles in the study reaches experienced darker conditions than predicted and have important implications for how to quantify underwater sunlight in rivers.</span></p>","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.11256","usgsCitation":"Gardner, J.R., Ensign, S.H., Houser, J.N., and Doyle, M.W., 2020, Light exposure along particle flowpaths in large rivers: Limnology and Oceanography, v. 65, no. 1, p. 128-142, https://doi.org/10.1002/lno.11256.","productDescription":"15 p.","startPage":"128","endPage":"142","ipdsId":"IP-102904","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":372097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Wisconsin","otherGeospatial":"Neuse River, Upper Missisiisppi River Pool 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,{"id":70210198,"text":"70210198 - 2020 - Estimating visitor use and economic contributions of National Park visitor spending","interactions":[],"lastModifiedDate":"2020-06-03T16:02:49.893141","indexId":"70210198","displayToPublicDate":"2019-07-12T11:01:28","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Estimating visitor use and economic contributions of National Park visitor spending","docAbstract":"<p><span>This chapter provides an overview of the National Park Service (NPS) methods for estimating visitor spending and calculating economic contributions of visitor spending in terms of jobs supported, wage and labor income, and total economic activity. The Visitor Spending Effects model combines visitor spending patterns and trip characteristic data with visitor use data to estimate total visitor spending. Economic contributions measure the total economic activity within a regional economy stemming from visitor spending, and include the effects of spending by both local visitors who live within gateway regions and non-local visitors who travel to NPS sites from outside of gateway regions. The Social Science Program collaborates with individual parks to develop visitor counting instructions that contain the procedures for measuring, compiling, and recording required visitor use data. Visitor surveys are used to collect the essential visitor spending and trip characteristic data necessary for developing spending profiles to represent distinct visitor spending patterns for each park.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Valuing U.S. National Parks and Programs","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Routledge","doi":"10.4324/9781351055789","collaboration":"National Park Service","usgsCitation":"Koontz, L., and Cullinane Thomas, C., 2020, Estimating visitor use and economic contributions of National Park visitor spending, chap. <i>of</i> Valuing U.S. National Parks and Programs, 13 p., https://doi.org/10.4324/9781351055789.","productDescription":"13 p.","ipdsId":"IP-099361","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":375349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2019-07-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Koontz, Lynne koontzl@usgs.gov","contributorId":2174,"corporation":false,"usgs":false,"family":"Koontz","given":"Lynne","email":"koontzl@usgs.gov","affiliations":[{"id":7016,"text":"Environmental Quality Division, National Park Service, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":789508,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cullinane Thomas, Catherine 0000-0001-8168-1271 ccullinanethomas@usgs.gov","orcid":"https://orcid.org/0000-0001-8168-1271","contributorId":141097,"corporation":false,"usgs":true,"family":"Cullinane Thomas","given":"Catherine","email":"ccullinanethomas@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":789509,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70208877,"text":"70208877 - 2020 - Investigating bedload transport under asymmetrical waves using a coupled ocean-wave model","interactions":[],"lastModifiedDate":"2020-03-04T16:45:11","indexId":"70208877","displayToPublicDate":"2019-06-30T16:39:32","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Investigating bedload transport under asymmetrical waves using a coupled ocean-wave model","docAbstract":"Transport by asymmetrical wave motions plays a key role in cross-shore movement of sand, which is important for bar migration, exchange through tidal inlets, and beach recovery after storms. We have implemented a modified version of the SANTOSS formulation in the three-dimensional open-source Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling framework. The calculation of bedload transport requires inputs that include: water depth, bulk wave statistics (significant wave height, wave period, wave orbital velocity), current velocity at the edge of the wave boundary layer, and sediment density and grain size. While the coupled ocean-wave model computes water density, depth, and