Invasive species are a global threat to ecosystem biodiversity and function; non-native grass invasion has been particularly problematic in sparsely vegetated ecosystems such as open dunes. Native plant population responses to invasion, however, are infrequently translated to landscape scales, limiting the effectiveness of these data for addressing conservation issues. We quantified population density, total population size, and age class distribution of the federally-endangered plant species Antioch Dunes evening primrose (Oenothera deltoides subsp. howellii), at sites along a non-native grass invasion gradient in California, USA. We then scaled relationships between invasion and plant density across the species’ range using spatial models and remote sensing data. Adult and juvenile O. deltoides subsp. howellii densities were more than 10 times higher in non-invaded areas (grids with 10% total plant cover) when compared to highly-invaded areas (grids with 80% total plant cover). The ratio of O. deltoides subsp. howellii juveniles to adults decreased to less than 1 at 54% total cover, highlighting sensitivity of the regeneration niche to invasion. Spatial models mapped hotspots of O. deltoides subsp. howellii abundance and population structure across the landscape at sub-meter scales. Scaling the impacts of increasing invasion on plant species of conservation concern holds promise when coupled with remote sensing approaches, especially in naturally low-cover ecosystems where readily available metrics (e.g., Normalized Difference Vegetation Index) can be used to quantify invasion. These spatial models inform how future invasive species management may influence population size and spatial distribution of species of conservation concern.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10530-021-02516-5","usgsCitation":"Jones, S., Kennedy, A., Freeman, C.M., and Thorne, K., 2021, Intensity of grass invasion negatively correlated with population density and age structure of an endangered dune plant across its range: Biological Invasions, v. 23, p. 2451-2471, https://doi.org/10.1007/s10530-021-02516-5.","productDescription":"21 p.","startPage":"2451","endPage":"2471","ipdsId":"IP-126563","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":436368,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PRVA0M","text":"USGS data release","linkHelpText":"Antioch Dunes evening primrose (Oenothera deltoides subsp. howellii) juvenile and adult abundance across the known range, California, USA (2019)"},{"id":386030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Antioch","otherGeospatial":"San Francisco Bay-Delta region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.92729949951172,\n 37.998597644907385\n ],\n [\n -121.6691207885742,\n 37.998597644907385\n ],\n [\n -121.6691207885742,\n 38.089174937729794\n ],\n [\n -121.92729949951172,\n 38.089174937729794\n ],\n [\n -121.92729949951172,\n 37.998597644907385\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2021-05-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Scott 0000-0002-1056-3785","orcid":"https://orcid.org/0000-0002-1056-3785","contributorId":215602,"corporation":false,"usgs":true,"family":"Jones","given":"Scott","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Anna 0000-0002-6530-7498","orcid":"https://orcid.org/0000-0002-6530-7498","contributorId":259164,"corporation":false,"usgs":true,"family":"Kennedy","given":"Anna","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816667,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Chase M. 0000-0003-4211-6709 cfreeman@usgs.gov","orcid":"https://orcid.org/0000-0003-4211-6709","contributorId":150052,"corporation":false,"usgs":true,"family":"Freeman","given":"Chase","email":"cfreeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816668,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816669,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222453,"text":"70222453 - 2021 - Quick and dirty (and accurate) 3-D paleoseismic trench models using coded scale bars","interactions":[],"lastModifiedDate":"2021-11-01T15:38:15.192062","indexId":"70222453","displayToPublicDate":"2021-05-12T08:43:23","publicationYear":"2021","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":"Quick and dirty (and accurate) 3-D paleoseismic trench models using coded scale bars","docAbstract":"Structure‐from‐motion (SfM) modeling has dramatically increased the speed of generating geometrically accurate orthophoto mosaics of paleoseismic trenches, but some aspects of this technique remain time and labor intensive. Model accuracy relies on control points to establish scale, reduce distortion, and orient 3D models. Traditional SfM methods use total station or Global Navigation Satellite System (GNSS) surveys to constrain models, but collecting control points along a vertical trench wall is often inhibited by poor line of sight to the survey sensor or limited sky view and requires many hours in the field and office. We used physical scale bars printed with coded targets to constrain SfM models of a dusty, 46‐m‐long trench excavation across the Teton fault (Wyoming, U.S.A.). We present a workflow for generating quick and accurate 3D SfM models and orthophoto mosaics and compare the effectiveness of using scale bar, GNSS, and total‐station control in the models. Our results show that the scale bar model deviates from total station survey points by an average of 3.1 cm (maximum of 5.3 cm). In addition, the scale‐bar model only deviates an average of 1.7 cm (maximum 3.5 cm) when compared to the best model alternative, the SfM model controlled by the total station survey. Scale bars eliminate several hours needed to collect and incorporate control points from total station or GNSS surveys and significantly simplify the workflow, at the cost of slightly increased 3D model and orthophoto mosaic error. Our results further suggest that trench models can be constrained with at least four physical scale bars, but using five to six physical scale bars provides redundant control for field deployment and model optimization. The scale bar method for paleoseismic trenches proves to be portable and fast, minimizes the need for specialized survey equipment, and maintains model accuracy needed for mapping trench walls.
Algal and cyanobacterial blooms can foul water systems, inhibit recreation, and produce cyanotoxins, which can be toxic to humans, domestic animals, and wildlife. Blooms that recur yearly present a special challenge, in that chronic effects of most cyanotoxins are unknown. To better understand cyanotoxin timing, possible environmental triggers, and inter-relations among taxa and toxins in bloom communities, recurring cyanobacterial blooms were investigated at three recreational sites in Kabetogama Lake in Voyageurs National Park from 2016-2019. Results indicated that peak neurotoxin concentrations occurred before peak microcystin concentrations and that toxin-forming cyanobacteria were present before visible blooms, which is a serious human health concern. Two cyanotoxin mixture models (MIX) and two microcystin (MC) models were developed using near-real-time environmental variables and additional comprehensive variables based on laboratory analyses. Comprehensive models explained more variability than the environmental models and neither MIX model was a better fit than the MC models. However, the MIX models produced no false negatives, indicating that all observations above human-health regulatory guidelines were simulated by the MIX models. The results show that a model based on a cyanotoxin mixture is more protective of human health than a model based on microcystin alone. In 2019, 7 of 19 toxins were detected in various mixtures. The potential toxin producing cyanobacteria, Microcystis, was significantly correlated with microcystin-YR, while Pseudanabaena sp. and Synechococcus sp. were negatively correlated to several toxins. Jaccard and Sorenson indices indicated strong same-day similarities among the three bloom communities. Nitrogen-fixing cyanobacteria were present at every site, and when combined with internal loading of phosphorus, might explain similarities among sites, and why seasonal differences, even in samples from the same site, were stronger. Information from this dissertation adds to the body of work on recurring blooms and under-studied toxins and toxin mixtures, providing a better understanding of future research options for freshwater cyanotoxins in and outside of Voyageurs National Park.
