{"pageNumber":"219","pageRowStart":"5450","pageSize":"25","recordCount":41062,"records":[{"id":70224567,"text":"70224567 - 2021 - Integrating airborne and mobile lidar data with UAV photogrammetry for rapid assessment of changing forest snow depth and cover","interactions":[],"lastModifiedDate":"2021-09-28T12:30:14.036461","indexId":"70224567","displayToPublicDate":"2021-09-17T07:27:18","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9346,"text":"Science of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Integrating airborne and mobile lidar data with UAV photogrammetry for rapid assessment of changing forest snow depth and cover","docAbstract":"

Forest structure and topography can influence the ecohydrologic function and resiliency to drought and changing climate. It is, therefore, important to understand how forest restoration treatments alter snowpack distribution and design the treatments accordingly. We use a combination of aerial lidar, multi-temporal terrestrial mobile lidar, and UAV photogrammetry to estimate rapidly changing snow depth and cover in northern Arizona, USA. We then examine the impact of forest structure and topography on snow depth and snow cover persistence to inform forest restoration treatments. Our results show that mobile lidar data can be used to estimate snow depth with standard errors of 8 cm when differenced with snow-off airborne lidar data. UAV-based Structure-from-Motion data can be used to estimate snow cover persistence with 92–97% overall accuracies in forested ecosystems. Random forest models indicate spatially varying importance of forest structural and topographic variables in predicting snow depth and cover persistence, when summarized at different spatial scales (from 5 m to 250 m) and with variable directional location offsets. Forest snow depth was best explained (R2 ≈ 0.46) by canopy height metrics at summary scales of >75 m, while canopy cover was most important at summary scales of <40 m (R2 ≈ 0.3). Snow cover persistence was best explained at very local scales by canopy cover (R2 ≈ 0.38) and less so at larger scales (>75 m) by topographic and forest patch characteristics (R2 ≈ 0.34). Our results demonstrate that 3-dimensional datasets are critical in rapidly characterizing changing snowpack to better understand the impacts of forest structure and topography to inform forest restoration treatment designs. The relationships observed in our study can inform currently ongoing regional-scale forest restoration in the southwest to improve forest health and resiliency.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.srs.2021.100029","usgsCitation":"Donager, J., Sankey, T., Sanchez-Meador, A., Sankey, J.B., and Springer, A.E., 2021, Integrating airborne and mobile lidar data with UAV photogrammetry for rapid assessment of changing forest snow depth and cover: Science of Remote Sensing, v. 4, 100029, 12 p., https://doi.org/10.1016/j.srs.2021.100029.","productDescription":"100029, 12 p.","ipdsId":"IP-104074","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":450790,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.srs.2021.100029","text":"Publisher Index Page"},{"id":389863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Donager, Jonathon","contributorId":196772,"corporation":false,"usgs":false,"family":"Donager","given":"Jonathon","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":824106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankey, Temuulen","contributorId":97000,"corporation":false,"usgs":true,"family":"Sankey","given":"Temuulen","affiliations":[],"preferred":false,"id":824107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanchez-Meador, Andrew","contributorId":266020,"corporation":false,"usgs":false,"family":"Sanchez-Meador","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":824108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":824109,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Springer, Abraham E. 0000-0003-4826-9124","orcid":"https://orcid.org/0000-0003-4826-9124","contributorId":216651,"corporation":false,"usgs":false,"family":"Springer","given":"Abraham","email":"","middleInitial":"E.","affiliations":[{"id":39494,"text":"School of Earth Science and Environmental Sustainability, Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":824110,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70230355,"text":"70230355 - 2021 - Female persistence during toxicant treatment predicts survival probability of offspring in invasive brown treesnakes (Boiga irregularis)","interactions":[],"lastModifiedDate":"2022-04-08T12:20:32.767332","indexId":"70230355","displayToPublicDate":"2021-09-17T07:18:24","publicationYear":"2021","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":"Female persistence during toxicant treatment predicts survival probability of offspring in invasive brown treesnakes (Boiga irregularis)","docAbstract":"

