{"pageNumber":"495","pageRowStart":"12350","pageSize":"25","recordCount":184828,"records":[{"id":70221857,"text":"70221857 - 2021 - Low MSP-1 haplotype diversity in the West Palearctic population of the avian malaria parasite Plasmodium relictum","interactions":[],"lastModifiedDate":"2021-07-12T17:33:46.698672","indexId":"70221857","displayToPublicDate":"2021-06-12T12:33:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2650,"text":"Malaria Journal","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Low MSP-1 haplotype diversity in the West Palearctic population of the avian malaria parasite Plasmodium relictum","title":"Low MSP-1 haplotype diversity in the West Palearctic population of the avian malaria parasite Plasmodium relictum","docAbstract":"

Background

Although avian Plasmodium species are widespread and common across the globe, limited data exist on how genetically variable their populations are. Here, the hypothesis that the avian blood parasite Plasmodium relictum exhibits very low genetic diversity in its Western Palearctic transmission area (from Morocco to Sweden in the north and Transcaucasia in the east) was tested.

Methods

The genetic diversity of Plasmodium relictum was investigated by sequencing a portion (block 14) of the fast-evolving merozoite surface protein 1 (MSP1) gene in 75 different P. relictum infections from 36 host species. Furthermore, the full-length MSP1 sequences representing the common block 14 allele was sequenced in order to investigate if additional variation could be found outside block 14.

Results

The majority (72 of 75) of the sequenced infections shared the same MSP1 allele. This common allele has previously been found to be the dominant allele transmitted in Europe.

Conclusion

The results corroborate earlier findings derived from a limited dataset that the globally transmitted malaria parasite P. relictum exhibits very low genetic diversity in its Western Palearctic transmission area. This is likely the result of a recent introduction event or a selective sweep.

","language":"English","publisher":"Springer Nature","doi":"10.1186/s12936-021-03799-8","usgsCitation":"Hellgren, O., Kelbskopf, V., Ellis, V.A., Ciloglu, A., Duc, M., Huang, X., Lopes, R.J., Mata, V.A., Aghayan, S.A., Inci, A., and Drovetski, S.V., 2021, Low MSP-1 haplotype diversity in the West Palearctic population of the avian malaria parasite Plasmodium relictum: Malaria Journal, v. 20, 265, 9 p., https://doi.org/10.1186/s12936-021-03799-8.","productDescription":"265, 9 p.","ipdsId":"IP-127806","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":451905,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12936-021-03799-8","text":"Publisher Index Page"},{"id":387130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","noUsgsAuthors":false,"publicationDate":"2021-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Hellgren, Olof","contributorId":140266,"corporation":false,"usgs":false,"family":"Hellgren","given":"Olof","email":"","affiliations":[{"id":13428,"text":"Lund University","active":true,"usgs":false}],"preferred":false,"id":819012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelbskopf, Victor","contributorId":260867,"corporation":false,"usgs":false,"family":"Kelbskopf","given":"Victor","email":"","affiliations":[{"id":52694,"text":"Department of Biology, Lund University, Lund, Sweden","active":true,"usgs":false}],"preferred":false,"id":819013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellis, Vincenzo A","contributorId":260868,"corporation":false,"usgs":false,"family":"Ellis","given":"Vincenzo","email":"","middleInitial":"A","affiliations":[{"id":52694,"text":"Department of Biology, Lund University, Lund, Sweden","active":true,"usgs":false}],"preferred":false,"id":819014,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ciloglu, Arif","contributorId":260869,"corporation":false,"usgs":false,"family":"Ciloglu","given":"Arif","email":"","affiliations":[{"id":52698,"text":"Department of Parasitology, Faculty of Veterinary Medicine, Erciyes University, Kayseri, Turkey","active":true,"usgs":false}],"preferred":false,"id":819015,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duc, Melanie","contributorId":260870,"corporation":false,"usgs":false,"family":"Duc","given":"Melanie","email":"","affiliations":[{"id":52695,"text":"Department of Biology, University of North Dakota, Grand Forks, ND 58201, USA","active":true,"usgs":false}],"preferred":false,"id":819016,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Huang, Xi","contributorId":260871,"corporation":false,"usgs":false,"family":"Huang","given":"Xi","email":"","affiliations":[{"id":16866,"text":"Beijing Normal University","active":true,"usgs":false}],"preferred":false,"id":819017,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lopes, Ricardo J.","contributorId":260872,"corporation":false,"usgs":false,"family":"Lopes","given":"Ricardo","email":"","middleInitial":"J.","affiliations":[{"id":52696,"text":"CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Universidade do Porto, Vairão, Portugal","active":true,"usgs":false}],"preferred":false,"id":819018,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mata, Vanessa A","contributorId":260873,"corporation":false,"usgs":false,"family":"Mata","given":"Vanessa","email":"","middleInitial":"A","affiliations":[{"id":52696,"text":"CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Universidade do Porto, Vairão, Portugal","active":true,"usgs":false}],"preferred":false,"id":819019,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Aghayan, Sargis A.","contributorId":260874,"corporation":false,"usgs":false,"family":"Aghayan","given":"Sargis","email":"","middleInitial":"A.","affiliations":[{"id":52697,"text":"Yerevan State University, 1 Alex Manoogian, Yerevan, 0025, Republic of Armenia","active":true,"usgs":false}],"preferred":false,"id":819020,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Inci, Abdullah","contributorId":260875,"corporation":false,"usgs":false,"family":"Inci","given":"Abdullah","email":"","affiliations":[{"id":52698,"text":"Department of Parasitology, Faculty of Veterinary Medicine, Erciyes University, Kayseri, Turkey","active":true,"usgs":false}],"preferred":false,"id":819021,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Drovetski, Sergei V. 0000-0002-1832-5597","orcid":"https://orcid.org/0000-0002-1832-5597","contributorId":229520,"corporation":false,"usgs":true,"family":"Drovetski","given":"Sergei","middleInitial":"V.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819022,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70223769,"text":"70223769 - 2021 - Response of fish assemblages to restoration of rapids habitat in a Great Lakes connecting channel","interactions":[],"lastModifiedDate":"2021-09-07T16:05:33.360728","indexId":"70223769","displayToPublicDate":"2021-06-12T11:00:01","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Response of fish assemblages to restoration of rapids habitat in a Great Lakes connecting channel","docAbstract":"

Rapids habitats are critical spawning and nursery grounds for multiple Laurentian Great Lakes fishes of ecological importance such as lake sturgeon, walleye, and salmonids. However, river modifications have destroyed important rapids habitat in connecting channels by modifying flow profiles and removing large quantities of cobble and gravel that are preferred spawning substrates of several fish species. The conversion of rapids habitat to slow moving waters has altered fish assemblages and decreased the spawning success of lithophilic species. The St. Marys River is a Great Lakes connecting channel in which the majority of rapids habitat has been lost. However, rapids habitat was restored at the Little Rapids in 2016 to recover important spawning habitat in this river. During the restoration, flow and substrate were recovered to rapids habitat. We sampled the fish community (pre- and post-restoration), focusing on age-0 fishes in order to characterize the response of the fish assemblage to the restoration, particularly for species of importance (e.g. lake whitefish, walleye, Atlantic salmon). Following restoration, we observed a 40% increase in age-0 fish catch per unit effort, increased presence of rare species, and a shift in assemblage structure of age-0 fishes (higher relative abundance of Salmonidae, Cottidae, and Gasterosteidae). We also observed a “transition” period in 2017, in which the assemblage was markedly different from the pre- and post-restoration assemblages and was dominated by Catostomidae. Responses from target species were mixed, with increased Atlantic salmon abundance, first documented presence of walleye and no presence of lake sturgeon or Coregoninae.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2021.05.009","usgsCitation":"Molina-Moctezuma, A., Godby, N., Kapuscinski, K., Roseman, E., Skubik, K., and Moerke, A., 2021, Response of fish assemblages to restoration of rapids habitat in a Great Lakes connecting channel: Journal of Great Lakes Research, v. 47, no. 4, p. 1182-1191, https://doi.org/10.1016/j.jglr.2021.05.009.","productDescription":"10 p.","startPage":"1182","endPage":"1191","ipdsId":"IP-126170","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":451907,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2021.05.009","text":"Publisher Index Page"},{"id":388884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan, Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.37362670898438,\n 46.150345757336574\n ],\n [\n -83.9190673828125,\n 46.150345757336574\n ],\n [\n -83.9190673828125,\n 46.538082005463075\n ],\n [\n -84.37362670898438,\n 46.538082005463075\n ],\n [\n -84.37362670898438,\n 46.150345757336574\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Molina-Moctezuma, A.","contributorId":247565,"corporation":false,"usgs":false,"family":"Molina-Moctezuma","given":"A.","affiliations":[{"id":49581,"text":"Lake Superior State Univ.","active":true,"usgs":false}],"preferred":false,"id":822595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Godby, N.","contributorId":265347,"corporation":false,"usgs":false,"family":"Godby","given":"N.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":822596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kapuscinski, K.","contributorId":247567,"corporation":false,"usgs":false,"family":"Kapuscinski","given":"K.","email":"","affiliations":[{"id":49581,"text":"Lake Superior State Univ.","active":true,"usgs":false}],"preferred":false,"id":822597,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":822598,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Skubik, K.","contributorId":265348,"corporation":false,"usgs":false,"family":"Skubik","given":"K.","email":"","affiliations":[{"id":49581,"text":"Lake Superior State Univ.","active":true,"usgs":false}],"preferred":false,"id":822599,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moerke, A.","contributorId":247569,"corporation":false,"usgs":false,"family":"Moerke","given":"A.","affiliations":[{"id":49581,"text":"Lake Superior State Univ.","active":true,"usgs":false}],"preferred":false,"id":822600,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222099,"text":"70222099 - 2021 - Integrating thermal infrared stream temperature imagery and spatial stream network models to understand natural spatial thermal variability in streams","interactions":[],"lastModifiedDate":"2021-07-20T12:18:00.475837","indexId":"70222099","displayToPublicDate":"2021-06-12T07:15:25","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2476,"text":"Journal of Thermal Biology","active":true,"publicationSubtype":{"id":10}},"title":"Integrating thermal infrared stream temperature imagery and spatial stream network models to understand natural spatial thermal variability in streams","docAbstract":"

