{"pageNumber":"151","pageRowStart":"3750","pageSize":"25","recordCount":40783,"records":[{"id":70238045,"text":"70238045 - 2022 - Rock alteration mapping in and around fossil shallow intrusions at Mt. Ruapehu New Zealand with laboratory and aerial hyperspectral imaging","interactions":[],"lastModifiedDate":"2022-11-07T12:50:24.402862","indexId":"70238045","displayToPublicDate":"2022-11-04T06:42:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Rock alteration mapping in and around fossil shallow intrusions at Mt. Ruapehu New Zealand with laboratory and aerial hyperspectral imaging","docAbstract":"

Diagnostic absorption features in hyperspectral data can be used to identify a specific mineral or mineral associations. However, it is unknown how accurate hyperspectral mapping can be for identifying alteration mineral compositions at the resolution required to describe structures such as fossil intrusions, or whether it can accurately quantify the alteration present. This study compared petrographic observation with visible, near-infrared (VNIR), and shortwave infrared (SWIR) hyperspectral remote sensing at laboratory- (centimetre-scale) and aerial- (metre-scale) scales to characterise the abundance of surface hydrothermal rock alteration in and around a shallow fossil intrusion on Pinnacle Ridge, Mt. Ruapehu, New Zealand. We classified a high-resolution aerial hyperspectral image to develop a new surface alteration map using Spectral Angle Mapper (SAM) algorithm. The petrographic thin-section and the laboratory and aerial hyperspectral imaging revealed a spectrum of hydrous alteration phases as indicated by the presence of an absorption feature at 2207 nm. Moderate correlation exists between the depth of the absorption feature at 2207 nm and the point counting-derived alteration percent values, indicating reliability of laboratory-based hyperspectral analytical methods. In contrast, aerial hyperspectral data failed to provide any clear correlations to field-mapped alteration using a band-depth approach, and we interpret this due to ‘oversampling’ of surface (supergene) alteration, spectral mixing, and sensor limitations (e.g., bandwidth, signal-to-noise ratio). The hyperspectral image-derived alteration map, created using supervised image classification, can loosely be translated to a geotechnical map where porosity and permeability play a major role in localizing hydrothermal fluid flow and the formation of alteration mineral associations.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2022.107700","usgsCitation":"Douglas, A., Kereszturi, G., Schaefer, L.N., and Kennedy, B.M., 2022, Rock alteration mapping in and around fossil shallow intrusions at Mt. Ruapehu New Zealand with laboratory and aerial hyperspectral imaging: Journal of Volcanology and Geothermal Research, 107700, 15 p., https://doi.org/10.1016/j.jvolgeores.2022.107700.","productDescription":"107700, 15 p.","ipdsId":"IP-141155","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":409188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"Mt. Ruapehu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 175.18450850284427,\n -38.81524047528322\n ],\n [\n 175.18450850284427,\n -39.6149627891337\n ],\n [\n 176.05242842471847,\n -39.6149627891337\n ],\n [\n 176.05242842471847,\n -38.81524047528322\n ],\n [\n 175.18450850284427,\n -38.81524047528322\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Douglas, Abbey","contributorId":298912,"corporation":false,"usgs":false,"family":"Douglas","given":"Abbey","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":856697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kereszturi, Gabor 0000-0003-4336-2012","orcid":"https://orcid.org/0000-0003-4336-2012","contributorId":247601,"corporation":false,"usgs":false,"family":"Kereszturi","given":"Gabor","email":"","affiliations":[{"id":49587,"text":"Volcanic Risk Solutions, Massey University, Palmerston North, 4474, New Zealand","active":true,"usgs":false}],"preferred":false,"id":856698,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":856699,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kennedy, Ben M. 0000-0001-7235-6493","orcid":"https://orcid.org/0000-0001-7235-6493","contributorId":270276,"corporation":false,"usgs":false,"family":"Kennedy","given":"Ben","email":"","middleInitial":"M.","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":856700,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70238436,"text":"70238436 - 2022 - Insight into Hurricane Maria peak flows from the development and application of the Precipitation-Runoff Modeling System (PRMS): Including Río Grande de Arecibo, Puerto Rico, 1981–2017","interactions":[],"lastModifiedDate":"2022-11-23T12:37:26.148964","indexId":"70238436","displayToPublicDate":"2022-11-04T06:33:28","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10778,"text":"Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Insight into Hurricane Maria peak flows from the development and application of the Precipitation-Runoff Modeling System (PRMS): Including Río Grande de Arecibo, Puerto Rico, 1981–2017","docAbstract":"
The Precipitation-Runoff Modeling System (PRMS) was used to develop a simulation of watershed hydrology on the island of Puerto Rico for the period 1981–2017, concentrating on the Río Grande de Arecibo, a river with some of the highest streamflows on the island. This development is part of the U.S. Geological Survey’s (USGS) National Hydrologic Model (NHM) infrastructure which supports coordinated, comprehensive, and consistent hydrologic modeling at the watershed scale for the coterminous United States (CONUS). A goal of the NHM program is to expand the domain outside of CONUS, leading to a PRMS application in Puerto Rico. This model was used to simulate the effects of Hurricane Maria on daily streamflow and provide information at locations where streamgages were damaged by the hurricane. Comparisons with streamflow estimates made by indirect methods in the field, up to ten times higher than simulated values, lends insight into the uncertainties in both the indirect methods and model simulated values and helps to identify potential error in the daily streamflow estimates. The PRMS can be applied to look at the effects of changes in climate and land use, water management, industrial and public water usage, and many other factors that affect hydrology on the island of Puerto Rico. The model is also designed as a support tool for the USGS National Water Census which provides comprehensive reporting of national information on withdrawal, conveyance, consumptive use, and return flow by water-use category.

","language":"English","publisher":"MDPI","doi":"10.3390/hydrology9110205","usgsCitation":"Swain, E., and Bellino, J.C., 2022, Insight into Hurricane Maria peak flows from the development and application of the Precipitation-Runoff Modeling System (PRMS): Including Río Grande de Arecibo, Puerto Rico, 1981–2017: Hydrology, v. 11, no. 9, 205, 27 p., https://doi.org/10.3390/hydrology9110205.","productDescription":"205, 27 p.","ipdsId":"IP-124891","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":445945,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/hydrology9110205","text":"Publisher Index Page"},{"id":435627,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IMU17O","text":"USGS data release","linkHelpText":"PRMS simulator used to assess rainfall, runoff, and river flow for the National Hydrologic Model (NHM) Puerto Rico"},{"id":409582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto 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Rico\",\"nation\":\"USA \"}}]}","volume":"11","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Swain, Eric 0000-0001-7168-708X","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":223705,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":857495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bellino, Jason C. 0000-0001-9046-9344 jbellino@usgs.gov","orcid":"https://orcid.org/0000-0001-9046-9344","contributorId":3724,"corporation":false,"usgs":true,"family":"Bellino","given":"Jason","email":"jbellino@usgs.gov","middleInitial":"C.","affiliations":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"preferred":true,"id":857496,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237995,"text":"70237995 - 2022 - Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability","interactions":[],"lastModifiedDate":"2022-11-03T17:07:22.337181","indexId":"70237995","displayToPublicDate":"2022-11-03T12:01:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability","docAbstract":"

Evaluation of sea-level rise (SLR) impacts on coastal landforms and habitats is a persistent need for informing coastal planning and management, including policy decisions, particularly those that balance human interests and habitat protection throughout the coastal zone. Bayesian networks (BNs) are used to model barrier island change under different SLR scenarios that are relevant to management and policy decisions. BNs utilized here include a shoreline change model and two models of barrier island biogeomorphological evolution at different scales (50 and 5 m). These BNs were then linked to another BN to predict habitat availability for piping plovers (Charadrius melodus), a threatened shorebird reliant on beach habitats. We evaluated the performance of the two linked geomorphology BNs and further examined error rates by generating hindcasts of barrier island geomorphology and habitat availability for 2014 conditions. Geomorphology hindcasts revealed that model error declined with a greater number of known inputs, with error rates reaching 55% when multiple outputs were hindcast simultaneously. We also found that, although error in predictions of piping plover nest presence/absence increased when outputs from the geomorphology BNs were used as inputs in the piping plover habitat BN, the maximum error rate for piping plover habitat suitability in the fully-linked BNs was only 30%. Our findings suggest this approach may be useful for guiding scenario-based evaluations where known inputs can be used to constrain variables that produce higher uncertainty for morphological predictions. Overall, the approach demonstrates a way to assimilate data and model structures with uncertainty to produce forecasts to inform coastal planning and management.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022EA002286","usgsCitation":"Gutierrez, B.T., Zeigler, S., Lentz, E.E., Sturdivant, E., and Plant, N., 2022, Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability: Earth and Space Science, v. 9, no. 11, e2022EA002286, 24 p., https://doi.org/10.1029/2022EA002286.","productDescription":"e2022EA002286, 24 p.","ipdsId":"IP-133519","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":445946,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022ea002286","text":"Publisher Index Page"},{"id":435628,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R63EMY","text":"USGS data release","linkHelpText":"LinkedBNs_4Habitat - Matlab files to link Bayesian networks to generate habitat predictions"},{"id":409116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.29594026716985,\n 40.63299474223902\n ],\n [\n -73.3215230252425,\n 40.62686351437537\n ],\n [\n -73.31075133763278,\n 40.61664355031391\n ],\n [\n -73.26429843481641,\n 40.61766561708444\n ],\n [\n -73.18687693012288,\n 40.63299474223902\n ],\n [\n -73.03405361216147,\n 40.66823837708819\n ],\n [\n -72.97548256078474,\n 40.69019238633578\n ],\n [\n -72.90142720846879,\n 40.71673176155275\n ],\n [\n -72.75498136755509,\n 40.76126281049005\n ],\n [\n -72.75113811514511,\n 40.771161378285385\n ],\n [\n -72.79008117864493,\n 40.76709873688291\n ],\n [\n -72.82145002511935,\n 40.7537050773594\n ],\n [\n -72.84023809567569,\n 40.75014350867727\n ],\n [\n -72.87497858406178,\n 40.735821347504924\n ],\n [\n -72.91489181798045,\n 40.735609108172895\n ],\n [\n -72.93239581034598,\n 40.71979331664596\n ],\n [\n -72.98894717029637,\n 40.70040108981058\n ],\n [\n -73.00241177980864,\n 40.69019238633578\n ],\n [\n -73.07512067117331,\n 40.66977028676959\n ],\n [\n -73.19495569582996,\n 40.64729875129544\n ],\n [\n -73.26631812624335,\n 40.628907319545874\n ],\n [\n -73.29594026716985,\n 40.63299474223902\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Gutierrez, Benjamin T. 0000-0002-1879-7893 bgutierrez@usgs.gov","orcid":"https://orcid.org/0000-0002-1879-7893","contributorId":2924,"corporation":false,"usgs":true,"family":"Gutierrez","given":"Benjamin","email":"bgutierrez@usgs.gov","middleInitial":"T.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zeigler, Sara 0000-0002-5472-769X","orcid":"https://orcid.org/0000-0002-5472-769X","contributorId":222703,"corporation":false,"usgs":true,"family":"Zeigler","given":"Sara","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sturdivant, Emily J.","contributorId":297196,"corporation":false,"usgs":false,"family":"Sturdivant","given":"Emily J.","affiliations":[{"id":56085,"text":"Woodwell Climate Research Center","active":true,"usgs":false}],"preferred":false,"id":856472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plant, Nathaniel 0000-0002-5703-5672","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":81234,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856473,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237895,"text":"70237895 - 2022 - Klamath natural flow study, Upper Klamath Basin groundwater flow model","interactions":[],"lastModifiedDate":"2023-08-23T13:26:00.51571","indexId":"70237895","displayToPublicDate":"2022-11-03T09:13:58","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":21,"text":"Fact Sheet","active":false,"publicationSubtype":{"id":1}},"displayTitle":"Klamath Natural Flow Study, Upper Klamath Basin Groundwater Flow Model","title":"Klamath natural flow study, Upper Klamath Basin groundwater flow model","docAbstract":"

The purpose of the Upper Klamath Basin Groundwater Flow Model (UKBGFM) is to simulate groundwater conditions in the Upper Klamath Basin under historical and predevelopment conditions. The UKBGFM quantifies estimates of and changes in groundwater levels, storage, pumping, drainage flow to tile drains, evapotranspiration, and flow between the Upper Klamath Basin and neighboring basins. The quantifications of base flow to streams and seepage to and from lakes and reservoirs can be used as inputs to the RiverWare Mass Balance Model (Zagona and others, 2001), a companion model being developed as part of the Klamath Natural Flow Study (KNFS).