","language":"English","publisher":"North Dakota State University","usgsCitation":"Christensen, V., 2021, Freshwater cyanotoxin mixtures in recurring cyanobacterial blooms in Voyageurs National Park, 221 p.","productDescription":"221 p.","ipdsId":"IP-128041","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":409293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":409284,"type":{"id":15,"text":"Index Page"},"url":"https://www.proquest.com/docview/2547519599","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Minnesota","otherGeospatial":"Kabetogama Lake, Voyageurs National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.7287375311439,\n 48.44384887858732\n ],\n [\n -92.74528481592849,\n 48.46823569471036\n ],\n [\n -92.85651934142741,\n 48.45238559671293\n ],\n [\n -92.80320031267578,\n 48.47311165228035\n ],\n [\n -92.9355785909554,\n 48.46823569471036\n ],\n [\n -93.01371854688433,\n 48.52184546050012\n ],\n [\n -93.05508675884663,\n 48.53280411143439\n ],\n [\n -93.11300225559437,\n 48.51271143988237\n ],\n [\n -93.11759872359,\n 48.48469017375146\n ],\n [\n -93.06703757563596,\n 48.47494001557638\n ],\n [\n -93.06060252044176,\n 48.44628808733975\n ],\n [\n -93.02199218927704,\n 48.431041110668644\n ],\n [\n -92.98062397731476,\n 48.41151830276564\n ],\n [\n -92.95120658214137,\n 48.426161111635196\n ],\n [\n -92.92822424216214,\n 48.42189072806485\n ],\n [\n -92.9034033149849,\n 48.43226103720582\n ],\n [\n -92.86755086461727,\n 48.42189072806485\n ],\n [\n -92.80871607427095,\n 48.410908094197964\n ],\n [\n -92.78113726629607,\n 48.40480560576938\n ],\n [\n -92.7287375311439,\n 48.44384887858732\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Christensen, Victoria 0000-0003-4166-7461","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":220548,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856888,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70220886,"text":"70220886 - 2021 - Exploring the factors controlling the error characteristics of the Surface Water and Ocean Topography mission discharge estimates","interactions":[],"lastModifiedDate":"2021-06-30T19:00:04.291567","indexId":"70220886","displayToPublicDate":"2021-05-12T07:16:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Exploring the factors controlling the error characteristics of the Surface Water and Ocean Topography mission discharge estimates","docAbstract":"The Surface Water and Ocean Topography (SWOT) satellite mission will measure river width, water surface elevation, and slope for rivers wider than 50-100 m. SWOT observations will enable estimation of river discharge by using simple flow laws such as the Manning-Strickler equation, complementing in-situ streamgages. Several discharge inversion algorithms designed to compute unobserved flow law parameters (e.g. friction coefficient, bathymetry) have been proposed, but to date, a systematic assessment of factors controlling algorithm performance has not been conducted. Here, we assess the performance of the five algorithms that are expected to be used in the construction of the SWOT product. To perform this assessment, we used synthetic SWOT observations created with hydraulic model output corrupted with SWOT-like error. Prior information provided to the algorithms was purposefully limited to an estimate of mean annual flow (MAF), designed to produce a “worst case” benchmark. Prior MAF error was an important control on algorithm performance, but discharge estimates produced by the algorithms are less biased than the MAF; thus, the discharge algorithms improve on the prior. We show for the first time that accuracy and frequency of remote sensing observations are less important than prior bias, hydraulic variability among reaches, and flow law accuracy in governing discharge algorithm performance. The discharge errors and error sensitivities reported herein are a bounding benchmark, representing worst possible expected errors and error sensitivities. This study lays the groundwork to develop predictive power of algorithm performance, and thus map the global distribution of worst-case SWOT discharge accuracy.
Maintaining functional connectivity is critical for the long-term conservation of wildlife populations. Landscape genomics provides an opportunity to assess long-term functional connectivity by relating environmental variables to spatial patterns of genomic variation resulting from generations of movement, dispersal and mating behaviors. Identifying landscape features associated with gene flow at large geographic scales for highly mobile species is becoming increasingly possible due to more accessible genomic approaches, improved analytical methods and enhanced computational power. We characterized the genetic structure and diversity of migratory mule deer Odocoileus hemionus using 4051 single nucleotide polymorphisms in 406 individuals sampled across multiple habitats throughout Wyoming, USA. We then identified environmental variables associated with genomic variation within genetic groups and statewide using a stepwise approach to first evaluate nonlinear relationships of landscape resistance with genetic distances and then use mixed-effects modeling to choose top landscape genomic models. We identified three admixed genetic groups of mule deer and found that environmental variables associated with gene flow varied among genetic groups, revealing scale-dependent and regional variation in functional connectivity. At the statewide scale, more gene flow occurred in areas with low elevation and mixed habitat. In the southern genetic group, more gene flow occurred in areas with low elevation. In the northern genetic group, more gene flow occurred in grassland and forest habitats, while highways and energy infrastructure reduced gene flow. In the western genetic group, the null model of isolation by distance best represented genetic patterns. Overall, our findings highlight the role of different seasonal ranges on mule deer genetic connectivity, and show that anthropogenic features hinder connectivity. This study demonstrates the value of combining a large, genome-wide marker set with recent advances in landscape genomics to evaluate functional connectivity in a wide-ranging migratory species.
