{"pageNumber":"33","pageRowStart":"800","pageSize":"25","recordCount":4111,"records":[{"id":70222956,"text":"70222956 - 2020 - Flea parasitism and host survival in a plague-relevant system: Theoretical and conservation implications","interactions":[],"lastModifiedDate":"2022-04-04T16:23:24.598092","indexId":"70222956","displayToPublicDate":"2020-03-31T08:27:16","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Flea parasitism and host survival in a plague-relevant system: Theoretical and conservation implications","docAbstract":"<p><span>Plague is a bacterial zoonosis of mammalian hosts and flea vectors. The disease is capable of ravaging rodent populations and transforming ecosystems. Because plague mortality is likely to be predicted by flea parasitism, it is critical to understand vector dynamics. It has been hypothesized that paltry precipitation and reduced vegetative production predispose herbivorous rodents to malnourishment and flea parasitism, and flea parasitism varies directly with plague mortality. We evaluated these hypotheses on five colonies of Utah prairie dogs (UPDs;&nbsp;</span><i>Cynomys parvidens</i><span>), on the Awapa Plateau, Utah, US, in 2013–16. Ten flea species were identified among 3,257 fleas from UPDs. These 10 flea species parasitize prairie dogs, mice, rats, voles, ground squirrels, chipmunks, and marmots, all known hosts of plague. The abundance of fleas on individual UPDs (1,198 observations) varied inversely with UPD body condition; fleas were most abundant on lightweight, malnourished UPDs. Flea abundance on UPDs was highest in dry years that were preceded by wet years. Increased precipitation and soil moisture in the prior year might generate humid microclimates in UPD burrows (that could facilitate flea survival and reproduction) and paltry precipitation in the current year could predispose UPDs to malnourishment and flea parasitism. Annual re-encounter rates for UPDs (1,072 observations) were reduced in wetter years preceded by drier years; reduced precipitation and vegetative production might kill UPDs, and increased flea densities in drier years could provide conditions for plague transmission (and UPD mortality) when moisture returns. Re-encounter rates were reduced for UPDs carrying at least one flea compared to UPDs with no detected fleas. These results support the hypothesis that reduced precipitation in the current year predisposes UPDs to flea parasitism. Our results also suggest a link between flea parasitism and UPD mortality. Given documented connections between flea parasitism and plague transmission, our results point toward an effect of flea parasitism on plague-related deaths for individual UPDs, a phenomenon rarely investigated in nature.</span></p>","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2019-08-201","usgsCitation":"Eads, D.A., Abbott, R.C., Biggins, D.E., and Rocke, T.E., 2020, Flea parasitism and host survival in a plague-relevant system: Theoretical and conservation implications: Journal of Wildlife Diseases, v. 56, no. 2, p. 378-387, https://doi.org/10.7589/2019-08-201.","productDescription":"10 p.","startPage":"378","endPage":"387","ipdsId":"IP-112909","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":437045,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IG320C","text":"USGS data release","linkHelpText":"Data on Flea Parasitism and Annual Re-encounters of Utah Prairie Dogs at 5 colonies on the Awapa Plateau, Utah, USA, 2013-2016"},{"id":387804,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Awapa Plateau","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.85317993164062,\n              38.10916794391597\n            ],\n            [\n              -111.69731140136719,\n              38.10916794391597\n            ],\n            [\n              -111.69731140136719,\n              38.24087667992996\n            ],\n            [\n              -111.85317993164062,\n              38.24087667992996\n            ],\n            [\n              -111.85317993164062,\n              38.10916794391597\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"56","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eads, David A. 0000-0002-4247-017X deads@usgs.gov","orcid":"https://orcid.org/0000-0002-4247-017X","contributorId":173639,"corporation":false,"usgs":true,"family":"Eads","given":"David","email":"deads@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":820904,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abbott, Rachel C. 0000-0003-4820-9295 rabbott@usgs.gov","orcid":"https://orcid.org/0000-0003-4820-9295","contributorId":1183,"corporation":false,"usgs":true,"family":"Abbott","given":"Rachel","email":"rabbott@usgs.gov","middleInitial":"C.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":820905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biggins, Dean E. 0000-0003-2078-671X bigginsd@usgs.gov","orcid":"https://orcid.org/0000-0003-2078-671X","contributorId":2522,"corporation":false,"usgs":true,"family":"Biggins","given":"Dean","email":"bigginsd@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":820906,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":820907,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70209829,"text":"70209829 - 2020 - High-throughput sequencing reveals distinct regional genetic structure among remaining populations of an endangered salt marsh plant in California","interactions":[],"lastModifiedDate":"2020-06-04T17:14:15.685216","indexId":"70209829","displayToPublicDate":"2020-03-30T07:31:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"High-throughput sequencing reveals distinct regional genetic structure among remaining populations of an endangered salt marsh plant in California","docAbstract":"Conservation of rare species requires careful consideration to both preserve locally adapted traits and maintain genetic diversity, as species’ ranges fluctuate in response to a changing climate and habitat loss. Salt marsh systems in California have been highly modified and many salt marsh obligate species have undergone range reductions and habitat loss with concomitant losses of genetic diversity and connectivity. Remaining salt marshes are threatened by rising sea levels, and so these habitats will likely require active restoration and re-establishment efforts. This study aims to provide a reference point for the current status of genetic diversity and range-wide population structure of a federally and state listed endangered plant, Salt Marsh Bird’s Beak (Chloropyron maritimum subsp. maritimum) that can inform future preservation and restoration efforts. We used historical data and current monitoring information to locate and sample all known occurrences throughout the species range in Southern California, and three additional occurrences from Baja California, Mexico. We used flow cytometry and single nucleotide polymorphic markers (SNPs), generated by double-digest restriction-site associated DNA sequencing (ddRAD), to assess relative ploidy, and estimate genetic diversity and population structure across the region. Overall, we found four to five distinct genetic clusters that coincide with geographic regions. Genetic diversity was greatest in the southern part of the range including Baja California and San Diego. These findings can bolster management and restoration efforts by identifying potentially isolated occurrences and areas that are rich sources of allelic diversity, and by providing insight into the amount of genetic differentiation across the species range.","language":"English","publisher":"Springer","doi":"10.1007/s10592-020-01269-3","usgsCitation":"Milano, E.R., Mulligan, M.R., Rebman, J.P., and Vandergast, A.G., 2020, High-throughput sequencing reveals distinct regional genetic structure among remaining populations of an endangered salt marsh plant in California: Conservation Genetics, v. 21, p. 547-559, https://doi.org/10.1007/s10592-020-01269-3.","productDescription":"13 p.","startPage":"547","endPage":"559","ipdsId":"IP-112923","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":374396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.201171875,\n              32.65787573695528\n            ],\n            [\n              -116.103515625,\n              32.65787573695528\n            ],\n            [\n              -116.103515625,\n              35.460669951495305\n            ],\n            [\n              -121.201171875,\n              35.460669951495305\n            ],\n            [\n              -121.201171875,\n              32.65787573695528\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"21","noUsgsAuthors":false,"publicationDate":"2020-03-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Milano, Elizabeth R. 0000-0003-4143-9303","orcid":"https://orcid.org/0000-0003-4143-9303","contributorId":210607,"corporation":false,"usgs":true,"family":"Milano","given":"Elizabeth","email":"","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":788206,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mulligan, Margaret R","contributorId":224408,"corporation":false,"usgs":false,"family":"Mulligan","given":"Margaret","email":"","middleInitial":"R","affiliations":[{"id":40878,"text":"San Diego Natural History Museum, San Diego, CA","active":true,"usgs":false}],"preferred":false,"id":788207,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rebman, Jon P.","contributorId":145616,"corporation":false,"usgs":false,"family":"Rebman","given":"Jon","email":"","middleInitial":"P.","affiliations":[{"id":16175,"text":"San Diego Natural History Museum","active":true,"usgs":false}],"preferred":false,"id":788208,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergast, Amy G. 0000-0002-7835-6571 avandergast@usgs.gov","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":3963,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"avandergast@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":788209,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70210106,"text":"70210106 - 2020 - Spatial distribution of heavy metals in the West Dongting Lake floodplain, China","interactions":[],"lastModifiedDate":"2020-06-04T17:16:23.814187","indexId":"70210106","displayToPublicDate":"2020-03-23T09:57:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1566,"text":"Environmental Science: Processes and Impacts","active":true,"publicationSubtype":{"id":10}},"title":"Spatial distribution of heavy metals in the West Dongting Lake floodplain, China","docAbstract":"The protection of Dongting Lake is important because it is an overwintering and migration route for many rare and endangered birds of East Asia and Australasia, but an assessment of heavy metal contamination in West Dongting Lake is lacking. A total of 75 sediment samples (five sites x three sediment depths x five repeats) were collected in West Dongting Lake in January 2017 to assess the spatial distribution and ecological risk of heavy metal in West Dongting Lake. Heavy metal values varied by sediment depth including As, Cd, Zn, and Cu, with depth giving an indication of recent vs. historical deposition. The major input of Hg, Cu, Ni may come from continued anthropogenic activities related to regional industrial activities within Yuan River and Li River whereas, the major sources of spread Cd pollution may be from agricultural fertilizers.","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/C9EM00536F","usgsCitation":"Peng, D., Liu, Z., Su, X., Xiao, Y., Wang, Y., and Middleton, B., 2020, Spatial distribution of heavy metals in the West Dongting Lake floodplain, China: Environmental Science: Processes and Impacts, v. 22, p. 1256-1265, https://doi.org/10.1039/C9EM00536F.","productDescription":"10 p.","startPage":"1256","endPage":"1265","ipdsId":"IP-104637","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":374822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"West Dongting Lake floodplain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              111.456298828125,\n              28.289870471423562\n            ],\n            [\n              112.82409667968749,\n              28.289870471423562\n            ],\n            [\n              112.82409667968749,\n              29.38217507514529\n            ],\n            [\n              111.456298828125,\n              29.38217507514529\n            ],\n            [\n              111.456298828125,\n              28.289870471423562\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"22","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peng, Dong","contributorId":224694,"corporation":false,"usgs":false,"family":"Peng","given":"Dong","email":"","affiliations":[{"id":40912,"text":"Beijing Forestry","active":true,"usgs":false}],"preferred":false,"id":789134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Ziyu","contributorId":224695,"corporation":false,"usgs":false,"family":"Liu","given":"Ziyu","email":"","affiliations":[{"id":40912,"text":"Beijing Forestry","active":true,"usgs":false}],"preferred":false,"id":789135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Su, Xinyue","contributorId":224696,"corporation":false,"usgs":false,"family":"Su","given":"Xinyue","email":"","affiliations":[{"id":40912,"text":"Beijing Forestry","active":true,"usgs":false}],"preferred":false,"id":789136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xiao, Yaquin","contributorId":224697,"corporation":false,"usgs":false,"family":"Xiao","given":"Yaquin","email":"","affiliations":[{"id":40912,"text":"Beijing Forestry","active":true,"usgs":false}],"preferred":false,"id":789137,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Yuechen","contributorId":224698,"corporation":false,"usgs":false,"family":"Wang","given":"Yuechen","email":"","affiliations":[{"id":40912,"text":"Beijing Forestry","active":true,"usgs":false}],"preferred":false,"id":789138,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":222689,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":789139,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70209164,"text":"70209164 - 2020 - Quantifying interregional flows of multiple ecosystem services – A case study for Germany","interactions":[],"lastModifiedDate":"2020-03-20T06:39:18","indexId":"70209164","displayToPublicDate":"2020-03-19T18:54:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1841,"text":"Global Environmental Change","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying interregional flows of multiple ecosystem services – A case study for Germany","docAbstract":"Despite a growing number of national-scale ecosystem service (ES) assessments, few studies consider the impacts of ES use and consumption beyond national or regional boundaries. Interregional ES flows – ecosystem services “imported” from and “exported” to other countries – are rarely analyzed and their importance for global sustainability is little known. Here, we provide a first multi-ES quantification of a nation's use of ES from abroad. We focus on ES flows that benefit the population in Germany but are supplied outside German territory. We employ a conceptual framework recently developed to systematically quantify interregional ES flows. We address four types of interregional ES flows with: (i) biophysical flows of traded goods: cocoa import for consumption; (ii) flows mediated by migratory species: migration of birds providing pest control; (iii) passive biophysical flows: flood control along transboundary watersheds; and (iv) information flows: China's giant panda loan to the Berlin Zoo. We determined that: (i) Ivory Coast and Ghana alone supply around 53% of Germany's cocoa while major negative consequences for biodiversity occurred in Cameroon and Ecuador; (ii) Africa´s humid and sub-humid climate zones are important habitats for the majority of migratory bird species that provide natural pest control services in agricultural areas in Germany; (iii) Upstream watersheds outside the country add an additional 64% flood regulation services nationally, while Germany exports 40% of flood regulation services in neighboring, downstream countries; (iv) Information flows transported by the pandas were mainly related to political aspects and - contrary to our expectations - considerably less on biological and natural aspects. We discuss the implications of these results for international resource management policy and governance.