Assessing the long-term efficacy of control methods is a critical component of invasive species management. For example, if traits related to control have significant heritability or are influenced by maternal effects, control methods may lose efficacy over time. The potential for these effects can be evaluated via parent/offspring survival analysis, which concomitantly recasts adaptive management as an evolutionary force for invasive species. However, difficulties can arise when the life history of an invasive is cryptic, precluding direct observations of familial relationships. Genomic pedigree reconstruction can facilitate such analyses by assigning offspring to parents in invasive species for which mating and reproduction are difficult to study. Here, we use genomic pedigree reconstruction to quantify parental longevity and probability of offspring survival for brown treesnakes (Boiga irregularis) on Guam in a landscape treated with toxic baits simulating application via an aerial delivery system (ADS). To do so, we used 398 single nucleotide polymorphisms (SNPs) to update an existing multi-generational genomic pedigree for a geographically-closed population of brown treesnakes. This facilitated assignment of parents to juveniles born during three consecutive years of toxic bait application under a simulated aerial treatment program (N = 72). We found that the offspring of dams that persisted until the end of the study displayed greater survival probability (cox proportional hazard model, P < 0.001), yet there was no such effect for sires. This sex-specific relationship between parental longevity and offspring survival indicates that heritability of traits contributing to resistance to ADS is unlikely, but it supports a role of maternal effects that could undermine ADS. Our study identifies potential risks associated with control efforts and also highlights the utility of parent-offspring survival analyses informed by genomic pedigree reconstruction as a tool for adaptive management.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2021.e01827","usgsCitation":"Levine, B., Yackel Adams, A.A., Douglas, M., Douglas, M., and Nafus, M., 2021, Female persistence during toxicant treatment predicts survival probability of offspring in invasive brown treesnakes (Boiga irregularis): Global Ecology and Conservation, v. 31, e01827, 7 p., https://doi.org/10.1016/j.gecco.2021.e01827.","productDescription":"e01827, 7 p.","ipdsId":"IP-125961","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":450793,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2021.e01827","text":"Publisher Index Page"},{"id":436199,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9STNBGE","text":"USGS data release","linkHelpText":"Offspring, dam, sire pedigree assignments in a managed population of Brown Treesnakes on Guam"},{"id":398385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Levine, Brenna A","contributorId":243207,"corporation":false,"usgs":false,"family":"Levine","given":"Brenna A","affiliations":[{"id":38022,"text":"University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":840051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":840052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Douglas, Marlis","contributorId":289912,"corporation":false,"usgs":false,"family":"Douglas","given":"Marlis","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":840053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Douglas, Michael","contributorId":289913,"corporation":false,"usgs":false,"family":"Douglas","given":"Michael","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":840054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nafus, Melia Gail 0000-0002-7325-3055","orcid":"https://orcid.org/0000-0002-7325-3055","contributorId":245717,"corporation":false,"usgs":true,"family":"Nafus","given":"Melia Gail","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":840055,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70225495,"text":"70225495 - 2021 - Time-fractional flow equations (t-FFEs) to upscale transient groundwater flow characterized by temporally non-darcian flow due to medium heterogeneity","interactions":[],"lastModifiedDate":"2021-11-16T15:52:35.903673","indexId":"70225495","displayToPublicDate":"2021-09-17T06:40:55","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":"Time-fractional flow equations (t-FFEs) to upscale transient groundwater flow characterized by temporally non-darcian flow due to medium heterogeneity","docAbstract":"