","language":"English","publisher":"U.S. Bureau of Reclamation","usgsCitation":"Traum, J.A., and Boyce, S.E., 2022, Klamath natural flow study, Upper Klamath Basin groundwater flow model: Fact Sheet, 2 p.","productDescription":"2 p.","ipdsId":"IP-145778","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":418055,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://www.usbr.gov/mp/kbao/docs/04-factsheet-gwmodeling-final.pdf"},{"id":418057,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Upper Klamath basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.54532325728275,\n 42.588031447169925\n ],\n [\n -124.57092240453784,\n 42.588031447169925\n ],\n [\n -124.57092240453784,\n 41.175\n ],\n [\n -121.54532325728275,\n 41.175\n ],\n [\n -121.54532325728275,\n 42.588031447169925\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Traum, Jonathan A. 0000-0002-4787-3680 jtraum@usgs.gov","orcid":"https://orcid.org/0000-0002-4787-3680","contributorId":4780,"corporation":false,"usgs":true,"family":"Traum","given":"Jonathan","email":"jtraum@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyce, Scott E. 0000-0003-0626-9492 seboyce@usgs.gov","orcid":"https://orcid.org/0000-0003-0626-9492","contributorId":4766,"corporation":false,"usgs":true,"family":"Boyce","given":"Scott","email":"seboyce@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856126,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238104,"text":"70238104 - 2022 - Plant community trajectories following livestock exclusion for conservation vary and hinge on initial invasion and soil-biocrust conditions in shrub steppe","interactions":[],"lastModifiedDate":"2022-12-15T15:37:49.27015","indexId":"70238104","displayToPublicDate":"2022-11-03T07:25:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Plant community trajectories following livestock exclusion for conservation vary and hinge on initial invasion and soil-biocrust conditions in shrub steppe","docAbstract":"

Adjustments or complete withdrawal of livestock grazing are among the most common conservation actions in semiarid uplands, but outcomes can vary considerably with ecological context. Invasion by exotic annual grasses and the excessive wildfire they promote are increasing threats to semiarid shrub-steppe, and plant-community response to livestock exclusion in these areas may be complicated by the rapid colonization ability of invaders. We evaluated vegetation-community changes over 14-year interval (2007–2021) in a shrub-steppe landscape where a >100-year history of livestock grazing had been terminated in 1996. Field surveys revealed that bare-soil exposure decreased >20% over the 14 years owing to biomass accumulation, but this was primarily due to large increases in exotic annual “cheatgrass” (Bromus tectorum, +1.8-fold) and the litter it produces (+1.5-fold). Soil biocrusts increased 11.9% and perennial bunchgrasses increased 3% over the 14 years. These community changes varied at the patch scale and entailed inverse relationships of (1) both cheatgrass and biocrusts to plant-community basal cover, (2) cheatgrass to both biocrusts and perennial grasses, and (3) biocrusts to cheatgrass and litter. The spatiotemporal variability in vegetation constituted changes in plant-community states, according to cluster analysis. The modeled probability of a community transitioning to a cheatgrass state was (1) strongly and positively related to the initial (2007) cover of cheatgrass in hotspots where initial cheatgrass cover was >20%, and (2) negatively related to biocrust cover where initial biocrust cover was >4% of ground area. The decision space for this landscape can be framed as a shifting from acceptance towards resisting further degradation by removing livestock and their trampling of soil surfaces and utilization of perennial herbs. However, cheatgrass appears to be the most impactful agent of change and continued invasion appears imminent. Active restoration may help resist further degradation and direct change towards tolerable conditions.

","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.12838","usgsCitation":"Germino, M., Kluender, C.R., and Anthony, C.R., 2022, Plant community trajectories following livestock exclusion for conservation vary and hinge on initial invasion and soil-biocrust conditions in shrub steppe: Conservation Science and Practice, v. 4, no. 12, e12838, 14 p., https://doi.org/10.1111/csp2.12838.","productDescription":"e12838, 14 p.","ipdsId":"IP-138776","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":445949,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.12838","text":"Publisher Index Page"},{"id":435629,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SO99W8","text":"USGS data release","linkHelpText":"Vegetation and soil cover data for long-term monitoring plots within Browns Park National Wildlife Refuge, Colorado, USA"},{"id":409290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","county":"Moffat County","otherGeospatial":"Browns Park National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.04917851176388,\n 40.831912228720284\n ],\n [\n -109.0482710374729,\n 40.80650230407173\n ],\n [\n -109.04010376885081,\n 40.802380858575475\n ],\n [\n -109.02513044304374,\n 40.79001498646366\n ],\n [\n -109.00607348292577,\n 40.78039549350518\n ],\n [\n -108.9847478370798,\n 40.771805483132596\n ],\n [\n -108.96251471694198,\n 40.754622130399156\n ],\n [\n -108.93710543678475,\n 40.74774754543358\n ],\n [\n -108.86677617920702,\n 40.747403797528335\n ],\n [\n -108.87539718497439,\n 40.74774754543358\n ],\n [\n -108.87539718497439,\n 40.791045563782774\n ],\n [\n -108.89536161938372,\n 40.79173260644234\n ],\n [\n -108.89581535652943,\n 40.81199716659302\n ],\n [\n -108.94255028253308,\n 40.81302740265849\n ],\n [\n -108.94300401967877,\n 40.82367223859845\n ],\n [\n -108.95253249973753,\n 40.82367223859845\n ],\n [\n -108.95253249973753,\n 40.83397206626529\n ],\n [\n -108.97204319700117,\n 40.8346586645591\n ],\n [\n -108.97204319700117,\n 40.845643270193364\n ],\n [\n -109.01832438585872,\n 40.84530002882232\n ],\n [\n -109.0187781230044,\n 40.86623449905673\n ],\n [\n -109.02876034020929,\n 40.86589136435694\n ],\n [\n -109.02876034020929,\n 40.87412610643992\n ],\n [\n -109.0487247746186,\n 40.87412610643992\n ],\n [\n -109.04917851176388,\n 40.831912228720284\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"4","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Germino, Matthew J. 0000-0001-6326-7579 mgermino@usgs.gov","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":152582,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","email":"mgermino@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":856869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kluender, Chad Raymond 0000-0002-4108-4437","orcid":"https://orcid.org/0000-0002-4108-4437","contributorId":296077,"corporation":false,"usgs":true,"family":"Kluender","given":"Chad","email":"","middleInitial":"Raymond","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":856870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anthony, Christopher R. 0000-0003-0968-224X","orcid":"https://orcid.org/0000-0003-0968-224X","contributorId":296314,"corporation":false,"usgs":true,"family":"Anthony","given":"Christopher","email":"","middleInitial":"R.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":856871,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238071,"text":"70238071 - 2022 - Bulk and intramolecular carbon isotopic compositions of hydrocarbon gases from laboratory pyrolysis of oil shale of the Green River Formation: Implications for isotope structures of kerogens","interactions":[],"lastModifiedDate":"2022-11-08T12:56:15.194903","indexId":"70238071","displayToPublicDate":"2022-11-03T06:49:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Bulk and intramolecular carbon isotopic compositions of hydrocarbon gases from laboratory pyrolysis of oil shale of the Green River Formation: Implications for isotope structures of kerogens","docAbstract":"

Evaluation of intramolecular isotope distributions within organic compounds can provide important insights into gas formation processes and structural properties of gas-generating precursors, such as kerogen, bitumen, and oil, in natural reservoirs. Until recently, little has been known about the intramolecular isotope distributions within kerogens. In this study, we conducted systematic pyrolysis experiments of gas generation from a lacustrine oil shale of the Eocene Green River Formation under hydrous and anhydrous conditions (equivalent maturity or Easy %Ro: 0.76 to 3.27 at 310 to 480 °C for 3 to 50 days), measuring gas yields and compositions, as well as bulk and position-specific (PS) carbon isotope compositions. Gas generation processes were investigated in combination with kinetic Monte Carlo (kMC) simulations on a model Type I kerogen based on the chemical structures of oil shale of the Green River Formation. The comparison of our experimental results with kMC modelling indicates a series of β-scission, radical isomerization, and recombination reactions better represent the bulk isotope compositions of propane in the pyrolysis of the oil shale of the Green River Formation, but the ΔCc-t (= δ13Ccen – δ13Cter) values of propane at Easy %Ro > 1.5 can be better simulated by a simple combination of propyl groups with H radicals. Combining our previous works on marine shale of the Woodford Formation and Springfield Coal Member of the Carbondale Formation, PS carbon isotopes of propane indicate that in the lacustrine shales of the Green River Formation and the marine Woodford Shale, propane is sourced from C\"singleC bond cleavage, while C\"singleO bond cracking generates propane from coal at the initial kerogen cracking stage. At high maturity, the differences of late-stage propane production among the source rocks lead to the different bulk and PS C kinetic isotope effects of propane. Our findings suggest that the δ13C at the terminal position of propane precursors is likely up to 3.6‰ higher than at the central position in the Green River kerogen, while they are similar in the marine shale of Woodford Formation. In addition, the δ13C at the central position of propyl groups attached to heteroatom compounds is relatively more positive in the Springfield Coal Member of the Carbondale Formation than in Green River kerogen. A comparison of intramolecular C isotopes of propyl groups in the kerogens with their bulk δ13C, based on the PS δ13C of early-generated propane, contributes to our understanding of heterogeneities of isotopic structures of sedimentary organic matter.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2022.104141","usgsCitation":"Li, X., Birdwell, J.E., and Horita, J., 2022, Bulk and intramolecular carbon isotopic compositions of hydrocarbon gases from laboratory pyrolysis of oil shale of the Green River Formation: Implications for isotope structures of kerogens: International Journal of Coal Geology, v. 264, 104141, 14 p., https://doi.org/10.1016/j.coal.2022.104141.","productDescription":"104141, 14 p.","ipdsId":"IP-142309","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":409228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"264","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Xiaoqiang","contributorId":298943,"corporation":false,"usgs":false,"family":"Li","given":"Xiaoqiang","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":856753,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":856754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horita, Juske","contributorId":146205,"corporation":false,"usgs":false,"family":"Horita","given":"Juske","email":"","affiliations":[{"id":16625,"text":"Department of Geosciences, Texas Tech University, Lubbock, Texas","active":true,"usgs":false}],"preferred":false,"id":856755,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70239764,"text":"70239764 - 2022 - Comparing line feature morphology with scale specific sinuosity distributions: A modified earth mover’s distance","interactions":[],"lastModifiedDate":"2023-01-19T12:04:41.843646","indexId":"70239764","displayToPublicDate":"2022-11-02T08:54:04","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Comparing line feature morphology with scale specific sinuosity distributions: A modified earth mover’s distance","docAbstract":"

No abstract available.