Under a warmer future climate, thermal refuges could facilitate the persistence of species relying on cold-water habitat. Often these refuges are small and easily missed or smoothed out by averaging in models. Thermal infrared (TIR) imagery can provide empirical water surface temperatures that capture these features at a high spatial resolution (<1 m) and over tens of kilometers. Our study examined how TIR data could be used along with spatial stream network (SSN) models to characterize thermal regimes spatially in the Middle Fork John Day (MFJD) River mainstem (Oregon, USA). We characterized thermal variation in seven TIR longitudinal temperature profiles along the MFJD mainstem and compared them with SSN model predictions of stream temperature (for the same time periods as the TIR profiles). TIR profiles identified reaches of the MFJD mainstem with consistently cooler temperatures across years that were not consistently captured by the SSN prediction models. SSN predictions along the mainstem identified ~80% of the 1-km reach scale temperature warming or cooling trends observed in the TIR profiles. We assessed whether landscape features (e.g., tributary junctions, valley confinement, geomorphic reach classifications) could explain the fine-scale thermal heterogeneity in the TIR profiles (after accounting for the reach-scale temperature variability predicted by the SSN model) by fitting SSN models using the TIR profile observation points. Only the distance to the nearest upstream tributary was identified as a statistically significant landscape feature for explaining some of the thermal variability in the TIR profile data. When combined, TIR data and SSN models provide a data-rich evaluation of stream temperature captured in TIR imagery and a spatially extensive prediction of the network thermal diversity from the outlet to the headwaters.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jtherbio.2021.103028","usgsCitation":"Fuller, M.R., Ebersole, J.L., Detenbeck, N., Labisoa, R., Leinenbach, P., and Torgersen, C.E., 2021, Integrating thermal infrared stream temperature imagery and spatial stream network models to understand natural spatial thermal variability in streams: Journal of Thermal Biology, v. 100, 103028, 19 p., https://doi.org/10.1016/j.jtherbio.2021.103028.","productDescription":"103028, 19 p.","ipdsId":"IP-128957","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":436314,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UQBZ2X","text":"USGS data release","linkHelpText":"Airborne thermal infrared remote sensing of summer water temperature in the Middle Fork John Day River (Oregon) in 1994-2003"},{"id":387293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Middle Fork John Day River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.311279296875,\n 43.739352079154706\n ],\n [\n -117.71850585937501,\n 43.739352079154706\n ],\n [\n -117.71850585937501,\n 44.98034238084973\n ],\n [\n -120.311279296875,\n 44.98034238084973\n ],\n [\n -120.311279296875,\n 43.739352079154706\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"100","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fuller, Matthew R.","contributorId":213261,"corporation":false,"usgs":false,"family":"Fuller","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":819513,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ebersole, Joseph L.","contributorId":146938,"corporation":false,"usgs":false,"family":"Ebersole","given":"Joseph","email":"","middleInitial":"L.","affiliations":[{"id":12657,"text":"EPA NEIC","active":true,"usgs":false}],"preferred":false,"id":819514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Detenbeck, Naomi","contributorId":261219,"corporation":false,"usgs":false,"family":"Detenbeck","given":"Naomi","email":"","affiliations":[{"id":39312,"text":"U.S. EPA","active":true,"usgs":false}],"preferred":false,"id":819515,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Labisoa, Rochelle","contributorId":261221,"corporation":false,"usgs":false,"family":"Labisoa","given":"Rochelle","email":"","affiliations":[{"id":39312,"text":"U.S. EPA","active":true,"usgs":false}],"preferred":false,"id":819516,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leinenbach, P.T.","contributorId":217976,"corporation":false,"usgs":false,"family":"Leinenbach","given":"P.T.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":819517,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":819518,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222090,"text":"70222090 - 2021 - Recency of faulting and subsurface architecture of the San Diego Bay pull-apart basin, California, USA","interactions":[],"lastModifiedDate":"2021-07-19T23:18:37.411565","indexId":"70222090","displayToPublicDate":"2021-06-11T18:12:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Recency of faulting and subsurface architecture of the San Diego Bay pull-apart basin, California, USA","docAbstract":"In southern California, plate boundary motion between the North American and Pacific plates is distributed across several sub-parallel fault systems. The offshore faults of the California Continental Borderland (CCB) are thought to accommodate ~10-15% of the total plate boundary motion, but the exact distribution of slip and the mechanics of slip partitioning remain uncertain. The Newport-Inglewood-Rose Canyon fault is the easternmost fault within the CCB whose southern segment splays out into a complex network of faults beneath San Diego Bay. A pull-apart basin model between the Rose Canyon and the offshore Descanso fault has been used to explain prominent fault orientations and subsidence beneath San Diego Bay; however this model does not account for faults in the southern portion of the bay or faulting east of the bay. To investigate the characteristics of faulting and stratigraphic architecture beneath San Diego Bay, we combined a suite of reprocessed legacy airgun multi-channel seismic profiles and high-resolution Chirp data, with age and lithology controls from geotechnical boreholes and shallow sub-surface vibracores. This combined dataset is used to create gridded horizon surfaces, fault maps, and perform a kinematic fault analysis. The structure beneath San Diego Bay is dominated by down-to-the-east motion on normal faults that can be separated into two distinct groups. The strikes of these two fault groups can be explained with a double pull-apart basin model for San Diego Bay. In our conceptual model, the western portion of San Diego Bay is controlled by a right-step between the Rose Canyon and Descanso faults, which matches both observations and predictions from laboratory models. The eastern portion of San Diego Bay appears to be controlled by an inferred step-over between the Rose Canyon and San Miguel-Vallecitos faults and displays distinct fault strike orientations, which kinematic analysis indicates should have a significant component of strike-slip partitioning that is not detectable in the seismic data. The potential of a Rose Canyon-San Miguel-Vallecitos fault connection would effectively cut the stepover distance in half and have important implications for the seismic hazard of the San Diego-Tijuana metropolitan area (population ~3 million people).","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2021.641346","usgsCitation":"Singleton, D.M., Maloney, J.M., Brothers, D.S., Klotsko, S., Driscoll, N., and Rockwell, T.K., 2021, Recency of faulting and subsurface architecture of the San Diego Bay pull-apart basin, California, USA: Frontiers in Earth Science, v. 9, 641346, 25 p., https://doi.org/10.3389/feart.2021.641346.","productDescription":"641346, 25 p.","ipdsId":"IP-125700","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451910,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2021.641346","text":"Publisher Index Page"},{"id":436315,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93Z2LYJ","text":"USGS data release","linkHelpText":"Reprocessed multichannel seismic-reflection (MCS) data from USGS field activity T-1-96-SC collected in San Diego Bay, California in 1996"},{"id":387256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Diego Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.34771728515625,\n 32.602361666817515\n ],\n [\n -117.037353515625,\n 32.602361666817515\n ],\n [\n -117.037353515625,\n 32.858825196463854\n ],\n [\n -117.34771728515625,\n 32.858825196463854\n ],\n [\n -117.34771728515625,\n 32.602361666817515\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2021-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Singleton, Drake Moore 0000-0001-5346-0623","orcid":"https://orcid.org/0000-0001-5346-0623","contributorId":261207,"corporation":false,"usgs":true,"family":"Singleton","given":"Drake","email":"","middleInitial":"Moore","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":819471,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maloney, Jillian M. 0000-0001-8223-4676","orcid":"https://orcid.org/0000-0001-8223-4676","contributorId":261208,"corporation":false,"usgs":false,"family":"Maloney","given":"Jillian","email":"","middleInitial":"M.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":819472,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brothers, Daniel S. 0000-0001-7702-157X dbrothers@usgs.gov","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":167089,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel","email":"dbrothers@usgs.gov","middleInitial":"S.","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":819473,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klotsko, Shannon","contributorId":261209,"corporation":false,"usgs":false,"family":"Klotsko","given":"Shannon","affiliations":[{"id":52774,"text":"University of North Carolina - Wilmington","active":true,"usgs":false}],"preferred":false,"id":819474,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Driscoll, Neal W.","contributorId":261210,"corporation":false,"usgs":false,"family":"Driscoll","given":"Neal W.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":819475,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rockwell, Thomas K.","contributorId":53290,"corporation":false,"usgs":true,"family":"Rockwell","given":"Thomas","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":819476,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70221913,"text":"70221913 - 2021 - Magnetotelluric sampling and geoelectric hazard estimation: Are national-scale surveys sufficient?","interactions":[],"lastModifiedDate":"2021-07-14T17:04:37.733359","indexId":"70221913","displayToPublicDate":"2021-06-11T11:59:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8968,"text":"AGU Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"Magnetotelluric sampling and geoelectric hazard estimation: Are national-scale surveys sufficient?","docAbstract":"

At present, the most reliable information for inferring storm-time ground electric fields along electrical transmission lines comes from coarsely sampled, national-scale magnetotelluric (MT) data sets, such as that provided by the EarthScope USArray program. An underlying assumption in the use of such data is that they adequately sample the spatial heterogeneity of the surface relationship between geomagnetic and geoelectric fields. Here, we assess the degree to which the density of MT data sampling affects geoelectric hazard assessments. For electrical transmission networks in each of four focus regions across the contiguous United States, we perform two parallel band-limited (101–103 s) hazard analyses: one using only USArray-style (∼70-km station spacing) MT data, and one incorporating denser (≪70-km station spacing) MT data. We find that the use of USArray-style MT sampling alone provides a useful first-order estimate of integrated geoelectric fields along electrical transmission lines. However, we also find that the use of higher density MT data can in some areas lead to order-of-magnitude differences in line-averaged electric field estimates at the level of individual transmission lines and can also yield significant differences in subregional hazard patterns. As we demonstrate using variogram plots, these differences reflect short-spatial-scale variability in Earth conductivity, which in turn reflects regional lithotectonic structure and history. We also provide a cautionary example in the use of electrical conductivity models to predict dense MT data; although valuable for hazard applications, models may only be able to reproduce surface geoelectric fields as captured by the MT data from which they were derived.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020SW002693","usgsCitation":"Murphy, B.S., Lucas, G., Love, J.J., Kelbert, A., Bedrosian, P.A., and Rigler, E.J., 2021, Magnetotelluric sampling and geoelectric hazard estimation: Are national-scale surveys sufficient?: AGU Space Weather, v. 19, no. 7, e2020SW002693, 24 p., https://doi.org/10.1029/2020SW002693.","productDescription":"e2020SW002693, 24 p.","ipdsId":"IP-128631","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":488915,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020sw002693","text":"Publisher Index Page"},{"id":387180,"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 -125.33203124999997,\n 39.70718665682654\n ],\n [\n -120.93749999999997,\n 39.70718665682654\n ],\n [\n -120.93749999999997,\n 46.37725420510028\n ],\n [\n -125.33203124999997,\n 46.37725420510028\n ],\n [\n -125.33203124999997,\n 39.70718665682654\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.140625,\n 37.23032838760387\n ],\n [\n -94.921875,\n 37.23032838760387\n ],\n [\n -94.921875,\n 41.64007838467894\n ],\n [\n -99.140625,\n 41.64007838467894\n ],\n [\n -99.140625,\n 37.23032838760387\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.833984375,\n 33.211116472416855\n ],\n [\n -86.748046875,\n 33.211116472416855\n ],\n [\n -86.748046875,\n 38.75408327579141\n ],\n [\n -94.833984375,\n 38.75408327579141\n ],\n [\n -94.833984375,\n 33.211116472416855\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.240234375,\n 44.276671273775186\n ],\n [\n -83.671875,\n 44.276671273775186\n ],\n [\n -83.671875,\n 49.03786794532644\n ],\n [\n -96.240234375,\n 49.03786794532644\n ],\n [\n -96.240234375,\n 44.276671273775186\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Benjamin Scott 0000-0001-7636-3711","orcid":"https://orcid.org/0000-0001-7636-3711","contributorId":242928,"corporation":false,"usgs":true,"family":"Murphy","given":"Benjamin","email":"","middleInitial":"Scott","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":819286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lucas, Greg M. 0000-0003-1331-1863","orcid":"https://orcid.org/0000-0003-1331-1863","contributorId":223556,"corporation":false,"usgs":false,"family":"Lucas","given":"Greg M.","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":819287,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":819288,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelbert, Anna 0000-0003-4395-398X akelbert@usgs.gov","orcid":"https://orcid.org/0000-0003-4395-398X","contributorId":184053,"corporation":false,"usgs":true,"family":"Kelbert","given":"Anna","email":"akelbert@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":819289,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":819290,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rigler, E. Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":819291,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70226924,"text":"70226924 - 2021 - Nuclear magnetic resonanance logs of fractured bedrock at the Hidden Lane Landfill site, Culpeper Basin, Virginia","interactions":[],"lastModifiedDate":"2022-01-20T17:29:54.637486","indexId":"70226924","displayToPublicDate":"2021-06-11T11:19:46","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Nuclear magnetic resonanance logs of fractured bedrock at the Hidden Lane Landfill site, Culpeper Basin, Virginia","docAbstract":"