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gloenvcha.2020.102051","usgsCitation":"Kleeman, J., Schroter, M., Bagstad, K.J., Kuhlicke, C., Kastner, T., Fridman, D., Schulp, C.J., Wolff, S., Martinez-Lopez, J., Koellner, T., Arnhold, S., Martin-Lopez, B., Marques, A., Lopez-Hoffman, L., Liu, J., Kissinger, M., Guerra, C., and Bonn, A., 2020, Quantifying interregional flows of multiple ecosystem services – A case study for Germany: Global Environmental Change, v. 61, 102051, https://doi.org/10.1016/j.gloenvcha.2020.102051.","productDescription":"102051","ipdsId":"IP-104288","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":457315,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gloenvcha.2020.102051","text":"Publisher Index Page"},{"id":373393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Germany","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[9.92191,54.9831],[9.93958,54.59664],[10.95011,54.36361],[10.93947,54.00869],[11.95625,54.19649],[12.51844,54.47037],[13.64747,54.07551],[14.11969,53.75703],[14.35332,53.24817],[14.07452,52.98126],[14.4376,52.62485],[14.68503,52.08995],[14.6071,51.74519],[15.017,51.10667],[14.57072,51.00234],[14.30701,51.11727],[14.05623,50.92692],[13.33813,50.73323],[12.96684,50.48408],[12.24011,50.26634],[12.41519,49.96912],[12.52102,49.54742],[13.03133,49.30707],[13.59595,48.87717],[13.24336,48.41611],[12.8841,48.28915],[13.02585,47.63758],[12.93263,47.46765],[12.62076,47.67239],[12.14136,47.70308],[11.42641,47.52377],[10.5445,47.5664],[10.40208,47.30249],[9.89607,47.5802],[9.59423,47.52506],[8.52261,47.83083],[8.3173,47.61358],[7.46676,47.62058],[7.59368,48.33302],[8.09928,49.01778],[6.65823,49.20196],[6.18632,49.4638],[6.24275,49.90223],[6.04307,50.12805],[6.15666,50.80372],[5.98866,51.85162],[6.5894,51.85203],[6.84287,52.22844],[7.09205,53.14404],[6.90514,53.48216],[7.10042,53.69393],[7.93624,53.7483],[8.12171,53.52779],[8.80073,54.02079],[8.57212,54.39565],[8.52623,54.96274],[9.28205,54.83087],[9.92191,54.9831]]]},\"properties\":{\"name\":\"Germany\"}}]}","volume":"61","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kleeman, Janina","contributorId":215954,"corporation":false,"usgs":false,"family":"Kleeman","given":"Janina","email":"","affiliations":[{"id":39336,"text":"Helmholtz Centre for Environmental Research","active":true,"usgs":false}],"preferred":false,"id":785177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schroter, Matthias 0000-0003-0207-7311","orcid":"https://orcid.org/0000-0003-0207-7311","contributorId":202612,"corporation":false,"usgs":false,"family":"Schroter","given":"Matthias","email":"","affiliations":[{"id":36494,"text":"UFZ – Helmholtz Centre for Environmental Research","active":true,"usgs":false}],"preferred":false,"id":785178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":785179,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuhlicke, Christian 0000-0002-1193-228X","orcid":"https://orcid.org/0000-0002-1193-228X","contributorId":215955,"corporation":false,"usgs":false,"family":"Kuhlicke","given":"Christian","email":"","affiliations":[{"id":39336,"text":"Helmholtz Centre for Environmental Research","active":true,"usgs":false}],"preferred":false,"id":785180,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kastner, Thomas","contributorId":202618,"corporation":false,"usgs":false,"family":"Kastner","given":"Thomas","email":"","affiliations":[{"id":27439,"text":"Senckenberg Biodiversity and Climate Research Centre","active":true,"usgs":false}],"preferred":false,"id":785181,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fridman, Dor 0000-0003-3908-3571","orcid":"https://orcid.org/0000-0003-3908-3571","contributorId":223486,"corporation":false,"usgs":false,"family":"Fridman","given":"Dor","email":"","affiliations":[{"id":36498,"text":"Ben-Gurion University of the Negev","active":true,"usgs":false}],"preferred":false,"id":785182,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schulp, Catharina J. E.","contributorId":202624,"corporation":false,"usgs":false,"family":"Schulp","given":"Catharina","email":"","middleInitial":"J. E.","affiliations":[{"id":28162,"text":"Vrije University Amsterdam","active":true,"usgs":false}],"preferred":false,"id":785183,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wolff, Sarah","contributorId":202626,"corporation":false,"usgs":false,"family":"Wolff","given":"Sarah","email":"","affiliations":[{"id":28162,"text":"Vrije University Amsterdam","active":true,"usgs":false}],"preferred":false,"id":785184,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Martinez-Lopez, Javier 0000-0003-4857-3396","orcid":"https://orcid.org/0000-0003-4857-3396","contributorId":208480,"corporation":false,"usgs":false,"family":"Martinez-Lopez","given":"Javier","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":785185,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Koellner, Thomas 0000-0001-5022-027X","orcid":"https://orcid.org/0000-0001-5022-027X","contributorId":202613,"corporation":false,"usgs":false,"family":"Koellner","given":"Thomas","email":"","affiliations":[{"id":36495,"text":"University of Bayeruth","active":true,"usgs":false}],"preferred":false,"id":785186,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Arnhold, Sebastian 0000-0003-4823-4570","orcid":"https://orcid.org/0000-0003-4823-4570","contributorId":202615,"corporation":false,"usgs":false,"family":"Arnhold","given":"Sebastian","email":"","affiliations":[{"id":36495,"text":"University of Bayeruth","active":true,"usgs":false}],"preferred":false,"id":785187,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Martin-Lopez, Berta 0000-0003-2622-0135","orcid":"https://orcid.org/0000-0003-2622-0135","contributorId":215956,"corporation":false,"usgs":false,"family":"Martin-Lopez","given":"Berta","email":"","affiliations":[{"id":36500,"text":"Leuphana University","active":true,"usgs":false}],"preferred":false,"id":785188,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Marques, Alexandra","contributorId":202622,"corporation":false,"usgs":false,"family":"Marques","given":"Alexandra","email":"","affiliations":[{"id":36499,"text":"Leiden University","active":true,"usgs":false}],"preferred":false,"id":785189,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Lopez-Hoffman, Laura","contributorId":149127,"corporation":false,"usgs":false,"family":"Lopez-Hoffman","given":"Laura","affiliations":[{"id":17654,"text":"School of Natural Resources & the Environment and Udall Center for Studies in Public Policy, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":785190,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Liu, Jianguo 0000-0002-6058-5472","orcid":"https://orcid.org/0000-0002-6058-5472","contributorId":202620,"corporation":false,"usgs":false,"family":"Liu","given":"Jianguo","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":785191,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Kissinger, Meidad","contributorId":202619,"corporation":false,"usgs":false,"family":"Kissinger","given":"Meidad","email":"","affiliations":[{"id":36498,"text":"Ben-Gurion University of the Negev","active":true,"usgs":false}],"preferred":false,"id":785192,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Guerra, Carlos 0000-0003-4917-2105","orcid":"https://orcid.org/0000-0003-4917-2105","contributorId":215953,"corporation":false,"usgs":false,"family":"Guerra","given":"Carlos","email":"","affiliations":[{"id":39335,"text":"Martin Luther University Halle-Wittenberg","active":true,"usgs":false}],"preferred":false,"id":785193,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Bonn, Aletta 0000-0002-8345-4600","orcid":"https://orcid.org/0000-0002-8345-4600","contributorId":202627,"corporation":false,"usgs":false,"family":"Bonn","given":"Aletta","email":"","affiliations":[{"id":36494,"text":"UFZ – Helmholtz Centre for Environmental Research","active":true,"usgs":false}],"preferred":false,"id":785194,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70211840,"text":"70211840 - 2020 - Consequences of ignoring group association in spatial capture-recapture analysis","interactions":[],"lastModifiedDate":"2020-10-28T15:45:48.200351","indexId":"70211840","displayToPublicDate":"2020-03-17T15:32:47","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3766,"text":"Wildlife Biology","active":true,"publicationSubtype":{"id":10}},"title":"Consequences of ignoring group association in spatial capture-recapture analysis","docAbstract":"<p><span>Many models in population ecology, including spatial capture–recapture (SCR) models, assume that individuals are distributed and detected independently of one another. In reality, this is rarely the case – both antagonistic and gregarious relationships lead to non-independent spatial configurations, with territorial exclusion at one end of the spectrum and group-living at the other. Previous simulation studies suggest that grouping has limited impact on the outcome of SCR analyses. However, group associations entail not only spatial clustering of activity centers but also coordinated space use by group members, potentially impacting both ecological and observation processes underlying SCR analysis. We simulated SCR scenarios with different strengths of aggregation (clustering of individuals into groups with shared activity centers) and cohesion (synchronization of detection patterns of members of a group). We then fit SCR models to the simulated data sets and evaluated the effect of aggregation and cohesion on parameter estimates. Low to moderate aggregation and cohesion did not impact the bias and precision of estimates of density and the scale parameter of the detection function. However, non-independence between individuals led to high levels of overdispersion. Overdispersion strongly decreased the coverage of confidence intervals around parameter estimates, thereby increasing the probability of erroneous predictions. Our results indicate that SCR models are robust to moderate levels of aggregation and cohesion. Nonetheless, spatial dependence between individuals can lead to false inference. We recommend that practitioners 1) test for the presence of overdispersion in SCR data caused by aggregation and cohesion, and, if necessary, 2) correct their variance estimates using the overdispersion factor ĉ . Approaches for doing both are described in this paper. We also urge the development of SCR models that incorporate spatial associations between individuals not only to account for overdispersion but also to obtain quantitative information about social aspects of study populations.</span></p>","language":"English","publisher":"BioOne","doi":"10.2981/wlb.00649","usgsCitation":"Bischof, R., Dupont, P., Milleret, C., Chipperfield, J., and Royle, J.A., 2020, Consequences of ignoring group association in spatial capture-recapture analysis: Wildlife Biology, v. 2020, no. 1, wlb.00649, 11 p., https://doi.org/10.2981/wlb.00649.","productDescription":"wlb.00649, 11 p.","ipdsId":"IP-113777","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":457343,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2981/wlb.00649","text":"Publisher Index Page"},{"id":377200,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2020","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bischof, Richard","contributorId":237793,"corporation":false,"usgs":false,"family":"Bischof","given":"Richard","affiliations":[{"id":40295,"text":"Norwegian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":795324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dupont, Pierre","contributorId":237794,"corporation":false,"usgs":false,"family":"Dupont","given":"Pierre","affiliations":[{"id":40295,"text":"Norwegian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":795325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Milleret, Cyril","contributorId":237795,"corporation":false,"usgs":false,"family":"Milleret","given":"Cyril","affiliations":[{"id":40295,"text":"Norwegian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":795326,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chipperfield, Joseph","contributorId":237796,"corporation":false,"usgs":false,"family":"Chipperfield","given":"Joseph","email":"","affiliations":[{"id":40295,"text":"Norwegian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":795327,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":795328,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70228651,"text":"70228651 - 2020 - Optimal spatial prioritization of control resources for elimination of invasive species under demographic uncertainty","interactions":[],"lastModifiedDate":"2022-02-16T18:02:33.912037","indexId":"70228651","displayToPublicDate":"2020-03-13T11:56:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Optimal spatial prioritization of control resources for elimination of invasive species under demographic uncertainty","docAbstract":"<p><span>Populations of invasive species often spread heterogeneously across a landscape, consisting of local populations that cluster in space but are connected by dispersal. A fundamental dilemma for invasive species control is how to optimally allocate limited fiscal resources across local populations. Theoretical work based on perfect knowledge of demographic connectivity suggests that targeting local populations from which migrants originate (sources) can be optimal. However, demographic processes such as abundance and dispersal can be highly uncertain, and the relationship between local population density and damage costs (damage function) is rarely known. We used a metapopulation model to understand how budget and uncertainty in abundance, connectivity, and the damage function, together impact return on investment (ROI) for optimal control strategies. Budget, observational uncertainty, and the damage function had strong effects on the optimal resource allocation strategy. Uncertainty in dispersal probability was the least important determinant of ROI. The damage function determined which resource prioritization strategy was optimal when connectivity was symmetric but not when it was asymmetric. When connectivity was asymmetric, prioritizing source populations had a higher ROI than allocating effort equally across local populations, regardless of the damage function, but uncertainty in connectivity structure and abundance reduced ROI of the optimal prioritization strategy by 57% on average depending on the control budget. With low budgets (monthly removal rate of 6.7% of population), there was little advantage to prioritizing resources, especially when connectivity was high or symmetric, and observational uncertainty had only minor effects on ROI. Allotting funding for improved monitoring appeared to be most important when budgets were moderate (monthly removal of 13–20% of the population). Our result showed that multiple sources of observational uncertainty should be considered concurrently for optimizing ROI. Accurate estimates of connectivity direction and abundance were more important than accurate estimates of dispersal rates. Developing cost-effective surveillance methods to reduce observational uncertainties, and quantitative frameworks for determining how resources should be spatially apportioned to multiple monitoring and control activities are important and challenging future directions for optimizing ROI for invasive species control programs.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/eap.2126","usgsCitation":"Pepin, K.M., Smyser, T.J., Davis, A., Miller, R., McKee, S., VerCauteren, K.C., Kendall, W.L., and Slootmaker, C., 2020, Optimal spatial prioritization of control resources for elimination of invasive species under demographic uncertainty: Ecological Applications, v. 30, no. 6, e02126, 15 p., https://doi.org/10.1002/eap.2126.","productDescription":"e02126, 15 p.","ipdsId":"IP-113401","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":457377,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/812305","text":"External Repository"},{"id":396025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Pepin, Kim M.","contributorId":279406,"corporation":false,"usgs":false,"family":"Pepin","given":"Kim","email":"","middleInitial":"M.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":834933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smyser, Timothy J.","contributorId":279407,"corporation":false,"usgs":false,"family":"Smyser","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":834934,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Amy J.","contributorId":279408,"corporation":false,"usgs":false,"family":"Davis","given":"Amy J.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":834935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Ryan S.","contributorId":279409,"corporation":false,"usgs":false,"family":"Miller","given":"Ryan S.