","conferenceTitle":"AutoCarto 2022","conferenceDate":"November 2-4, 2022","conferenceLocation":"Redlands, CA","language":"English","publisher":"Cartography and Geographic Information Society","usgsCitation":"Kronenfeld, B., Buttenfield, B., Shavers, E.J., and Stanislawski, L., 2022, Comparing line feature morphology with scale specific sinuosity distributions: A modified earth mover’s distance, AutoCarto 2022, Redlands, CA, November 2-4, 2022, 6 p.","productDescription":"6 p.","ipdsId":"IP-141934","costCenters":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":412028,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://cartogis.org/autocarto/autocarto-2022/program/presentations/","linkFileType":{"id":5,"text":"html"}},{"id":412030,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kronenfeld, Barry J.","contributorId":301029,"corporation":false,"usgs":false,"family":"Kronenfeld","given":"Barry J.","affiliations":[{"id":65272,"text":"Eastern Illinois University, Charleston, Illinois","active":true,"usgs":false}],"preferred":false,"id":861800,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buttenfield, Barbara","contributorId":301030,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":861801,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shavers, Ethan J. 0000-0001-9470-5199 eshavers@usgs.gov","orcid":"https://orcid.org/0000-0001-9470-5199","contributorId":206890,"corporation":false,"usgs":true,"family":"Shavers","given":"Ethan","email":"eshavers@usgs.gov","middleInitial":"J.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":861802,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanislawski, Larry 0000-0002-9437-0576","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":217849,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":861803,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237852,"text":"ofr20221085 - 2022 - Systematic mapping of the ocean-continent transform plate boundary of the Queen Charlotte fault system, southeastern Alaska and western British Columbia—A preliminary bathymetric terrain model","interactions":[],"lastModifiedDate":"2026-03-30T20:38:03.192379","indexId":"ofr20221085","displayToPublicDate":"2022-11-02T08:15:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1085","displayTitle":"Systematic Mapping of the Ocean-Continent Transform Plate Boundary of the Queen Charlotte Fault System, Southeastern Alaska and Western British Columbia—A Preliminary Bathymetric Terrain Model","title":"Systematic mapping of the ocean-continent transform plate boundary of the Queen Charlotte fault system, southeastern Alaska and western British Columbia—A preliminary bathymetric terrain model","docAbstract":"

In 2015, U.S. Geological Survey scientists in collaboration with scientists from other institutions began a study of the Queen Charlotte fault—the first systematic study of the fault in more than three decades. The primary goal of the study was to gain a better understanding of the earthquake, tsunami, and underwater-landslide hazards throughout southeastern Alaska, as well as gather data to develop geologic models that can be applied to similar plate boundaries around the globe, such as the San Andreas fault system in southern California, the Alpine fault in New Zealand, and the North Anatolian fault in Turkey. A bathymetric terrain model was compiled from six different multibeam surveys of the previously unmapped Queen Charlotte fault offshore of southeastern Alaska and Haida Gwaii archipelago.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221085","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration","usgsCitation":"Andrews, B.D., Brothers, D.S., Dartnell, P., Barrie, J.V., Haeussler, P.J., Green, K.M., Greene, H.G., Miller, N.C., Kluesner, J.W., and ten Brink, U.S., 2022, Systematic mapping of the ocean-continent transform plate boundary of the Queen Charlotte fault system, southeastern Alaska and western British Columbia—A preliminary bathymetric terrain model: U.S. Geological Survey Open-File Report 2022–1085, 2 sheets, 7-p. pamphlet, https://doi.org/10.3133/ofr20221085.","productDescription":"Pamphlet: iii, 7 p.; 2 Sheets: 60.50 × 42.50 inches and 60.00 × 42.00 inches; Data Release","numberOfPages":"7","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-128196","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":501832,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113792.htm","linkFileType":{"id":5,"text":"html"}},{"id":408793,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2022/1085/ofr20221085_sheet2.pdf","text":"Sheet 2","size":"101 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Contents of sheet replicated in the HTML version of the report linked to above"},{"id":408792,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2022/1085/ofr20221085_sheet1.pdf","text":"Sheet 1","size":"72.3 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Contents of sheet replicated in the HTML version of the report linked to above"},{"id":408791,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1085/images/"},{"id":408787,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1085/coverthb.jpg"},{"id":408788,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1085/ofr20221085_pamphlet.pdf","text":"Pamphlet","size":"5.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1085"},{"id":408790,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1085/ofr20221085.XML"},{"id":408789,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221085/full","text":"Pamphlet","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1085"},{"id":408794,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YGDHIQ","text":"USGS data release","linkHelpText":"A bathymetric terrain model of multibeam sonar data collected between 2005 and 2018 along the Queen Charlotte fault system in the eastern Gulf of Alaska from Cross Sound, Alaska, to Queen Charlotte Sound, Canada"}],"country":"Canada, United States","state":"Alaska, British Columbia","otherGeospatial":"Queen Charlotte Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -140.92029001527425,\n 58\n ],\n [\n -140.92029001527425,\n 46.46240819189495\n ],\n [\n -124.69923324285543,\n 46.46240819189495\n ],\n [\n -124.69923324285543,\n 58\n ],\n [\n -140.92029001527425,\n 58\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2022-11-02","noUsgsAuthors":false,"publicationDate":"2022-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Andrews, Brian D. 0000-0003-1024-9400 bandrews@usgs.gov","orcid":"https://orcid.org/0000-0003-1024-9400","contributorId":201662,"corporation":false,"usgs":true,"family":"Andrews","given":"Brian","email":"bandrews@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":855906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":855907,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dartnell, Peter 0000-0002-9554-729X","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":208208,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":855908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barrie, J. Vaughn","contributorId":298573,"corporation":false,"usgs":false,"family":"Barrie","given":"J.","email":"","middleInitial":"Vaughn","affiliations":[{"id":7219,"text":"Natural Resources Canada","active":true,"usgs":false}],"preferred":false,"id":855909,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":855910,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Green, Kristen M.","contributorId":298574,"corporation":false,"usgs":false,"family":"Green","given":"Kristen","email":"","middleInitial":"M.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":855911,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Greene, H. Gary","contributorId":139063,"corporation":false,"usgs":false,"family":"Greene","given":"H.","email":"","middleInitial":"Gary","affiliations":[{"id":12639,"text":"Moss Landing Marine Labs","active":true,"usgs":false}],"preferred":false,"id":855912,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Nathaniel C. 0000-0003-3271-2929 ncmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3271-2929","contributorId":174592,"corporation":false,"usgs":true,"family":"Miller","given":"Nathaniel","email":"ncmiller@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":855913,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kluesner, Jared W. 0000-0003-1701-8832 jkluesner@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":201261,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared","email":"jkluesner@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":855914,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"ten Brink, Uri S. 0000-0001-6858-3001","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":201741,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri","email":"","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":855915,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70238161,"text":"70238161 - 2022 - Contemporary (1984–2020) fire history metrics for the conterminous United States and ecoregional differences by land ownership","interactions":[],"lastModifiedDate":"2022-12-28T16:46:17.662436","indexId":"70238161","displayToPublicDate":"2022-11-02T06:34:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Contemporary (1984–2020) fire history metrics for the conterminous United States and ecoregional differences by land ownership","docAbstract":"

Background: Remotely sensed burned area products are critical to support fire modelling, policy, and management but often require further processing before use.

Aim: We calculated fire history metrics from the Landsat Burned Area Product (1984–2020) across the conterminous U.S. (CONUS) including (1) fire frequency, (2) time since last burn (TSLB), (3) year of last burn, (4) longest fire-free interval, (5) average fire interval length, and (6) contemporary fire return interval (cFRI).

Methods: Metrics were summarised by ecoregion and land ownership, and related to historical and cheatgrass datasets to demonstrate further applications of the products.

Key results: The proportion burned ranged from 0.7% in the Northeast Mixed Woods to 74.1% in the Kansas Flint Hills. The Flint Hills and Temperate Prairies showed the highest burn frequency, while the Flint Hills and the Sierra Nevada and Klamath Mountains showed the shortest TSLB. Compared to private, public land had greater burned area (19 of 31 ecoregions) and shorter cFRI (25 of 31 ecoregions).

Conclusions: Contemporary fire history metrics can help characterise recent fire regimes across CONUS.

Implications: In regions with frequent fire, comparison of contemporary with target fire regimes or invasive species datasets enables the efficient incorporation of burned area data into decision-making.

","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF22044","usgsCitation":"Vanderhoof, M.K., Hawbaker, T., Teske, C., Noble, J., and Smith, J., 2022, Contemporary (1984–2020) fire history metrics for the conterminous United States and ecoregional differences by land ownership: International Journal of Wildland Fire, v. 31, no. 12, p. 1167-1183, https://doi.org/10.1071/WF22044.","productDescription":"17 p.","startPage":"1167","endPage":"1183","ipdsId":"IP-139315","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":445959,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wf22044","text":"Publisher Index Page"},{"id":435630,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98996IH","text":"USGS data release","linkHelpText":"Contemporary fire history metrics for the conterminous United States (1984-2023) (ver. 3.0, 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[\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"31","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":857021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":857022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teske, Casey","contributorId":224732,"corporation":false,"usgs":false,"family":"Teske","given":"Casey","email":"","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":857023,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noble, Joe","contributorId":257938,"corporation":false,"usgs":false,"family":"Noble","given":"Joe","email":"","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":857024,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Jim","contributorId":191054,"corporation":false,"usgs":false,"family":"Smith","given":"Jim","email":"","affiliations":[],"preferred":false,"id":857025,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237996,"text":"70237996 - 2022 - Affinity of the benthic foraminifer Cassidulinoides parkeriana (Brady) for whale-falls: Evidence from off western Vancouver Island, British Columbia, Canada","interactions":[],"lastModifiedDate":"2022-12-01T16:17:42.428534","indexId":"70237996","displayToPublicDate":"2022-11-01T17:28:27","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2735,"text":"Micropaleontology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Affinity of the benthic foraminifer Cassidulinoides parkeriana (Brady) for whale-falls: Evidence from off western Vancouver Island, British Columbia, Canada","title":"Affinity of the benthic foraminifer Cassidulinoides parkeriana (Brady) for whale-falls: Evidence from off western Vancouver Island, British Columbia, Canada","docAbstract":"

A partial skeleton of a blue or fin whale, estimated to have been 16.5 m in length and thought to have been lying on the seafloor for less than 10 years, was observed at a depth of 1288 m off western Vancouver Island, British Columbia, Canada (48.68° N, 126.84° W). Four push cores were taken at the site, three (15-26 cm in length) directly under caudal vertebrae and one 18 cm long, considered a reference, 15 m away, in order to characterize changes in the benthic foraminiferal assemblage due to the whale-fall. A Q-mode cluster analysis identified four groupings, separating the surface and deeper samples of both the whale-fall and reference cores. The results of a metric multi-dimensional scaling plot and permutational multivariate analysis of variance test of the surface samples also suggest there was a significant difference between the whale-fall and reference core benthic foraminiferal faunas. No endemic species were recovered. Downcore samples below 6 cm in the whale-fall and reference cores were characterized by common Uvigerina peregrina, Pseudoparrella pacifica, Bolivina spissa, Bulimina striata, and Takayanagia delicata. In contrast, Cassidulinoides parkeriana, which typically is a minor component of benthic foraminiferal assemblages, dominated the upper 6 cm of the whale-fall cores, whereas the low oxygen-tolerant species T. delicata dominated the same interval in the reference core. The dramatic increase in abundance of C. parkeriana in the upper sediments below this whale-fall, as well as at the Torishima Seamount whale-fall site off Japan, indicate that it is an opportunistic species well adapted to taking advantage of unpredictable and highly localized tropic windfalls such as whale-falls. To our knowledge, this is the first benthic foraminiferal species shown to increase dramatically in abundance in the presence of a whale-fall. Additionally, modern fragments of whale bones occurring as deep as 12 to 15 cm downcore at the western Vancouver Island site demonstrate the effect of bioturbation by invertebrate scavengers that consume whale carcasses, indicating that detailed biostratigraphic records below whale-falls should be interpreted with caution.