bulk wave statistics, we implement a method to calculate current velocity assuming a log profile and using the Madsen formulations for wave-current bottom boundary layer flows. We investigate the sensitivity of the calculation of near-bottom current velocity to model choices and its influence on cross-shore bedload transport. Results are compared to available numerical experiments using coupled fluid and discrete element model (CFDEM) simulations.","largerWorkType":{"id":4,"text":"Book"},"largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"World Scientific","doi":"10.1142/9789811204487_0052","usgsCitation":"Kalra, T., Sherwood, C.R., Warner, J., Rafati, Y., and Hsu, T.J., 2020, Investigating bedload transport under asymmetrical waves using a coupled ocean-wave model, p. 591-604, https://doi.org/10.1142/9789811204487_0052.","productDescription":"15 p.","startPage":"591","endPage":"604","ipdsId":"IP-105261","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":372929,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":783926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":783927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":783928,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rafati, Yashar","contributorId":223049,"corporation":false,"usgs":false,"family":"Rafati","given":"Yashar","email":"","affiliations":[],"preferred":false,"id":783929,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hsu, Tian Jian","contributorId":149140,"corporation":false,"usgs":false,"family":"Hsu","given":"Tian","email":"","middleInitial":"Jian","affiliations":[],"preferred":false,"id":783930,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70208878,"text":"70208878 - 2020 - Modeling the morphological response of a barrier island to Hurricane Matthew","interactions":[],"lastModifiedDate":"2020-03-04T16:34:17","indexId":"70208878","displayToPublicDate":"2019-06-30T16:34:01","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Modeling the morphological response of a barrier island to Hurricane Matthew","docAbstract":"Surge and wave forcing from Hurricane Matthew caused a breach south of Matanzas Inlet (FL, USA) on a complex barrier island, including sandy dunes, hard structures (residential buildings and a highway), wetlands, and the US Intracoastal Waterway. In this paper, the skill of the XBeach model to predict hurricane-induced barrier island overwash, dune erosion, and breaching is demonstrated. The location of the breach is predicted correctly if bottom roughness based on land cover is used to calculate bed shear stresses. While the dunes are initially lowered by wave attack and surge from the ocean side, the main driver for breach formation is the water level difference between the back-barrier and nearshore, causing an ocean-directed outflow of water after the peak of the storm.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal sediments 2019: Proceedings of the 9th international conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"International Conference on Coastal Sediments 2019","conferenceDate":"May 27-31, 2019","conferenceLocation":"Tampa/St. Petersburg, FL","language":"English","publisher":"World Scientific","doi":"10.1142/9789811204487_0012","usgsCitation":"Quataert, E., van der Lugt, M., Sherwood, C.R., van Oormondt, M., and van Dongeran, A., 2020, Modeling the morphological response of a barrier island to Hurricane Matthew, <i>in</i> Coastal sediments 2019: Proceedings of the 9th international conference, Tampa/St. Petersburg, FL, May 27-31, 2019, p. 128-138, https://doi.org/10.1142/9789811204487_0012.","productDescription":"11 p.","startPage":"128","endPage":"138","ipdsId":"IP-105247","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":372928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Matanzas Inlet","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.19171142578125,\n              29.621818021144485\n            ],\n            [\n              -81.24629974365234,\n              29.767059606099\n            ],\n            [\n              -81.26106262207031,\n              29.806688644587382\n            ],\n            [\n              -81.28921508789062,\n              29.80609283540296\n            ],\n            [\n              -81.25179290771484,\n              29.719364794202505\n            ],\n            [\n              -81.23085021972656,\n              29.65434412369176\n            ],\n            [\n              -81.21437072753906,\n              29.608088257406806\n            ],\n            [\n              -81.19171142578125,\n              29.621818021144485\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Quataert, Ellen","contributorId":149000,"corporation":false,"usgs":false,"family":"Quataert","given":"Ellen","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":783921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van