Large magnitude snow avalanches pose a hazard to humans and infrastructure worldwide. Analyzing the spatiotemporal behavior of avalanches and the contributory climate factors is important for understanding historical variability in climate-avalanche relationships as well as improving avalanche forecasting. We used established dendrochronological methods to develop a long-term (1867–2019) regional avalanche chronology for the Rocky Mountains of northwest Montana using tree-rings from 647 trees exhibiting 2134 avalanche-related growth disturbances. We then used principal component analysis and a generalized linear autoregressive moving average model to examine avalanche-climate relationships. Historically, large magnitude regional avalanche years were characterized by stormy winters with positive snowpack anomalies, with avalanche years over recent decades increasingly influenced by warmer temperatures and a shallow snowpack. The amount of snowpack across the region, represented by the first principal component, is shown to be directly related to avalanche probability. Coincident with warming and regional snowpack reductions, a decline of ~ 14% (~ 2% per decade) in overall large magnitude avalanche probability is apparent through the period 1950–2017. As continued climate warming drives further regional snowpack reductions in the study region our results suggest a decreased probability of regional large magnitude avalanche frequency associated with winters characterized by large snowpacks and a potential increase in large magnitude events driven by warming temperatures and spring precipitation.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-021-89547-z","usgsCitation":"Peitzsch, E.H., Pederson, G.T., Birkeland, K.W., Hendrikx, J., and Fagre, D.B., 2021, Climate drivers of large magnitude snow avalanche years in the U.S. northern Rocky Mountains: Scientific Reports, v. 11, 10032, 13 p., https://doi.org/10.1038/s41598-021-89547-z.","productDescription":"10032, 13 p.","ipdsId":"IP-124589","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":452307,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-021-89547-z","text":"Publisher Index Page"},{"id":385581,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.158203125,\n 47.15984001304432\n ],\n [\n -111.22558593749999,\n 47.15984001304432\n ],\n [\n -111.22558593749999,\n 48.951366470947725\n ],\n [\n -117.158203125,\n 48.951366470947725\n ],\n [\n -117.158203125,\n 47.15984001304432\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2021-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Peitzsch, Erich H. 0000-0001-7624-0455","orcid":"https://orcid.org/0000-0001-7624-0455","contributorId":202576,"corporation":false,"usgs":true,"family":"Peitzsch","given":"Erich","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":815449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":815450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Birkeland, Karl W.","contributorId":209943,"corporation":false,"usgs":false,"family":"Birkeland","given":"Karl","email":"","middleInitial":"W.","affiliations":[{"id":38033,"text":"U.S.D.A. Forest Service National Avalanche Center, Bozeman, Montana, USA","active":true,"usgs":false}],"preferred":false,"id":815451,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hendrikx, Jordy 0000-0001-6194-3596","orcid":"https://orcid.org/0000-0001-6194-3596","contributorId":140954,"corporation":false,"usgs":false,"family":"Hendrikx","given":"Jordy","email":"","affiliations":[{"id":13628,"text":"Department of Earth Sciences, P.O. Box 173480, Montana State University, Bozeman, MT, USA. 59717.","active":true,"usgs":false}],"preferred":false,"id":815452,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":815471,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227795,"text":"70227795 - 2021 - Gradient self-potential logging in the Rio Grande to identify gaining and losing reaches across the Mesilla Valley","interactions":[],"lastModifiedDate":"2022-01-31T12:42:56.341708","indexId":"70227795","displayToPublicDate":"2021-05-11T06:38:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Gradient self-potential logging in the Rio Grande to identify gaining and losing reaches across the Mesilla Valley","docAbstract":"Accurate population estimates provide the foundation for managing feral horses (Equus caballus ferus) across the western United States. Certain feral horse populations are protected by the Wild and Free-Roaming Horses and Burros Act of 1971 and managed by the Bureau of Land Management (BLM) or the United States Forest Service on designated herd management areas (HMAs) or wild horse territories, respectively. Horses are managed to achieve an appropriate management level (AML), which represents the number of horses determined by BLM to contribute to a thriving natural ecological balance and avoid deterioration of the range. To achieve AML for each HMA, BLM resource managers need accurate and precise population estimates. We tested the use of non-invasive fecal samples in a genetic capture-recapture framework to estimate population size in a closed horse population at the Little Book Cliffs HMA, Colorado, USA, with a known size of 153 individuals. We collected 1,957 samples over 3 independent sampling periods in 2014 and amplified them at 8 microsatellite loci. We applied mark-recapture models to determine population size using 954 samples that amplified at all 8 loci. We subsampled and reanalyzed our dataset to simulate different data collection protocols and evaluated effects on accuracy and precision of estimates using N-mixture modeling, full likelihood closed-capture modeling, and capwire single-occasion modeling that used data from all 3 sampling periods. Our model results were accurate and precise for analyses that used data from all 3 occasions; however, capwire single-occasion modeling was not accurate when we analyzed each sampling period separately. For all subsampling analysis scenarios, reducing sample size decreased precision, whether by reducing number of field staff, field days, or geographic areas surveyed on each period. Reducing spatial coverage of the survey area did not result in accurate population estimates and only marginally lowered the number of samples that would need to be collected to maintain accuracy. Because laboratory analysis contributes the greatest expense for this method ($80 U.S./sample), reducing fecal sample size is advantageous. Our results demonstrate that non-invasive sampling combined with good survey design and careful genetic and capture-recapture analyses can provide an alternative method to estimate the number of feral horses in a closed population. This method may be especially appropriate in situations where aerial inventories are not practical or accurate because of low sighting conditions. But the higher costs associated with laboratory sample analyses may reduce the method's feasibility compared to helicopter surveys.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22056","usgsCitation":"Schoenecker, K., King, S.R., Ekernas, L.S., and Oyler-McCance, S.J., 2021, Using fecal DNA and closed-capture models to estimate feral horse population size: Journal of Wildlife Management, v. 85, no. 6, p. 1150-1161, https://doi.org/10.1002/jwmg.22056.","productDescription":"12 p.","startPage":"1150","endPage":"1161","ipdsId":"IP-103976","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":396432,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Little Book Cliffs Horse management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.49136352539062,\n 39.13432124527173\n ],\n [\n -108.34304809570312,\n 39.13432124527173\n ],\n [\n -108.34304809570312,\n 39.27691581029594\n ],\n [\n -108.49136352539062,\n 39.27691581029594\n ],\n [\n -108.49136352539062,\n 39.13432124527173\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":202531,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835961,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sarah R. B. 0000-0002-9316-7488","orcid":"https://orcid.org/0000-0002-9316-7488","contributorId":280063,"corporation":false,"usgs":false,"family":"King","given":"Sarah","email":"","middleInitial":"R. B.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":835962,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ekernas, L. Stefan 0000-0002-9205-1985","orcid":"https://orcid.org/0000-0002-9205-1985","contributorId":223034,"corporation":false,"usgs":true,"family":"Ekernas","given":"L.","email":"","middleInitial":"Stefan","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835963,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835964,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220585,"text":"70220585 - 2021 - Efficacy of fenbendazole and ivermectin against Trichuris spp. in African green monkeys (Chlorocebus sabaeus) in Barbados West Indies","interactions":[],"lastModifiedDate":"2021-08-17T15:23:22.803496","indexId":"70220585","displayToPublicDate":"2021-05-10T07:35:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8604,"text":"Journal of the American Association for Laboratory Animal Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Efficacy of fenbendazole and ivermectin against Trichuris spp. in African green monkeys (Chlorocebus sabaeus) in Barbados West Indies","title":"Efficacy of fenbendazole and ivermectin against Trichuris spp. in African green monkeys (Chlorocebus sabaeus) in Barbados West Indies","docAbstract":"Tradeoff theory, which postulates that virulence provides both transmission costs and benefits for pathogens, has become widely adopted by the scientific community. Although theoretical literature exploring virulence-tradeoffs is vast, empirical studies validating various assumptions still remain sparse. In particular, truncation of transmission duration as a cost of virulence has been difficult to quantify with robust controlled in vivo studies. We sought to fill this knowledge gap by investigating how transmission rate and duration were associated with virulence for infectious hematopoietic necrosis virus (IHNV) in rainbow trout (Oncorhynchus mykiss). Using host mortality to quantify virulence and viral shedding to quantify transmission, we found that IHNV did not conform to classical tradeoff theory. More virulent genotypes of the virus were found to have longer transmission durations due to lower recovery rates of infected hosts, but the relationship was not saturating as assumed by tradeoff theory. Furthermore, the impact of host mortality on limiting transmission duration was minimal and greatly outweighed by recovery. Transmission rate differences between high and low virulence genotypes were also small and inconsistent. Ultimately, more virulent genotypes were found to have the overall fitness advantage, and there was no apparent constraint on the evolution of increased virulence for IHNV. However, using a mathematical model parameterized with experimental data, it was found that host culling resurrected the virulence tradeoff and provided low virulence genotypes with the advantage. Human-induced or natural culling, as well as host population fragmentation, may be some of the mechanisms by which virulence diversity is maintained in nature. This work highlights the importance of considering non-classical virulence tradeoffs.