","language":"English","publisher":"Micropaleontology Press","doi":"10.47894/mpal.68.6.03","usgsCitation":"McGann, M., and Paull, C.K., 2022, Affinity of the benthic foraminifer Cassidulinoides parkeriana (Brady) for whale-falls: Evidence from off western Vancouver Island, British Columbia, Canada: Micropaleontology, v. 68, no. 6, p. 569-586, https://doi.org/10.47894/mpal.68.6.03.","productDescription":"18 p.","startPage":"569","endPage":"586","ipdsId":"IP-131051","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":409137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Pacific Ocean, Vancouver Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -127,\n 48.75\n ],\n [\n -127,\n 48.5\n ],\n [\n -126.75,\n 48.5\n ],\n [\n -126.75,\n 48.75\n ],\n [\n -127,\n 48.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"68","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McGann, Mary 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":169540,"corporation":false,"usgs":true,"family":"McGann","given":"Mary","email":"mmcgann@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paull, Charles K. 0000-0001-5940-3443","orcid":"https://orcid.org/0000-0001-5940-3443","contributorId":55825,"corporation":false,"usgs":false,"family":"Paull","given":"Charles","email":"","middleInitial":"K.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":true,"id":856475,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238678,"text":"70238678 - 2022 - Geologic map of the Mount Blue Sky (formerly Mount Evans) quadrangle, Clear Creek and Park Counties, Colorado","interactions":[],"lastModifiedDate":"2024-12-12T19:04:46.137756","indexId":"70238678","displayToPublicDate":"2022-11-01T11:37:18","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":128,"text":"Open-File Report","active":false,"publicationSubtype":{"id":2}},"seriesNumber":"OF-22-11","title":"Geologic map of the Mount Blue Sky (formerly Mount Evans) quadrangle, Clear Creek and Park Counties, Colorado","docAbstract":"

The Mount Blue Sky (formerly Mount Evans) 7.5’ quadrangle lies in Park and Clear Creek counties, Colorado, about 60 km west of Denver. The highest elevation in the quadrangle is 14,265 ft (4,348 m) at the top of Mount Blue Sky. The lowest is at about 9,200 ft (2,804 m) on Guanella Pass Road at the southern edge of the quadrangle. Bedrock directly underlies most of the map area, with surficial deposits primarily in the valleys. The geology of the quadrangle was previously mapped at 1:100,000 scale as part of a regional compilation by Kellogg and others (2008). The oldest rocks in the Mount Blue Sky 7.5-minute quadrangle are Paleoproterozoic metasedimentary rocks, and mafic to felsic metaigneous rocks (all units starting with ‘X’ on Plate 1). These rocks were metamorphosed under upper amphibolite facies conditions and intruded by Mesoproterozoic felsic igneous rocks of the ~1442 Ma Mount Blue Sky (YgR, Yt, Ygdm, Ymgm and ~1424 Ma Silver Plume (Yg) batholiths (Spurr and others, 1908; Tweto, 1897; Aleinikoff and others, 1993; du Bray and others, 2018) and, in the southern part of the quadrangle, by rocks that may also be part of the Mount Blue Sky batholith, but may alternatively interpreted as part of the ~1115 Ma to ~1066 Ma Pikes Peak batholith (Unruh and others, 1995; Guitreau and others, 2016). Four generations of folds affected the area. The oldest, F1 folds are isoclinal of various orientations, but primarily northerly-plunging in the southern part of the quadrangle (Mahatma, 2019; Mahatma and others, 2022). In the northern part of the quadrangle (Powell, 2020), open to close F2 chevron folds exist with various orientations. F3 folds in the northern part of the quadrangle are open to close with upright axial planes and plunges to the north and south, and in the southern part of the quadrangle they are open centimeter- to meter- scale northerly-plunging folds, possibly overprinted by another generation of northerly-plunging folds based on orientations of axial planes (F2 and F3 of Mahatma and others, 2022). F4 folds throughout the quadrangle are open to gentle with upright axial planes and shallow plunges to the east and west. The Mount Blue Sky batholith displays a pervasive moderately NW-dipping biotite-hornblende foliation (Fig. 1) in addition to a flow foliation near the margins, indicating NW-directed shortening after ~1442 Ma (Powell, 2020). The relationship between this foliation and the folds is not clear. Various joint sets are present in the area. The most pervasive joint set strikes 355°-020° and is subvertical. It is best developed in the western to southwestern part of the map area, and may be related to late Cenozoic extension associated with the Rio Grande Rift. Joint orientations are generally consistent with the trends of topographical lineaments. Surficial deposits include two series of glacial till deposits (Qtb and Qtp), and outwash (Qgp) deposits. They correlate with the Bull Lake (170-120 ka) and Pinedale (30-12 ka) glacial periods (Dahms, 2004) based on original depositional morphology, geomorphic and topographic position, deposit weathering and pedogenic properties. Possible older glacial deposits (Qti) have been observed along topographically higher surfaces.

","language":"English","publisher":"Colorado Geological Survey","usgsCitation":"Powell, L., Mahatma, A.A., Kuiper, Y., and Ruleman, C.A., 2022, Geologic map of the Mount Blue Sky (formerly Mount Evans) quadrangle, Clear Creek and Park Counties, Colorado: Open-File Report OF-22-11, 2 Plates: 33.00 x 31.50 inches and 41.00 x 31.00 inches: Data Files.","productDescription":"2 Plates: 33.00 x 31.50 inches and 41.00 x 31.00 inches: Data Files","ipdsId":"IP-139573","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":413293,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":413292,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://coloradogeologicalsurvey.org/publications/geologic-map-mount-evans-quadrangle-clear-creek-park-colorado/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","otherGeospatial":"Mount Evans quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.75,\n 39.625\n ],\n [\n -105.75,\n 39.5\n ],\n [\n -105.625,\n 39.5\n ],\n [\n -105.625,\n 39.625\n ],\n [\n -105.75,\n 39.625\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Powell, Logan 0000-0002-0528-3092 ljpowell@usgs.gov","orcid":"https://orcid.org/0000-0002-0528-3092","contributorId":299647,"corporation":false,"usgs":false,"family":"Powell","given":"Logan","email":"ljpowell@usgs.gov","affiliations":[{"id":64912,"text":"Colorado School of Mines MS Graduate","active":true,"usgs":false}],"preferred":false,"id":858245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahatma, Asha A.","contributorId":299648,"corporation":false,"usgs":false,"family":"Mahatma","given":"Asha","email":"","middleInitial":"A.","affiliations":[{"id":64913,"text":"Colorado School of Mines PhD Graduate","active":true,"usgs":false}],"preferred":false,"id":858246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuiper, Yvette 0000-0002-8506-8180","orcid":"https://orcid.org/0000-0002-8506-8180","contributorId":299649,"corporation":false,"usgs":false,"family":"Kuiper","given":"Yvette","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":858247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":858248,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70240970,"text":"70240970 - 2022 - Behavioral responses of native and invasive fishes of the Upper Mississippi River to 100 hp boat motor acoustic stimulus","interactions":[],"lastModifiedDate":"2023-03-03T16:24:42.483833","indexId":"70240970","displayToPublicDate":"2022-11-01T10:17:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Behavioral responses of native and invasive fishes of the Upper Mississippi River to 100 hp boat motor acoustic stimulus","docAbstract":"

Acoustic deterrents are currently being considered for deployment at strategic bottlenecks, such as lock and dams of major rivers, to deter upstream movement of invasive carp. Previous studies have demonstrated that bighead and silver carp (Hypophthalmichthys nobilis and H. molitrix, respectively) display negative phonotaxis to playbacks of broadband sound recordings produced from a 100 hp outboard boat motor. However, there is concern that acoustic deterrents may impact the movement of non-target native fishes in the Upper Mississippi River. We evaluated the potential impacts of a broadband underwater acoustic deterrent on native ostariophysans [bigmouth buffalo (Ictiobus cyprinellus), channel catfish (Ictalurus punctatus) and fathead minnow (Pimephales promelas)], invasive ostariophysans [bighead carp, common carp (Cyprinus carpio), grass carp (Ctenopharyngodon idella) and silver carp], and native non-ostariophysans [(American eel (Anguilla rostrata), gizzard shad (Dorosoma cepedianum), hybrid striped bass (M. saxatilis × M. chrysops), lake sturgeon (Acipenser fulvescens) and paddlefish (Polyodon spathula)]. Fish were exposed to playback of the broadband sound (60–10000 Hz), and their behavior was evaluated. Bighead carp showed a strong negative phonotaxis response to the stimulus [12.3 ± 7.5 (SD) mean consecutive reactions], silver carp and grass carp showed moderate responses (4.5 ± 5.2 and 3.8 ± 3.5 reactions), and common carp displayed low responses (1.3 ± 1.9 reactions). Of the native fish, bigmouth buffalo (2.1 ± 2.9 reactions) and hybrid striped bass (0.3 ± 0.5 reactions) were the only species to demonstrate observable response to the acoustic stimulus. Based on this small-scale behavioral screening, acoustic deterrents should have minimal impact on native species; however, larger pond and field trials are necessary to confirm this finding.

","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre (REABIC)","doi":"10.3391/mbi.2022.13.4.11","usgsCitation":"Murchy, K., Vetter, B.J., Brey, M.K., and Mensinger, A.F., 2022, Behavioral responses of native and invasive fishes of the Upper Mississippi River to 100 hp boat motor acoustic stimulus: Management of Biological Invasions, v. 13, no. 4, p. 750-768, https://doi.org/10.3391/mbi.2022.13.4.11.","productDescription":"19 p.","startPage":"750","endPage":"768","ipdsId":"IP-100082","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":445962,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2022.13.4.11","text":"Publisher Index Page"},{"id":435632,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A4DG5S","text":"USGS data release","linkHelpText":"Native Species Response to 100 HP boat motor acoustic stimulus"},{"id":413668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"La Crosse","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.3004835543801,\n 43.87708421881712\n ],\n [\n -91.3004835543801,\n 43.843591735448996\n ],\n [\n -91.22936746021168,\n 43.843591735448996\n ],\n [\n -91.22936746021168,\n 43.87708421881712\n ],\n [\n -91.3004835543801,\n 43.87708421881712\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Murchy, Kelsie A.","contributorId":190582,"corporation":false,"usgs":false,"family":"Murchy","given":"Kelsie A.","affiliations":[],"preferred":false,"id":865530,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vetter, Brooke J","contributorId":192270,"corporation":false,"usgs":false,"family":"Vetter","given":"Brooke","email":"","middleInitial":"J","affiliations":[],"preferred":false,"id":865531,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":865532,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mensinger, Allen F.","contributorId":150852,"corporation":false,"usgs":false,"family":"Mensinger","given":"Allen","email":"","middleInitial":"F.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":false,"id":865533,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248234,"text":"70248234 - 2022 - Preface to the focus section on deformation models for the U.S. National Seismic Hazard Model","interactions":[],"lastModifiedDate":"2023-09-05T14:22:47.000892","indexId":"70248234","displayToPublicDate":"2022-11-01T09:05:02","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Preface to the focus section on deformation models for the U.S. National Seismic Hazard Model","docAbstract":"

No abstract available.