In May 2018, the U.S. Geological Survey (USGS) in cooperation with the U.S. Environmental Protection Agency (EPA) collected borehole nuclear magnetic resonance (bNMR) logs in three boreholes completed in sandstone and siltstone of the Balls Bluff Member of the Bull Run Formation at a Superfund Site in Culpeper Basin, Virginia. The bNMR logs were used to aid in the evaluation of the aquifer by measuring the porosity, determining the mobile and immobile fractions of water, and estimating the hydraulic conductivity, to evaluate the potential storage and transport properties at the site. The bNMR method measures the transverse (T2) decay in nuclear magnetism in response to radio-frequency pulses. The relaxation decay is related to water content and the size of the pores where the water resides. In addition, the relaxation decay parameters are used to estimate hydraulic conductivity. The results were compared to other borehole logs collected at the site and to regional groundwater investigations in similar rock formations.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Symposium on the application of geophysics to engineering and environmental problems proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Symposium on the Application of Geophysics to Engineering and Environmental Problems 2021","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.4133/sageep.33-029","usgsCitation":"Johnson, C., Phillips, S.N., Day-Lewis, F.D., Tiedeman, C.R., Rundell, B., and Gilbert, E., 2021, Nuclear magnetic resonanance logs of fractured bedrock at the Hidden Lane Landfill site, Culpeper Basin, Virginia, in Symposium on the application of geophysics to engineering and environmental problems proceedings, p. 63-68, https://doi.org/10.4133/sageep.33-029.","productDescription":"6 p.","startPage":"63","endPage":"68","ipdsId":"IP-125623","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":394594,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","city":"Culpeper","otherGeospatial":"Hidden Lane Landfill site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.5169563293457,\n 38.783126804001704\n ],\n [\n -77.44245529174805,\n 38.783126804001704\n ],\n [\n -77.44245529174805,\n 38.81630492781235\n ],\n [\n -77.5169563293457,\n 38.81630492781235\n ],\n [\n -77.5169563293457,\n 38.783126804001704\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2021-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Carole D. 0000-0001-6941-1578","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":245365,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":828802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Stephanie N. 0000-0002-2022-7726","orcid":"https://orcid.org/0000-0002-2022-7726","contributorId":214857,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephanie","email":"","middleInitial":"N.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":828803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - 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2021 - Experimental warming differentially affects vegetative and reproductive phenology of tundra plants","interactions":[],"lastModifiedDate":"2021-07-13T10:13:24.993767","indexId":"70221874","displayToPublicDate":"2021-06-11T09:55:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Experimental warming differentially affects vegetative and reproductive phenology of tundra plants","docAbstract":"

Rapid climate warming is altering Arctic and alpine tundra ecosystem structure and function, including shifts in plant phenology. While the advancement of green up and flowering are well-documented, it remains unclear whether all phenophases, particularly those later in the season, will shift in unison or respond divergently to warming. Here, we present the largest synthesis to our knowledge of experimental warming effects on tundra plant phenology from the International Tundra Experiment. We examine the effect of warming on a suite of season-wide plant phenophases. Results challenge the expectation that all phenophases will advance in unison to warming. Instead, we find that experimental warming caused: (1) larger phenological shifts in reproductive versus vegetative phenophases and (2) advanced reproductive phenophases and green up but delayed leaf senescence which translated to a lengthening of the growing season by approximately 3%. Patterns were consistent across sites, plant species and over time. The advancement of reproductive seasons and lengthening of growing seasons may have significant consequences for trophic interactions and ecosystem function across the tundra.

","language":"English","publisher":"Nature","doi":"10.1038/s41467-021-23841-2","usgsCitation":"Collins, C.G., Elmendorf, S.C., Hollister, R.D., Henry, G., Clark, K., Bjorkman, A., Myers-Smith, I.H., Prevey, J.S., Ashton, I., Assmann, J.J., Alatalo, J., Carbognani, M., Chisholm, C., Cooper, E.J., , C., Jonsdottir, I.S., Klanderud, K., Kopp, C., Livensperger, C., Mauritz, M., May, J., Molau, U., Oberbaeur, S.F., Ogburn, E., Panchen, Z., Petraglia, A., Post, E., Rixen, C., Rodenhizer, H., Schuur, T., Semenchuk, P., Smith, J.G., Steltzer, H., Totland, Ø., Walker, M., Welker, J., and Suding, K.N., 2021, Experimental warming differentially affects vegetative and reproductive phenology of tundra plants: Nature Communications, v. 12, 3442, 12 p., https://doi.org/10.1038/s41467-021-23841-2.","productDescription":"3442, 12 p.","ipdsId":"IP-124079","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":451918,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-021-23841-2","text":"Publisher Index Page"},{"id":387114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","noUsgsAuthors":false,"publicationDate":"2021-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Collins, Courtney G. 0000-0001-5455-172X","orcid":"https://orcid.org/0000-0001-5455-172X","contributorId":260909,"corporation":false,"usgs":false,"family":"Collins","given":"Courtney","email":"","middleInitial":"G.","affiliations":[{"id":52708,"text":"Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO USA","active":true,"usgs":false}],"preferred":false,"id":819119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elmendorf, Sarah Claire","contributorId":260910,"corporation":false,"usgs":false,"family":"Elmendorf","given":"Sarah","email":"","middleInitial":"Claire","affiliations":[{"id":52709,"text":"University of Colorado, Boulder CO 80309-0450","active":true,"usgs":false}],"preferred":false,"id":819120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hollister, Robert D. 0000-0002-4764-7691","orcid":"https://orcid.org/0000-0002-4764-7691","contributorId":260917,"corporation":false,"usgs":false,"family":"Hollister","given":"Robert","email":"","middleInitial":"D.","affiliations":[{"id":52714,"text":"Grand Valley State University; Biology Department; Allendale, Michigan, USA 49401-9403","active":true,"usgs":false}],"preferred":false,"id":819129,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Henry, Greg","contributorId":260918,"corporation":false,"usgs":false,"family":"Henry","given":"Greg","email":"","affiliations":[{"id":52715,"text":"Department of Geography, University of British Columbia, Vancouver, Canada","active":true,"usgs":false}],"preferred":false,"id":819130,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Karin","contributorId":260915,"corporation":false,"usgs":false,"family":"Clark","given":"Karin","email":"","affiliations":[{"id":52712,"text":"Environment and Natural Resources Government of the Northwest Territories","active":true,"usgs":false}],"preferred":false,"id":819127,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bjorkman, Anne 0000-0003-2174-7800","orcid":"https://orcid.org/0000-0003-2174-7800","contributorId":260911,"corporation":false,"usgs":false,"family":"Bjorkman","given":"Anne","email":"","affiliations":[{"id":52710,"text":"(1) Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden (2) Gothenburg Global Biodiversity Centre, Gothenburg, Sweden","active":true,"usgs":false}],"preferred":false,"id":819121,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Myers-Smith, Isla H. 0000-0002-8417-6112","orcid":"https://orcid.org/0000-0002-8417-6112","contributorId":169406,"corporation":false,"usgs":false,"family":"Myers-Smith","given":"Isla","email":"","middleInitial":"H.","affiliations":[{"id":25497,"text":"University of Edinburgh","active":true,"usgs":false}],"preferred":false,"id":819122,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prevey, Janet S. 0000-0003-2879-6453","orcid":"https://orcid.org/0000-0003-2879-6453","contributorId":222702,"corporation":false,"usgs":true,"family":"Prevey","given":"Janet","email":"","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":819123,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ashton, 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The PLUM (Propagation of Local Undamped Motion) earthquake early warning (EEW) algorithm differs from typical source-based EEW algorithms as it predicts shaking directly from observed shaking without first deriving earthquake source information (e.g., magnitude and epicenter). Here, we determine optimal PLUM event detection thresholds for U.S. West Coast earthquakes using two data sets: 558 M3.5+ earthquakes (California, Oregon, Washington; 2012–2017) and the ShakeAlert test suite of historic and problematic signals (1999–2015). PLUM computes Modified Mercalli Intensity (IMMI) using velocity and acceleration data, leveraging co-located sensors to avoid problematic signals. An event detection is issued when the observed IMMI exceeds a given threshold(s). We find a two-station detection method using IMMI trigger thresholds of 4.0 and 3.0 for the first and second stations, respectively, is optimal for detecting M4.5+ earthquakes. PLUM detected 79 events in the 2012–2017 data set, reporting (not including telemetry or alert dissemination) detection times on par, and sometimes faster than current EEW methods (mean 8 s; median 6 s). As expected, detection times were slower for the older 1999–2015 earthquakes (N = 21; mean 11 s; median 6 s) when station coverage was sparser. Of the 31 PLUM detected M5+ events (10 2012–2017; 21 1999–2015), theoretically 20 (∼65%) could provide timely warnings. PLUM issued no false detections and avoided issuing detections for all calibration/anomalous signals, regional and teleseismic events. We conclude PLUM can successfully identify IMMI 4+ shaking from local earthquakes and could complement and enhance EEW in the U.S.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB021053","usgsCitation":"Kilb, D., Bunn, J.J., Saunders, J.K., Cochran, E.S., Minson, S.E., Baltay Sundstrom, A.S., O’Rourke, C.T., Hoshiba, M., and Kodera, Y., 2021, The PLUM earthquake early warning algorithm: A retrospective case study of West Coast, USA, data: JGR Solid Earth, v. 126, no. 7, e2020JB021053, 25 p., https://doi.org/10.1029/2020JB021053.","productDescription":"e2020JB021053, 25 p.","ipdsId":"IP-127285","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":487640,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jb021053","text":"Publisher Index Page"},{"id":481971,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, California, Oregon, Washington","geographicExtents":"{\n 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Waterdogs (Necturus beyeri) along Bayou Lacombe, Saint Tammany Parish, Louisiana","interactions":[],"lastModifiedDate":"2023-06-09T14:10:31.349995","indexId":"70223335","displayToPublicDate":"2021-06-11T08:18:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2334,"text":"Journal of Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Abundance of Gulf Coast Waterdogs (Necturus beyeri) along Bayou Lacombe, Saint Tammany Parish, Louisiana","docAbstract":"

Few ecological studies have been conducted on Gulf Coast Waterdogs (Necturus beyeri), and published studies have focused on relatively small stream sections of 125 m to 1.75 km. In 2015, we sampled 25 sites along a 13.4-km stretch of Bayou Lacombe (Saint Tammany Parish, Louisiana, USA) to better understand factors that may influence the distribution of Gulf Coast Waterdogs within streams. We checked 250 unbaited traps once per week for 3 weeks, capturing 170 Gulf Coast Waterdogs at 18 of 25 sites. We used hierarchical models of abundance to estimate abundance at each site, as a function of site covariates including pH, turbidity, and distance from headwaters. The abundance of Gulf Coast Waterdogs within Bayou Lacombe was highest toward the center of the sampled stream segment, but we found no evidence that pH or turbidity affected abundance within our study area. Site-level abundance estimates of Gulf Coast Waterdogs ranged from 0 to 82, and we estimated there were 767 (95% Bayesian credible interval [CRI]: 266–983) Gulf Coast Waterdogs summed across all 25 sampling sites. We derived an estimate of 6,321 (95% CRI: 2,139–15,922) Gulf Coast Waterdogs for the entire 13.4-km stream section, which includes our 25 sites and the adjoining stream reaches between sites. Our results suggest that Gulf Coast Waterdogs may be uncommon or absent in the headwaters, possibly because of shallow water and swift currents with limited preferred habitats. Gulf Coast Waterdogs favor the middle stream reaches with adequate depth and abundant preferred microhabitats.