The need of citizens in any nation to access geospatial data in readily usable form is critical to societal well-being, and in the United States (US), demands for information by scientists, students, professionals and citizens continue to grow. Areas such as public health, urbanization, resource management, economic development and environmental management require a variety of data collected from many sources to identify problems, monitor trends and propose solutions. Such information needs and demands have driven the coordination of federal and regional government agencies with respective private sector participation to develop national geospatial data infrastructures in many countries.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Handbook of big geospatial data","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-55462-0_23","usgsCitation":"Buttenfield, B.P., Stanislawski, L., Kronenfeld, B.J., and Shavers, E.J., 2021, The 4th paradigm in multiscale data representation: Modernizing the National Geospatial Data Infrastructure, chap. of Handbook of big geospatial data, p. 589-618, https://doi.org/10.1007/978-3-030-55462-0_23.","productDescription":"30 p.","startPage":"589","endPage":"618","ipdsId":"IP-125863","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":423017,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-05-08","publicationStatus":"PW","contributors":{"editors":[{"text":"Werner, Martin","contributorId":331851,"corporation":false,"usgs":false,"family":"Werner","given":"Martin","email":"","affiliations":[],"preferred":false,"id":888929,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Chiang, Yao-Yi","contributorId":288084,"corporation":false,"usgs":false,"family":"Chiang","given":"Yao-Yi","email":"","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":888930,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Buttenfield, Barbara P. 0000-0001-5961-5809","orcid":"https://orcid.org/0000-0001-5961-5809","contributorId":206887,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara","email":"","middleInitial":"P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":888724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanislawski, Larry 0000-0002-9437-0576","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":217849,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":888725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kronenfeld, Barry J. 0000-0002-9518-2462","orcid":"https://orcid.org/0000-0002-9518-2462","contributorId":207104,"corporation":false,"usgs":false,"family":"Kronenfeld","given":"Barry","email":"","middleInitial":"J.","affiliations":[{"id":5043,"text":"Eastern Illinois University","active":true,"usgs":false}],"preferred":false,"id":888726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":888727,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228733,"text":"70228733 - 2021 - Plasma metabolite indices are robust to extrinsic variation and useful indicators of foraging habitat quality in Lesser Scaup","interactions":[],"lastModifiedDate":"2024-01-11T18:34:27.235686","indexId":"70228733","displayToPublicDate":"2021-05-08T08:53:28","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10109,"text":"Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Plasma metabolite indices are robust to extrinsic variation and useful indicators of foraging habitat quality in Lesser Scaup","docAbstract":"Energy acquisition and storage are important for survival and fecundity of birds during resource-limited periods such as spring migration. Plasma-lipid metabolites (i.e. triglyceride [TRIG], β-hydroxybutyrate [BOHB]) have been used to index changes in lipid stores and, thus, have utility for assessing foraging habitat quality during migration. However, such an index may be affected by energetic maintenance costs, diet, and other factors, and further validation under experimental conditions is needed to understand potential sources of variation and verify existing indices. We evaluated a plasma-lipid metabolite index using 30 female and 28 male wild Lesser Scaup (Aythya affinis; hereafter scaup) held in short-term captivity (~24 hr) during spring migration. Similar to previous observational studies, BOHB was negatively associated and TRIG was positively associated with mass change (R2 = 0.68). BOHB estimates were nearly identical to those published on free-living scaup, but TRIG estimates differed from free-living scaup and varied by sex, with females having a greater rate of predicted mass change than captive and free-living males. Our results suggest TRIG may be a better measure of energy income than deposition because lipid deposition likely varies with energetic maintenance costs, stress, and underlying physiological processes while TRIG relates primarily to energy income. In contrast, BOHB was a reliable predictor of negative mass change across sexes. The sex-based differences in apparent lipid deposition rates warrant further research before a generalizable model is advisable for comparing mass change predictions across studies. However, if predictions are standardized, this technique is generally robust to variations in energy income vs. lipid deposition across sexes. Accordingly, our evaluation provides verification for the utility of plasma-lipid metabolites as an indicator of foraging habitat quality during migration.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithology/ukab029","usgsCitation":"Smith, E.J., Anteau, M.J., Hagy, H.M., and Jacques, C.N., 2021, Plasma metabolite indices are robust to extrinsic variation and useful indicators of foraging habitat quality in Lesser Scaup: Ornithology, v. 138, no. 3, ukab029, 11 p., https://doi.org/10.1093/ornithology/ukab029.","productDescription":"ukab029, 11 p.","ipdsId":"IP-101470","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":396096,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Mississippi River, Pool 19","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.43131256103514,\n 40.39336516184327\n ],\n [\n -91.32110595703125,\n 40.39336516184327\n ],\n [\n -91.32110595703125,\n 40.541199704952014\n ],\n [\n -91.43131256103514,\n 40.541199704952014\n ],\n [\n -91.43131256103514,\n 40.39336516184327\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"138","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Eric J.","contributorId":333129,"corporation":false,"usgs":false,"family":"Smith","given":"Eric","email":"","middleInitial":"J.","affiliations":[{"id":49637,"text":"Western Illinois University","active":true,"usgs":false}],"preferred":false,"id":892052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":835229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagy, Heath M.","contributorId":172326,"corporation":false,"usgs":false,"family":"Hagy","given":"Heath","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":835230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jacques, Christopher N.","contributorId":274285,"corporation":false,"usgs":false,"family":"Jacques","given":"Christopher","email":"","middleInitial":"N.","affiliations":[{"id":49637,"text":"Western Illinois University","active":true,"usgs":false}],"preferred":false,"id":835231,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222489,"text":"70222489 - 2021 - The timing and magnitude of changes to Hortonian overland flow at the watershed scale during the post-fire recovery process","interactions":[],"lastModifiedDate":"2021-07-30T13:19:06.765468","indexId":"70222489","displayToPublicDate":"2021-05-08T08:16:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"The timing and magnitude of changes to Hortonian overland flow at the watershed scale during the post-fire recovery process","docAbstract":"Extreme hydrologic responses following wildfires can lead to floods and debris flows with costly economic and societal impacts. Process-based hydrologic and geomorphic models used to predict the downstream impacts of wildfire must account for temporal changes in hydrologic parameters related to the generation and subsequent routing of infiltration-excess overland flow across the landscape. However, we lack quantitative relationships showing how parameters change with time-since-burning, particularly at the watershed scale. To assess variations in best-fit hydrologic parameters with time, we used the KINEROS2 hydrological model to explore temporal changes in hillslope saturated hydraulic conductivity (Ksh) and channel hydraulic roughness (nc) following a wildfire in the upper Arroyo Seco watershed (41.5 km2), which burned during the 2009 Station fire in the San Gabriel Mountains, California, USA. This study explored runoff-producing storms between 2008 and 2014 to infer watershed hydraulic properties by calibrating the model to observations at the watershed outlet. Modelling indicates Ksh is lowest in the first year following the fire and then increases at an average rate of approximately 4.2 mm/h/year during the first 5 years of recovery. The estimated values for Ksh in the first year following the fire are similar to those obtained in previous studies on smaller watersheds (<1.5 km2) following the Station fire, suggesting hydrologic changes detected here can be applied to lower-order watersheds. Hydraulic roughness, nc, was lowest in the first year following the fire, but increased by a factor of 2 after 1 year of recovery. Post-fire observations suggest changes in nc are due to changes in grain roughness and vegetation in channels. These results provide quantitative constraints on the magnitude of fire-induced hydrologic changes following severe wildfires in chaparral-dominated ecosystems as well as the timing of hydrologic recovery.