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":834936,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKee, Sophie","contributorId":279410,"corporation":false,"usgs":false,"family":"McKee","given":"Sophie","email":"","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":834937,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"VerCauteren, Kurt C.","contributorId":279413,"corporation":false,"usgs":false,"family":"VerCauteren","given":"Kurt","email":"","middleInitial":"C.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":834938,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834932,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Slootmaker, Chris","contributorId":279414,"corporation":false,"usgs":false,"family":"Slootmaker","given":"Chris","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":834939,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70203860,"text":"sir20195059 - 2020 - Groundwater quality and geochemistry of West Virginia’s southern coal fields","interactions":[],"lastModifiedDate":"2023-03-03T15:42:41.455704","indexId":"sir20195059","displayToPublicDate":"2020-03-12T13:15:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5059","displayTitle":"Groundwater Quality and Geochemistry of West Virginia’s Southern Coal Fields","title":"Groundwater quality and geochemistry of West Virginia’s southern coal fields","docAbstract":"<p>Coal mining has been the dominant industry and land use in West Virginia’s southern coal fields since the mid-1800s. Mortality rates for a variety of serious chronic conditions, such as diabetes, heart disease, and some forms of cancer in Appalachian coal mining regions, are higher than in areas lacking substantial coal mining activity within the Appalachian Region or elsewhere in the United States. Causes of the increased mortality and morbidity are not clear, but poor diet, high rates of smoking, socioeconomic factors, and the quality of groundwater used by area residents are all possible contributing factors. This study was conducted by the U.S. Geological Survey in cooperation with the West Virginia Department of Health and Human Resources and the West Virginia Department of Environmental Protection, with grant support from the Centers for Disease Control and Prevention (CDC) to assess the quality of groundwater in southern West Virginia. The data from this assessment of groundwater quality may be used by the CDC and other agencies to potentially investigate the role or lack thereof of groundwater quality with respect to mortality and morbidity rates in the region. The study was conducted in a region where a high density of current or past coal mining combined with a lack of advanced sewage treatment could affect concentrations of commonly occurring constituents plus contaminants, including nitrate, trace metals, major ions, indicator bacteria, radon, hydrogen sulfide, and dissolved hydrocarbons.</p><p>Because rural residential wells and mine outfalls are considered private sources of water in the region, and are therefore unregulated and unmonitored, water-quality data are sparse. To fill the data gap and assess the groundwater quality in the region, water-quality samples were collected from 60 sites in a 10-county area. The 60 sites sampled included 46 rural residential homeowner wells and 14 mine outfall discharges used for residential supply. For this study, all samples were collected prior to any filtration or other treatments, typically at the pressure tank, and are indicative of total and dissolved constituents in the untreated water.</p><p>Generally, data for the 60 sites indicate that most waters sampled do not exceed thresholds for most U.S. Environmental Protection Agency (EPA) drinking-water standards and U.S. Geological Survey (USGS) drinking-water screening criteria. However, there were several notable exceptions. Turbidity exceeded the 5-Nephelometric Turbidity Unit (NTU) EPA treatment technique (TT) drinking-water standard in 14 of 60 (23 percent) sites sampled and exceeded the 1-NTU TT standard in 51 of 60 (85 percent) sites sampled. Turbidity is common in many wells in southern West Virginia and may be attributed to iron oxyhydroxide precipitates, sediment carried into the aquifers from the shallow soil zone due to improperly constructed or cased wells or transported to the aquifer in shallow stress-relief fracture zones or through permeable bedding-plane partings. For the sites sampled, 31 of 60 (52 percent) had pH values at, above, or below the upper and lower range of the EPA Secondary Maximum Contaminant Level (SMCL, 6.5–8.5 standard units). Of those 31 sites, 28 (90 percent) were indicative of acidic corrosive water and 3 (10 percent) were indicative of alkaline water.</p><p>The Langelier Saturation Index (LSI), which is a measure of the corrosivity of the water, was computed for all sites sampled for the study. Eighty-two percent of the sites sampled had waters that were classified as corrosive, based on a LSI less than −0.5. Corrosive water has the potential to leach lead, copper, and other metals from lead, copper, galvanized, or lead-tin soldered connections in water lines. The chloride to sulfate mass ratio also was assessed with the alkalinity to indicate the potential to promote galvanic corrosion (PPGC) of water lines and plumbing fixtures. Only one of the sites (1.7 percent) classified as a corrosive water site, had a PPGC considered high; the remaining sites were classified as having either a moderate (53.3 percent) or low (45 percent) PPGC. Therefore, the type of plumbing systems sampled for this study may be affected by corrosive water, but the potential for leaching trace metals and other constituents from residential plumbing systems containing older galvanized pipes or lead-tin soldered copper pipes is moderate to low.</p><p>The indicator bacteria total coliform and <i>Escherichia coli</i> (<i>E. coli</i>) also were detected in groundwater samples to varying degrees. Total coliforms, which are a broad class of indicator bacteria, are common in groundwater in southern West Virginia and were detected in 39 of the 60 sites (65 percent) sampled. The presence of total coliform bacteria is a potential indicator of surface contamination, due to improperly constructed or cased wells, or infiltration of soil or other surface contaminants into the aquifer or well bore. <i>E. coli</i> bacteria, however, are much more indicative of fecal contamination of groundwater from either human or animal sources, and 14 of the 60 (23 percent) sites sampled had detections of <i>E. coli</i>. Although only a few strains of <i>E. coli</i> are known pathogens, their presence in groundwater may be an indicator of other related pathogens such as viruses and should be regarded as a serious potential issue. Water treatment such as chlorination, ozonation, or ultraviolet light may be appropriate to kill potential pathogenic bacteria or viruses in the source water.</p><p>Manganese and iron were prevalent contaminants in the groundwater samples collected for this study, with 30 of 60 (50 percent) sites analyzed for manganese and 25 of 60 (42 percent) sites analyzed for iron exceeding the proposed 50- and 300-micrograms per liter (µg/L) SMCL drinking-water standards, respectively, for aesthetic criteria such as taste, odor, or staining of plumbing fixtures. Fourteen of the 60 sites sampled (23 percent) had concentrations of manganese that exceeded the 300-µg/L USGS health-based screening level, and 1 site exceeded the 1,600-µg/L EPA drinking-water equivalent level, which is based on a lifetime exposure level. Sodium is another common constituent in groundwater within the study area. Sodium has an EPA health-based value (HBV) of 20 milligrams per liter (mg/L) for individuals who are on a sodium-restricted diet for blood pressure or other health reasons. Sodium concentrations exceeded the 20-mg/L EPA HBV in 27 of 60 (45 percent) samples.</p><p>Radon, a naturally occurring carcinogenic radioactive gas known to cause lung cancer, was detected at concentrations at or exceeding the proposed 300-picocuries per liter (pCi/L) EPA Maximum Contaminant Level (MCL) in 12 of the 60 (20 percent) sites sampled. Sites with radon gas concentrations exceeding the 300-pCi/L proposed MCL have the potential for airborne concentrations of radon to exceed the 4-pCi/L indoor air standard. Inhalation of radon can cause lung cancer, and the 4-pCi/L indoor air standard is based on an inhalation standard. Therefore, homeowners whose wells have radon gas concentrations exceeding 300 pCi/L may be advised to have their indoor air tested to determine if indoor air concentrations exceed the 4-pCi/L indoor air standard established by the EPA.</p><p>Various factors were analyzed statistically and graphically to determine whether they have an influence on groundwater quality within the study area, including topographic setting, well depth, type of mining (surface or underground), type of site (well or mine outfall), and geologic formation. Only geologic formation and the type of site sampled had strong statistical correlations with one or more of the constituents of concern for this study. The overall chemistry of outfalls (mine outfalls) and wells was significantly different, with a much higher dissolved oxygen content in outfalls than in wells. The dissolved oxygen content is the primary component driving the oxidation and reduction of minerals, and the precipitation of minerals that are saturated or super saturated with respect to various cations and anions. Median dissolved oxygen concentrations for the outfalls sampled was 8.75 mg/L, and only 0.4 mg/L for the wells sampled.</p><p>Median concentrations of sulfate and selenium were much higher in waters from the outfalls sampled, with median concentrations of 73.75 mg/L and 2.35 µg/L, respectively, compared to the wells sampled, which had median concentrations of 18.3 mg/L and less than (&lt;) the 0.05-µg/L method detection limit, respectively. The maximum selenium concentration was for a well, with a concentration of 16.6 µg/L. The geochemical processes that control sulfate and selenium concentrations in groundwater are similar and are the result of the oxidation of sulfide minerals such as pyrite and ferroselite. Iron and manganese concentrations were elevated in most of the wells sampled, with median concentrations of 269.5 and 124.5 µg/L, respectively, but were rarely detected in the outfalls sampled, with median concentrations of &lt; 4.0 and &lt; 0.4 µg/L, respectively. The difference in iron and manganese between wells and outfalls is indicative of the role of dissolved oxygen on processes controlling groundwater chemistry in the region.</p><p>Three principal geologic formations were assessed for the study, and the overall chemistry for the Pocahontas, New River, and Kanawha Formations varied substantially with respect to several constituents. Concentrations of calcium, magnesium, and total dissolved solids were highest for sites sampled in the Pocahontas Formation, with median concentrations of 41.9, 18.6, and 312 mg/L, respectively. For constituents that are commonly associated with mining activity, the highest concentrations were for sites sampled in the New River Formation, with median concentrations of iron and manganese of 2,450 µg/L and 482 µg/L, respectively, and a median pH of 6.35 standard units. Concentrations of barium also were elevated in samples collected from sites in the New River Formation, with a median barium concentration of 184 µg/L. The source of the barium is not fully known but may be associated with commingling of shallow groundwater with deeper brines or dissolution of the mineral barite. The highest median sulfate concentrations were from sites sampled in the Pocahontas Formation, with a median concentration of 64.0 mg/L. Of the 12 sites at or exceeding the 300-pCi/L proposed drinking-water standard for radon, 8 (67 percent of MCL exceedances) were for sites deriving water from the Kanawha Formation, 3 (25 percent of MCL exceedances) were for sites deriving water from the New River Formation, and only 1 site was for water from the Pocahontas Formation (8 percent of proposed MCL exceedances).</p><p>Dissolved hydrocarbons, including methane, ethane, propane, propene, <i>n</i>- and <i>i</i>-butane, 1-butene, <i>n</i>- and <i>i</i>-pentane, pentane, 2- and 3-ethyl pentane, hexane, and benzene were analyzed in samples collected from 59 of the 60 sites to assess the potential occurrence and sources of these trace gases in groundwater within the study area. Results of the analysis indicate that most of the gas is of shallow biogenic origin, possibly associated with coal-bed methane, but a subset of samples has a gas signature and a chloride to bromide ratio indicative of potential mixing with deeper thermogenic gases. Only 2 of the 59 (3.3 percent) sites sampled had concentrations of methane gas, which is a highly combustible and explosive gas, exceeding the 10 milligrams per kilogram level of concern established by the U.S. Office of Surface Mining Reclamation and Enforcement.</p><p>Principal components analysis was used to assess the primary geochemical processes occurring in the aquifers sampled. The first principal component had significant positive loadings for bromide, chloride, silica, ammonia, barium, iron, manganese, and arsenic, and significant negative loadings for dissolved oxygen, potassium, nitrate, and uranium, and reflects reduction and oxidation (redox) processes occurring in deeper anoxic groundwater or shallow oxic groundwater. The strong positive loadings for iron, manganese, barium, and arsenic are correlated with reducing conditions often found deeper in the aquifer. More oxic water is correlated with oxidation of nitrogen species to nitrate and environmental mobilization of uranium and sulfate in shallow wells and mine outfalls.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195059","collaboration":"Prepared in cooperation with the West Virginia Department of Health and Human Resources, Office of Environmental Health Services and the West Virginia Department of Environmental Protection, Division of Water and Waste Management","usgsCitation":"Kozar, M.D., McAdoo, M.A., and Haase, K.B., 2020, Groundwater quality and geochemistry of West Virginia’s southern coal fields (ver. 1.1, March 2020): U.S. Geological Survey Scientific Investigations Report 2019−5059, 78 p., https://doi.org/10.3133/sir20195059.","productDescription":"x, 78 p.","numberOfPages":"92","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-103597","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":399535,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109686.htm"},{"id":373178,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2019/5059/versionhistory.txt","size":"544 B","linkFileType":{"id":2,"text":"txt"}},{"id":373186,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5059/sir20195059.pdf","text":"Report","size":"9.89 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5059"},{"id":371713,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5059/coverthb2.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Southern coal 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1.1: March 2020; Version 1.0: February 2020","contact":"<p><a href=\"mailto:dc_va@usgs.gov\" data-mce-href=\"mailto:dc_va@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/va-wv-water\" data-mce-href=\"https://www.usgs.gov/centers/va-wv-water\">Virginia/West Virginia Science Center</a><br>U.S. Geological Survey<br>11 Dunbar Street<br>Charleston, WV 25301</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods of Data Collection and Analysis</li><li>Groundwater Quality</li><li>Geochemistry</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Correlation matrix showing Spearman correlation coefficients of statistical significance at a confidence interval of 99.9 percent for 46 variables, including 41 chemical constituents and 5 principal component analysis scores</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2020-02-19","revisedDate":"2020-03-12","noUsgsAuthors":false,"publicationDate":"2020-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Kozar, Mark D. 0000-0001-7755-7657 mdkozar@usgs.gov","orcid":"https://orcid.org/0000-0001-7755-7657","contributorId":1963,"corporation":false,"usgs":true,"family":"Kozar","given":"Mark","email":"mdkozar@usgs.gov","middleInitial":"D.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":764486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAdoo, Mitchell A. 0000-0002-3895-0816 mmcadoo@usgs.gov","orcid":"https://orcid.org/0000-0002-3895-0816","contributorId":200287,"corporation":false,"usgs":true,"family":"McAdoo","given":"Mitchell","email":"mmcadoo@usgs.gov","middleInitial":"A.