","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","doi":"10.1670/20-062","usgsCitation":"Glorioso, B., Waddle, H., Muse, L.J., and Godfrey, S., 2021, Abundance of Gulf Coast Waterdogs (Necturus beyeri) along Bayou Lacombe, Saint Tammany Parish, Louisiana: Journal of Herpetology, v. 55, no. 2, p. 160-166, https://doi.org/10.1670/20-062.","productDescription":"7 p.; Data Release","startPage":"160","endPage":"166","ipdsId":"IP-118494","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":388417,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417850,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UQGAAZ"}],"country":"United States","state":"Louisiana","county":"Saint Tammany 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Tammany\",\"state\":\"LA\"}}]}","volume":"55","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glorioso, Brad 0000-0002-5400-7414","orcid":"https://orcid.org/0000-0002-5400-7414","contributorId":203421,"corporation":false,"usgs":true,"family":"Glorioso","given":"Brad","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":821796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waddle, Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":209861,"corporation":false,"usgs":true,"family":"Waddle","given":"Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":821797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muse, Lindy J.","contributorId":172438,"corporation":false,"usgs":false,"family":"Muse","given":"Lindy","email":"","middleInitial":"J.","affiliations":[{"id":27041,"text":"Cherokee at USGS-WARC Lafayette","active":true,"usgs":false}],"preferred":false,"id":821798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Godfrey, Sidney T","contributorId":222188,"corporation":false,"usgs":false,"family":"Godfrey","given":"Sidney T","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":821799,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223351,"text":"70223351 - 2021 - Population estimates and trends of three Maui Island-endemic Hawaiian Honeycreepers","interactions":[],"lastModifiedDate":"2021-08-24T12:51:04.010857","indexId":"70223351","displayToPublicDate":"2021-06-11T07:48:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Population estimates and trends of three Maui Island-endemic Hawaiian Honeycreepers","docAbstract":"

Population monitoring is critical for informing the management and conservation of rare Hawaiian forest birds. In 2017, we used point-transect distance sampling methods to estimate population densities of birds on Haleakalā Volcano on east Maui island. We estimated the populations and ranges of three island-endemic Hawaiian honeycreepers, including the endangered ‘Ākohekohe (Palmeria dolei), the endangered Kiwikiu (Maui Parrotbill; Pseudonestor xanthophrys), and the Maui ʻAlauahio (Paroreomyza montana newtoni). We examined population trends back to 1980, and our 2017 density estimates were the lowest ever recorded for each species. Most concerning was the status of Kiwikiu, with a 71% decline in population since 2001 to a current population of 157 (95% CI 44–312) birds. The population of ‘Ākohekohe similarly decreased by 78% to a current population of 1768 (1193–2411) birds. For both species, population declines were due to declines in density and contraction of ranges from lower elevations. Both species are now restricted to ranges of less than 3000 ha. We surveyed ~ 91% of the range of Maui ‘Alauahio and estimated a population of 99,060 (88,502–106,954) birds, a 41% decrease since the highest estimate in 1992. Contraction of ranges to higher elevations is consistent with evidence that the impacts of avian malaria are being exacerbated by global warming trends. Our results indicate that the landscape control of either avian malaria transmission or its vector (Culex mosquitoes) will be a pre-requisite to preventing the extinction of endemic forest birds in Hawaii.

","language":"English","publisher":"Wiley","doi":"10.1111/jofo.12364","usgsCitation":"Judge, S., Warren, C.C., Camp, R.J., Berthold, L.K., Mounce, H., Hart, P.J., and Monello, R.J., 2021, Population estimates and trends of three Maui Island-endemic Hawaiian Honeycreepers: Journal of Field Ornithology, v. 92, no. 2, p. 115-126, https://doi.org/10.1111/jofo.12364.","productDescription":"12 p.","startPage":"115","endPage":"126","ipdsId":"IP-124720","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":451922,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jofo.12364","text":"Publisher Index Page"},{"id":388410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.42333984375,\n 18.823116948090494\n ],\n [\n -154.51171875,\n 18.823116948090494\n ],\n [\n -154.51171875,\n 20.447602397594167\n ],\n [\n -156.42333984375,\n 20.447602397594167\n ],\n [\n -156.42333984375,\n 18.823116948090494\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"92","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Judge, Seth 0000-0003-3832-3246","orcid":"https://orcid.org/0000-0003-3832-3246","contributorId":189965,"corporation":false,"usgs":false,"family":"Judge","given":"Seth","email":"","affiliations":[],"preferred":false,"id":821823,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warren, Christopher C","contributorId":264665,"corporation":false,"usgs":false,"family":"Warren","given":"Christopher","email":"","middleInitial":"C","affiliations":[{"id":54533,"text":"Maui Forest Bird Recovery Project, Pacific Cooperative Studies Unit, University of Hawai‘i at Manoa","active":true,"usgs":false}],"preferred":false,"id":821824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":821825,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Berthold, Laura K","contributorId":264666,"corporation":false,"usgs":false,"family":"Berthold","given":"Laura","email":"","middleInitial":"K","affiliations":[{"id":54533,"text":"Maui Forest Bird Recovery Project, Pacific Cooperative Studies Unit, University of Hawai‘i at Manoa","active":true,"usgs":false}],"preferred":false,"id":821826,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mounce, Hanna L.","contributorId":253154,"corporation":false,"usgs":false,"family":"Mounce","given":"Hanna L.","affiliations":[{"id":13352,"text":"Maui Forest Bird Recovery Project","active":true,"usgs":false}],"preferred":false,"id":821827,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hart, Patrick J.","contributorId":147728,"corporation":false,"usgs":false,"family":"Hart","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":821828,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Monello, Ryan J.","contributorId":184143,"corporation":false,"usgs":false,"family":"Monello","given":"Ryan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":821829,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70223726,"text":"70223726 - 2021 - A review of sand detachment in modern deep marine environments: Analogues for upslope stratigraphic traps","interactions":[],"lastModifiedDate":"2021-09-07T13:18:34.511432","indexId":"70223726","displayToPublicDate":"2021-06-11T07:47:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"A review of sand detachment in modern deep marine environments: Analogues for upslope stratigraphic traps","docAbstract":"

Isolated, detached sands provide opportunities for large-volume stratigraphic traps in many deepwater petroleum systems. Here we provide a review of the different types of sandbody detachments based on published data from the modern-day seafloor and recent (generally Quaternary-present), shallow-buried strata. Detachment mechanisms can be classified based on their timing of formation relative to deposition of the detached sandbody as well as their process of formation. Syndepositional detachment mechanisms include flow transformation associated with slope failure (Class 1), turbidity current erosion (Class 2), and contourite deposition (Class 3). Post-depositional detachment is related to subsequent erosive processes and truncation of the pre-existing sandbody, either by submarine channels (Class 4), mass-transport events (Class 5), post-depositional sliding or faulting (Class 6) or bottom currents (Class 7). Examples of each of these mechanisms are identified on the modern seafloor, and show that detached sandbodies can form at different locations along the continental slope and rise (from upper slope to basin floor), and between or within different architectural elements (i.e., canyon, channels and lobes). This variation in formation style results in detached sands of highly variable sizes (tens to hundreds of kilometres) and geometries across and along the depositional profile, which are dependent upon the erosive and/or depositional processes involved, as well as the seafloor topography of the area in question. Whilst modern seafloor systems may not always represent the final stratigraphic architecture in the subsurface, they provide important insights into the development of detached sandbodies and therefore serve as potential analogues for subsurface stratigraphic traps.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2021.105184","usgsCitation":"Counts, J.W., Amy, L., Georgiopoulou, A., and Haughton, P., 2021, A review of sand detachment in modern deep marine environments: Analogues for upslope stratigraphic traps: Marine and Petroleum Geology, v. 132, 105184, 15 p., https://doi.org/10.1016/j.marpetgeo.2021.105184.","productDescription":"105184, 15 p.","ipdsId":"IP-126445","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":451923,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://cris.brighton.ac.uk/ws/files/30716190/Counts_et_al_2021_MPG_compressed.pdf","text":"External Repository"},{"id":388834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"132","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Counts, John W. 0000-0001-7374-6928","orcid":"https://orcid.org/0000-0001-7374-6928","contributorId":248711,"corporation":false,"usgs":true,"family":"Counts","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":822499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amy, Lawrence","contributorId":265269,"corporation":false,"usgs":false,"family":"Amy","given":"Lawrence","email":"","affiliations":[],"preferred":false,"id":822500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Georgiopoulou, Aggeliki","contributorId":265270,"corporation":false,"usgs":false,"family":"Georgiopoulou","given":"Aggeliki","affiliations":[],"preferred":false,"id":822501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haughton, Peter","contributorId":265271,"corporation":false,"usgs":false,"family":"Haughton","given":"Peter","email":"","affiliations":[],"preferred":false,"id":822502,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221540,"text":"70221540 - 2021 - Identification of Aphanomyces invadans, the cause of epizootic ulcerative syndrome, in smallmouth bass (Micropterus dolomieu) from the Cheat River, West Virginia, USA","interactions":[],"lastModifiedDate":"2021-09-14T16:14:46.156546","indexId":"70221540","displayToPublicDate":"2021-06-11T07:24:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2286,"text":"Journal of Fish Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Identification of Aphanomyces invadans, the cause of epizootic ulcerative syndrome, in smallmouth bass (Micropterus dolomieu) from the Cheat River, West Virginia, USA","title":"Identification of Aphanomyces invadans, the cause of epizootic ulcerative syndrome, in smallmouth bass (Micropterus dolomieu) from the Cheat River, West Virginia, USA","docAbstract":"

The oomycete Aphanomyces invadans (Saprolegniales, Oomycetes), the cause of epizootic ulcerative syndrome (EUS), is an OIE (World Organization for Animal Health) reportable pathogen, capable of infecting many fish species worldwide in both freshwater and estuarine environments (Iberahim et al. 2018). Since the discovery of EUS in Japan in 1971 (Egusa and Masuda 1971), it has spread globally and caused substantial fish mortalities and economic losses (Lilley et al. 1998). Cases in the United States have included lesions initially named ulcerative mycosis of Atlantic menhaden Brevoortia tyrannus (Noga et al. 1988) along the Atlantic coast and later confirmed as A. invadans in menhaden from the Chesapeake Bay (Blazer et al. 1999). It has also been reported in several freshwater and estuarine fishes from Florida, including largemouth bass Micropterus salmoides (Sosa et al. 2007) and channel catfish, black bullhead, and bluegill from recreational ponds in Louisiana (Hawke et al. 2003).This communication reports the finding of A. invadans in smallmouth bass Micropterus dolomieu from the Cheat River, West Virginia. During fish health assessments in October 2020, smallmouth bass with grossly observable skin lesions were determined to be infected with A. invadans. We believe this is the first report of A. invadans infection in smallmouth bass and it was not observed during previous health assessments in this region.

","language":"English","publisher":"Wiley","doi":"10.1111/jfd.13468","usgsCitation":"Walsh, H.L., Blazer, V., and Mazik, P.M., 2021, Identification of Aphanomyces invadans, the cause of epizootic ulcerative syndrome, in smallmouth bass (Micropterus dolomieu) from the Cheat River, West Virginia, USA: Journal of Fish Diseases, v. 44, no. 10, p. 1639-1641, https://doi.org/10.1111/jfd.13468.","productDescription":"3 p.","startPage":"1639","endPage":"1641","ipdsId":"IP-129024","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":386645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Cheat River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.16448974609375,\n 39.39587712612034\n ],\n [\n -79.84039306640625,\n 39.39587712612034\n ],\n [\n -79.84039306640625,\n 39.71775084250472\n ],\n [\n -80.16448974609375,\n 39.71775084250472\n ],\n [\n -80.16448974609375,\n 39.39587712612034\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","issue":"10","noUsgsAuthors":false,"publicationDate":"2021-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Walsh, Heather L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":4696,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather","email":"hwalsh@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":817997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":818038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":818039,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229492,"text":"70229492 - 2021 - Caution is warranted when using animal space-use and movement to infer behavioral states","interactions":[],"lastModifiedDate":"2022-03-09T12:58:06.746424","indexId":"70229492","displayToPublicDate":"2021-06-11T06:53:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Caution is warranted when using animal space-use and movement to infer behavioral states","docAbstract":"

Background

Identifying the behavioral state for wild animals that can’t be directly observed is of growing interest to the ecological community. Advances in telemetry technology and statistical methodologies allow researchers to use space-use and movement metrics to infer the underlying, latent, behavioral state of an animal without direct observations. For example, researchers studying ungulate ecology have started using these methods to quantify behaviors related to mating strategies. However, little work has been done to determine if assumed behaviors inferred from movement and space-use patterns correspond to actual behaviors of individuals.