Upscaling groundwater flow is a fundamental challenge in hydrogeology. This study proposed time-fractional flow equations (t-FFEs) for upscaling long-term, transient groundwater flow and propagation of pressure heads in heterogeneous media. Monte Carlo simulations showed that, with increasing variance and correlation of the hydraulic conductivity (K), flow dynamics gradually deviated from Darcian flow and exhibit sub-diffusive, time-dependent evolution which can be separated into three major stages. At the early stage, the interconnected high-K zones dominated flow, while at intermediate times, the transverse flow due to mixed high- and low-K zones caused delayed rise of the piezometric head. At late times when flow in the relatively high-K domains reached stability, cells with very low-K continued to block the entry of water and generate “islands” with low piezometric head, significantly extending the temporal evolution of the piezometric head. The elongated water breakthrough curve cannot be quantified by the flow equation with an effective K, the space-fractional flow equation, or the multi-rate mass transfer (MRMT) flow model with a few rates, motivating the development of t-FFEs assuming temporally non-Darcian flow. Model applications showed that both the early and intermediate stages of flow dynamics can be captured by a single-index t-FFE (whose index is the exponent of the power-law probability density function of the random operational time for water parcels), but the overall evolution of flow dynamics, especially the enhanced retention of flow at later times, required a distributed-order t-FFE with variable indexes for different flow phases that can dominate flow dynamics at different stages. Therefore, transient groundwater flow in aquifers with spatially stationary heterogeneity can be temporally non-Darcian and non-stationary, due to the time-sensitive, combined effects of interconnected high-K channels and isolated low-K deposits on flow dynamics (which is the hydrogeological mechanism for the temporally non-Darcian flow and sub-diffusive pressure propagation), whose long-term behavior can be quantified by multi-index stochastic models.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR029554","usgsCitation":"Xia, Y., Zhang, Y., Green, C., and Fogg, G., 2021, Time-fractional flow equations (t-FFEs) to upscale transient groundwater flow characterized by temporally non-darcian flow due to medium heterogeneity: Water Resources Research, v. 57, no. 11, e2020WR029554, 30 p., https://doi.org/10.1029/2020WR029554.","productDescription":"e2020WR029554, 30 p.","ipdsId":"IP-119835","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":450800,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/0pv0z4t0","text":"External Repository"},{"id":390598,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Xia, Yuan","contributorId":267790,"corporation":false,"usgs":false,"family":"Xia","given":"Yuan","email":"","affiliations":[{"id":55508,"text":"Guilin University of Technology","active":true,"usgs":false}],"preferred":false,"id":825278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Yong","contributorId":214040,"corporation":false,"usgs":false,"family":"Zhang","given":"Yong","email":"","affiliations":[{"id":16675,"text":"U Alabama","active":true,"usgs":false}],"preferred":false,"id":825279,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Green, Christopher 0000-0002-6480-8194","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":201642,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":825280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fogg, Graham 0000-0003-0676-1911","orcid":"https://orcid.org/0000-0003-0676-1911","contributorId":267791,"corporation":false,"usgs":false,"family":"Fogg","given":"Graham","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":825281,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70224196,"text":"sir20215070 - 2021 - Estimating invertebrate response to changes in total nitrogen, total phosphorus, and specific conductance at sites where invertebrate data are unavailable","interactions":[],"lastModifiedDate":"2021-09-16T16:17:28.171074","indexId":"sir20215070","displayToPublicDate":"2021-09-16T09:50:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5070","displayTitle":"Estimating Invertebrate Response to Changes in Total Nitrogen, Total Phosphorus, and Specific Conductance at Sites Where Invertebrate Data are Unavailable","title":"Estimating invertebrate response to changes in total nitrogen, total phosphorus, and specific conductance at sites where invertebrate data are unavailable","docAbstract":"

The purpose of this report is to describe a possible approach to estimate changes in invertebrate taxa richness at sites with known water-quality trends but no invertebrate data. In this study, data from 1,322 sites were used to describe invertebrate response to changes in total nitrogen, total phosphorus, or specific conductance, and to estimate changes in invertebrate taxa richness at 259 sites with reported water-quality trends but no invertebrate data. Sites were stratified using propensity score analysis to control for confounding factors (for example, climate, land use, land cover). Generalized linear models were developed to describe changes in invertebrate taxa richness along gradients of total nitrogen, total phosphorus, and specific conductance values. The magnitude and direction of invertebrate response to gradients of water quality varied among parameters and strata, with changes in invertebrate taxa richness per natural log unit change in concentration ranging from –7 to +6. However, estimated changes in invertebrate taxa richness at sites with known water-quality trends were much less and did not exceed three taxa until changes in concentration were greater than 50 percent. Applying this approach provides (1) a first screening to identify where changes in invertebrate taxa richness are likely to occur and (2) the necessary groundwork to improve estimation of invertebrate response to trends in water quality where biological data are lacking.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20215070","usgsCitation":"Zuellig, R.E., and Carlisle, D.M., 2021, Estimating invertebrate response to changes in total nitrogen, total phosphorus, and specific conductance at sites where invertebrate data are unavailable: U.S. Geological Survey Scientific Investigations Report 2021–5070, 24 p., https://doi.org/10.3133/sir20215070.","productDescription":"Report: v, 24 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-119660","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":389267,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SMFACO","text":"USGS data release","linkHelpText":"Datasets for estimating invertebrate response to changes in total nitrogen, total phosphorus, and specific conductance at sites where invertebrate data are unavailable"},{"id":389266,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5070/sir20215070.pdf","text":"Report","size":"5.06 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5070"},{"id":389265,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5070/coverthb.jpg"}],"contact":"