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0000-0003-1511-5241","orcid":"https://orcid.org/0000-0003-1511-5241","contributorId":329357,"corporation":false,"usgs":false,"family":"Johnson","given":"Kaj","email":"","middleInitial":"M.","affiliations":[{"id":37145,"text":"Indiana University","active":true,"usgs":false}],"preferred":false,"id":882059,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70237964,"text":"ofr20221096 - 2022 - Assessing the efficacy of using a parentage-based tagging survival model to evaluate two sources of mortality for juvenile Chinook salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon","interactions":[],"lastModifiedDate":"2023-09-18T20:04:08.872815","indexId":"ofr20221096","displayToPublicDate":"2022-11-01T08:50:41","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1096","displayTitle":"Assessing the Efficacy of Using a Parentage-Based Tagging Survival Model to Evaluate Two Sources of Mortality for Juvenile Chinook Salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon","title":"Assessing the efficacy of using a parentage-based tagging survival model to evaluate two sources of mortality for juvenile Chinook salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon","docAbstract":"

We conducted a study to assess the efficacy of using a parentage-based tagging survival model (PBT N-mixture model) to evaluate two sources of mortality for juvenile Chinook salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon. The model was originally developed to evaluate reservoir mortality because of predation from piscivorous fish. However, recent studies have also found that juvenile Chinook salmon experience high infection rates from parasitic copepods (Salmincola californiensis), which are known to negatively affect performance and survival. Our study was conducted to determine if the PBT N-mixture model could separately estimate mortality because of predation from non-native fish and mortality resulting from copepod infection. This assessment was conducted in two parts: (1) data collected in Lookout Point Reservoir during 2018 were re-analyzed; and (2) a simulation was conducted to evaluate a multi-year study that included inter-annual variation in copepod infection rate and two subsampling strategies (10 fish per month, 30 fish per month) to characterize monthly copepod infection rate. Results from each of these efforts suggest that the survival model is unlikely to provide reliable survival estimates for the two mortality sources that we evaluated. The re-analysis of 2018 data showed that “predation only” and “copepod only” models estimated a negative coefficient for the respective covariate, but the model that included both covariates provided coefficient estimates that differed from the other models and were highly uncertain. Similarly, the simulation results showed that most models failed to correctly estimate the magnitude and direction of mortality due to predation and copepods. These results suggest that additional data will be required if a model is desired that can separately estimate mortality effects due to both predation and copepods in the future. The existing data are limited by factors including low detection probabilities from previous field studies, existing uncertainties about copepod effects on mortality in a natural setting and expected limitations in the number of years that a field study could realistically be expected to receive funding.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221096","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Hance, D.J., Kock, T.J., Perry, R.W., and Pope, A.C., 2022, Assessing the efficacy of using a parentage-based tagging survival model to evaluate two sources of mortality for juvenile Chinook salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon: U.S. Geological Survey Open-File Report 2022–1096, 14 p., https://doi.org/10.3133/ofr20221096.","productDescription":"v, 14 p.","onlineOnly":"Y","ipdsId":"IP-141621","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":408997,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1096/ofr20221096.XML"},{"id":408996,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1096/images"},{"id":408995,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221096/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1096"},{"id":408994,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1096/ofr20221096.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1096"},{"id":408993,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1096/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Lookout Point Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.84577497588536,\n 43.952222617898286\n ],\n [\n -122.84577497588536,\n 43.78093867902544\n ],\n [\n -122.51343855010415,\n 43.78093867902544\n ],\n [\n -122.51343855010415,\n 43.952222617898286\n ],\n [\n -122.84577497588536,\n 43.952222617898286\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016

","tableOfContents":"","publishedDate":"2022-11-01","noUsgsAuthors":false,"publicationDate":"2022-11-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Hance, Dalton J. 0000-0002-4475-706X dhance@usgs.gov","orcid":"https://orcid.org/0000-0002-4475-706X","contributorId":206496,"corporation":false,"usgs":true,"family":"Hance","given":"Dalton","email":"dhance@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":856393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":856394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":856395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pope, Adam C. 0000-0002-7253-2247 apope@usgs.gov","orcid":"https://orcid.org/0000-0002-7253-2247","contributorId":5664,"corporation":false,"usgs":true,"family":"Pope","given":"Adam","email":"apope@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":856396,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70238033,"text":"70238033 - 2022 - Warming-driven erosion and sediment transport in cold regions","interactions":[],"lastModifiedDate":"2022-12-15T15:17:16.294124","indexId":"70238033","displayToPublicDate":"2022-11-01T07:28:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12813,"text":"Nature--Reviews of Earth and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Warming-driven erosion and sediment transport in cold regions","docAbstract":"

Rapid atmospheric warming since the mid-twentieth century has increased temperature-dependent erosion and sediment-transport processes in cold environments, affecting food, energy and water security. In this Review, we summarize landscape changes in cold environments and provide a global inventory of increases in erosion and sediment yield driven by cryosphere degradation. Anthropogenic climate change, deglaciation, and thermokarst disturbances are causing increased sediment mobilization and transport processes in glacierized and periglacierized basins. With continuous cryosphere degradation, sediment transport will continue to increase until reaching a maximum (peak sediment). Thereafter, transport is likely to shift from a temperature-dependent regime toward a rainfall-dependent regime roughly between 2100–2200. The timing of the regime shift would be regulated by changes in meltwater, erosive rainfall and landscape erodibility, and complicated by geomorphic feedbacks and connectivity. Further progress in integrating multisource sediment observations, developing physics-based sediment-transport models, and enhancing interdisciplinary and international scientific collaboration is needed to predict sediment dynamics in a warming world.

","language":"English","publisher":"Nature","doi":"10.1038/s43017-022-00362-0","usgsCitation":"Zhang, T., Li, D., East, A.E., Walling, D.E., Lane, S.N., Overeem, I., Beylich, A.A., Koppes, M.N., and Lu, X., 2022, Warming-driven erosion and sediment transport in cold regions: Nature--Reviews of Earth and Environment, v. 3, p. 832-851, https://doi.org/10.1038/s43017-022-00362-0.","productDescription":"20 p.","startPage":"832","endPage":"851","ipdsId":"IP-143040","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467151,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://serval.unil.ch/notice/serval:BIB_8952BC5CEDD0","text":"External Repository"},{"id":409162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2022-11-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhang, Tinghu","contributorId":210005,"corporation":false,"usgs":false,"family":"Zhang","given":"Tinghu","email":"","affiliations":[],"preferred":false,"id":856644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Dongfeng","contributorId":297068,"corporation":false,"usgs":false,"family":"Li","given":"Dongfeng","email":"","affiliations":[{"id":64287,"text":"National University of Singapore","active":true,"usgs":false}],"preferred":false,"id":856645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walling, Desmond E.","contributorId":298885,"corporation":false,"usgs":false,"family":"Walling","given":"Desmond","email":"","middleInitial":"E.","affiliations":[{"id":17840,"text":"University of Exeter","active":true,"usgs":false}],"preferred":false,"id":856647,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lane, Stuart N.","contributorId":271165,"corporation":false,"usgs":false,"family":"Lane","given":"Stuart","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":856648,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Overeem, Irina","contributorId":197487,"corporation":false,"usgs":false,"family":"Overeem","given":"Irina","email":"","affiliations":[],"preferred":false,"id":856649,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beylich, Achim A.","contributorId":298886,"corporation":false,"usgs":false,"family":"Beylich","given":"Achim","email":"","middleInitial":"A.","affiliations":[{"id":64724,"text":"Geomorphological Field Laboratory (GFL)","active":true,"usgs":false}],"preferred":false,"id":856650,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Koppes, Michele N","contributorId":248379,"corporation":false,"usgs":false,"family":"Koppes","given":"Michele","email":"","middleInitial":"N","affiliations":[{"id":36972,"text":"University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":856651,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lu, Xixi","contributorId":298889,"corporation":false,"usgs":false,"family":"Lu","given":"Xixi","email":"","affiliations":[{"id":64287,"text":"National University of Singapore","active":true,"usgs":false}],"preferred":false,"id":856652,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70266792,"text":"70266792 - 2022 - A statistical framework for modelling migration corridors","interactions":[],"lastModifiedDate":"2025-05-13T15:19:21.848873","indexId":"70266792","displayToPublicDate":"2022-11-01T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A statistical framework for modelling migration corridors","docAbstract":"

1. Management of animal populations requires spatially explicit knowledge of movement corridors, such as those used during seasonal migrations. GPS tracking data allows for mapping of corridors from directly observed movements, providing important insights, but tracking data is absent for many populations.

2. We developed a novel statistical corridor modeling approach that predicts movement corridors from cost-distance movement models fit directly to migration tracking data. Unlike existing predictive approaches, this does not require the ad-hoc transformation of habitat suitability surfaces into resistance surfaces. We tested the ability of the approach to recover parameters used to generate simulated movements. We then used GPS data from three migrating mule deer (Odocoileus hemionus) herds in Idaho and Wyoming to model corridors as a function of elevation, slope, aspect, percent shrub, date of peak green-up, snow-off date, and human footprint. We assessed the predictive ability of the fitted models using validation tracks from the same herd as well as from the other herds.

3. The approach reproduced parameters used to generate the simulated movements, predicted the corridors used by migratory populations, and described the direction, magnitude, and confidence levels of the effects of environmental variables on corridors. The effects environmental variables had on corridors differed depending on the herd. Within-herd validation indicated that fitted corridor models are more accurate at predicting migration corridors than null models, and cross-herd validation indicated that fitted models for some herds accurately predicted the observed migrations of other herds.

4. In addition to the practical benefit of mapping corridors for management, our statistical corridor modeling framework sets the stage for evaluating fundamental questions about the fitness tradeoffs, navigation, learning, fidelity, and movement constraints that influence migratory and other corridor-generating behavior. Models of predictive corridors can inform management and planning for the conservation of migrations across taxa, including the potential restoration of corridors. Our corridor modeling approach is also readily applied to non-migratory animal movements.