Methods

Using a dataset with male and female white-tailed deer location data, we evaluated the ability of these two methods to correctly identify male-female interaction events (MFIEs). We identified MFIEs using the proximity of their locations in space as indicators of when mating could have occurred. We then tested the ability of utilization distributions (UDs) and hidden Markov models (HMMs) rendered with single sex location data to identify these events.

Results

For white-tailed deer, male and female space-use and movement behavior did not vary consistently when with a potential mate. There was no evidence that a probability contour threshold based on UD volume applied to an individual’s UD could be used to identify MFIEs. Additionally, HMMs were unable to identify MFIEs, as single MFIEs were often split across multiple states and the primary state of each MFIE was not consistent across events.

Conclusions

Caution is warranted when interpreting behavioral insights rendered from statistical models applied to location data, particularly when there is no form of validation data. For these models to detect latent behaviors, the individual needs to exhibit a consistently different type of space-use and movement when engaged in the behavior. Unvalidated assumptions about that relationship may lead to incorrect inference about mating strategies or other behaviors.

","language":"English","publisher":"Springer","doi":"10.1186/s40462-021-00264-8","usgsCitation":"Buderman, F.E., Gingery, T.M., Diefenbach, D.R., Gigliotti, L., Begley-Miller, D., McDill, M.E., Wallingford, B., Rosenberry, C., and Drohan, P.J., 2021, Caution is warranted when using animal space-use and movement to infer behavioral states: Movement Ecology, v. 9, 30, 12 p., https://doi.org/10.1186/s40462-021-00264-8.","productDescription":"30, 12 p.","ipdsId":"IP-126195","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":451927,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-021-00264-8","text":"Publisher Index Page"},{"id":396898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2021-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Buderman, Frances E.","contributorId":171634,"corporation":false,"usgs":false,"family":"Buderman","given":"Frances","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":837600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gingery, Tess M.","contributorId":204865,"corporation":false,"usgs":false,"family":"Gingery","given":"Tess","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":837601,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":837599,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gigliotti, Laura C.","contributorId":204828,"corporation":false,"usgs":false,"family":"Gigliotti","given":"Laura C.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":837602,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Begley-Miller, Danielle","contributorId":288270,"corporation":false,"usgs":false,"family":"Begley-Miller","given":"Danielle","affiliations":[{"id":54482,"text":"Teatown Lake Reservation","active":true,"usgs":false}],"preferred":false,"id":837603,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDill, Marc E.","contributorId":264499,"corporation":false,"usgs":false,"family":"McDill","given":"Marc","email":"","middleInitial":"E.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":837654,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wallingford, Bret D.","contributorId":276207,"corporation":false,"usgs":false,"family":"Wallingford","given":"Bret D.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":837604,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rosenberry, Christopher S.","contributorId":276209,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher S.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":837605,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Drohan, Patrick J.","contributorId":190141,"corporation":false,"usgs":false,"family":"Drohan","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":837655,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70221411,"text":"70221411 - 2021 - Diet composition and body condition of polar bears (Ursus maritimus) in relation to sea ice habitat in the Canadian High Arctic","interactions":[],"lastModifiedDate":"2021-06-30T19:05:36.806175","indexId":"70221411","displayToPublicDate":"2021-06-11T06:52:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3093,"text":"Polar Biology","active":true,"publicationSubtype":{"id":10}},"title":"Diet composition and body condition of polar bears (Ursus maritimus) in relation to sea ice habitat in the Canadian High Arctic","docAbstract":"

Polar bears (Ursus maritimus) rely on sea ice for hunting marine mammal prey. Declining sea ice conditions associated with climate warming have negatively affected polar bears, especially in the southern portion of their range. At higher latitudes, the transition from multi-year ice to thinner annual ice has been hypothesized to increase biological productivity and potentially improve polar bear foraging conditions. To investigate this possibility, we used quantitative fatty acid signature analysis to characterize the diet composition of 148 polar bears in two high-latitude subpopulations from 2012 to 2014: (1) Viscount Melville Sound, where little is known about marine mammal ecology, and (2) Northern Beaufort Sea, a subpopulation considered stable with comparatively more ecological data. We used adipose tissue lipid content as an index of body condition. To characterize long-term habitat conditions, we examined trends in sea ice metrics from 1979 to 2014 in both regions. Although the diets of bears in both subpopulations were dominated by ringed seal (Pusa hispida, mean biomass consumption = 45%), bears in Viscount Melville Sound showed higher proportional consumption of beluga whale (Delphinapterus leucas; mean biomass consumption = 37%) than any other polar bear subpopulation studied to date. Although the three-year duration of our study precludes long-term insights, relatively lighter sea ice conditions in Viscount Melville Sound were associated with reduced consumption of preferred prey (i.e., ringed seal), especially among female polar bears. Further, polar bears in Viscount Melville sound were in poorer body condition than those in the Northern Beaufort Sea. Our results do not indicate that declining sea ice has had any positive effect on polar bear foraging at high-latitudes.

","language":"English","publisher":"Springer","doi":"10.1007/s00300-021-02891-8","usgsCitation":"Florko, K.R., Thiemann, G.W., Bromaghin, J.F., and Richardson, E.S., 2021, Diet composition and body condition of polar bears (Ursus maritimus) in relation to sea ice habitat in the Canadian High Arctic: Polar Biology, v. 44, p. 1445-1456, https://doi.org/10.1007/s00300-021-02891-8.","productDescription":"12 p.","startPage":"1445","endPage":"1456","ipdsId":"IP-105864","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":386489,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Canadian High Arctic","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.03515625,\n 64.39693778132846\n ],\n [\n -105.29296874999999,\n 64.39693778132846\n ],\n [\n -105.29296874999999,\n 72.28906720017675\n ],\n [\n -126.03515625,\n 72.28906720017675\n ],\n [\n -126.03515625,\n 64.39693778132846\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","noUsgsAuthors":false,"publicationDate":"2021-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Florko, Katie R. N.","contributorId":239941,"corporation":false,"usgs":false,"family":"Florko","given":"Katie","email":"","middleInitial":"R. N.","affiliations":[{"id":48064,"text":"Department of Biology, York University","active":true,"usgs":false}],"preferred":false,"id":817622,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thiemann, Gregory W.","contributorId":83023,"corporation":false,"usgs":false,"family":"Thiemann","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":27291,"text":"York University, Toronto, ON","active":true,"usgs":false}],"preferred":false,"id":817623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":817624,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richardson, Evan S.","contributorId":139901,"corporation":false,"usgs":false,"family":"Richardson","given":"Evan","email":"","middleInitial":"S.","affiliations":[{"id":6962,"text":"Science and Technology Branch, Environment Canada","active":true,"usgs":false}],"preferred":false,"id":817625,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221339,"text":"sir20215016 - 2021 - Assessment of streamflow and water quality in the Upper Yampa River Basin, Colorado, 1992–2018","interactions":[],"lastModifiedDate":"2021-06-11T12:06:48.298229","indexId":"sir20215016","displayToPublicDate":"2021-06-10T17:00:00","publicationYear":"2021","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":"2021-5016","displayTitle":"Assessment of Streamflow and Water Quality in the Upper Yampa River Basin, Colorado, 1992–2018","title":"Assessment of streamflow and water quality in the Upper Yampa River Basin, Colorado, 1992–2018","docAbstract":"

The Upper Yampa River Basin drains approximately 2,100 square miles west of the Continental Divide in north-western Colorado. There is a growing need to understand potential changes in the quantity and quality of water resources as the basin is undergoing increasing land and water development to support growing municipal, industrial, and recreational needs. The U.S. Geological Survey, in cooperation with stakeholders in the Upper Yampa River Basin water community, began a study to characterize and identify changes in streamflow and selected water-quality constituents, including  suspended sediment, Kjeldahl nitrogen, total nitrogen, total phosphorus, and orthophosphate, in the basin. This study used streamflow and water-quality data from selected U.S. Geological Survey sites to provide a better understanding of how major factors, including land use, climate change, and geological features, may influence streamflow and water quality.

Analysis of long-term (1910–2018) and short-term (1992–2018) records of streamflow at main-stem Yampa River and tributary sites indicate downward trends in one or more streamflow statistics, including 1-day maximum, mean, and 7-day minimum. Long-term downward trends in daily mean streamflow in April (22 percent overall) at Yampa River at Steamboat Springs, Colorado, correspond to observed changes in streamflow documented across western North America and the Colorado River Basin that are predominately associated with changes in snowmelt runoff and temperatures. During the short-term period of analysis, decreases in streamflow at main-stem Yampa River and some tributary sites are likely related to changes in consumptive use and reservoir management or, at sites with no upstream flow impoundments, changes in irrigation diversions and climate.

Concentrations of water-quality constituents were typically highest in spring (March, April, and May) during the early snowmelt runoff period as material that is washed off the land surface drains into streams. Highest concentrations occurred slightly later, in May, June, and July, at Yampa River above Stagecoach Reservoir, Colo., and slightly earlier, in February and March at Yampa River at Milner, Colo., indicating that these sites may have different or additional sources of phosphorus from upstream inputs. Yampa River at Milner, Colo., and Yampa River above Elkhead Creek, Colo., had the highest net yields of suspended sediment, Kjeldahl nitrogen, and total phosphorus, and are likely influenced by land use and erosion as the basins of both of these sites are underlain by highly erodible Cretaceous shales.

Upward trends in estimated Kjeldahl nitrogen and total phosphorus concentrations and loads were found at Yampa River at Steamboat Springs, Colo. From 1999 to 2018, the Kjeldahl nitrogen concentration increased by 10 percent or 0.035 milligram per liter, and load increased by 22 percent or 26 tons. Total phosphorus concentration increased by 20 percent or 0.0081 milligram per liter, and loads increased by 41 percent or 6.2 tons. Decreases in streamflow and changes in land use may contribute to these trends.