der Lugt, Marlies","contributorId":221148,"corporation":false,"usgs":false,"family":"van der Lugt","given":"Marlies","email":"","affiliations":[{"id":40335,"text":"Detlares","active":true,"usgs":false}],"preferred":false,"id":783922,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":783923,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Oormondt, Maarten","contributorId":223048,"corporation":false,"usgs":false,"family":"van Oormondt","given":"Maarten","email":"","affiliations":[],"preferred":false,"id":783924,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van Dongeran, Ap","contributorId":176244,"corporation":false,"usgs":false,"family":"van Dongeran","given":"Ap","email":"","affiliations":[],"preferred":false,"id":783925,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70204052,"text":"70204052 - 2020 - Establishing genome sizes of focal fishery and aquaculture species along Baja California, Mexico","interactions":[],"lastModifiedDate":"2020-06-04T16:32:07.115911","indexId":"70204052","displayToPublicDate":"2019-06-25T09:50:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1325,"text":"Conservation Genetics Resources","active":true,"publicationSubtype":{"id":10}},"title":"Establishing genome sizes of focal fishery and aquaculture species along Baja California, Mexico","docAbstract":"<p><span>Genome size—the total haploid content of nuclear DNA— is constant in all cells in individuals within a species, but differs among species. Consequently, the genome size is a quantifiable genetic signature that not only characterizes a species, but it can reflect chromatin modifications, which play fundamental roles in most biological processes that are involved in the manipulation and expression of DNA. This characteristic makes the genome size a crucial parameter for genetic research on endemic aquatic species and for genetic manipulations in aquaculture species. Technologies for genetic assessments and improvements applied to fishery and aquaculture species use genome size values as a means by which hybrids, polyploids, and sex can be identified, when sex chromosomes exist. The objectives of this study were to determine genome sizes of aquatic species with economic and biological importance along the Pacific coast of Mexico, as well as to identify the appropriate reference standards for use in this study. Blood, hemolymph or milt were collected from 10 species occurring along the coast of Baja California: Sablefish&nbsp;</span><i>Anoplopoma fimbria</i><span>, Black Snapper&nbsp;</span><i>Lutjanus novemfasciatus</i><span>, California Halibut&nbsp;</span><i>Paralichthys californicus</i><span>, Pacific Sardine&nbsp;</span><i>Sardinops sagax</i><span>, Flag Rockfish&nbsp;</span><i>Sebastes rubrivinctus</i><span>, Starry Rockfish&nbsp;</span><i>Sebastes constellatus,</i><span>&nbsp;Totoaba&nbsp;</span><i>Totoaba macdonaldi</i><span>, Whiteleg Shrimp&nbsp;</span><i>Litopenaeus vannamei</i><span>&nbsp;and two Yellowtail&nbsp;</span><i>Seriola lalandi</i><span>&nbsp;and&nbsp;</span><i>S. dorsalis</i><span>. Nuclear DNA was stained with propidium iodide solution and the genome size was determined by flow cytometry, with results ranging from 0.61&nbsp;pg (1.22&nbsp;pg/diploid cell) to 2.59&nbsp;pg (5.18&nbsp;pg/diploid cell), with the smallest value in Sablefish and the largest in the Whiteleg Shrimp. No significant differences were detected (</span><i>P</i><span> ≤ 0.05) among individuals of the same species; the likely reason behind any dissimilar DNA content values with those from the literature were differences in methodologies or variations in genetics. Red-ear Slider Turtle&nbsp;</span><i>Trachemys scripta elegans</i><span>&nbsp;2.65&nbsp;pg (5.30&nbsp;pg/diploid cell) and Red Junglefowl&nbsp;</span><i>Gallus gallus</i><span>&nbsp;1.27&nbsp;pg (2.54&nbsp;pg/diploid cell) were chosen as the standards for reference values. These results establish the basis for the Mexican National Aquatic Genetic Resources project supporting genetic improvements for aquaculture and conservation status parameters for fisheries species.