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":764487,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haase, Karl B. 0000-0002-6897-6494","orcid":"https://orcid.org/0000-0002-6897-6494","contributorId":216317,"corporation":false,"usgs":true,"family":"Haase","given":"Karl B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":764488,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70208979,"text":"70208979 - 2020 - Coupling of Indo-Pacific climate variability over the last millennium","interactions":[],"lastModifiedDate":"2020-04-06T23:21:11.759548","indexId":"70208979","displayToPublicDate":"2020-03-09T18:28:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Coupling of Indo-Pacific climate variability over the last millennium","docAbstract":"The Indian Ocean Dipole (IOD) impacts climate and rainfall across the world, and most\nseverely in nations surrounding the Indian Ocean1-4. The frequency and intensity of positive\nIOD events increased during the 20th Century5 and may continue to intensify in a warming\nworld6; however, confidence in future IOD changes is limited by known biases in model\nrepresentations of the IOD7 and the lack of information on natural IOD variability prior to\nanthropogenic climate change. Here we use precisely dated and highly resolved coral records\nfrom the eastern equatorial Indian Ocean, where the signature of IOD variability is optimised,\nto produce a semi-continuous reconstruction of IOD variability that covers five centuries of\nthe last millennium. Our reconstruction demonstrates that extreme positive IOD events were\nrare prior to 1960. However, the strongest event on record (1997) is not unprecedented as at\nleast one event that was approximately 27% to 42% larger occurred naturally during the 17th\nCentury. We further show that a persistent, tight coupling existed between variability of the\nIOD and the El Niño-Southern Oscillation during the last millennium. Indo-Pacific coupling was\ncharacterised by weak interannual variability prior to ~1590 CE which likely altered\nteleconnection patterns, and anomalously strong variability during the 17th Century that was\nassociated with societal upheaval in tropical Asia. A tendency for clustering of positive IOD\nevents is evident in our reconstruction, which together with the identification of extreme IOD\nvariability and persistent tropical Indo-Pacific climate coupling may have implications for\nimproving seasonal and decadal prediction schemes and managing the climate risks of future\nIOD variability.","language":"English","publisher":"Nature ","doi":"10.1038/s41586-020-2084-4","usgsCitation":"Abram, N.J., Wright, N.M., Ellis, B., Dixon, B.C., Wurtzel, J.B., England, M.H., Ummenhofer, C.C., Philibosian, B.E., Cahyarini, S.Y., Yu, T., Shen, C., Cheng, H., Edwards, R.L., and Heslop, D., 2020, Coupling of Indo-Pacific climate variability over the last millennium: Nature, v. 579, p. 385-392, https://doi.org/10.1038/s41586-020-2084-4.","productDescription":"8 p.","startPage":"385","endPage":"392","ipdsId":"IP-107432","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":467295,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://openresearch-repository.anu.edu.au/bitstream/1885/218995/3/01_Abram_Coupling_of_Indo-Pacific_2020.pdf.jpg","text":"External Repository"},{"id":373037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              71.015625,\n              -31.653381399663985\n            ],\n            [\n              155.390625,\n              -31.653381399663985\n            ],\n            [\n              155.390625,\n              24.84656534821976\n            ],\n            [\n              71.015625,\n              24.84656534821976\n            ],\n            [\n              71.015625,\n              -31.653381399663985\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"579","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2020-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Abram, Nerilie J.","contributorId":195006,"corporation":false,"usgs":false,"family":"Abram","given":"Nerilie","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":784263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Nicky M. 0000-0002-5600-3193","orcid":"https://orcid.org/0000-0002-5600-3193","contributorId":223135,"corporation":false,"usgs":false,"family":"Wright","given":"Nicky","email":"","middleInitial":"M.","affiliations":[{"id":16807,"text":"Australian National University","active":true,"usgs":false}],"preferred":false,"id":784264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellis, Bethany 0000-0002-4662-1115","orcid":"https://orcid.org/0000-0002-4662-1115","contributorId":223136,"corporation":false,"usgs":false,"family":"Ellis","given":"Bethany","email":"","affiliations":[{"id":16807,"text":"Australian National University","active":true,"usgs":false}],"preferred":false,"id":784265,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dixon, Bronwyn C.","contributorId":195017,"corporation":false,"usgs":false,"family":"Dixon","given":"Bronwyn","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":784266,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wurtzel, Jennifer B. 0000-0002-5285-4492","orcid":"https://orcid.org/0000-0002-5285-4492","contributorId":223137,"corporation":false,"usgs":false,"family":"Wurtzel","given":"Jennifer","email":"","middleInitial":"B.","affiliations":[{"id":16807,"text":"Australian National University","active":true,"usgs":false}],"preferred":false,"id":784267,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"England, Matthew H. 0000-0001-9696-2930","orcid":"https://orcid.org/0000-0001-9696-2930","contributorId":223138,"corporation":false,"usgs":false,"family":"England","given":"Matthew","email":"","middleInitial":"H.","affiliations":[{"id":27304,"text":"University of New South Wales","active":true,"usgs":false}],"preferred":false,"id":784268,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ummenhofer, Caroline C. 0000-0002-9163-3967","orcid":"https://orcid.org/0000-0002-9163-3967","contributorId":223139,"corporation":false,"usgs":false,"family":"Ummenhofer","given":"Caroline","email":"","middleInitial":"C.","affiliations":[{"id":40678,"text":"University of New South Wales; Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":784269,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Philibosian, Belle E. 0000-0003-3138-4716","orcid":"https://orcid.org/0000-0003-3138-4716","contributorId":206110,"corporation":false,"usgs":true,"family":"Philibosian","given":"Belle","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":784262,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cahyarini, Sri Yudawati 0000-0001-8378-0716","orcid":"https://orcid.org/0000-0001-8378-0716","contributorId":223140,"corporation":false,"usgs":false,"family":"Cahyarini","given":"Sri","email":"","middleInitial":"Yudawati","affiliations":[{"id":40679,"text":"Research Center for Geotechnology, Indonesian Institute of Sciences (LIPI)","active":true,"usgs":false}],"preferred":false,"id":784270,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yu, Tsai-Luen","contributorId":223141,"corporation":false,"usgs":false,"family":"Yu","given":"Tsai-Luen","email":"","affiliations":[{"id":30216,"text":"National Taiwan University","active":true,"usgs":false}],"preferred":false,"id":784271,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Shen, Chuan-Chou","contributorId":193424,"corporation":false,"usgs":false,"family":"Shen","given":"Chuan-Chou","email":"","affiliations":[{"id":27347,"text":"High-precision Mass Spectrometry and Environment Change Laboratory (HISPEC), Department of Geosciences, National Taiwan University","active":true,"usgs":false}],"preferred":false,"id":784272,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"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":784273,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"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":784274,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Heslop, David 0000-0001-8245-0555","orcid":"https://orcid.org/0000-0001-8245-0555","contributorId":223144,"corporation":false,"usgs":false,"family":"Heslop","given":"David","email":"","affiliations":[{"id":16807,"text":"Australian National University","active":true,"usgs":false}],"preferred":false,"id":784275,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70228433,"text":"70228433 - 2020 - Estimating population persistence for at-risk species using citizen science data","interactions":[],"lastModifiedDate":"2022-02-10T13:24:33.608697","indexId":"70228433","displayToPublicDate":"2020-03-03T07:22:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Estimating population persistence for at-risk species using citizen science data","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0050\">Population persistence probability is valuable for characterizing risk to species and informing listing and conservation decisions but is challenging to estimate through traditional methods for rare, data-limited species. Modeling approaches have used citizen science data to mitigate data limitations of focal species and better estimate parameters such as occupancy and detection, but their use to estimate persistence and inform conservation decisions is limited. We developed an approach to estimate persistence using only occurrence records of the target species and citizen science occurrence data of non-target species to account for search effort and imperfect detection. We applied the approach to a highly cryptic and data-limited species, the southern hognose snake (<i>Heterodon simus</i>), as part of its USFWS Species Status Assessment, and estimated current (in 2018) and future persistence under plausible scenarios of varying levels of urbanization, sea level rise, and management. Of 222 known populations, 133 (60%) are likely extirpated currently (persistence probability&nbsp;&lt;&nbsp;50%), and 165 (74%) populations are likely to be extirpated by 2080 with no additional management. Future management scenarios that included strategies to acquire and improve habitat on currently unprotected lands with existing populations lessened the estimated rate of population declines. These results can directly inform listing decisions and conservation planning for the southern hognose snake by Federal, State, and other partners. Our approach – using occurrence records and auxiliary data from non-target species to estimate population persistence – is applicable across rare and at-risk species for evaluating extinction risk with limited data and prioritizing management actions.</p></div></div><div id=\"ab0010\" class=\"abstract graphical\" lang=\"en\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2020.108489","usgsCitation":"Crawford, B., Olds, M., Maerz, J., and Moore, C.T., 2020, Estimating population persistence for at-risk species using citizen science data: Biological Conservation, v. 243, 108489, 13 p., https://doi.org/10.1016/j.biocon.2020.108489.","productDescription":"108489, 13 p.","ipdsId":"IP-111355","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":457518,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2020.108489","text":"Publisher Index Page"},{"id":395763,"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              -77.34374999999999,\n              39.027718840211605\n            ],\n            [\n              -79.98046875,\n              37.43997405227057\n            ],\n            [\n              -83.84765625,\n              33.797408767572485\n            ],\n            [\n              -87.5390625,\n              32.91648534731439\n            ],\n            [\n              -90,\n              31.42866311735861\n            ],\n            [\n              -89.82421875,\n              30.06909396443887\n            ],\n            [\n              -87.36328125,\n              30.221101852485987\n            ],\n            [\n              -84.375,\n              29.458731185355344\n            ],\n            [\n              -82.705078125,\n              26.745610382199022\n            ],\n            [\n              -80.771484375,\n              24.926294766395593\n            ],\n            [\n              -79.27734374999999,\n              25.562265014427492\n            ],\n            [\n              -79.89257812499999,\n              28.536274512989916\n            ],\n            [\n              -80.5078125,\n              30.826780904779774\n            ],\n            [\n              -78.75,\n              32.32427558887655\n            ],\n            [\n              -75.322265625,\n              35.17380831799959\n            ],\n            [\n              -75.41015624999999,\n              36.66841891894786\n            ],\n            [\n              -75.673828125,\n              37.85750715625203\n            ],\n            [\n              -76.46484375,\n              38.95940879245423\n            ],\n            [\n              -77.34374999999999,\n              39.027718840211605\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"243","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Crawford, B.A.","contributorId":275273,"corporation":false,"usgs":false,"family":"Crawford","given":"B.A.","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olds, M.","contributorId":275789,"corporation":false,"usgs":false,"family":"Olds","given":"M.","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":834287,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maerz, J.C.","contributorId":275274,"corporation":false,"usgs":false,"family":"Maerz","given":"J.C.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834288,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834289,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70217774,"text":"70217774 - 2020 - Niche partitioning among native ciscoes and nonnative Rainbow Smelt in Lake Superior","interactions":[],"lastModifiedDate":"2021-02-03T21:22:01.680529","indexId":"70217774","displayToPublicDate":"2020-03-03T06:56:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Niche partitioning among native ciscoes and nonnative Rainbow Smelt in Lake Superior","docAbstract":"<p><span>Several species of ciscoes&nbsp;</span><i>Coregonus</i><span>, subgenus&nbsp;</span><i>Leucichthys</i><span>&nbsp;that are native to the Laurentian Great Lakes are rare or extirpated. The restoration of&nbsp;</span><i>Coregonus</i><span>&nbsp;fishes is being actively pursued through stocking, and success may depend on the availability of unoccupied niche space. We described the spring–summer habitat occupancy and diets of three native cisco species (Bloater&nbsp;</span><i>Coregonus hoyi</i><span>, Cisco&nbsp;</span><i>C. artedi,</i><span>&nbsp;and Kiyi&nbsp;</span><i>C. Kiyi</i><span>) and invasive Rainbow Smelt&nbsp;</span><i>Osmerus mordax</i><span>&nbsp;in Lake Superior and measured niche overlap among these species for both small and large sizes. The potential habitat area was highest for Cisco and Kiyi, followed by Bloater and Rainbow Smelt. The probability of overlap in habitat occupation, as measured by bathymetric depth, fish capture depth, distance from shore, and fish capture water temperature was highest for small Rainbow Smelt and Cisco. Trophic overlap, as measured by stomach contents and stable isotopes, was highest between small Bloater and Cisco and between large Bloater and Kiyi. All of the species showed significant ontogenetic change in both habitat occupation and diet. The overall niche overlap in spring–summer habitat and diet was greatest between small Cisco and Rainbow Smelt and between large Bloater and Kiyi; however, differences in individual niche dimensions likely limit competition for both species pairs. Synthesizing the diet and habitat niche data revealed nuanced niches that allow these seemingly similar planktivorous species to coexist. Kiyi had the least niche overlap with other cisco species and Rainbow Smelt, so from an available niche perspective Kiyi would be a strong candidate for reintroduction into lakes from which they were extirpated.