Any large, multifaceted data collection that is challenging to handle with traditional management practices can be branded ‘Big Data.’ Any big data containing geo-referenced attributes can be considered big geospatial data. The increased proliferation of big geospatial data is currently reforming the geospatial industry into a data-driven enterprise. Challenges in the big spatial data domain can be summarized as the ‘Big Vs’ – variety, volume, velocity, veracity and value. Big spatial data sources can be considered in two broad classes, active and passive, as each is impacted to varying degrees. Some of these challenges may be alleviated by reducing unprocessed, or minimally processed, (raw) data to features, which we refer to as the extraction of Elements of Interest (EOI). In fact, many applications require EOI extraction from raw data to enable their basic employment. This chapter presents current state-of-the-art methods to create EOI from some types of georeferenced big data. We classify the data types into two realms: active and passive. Active data are those collected specifically for the purpose to which they are applied. Passive data are those collected for purposes other than those for which they are utilized, included those ‘collected’ for no particular purpose at all. The chapter then presents use cases from both the active and passive spatial realms, including the active applications of terrain feature extraction from digital elevation models and vegetation mapping from remotely-sensed imagery and passive applications like building identification from VGI and point-of-interest data mining from social networks for land use classification. Finally, the chapter concludes with future research needs.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Handbook of big geospatial data","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-55462-0_5","usgsCitation":"Arundel, S., and Usery, E., 2021, Spatial data reduction through element -of-interest (EOI) extraction, chap. of Handbook of big geospatial data, p. 119-134, https://doi.org/10.1007/978-3-030-55462-0_5.","productDescription":"16 p.","startPage":"119","endPage":"134","ipdsId":"IP-113380","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":385704,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":815856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Usery, E. Lynn 0000-0002-2766-2173","orcid":"https://orcid.org/0000-0002-2766-2173","contributorId":204684,"corporation":false,"usgs":true,"family":"Usery","given":"E. Lynn","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":815857,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70220388,"text":"70220388 - 2021 - Using the Landsat Burned Area products to derive fire history relevant for fire management and conservation in the state of Florida, southeastern USA","interactions":[],"lastModifiedDate":"2024-05-16T15:27:57.216807","indexId":"70220388","displayToPublicDate":"2021-05-08T06:59:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5678,"text":"Fire","active":true,"publicationSubtype":{"id":10}},"title":"Using the Landsat Burned Area products to derive fire history relevant for fire management and conservation in the state of Florida, southeastern USA","docAbstract":"Development of comprehensive spatially explicit fire occurrence data remains one of the most critical needs for fire managers globally, and especially for conservation across the southeastern United States. Not only are many endangered species and ecosystems in that region reliant on frequent fire, but fire risk analysis, prescribed fire planning, and fire behavior modeling are sensitive to fire history due to the long growing season and high vegetation productivity. Spatial data that map burned areas over time provide critical information for evaluating management successes. However, existing fire data have undocumented shortcomings that limit their use when detailing the effectiveness of fire management at state and regional scales. Here, we assessed information in existing fire datasets for Florida and the Landsat Burned Area products based on input from the fire management community. We considered the potential of different datasets to track the spatial extents of fires and derive fire history metrics (e.g., time since last burn, fire frequency, and seasonality). We found that burned areas generated by applying a 90% threshold to the Landsat burn probability product matched patterns recorded and observed by fire managers at three pilot areas. We then created fire history metrics for the entire state from the modified Landsat Burned Area product. Finally, to show their potential application for conservation management, we compared fire history metrics across ownerships for natural pinelands, where prescribed fire is frequently applied. Implications of this effort include increased awareness around conservation and fire management planning efforts and an extension of derivative products regionally or globally.
","language":"English","publisher":"MDPI","doi":"10.3390/fire4020026","usgsCitation":"Teske, C., Vanderhoof, M.K., Hawbaker, T., Noble, J., and Hires, J.K., 2021, Using the Landsat Burned Area products to derive fire history relevant for fire management and conservation in the state of Florida, southeastern USA: Fire, v. 4, no. 2, 26, 21 p., https://doi.org/10.3390/fire4020026.","productDescription":"26, 21 p.","ipdsId":"IP-126697","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":452347,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fire4020026","text":"Publisher Index Page"},{"id":385562,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Panhandle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.64892578125,\n 29.554345125748267\n ],\n [\n -83.43017578125,\n 29.554345125748267\n ],\n [\n -83.43017578125,\n 30.939924331023445\n ],\n [\n -87.64892578125,\n 30.939924331023445\n ],\n [\n -87.64892578125,\n 29.554345125748267\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-05-08","publicationStatus":"PW","contributors":{"authors":[{"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":815369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":815372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":815371,"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":815370,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hires, J. Kevin","contributorId":257941,"corporation":false,"usgs":false,"family":"Hires","given":"J.","email":"","middleInitial":"Kevin","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":815373,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221481,"text":"70221481 - 2021 - Stochastic inversion of gravity, magnetic, tracer, lithology, and fault data for geologically realistic structural models: Patua Geothermal Field case study","interactions":[],"lastModifiedDate":"2021-06-17T11:49:03.530012","indexId":"70221481","displayToPublicDate":"2021-05-08T06:44:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Stochastic inversion of gravity, magnetic, tracer, lithology, and fault data for geologically realistic structural models: Patua Geothermal Field case study","docAbstract":"Financial risk due to geological uncertainty is a major barrier for geothermal development. Production from a geothermal well depends on the unknown location of subsurface geological structures, such as faults that contain hydrothermal fluids. Traditionally, geoscientists collect many different datasets, interpret the datasets manually, and create a single model estimating faults' locations. This method, however, does not provide information about the uncertainty regarding the location of faults and often does not fully respect all observed datasets. Previous researchers investigated the use of stochastic inversion schemes for addressing geological uncertainty, but often at the expense of geologic realism. In this paper, we present algorithms and open-source code to stochastically invert five typical datasets for creating geologically realistic structural models. Using a case study with real data from the Patua Geothermal Field, we show that these inversion algorithms are successful in finding an ensemble of structural models that are geologically realistic and match the observed data sufficiently. Geoscientists can use this ensemble of models to optimize reservoir management decisions given structural uncertainty.