","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210x.13969","usgsCitation":"Nuñez, T., Hurley, M., Graves, T., Ortega, A., Sawyer, H., Fattebert, J., Merkle, J., and Kauffman, M., 2022, A statistical framework for modelling migration corridors: Methods in Ecology and Evolution, v. 13, no. 11, p. 2635-2648, https://doi.org/10.1111/2041-210x.13969.","productDescription":"14 p.","startPage":"2635","endPage":"2648","ipdsId":"IP-136728","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488193,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13969","text":"Publisher Index Page"},{"id":485818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.51571099773642,\n 45.9008891737889\n ],\n [\n -116.51571099773642,\n 42.05335013528642\n ],\n [\n -108.42991483721727,\n 42.05335013528642\n ],\n [\n -108.42991483721727,\n 45.9008891737889\n ],\n [\n -116.51571099773642,\n 45.9008891737889\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-09-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Nuñez, Tristan A.","contributorId":355041,"corporation":false,"usgs":false,"family":"Nuñez","given":"Tristan A.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":936789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hurley, Mark A.","contributorId":355042,"corporation":false,"usgs":false,"family":"Hurley","given":"Mark A.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":936790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":936791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ortega, Anna C.","contributorId":355044,"corporation":false,"usgs":false,"family":"Ortega","given":"Anna C.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":936792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sawyer, Hall","contributorId":355048,"corporation":false,"usgs":false,"family":"Sawyer","given":"Hall","affiliations":[{"id":84702,"text":"Western EcoSystems Technology (WEST), Inc.,","active":true,"usgs":false}],"preferred":false,"id":936793,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fattebert, Julien","contributorId":355051,"corporation":false,"usgs":false,"family":"Fattebert","given":"Julien","affiliations":[{"id":84703,"text":"University of Wyoming,","active":true,"usgs":false}],"preferred":false,"id":936794,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Merkle, Jerod A.","contributorId":355052,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod A.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":936795,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":936796,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70238109,"text":"70238109 - 2022 - Know what you don't know: Embracing state uncertainty in disease-structured multistate models","interactions":[],"lastModifiedDate":"2022-12-15T15:44:51.910487","indexId":"70238109","displayToPublicDate":"2022-10-31T07:27:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Know what you don't know: Embracing state uncertainty in disease-structured multistate models","docAbstract":"
  1. Hidden Markov models (HMMs) are broadly applicable hierarchical models that derive their utility from separating state processes from observation processes yielding the data. Multistate models such as mark–recapture and dynamic multistate occupancy models are HMMs frequently used in ecology. In their early formulations, states, such as pathogen infection status, were assumed to be perfectly observed without ambiguity. However, state uncertainty is a pervasive feature of many ecological studies, and multievent models were developed to explicitly account for it.
  2. We developed a novel extended multievent mark–recapture model that incorporates state uncertainty at multiple levels of detection. Using a disease-structured example, both false negative and false positive state assignment errors are modelled at two levels of state assignment—the pathogen sampling process and the diagnostic process that samples are subjected to. We additionally describe methods to jointly model infection intensity to integrate heterogeneity in ecological parameters, such as mortality and infection dynamics, and the pathogen detection processes. We provide code to simulate and analyse datasets with various underlying ecological processes and fit our model to a mark–recapture dataset of Mixophyes fleayi (Fleay's barred frog) infected with the amphibian chytrid fungus (Batrachochytrium dendrobatidis, Bd).
  3. In our case study, we found evidence for various state assignment errors: the sampling protocol performed poorly in detecting Bd, pathogen detection was highly dependent on infection intensity and false positives were non-negligible. Incorporating state uncertainty yielded significantly higher estimates of infection prevalence and 4–5 times lower rates of infection state transitions compared to those obtained from a traditional multistate model.
  4. Our results highlight that incorporating state assignment errors improves inference on the ecological process, especially when sensitivity and specificity of the state assignment processes are low. The general model structure can be applied to other HMMs, providing a foundation for modelling state uncertainty in related models. For disease-structured multistate models, we recommend conducting robust design surveys and collecting samples during each capture event to facilitate incorporating pathogen detection errors.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.13993","usgsCitation":"Hollanders, M., and Royle, A., 2022, Know what you don't know: Embracing state uncertainty in disease-structured multistate models: Methods in Ecology and Evolution, v. 13, no. 12, p. 2827-2837, https://doi.org/10.1111/2041-210X.13993.","productDescription":"11 p.","startPage":"2827","endPage":"2837","ipdsId":"IP-143355","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":445975,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13993","text":"Publisher Index Page"},{"id":409291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-10-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Hollanders, Matthijs","contributorId":299029,"corporation":false,"usgs":false,"family":"Hollanders","given":"Matthijs","email":"","affiliations":[{"id":64751,"text":"Southern Cross University, Lismore, New South Wales","active":true,"usgs":false}],"preferred":false,"id":856901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":856902,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70239143,"text":"70239143 - 2022 - On the use of high-resolution and deep-learning seismic catalogs for short-term earthquake forecasts: Potential benefits and current limitations","interactions":[],"lastModifiedDate":"2022-12-29T13:12:05.588882","indexId":"70239143","displayToPublicDate":"2022-10-31T07:09:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12989,"text":"Journal of Geophysical Research--Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"On the use of high-resolution and deep-learning seismic catalogs for short-term earthquake forecasts: Potential benefits and current limitations","docAbstract":"

Enhanced earthquake catalogs provide detailed images of evolving seismic sequences. Currently, these data sets take some time to be released but will soon become available in real time. Here, we explore whether and how enhanced seismic catalogs feeding into established short-term earthquake forecasting protocols may result in higher predictive skill. We consider three enhanced catalogs for the 2016–2017 Central Italy sequence, featuring a bulk completeness lower by at least two magnitude units compared to the real-time catalog and an improved hypocentral resolution. We use them to inform a set of physical Coulomb Rate-and-State (CRS) and statistical Epidemic-Type Aftershock Sequence (ETAS) models to forecast the space-time occurrence of M3+ events during the first 6 months of the sequence. We track model performance using standard likelihood-based metrics and compare their skill against the best-performing CRS and ETAS models among those developed with the real-time catalog. We find that while the incorporation of the triggering contributions from new small magnitude detections of the enhanced catalogs is beneficial for both types of forecasts, these models do not significantly outperform their respective near real-time benchmarks. To explore the reasons behind this result, we perform targeted sensitivity tests that show how (a) the typical spatial discretizations of forecast experiments (\"urn:x-wiley:21699313:media:jgrb55931:jgrb55931-math-0001\"2 km) hamper the ability of models to capture highly localized secondary triggering patterns and (b) differences in earthquake parameters (i.e., magnitude and hypocenters) reported in different catalogs can affect forecast evaluation. These findings will contribute toward improving forecast model design and evaluation strategies for next-generation seismic catalogs.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JB025202","usgsCitation":"Mancini, S., Segou, M., Werner, M.J., Parsons, T.E., Beroza, G.C., and Chiaraluce, L., 2022, On the use of high-resolution and deep-learning seismic catalogs for short-term earthquake forecasts: Potential benefits and current limitations: Journal of Geophysical Research--Solid Earth, v. 127, no. 11, e2022JB025202, 16 p., https://doi.org/10.1029/2022JB025202.","productDescription":"e2022JB025202, 16 p.","ipdsId":"IP-143668","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":445979,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2022jb025202","text":"External Repository"},{"id":411176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 12.153022380111537,\n 43.88263963722096\n ],\n [\n 12.153022380111537,\n 42.213562034839185\n ],\n [\n 14.568988554409458,\n 42.213562034839185\n ],\n [\n 14.568988554409458,\n 43.88263963722096\n ],\n [\n 12.153022380111537,\n 43.88263963722096\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"127","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Mancini, Simone 0000-0003-3415-2080","orcid":"https://orcid.org/0000-0003-3415-2080","contributorId":225525,"corporation":false,"usgs":false,"family":"Mancini","given":"Simone","email":"","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":860333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Segou, Margarita","contributorId":199044,"corporation":false,"usgs":false,"family":"Segou","given":"Margarita","affiliations":[],"preferred":false,"id":860334,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Werner, Maximillan J.","contributorId":194147,"corporation":false,"usgs":false,"family":"Werner","given":"Maximillan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":860335,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":860336,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beroza, Gregory C.","contributorId":191201,"corporation":false,"usgs":false,"family":"Beroza","given":"Gregory","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":860337,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chiaraluce, Lauro","contributorId":300501,"corporation":false,"usgs":false,"family":"Chiaraluce","given":"Lauro","email":"","affiliations":[{"id":35766,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy","active":true,"usgs":false}],"preferred":false,"id":860338,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70237988,"text":"70237988 - 2022 - Observed and forecasted changes in land use by polar bears in the Beaufort and Chukchi Seas, 1985–2040","interactions":[],"lastModifiedDate":"2022-11-16T17:25:45.53204","indexId":"70237988","displayToPublicDate":"2022-10-31T06:52:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Observed and forecasted changes in land use by polar bears in the Beaufort and Chukchi Seas, 1985–2040","docAbstract":"

Monitoring changes in the distribution of large carnivores is important for managing human safety and supporting conservation. Throughout much of their range, polar bears (Ursus maritimus) are increasingly using terrestrial habitats in response to Arctic sea ice decline. Their increased presence in coastal areas has implications for bear-human conflict, inter-species interactions, and polar bear health and survival. We examined observed trends in land use over three decades by polar bears in the southern Beaufort Sea (SB) and Chukchi Sea (CS) where bears have traditionally spent most of the year on the sea ice. Using data from 408 adult females fitted with satellite radio-collars, we examined trends in the annual proportion of bears coming onshore (hereafter referred to as “percent of bears”) during the summer for ≥21 days, arrival and departure dates, duration spent onshore and relationships with sea ice metrics. We then estimated future land use through 2040 by extrapolating trends and by combining observed relationships between land use and sea ice with projections of future sea ice from an ensemble of earth system models. The observed percent of bears summering onshore and their duration onshore was correlated with the percent of open water that occurred within their population’s range between July and October. As sea ice declined, the percent of bears summering onshore increased from ~5 to 30% in the SB and ~10 to 50% in the CS and duration onshore increased by >30 days to 60–70 days in both populations. Using a range of greenhouse gas emission scenarios and adjustments for faster than forecasted sea ice loss we estimated that 50-62% of SB and 79-88% of CS bears will spend 90–108 and 110–126 days onshore during summer in the SB and CS, respectively, by 2040. Sea ice projections varied little between greenhouse gas emission scenarios prior to 2040 but diverged thereafter. Observed and forecasted increases in polar bear land occupancy puts more bears in proximity to human activities and settlements for longer durations while extending the lack of access to their primary prey. Because human conflict is one of the primary factors affecting the conservation of large carnivores worldwide, mitigation of bear-human interactions on land will be an increasingly important component of polar bear conservation.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02319","usgsCitation":"Rode, K.D., Douglas, D.C., Atwood, T.C., Durner, G.M., Wilson, R., and Pagano, A.M., 2022, Observed and forecasted changes in land use by polar bears in the Beaufort and Chukchi Seas, 1985–2040: Global Ecology and Conservation, v. 40, e02319, 21 p., https://doi.org/10.1016/j.gecco.2022.e02319.","productDescription":"e02319, 21 p.","ipdsId":"IP-144828","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":445984,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02319","text":"Publisher Index Page"},{"id":435636,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XEOBWV","text":"USGS data release","linkHelpText":"Polar Bear Continuous Time-Correlated Random Walk (CTCRW) Location Data Derived from Satellite Location Data, Chukchi and Beaufort Seas, July-November 1985-2017"},{"id":409057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Russia, United States","state":"Alaska","otherGeospatial":"Beaufort Sea, Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 179.9,\n 80\n ],\n [\n 158.6872334047083,\n 80\n ],\n [\n 158.6872334047083,\n 54\n ],\n [\n 179.9,\n 54\n ],\n [\n 179.9,\n 80\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.5651724337921,\n 80\n ],\n [\n -179.9,\n 80\n ],\n [\n -179.9,\n 65\n ],\n [\n -103.5651724337921,\n 65\n ],\n [\n -103.5651724337921,\n 80\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -160,\n 65\n ],\n [\n -179.9,\n 65\n ],\n [\n -179.9,\n 54\n ],\n [\n -160,\n 54\n ],\n [\n -160,\n 65\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","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":856441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":856442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":856443,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":856444,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Ryan R. ","contributorId":222456,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan R. ","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":856445,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":856446,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70237947,"text":"70237947 - 2022 - Modeling geomagnetic induction in submarine cables","interactions":[],"lastModifiedDate":"2022-11-01T11:54:23.10118","indexId":"70237947","displayToPublicDate":"2022-10-31T06:48:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12804,"text":"Frontiers in Physics","active":true,"publicationSubtype":{"id":10}},"title":"Modeling geomagnetic induction in submarine cables","docAbstract":"

Submarine cables have become a vital component of modern infrastructure, but past submarine cable natural hazard studies have mostly focused on potential cable damage from landslides and tsunamis. A handful of studies examine the possibility of space weather effects in submarine cables. The main purpose of this study is to develop a computational model, using Python, of geomagnetic induction on submarine cables. The model is used to estimate the induced voltage in the submarine cables in response to geomagnetic disturbances. It also utilizes newly acquired knowledge from magnetotelluric studies and associated investigations of geomagnetically induced currents in power systems. We describe the Python-based software, its working principle, inputs/outputs based on synthetic geomagnetic field data, and compare its operational capabilities against analytical solutions. We present the results for different model inputs, and find: 1) the seawater layer acts as a shield in the induction process: the greater the ocean depth, the smaller the seafloor geoelectric field; and 2) the model is sensitive to the Ocean-Earth layered conductivity structure.