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10219","usgsCitation":"Rosinski, C.L., Vinson, M., and Yule, D.L., 2020, Niche partitioning among native ciscoes and nonnative Rainbow Smelt in Lake Superior: Transactions of the American Fisheries Society, v. 149, no. 2, p. 184-203, https://doi.org/10.1002/tafs.10219.","productDescription":"10 p.","startPage":"184","endPage":"203","ipdsId":"IP-113030","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":382868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Lake Superior","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.11035156249999,\n              49.009050809382046\n            ],\n            [\n              -89.1650390625,\n              48.574789910928864\n            ],\n            [\n              -89.4287109375,\n              48.019324184801185\n            ],\n            [\n              -90.703125,\n              47.724544549099676\n            ],\n            [\n              -92.1533203125,\n              46.6795944656402\n            ],\n            [\n              -90.8349609375,\n              46.9502622421856\n            ],\n            [\n              -90.8349609375,\n              46.558860303117164\n            ],\n            [\n              -90,\n              46.76996843356982\n            ],\n            [\n              -88.9892578125,\n              47.07012182383309\n            ],\n            [\n              -87.978515625,\n              47.338822694822\n            ],\n            [\n              -88.505859375,\n              46.76996843356982\n            ],\n            [\n              -88.11035156249999,\n              46.9502622421856\n            ],\n            [\n              -87.451171875,\n              46.558860303117164\n            ],\n            [\n              -86.3525390625,\n              46.46813299215554\n            ],\n            [\n              -85.4736328125,\n              46.70973594407157\n            ],\n            [\n              -85.0341796875,\n              46.70973594407157\n            ],\n            [\n              -84.8583984375,\n              46.31658418182218\n            ],\n            [\n              -84.3310546875,\n              46.49839225859763\n            ],\n            [\n              -84.5068359375,\n              47.07012182383309\n            ],\n            [\n              -84.90234375,\n              47.989921667414194\n            ],\n            [\n              -85.95703125,\n              48.10743118848039\n            ],\n            [\n              -86.3525390625,\n              48.719961222646276\n            ],\n            [\n              -88.11035156249999,\n              49.009050809382046\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"149","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-03-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosinski, Caroline Lynn 0000-0003-3635-2748","orcid":"https://orcid.org/0000-0003-3635-2748","contributorId":248618,"corporation":false,"usgs":true,"family":"Rosinski","given":"Caroline","email":"","middleInitial":"Lynn","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":809624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vinson, Mark R. 0000-0001-5256-9539 mvinson@usgs.gov","orcid":"https://orcid.org/0000-0001-5256-9539","contributorId":3800,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark","email":"mvinson@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":809625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yule, Daniel L. 0000-0002-0117-5115","orcid":"https://orcid.org/0000-0002-0117-5115","contributorId":248693,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":809626,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70227806,"text":"70227806 - 2020 - Use of multiple temperature logger models can alter conclusions","interactions":[],"lastModifiedDate":"2022-02-01T20:38:40.959549","indexId":"70227806","displayToPublicDate":"2020-03-01T15:37:57","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Use of multiple temperature logger models can alter conclusions","docAbstract":"<p>Remote temperature loggers are often used to measure water temperatures for ecological studies and by regulatory agencies to determine whether water quality standards are being maintained. Equipment specifications are often given a cursory review in the methods; however, the effect of temperature logger model is rarely addressed in the discussion. In a laboratory environment, we compared measurements from three models of temperature loggers at 5 to 40 °C to better understand the utility of these devices. Mean water temperatures recorded by logger models differed statistically even for those with similar accuracy specifications, but were still within manufacturer accuracy specifications. Maximum mean temperature difference between models was 0.4 °C which could have regulatory and ecological implications, such as when a 0.3 °C temperature change triggers a water quality violation or increases species mortality rates. Additionally, precision should be reported as the overall precision (including a consideration of significant digits) for combined model types which in our experiment was 0.7 °C, not the ≤0.4 °C for individual models. Our results affirm that analyzing data collected by different logger models can result in potentially erroneous conclusions when &lt;1 °C difference has regulatory compliance or ecological implications and that combining data from multiple logger models can reduce the overall precision of results.</p>","language":"English","publisher":"MDPI","doi":"10.3390/w12030668","usgsCitation":"Whittier, J.B., Westhoff, J.T., Paukert, C.P., and Rotman, R.M., 2020, Use of multiple temperature logger models can alter conclusions: Water, v. 12, no. 3, 9 p., https://doi.org/10.3390/w12030668.","productDescription":"9 p.","ipdsId":"IP-092924","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":457535,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12030668","text":"Publisher Index Page"},{"id":395243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-03-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Whittier, Joanna B.","contributorId":53151,"corporation":false,"usgs":false,"family":"Whittier","given":"Joanna","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":832344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Westhoff, Jacob T.","contributorId":58106,"corporation":false,"usgs":true,"family":"Westhoff","given":"Jacob","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":832345,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paukert, Craig P. 0000-0002-9369-8545 cpaukert@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":879,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","email":"cpaukert@usgs.gov","middleInitial":"P.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rotman, Robin M.","contributorId":272858,"corporation":false,"usgs":false,"family":"Rotman","given":"Robin","email":"","middleInitial":"M.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":832347,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70204123,"text":"70204123 - 2020 - Quality control and assessment of interpreter consistency of annual land cover reference data in an operational national monitoring program","interactions":[],"lastModifiedDate":"2024-05-17T15:49:38.223294","indexId":"70204123","displayToPublicDate":"2020-03-01T11:07:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Quality control and assessment of interpreter consistency of annual land cover reference data in an operational national monitoring program","docAbstract":"The U.S. Geological Survey Land Change Monitoring, Assessment and Projection (USGS LCMAP) initiative is working toward a comprehensive capability to characterize land cover and land cover change using dense Landsat time series data. A suite of products including annual land cover maps and annual land cover change maps will be produced using the Landsat 4-8 data record. LCMAP products will initially be created for the conterminous United States (CONUS) and then extended to include Alaska and Hawaii. A critical component of LCMAP is the collection of reference data using the TimeSync tool, a web-based interface for manually interpreting and recording land cover from Landsat data supplemented with fine resolution imagery and other ancillary data. These reference data will be used for area estimation and validation of the LCMAP annual land cover products. Nearly 12,000 LCMAP reference sample pixels have been interpreted and a simple random subsample of these pixels has been interpreted independently by a second analyst (hereafter referred to as \"duplicate interpretations\"). The annual land cover reference class labels for the 1984-2016 monitoring period obtained from these duplicate interpretations are used to address the following questions: 1) How consistent are the reference class labels among interpreters overall and per class?  2) Does consistency vary by geographic region?  3) Does consistency vary as interpreters gain experience over time; and 4) Does interpreter consistency change with improving availability and quality of imagery from 1984 to 2016?  Overall agreement between interpreters was 88%. Class-specific agreement ranged from 46% for Disturbed to 94% for Water, with more prevalent classes (Tree Cover, Grass/Shrub and Cropland) generally having greater agreement than rare classes (Developed, Barren and Wetland). Agreement between interpreters remained approximately the same over the 12-month period during which these interpretations were completed. Increasing availability of Landsat and Google Earth fine resolution data over the 1984 to 2016 monitoring period coincided with increased interpreter consistency for the post-2000 data record. The reference data interpretation and quality assurance protocols implemented for LCMAP demonstrate the technical and practical feasibility of using the Landsat archive and intensive human interpretation to produce national, annual reference land cover data over a 30 year period. Protocols to quantify and enhance interpreter consistency are critical elements to document and ensure quality of these reference data.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2019.111261","usgsCitation":"Pengra, B., Stehman, S.V., Horton, J., Dockter, D., Schroeder, T.A., Yang, Z., Cohen, W.B., Healey, S.P., and Loveland, T., 2020, Quality control and assessment of interpreter consistency of annual land cover reference data in an operational national monitoring program: Remote Sensing of Environment, v. 238, 111261, 10 p., https://doi.org/10.1016/j.rse.2019.111261.","productDescription":"111261, 10 p.","ipdsId":"IP-101422","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":457550,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2019.111261","text":"Publisher Index Page"},{"id":437077,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QA5Q25","text":"USGS data release","linkHelpText":"LCMAP CONUS Intensification Reference Data Product 1984&amp;ndash;2019 land cover, land use and change process attributes"},{"id":414788,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"238","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pengra, Bruce 0000-0003-2497-8284 bpengra@usgs.gov","orcid":"https://orcid.org/0000-0003-2497-8284","contributorId":5132,"corporation":false,"usgs":true,"family":"Pengra","given":"Bruce","email":"bpengra@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) 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Zhiqiang","contributorId":189584,"corporation":false,"usgs":false,"family":"Yang","given":"Zhiqiang","email":"","affiliations":[],"preferred":false,"id":765627,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cohen, Warren B 0000-0003-3144-9532","orcid":"https://orcid.org/0000-0003-3144-9532","contributorId":216815,"corporation":false,"usgs":false,"family":"Cohen","given":"Warren","email":"","middleInitial":"B","affiliations":[{"id":39525,"text":"USDA Forest Service, Pacific Northwest Research Station, 3200 SW Jefferson Way, Corvallis, OR 97331","active":true,"usgs":false}],"preferred":false,"id":765628,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Healey, Sean P.","contributorId":216816,"corporation":false,"usgs":false,"family":"Healey","given":"Sean","email":"","middleInitial":"P.","affiliations":[{"id":39526,"text":"USDA Forest Service, Rocky Mountain Research Station, 507 25th Street, Ogden, UT 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In this analysis, we utilize a conventional risk-modeling framework to develop and apply a new methodology for assessing the supply risk to the U.S. manufacturing sector. Specifically, supply risk is defined as the confluence of three factors: the likelihood of a foreign supply disruption, the dependency of U.S. manufacturers on foreign supplies, and the ability of U.S. manufacturers to withstand a supply disruption. The methodology is applied to 52 commodities for the decade spanning 2007-2016. The results indicate that a subset of 23 commodities, including cobalt, niobium, rare earth elements, and tungsten, pose the greatest supply risk. Importantly, this supply risk is dynamic, shifting with changes in global market conditions.","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.aay8647","usgsCitation":"Nassar, N., Brainard, J., Gulley, A.L., Manley, R., Matos, G., Lederer, G.W., Bird, L., Pineault, D., Alonso, E., Gambogi, J., and Fortier, S.M., 2020, Evaluating the mineral commodity supply risk of the U.S. manufacturing sector: Science Advances, v. 6, no. 8, eaay8647, 12 p., https://doi.org/10.1126/sciadv.aay8647.","productDescription":"eaay8647, 12 p.","ipdsId":"IP-109911","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":457638,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1126/sciadv.aay8647","text":"External 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0000-0002-3285-3070 gmatos@usgs.gov","orcid":"https://orcid.org/0000-0002-3285-3070","contributorId":195499,"corporation":false,"usgs":true,"family":"Matos","given":"Grecia R.","email":"gmatos@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":783822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lederer, Graham W. 0000-0002-9505-9923","orcid":"https://orcid.org/0000-0002-9505-9923","contributorId":202407,"corporation":false,"usgs":true,"family":"Lederer","given":"Graham","email":"","middleInitial":"W.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":783823,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bird, Laurence 0000-0002-6034-9533","orcid":"https://orcid.org/0000-0002-6034-9533","contributorId":223013,"corporation":false,"usgs":true,"family":"Bird","given":"Laurence","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":783824,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pineault, David G.","contributorId":223014,"corporation":false,"usgs":false,"family":"Pineault","given":"David G.","affiliations":[{"id":40641,"text":"U.S. Defense Logistics Agency","active":true,"usgs":false}],"preferred":false,"id":783825,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Alonso, Elisa 0000-0002-0090-8284","orcid":"https://orcid.org/0000-0002-0090-8284","contributorId":223015,"corporation":false,"usgs":true,"family":"Alonso","given":"Elisa","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":783826,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gambogi, Joseph 0000-0002-5719-2280 jgambogi@usgs.gov","orcid":"https://orcid.org/0000-0002-5719-2280","contributorId":4424,"corporation":false,"usgs":true,"family":"Gambogi","given":"Joseph","email":"jgambogi@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":783827,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fortier, Steven M. 0000-0001-8123-5749","orcid":"https://orcid.org/0000-0001-8123-5749","contributorId":202406,"corporation":false,"usgs":true,"family":"Fortier","given":"Steven","email":"","middleInitial":"M.