Distilling my experience in having field mapped in detail the volcanic fields at Laguna del Maule and Long Valley and having worked out their time-volume-composition magmatic histories, I compare and contrast the postglacial rhyolites of the former with six multi-vent eruptive sequences of rhyolite in California. Compilations and discussions are made of volcanic-field areas and longevities, their compositions, vent distributions, individual batch and total volumes, eruptive episodicities, and tectonic influences. Growth of long-lived pluton-scale reservoirs of granitic crystal mush, from which the rhyolite melts separated, are interpreted in terms of conceptual models I published previously—(1) fundamentally basaltic transcrustal magmatism, 1981; (2) the deep-crustal MASH zone model, 1988; and (3) the rhyolite-melt crystal-mush model, 2001. Inferences and speculations are advanced concerning processes and timescales of rhyolite-melt separation from granitic mush and of prompt or long-delayed subsequent eruption.
The unknown onshore extent of megathrust earthquake rupture in the Cascadia subduction zone represents a key uncertainty in earthquake hazard for the Pacific Northwest that is governed by the physical state and mechanical properties of the plate interface. The Cascadia plate interface is segmented into an interseismically locked zone located primarily offshore that is expected to rupture in large earthquakes, a region of aseismic slow slip at greater depth, and an intervening transition zone of uncertain rupture potential. Here we image the evolution of the ratio of seismic compressional to shear wave velocities from the locked zone to the transition zone, which is related to changes in fluid content of the plate boundary zone, using a dense onshore–offshore seismic dataset from southernmost Cascadia. The locked zone shows evidence of high fluid content implying a high porosity, yet the downdip transition zone shows an order of magnitude lower porosity. This strong variation is consistent with models that contain a ductile region between the earthquake rupture and slow slip zones that would inhibit onshore propagation of future large earthquake ruptures and hence reduce seismic hazard.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41561-021-00740-1","usgsCitation":"Guo, H., McGuire, J., and Zhang, H., 2021, Correlation of porosity variations and rheological transitions on the southern Cascadia megathrust: Nature Geoscience, v. 14, no. 5, p. 341-348, https://doi.org/10.1038/s41561-021-00740-1.","productDescription":"8 p.","startPage":"341","endPage":"348","ipdsId":"IP-106445","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":387387,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cascadia subduction zone, Mendocino triple junction","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.925048828125,\n 39.85915479295669\n ],\n [\n -123.28857421875,\n 39.85915479295669\n ],\n [\n -123.28857421875,\n 40.96330795307353\n ],\n [\n -126.925048828125,\n 40.96330795307353\n ],\n [\n -126.925048828125,\n 39.85915479295669\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Guo, Hao","contributorId":261277,"corporation":false,"usgs":false,"family":"Guo","given":"Hao","email":"","affiliations":[{"id":52789,"text":"Univ. of Science and Technology of China","active":true,"usgs":false}],"preferred":false,"id":819659,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":219786,"corporation":false,"usgs":true,"family":"McGuire","given":"Jeffrey J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":819661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Haijiang","contributorId":174443,"corporation":false,"usgs":false,"family":"Zhang","given":"Haijiang","email":"","affiliations":[{"id":36359,"text":"University of Science and Technology of China, Anhui, China","active":true,"usgs":false}],"preferred":false,"id":819663,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70220322,"text":"sir20215021 - 2021 - Hydraulic characterization of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada","interactions":[],"lastModifiedDate":"2025-05-14T18:34:47.405035","indexId":"sir20215021","displayToPublicDate":"2021-05-07T07:51:36","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5021","displayTitle":"Hydraulic Characterization of Carbonate-Rock and Basin-Fill Aquifers near Long Canyon, Goshute Valley, Northeastern Nevada","title":"Hydraulic characterization of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada","docAbstract":"Understanding groundwater flow and pumping effects near pending mining operations requires accurate subsurface hydraulic characterization. To improve conceptual models of groundwater flow and development in the complex hydrogeologic system near Long Canyon Mine, in northwestern Goshute Valley, northeastern Nevada, the U.S. Geological Survey characterized the hydraulic properties of carbonate rocks and basin-fill aquifers using an integrated analysis of steady-state and stressed aquifer conditions informed by water chemistry and aquifer-test data. Hydraulic gradients and groundwater-age data in northern Goshute Valley indicate carbonate rocks in the Pequop Mountains just west and south of the Long Canyon Mine project area constitute a more permeable and active flow system than saturated rocks in the northern Pequop Mountains, western Toano Range, and basin fill. Permeable carbonate rocks in the northern Pequop Mountains, in part, discharge to the Johnson Springs wetland complex (JSWC), where mean groundwater ages range from 500 to 2,400 years and samples all contain a small fraction of modern waters, relative to mean ages of 8,600 to more than 22,000 years for most groundwater sampled to the north and east. Recharge to the JSWC occurs from a roughly 27-square-mile area in the upgradient Pequop Mountains to the west, composed mostly of permeable carbonate rock and fractured quartzite, and bounded by low-permeability shales and marbleized and siliclastic rocks.