","language":"English","publisher":"Frontiers","doi":"10.3389/fphy.2022.1022475","usgsCitation":"Chakraborty, S., Boteler, D.H., Shi, X., Murphy, B.S., Hartinger, M.D., Wang, X., Lucas, G., and Baker, J.B., 2022, Modeling geomagnetic induction in submarine cables: Frontiers in Physics, v. 10, 1022475, 14 p., https://doi.org/10.3389/fphy.2022.1022475.","productDescription":"1022475, 14 p.","ipdsId":"IP-145634","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":445987,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fphy.2022.1022475","text":"Publisher Index Page"},{"id":408969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-10-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Chakraborty, Shibaji","contributorId":298710,"corporation":false,"usgs":false,"family":"Chakraborty","given":"Shibaji","email":"","affiliations":[{"id":64669,"text":"Center for Space Science and Engineering Research, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":856297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boteler, David H.","contributorId":298711,"corporation":false,"usgs":false,"family":"Boteler","given":"David","email":"","middleInitial":"H.","affiliations":[{"id":7219,"text":"Natural Resources Canada","active":true,"usgs":false}],"preferred":false,"id":856298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shi, Xueling 0000-0001-8425-8241","orcid":"https://orcid.org/0000-0001-8425-8241","contributorId":296644,"corporation":false,"usgs":false,"family":"Shi","given":"Xueling","email":"","affiliations":[{"id":64114,"text":"Virginia Tech; NCAR High Altitude Observatory","active":true,"usgs":false}],"preferred":false,"id":856299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":856300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartinger, Michael D.","contributorId":298712,"corporation":false,"usgs":false,"family":"Hartinger","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":48422,"text":"Space Science Institute","active":true,"usgs":false}],"preferred":false,"id":856301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Xuan","contributorId":298713,"corporation":false,"usgs":false,"family":"Wang","given":"Xuan","email":"","affiliations":[{"id":64670,"text":"Department of Electrical Engineering, Tsinghua University","active":true,"usgs":false}],"preferred":false,"id":856302,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":856303,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baker, Joseph B. H. 0000-0001-6255-3039","orcid":"https://orcid.org/0000-0001-6255-3039","contributorId":296646,"corporation":false,"usgs":false,"family":"Baker","given":"Joseph","email":"","middleInitial":"B. H.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":856304,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70238514,"text":"70238514 - 2022 - Evolutionary ecology of fire","interactions":[],"lastModifiedDate":"2022-11-28T12:46:07.911621","indexId":"70238514","displayToPublicDate":"2022-10-31T06:44:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":808,"text":"Annual Review of Ecology, Evolution, and Systematics","active":true,"publicationSubtype":{"id":10}},"title":"Evolutionary ecology of fire","docAbstract":"

Fire has been an ecosystem process since plants colonized land over 400 million years ago. Many diverse traits provide a fitness benefit following fires, and these adaptive traits vary with the fire regime. Some of these traits enhance fire survival, while others promote recruitment in the postfire environment. Demonstrating that these traits are fire adaptations is challenging, since many arose early in the paleontological record, although increasingly better fossil records and phylogenetic analysis make timing of these trait origins to fire more certain. Resprouting from the base of stems is the most widely distributed fire-adaptive trait, and it is likely to have evolved under a diversity of disturbance types. The origins of other traits like serotiny, thick bark, fire-stimulated germination, and postfire flowering are more tightly linked to fire. Fire-adaptive traits occur in many environments: boreal and temperate forests, Mediterranean-type climate (MTC) shrublands, savannas, and other grasslands. MTC ecosystems are distinct in that many taxa in different regions have lost the resprouting ability and depend solely on postfire recruitment for postfire recovery. This obligate seeding mode is perhaps the most vulnerable fire-adaptive syndrome in the face of current global change, particularly in light of increasing anthropogenic fire frequency.

","language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev-ecolsys-102320-095612","usgsCitation":"Keeley, J., and Pausas, J.G., 2022, Evolutionary ecology of fire: Annual Review of Ecology, Evolution, and Systematics, v. 53, p. 203-225, https://doi.org/10.1146/annurev-ecolsys-102320-095612.","productDescription":"23 p.","startPage":"203","endPage":"225","ipdsId":"IP-137218","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445990,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/10261/303433","text":"External Repository"},{"id":409668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Keeley, Jon 0000-0002-4564-6521","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":216485,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pausas, Juli G.","contributorId":197439,"corporation":false,"usgs":false,"family":"Pausas","given":"Juli","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":857715,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237766,"text":"sim3491 - 2022 - Bedrock geologic map of the Crown Point quadrangle, Essex County, New York, and Addison County, Vermont","interactions":[],"lastModifiedDate":"2026-04-01T15:22:38.069829","indexId":"sim3491","displayToPublicDate":"2022-10-28T11:30:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3491","displayTitle":"Bedrock Geologic Map of the Crown Point Quadrangle, Essex County, New York, and Addison County, Vermont","title":"Bedrock geologic map of the Crown Point quadrangle, Essex County, New York, and Addison County, Vermont","docAbstract":"

The bedrock geology of the 7.5-minute Crown Point quadrangle consists of deformed and metamorphosed Mesoproterozoic gneisses of the Adirondack Highlands unconformably overlain by weakly deformed lower Paleozoic sedimentary rocks of the Champlain Valley. The Mesoproterozoic rocks occur on the eastern edge of the Adirondack Highlands and represent an extension of the Grenville Province of Laurentia. Granulite facies Mesoproterozoic paragneiss, marble, and amphibolite hosted the emplacement of granitic orthogneiss at approximately 1.18–1.15 giga-annum (Ga, billion years before present). The earliest of four phases of deformation (D1) is characterized by gneissosity, rarely preserved F1 isoclinal folds, and migmatite in the host rocks. Subsequent D2 deformation produced a composite penetrative gneissosity, migmatite, and isoclinal F2 folds. Towards the end of D2, felsic magmatism (including the regionally extensive Lyon Mountain Granite Gneiss, abbreviated “LMG”) spread by penetrative migration as semiconcordant alkali feldspar granite sheets subparallel to S2 into previously deformed lithologies. The LMG crystallized at approximately 1.15 Ga and displays synkinematic F2 folds thus constraining the time of D2 deformation. Exhumation during D3 produced F3 folds exhibited in regional domes and basins, such as the Keeney Mountain synform, local reactivation of the S2 foliation, partial melting, metamorphism, metasomatism, iron ore remobilization, and intrusion of magnetite-bearing pegmatite both as layer-parallel sills and crosscutting dikes. D4 created NE- and NW-trending boudinage, local high-grade ductile shear zones, and crosscutting granitic pegmatite dikes. Kilometer (km)-scale lineaments readily observed in lidar data are Ediacaran mafic dikes and Phanerozoic brittle faults. The Paleozoic rocks are part of the Early Cambrian to Late Ordovician great American carbonate bank on the ancient margin of Laurentia. Cambrian-Ordovician stratigraphy records an approximately 1-km-thick section and a transition from synrift clastics to passive margin peritidal carbonate buildups to gradually deeper water subtidal to shelf carbonates during foreland basin development associated with the Taconic orogeny. The Paleozoic rocks are weakly folded and block faulted. Large areas of the Champlain Valley are covered by undifferentiated glacial deposits, some of which contain mapped landslides. The map also shows waste rock piles and tailings from historical mining operations and large areas of artificial fill.

This study was undertaken to improve our understanding of the bedrock geology in the Adirondack Highlands, establish a modern framework for 1:24,000-scale bedrock geologic mapping in the Adirondacks, provide a context for historical iron mines in the eastern Adirondacks, and update the stratigraphy of the Champlain Valley in New York and Vermont. This Scientific Investigations Map of the Crown Point 7.5-minute quadrangle consists of a map sheet, an explanatory pamphlet, and a geographic information system database that includes bedrock geologic units, faults, outcrops, and structural geologic information. The map sheet includes a bedrock geologic map, a correlation of map units, a description of map units, an explanation of map symbols, three cross sections, and a simplified surficial geologic map that includes lidar percent slope. The explanatory pamphlet includes a discussion of the geology.

The bedrock geologic map on the map sheet is multi-layered and has been designed to enable the user to turn off the surficial map layer to view the concealed bedrock map units.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3491","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey, and the State of New York, Department of Education, New York Geological Survey","usgsCitation":"Walsh, G.J., Orndorff, R.C., and McAleer, R.J., 2022, Bedrock geologic map of the Crown Point quadrangle, Essex County, New York, and Addison County, Vermont: U.S. Geological Survey Scientific Investigations Map 3491, 1 sheet, scale 1:24,000, 44-p. pamphlet, https://doi.org/10.3133/sim3491.","productDescription":"Pamphlet: viii, 44 p.; Sheet: 62.00 x 41.00 inches; Base Map; Database; Metadata","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-117525","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":435638,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1FHRNVU","text":"USGS data release","linkHelpText":"Database for the bedrock geologic map of the Crown Point quadrangle, Essex County, New York, and Addison County, Vermont"},{"id":410043,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_sheet1.pdf","size":"178 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":408680,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_metadata.zip","size":"216 KB","linkFileType":{"id":6,"text":"zip"}},{"id":408682,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_basemap.zip","text":"Topographic Spatial Data","size":"119 MB","linkFileType":{"id":6,"text":"zip"}},{"id":408679,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_database.zip","size":"4.40 MB","linkFileType":{"id":6,"text":"zip"}},{"id":408674,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_pamphlet.pdf","text":"Pamphlet","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3491"},{"id":408673,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3491/coverthb.jpg"},{"id":501933,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113783.htm","linkFileType":{"id":5,"text":"html"}},{"id":408681,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_openaccess.zip","text":"Open Access","size":"6.29 MB","linkFileType":{"id":6,"text":"zip"}}],"country":"United States","state":"New York, Vermont","county":"Addison County, Essex County","otherGeospatial":"Crown Point quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.5,\n 44\n ],\n [\n -73.5,\n 43.875\n ],\n [\n -73.375,\n 43.875\n ],\n [\n -73.375,\n 44\n ],\n [\n -73.5,\n 44\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Florence Bascom Geoscience Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2022-10-28","noUsgsAuthors":false,"publicationDate":"2022-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Walsh, Gregory J. 0000-0003-4264-8836","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":265307,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":855539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orndorff, Randall C. 0000-0002-8956-5803 rorndorf@usgs.gov","orcid":"https://orcid.org/0000-0002-8956-5803","contributorId":2739,"corporation":false,"usgs":true,"family":"Orndorff","given":"Randall","email":"rorndorf@usgs.gov","middleInitial":"C.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":855540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@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":855541,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70237867,"text":"70237867 - 2022 - Nutrient limitation of phytoplankton in three tributaries of Chesapeake Bay: Detecting responses following nutrient reductions","interactions":[],"lastModifiedDate":"2022-10-28T14:11:06.662086","indexId":"70237867","displayToPublicDate":"2022-10-28T09:05:32","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Nutrient limitation of phytoplankton in three tributaries of Chesapeake Bay: Detecting responses following nutrient reductions","docAbstract":"