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":783828,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70209068,"text":"70209068 - 2020 - Ichthyophonus sp. Infection in Opaleye (Girella nigricans)","interactions":[],"lastModifiedDate":"2020-03-13T06:56:46","indexId":"70209068","displayToPublicDate":"2020-02-21T06:55:18","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3687,"text":"Veterinary Pathology","active":true,"publicationSubtype":{"id":10}},"title":"Ichthyophonus sp. Infection in Opaleye (Girella nigricans)","docAbstract":"Over a 3-year-period, 17 wild-caught opaleye (Girella nigricans) housed in a public display aquarium were found dead without premonitory signs. Grossly, 4 animals had pinpoint brown or black foci on coelomic adipose tissue. Histologically, liver, spleen, heart, and posterior kidney had mesomycetozoan granulomas in all cases; other organs were less commonly infected. Four opaleye had goiter; additional substantial lesions were not identified. Granulomas surrounded melanized debris, leukocytes, and mesomycetozoa represented by folded membranes (collapsed schizont walls), intact schizonts (50- to >200 µm in diameter with a multilaminate membrane), plasmodia (budding from schizonts or free in tissue), or rarely germinal tubes (budding from schizonts). Ichthyophonus was grown from fresh tissues in tissue explant broth cultures of the heart, liver, and/or spleen. Polymerase chain reaction using 18S ribosomal DNA primers amplified a 1730-bp region, and the DNA sequence was most similar to Ichthyophonus hoferi, which is often associated with freshwater aquaculture fish.","language":"English","publisher":"SAGE Journals","doi":"10.1177/0300985819900015","usgsCitation":"LaDouceur, E., St. Leger, J., Mena, A., MacKenzie, A., Gregg, J., Purcell, M.K., Batts, W.N., and Hershberger, P., 2020, Ichthyophonus sp. Infection in Opaleye (Girella nigricans): Veterinary Pathology, v. 57, no. 2, p. 316-320, https://doi.org/10.1177/0300985819900015.","productDescription":"5 p.","startPage":"316","endPage":"320","ipdsId":"IP-111483","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":457648,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/0300985819900015","text":"Publisher Index Page"},{"id":373228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"LaDouceur, Elise E. B","contributorId":223265,"corporation":false,"usgs":false,"family":"LaDouceur","given":"Elise E. B","affiliations":[{"id":40698,"text":"Joint Pathology Center, Silver Spring, MD","active":true,"usgs":false}],"preferred":false,"id":784703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"St. Leger, Judy","contributorId":223266,"corporation":false,"usgs":false,"family":"St. Leger","given":"Judy","email":"","affiliations":[{"id":25346,"text":"Cornell University, Ithaca, NY","active":true,"usgs":false}],"preferred":false,"id":784704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mena, Alexandria","contributorId":223267,"corporation":false,"usgs":false,"family":"Mena","given":"Alexandria","email":"","affiliations":[{"id":40699,"text":"SeaWorld, San Diego, CA","active":true,"usgs":false}],"preferred":false,"id":784705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"MacKenzie, Ashley 0000-0002-7402-7877 amackenzie@usgs.gov","orcid":"https://orcid.org/0000-0002-7402-7877","contributorId":150817,"corporation":false,"usgs":true,"family":"MacKenzie","given":"Ashley","email":"amackenzie@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784706,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gregg, Jacob jgregg@usgs.gov","contributorId":140132,"corporation":false,"usgs":true,"family":"Gregg","given":"Jacob","email":"jgregg@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784707,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784708,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Batts, William N. 0000-0002-6469-9004 bbatts@usgs.gov","orcid":"https://orcid.org/0000-0002-6469-9004","contributorId":3815,"corporation":false,"usgs":true,"family":"Batts","given":"William","email":"bbatts@usgs.gov","middleInitial":"N.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784709,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hershberger, Paul 0000-0002-2261-7760 phershberger@usgs.gov","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":150816,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","email":"phershberger@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784710,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70216756,"text":"70216756 - 2020 - Timescales of magmatic processes in post-collisional potassic lavas, northwestern Tibet","interactions":[],"lastModifiedDate":"2020-12-04T16:00:33.723385","indexId":"70216756","displayToPublicDate":"2020-02-12T09:55:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2588,"text":"LITHOS","active":true,"publicationSubtype":{"id":10}},"title":"Timescales of magmatic processes in post-collisional potassic lavas, northwestern Tibet","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0055\">Post-collisional potassic volcanic rocks on the Tibetan Plateau are widespread, but geologically young (&lt;375&nbsp;ka) volcanism suitable for<span>&nbsp;</span><sup>238</sup>U-<sup>230</sup>Th geochronology is rare on the plateau. The geologically young Ashikule volcanic field from northern Tibet offers an excellent opportunity for studying high-resolution timescales of magmatism in continental collision zones. Here we report U-Th crystallization ages of zircons from Ashishan volcano and Wulukeshan volcano within the Ashikule volcanic field. In this study, we have identified 3 pulses of zircon crystallization at circa 70&nbsp;ka, 105&nbsp;ka, and 290&nbsp;ka for Ashishan volcanic rocks and 1 pulse of zircon crystallization at circa 115&nbsp;ka for Wulukeshan. Comparison of high-resolution zircon crystallization ages of 70&nbsp;ka and 105&nbsp;ka with respective eruption ages indicate that the zircon crystal residence time for the Ashishan volcano is short (&lt;5 kyr). The presence of 290-ka zircon in a different Ashishan lava flow suggests the 270-ka volcanic pulse previously reported for other volcanoes in Ashikule volcanic field also occurred at Ashishan. The zircon crystallization age of ~115&nbsp;ka for Wulukeshan volcano suggests that Wulukeshan volcano erupted later than previously inferred. Similar zircon age spectrums of ~105–115&nbsp;ka for Ashishan and Wulukeshan volcanoes suggest a common interconnected subsurface magma reservoir for these two young volcanoes during Pleistocene time. Our new high-resolution U-Th zircon age data reveal that post-collisional potassic magmas below northern Tibet erupted soon after their formation (&lt;5 kyr), in spite of their passage through thick continental crust. The high abundance (~60%) of geologically old (&gt;375&nbsp;ka) zircons demands for crystal-scale isotope studies of the widespread post-collisional lavas in continental collision zones, as the complexities cannot be resolved by bulk analysis methods alone.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.lithos.2020.105418","usgsCitation":"Zou, H., Vazquez, J.A., and Fan, Q., 2020, Timescales of magmatic processes in post-collisional potassic lavas, northwestern Tibet: LITHOS, v. 358-359, 105418, 8 p., https://doi.org/10.1016/j.lithos.2020.105418.","productDescription":"105418, 8 p.","ipdsId":"IP-111941","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":380984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Tibet","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              78.57421875,\n              27.059125784374068\n            ],\n            [\n              93.42773437499999,\n              27.059125784374068\n            ],\n            [\n              93.42773437499999,\n              35.53222622770337\n            ],\n            [\n              78.57421875,\n              35.53222622770337\n            ],\n            [\n              78.57421875,\n              27.059125784374068\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"358-359","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zou, Haibo 0000-0001-5825-2428","orcid":"https://orcid.org/0000-0001-5825-2428","contributorId":245380,"corporation":false,"usgs":false,"family":"Zou","given":"Haibo","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":806089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":806090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fan, Qicheng","contributorId":245381,"corporation":false,"usgs":false,"family":"Fan","given":"Qicheng","email":"","affiliations":[{"id":49174,"text":"China Earthquake Administration","active":true,"usgs":false}],"preferred":false,"id":806091,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70208510,"text":"70208510 - 2020 - Spatial and temporal trends in Potomac River fish abundance linked to species traits","interactions":[],"lastModifiedDate":"2020-02-14T06:24:45","indexId":"70208510","displayToPublicDate":"2020-02-12T08:57:14","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":"Spatial and temporal trends in Potomac River fish abundance linked to species traits","docAbstract":"Analysis of species abundance trends can inform an understanding of the underlying mechanisms. We evaluated spatial and temporal trends in fish species abundance in the non-tidal Potomac River (USA) from a dataset comprising 2841 seine-hauls with > 250,000 individual fish records across 10 sites and 43 years (1975-2017). The dataset contained 47 species from 7 taxonomic families, with species richness and abundance dominated by leuciscids, centrarchids, and percids (85% and 95% of the total dataset, respectively). We used linear modeling and bootstrapping techniques to estimate spatial and temporal trends in abundance (CPUE) for 38 species, excluding the rarest taxa (< 30 individuals). Spatial trends in abundance were detected for 22 species (58%), of which 15 were more abundant downstream than upstream and 7 were more abundant upstream than downstream. Temporal trends in abundance were detected for 25 species (66%), of which 15 increased over time and 10 decreased over time. Spatial trends were associated with reproductive life history strategies: egg-attachers and viviparous fishes generally increased in a downstream direction, whereas species with other reproductive modes and relatively short spawning durations (< ~2 months) showed the opposite spatial trend. Temporal trends were associated with reproductive guilds and range area (a surrogate for environmental tolerance): egg-attachers and nest-associates generally increased in abundance over time, whereas broadcast spawners, clean-gravel spawners, and nest-guarders with relatively small range areas (< ~ 1.2 million km2) tended to decrease over time. This study provides an analysis of one of the largest systematic collections of freshwater fishes to our knowledge and provides a framework to evaluate mechanisms underlying observed trends.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3026","usgsCitation":"Hitt, N.P., Rogers, K., Kelly, Z.A., Henesy, J., and Mullican, J.E., 2020, Spatial and temporal trends in Potomac River fish abundance linked to species traits: Ecosphere, v. 11, no. 2, e03026, 17 p., https://doi.org/10.1002/ecs2.3026.","productDescription":"e03026, 17 p.","ipdsId":"IP-107694","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":457742,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3026","text":"Publisher Index Page"},{"id":372312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Potomac River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.35498046875,\n              38.08701320402273\n            ],\n            [\n              -76.65710449218749,\n              38.25112269630296\n            ],\n            [\n              -76.8768310546875,\n              38.315801006824984\n            ],\n            [\n              -76.9866943359375,\n              38.46649284538942\n            ],\n            [\n              -77.0416259765625,\n              38.50519140240356\n            ],\n            [\n              -77.156982421875,\n              38.40194908237822\n            ],\n            [\n              -77.222900390625,\n              38.46219172306828\n            ],\n            [\n              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0000-0003-4684-2345","orcid":"https://orcid.org/0000-0003-4684-2345","contributorId":222459,"corporation":false,"usgs":true,"family":"Kelly","given":"Zachary","email":"","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":782202,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Henesy, Josh","contributorId":222460,"corporation":false,"usgs":false,"family":"Henesy","given":"Josh","email":"","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":782203,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mullican, John E.","contributorId":203245,"corporation":false,"usgs":false,"family":"Mullican","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":782204,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70231217,"text":"70231217 - 2020 - Anthropogenic pollutants and biomarkers for the identification of 2011 Tohoku-oki tsunami deposits (Japan)","interactions":[],"lastModifiedDate":"2022-05-03T11:45:22.148529","indexId":"70231217","displayToPublicDate":"2020-02-12T06:42:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Anthropogenic pollutants and biomarkers for the identification of 2011 Tohoku-oki tsunami deposits (Japan)","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0060\">Organic geochemistry is commonly used in environmental studies. In tsunami research, however, its applications are in their infancy and it is still rarely used. We present results for two types of organic geochemical markers, biomarkers and anthropogenic markers, present in deposits left by 2011 Tohoku-oki tsunami on the Sendai Plain, Japan. As the tsunami inundated the coastal lowland up to 4.85&nbsp;km inland, sediments from various sources were eroded, transported and deposited. This led to the distribution of biomarkers from different sources across the Sendai Plain creating a unique geochemical signature in the tsunami deposits. The tsunami also caused destruction along the Sendai coastline, leading to the release of large quantities of environmental pollutants (e.g., fossil fuels, tarmac, pesticides, plastics, etc.) that were distributed across the inundated area. These anthropogenic markers, represented by three main compound groups (polycyclic aromatic hydrocarbons, pesticides, and halogenated compounds), were preserved in tsunami deposits (at least until 2013, prior to land clearing). Their concentrations differed significantly from the pre- and post-tsunami background contamination levels. Organic proxy concentrations can differ for sand and mud deposits due to various factors (e.g., preservation, dilution, microbial alteration). However, it can be concluded that anthropogenic markers and biomarkers have the potential to be a valuable proxy for future studies of recent tsunami deposits because of their high source specificity and relatively good preservation potential providing information about sediment sources and transport pathways (e.g., marine source, evidence of backwash).</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2020.106117","usgsCitation":"Bellanova, P., Frenken, M., Reicherter, K., Jaffe, B.E., Szczucinski, W., and Schwarzbauer, J., 2020, Anthropogenic pollutants and biomarkers for the identification of 2011 Tohoku-oki tsunami deposits (Japan): Marine Geology, v. 422, 106117, 15 p., https://doi.org/10.1016/j.margeo.2020.106117.","productDescription":"106117, 15 p.","ipdsId":"IP-110771","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":400021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan","otherGeospatial":"Sendai","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              140.5810546875,\n              37.50972584293751\n            ],\n            [\n              141.591796875,\n              37.50972584293751\n            ],\n            [\n              141.591796875,\n              38.89103282648846\n            ],\n            [\n              140.5810546875,\n              38.89103282648846\n            ],\n            [\n              140.5810546875,\n              37.50972584293751\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"422","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bellanova, Piero","contributorId":213414,"corporation":false,"usgs":false,"family":"Bellanova","given":"Piero","email":"","affiliations":[{"id":38752,"text":"1 Institute for Geology and Geochemistry of Petroleum and Coal, RWTH Aachen University Lochnerstrasse 4-20, 52056, Aachen, Germany,","active":true,"usgs":false}],"preferred":false,"id":842056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frenken, Mike","contributorId":213430,"corporation":false,"usgs":false,"family":"Frenken","given":"Mike","email":"","affiliations":[],"preferred":false,"id":842057,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reicherter, Klaus","contributorId":213418,"corporation":false,"usgs":false,"family":"Reicherter","given":"Klaus","email":"","affiliations":[{"id":38754,"text":"Lehr- und Forschungsgebiet Neotektonik und Georisiken, RWTH Aachen University Lochnerstrasse 4-20, 52056, Aachen, Germany","active":true,"usgs":false}],"preferred":false,"id":842058,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":842059,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szczucinski, Witold","contributorId":76572,"corporation":false,"usgs":false,"family":"Szczucinski","given":"Witold","email":"","affiliations":[],"preferred":false,"id":842060,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwarzbauer, Jan","contributorId":291328,"corporation":false,"usgs":false,"family":"Schwarzbauer","given":"Jan","affiliations":[{"id":62691,"text":"Aachen