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s12686-019-01105-y","usgsCitation":"del Mar Ochoa-Saloma, C., Jenkins, J.A., Segovia, M.A., Del Rio-Portilla, M.A., and Paniagua-Chavez, C.G., 2020, Establishing genome sizes of focal fishery and aquaculture species along Baja California, Mexico: Conservation Genetics Resources, v. 12, p. 301-309, https://doi.org/10.1007/s12686-019-01105-y.","productDescription":"9 p.","startPage":"301","endPage":"309","ipdsId":"IP-089376","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":365244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","otherGeospatial":"Baja 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Center","active":true,"usgs":true}],"preferred":true,"id":765288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Segovia, Manuel A.","contributorId":216674,"corporation":false,"usgs":false,"family":"Segovia","given":"Manuel","email":"","middleInitial":"A.","affiliations":[{"id":39498,"text":"Departmento de Acuicultura, Centro de Investigacion Cientifica y de Educacion Superior de Ensenada, Baja California (CICESE)","active":true,"usgs":false}],"preferred":false,"id":765290,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Del Rio-Portilla, Miguel A.","contributorId":216675,"corporation":false,"usgs":false,"family":"Del Rio-Portilla","given":"Miguel","email":"","middleInitial":"A.","affiliations":[{"id":39498,"text":"Departmento de Acuicultura, Centro de Investigacion Cientifica y de Educacion Superior de Ensenada, Baja California (CICESE)","active":true,"usgs":false}],"preferred":false,"id":765291,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paniagua-Chavez, Carmen G.","contributorId":216676,"corporation":false,"usgs":false,"family":"Paniagua-Chavez","given":"Carmen","email":"","middleInitial":"G.","affiliations":[{"id":39498,"text":"Departmento de Acuicultura, Centro de Investigacion Cientifica y de Educacion Superior de Ensenada, Baja California (CICESE)","active":true,"usgs":false}],"preferred":false,"id":765292,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70204110,"text":"70204110 - 2020 - Hydroseeding tackifiers and dryland moss restoration potential","interactions":[],"lastModifiedDate":"2024-07-17T21:41:12.423442","indexId":"70204110","displayToPublicDate":"2019-06-17T16:45:31","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":"Hydroseeding tackifiers and dryland moss restoration potential","docAbstract":"<p><span>Tackifiers are long‐chain carbon compounds used for soil stabilization and hydroseeding and could provide a vehicle for biological soil crust restoration. We examined the sensitivity of two dryland mosses,&nbsp;</span><i>Bryum argenteum</i><span>&nbsp;and&nbsp;</span><i>Syntrichia ruralis,</i><span>&nbsp;to three common tackifiers ‐ guar, psyllium, and polyacrylamide (PAM) ‐ at 0.5x, 1.0x, and 2.0x of recommended (x) concentrations for erosion control and revegetation. We measured moss shoot, gemma, and protonema production as well as moss organic matter and bound sand masses as indicators of growth and soil holding ability. We tested sand and tackifier chemistry to investigate potential nutrient and toxicant potential on moss growth. Groups of ten fragments from field‐collected mosses were grown on sand in open petri dishes arranged in a growth chamber in replicated blocks containing each tackifier and concentration combination plus a distilled water control.&nbsp;</span><i>Bryum</i><span>&nbsp;(</span><i>n</i><span>=10) and&nbsp;</span><i>Syntrichia</i><span>&nbsp;(</span><i>n</i><span>=9) growth were measured at the end of six and five weeks, respectively. Overall model tests yielded statistically significant results (</span><i>p</i><span>&lt;0.001) for every variable in each species. When compared to water, guar tended to decrease growth, psyllium tended to increase growth, and PAM's effects were generally neutral to positive. Within tackifier types, increasing concentrations of guar tended to decrease growth, while increasing concentrations of psyllium tended to increase growth. Changes in PAM concentrations had little effect on growth. Increases in guar and psyllium lowered pH and increased P and K. Psyllium and PAM yielded promising results as potential agents of dispersal and adherence of dryland mosses in field restoration.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/rec.12997","usgsCitation":"Blankenship, W.D., Condon, L.A., and Pyke, D.A., 2020, Hydroseeding tackifiers and dryland moss restoration potential: Restoration Ecology, v. 28, no. S2, p. S127-S138, https://doi.org/10.1111/rec.12997.","productDescription":"12 p.","startPage":"S127","endPage":"S138","ipdsId":"IP-106770","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"links":[{"id":458742,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.12997","text":"Publisher Index Page"},{"id":365318,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"S2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Blankenship, W. Dillon","contributorId":216798,"corporation":false,"usgs":false,"family":"Blankenship","given":"W.","email":"","middleInitial":"Dillon","affiliations":[{"id":39520,"text":"Oregon State University, Department of Botany and Plant Pathology","active":true,"usgs":false}],"preferred":false,"id":765561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":765560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":765559,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70221421,"text":"70221421 - 2020 - Upwelling buffers climate change impacts on coral reefs of the eastern tropical Pacific","interactions":[],"lastModifiedDate":"2021-06-15T11:43:50.746984","indexId":"70221421","displayToPublicDate":"2019-06-15T06:40:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Upwelling buffers climate change impacts on coral reefs of the eastern tropical Pacific","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Corals of the eastern tropical Pacific live in a marginal and oceanographically dynamic environment. Along the Pacific coast of Panamá, stronger seasonal upwelling in the Gulf of Panamá in the east transitions to weaker upwelling in the Gulf of Chiriquí in the west, resulting in complex regional oceanographic conditions that drive differential coral-reef growth. Over millennial timescales, reefs in the Gulf of Chiriquí recovered more quickly from climatic disturbances compared with reefs in the Gulf of Panamá. In recent decades, corals in the Gulf of Chiriquí have also had higher growth rates than in the Gulf of Panamá. As the ocean continues to warm, however, conditions could shift to favor the growth of corals in the Gulf of Panamá, where upwelling may confer protection from high-temperature anomalies. Here we describe the recent spatial and temporal variability in surface oceanography of nearshore environments in Pacific Panamá and compare those conditions with the dynamics of contemporary coral-reef communities during and after the 2016 coral-bleaching event. Although both gulfs have warmed significantly over the last 150&nbsp;yr, the annual thermal maximum in the Gulf of Chiriquí is increasing faster, and ocean temperatures there are becoming more variable than in the recent past. In contrast to historical trends, we found that coral cover, coral survival, and coral growth rates were all significantly higher in the Gulf of Panamá. Corals bleached extensively in the Gulf of Chiriquí following the 2015–2016 El Niño event, whereas upwelling in the Gulf of Panamá moderated the high temperatures caused by El Niño, allowing the corals largely to escape thermal stress. As the climate continues to warm, upwelling zones may offer a temporary and localized refuge from the thermal impacts of climate change, while reef growth in the rest of the eastern tropical Pacific continues to decline.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2918","usgsCitation":"Randall, C.J., Toth, L., Leichter, J.J., Mate, J.L., and Aronson, R.B., 2020, Upwelling buffers climate change impacts on coral reefs of the eastern tropical Pacific: Ecology, v. 2, no. 101, e02918, 15 p., https://doi.org/10.1002/ecy.2918.","productDescription":"e02918, 15 p.","ipdsId":"IP-108323","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":458743,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.2918","text":"Publisher Index Page"},{"id":386485,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Panama","otherGeospatial":"Gulf of Chiriqui, Gulf of Panama","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.9033203125,\n              7.297087564172005\n            ],\n            [\n              -78.7060546875,\n              7.297087564172005\n            ],\n            [\n              -78.7060546875,\n              8.819938928283147\n            ],\n            [\n              -80.9033203125,\n              8.819938928283147\n            ],\n            [\n              -80.9033203125,\n              7.297087564172005\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.7822265625,\n              6.730075707109153\n            ],\n            [\n              -80.48583984375,\n              6.730075707109153\n            ],\n            [\n              -80.48583984375,\n              8.080984688871991\n            ],\n            [\n              -81.7822265625,\n              8.080984688871991\n            ],\n            [\n              -81.7822265625,\n              6.730075707109153\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"2","issue":"101","noUsgsAuthors":false,"publicationDate":"2020-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Randall, Carly J. 0000-0001-8112-3552","orcid":"https://orcid.org/0000-0001-8112-3552","contributorId":212696,"corporation":false,"usgs":false,"family":"Randall","given":"Carly","email":"","middleInitial":"J.","affiliations":[{"id":32935,"text":"Australian Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":817646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leichter, James J 0000-0003-4224-0355","orcid":"https://orcid.org/0000-0003-4224-0355","contributorId":260265,"corporation":false,"usgs":false,"family":"Leichter","given":"James","email":"","middleInitial":"J","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":817648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mate, Juan