During multiple summer sampling events at Stagecoach Reservoir, the physical and chemical factors indicated conditions conducive to cyanobacterial blooms, including surface-water temperatures greater than 20 degrees Celsius and total phosphorus and total nitrogen concentrations in exceedance of Colorado Department of Public Health and Environment interim concentrations for water-quality standards. Local geological features (predominately sandstones and shales) and additional inputs from upstream land use likely contribute to the elevated nutrient conditions in Stagecoach Reservoir.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215016","isbn":"978-1-4113-4402-0","collaboration":"Prepared in cooperation with Upper Yampa River Watershed Group, Upper Yampa Water Conservancy District, Colorado Water Conservation Board, Yampa-White-Green Basin Roundtable, Mount Werner Water and Sanitation District, Routt County, Colorado, and the city of Steamboat Springs, Colorado","usgsCitation":"Day, N.K., 2021, Assessment of streamflow and water quality in the Upper Yampa River Basin, Colorado, 1992–2018: U.S. Geological Survey Scientific Investigations Report 2021–5016, 45 p., https://doi.org/10.3133/sir20215016.","productDescription":"Report: vii, 45 p.; Data Release","onlineOnly":"N","ipdsId":"IP-118673","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":386393,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5016/coverthb.jpg"},{"id":386394,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5016/sir20215016.pdf","text":"Report","size":"4.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5016"},{"id":386395,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L7S3NQ","text":"USGS data release","linkHelpText":"Input and output data from streamflow and water-quality regression models used to characterize streamflow and water-quality conditions in the Upper Yampa River Basin, Colorado, from 1992-2018"}],"country":"United States","state":"Colorado","otherGeospatial":"Upper Yampa River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.314453125,\n 40.052847601823984\n ],\n [\n -106.424560546875,\n 40.052847601823984\n ],\n [\n -106.424560546875,\n 40.9964840143779\n ],\n [\n -107.314453125,\n 40.9964840143779\n ],\n [\n -107.314453125,\n 40.052847601823984\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225-0046

","tableOfContents":"","publishedDate":"2021-06-10","noUsgsAuthors":false,"publicationDate":"2021-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Day, Natalie K. 0000-0002-8768-5705","orcid":"https://orcid.org/0000-0002-8768-5705","contributorId":207302,"corporation":false,"usgs":true,"family":"Day","given":"Natalie","middleInitial":"K.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817370,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70221322,"text":"sir20215051 - 2021 - Estimating Piacenzian sea surface temperature using an alkenone-calibrated transfer function","interactions":[],"lastModifiedDate":"2021-06-11T22:34:30.076675","indexId":"sir20215051","displayToPublicDate":"2021-06-10T13:12:07","publicationYear":"2021","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":"2021-5051","displayTitle":"Estimating Piacenzian Sea Surface Temperature Using an Alkenone-Calibrated Transfer Function","title":"Estimating Piacenzian sea surface temperature using an alkenone-calibrated transfer function","docAbstract":"

Stationarity of environmental preferences is a primary assumption required for any paleoenvironmental reconstruction using fossil materials based upon calibration to modern organisms. Confidence in this assumption decreases the further back in time one goes, and the validity of the assumption that species temperature tolerances have not changed over time has been challenged in Pliocene studies. We use paired UK′37  (unsaturated ketones with 37 carbon atoms) sea surface temperature (SST) and faunal assemblage data to directly calibrate North Atlantic Piacenzian planktonic foraminifer assemblages to Piacenzian alkenone paleotemperature estimates to provide an alternative paleoceanographic reconstruction approach that does not rely on stationarity. In doing so, we extend Pliocene SST estimates to sites where only quantitative faunal assemblage data were previously available and improve the spatial resolution of the North Atlantic SST reconstruction.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215051","usgsCitation":"Dowsett, H.J., Robinson, M.M., and Foley, K.M., 2021, Estimating Piacenzian sea surface temperature using an alkenone-calibrated transfer function: U.S. Geological Survey Scientific Investigations Report 2021–5051, 17 p., https://doi.org/10.3133/sir20215051.","productDescription":"Report: vi, 17 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-114329","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":386375,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.1038/sdata.2015.76","text":"Scientific Data","linkHelpText":"— A global planktic foraminifer census data set for the Pliocene ocean"},{"id":386376,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7959G1S","text":"USGS data release","linkHelpText":"PRISM late Pliocene (Piacenzian) alkenone-derived SST data"},{"id":386374,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5051/sir20215051.pdf","text":"Report","size":"1.90 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5051"},{"id":386373,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5051/coverthb.jpg"},{"id":386377,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://www.ncdc.noaa.gov/paleo/study/27310","text":"National Oceanic and Atmospheric Administration, National Centers for Environmental Information","linkHelpText":"— A global planktic foraminifer census data set for the Pliocene ocean, addendum"}],"contact":"

Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2021-06-10","noUsgsAuthors":false,"publicationDate":"2021-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":817300,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Marci M. 0000-0002-9200-4097 mmrobinson@usgs.gov","orcid":"https://orcid.org/0000-0002-9200-4097","contributorId":2082,"corporation":false,"usgs":true,"family":"Robinson","given":"Marci","email":"mmrobinson@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":817301,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foley, Kevin M. 0000-0003-1013-462X kfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-1013-462X","contributorId":2543,"corporation":false,"usgs":true,"family":"Foley","given":"Kevin","email":"kfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":817302,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221704,"text":"70221704 - 2021 - Lateral shoreline erosion and shore-proximal sediment deposition on a coastal marsh from seasonal, storm and decadal measurements","interactions":[],"lastModifiedDate":"2025-05-14T13:28:26.269202","indexId":"70221704","displayToPublicDate":"2021-06-10T09:59:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Lateral shoreline erosion and shore-proximal sediment deposition on a coastal marsh from seasonal, storm and decadal measurements","docAbstract":"

The persistence of coastal marsh is dependent on its ability to maintain elevation relative to sea level, particularly for marshes experiencing high rates of shoreline erosion due to wave-attack, storms, and sea level rise. Sediments eroded at the marsh edge are either delivered onto the marsh platform or into the estuary, the latter resulting in a net loss of marsh sediments and soil carbon. Knowledge on the timing, pattern, and quantity of sediment deposition versus shoreline erosion along the marsh-estuary interface is critical for evaluating the overall health and vulnerability of coastal marshes to future scenarios of sea level rise and for estimating sediment budgets. Here we examined marsh shoreline erosion and sediment deposition for marsh sites experiencing a range of shoreline erosion rates and different levels of wind-wave exposure within the Grand Bay National Estuarine Research Reserve and Wildlife Refuge in Mississippi. We developed a method for calculating an erosion-deposition sediment budget using marsh elevation profiles, shoreline erosion rate, and sediment deposition measurements. Sediment budgets were calculated at four sites with varying shoreline erosion rates. Much of the sediment eroded at the marsh edge can be accounted for as marsh platform deposition, except at the most erosive site, suggesting a possible erosion threshold where eroded sediment mass is greater than platform deposition. Consistent with other studies of marsh creeks, sediment delivery to the marsh platform appears to be largely driven by wave climate. These data suggest that for erosive bay-estuarine shorelines, sediment delivered into the marsh is largely concentrated near the marsh shoreline, although shoreline erosion does not always result in a net loss of sediments from the marsh system in either decadal or annual assessments.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2021.107829","usgsCitation":"Smith, K., Terrano, J.F., Khan, N.S., Smith, C., and Pitchford, J.L., 2021, Lateral shoreline erosion and shore-proximal sediment deposition on a coastal marsh from seasonal, storm and decadal measurements: Geomorphology, v. 389, 107829, 16 p., https://doi.org/10.1016/j.geomorph.2021.107829.","productDescription":"107829, 16 p.","ipdsId":"IP-122214","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451930,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2021.107829","text":"Publisher Index Page"},{"id":386866,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Grand Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.76953125,\n 30.246018268082167\n ],\n [\n -88.39736938476562,\n 30.246018268082167\n ],\n [\n -88.39736938476562,\n 30.527962116594164\n ],\n [\n -88.76953125,\n 30.527962116594164\n ],\n [\n -88.76953125,\n 30.246018268082167\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"389","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Kathryn E.L. 0000-0002-7521-7875 kelsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-7521-7875","contributorId":173264,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E.L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terrano, Joseph F. 0000-0003-3060-7682 jterrano@usgs.gov","orcid":"https://orcid.org/0000-0003-3060-7682","contributorId":173263,"corporation":false,"usgs":true,"family":"Terrano","given":"Joseph","email":"jterrano@usgs.gov","middleInitial":"F.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818475,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Khan, Nicole S.","contributorId":213942,"corporation":false,"usgs":false,"family":"Khan","given":"Nicole","email":"","middleInitial":"S.","affiliations":[{"id":38935,"text":"Asian School of the Environment, Nanyang Technological University, 50 Nanyang Ave., Singapore 639798","active":true,"usgs":false}],"preferred":false,"id":818476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818477,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pitchford, Jonathan L 0000-0003-1168-5087","orcid":"https://orcid.org/0000-0003-1168-5087","contributorId":260687,"corporation":false,"usgs":false,"family":"Pitchford","given":"Jonathan","email":"","middleInitial":"L","affiliations":[{"id":52643,"text":"Grand Bay National Estuarine Research Reserve","active":true,"usgs":false}],"preferred":false,"id":818478,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221587,"text":"70221587 - 2021 - The biophysical role of water and ice within permafrost nearing collapse: Insights from novel geophysical observations","interactions":[],"lastModifiedDate":"2021-06-30T19:19:52.483157","indexId":"70221587","displayToPublicDate":"2021-06-10T09:20:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7357,"text":"JGR Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"The biophysical role of water and ice within permafrost nearing collapse: Insights from novel geophysical observations","docAbstract":"

The impact of permafrost thaw on hydrologic, thermal, and biotic processes remains uncertain, in part due to limitations in subsurface measurement capabilities. To better understand subsurface processes in thermokarst environments, we collocated geophysical and biogeochemical instruments along a thaw gradient between forested permafrost and collapse-scar bogs at the Alaska Peatland Experiment (APEX) site near Fairbanks, Alaska. Ambient seismic noise monitoring provided continuous high-temporal resolution measurements of water and ice saturation changes. Maps of seismic velocity change identified areas of large summertime velocity reductions nearest the youngest bog, indicating potential thaw and expansion at the bog margin. These results corresponded well with complementary borehole nuclear magnetic resonance measurements of unfrozen water content with depth, which showed permafrost soils nearest the bog edges contained the largest amount of unfrozen water along the study transect, up to 25% by volume. In situ measurements of methane within permafrost soils revealed high concentrations at these bog-edge locations, up to 30% soil gas. Supra-permafrost talik zones were observed at the bog margins, indicating talik formation and perennial liquid water may drive lateral bog expansion and enhanced permafrost carbon losses preceding thaw. Comparison of seismic monitoring with wintertime surface carbon dioxide fluxes revealed differential responses depending on time and proximity to the bogs, capturing the controlling influence of subsurface water and ice on microbial activity and surficial emissions. This study demonstrates a multidisciplinary approach for gaining new understanding of how subsurface physical properties influence greenhouse gas production, emissions, and thermokarst development.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JF006104","usgsCitation":"James, S.R., Minsley, B.J., McFarland, J., Euskirchen, E.S., Edgar, C.W., and Waldrop, M., 2021, The biophysical role of water and ice within permafrost nearing collapse: Insights from novel geophysical observations: JGR Earth Surface, v. 126, no. 6, e2021JF006104, 21 p., https://doi.org/10.1029/2021JF006104.","productDescription":"e2021JF006104, 21 p.","ipdsId":"IP-129192","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":451931,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021jf006104","text":"Publisher Index Page"},{"id":436316,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9455D1K","text":"USGS data release","linkHelpText":"Permafrost greenhouse gas and microbial data from the Alaska Peatland Experiment (APEX) 2017 to 2019"},{"id":386697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Fairbanks","otherGeospatial":"Alaska Peatland Experiment (APEX) site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.293212890625,\n 64.35893097894458\n ],\n [\n -147.667236328125,\n 64.35893097894458\n ],\n [\n -147.667236328125,\n 64.88160222555004\n ],\n [\n -149.293212890625,\n 64.88160222555004\n ],\n [\n -149.293212890625,\n 64.35893097894458\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-25","publicationStatus":"PW","contributors":{"authors":[{"text":"James, Stephanie R. 0000-0001-5715-253X","orcid":"https://orcid.org/0000-0001-5715-253X","contributorId":260620,"corporation":false,"usgs":true,"family":"James","given":"Stephanie","email":"","middleInitial":"R.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":818202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minsley, Burke J. 0000-0003-1689-1306","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":248573,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"","middleInitial":"J.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":818203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McFarland, Jack 0000-0001-9672-8597","orcid":"https://orcid.org/0000-0001-9672-8597","contributorId":214819,"corporation":false,"usgs":true,"family":"McFarland","given":"Jack","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":818204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Euskirchen, Eugenie S. 0000-0002-0848-4295","orcid":"https://orcid.org/0000-0002-0848-4295","contributorId":173730,"corporation":false,"usgs":false,"family":"Euskirchen","given":"Eugenie","email":"","middleInitial":"S.","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":818205,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edgar, Colin W. 0000-0002-7026-8358","orcid":"https://orcid.org/0000-0002-7026-8358","contributorId":260621,"corporation":false,"usgs":false,"family":"Edgar","given":"Colin","email":"","middleInitial":"W.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":818206,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waldrop, Mark 0000-0003-1829-7140","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":216758,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","affiliations":[],"preferred":true,"id":818207,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222443,"text":"70222443 - 2021 - Evaluation of remote mapping techniques for earthquake-triggered landslide inventories in an urban subarctic environment: A case study of the 2018 Anchorage, Alaska Earthquake","interactions":[],"lastModifiedDate":"2021-07-30T14:11:27.923693","indexId":"70222443","displayToPublicDate":"2021-06-10T09:08:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9121,"text":"Frontiers Earth Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of remote mapping techniques for earthquake-triggered landslide inventories in an urban subarctic environment: A case study of the 2018 Anchorage, Alaska Earthquake","docAbstract":"