University","active":true,"usgs":false}],"preferred":false,"id":842061,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70228771,"text":"70228771 - 2020 - Identification of factors affecting predation risk for juvenile turtles using 3D printed models","interactions":[],"lastModifiedDate":"2022-02-18T13:08:17.024241","indexId":"70228771","displayToPublicDate":"2020-02-11T07:01:02","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5762,"text":"Animals","active":true,"publicationSubtype":{"id":10}},"title":"Identification of factors affecting predation risk for juvenile turtles using 3D printed models","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">Although it is widely accepted that juvenile turtles experience high levels of predation, such events are rarely observed, providing limited evidence regarding predator identities and how juvenile habitat selection and availability of sensory cues to predators affects predation risk. We placed three-dimensional printed models resembling juvenile box turtles (<span class=\"html-italic\">Terrapene carolina</span>) across habitats commonly utilized by the species at three sites within their geographical range and monitored models with motion-triggered cameras. To explore how the presence or absence of visual and olfactory cues affected predator interactions with models, we employed a factorial design where models were either exposed or concealed and either did or did not have juvenile box turtle scent applied on them. Predators interacted with 18% of models during field trials. Nearly all interactions were by mesopredators (57%) and rodents (37%). Mesopredators were more likely to attack models than rodents; most (76%) attacks occurred by raccoons (<span class=\"html-italic\">Procyon lotor</span>). Interactions by mesopredators were more likely to occur in wetlands than edges, and greater in edges than grasslands. Mesopredators were less likely to interact with models as surrounding vegetation height increased. Rodents were more likely to interact with models that were closer to woody structure and interacted with exposed models more than concealed ones, but model exposure had no effect on interactions by mesopredators. Scent treatment appeared to have no influence on interactions by either predator group. Our results suggest raccoons can pose high predation risk for juvenile turtles (although rodents could also be important predators) and habitat features at multiple spatial scales affect predator-specific predation risk. Factors affecting predation risk for juveniles are important to consider in management actions such as habitat alteration, translocation, or predator control.<span>&nbsp;</span></div>","language":"English","publisher":"MDPI","doi":"10.3390/ani10020275","usgsCitation":"Tetzlaff, S., Estrada, A., DeGregorio, B.A., and Sperry, J.H., 2020, Identification of factors affecting predation risk for juvenile turtles using 3D printed models: Animals, v. 10, no. 2, 275, 16 p., https://doi.org/10.3390/ani10020275.","productDescription":"275, 16 p.","ipdsId":"IP-114047","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":457770,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ani10020275","text":"Publisher Index Page"},{"id":396162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Michigan","otherGeospatial":"Fort Custer Training Center, Nettie Hart Memorial Woods, Vermilion River Observatory","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -85.43792724609375,\n              42.261049162113856\n            ],\n            [\n              -85.2490997314453,\n              42.261049162113856\n            ],\n            [\n              -85.2490997314453,\n              42.384922757848045\n            ],\n            [\n              -85.43792724609375,\n              42.384922757848045\n            ],\n            [\n              -85.43792724609375,\n              42.261049162113856\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.58506774902344,\n              39.985538414809746\n            ],\n            [\n              -87.52944946289062,\n              39.985538414809746\n            ],\n            [\n              -87.52944946289062,\n              40.047591462658794\n            ],\n            [\n              -87.58506774902344,\n              40.047591462658794\n            ],\n            [\n              -87.58506774902344,\n              39.985538414809746\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.077392578125,\n              39.9897471840457\n            ],\n            [\n              -87.77801513671875,\n              39.9897471840457\n            ],\n            [\n              -87.77801513671875,\n              40.19356109815612\n            ],\n            [\n              -88.077392578125,\n              40.19356109815612\n            ],\n            [\n              -88.077392578125,\n              39.9897471840457\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-02-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Tetzlaff, S.J.","contributorId":243211,"corporation":false,"usgs":false,"family":"Tetzlaff","given":"S.J.","email":"","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":835379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Estrada, A.","contributorId":279698,"corporation":false,"usgs":false,"family":"Estrada","given":"A.","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":835380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":835381,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sperry, J. H.","contributorId":279699,"corporation":false,"usgs":false,"family":"Sperry","given":"J.","email":"","middleInitial":"H.","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":835382,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227005,"text":"70227005 - 2020 - Inexpensive, underwater filming of rare fishes in high definition","interactions":[],"lastModifiedDate":"2021-12-27T14:30:12.954468","indexId":"70227005","displayToPublicDate":"2020-02-10T08:26:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5686,"text":"Fisheries Magazine","active":true,"publicationSubtype":{"id":10}},"title":"Inexpensive, underwater filming of rare fishes in high definition","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Generating public interest in fish and their biology is often challenging. Many aquatic species are cryptic and largely invisible to the public. Therefore, increasing public awareness of cryptic fishes and elevating their visibility to broad audiences requires innovation. Inexpensive technological advancements now provide fisheries biologists, managers, and researchers with means never before possible for documenting fish in their natural habitat via underwater videography. We investigated cost efficient and simple methods for capturing and creating high quality, high definition, and informative underwater videos that could be used by people with little or no previous experience in videography. We tested 1) a variety of filming equipment including cameras and camera recording settings, lenses, batteries, and memory cards; 2) active and passive camera deployment techniques; and 3) a variety of free and paid postproduction software and compared them for ease of use, expense, and quality of output. Highest quality footage, i.e., highest resolution, clearest, and most stable, was obtained using a GoPro action camera deployed underwater in a stationary position mounted to a metal base plate using a combination of stock and macro lenses, and filming in 4K resolution at 30 frames per second. Final production videos were created using Adobe Premiere Pro.</p></div></div>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/fsh.10391","usgsCitation":"Bonar, S.A., and Ulrich, T., 2020, Inexpensive, underwater filming of rare fishes in high definition: Fisheries Magazine, v. 45, no. 3, p. 121-130, https://doi.org/10.1002/fsh.10391.","productDescription":"10 p.","startPage":"121","endPage":"130","ipdsId":"IP-106514","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":393410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":829152,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ulrich, Taylor","contributorId":270364,"corporation":false,"usgs":false,"family":"Ulrich","given":"Taylor","email":"","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":829153,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70224284,"text":"70224284 - 2020 - Flea sharing among sympatric rodent hosts: implications for potential plague effects on a threatened sciurid","interactions":[],"lastModifiedDate":"2021-09-20T13:02:13.220326","indexId":"70224284","displayToPublicDate":"2020-02-07T08:00:41","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":"Flea sharing among sympatric rodent hosts: implications for potential plague effects on a threatened sciurid","docAbstract":"<div class=\"article-section__content en main\"><p>For vector-borne diseases, the abundance and competency of different vector species and their host preferences will impact the transfer of pathogens among hosts. Sylvatic plague is a lethal disease caused by the primarily flea-borne bacterium<span>&nbsp;</span><i>Yersinia pestis</i>. Sylvatic plague was introduced into the western United States in the early 1900s and impacts many species of rodents. Plague may be suppressing populations of the threatened northern Idaho ground squirrel (<i>Urocitellus brunneus</i>) if a competent flea community is allowing plague to be maintained within the few extant sites that support this rare ground squirrel. We collected fleas from four species of sympatric rodents in central Idaho: northern Idaho ground squirrels, Columbian ground squirrels (<i>Urocitellus columbianus</i>), yellow-pine chipmunks (<i>Tamias amoenus</i>), and deer mice (<i>Peromyscus maniculatus</i>). We evaluated which flea species were present and whether fleas were shared among the rodent community. We documented seven species of fleas among 3356 fleas collected from the four host species of rodents, and all seven species of fleas are known vectors of plague. Three of the seven flea species were detected on all four rodent species, demonstrating potential for spillover of plague (bridge vectors) in the rodent community. We used generalized linear mixed models to evaluate which abiotic and biotic factors influence flea abundance (total number of fleas, regardless of flea species, on each individual host of the four rodent host species). Factors that impacted flea abundance varied among the four host species, but flea abundance: (1) changed over summer depending on host species, (2) was greater on males, and (3) was impacted by summer and winter precipitation depending on host species. Our results suggest this diverse flea community has the capacity to transfer<span>&nbsp;</span><i>Y. pestis</i><span>&nbsp;</span>among populations of the four rodents if<span>&nbsp;</span><i>Y. pestis</i><span>&nbsp;</span>is present. Furthermore, the disease may be more likely to persist in some locations than others, those that have higher flea abundances, more sympatric hosts, or optimal conditions for fleas, and such high-risk sites can be identified based on their abiotic and biotic factors.</p></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3033","usgsCitation":"Goldberg, A., Conway, C.J., and Biggins, D.E., 2020, Flea sharing among sympatric rodent hosts: implications for potential plague effects on a threatened sciurid: Ecosphere, v. 11, no. 2, e03033, 19 p., https://doi.org/10.1002/ecs2.3033.","productDescription":"e03033, 19 p.","ipdsId":"IP-105632","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":457805,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3033","text":"Publisher Index Page"},{"id":389476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.619873046875,\n              44.74673324024678\n            ],\n            [\n              -115.103759765625,\n              44.74673324024678\n            ],\n            [\n              -115.103759765625,\n              45.336701909968134\n            ],\n            [\n              -116.619873046875,\n              45.336701909968134\n            ],\n            [\n              -116.619873046875,\n              44.74673324024678\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Goldberg, Amanda R.","contributorId":265814,"corporation":false,"usgs":false,"family":"Goldberg","given":"Amanda R.","affiliations":[{"id":54806,"text":"iu","active":true,"usgs":false}],"preferred":false,"id":823450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":823451,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biggins, Dean E. 0000-0003-2078-671X bigginsd@usgs.gov","orcid":"https://orcid.org/0000-0003-2078-671X","contributorId":2522,"corporation":false,"usgs":true,"family":"Biggins","given":"Dean","email":"bigginsd@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":823452,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70209709,"text":"70209709 - 2020 - A weight-of-evidence approach for defining thermal sensitivity in a federally endangered species","interactions":[],"lastModifiedDate":"2020-04-22T14:47:54.906248","indexId":"70209709","displayToPublicDate":"2020-02-06T09:35:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"A weight-of-evidence approach for defining thermal sensitivity in a federally endangered species","docAbstract":"<p>1. Managing for threatened and endangered species under changing environmental conditions is a challenge faced by resource managers worldwide. Lack of basic knowledge of the biology and habitat requirements of these species can contribute to this difficulty, but is confounded by the limitations of working with rare (i.e. few individuals) species or unrefined methods for evaluating stress. </p><p>2. A weight of evidence approach was used to evaluate the thermal biology of the federally endangered dwarf wedgemussel (<i>Alasmidonta heterodon</i>), utilizing cumulative results from multiple experimental assessments, co-occurring species, and their host fish to begin defining thermal limits and optimal conditions for the species. </p><p>3. Results suggest that dwarf wedgemussel and its host fish are thermally sensitive species compared to other Atlantic-slope mussels, with lower critical thermal maximum and selection of reduced temperatures during choice experiments. </p><p>4. Physiological studies resulted in lack of statistical significance primarily due to low power which was a function of sample size, one unavoidable problem when studying rare species. Given these limitations, thermal choice and CTM may be more useful endpoints than physiological processes such as clearance and respiration rates when dealing with sample size limitations. </p><p>5. These results suggest that management strategies that avoid exposing dwarf wedgemussel and its thermally sensitive host fish to extreme temperatures could be important for species conservation.</p>","language":"English","publisher":"Wiley","doi":"10.1002/aqc.3287","collaboration":"","usgsCitation":"Galbraith, H., Blakeslee, C.J., Spooner, D.E., and Lellis, W.A., 2020, A weight-of-evidence approach for defining thermal sensitivity in a federally endangered species: Aquatic Conservation: Marine and Freshwater Ecosystems, v. 30, no. 3, p. 540-553, https://doi.org/10.1002/aqc.3287.","productDescription":"14 p.","startPage":"540","endPage":"553","ipdsId":"IP-098162","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":437123,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9T7YVOW","text":"USGS data release","linkHelpText":"Laboratory studies on the thermal biology of freshwater mussels and their host fish species"},{"id":374188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, Pennsylvania","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -79.749755859375,\n              38.66835610151506\n            ],\n            [\n              -73.95996093749999,\n              38.66835610151506\n            ],\n            [\n              -73.95996093749999,\n              41.78769700539063\n            ],\n            [\n              -79.749755859375,\n              41.78769700539063\n            ],\n            [\n              -79.749755859375,\n              38.66835610151506\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"30","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Galbraith, Heather 0000-0003-3704-3517","orcid":"https://orcid.org/0000-0003-3704-3517","contributorId":207512,"corporation":false,"usgs":true,"family":"Galbraith","given":"Heather","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":787622,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blakeslee, Carrie J. 0000-0002-0801-5325 cblakeslee@usgs.gov","orcid":"https://orcid.org/0000-0002-0801-5325","contributorId":5462,"corporation":false,"usgs":true,"family":"Blakeslee","given":"Carrie","email":"cblakeslee@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":787623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spooner, Daniel E. 0000-0002-5408-4364 dspooner@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-4364","contributorId":4603,"corporation":false,"usgs":true,"family":"Spooner","given":"Daniel","email":"dspooner@usgs.gov","middleInitial":"E.