L 0000-0002-4423-4816","orcid":"https://orcid.org/0000-0002-4423-4816","contributorId":260268,"corporation":false,"usgs":false,"family":"Mate","given":"Juan","email":"","middleInitial":"L","affiliations":[{"id":12671,"text":"Smithsonian Tropical Research Institute","active":true,"usgs":false}],"preferred":false,"id":817649,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aronson, Richard B. 0000-0003-0383-3844","orcid":"https://orcid.org/0000-0003-0383-3844","contributorId":212695,"corporation":false,"usgs":false,"family":"Aronson","given":"Richard","email":"","middleInitial":"B.","affiliations":[{"id":17748,"text":"Florida Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":817650,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70221422,"text":"70221422 - 2020 - Enhanced El Niño-Southern Oscillation variability in recent decades","interactions":[],"lastModifiedDate":"2021-06-15T11:39:13.073166","indexId":"70221422","displayToPublicDate":"2019-06-15T06:35:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Enhanced El Niño-Southern Oscillation variability in recent decades","docAbstract":"<div class=\"article-section__content en main\"><p>The El Niño–Southern Oscillation (ENSO) represents the largest source of year-to-year global climate variability. While Earth system models suggest a range of possible shifts in ENSO properties under continued greenhouse gas forcing, many centuries of preindustrial climate data are required to detect a potential shift in the properties of recent ENSO extremes. Here we reconstruct the strength of ENSO variations over the last 7,000 years with a new ensemble of fossil coral oxygen isotope records from the Line Islands, located in the central equatorial Pacific. The corals document a significant decrease in ENSO variance of ~20% from 3,000 to 5,000 years ago, coinciding with changes in spring/fall precessional insolation. We find that ENSO variability over the last five decades is ~25% stronger than during the preindustrial. Our results provide empirical support for recent climate model projections showing an intensification of ENSO extremes under greenhouse forcing.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GL083906","usgsCitation":"Grothe, P.R., Cobb, K.M., Liguori, G., Di Lorenzo, E., Capotondi, A., Lu, Y., Cheng, H., Edwards, R.L., Southon, J.R., Santos, G.M., Decampo, D.M., Lynch-Stieglitz, J., Chen, T., Sayani, H.R., Thompson, D.M., Conroy, J.L., Moore, A.L., Townsend, K., Hagos, M., O’Connor, G., and Toth, L., 2020, Enhanced El Niño-Southern Oscillation variability in recent decades: Geophysical Research Letters, v. 46, no. 7, e2019GL083906, 8 p., https://doi.org/10.1029/2019GL083906.","productDescription":"e2019GL083906, 8 p.","ipdsId":"IP-090316","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":458747,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019gl083906","text":"Publisher Index Page"},{"id":386484,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-04-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Grothe, Pamela R. 0000-0003-1855-4776","orcid":"https://orcid.org/0000-0003-1855-4776","contributorId":260269,"corporation":false,"usgs":false,"family":"Grothe","given":"Pamela","email":"","middleInitial":"R.","affiliations":[{"id":27815,"text":"Georgia Tech","active":true,"usgs":false}],"preferred":false,"id":817651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cobb, Kim M. 0000-0002-2125-9164","orcid":"https://orcid.org/0000-0002-2125-9164","contributorId":260270,"corporation":false,"usgs":false,"family":"Cobb","given":"Kim","email":"","middleInitial":"M.","affiliations":[{"id":27815,"text":"Georgia Tech","active":true,"usgs":false}],"preferred":false,"id":817652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liguori, Giovanni","contributorId":260271,"corporation":false,"usgs":false,"family":"Liguori","given":"Giovanni","email":"","affiliations":[{"id":27815,"text":"Georgia Tech","active":true,"usgs":false}],"preferred":false,"id":817653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Di Lorenzo, Emanuele","contributorId":203861,"corporation":false,"usgs":false,"family":"Di Lorenzo","given":"Emanuele","email":"","affiliations":[{"id":36732,"text":"School of Earth & Atmospheric Sciences, Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":817654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Capotondi, Antonietta 0000-0002-3594-5472","orcid":"https://orcid.org/0000-0002-3594-5472","contributorId":260272,"corporation":false,"usgs":false,"family":"Capotondi","given":"Antonietta","email":"","affiliations":[{"id":52553,"text":"NOAA Earth System Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":817655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lu, Yanbin","contributorId":260273,"corporation":false,"usgs":false,"family":"Lu","given":"Yanbin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":817656,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cheng, Hai 0000-0002-5305-9458","orcid":"https://orcid.org/0000-0002-5305-9458","contributorId":223142,"corporation":false,"usgs":false,"family":"Cheng","given":"Hai","email":"","affiliations":[{"id":40680,"text":"Xi'an Jiaotong University","active":true,"usgs":false}],"preferred":false,"id":817657,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Edwards, R. Lawrence 0000-0002-7027-5881","orcid":"https://orcid.org/0000-0002-7027-5881","contributorId":223143,"corporation":false,"usgs":false,"family":"Edwards","given":"R.","email":"","middleInitial":"Lawrence","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":817658,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Southon, John R.","contributorId":201538,"corporation":false,"usgs":false,"family":"Southon","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":36191,"text":"Keck Carbon Cycle AMS Laboratory, Department of Earth System Science, University of California Irvine, Irvine, California, USA.","active":true,"usgs":false}],"preferred":false,"id":817659,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Santos, Guaciara M. 0000-0003-1755-6390","orcid":"https://orcid.org/0000-0003-1755-6390","contributorId":260274,"corporation":false,"usgs":false,"family":"Santos","given":"Guaciara","email":"","middleInitial":"M.","affiliations":[{"id":13696,"text":"University of California Irvine","active":true,"usgs":false}],"preferred":false,"id":817660,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Decampo, Daniel M. 0000-0003-3523-2592","orcid":"https://orcid.org/0000-0003-3523-2592","contributorId":260276,"corporation":false,"usgs":false,"family":"Decampo","given":"Daniel","email":"","middleInitial":"M.","affiliations":[{"id":52554,"text":"Georgia State University","active":true,"usgs":false}],"preferred":false,"id":817661,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lynch-Stieglitz, Jean 0000-0002-9353-1972","orcid":"https://orcid.org/0000-0002-9353-1972","contributorId":260279,"corporation":false,"usgs":false,"family":"Lynch-Stieglitz","given":"Jean","email":"","affiliations":[{"id":27815,"text":"Georgia Tech","active":true,"usgs":false}],"preferred":false,"id":817662,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Chen, Tianran","contributorId":260282,"corporation":false,"usgs":false,"family":"Chen","given":"Tianran","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":817663,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sayani, Hussein R. 0000-0002-0607-4882","orcid":"https://orcid.org/0000-0002-0607-4882","contributorId":260284,"corporation":false,"usgs":false,"family":"Sayani","given":"Hussein","email":"","middleInitial":"R.","affiliations":[{"id":27815,"text":"Georgia Tech","active":true,"usgs":false}],"preferred":false,"id":817664,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Thompson, Diane M. 0000-0002-6181-1259","orcid":"https://orcid.org/0000-0002-6181-1259","contributorId":260285,"corporation":false,"usgs":false,"family":"Thompson","given":"Diane","email":"","middleInitial":"M.","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":817665,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Conroy, Jessica L.","contributorId":260286,"corporation":false,"usgs":false,"family":"Conroy","given":"Jessica","email":"","middleInitial":"L.","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":817666,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Moore, Andrea L.","contributorId":260287,"corporation":false,"usgs":false,"family":"Moore","given":"Andrea","email":"","middleInitial":"L.","affiliations":[{"id":52557,"text":"University of Mary Washington","active":true,"usgs":false}],"preferred":false,"id":817667,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Townsend, Kayla","contributorId":260288,"corporation":false,"usgs":false,"family":"Townsend","given":"Kayla","email":"","affiliations":[{"id":27815,"text":"Georgia Tech","active":true,"usgs":false}],"preferred":false,"id":817668,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Hagos, Melat","contributorId":260289,"corporation":false,"usgs":false,"family":"Hagos","given":"Melat","email":"","affiliations":[{"id":27815,"text":"Georgia Tech","active":true,"usgs":false}],"preferred":false,"id":817669,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"O’Connor, Gemma","contributorId":260290,"corporation":false,"usgs":false,"family":"O’Connor","given":"Gemma","email":"","affiliations":[{"id":27815,"text":"Georgia Tech","active":true,"usgs":false}],"preferred":false,"id":817670,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":817671,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}}
]}