Earthquake-induced landslide inventories can be generated using field observations but doing so can be challenging if the affected landscape is large or inaccessible after an earthquake. Remote sensing data can be used to help overcome these limitations. The effectiveness of remotely sensed data to produce landslide inventories, however, is dependent on a variety of factors, such as the extent of coverage, timing, and data quality, as well as environmental factors such as atmospheric interference (e.g., clouds, water vapor) or snow and vegetation cover. With these challenges in mind, we use a combination of field observations and remote sensing data from multispectral, light detection and ranging (lidar), and synthetic aperture radar (SAR) sensors to produce a ground failure inventory for the urban areas affected by the 2018 magnitude (Mw) 7.1 Anchorage, Alaska earthquake. The earthquake occurred during late November at high latitude (∼61°N), and the lack of sunlight, persistent cloud cover, and snow cover that occurred after the earthquake made remote mapping challenging for this event. Despite these challenges, 43 landslides were manually mapped and classified using a combination of the datasets mentioned previously. Using this manually compiled inventory, we investigate the individual performance and reliability of three remote sensing techniques in this environment not typically hospitable to remotely sensed mapping. We found that differencing pre- and post-event normalized difference vegetation index maps and lidar worked best for identifying soil slumps and rapid soil flows, but not as well for small soil slides, soil block slides and rock falls. The SAR-based methods did not work well for identifying any landslide types because of high noise levels likely related to snow. Some landslides, especially those that resulted in minor surface displacement, were identifiable only from the field observations. This work highlights the importance of the rapid collection of field observations and provides guidance for future mappers on which techniques, or combination of techniques, will be most effective at remotely mapping landslides in a subarctic and urban environment.

","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2021.673137","usgsCitation":"Martinez, S.N., Schaefer, L.N., Allstadt, K.E., and Thompson, E.M., 2021, Evaluation of remote mapping techniques for earthquake-triggered landslide inventories in an urban subarctic environment: A case study of the 2018 Anchorage, Alaska Earthquake: Frontiers Earth Science Journal, v. 9, 673137, 13 p., https://doi.org/10.3389/feart.2021.673137.","productDescription":"673137, 13 p.","ipdsId":"IP-129070","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":451933,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2021.673137","text":"Publisher Index Page"},{"id":436317,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S5PVON","text":"USGS data release","linkHelpText":"Initial Observations of Landslides triggered by the 2018 Anchorage, Alaska earthquake"},{"id":387597,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Anchorage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -151.2158203125,\n 60.71619779357714\n ],\n [\n -148.53515625,\n 60.71619779357714\n ],\n [\n -148.53515625,\n 61.71070595883174\n ],\n [\n -151.2158203125,\n 61.71070595883174\n ],\n [\n -151.2158203125,\n 60.71619779357714\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2021-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Martinez, Sabrina N. 0000-0002-1812-5990","orcid":"https://orcid.org/0000-0002-1812-5990","contributorId":237051,"corporation":false,"usgs":true,"family":"Martinez","given":"Sabrina","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schaefer, Lauren N. 0000-0003-3216-7983","orcid":"https://orcid.org/0000-0003-3216-7983","contributorId":241997,"corporation":false,"usgs":true,"family":"Schaefer","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820062,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820063,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222072,"text":"70222072 - 2021 - Spatial ecology of invasive Burmese pythons in southwestern Florida","interactions":[],"lastModifiedDate":"2021-07-16T14:09:48.012348","indexId":"70222072","displayToPublicDate":"2021-06-10T09:00:59","publicationYear":"2021","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 ecology of invasive Burmese pythons in southwestern Florida","docAbstract":"

Understanding the spatial ecology of an invasive species is critical for designing effective control programs. Determining and quantifying home range estimates and habitat associations can streamline targeted removal efforts for wide-ranging, cryptic animals. The Burmese python (Python bivittatus) is a large-bodied constrictor snake with an established and expanding invasive population in southern Florida. This apex predator has severely impacted native wildlife across the Greater Everglades ecosystem. However, limited ecological information exists on this invasive species at the landscape level. Here, we present results from a study using radiotelemetry to quantify movements and habitat use patterns of 25 adult Burmese pythons in southwestern Florida, USA, for average periods of 814 d (range: 288–1809). Our objective was to quantify home range size, movement rates, and second- and third-order habitat selection. Mean annual home range size was 7.5 km2 ± 2.9 km2 (95% kernel density estimate), and pythons moved at a maximum mean daily rate of 0.52 km/d. Burmese pythons selected agriculture, freshwater wetland, saline wetland, and upland land cover classes but avoided open water and urban land cover classes. Nest site selection was highest for pythons at an elevation of 1.7 m with nesting hotspots concentrated on the borders of urban and agricultural areas or in sandy forested upland habitats. A broader understanding of the spatial utilization of Burmese pythons will enhance the utility of emerging control strategies across their invaded range.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3564","usgsCitation":"Bartoszek, I.A., Smith, B., Reed, R., and Hart, K., 2021, Spatial ecology of invasive Burmese pythons in southwestern Florida: Ecosphere, v. 12, no. 6, e03564, 19 p., https://doi.org/10.1002/ecs2.3564.","productDescription":"e03564, 19 p.","ipdsId":"IP-120516","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":451934,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3564","text":"Publisher Index Page"},{"id":387224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","county":"Collier County","otherGeospatial":"Collier Seminole State Park, Picayune Strand State Forest, Rookery Bay National Estuarine Research Reserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.815185546875,\n 25.857987767091547\n ],\n [\n -81.43272399902344,\n 25.857987767091547\n ],\n [\n -81.43272399902344,\n 26.19241214758277\n ],\n [\n -81.815185546875,\n 26.19241214758277\n ],\n [\n -81.815185546875,\n 25.857987767091547\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Bartoszek, Ian A.","contributorId":138954,"corporation":false,"usgs":false,"family":"Bartoszek","given":"Ian","email":"","middleInitial":"A.","affiliations":[{"id":12592,"text":"Conservancy of Southwest Florida, Naples, FL","active":true,"usgs":false}],"preferred":false,"id":819437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Brian J. 0000-0002-0531-0492","orcid":"https://orcid.org/0000-0002-0531-0492","contributorId":139672,"corporation":false,"usgs":false,"family":"Smith","given":"Brian J.","affiliations":[{"id":12876,"text":"Cherokee Nation Technology Solutions","active":true,"usgs":false}],"preferred":false,"id":819438,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":152301,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":819439,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":220333,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":819440,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221399,"text":"70221399 - 2021 - A massive rock and ice avalanche caused the 2021 disaster at Chamoli, Indian Himalaya","interactions":[],"lastModifiedDate":"2021-06-14T14:00:27.974633","indexId":"70221399","displayToPublicDate":"2021-06-10T08:18:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"A massive rock and ice avalanche caused the 2021 disaster at Chamoli, Indian Himalaya","docAbstract":"

On 7 Feb 2021, a catastrophic mass flow descended the Ronti Gad, Rishiganga, and Dhauliganga valleys in Chamoli, Uttarakhand, India, causing widespread devastation and severely damaging two hydropower projects. Over 200 people were killed or are missing. Our analysis of satellite imagery, seismic records, numerical model results, and eyewitness videos reveals that ~27x106 m3 of rock and glacier ice collapsed from the steep north face of Ronti Peak. The rock and ice avalanche rapidly transformed into an extraordinarily large and mobile debris flow that transported boulders >20 m in diameter, and scoured the valley walls up to 220 m above the valley floor. The intersection of the hazard cascade with downvalley infrastructure resulted in a disaster, which highlights key questions about adequate monitoring and sustainable development in the Himalaya as well as other remote, high-mountain environments.

","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/science.abh4455","usgsCitation":"Shugar, D.H., Jacquemart, M., Shean, D., Bhushan, S., Upadhyay, K., Sattar, A., Schwanghart, W., McBride, S.K., Van Wyk de Vries, M., Mergili, M., Emmer, A., Deschamps-Berger, C., McDonnell, M., Bhambri, R., Allen, S., Berthier, E., Carrivick, J., Clague, J., Dokukin, M., Dunning, S., Frey, H., Gascoin, S., Haritashya, U., Huggel, C., Kaab, A., Kargel, J., Kavanaugh, J., Lacroix, P., Petley, D., Rupper, S., Azam, M., Cook, S., Dimri, A., Eriksson, M., Farinotti, D., Fiddes, J., Gnyawali, K., Harrison, S., Jha, M., Koppes, M., Kumar, S., Leiness, S., Majeed, U., Mai, S., Muhuri, A., Noetzli, J., Paul, F., Rashid, I., Sain, K., Steiner, J., Ugalde, F., Watson, C., and Westoby, M., 2021, A massive rock and ice avalanche caused the 2021 disaster at Chamoli, Indian Himalaya: Science, eabh4455, 15 p., https://doi.org/10.1126/science.abh4455.","productDescription":"eabh4455, 15 p.","ipdsId":"IP-127686","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":451939,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://discovery.dundee.ac.uk/en/publications/cd9567f5-1430-46d5-b8f5-81132306087a","text":"External Repository"},{"id":386471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","otherGeospatial":"Chamoli","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 78.8818359375,\n 30.244831915307145\n ],\n [\n 79.6893310546875,\n 30.244831915307145\n ],\n [\n 79.6893310546875,\n 30.694611546632277\n ],\n [\n 78.8818359375,\n 30.694611546632277\n ],\n [\n 78.8818359375,\n 30.244831915307145\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shugar, D. 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Annual exceedance probability flows at gaged locations and regional regression equations used to estimate annual exceedance probability flows at ungaged locations were developed by the U.S. Geological Survey, in cooperation with the Mississippi Department of Transportation, to improve flood-frequency estimates at rural streams in the alluvial plain of the lower Mississippi River. These estimates were developed using current geospatial data, analytical methods, and annual peak-flow data through September 2017 at 58 streamgages in the alluvial plain of the lower Mississippi River, including 9 in Mississippi, 35 in Arkansas, 4 in Missouri, and 10 in Louisiana. Annual exceedance probability flows presented in this report incorporate streamflow data through the 2017 water year, 32 additional years of record since the previous study in 1985 of flood magnitude and frequency in the Mississippi portion of the alluvial plain of the lower Mississippi River. Ranges for standard error of prediction, average variance of prediction, and pseudo-R2 are 45–61 percent, 0.035–0.059 (log cubic feet per second)2, and 90–94 percent, respectively.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215046","collaboration":"Prepared in cooperation with the Mississippi Department of Transportation","usgsCitation":"Anderson, B.T., 2021, Magnitude and frequency of floods in the alluvial plain of the lower Mississippi River, 2017: U.S. Geological Survey Scientific Investigations Report 2021–5046, 15 p., https://doi.org/10.3133/sir20215046.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"N","ipdsId":"IP-118369","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":386320,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5046/images"},{"id":386316,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5046/coverthb.jpg"},{"id":386317,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5046/sir20215046.pdf","text":"Report","size":"2.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5046"}],"country":"United States","state":"Arkansas, Illinois, Kentucky, Louisiana, Mississippi, Missouri, Tennessee","otherGeospatial":"Alluvial plain of the lower Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.36279296875,\n 37.16031654673677\n ],\n [\n -90.3076171875,\n 36.914764288955936\n ],\n [\n -90.791015625,\n 36.19109202182454\n ],\n [\n -91.51611328125,\n 34.867904962568716\n ],\n [\n -92.0654296875,\n 33.99802726234877\n ],\n [\n -92.21923828124999,\n 32.713355353177555\n ],\n [\n -92.83447265624999,\n 30.845647420182598\n ],\n [\n -92.7685546875,\n 29.516110386062277\n ],\n [\n -91.97753906249999,\n 29.11377539511439\n ],\n [\n -90.4833984375,\n 28.844673680771795\n ],\n [\n -89.12109375,\n 28.94086176940557\n ],\n [\n -89.23095703125,\n 29.554345125748267\n ],\n [\n -89.49462890625,\n 30.35391637229704\n ],\n [\n -89.9560546875,\n 30.713503990354965\n ],\n [\n -90.263671875,\n 31.59725256170666\n ],\n [\n -89.75830078125,\n 34.615126683462194\n ],\n [\n -89.07714843749999,\n 35.639441068973944\n ],\n [\n -88.61572265625,\n 36.474306755095235\n ],\n [\n -88.70361328125,\n 36.914764288955936\n ],\n [\n -89.36279296875,\n 37.16031654673677\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2021-06-10","noUsgsAuthors":false,"publicationDate":"2021-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Brandon T. 0000-0001-6698-0791","orcid":"https://orcid.org/0000-0001-6698-0791","contributorId":209976,"corporation":false,"usgs":true,"family":"Anderson","given":"Brandon","email":"","middleInitial":"T.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817197,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70222475,"text":"70222475 - 2021 - A near-real-time model for estimating probability of road obstruction due to earthquake-triggered landslides","interactions":[],"lastModifiedDate":"2021-11-16T15:33:34.255617","indexId":"70222475","displayToPublicDate":"2021-06-10T08:08:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"A near-real-time model for estimating probability of road obstruction due to earthquake-triggered landslides","docAbstract":"