Single-well aquifer-test analyses provided transmissivity estimates at pumped wells. Transmissivity estimates ranged from 7,000 to 400,000 feet squared per day (ft2/d) in carbonate rocks and from 2,000 to 80,000 ft2/d in basin fill near the Long Canyon Mine. Water-level drawdown from multiple-well aquifer testing and rise from unintentional leakage into the overlying basin-fill aquifer were estimated and distinguished from natural fluctuations in 93 pumping and monitoring sites using analytical water-level models. Leakage of disposed aquifer-test pumpage occurred south of the aquifer test area through an unlined irrigation ditch. Drawdown was detected at distances of as much as 3 miles (mi) from pumping wells at all but one carbonate-rock site, at basin-fill sites on the alluvial fan immediately downgradient from pumping wells, and in Big Spring and spring NS-05. Similar drawdowns in carbonate rocks within the drawdown detection area suggest all wells penetrate a highly transmissive zone (HTZ) that is bounded by low-permeability rocks. Drawdown was not detected in carbonate rocks to the west of Canyon fault, in any basin-fill sites on the valley floor east of the Hardy fault, or at volcanic sites to the north, indicating that these major fault structures and (or) permeability contrasts between hydrogeologic units impeded groundwater flow or obscured pumping signals. Alternatively, unintentional leakage might have obscured drawdown at basin-fill sites on the valley floor, where water-level rise was detected at nine sites over 3 mi.
Consistent hydraulic properties were estimated by simultaneously interpreting steady-state flow during predevelopment conditions and changes in groundwater levels and springflows from the 2016 carbonate-rock aquifer test with an integrated groundwater-flow model. Hydraulic properties were distributed across carbonate rocks, basin fill, volcanic rocks, and siliciclastic rocks with a hydrogeologic framework developed from geologic mapping and hydraulic testing. Estimated transmissivity distributions spanned at least three orders of magnitude in each rock unit. In the HTZ, simulated transmissivities ranged from 10,000 to 23,000,000 ft2/d, with the most transmissive areas occurring around Big Spring. Comparatively low carbonate-rock transmissivities of less than 10,000 ft2/d were estimated in the northern Pequop Mountains and poorly defined values of less than 1,000 ft2/d were estimated in the western Toano Range. Transmissivities in basin fill ranged from less than 10 to 80,000 ft2/d and were minimally constrained by the 2016 carbonate-rock aquifer test because poorly quantified leakage affected water levels more so than pumping. The most transmissive areas were informed by single-well aquifer tests along the eastern edge of the Pequop Mountains near Long Canyon Mine and could be indicative of a hydraulic connection between basin fill and more transmissive underlying carbonate rocks. Simulated transmissivities of volcanic and low-permeability rocks mostly are less than 1,000 ft2/d. The estimated hydraulic-property distributions and informed interpretation of hydraulic connections among hydrogeologic units improved the characterization and representation of groundwater flow near the Long Canyon Mine.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215021","collaboration":"Prepared in cooperation with the Nevada Division of Water Resources","usgsCitation":"Garcia, C.A., Halford, K.J., Gardner, P.M., and Smith, D.W., 2021, Hydraulic characterization of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada: U.S. Geological Survey Scientific Investigations Report 2021–5021, 99 p., https://doi.org/10.3133/sir20215021.","productDescription":"Report: xii, 99 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-094004","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":397361,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5021/sir20215021.XML"},{"id":397360,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5021/images"},{"id":385454,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P1P7QV","text":"USGS data release","description":"USGS data release","linkHelpText":"Appendixes and supplemental data—Hydraulic characterization of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada, 2011–16."},{"id":385453,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JI8NQF","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-2005 and PEST models used to simulate the 2016 carbonate-rock aquifer test and characterize hydraulic properties of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada."},{"id":385451,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5021/coverthb.jpg"},{"id":385452,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5021/sir20215021.pdf","text":"Report","size":"9.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5021"}],"country":"United States","state":"Nevada","otherGeospatial":"Goshute Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.98840332031249,\n 40.55554790286311\n ],\n [\n -114.2633056640625,\n 40.55554790286311\n ],\n [\n -114.2633056640625,\n 41.693424216151314\n ],\n [\n -114.98840332031249,\n 41.693424216151314\n ],\n [\n -114.98840332031249,\n 40.55554790286311\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Many shorebirds rely on small numbers of staging sites during long annual migrations. Numerous shorebird species are declining and understanding the importance of these staging sites is important for successful conservation. We surveyed endangered rufa red knots (Calidris canutus rufa) staging in James Bay, Ontario, Canada, during southbound migration in 2017 and 2018. We used mark‐resight data and count data in an integrated Bayesian analysis to quantify migration phenology, estimate passage population size, and model the age structure of the stopover population. Many adult red knots arrived in James Bay in a single wave in early August in 2017, whereas adult red knots arrived in multiple smaller waves in July and mid‐August in 2018. These waves may correspond with breeding phenology where more red knots bred successfully and arrived in one large event in 2017 and the higher number of earlier arrivals in July 2018 may have been failed breeders. We included a binomial generalized linear model in the integrated analysis to estimate that 20% and 10% of staging red knots were juveniles in 2017 and 2018, respectively. In future applications, this method could provide a metric to assess breeding performance and develop our understanding of its role in population declines. Overall, we estimated that up to 23% of the estimated rufa red knot population staged in southwestern James Bay for an average of 10–12 days. The region is a key staging site for endangered red knots and could be included in conservation planning.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22059","usgsCitation":"MacDonald, A., Smith, P., Friis, C., Lyons, J., Aubry, Y., and Nol, E., 2021, Stopover ecology of red knots in southwestern James Bay during southbound migration: Journal of Wildlife Management, v. 85, no. 5, p. 932-944, https://doi.org/10.1002/jwmg.22059.","productDescription":"13 p.","startPage":"932","endPage":"944","ipdsId":"IP-123446","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":385641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"James Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.8369140625,\n 51.17934297928927\n ],\n [\n -77.2998046875,\n 51.17934297928927\n ],\n [\n -77.2998046875,\n 55.229023057406344\n ],\n [\n -82.8369140625,\n 55.229023057406344\n ],\n [\n -82.8369140625,\n 51.17934297928927\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"MacDonald, Amie 0000-0002-6424-7761","orcid":"https://orcid.org/0000-0002-6424-7761","contributorId":258022,"corporation":false,"usgs":false,"family":"MacDonald","given":"Amie","email":"","affiliations":[{"id":36679,"text":"Trent University","active":true,"usgs":false}],"preferred":false,"id":815564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Paul","contributorId":147639,"corporation":false,"usgs":false,"family":"Smith","given":"Paul","affiliations":[],"preferred":false,"id":815565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friis, Christian","contributorId":194605,"corporation":false,"usgs":false,"family":"Friis","given":"Christian","email":"","affiliations":[],"preferred":false,"id":815566,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":210574,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":815567,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aubry, Yves","contributorId":202279,"corporation":false,"usgs":false,"family":"Aubry","given":"Yves","email":"","affiliations":[],"preferred":false,"id":815568,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nol, Erica","contributorId":216259,"corporation":false,"usgs":false,"family":"Nol","given":"Erica","email":"","affiliations":[{"id":36679,"text":"Trent University","active":true,"usgs":false}],"preferred":false,"id":815569,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70220394,"text":"70220394 - 2021 - Associations between private well water and community water supply arsenic concentrations in the conterminous United States","interactions":[],"lastModifiedDate":"2021-05-18T14:00:13.220699","indexId":"70220394","displayToPublicDate":"2021-05-06T07:13:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Associations between private well water and community water supply arsenic concentrations in the conterminous United States","docAbstract":"Geogenic arsenic contamination typically occurs in groundwater as opposed to surface water supplies. Groundwater is a major source for many community water systems (CWSs) in the United States (US). Although the US Environmental Protection Agency sets the maximum contaminant level (MCL enforceable since 2006: 10 μg/L) for arsenic in CWSs, private wells are not federally regulated. We evaluated county-level associations between modeled values of the probability of private well arsenic exceeding 10 μg/L and CWS arsenic concentrations for 2231 counties in the conterminous US, using time invariant private well arsenic estimates and CWS arsenic estimates for two time periods. Nationwide, county-level CWS arsenic concentrations increased by 8.4 μg/L per 100% increase in the probability of private well arsenic exceeding 10 μg/L for 2006–2008 (the initial compliance monitoring period after MCL implementation), and by 7.3 μg/L for 2009–2011 (the second monitoring period following MCL implementation) (1.1 μg/L mean decline over time). Regional differences in this temporal decline suggest that interventions to implement the MCL were more pronounced in regions served primarily by groundwater. The strong association between private well and CWS arsenic in Rural, American Indian, and Semi Urban, Hispanic counties suggests that future research and regulatory support are needed to reduce water arsenic exposures in these vulnerable subpopulations. This comparison of arsenic exposure values from major private and public drinking water sources nationwide is critical to future assessments of drinking water arsenic exposure and health outcomes.