Many coastal ecosystems suffer from eutrophication, algal blooms, and dead zones due to excessive anthropogenic inputs of nitrogen (N) and phosphorus (P). This has led to regional restoration efforts that focus on managing watershed loads of N and P. In Chesapeake Bay, the largest estuary in the United States, dual nutrient reductions of N and P have been pursued since the 1980s. However, it remains unclear whether nutrient limitation – an indicator of restriction of algal growth by supplies of N and P – has changed in the tributaries of Chesapeake Bay following decades of reduction efforts. Toward that end, we analyzed historical data from nutrient-addition bioassay experiments and data from the Chesapeake Bay long-term water-quality monitoring program for six stations in three tidal tributaries (i.e., Patuxent, Potomac, and Choptank Rivers). Classification and regression tree (CART) models were developed using concurrent collections of water-quality parameters for each bioassay monitoring location during 1990-2003, which satisfactorily predicted the bioassay-based measures of nutrient limitation (classification accuracy = 96%). Predictions from the CART models using water-quality monitoring data showed enhanced nutrient limitation over the period of 1985-2020 at four of the six stations, including the downstream station in each of these three tributaries. These results indicate detectable, long-term water-quality improvements in the tidal tributaries. Overall, this research provides a new analytical tool for detecting signs of ecosystem recovery following nutrient reductions. More broadly, the approach can be adapted to other waterbodies with long-term bioassays and water-quality data sets to detect ecosystem recovery.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2022.119099","usgsCitation":"Zhang, Q., Fisher, T., Buchanan, C., Gustafson, A., Karrh, R., Murphy, R.R., Testa, J.M., Tian, R., and Tango, P.J., 2022, Nutrient limitation of phytoplankton in three tributaries of Chesapeake Bay: Detecting responses following nutrient reductions: Water Research, v. 226, 119099, 13 p., https://doi.org/10.1016/j.watres.2022.119099.","productDescription":"119099, 13 p.","ipdsId":"IP-141495","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":446002,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2022.119099","text":"Publisher Index Page"},{"id":408854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, Pennsylvania, Virginia, West Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.4995115646526,\n 39.73514540052781\n ],\n [\n -79.4995115646526,\n 36.84589584682243\n ],\n [\n -75.01514437223935,\n 36.84589584682243\n ],\n [\n -75.01514437223935,\n 39.73514540052781\n ],\n [\n -79.4995115646526,\n 39.73514540052781\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"226","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhang, Qian 0000-0003-0500-5655","orcid":"https://orcid.org/0000-0003-0500-5655","contributorId":174393,"corporation":false,"usgs":false,"family":"Zhang","given":"Qian","email":"","affiliations":[{"id":38802,"text":"University of Maryland Center for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":856002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Thomas R.","contributorId":292864,"corporation":false,"usgs":false,"family":"Fisher","given":"Thomas R.","affiliations":[{"id":63047,"text":"University of Maryland Center for Environmental Science, Horn Point Laboratory, 2020 Horns Point Rd, Cambridge, MD 21613, USA","active":true,"usgs":false}],"preferred":false,"id":856003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buchanan, Claire 0000-0001-5627-448X","orcid":"https://orcid.org/0000-0001-5627-448X","contributorId":291854,"corporation":false,"usgs":false,"family":"Buchanan","given":"Claire","email":"","affiliations":[{"id":39005,"text":"ICPRB","active":true,"usgs":false}],"preferred":false,"id":856004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gustafson, Anne B.","contributorId":292865,"corporation":false,"usgs":false,"family":"Gustafson","given":"Anne 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M.","contributorId":244524,"corporation":false,"usgs":false,"family":"Testa","given":"Jeremy","email":"","middleInitial":"M.","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":false,"id":856008,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tian, Richard 0000-0002-9416-8669","orcid":"https://orcid.org/0000-0002-9416-8669","contributorId":261309,"corporation":false,"usgs":false,"family":"Tian","given":"Richard","email":"","affiliations":[{"id":52807,"text":"U.S. Environmental Protection Agency Chesapeake Bay Program","active":true,"usgs":false}],"preferred":false,"id":856009,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tango, Peter J. 0000-0001-6669-6969","orcid":"https://orcid.org/0000-0001-6669-6969","contributorId":292845,"corporation":false,"usgs":true,"family":"Tango","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856010,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70238167,"text":"70238167 - 2022 - Spatial models of jaguar energy expenditure in response to border wall construction and remediation","interactions":[],"lastModifiedDate":"2022-11-15T12:50:52.470023","indexId":"70238167","displayToPublicDate":"2022-10-28T06:47:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9319,"text":"Frontiers in Conservation Science","active":true,"publicationSubtype":{"id":10}},"title":"Spatial models of jaguar energy expenditure in response to border wall construction and remediation","docAbstract":"

The construction of a wall at the United States-Mexico border is known to impede and deter movement of terrestrial wildlife between the two countries. One such species is the jaguar, in its northernmost range in the borderlands of Arizona and Sonora. We developed an anisotropic cost distance model for jaguar in a binational crossing area of the Madrean Sky Islands at the United States-Mexico border in Southern Arizona as a case study by using previously collected GPS tracking data for jaguars, bioenergetic calculations for pumas, and a digital elevation model. This model describes projected energy expenditure for jaguar to reach key water sources north of the international border. These desert springs and the broader study region provide vital habitat for jaguar conservation and reintroduction efforts in the United States. An emerging impediment to jaguar conservation and reintroduction is border infrastructure including border wall. By comparing walled and un-walled border sections, and three remediation scenarios, we demonstrate that existing border infrastructure significantly increases energy expenditure by jaguars and that some partial remediation scenarios are more beneficial than others. Our results demonstrate opportunities for remediation. Improved understanding of how border infrastructure impacts physiological requirements and resulting impacts to jaguar and other terrestrial wildlife in the United States-Mexico borderlands may inform conservation management.

","language":"English","publisher":"Frontiers","doi":"10.3389/fcosc.2022.1012010","usgsCitation":"Chambers, S.N., Villarreal, M.L., Norman, L., Bravo, J.C., and Traphagen, M.B., 2022, Spatial models of jaguar energy expenditure in response to border wall construction and remediation: Frontiers in Conservation Science, v. 3, 1012010, 9 p., https://doi.org/10.3389/fcosc.2022.1012010.","productDescription":"1012010, 9 p.","ipdsId":"IP-143998","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":446012,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fcosc.2022.1012010","text":"Publisher Index Page"},{"id":435642,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DSSV2Q","text":"USGS data release","linkHelpText":"Maps of cumulative energy expenditure models for jaguar in southern Arizona"},{"id":409349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Tumacacori Highlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.7240776436901,\n 32.20918805856094\n ],\n [\n -111.7240776436901,\n 31.199752402944327\n ],\n [\n -110.41670459681502,\n 31.199752402944327\n ],\n [\n -110.41670459681502,\n 32.20918805856094\n ],\n [\n -111.7240776436901,\n 32.20918805856094\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2022-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Chambers, Samuel Norton 0000-0002-9840-7989","orcid":"https://orcid.org/0000-0002-9840-7989","contributorId":297110,"corporation":false,"usgs":true,"family":"Chambers","given":"Samuel","email":"","middleInitial":"Norton","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":857031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":857032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":857033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bravo, Juan Carlos","contributorId":299075,"corporation":false,"usgs":false,"family":"Bravo","given":"Juan","email":"","middleInitial":"Carlos","affiliations":[{"id":64759,"text":"Wildlands Network","active":true,"usgs":false}],"preferred":false,"id":857034,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Traphagen, Myles B.","contributorId":299076,"corporation":false,"usgs":false,"family":"Traphagen","given":"Myles","email":"","middleInitial":"B.","affiliations":[{"id":64759,"text":"Wildlands Network","active":true,"usgs":false}],"preferred":false,"id":857035,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237853,"text":"70237853 - 2022 - Probing the upper end of intracontinental earthquake magnitude: A prehistoric example from the Dzhungarian and Lepsy faults of Kazakhstan","interactions":[],"lastModifiedDate":"2022-10-27T16:07:43.167415","indexId":"70237853","displayToPublicDate":"2022-10-27T10:52:35","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Probing the upper end of intracontinental earthquake magnitude: A prehistoric example from the Dzhungarian and Lepsy faults of Kazakhstan","docAbstract":"The study of surface ruptures is key to understanding the earthquake occurrence of faults especially in the absence of historical events. We present a detailed analysis of geomorphic displacements along the Dzhungarian Fault, which straddles the border of China and Kazakhstan. We use digital elevation models derived from structure-from-motion analysis of Pléiades satellite imagery and drone imagery from specific field sites to measure surface offsets. We provide direct age constraints from alluvial terraces displaced by faulting and indirect dating from morphological analysis of the scarps. We find that the southern 250 km of the fault likely ruptured in a single event in the last 4000 years, with displacements of 10-15 m, and potentially up to 20 m at one site. We infer that this Dzhungarian rupture is likely linked with a previously identified paleo-earthquake rupture on the Lepsy Fault through a system of splays in the intervening highlands. Though there are remaining uncertainties regarding consistency in age constraints between the two fault ruptures, the majority of sites along the two faults are consistent with a most recent event 2000-4000 years ago. Rupture on the Dzhungarian fault alone is likely to have exceeded Mw 8, and the combined Lepsy-Dzhungarian rupture may have been up to Mw 8.4. Despite being at the upper end of known or inferred continental earthquake magnitudes, our proposed scenario combining the 375 km of the Dzhungarian and Lepsy ruptures yields a slip-to-length ratio consistent with global averages and so do other historical intra-continental earthquakes in Central Asia.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022TC007300","usgsCitation":"Tsai, C., Abdrakhmatov, K., Mukambayev, A., Elliott, A.J., Elliott, J.R., Grutzner, C., Rhodes, E.J., Ivester, A.H., Walker, R.T., and Wilkinson, R., 2022, Probing the upper end of intracontinental earthquake magnitude: A prehistoric example from the Dzhungarian and Lepsy faults of Kazakhstan: Tectonics, v. 41, no. 10, e2022TC007300, 33 p., https://doi.org/10.1029/2022TC007300.","productDescription":"e2022TC007300, 33 p.","ipdsId":"IP-141076","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":446017,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022tc007300","text":"Publisher Index Page"},{"id":408807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China, Kazakhstan","otherGeospatial":"Dzhungarian fault, Lepsy fault, Tien Shan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 78.02959818866935,\n 46.96607203759535\n ],\n [\n 78.02959818866935,\n 43.10814337437159\n ],\n [\n 85.50354350935629,\n 43.10814337437159\n ],\n [\n 85.50354350935629,\n 46.96607203759535\n ],\n [\n 78.02959818866935,\n 46.96607203759535\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"41","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-10-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Tsai, Chia-Hsin 0000-0002-2496-511X","orcid":"https://orcid.org/0000-0002-2496-511X","contributorId":298575,"corporation":false,"usgs":false,"family":"Tsai","given":"Chia-Hsin","email":"","affiliations":[{"id":25447,"text":"University of Oxford","active":true,"usgs":false}],"preferred":false,"id":855916,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abdrakhmatov, Kanatbek 0000-0002-8106-3876","orcid":"https://orcid.org/0000-0002-8106-3876","contributorId":298576,"corporation":false,"usgs":false,"family":"Abdrakhmatov","given":"Kanatbek","email":"","affiliations":[{"id":64616,"text":"Kyrgyz Institute of Seismology","active":true,"usgs":false}],"preferred":false,"id":855917,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mukambayev, Aidyn 0000-0002-5987-1439","orcid":"https://orcid.org/0000-0002-5987-1439","contributorId":298577,"corporation":false,"usgs":false,"family":"Mukambayev","given":"Aidyn","email":"","affiliations":[{"id":64617,"text":"Kazakhstan National Data Center","active":true,"usgs":false}],"preferred":false,"id":855918,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elliott, Austin John 0000-0001-5924-7268","orcid":"https://orcid.org/0000-0001-5924-7268","contributorId":248824,"corporation":false,"usgs":true,"family":"Elliott","given":"Austin","email":"","middleInitial":"John","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":855919,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elliott, John R. 0000-0003-2957-4596","orcid":"https://orcid.org/0000-0003-2957-4596","contributorId":244224,"corporation":false,"usgs":false,"family":"Elliott","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":855920,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grutzner, Christoph 0000-0003-0777-2751","orcid":"https://orcid.org/0000-0003-0777-2751","contributorId":298578,"corporation":false,"usgs":false,"family":"Grutzner","given":"Christoph","email":"","affiliations":[{"id":64618,"text":"Freidrich Schiller University Jena","active":true,"usgs":false}],"preferred":false,"id":855921,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rhodes, Edward J. 0000-0002-0361-8637","orcid":"https://orcid.org/0000-0002-0361-8637","contributorId":192722,"corporation":false,"usgs":false,"family":"Rhodes","given":"Edward","email":"","middleInitial":"J.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false},{"id":28159,"text":"University of Sheffield","active":true,"usgs":false}],"preferred":false,"id":855922,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ivester, A. 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