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":787624,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lellis, William A. 0000-0001-7806-2904 wlellis@usgs.gov","orcid":"https://orcid.org/0000-0001-7806-2904","contributorId":2369,"corporation":false,"usgs":true,"family":"Lellis","given":"William","email":"wlellis@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":787625,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70228637,"text":"70228637 - 2020 - Mapping habitat suitability at range-wide scales: Spatially explicit distribution models to inform conservation and research for marsh birds","interactions":[],"lastModifiedDate":"2022-02-16T21:04:33.98395","indexId":"70228637","displayToPublicDate":"2020-02-03T14:52:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Mapping habitat suitability at range-wide scales: Spatially explicit distribution models to inform conservation and research for marsh birds","docAbstract":"Habitat Loss is a primary cause of species decline, and predicting the distribution of quality habitats across broad scales is needed for conservation of rare species. Secretive marsh birds are a group of emergent-wetland specialists that include multiple threatened and endangered species whose populations have been impacted by wetland loss and modification. Habitat suitability for marsh birds is poorly mapped, and predictions of habitat quality over broad scales are primarily generated via expert judgment. We developed data-driven models to predict fine-resolution habitat quality for 13 marsh bird species across their ranges within the U.S. We demonstrate how these models are useful for conservation by quantifying range contraction, assessing the usefulness of existing protected areas, and assessing the vulnerability of habitats to global change for rare species. These tools provide a quantitative foundation for broad-scale conservation, research, and monitoring efforts, and a starting point for adaptive conservation of marsh bird breeding habitat over broad spatial extents.","language":"English","publisher":"Wiley","doi":"10.1111/csp2.178","usgsCitation":"Stevens, B.S., and Conway, C.J., 2020, Mapping habitat suitability at range-wide scales: Spatially explicit distribution models to inform conservation and research for marsh birds: Conservation Science and Practice, v. 2, no. 4, e178, 8 p., https://doi.org/10.1111/csp2.178.","productDescription":"e178, 8 p.","ipdsId":"IP-113280","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":457877,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.178","text":"Publisher Index Page"},{"id":396039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Stevens, Bryan S.","contributorId":171809,"corporation":false,"usgs":false,"family":"Stevens","given":"Bryan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":835048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834900,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70208263,"text":"70208263 - 2020 - Throughfall reduction x fertilization: Deep soil water usage in a clay rich ultisol under loblolly pine in the Southeast USA","interactions":[],"lastModifiedDate":"2020-06-19T16:20:27.21759","indexId":"70208263","displayToPublicDate":"2020-01-31T07:06:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5860,"text":"Frontiers in Forests and Global Change","active":true,"publicationSubtype":{"id":10}},"title":"Throughfall reduction x fertilization: Deep soil water usage in a clay rich ultisol under loblolly pine in the Southeast USA","docAbstract":"Forests in the Southeast USA are predicted to experience a moderate decrease in precipitation inputs over this century that may result in soil water deficiency during the growing season. The potential impact of a drier climate on the productivity of managed loblolly pine (Pinus taeda L.) plantations in the Southeast USA is uncertain. Access to water reserves in deep soil during drought periods may help buffer these forests from the effects of water deficits. To better understand the potential impact of drought on deep soil water, we studied the combined effects of throughfall reduction and fertilization on soil water usage in a clay rich Piedmont Ultisol to a depth of 3 m. In a 6-year-old loblolly pine plantation, we applied a throughfall reduction treatment (ambient vs. ~30% throughfall reduction) and a fertilization treatment (no fertilization vs. fertilization). Over 28 months, throughfall reduction lowered soil moisture for all depths and differences were significant in the surface soils (0–0.3 m) (1.2–3.6%) and deep soils (below 2 m) (2.6–3.6%). Fertilization also lowered soil moisture for all depths and differences were significant at 0.3–0.6 m (2.9%) and 1.94–3.06 m (4.5%). Fertilization when combined with the throughfall reduction treatment significantly decreased soil water at 0.1–0.9 m depth. Soils of all depths were rarely depleted of plant available water with the exception of 0–0.1 m, mainly during the growing season. Under throughfall reduction treatment, soil below 0.9 m consistently accounted for more than half of the change in plant available water during months when transpiration exceeded precipitation. When considering the whole soil profile in this clay rich Ultisol, soil water storage buffered transpirational demand in the face of decreasing throughfall input.","language":"English","publisher":"Frontiers","doi":"10.3389/ffgc.2019.00093","usgsCitation":"Qi, J., Markewitz, D.M., McGuire, M.A., Samuelson, L., and Ward, E., 2020, Throughfall reduction x fertilization: Deep soil water usage in a clay rich ultisol under loblolly pine in the Southeast USA: Frontiers in Forests and Global Change, v. 2, 93, 13 p., https://doi.org/10.3389/ffgc.2019.00093.","productDescription":"93, 13 p.","ipdsId":"IP-112050","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":457937,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffgc.2019.00093","text":"Publisher Index Page"},{"id":371901,"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              -94.130859375,\n              25.085598897064752\n            ],\n            [\n              -78.837890625,\n              25.085598897064752\n            ],\n            [\n              -78.837890625,\n              37.78808138412046\n            ],\n            [\n              -94.130859375,\n              37.78808138412046\n            ],\n            [\n              -94.130859375,\n              25.085598897064752\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Qi, Jiaguo","contributorId":191352,"corporation":false,"usgs":false,"family":"Qi","given":"Jiaguo","email":"","affiliations":[],"preferred":false,"id":781188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Markewitz, Daniel M.","contributorId":222099,"corporation":false,"usgs":false,"family":"Markewitz","given":"Daniel","email":"","middleInitial":"M.","affiliations":[{"id":37470,"text":"University of Georgia, Athens","active":true,"usgs":false}],"preferred":false,"id":781189,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGuire, Mary Ann","contributorId":222100,"corporation":false,"usgs":false,"family":"McGuire","given":"Mary","email":"","middleInitial":"Ann","affiliations":[{"id":37470,"text":"University of Georgia, Athens","active":true,"usgs":false}],"preferred":false,"id":781190,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Samuelson, Lisa","contributorId":222101,"corporation":false,"usgs":false,"family":"Samuelson","given":"Lisa","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":781191,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ward, Eric 0000-0002-5047-5464","orcid":"https://orcid.org/0000-0002-5047-5464","contributorId":167035,"corporation":false,"usgs":true,"family":"Ward","given":"Eric","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":781187,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70208398,"text":"70208398 - 2020 - Multi-decadal patterns of vegetation succession after tundra fire on the Yukon-Kuskokwim Delta, Alaska","interactions":[],"lastModifiedDate":"2020-02-09T13:41:53","indexId":"70208398","displayToPublicDate":"2020-01-30T13:39:46","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Multi-decadal patterns of vegetation succession after tundra fire on the Yukon-Kuskokwim Delta, Alaska","docAbstract":"Alaska’s Yukon-Kuskokwim Delta (YKD) is one of the warmest parts of the\nArctic tundra biome and tundra fires are common in its upland areas. Here we combine\nfield measurements, Landsat observations, and quantitative cover maps for tundra plant\nfunctional types (PFTs) to characterize multi-decadal succession and landscape change\nafter fire in lichen-dominated upland tundra of the YKD, where extensive wildfires\noccurred in 1971–1972, 1985, 2006–2007, and 2015. Unburned tundra was\ncharacterized by abundant lichens and low lichen cover was consistently associated\nwith historical fire. While we observed some successional patterns that were consistent\nwith earlier work in Alaskan tussock tundra, other patterns were not. In the landscape\nwe studied, a large proportion of pre-fire moss cover and surface peat tended to survive\nfire, which favors survival of existing vascular plants and limits opportunities for seed\nrecruitment. Although shrub cover was much higher in 1985 and 1971–1972 burns than\nin unburned tundra, tall shrubs (>0.5 m height) were rare and the PFT maps indicate\nhigh landscape-scale variability in the degree and persistence of shrub increase after\nfire. Fire has induced persistent changes in species composition and structure of upland\ntundra on the YKD, but the lichen-dominated fuels and thick surface peat appear to\nhave limited the potential for severe fire and accompanying edaphic changes. Soil thaw\ndepths were about 10 cm deeper in 2006–2007 burns than in unburned tundra, but\nwere similar to unburned tundra in 1985 and 1971–1972 burns. Historically, repeat fire\nhas been rare on the YKD, and the functional diversity of vegetation has recovered\nwithin several decades post-fire. Our findings provide a basis for predicting and\nmonitoring post-fire tundra succession on the YKD and elsewhere.","language":"English","publisher":"IOPScience","doi":"10.1088/1748-9326/ab5f49","usgsCitation":"Frost, G., Loehman, R.A., Saperstein, L., Macander, M.J., Nelson, P., Paradis, D., and Natali, S.M., 2020, Multi-decadal patterns of vegetation succession after tundra fire on the Yukon-Kuskokwim Delta, Alaska: Environmental Research Letters, no. 2, 14 p., https://doi.org/10.1088/1748-9326/ab5f49.","productDescription":"14 p.","ipdsId":"IP-112003","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":457945,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ab5f49","text":"Publisher Index Page"},{"id":372177,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon-Kuskokwim Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -167.958984375,\n              58.619777025081675\n            ],\n            [\n              -157.52197265625,\n              58.619777025081675\n            ],\n            [\n              -157.52197265625,\n              63.30281270313518\n            ],\n            [\n              -167.958984375,\n              63.30281270313518\n            ],\n            [\n              -167.958984375,\n              58.619777025081675\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","issue":"2","edition":"15","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Frost, Gerald","contributorId":222261,"corporation":false,"usgs":false,"family":"Frost","given":"Gerald","email":"","affiliations":[{"id":40510,"text":"ABR, Inc","active":true,"usgs":false}],"preferred":false,"id":781726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":781725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saperstein, Lisa","contributorId":218974,"corporation":false,"usgs":false,"family":"Saperstein","given":"Lisa","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":781727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Macander, Matthew J.","contributorId":203639,"corporation":false,"usgs":false,"family":"Macander","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":36669,"text":"ABR, Inc.—Environmental Research & Services","active":true,"usgs":false}],"preferred":false,"id":781728,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, Peter","contributorId":198617,"corporation":false,"usgs":false,"family":"Nelson","given":"Peter","affiliations":[],"preferred":false,"id":781729,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Paradis, David","contributorId":222262,"corporation":false,"usgs":false,"family":"Paradis","given":"David","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":781730,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Natali, Sue M.","contributorId":204028,"corporation":false,"usgs":false,"family":"Natali","given":"Sue","email":"","middleInitial":"M.","affiliations":[{"id":16705,"text":"Woods Hole Research Center","active":true,"usgs":false}],"preferred":false,"id":781731,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70209031,"text":"70209031 - 2020 - Response to terrestrial nest predators among endemic and introduced Hawaiian birds","interactions":[],"lastModifiedDate":"2020-03-12T08:00:36","indexId":"70209031","displayToPublicDate":"2020-01-23T07:58:59","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Response to terrestrial nest predators among endemic and introduced Hawaiian birds","docAbstract":"Birds free from nest predators for long periods may either lose the ability to recognize and respond to predators or retain antipredator responses if they are not too costly. How these alternate scenarios play out has rarely been investigated in an avian community whose members have different evolutionary histories. We presented models of two nest predators (rat and snake) and a negative control (tree branch) to birds on Hawaiʻi Island. Endemic Hawaiian birds evolved in the absence of terrestrial predators until rats were introduced approximately 1,000 years ago. Introduced birds evolved with diverse predator communities including mammals and snakes, but since their introduction onto the island approximately one century ago have been free from snake predation. We found that (a) endemic and introduced birds had higher agitation scores toward the rat model compared with the branch, and (b) none of the endemic birds reacted to the snake model, while one introduced bird, the Red-billed Leiothrix\n(Leiothrix lutea), reacted as strongly to the snake as to the rat. Overall, endemic and introduced birds differ in their response to predators, but some endemic birds have the capacity to recognize and respond to introduced rats, and one introduced bird species retained recognition of snake predators from which they had been free for nearly a century, while another apparently lost that ability. Our results indicate that the retention or loss of predator recognition by introduced and endemic island birds is variable, shaped by each species' unique history, ecology, and the potential interplay of genetic drift, and that endemic Hawaiian birds could be especially vulnerable to introduced snake predators.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.6021","usgsCitation":"Cummins, G.C., Theimer, T.C., and Paxton, E., 2020, Response to terrestrial nest predators among endemic and introduced Hawaiian birds: Ecology and Evolution, v. 10, no. 4, p. 1949-1958, https://doi.org/10.1002/ece3.6021.","productDescription":"10 p.","startPage":"1949","endPage":"1958","ipdsId":"IP-109470","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":458044,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.6021","text":"Publisher Index Page"},{"id":437145,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ADI937","text":"USGS data release","linkHelpText":"Hawaii Island forest bird response to simulated nest predator 2015-2016"},{"id":373165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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