Evolutionary radiations are central to the origin and maintenance of biodiversity, yet we rarely understand how they are jointly shaped by demography and ecological opportunity. Astragalus is the largest plant genus in the world and is disproportionately comprised of rare species restricted to narrow geographic and ecological regions. Here, we explored the demographic and ecological mechanisms underlying patterns of diversification in a threatened Astragalus species complex endemic to a small desert region in the western United States.
Southeast Utah, USA.
We used high‐throughput DNA sequencing to infer genetic structure, genetic diversity, and demographic history (i.e., the timing of population divergence, effective population sizes and gene flow) among Astragalus taxa. We performed landscape genetic analyses to quantify the relationships between genetic differentiation, geographic distance, and ecological distance based on bioclimatic and soil variables. Finally, we identified putative adaptive loci that show higher genetic differentiation between taxa than expected based on our inferred neutral demographic model.
We found evidence of low gene flow between three highly differentiated taxa (currently delineated as A. iselyi, A. sabulosus var. sabulosus and A. sabulosus var. vehiculus) that rapidly diverged from a small ancestral population near the beginning of the last glacial period. Genomic signatures revealed long‐term effective population sizes are 2–10× larger than recent census sizes, perhaps due to the maintenance of standing genetic variation through seed banks. Consistent with limited dispersal and local adaptation, genome‐wide patterns of differentiation are shaped by geographic distance (isolation‐by‐distance) and climate and soil variation (isolation‐by‐environment). Taxon‐specific adaptation is further supported by uncovering putative adaptive loci.
Our findings suggest that interactions between demography (i.e., dispersal limitations and seeds banks) and ecological opportunity (i.e., spatial and temporal environmental heterogeneity) may promote diversification, endemism, and rarity among closely related Astragalus species and similar plant clades distributed across complex landscapes.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13288","usgsCitation":"Jones, M.R., Winkler, D.E., and Massatti, R., 2021, The demographic and ecological factors shaping diversification among rare Astragalus species: Diversity and Distributions, v. 27, no. 8, p. 1407-1421, https://doi.org/10.1111/ddi.13288.","productDescription":"15 p.","startPage":"1407","endPage":"1421","ipdsId":"IP-119600","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":452394,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13288","text":"Publisher Index Page"},{"id":436380,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93SRC7M","text":"USGS data release","linkHelpText":"Astragalus species complex genetic data from southeast Utah (Grand County and San Juan County), USA"},{"id":385525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.58837890625,\n 38.229550455326134\n ],\n [\n -109.072265625,\n 38.229550455326134\n ],\n [\n -109.072265625,\n 39.59722324495565\n ],\n [\n -110.58837890625,\n 39.59722324495565\n ],\n [\n -110.58837890625,\n 38.229550455326134\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Matthew Richard 0000-0002-4822-157X","orcid":"https://orcid.org/0000-0002-4822-157X","contributorId":257921,"corporation":false,"usgs":true,"family":"Jones","given":"Matthew","email":"","middleInitial":"Richard","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":815282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":815283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Massatti, Robert 0000-0001-5854-5597","orcid":"https://orcid.org/0000-0001-5854-5597","contributorId":207294,"corporation":false,"usgs":true,"family":"Massatti","given":"Robert","email":"","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":815284,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70231639,"text":"70231639 - 2021 - Geomorphic expression and slip rate of the Fairweather fault, southeast Alaska, and evidence for predecessors of the 1958 rupture","interactions":[],"lastModifiedDate":"2022-05-17T11:54:18.758519","indexId":"70231639","displayToPublicDate":"2021-05-06T06:46:51","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphic expression and slip rate of the Fairweather fault, southeast Alaska, and evidence for predecessors of the 1958 rupture","docAbstract":"Active traces of the southern Fairweather fault were revealed by light detection and ranging (lidar) and show evidence for transpressional deformation between North America and the Yakutat block in southeast Alaska. We map the Holocene geomorphic expression of tectonic deformation along the southern 30 km of the Fairweather fault, which ruptured in the 1958 moment magnitude 7.8 earthquake. Digital maps of surficial geology, geomorphology, and active faults illustrate both strike-slip and dip-slip deformation styles within a 10°–30° double restraining bend where the southern Fairweather fault steps offshore to the Queen Charlotte fault. We measure offset landforms along the fault and calibrate legacy 14C data to reassess the rate of Holocene strike-slip motion (≥49 mm/yr), which corroborates published estimates that place most of the plate boundary motion on the Fairweather fault. Our slip-rate estimates allow a component of oblique-reverse motion to be accommodated by contractional structures west of the Fairweather fault consistent with geodetic block models. Stratigraphic and structural relations in hand-dug excavations across two active fault strands provide an incomplete paleoseismic record including evidence for up to six surface ruptures in the past 5600 years, and at least two to four events in the past 810 years. The incomplete record suggests an earthquake recurrence interval of ≥270 years—much longer than intervals <100 years implied by published slip rates and expected earthquake displacements. Our paleoseismic observations and map of active traces of the southern Fairweather fault illustrate the complexity of transpressional deformation and seismic potential along one of Earth's fastest strike-slip plate boundaries.