Coseismic landslides are a major source of transportation disruption in mountainous areas, but few approaches exist for rapidly estimating impacts to road networks. We develop a model that links the U.S. Geological Survey (USGS) near-real-time earthquake-triggered landslide hazard model with Open Street Map (OSM) road network data to rapidly estimate segment-level obstruction risk following major earthquake activity worldwide. To train and validate the model, we process OSM data for 15 historical earthquakes and calculate the average segment-level landslide hazard from the USGS model for each event. We then fit a multivariate adaptive regression spline model for the probability of road obstruction as a function of road segment length and landslide hazard, using a training and validation dataset derived from the intersections of road networks with earthquake-triggered landslide inventories. The resulting probabilistic model is well calibrated across a range of earthquake events, with estimated obstruction probabilities matching the relative frequency of potential road obstructions. The model runs quickly and is capable of producing road segment-level obstruction estimates within minutes to hours of a major earthquake. However, in near-real-time application, the accuracy of the obstruction estimates will be dependent on the quality of the ShakeMap shaking estimates, which often improves with time as more information becomes available after the earthquake. By providing a rapid first-order translation of landslide hazard into potential infrastructure impacts, this model helps provide emergency responders with tangible information on initial areas of concern.

","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1177/87552930211020022","usgsCitation":"Wilson, B., Allstadt, K.E., and Thompson, E.M., 2021, A near-real-time model for estimating probability of road obstruction due to earthquake-triggered landslides: Earthquake Spectra, v. 37, no. 4, p. 2400-2418, https://doi.org/10.1177/87552930211020022.","productDescription":"19 p.","startPage":"2400","endPage":"2418","ipdsId":"IP-127999","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":436318,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9681WYD","text":"USGS data release","linkHelpText":"gfail_lifelines"},{"id":387580,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, B.H.","contributorId":221584,"corporation":false,"usgs":false,"family":"Wilson","given":"B.H.","email":"","affiliations":[],"preferred":false,"id":820169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820171,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221414,"text":"70221414 - 2021 - Evidence for variable precipitation and discharge from Upper Cretaceous–Paleogene fluvial deposits of the Raton Basin, Colorado–New Mexico, U.S.A.","interactions":[],"lastModifiedDate":"2021-06-15T11:51:45.486509","indexId":"70221414","displayToPublicDate":"2021-06-10T06:49:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2451,"text":"Journal of Sedimentary Research","onlineIssn":"1938-3681","printIssn":"1527-1404","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for variable precipitation and discharge from Upper Cretaceous–Paleogene fluvial deposits of the Raton Basin, Colorado–New Mexico, U.S.A.","docAbstract":"

The Raton Basin of Colorado–New Mexico, USA, is the southeasternmost basin of the Laramide intraforeland province of North America. It hosts a thick succession (4.5 km or 15,000 ft) of Upper Cretaceous to Paleogene marine and continental strata that were deposited in response to the final regression of the Western Interior Seaway and the onset of Laramide intraforeland deformation. The Upper Cretaceous–Paleogene Raton and Poison Canyon formations were previously described as meandering river and braided river deposits that represented distal and proximal members of rivers that drained the basin-bounding Sangre de Cristo–Culebra uplift. We present new observations of fluvial-channel architecture that show that both formations contain the deposits of sinuous fluvial channels. However, fluvial channels of the Raton Formation formed in ever-wet environments and were affected by steady discharge, whereas channels of the overlying Poison Canyon Formation formed in drier environments and were affected by variable discharge. The apparent transition in fluvial discharge characteristics was coeval with the progradation of fluvial fans across the Raton Basin during the Paleocene, emanating from the ancestral Sangre de Cristo–Culebra uplift. The construction of fluvial fans, coupled with the sedimentary features observed within, highlights the dual control of Laramide deformation and early Cenozoic climatic patterns on the sedimentary evolution of the Raton Basin.

","language":"English","publisher":"Society for Sedimentary Geology","doi":"10.2110/jsr.2020.081","usgsCitation":"Schwartz, T.M., Dechesne, M., and Zellman, K.L., 2021, Evidence for variable precipitation and discharge from Upper Cretaceous–Paleogene fluvial deposits of the Raton Basin, Colorado–New Mexico, U.S.A.: Journal of Sedimentary Research, v. 91, no. 6, p. 571-594, https://doi.org/10.2110/jsr.2020.081.","productDescription":"24 p.","startPage":"571","endPage":"594","ipdsId":"IP-116144","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":436319,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X7Z5VM","text":"USGS data release","linkHelpText":"Measured sections and paleocurrent data from fluvial deposits of the Upper Cretaceous-Paleogene Raton and Poison Canyon Formations, Raton Basin, Colorado-New Mexico, USA"},{"id":386488,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, New Mexico","otherGeospatial":"Raton Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.58984375,\n 36.24427318493909\n ],\n [\n -103.3154296875,\n 36.24427318493909\n ],\n [\n -103.3154296875,\n 37.37015718405753\n ],\n [\n -104.58984375,\n 37.37015718405753\n ],\n [\n -104.58984375,\n 36.24427318493909\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"91","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Schwartz, Theresa Maude 0000-0001-6606-4072","orcid":"https://orcid.org/0000-0001-6606-4072","contributorId":245180,"corporation":false,"usgs":true,"family":"Schwartz","given":"Theresa","email":"","middleInitial":"Maude","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":817626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dechesne, Marieke 0000-0002-4468-7495","orcid":"https://orcid.org/0000-0002-4468-7495","contributorId":213936,"corporation":false,"usgs":true,"family":"Dechesne","given":"Marieke","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":817627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zellman, Kristine L. 0000-0002-7088-429X kzellman@usgs.gov","orcid":"https://orcid.org/0000-0002-7088-429X","contributorId":4849,"corporation":false,"usgs":true,"family":"Zellman","given":"Kristine","email":"kzellman@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":817628,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228458,"text":"70228458 - 2021 - Age-structured Jolly-Seber model expands inference and improves parameter estimation from capture-recapture data","interactions":[],"lastModifiedDate":"2022-02-11T20:17:25.428531","indexId":"70228458","displayToPublicDate":"2021-06-09T14:13:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Age-structured Jolly-Seber model expands inference and improves parameter estimation from capture-recapture data","docAbstract":"Understanding the influence of individual attributes on demographic processes is a key objective of wildlife population studies. Capture-recapture and age data are commonly collected to investigate hypotheses about survival, reproduction, and viability. We present a novel age-structured Jolly-Seber model that incorporates age and capture-recapture data to provide comprehensive information on population dynamics, including abundance, age-dependent survival, recruitment, age structure, and population growth rates. We applied our model to a multi-year capture-recapture study of polar bears (Ursus maritimus) in western Hudson Bay, Canada (20122018), where management and conservation require a detailed understanding of how polar bears respond to climate change and other factors. In simulation studies, the age-structured Jolly-Seber model improved precision of survival, recruitment, and annual abundance estimates relative to standard Jolly-Seber models that omit age information. Furthermore, incorporating age information improved precision of population growth rates, increased power to detect trends in abundance, and allowed direct estimation of age-dependent survival and changes in annual age structure. Our case study provided detailed evidence for senescence in polar bear survival. Median survival estimates were lower (<0.95) for individuals aged <5 years, remained high (>0.95) for individuals aged 722 years, and subsequently declined to near zero for individuals >30 years. We also detected cascading effects of large recruitment classes on population age structure, which created major shifts in age structure when these classes entered the population and then again when they reached prime breeding ages (1015 years old). Overall, age-structured Jolly-Seber models provide a flexible means to investigate ecological and evolutionary processes that shape populations (e.g., via senescence, life expectancy, and lifetime reproductive success) while improving our ability to investigate population dynamics and forecast population changes from capture-recapture data.","language":"English","publisher":"Plos","doi":"10.1371/journal.pone.0252748","usgsCitation":"Hostetter, N., Lunn, N.J., Richardson, E.S., Regehr, E.V., and Converse, S.J., 2021, Age-structured Jolly-Seber model expands inference and improves parameter estimation from capture-recapture data: PLoS ONE, .0252748, 19 p., https://doi.org/10.1371/journal.pone.0252748.","productDescription":".0252748, 19 p.","ipdsId":"IP-116069","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":451942,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0252748","text":"Publisher Index Page"},{"id":395865,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Hostetter, Nathan J.","contributorId":275833,"corporation":false,"usgs":false,"family":"Hostetter","given":"Nathan J.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":834349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lunn, Nicholas J.","contributorId":275835,"corporation":false,"usgs":false,"family":"Lunn","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":56899,"text":"canada","active":true,"usgs":false}],"preferred":false,"id":834350,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, Evan S.","contributorId":275836,"corporation":false,"usgs":false,"family":"Richardson","given":"Evan","email":"","middleInitial":"S.","affiliations":[{"id":56899,"text":"canada","active":true,"usgs":false}],"preferred":false,"id":834351,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Regehr, Eric V.","contributorId":275837,"corporation":false,"usgs":false,"family":"Regehr","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":834352,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":834348,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}