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

","tableOfContents":"","publishedDate":"2021-09-16","noUsgsAuthors":false,"publicationDate":"2021-09-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Zuellig, Robert E. 0000-0002-4784-2905 rzuellig@usgs.gov","orcid":"https://orcid.org/0000-0002-4784-2905","contributorId":1620,"corporation":false,"usgs":true,"family":"Zuellig","given":"Robert","email":"rzuellig@usgs.gov","middleInitial":"E.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlisle, Daren M. 0000-0002-7367-348X","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":223188,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":823308,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70240159,"text":"70240159 - 2021 - Waterborne gradient Self-Potential (WaSP) logging in the Rio Grande to map localized and regional surface and groundwater exchanges across the Mesilla Valley","interactions":[],"lastModifiedDate":"2023-01-31T15:30:33.818125","indexId":"70240159","displayToPublicDate":"2021-09-16T09:24:08","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7446,"text":"FastTIMES","active":true,"publicationSubtype":{"id":10}},"title":"Waterborne gradient Self-Potential (WaSP) logging in the Rio Grande to map localized and regional surface and groundwater exchanges across the Mesilla Valley","docAbstract":"

The Rio Grande is the primary source of recharge to the Mesilla Basin/Conejos-Médanos aquifer system (“Mesilla Basin aquifer system”) in the Mesilla Valley of New Mexico and Texas. The Mesilla Basin aquifer system is the primary source of water supply to several large cities along the United States–Mexico border. Identifying gaining and losing reaches of the Rio Grande in the Mesilla Valley is therefore critical for managing the quality and quantity of surface and groundwater-resources available to stakeholders in the Mesilla Valley and downstream. A Waterborne gradient Self-Potential (WaSP) logging survey was completed in the Rio Grande across the Mesilla Valley between June 26 and July 2, 2020 to identify reaches where surface-water gains and losses were occurring by interpreting an estimate of the streaming-potential component of the electrostatic field in the river, measured during bank-full flow. The WaSP survey, completed as part of the Transboundary Aquifer Assessment Program, began at Leasburg Dam State Park, New Mexico near the northern terminus of the Mesilla Valley and ended ~72 kilometers (km) downstream in Canutillo, Texas. Electric potential data indicated a net losing condition for ~32 km between Leasburg Dam and Mesilla Diversion Dam in New Mexico, with one 200-m long reach showing a localized gaining condition. Downstream from Mesilla Diversion Dam, electric-potential data indicated a neutral-to-mild gaining condition for 12-km that transitioned to a mild-to-moderate gaining condition between 12 and ~22 km from the dam before transitioning back to a losing condition along the remaining 18 km of the survey reach. The interpreted gaining and losing reaches are substantiated by potentiometric surface mapping in hydrostratigraphic units of the Mesilla Basin aquifer system between 2010 and 2011 and streamflow gains and losses quantified from annual streamflow gaging at 16 stations along the survey reach between 1988 and 1998 and between 2004 and 2013. The gaining and losing reaches of the Rio Grande in the Mesilla Valley, interpreted from electric potential data, compare notably well with streamflow gains and losses quantified at 16 locations along the 72-km long survey reach.

","language":"English","publisher":"Environmental and Engineering Geophysical Society","usgsCitation":"Ikard, S., and Teeple, A., 2021, Waterborne gradient Self-Potential (WaSP) logging in the Rio Grande to map localized and regional surface and groundwater exchanges across the Mesilla Valley: FastTIMES, v. 26, no. 3, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-132631","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":412505,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":412478,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://fasttimesonline.co/waterborne-gradient-self-potential-wasp-logging-in-the-rio-grande-to-map-localized-and-regional-surface-and-groundwater-exchanges-across-the-mesilla-valley/"}],"country":"United States","state":"New Mexico, Texas","otherGeospatial":"Mesilla Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.44524373222445,\n 31.760633532310962\n ],\n [\n -106.6117012652096,\n 32.435777766328556\n ],\n [\n -106.97488133717744,\n 32.96635814299131\n ],\n [\n -107.04549968450479,\n 33.44327742390567\n ],\n [\n -107.58018145712424,\n 33.388542989837234\n ],\n [\n -107.50956310979689,\n 32.79267559856237\n ],\n [\n -107.07576469050201,\n 32.350592719244176\n ],\n [\n -106.67223127720436,\n 31.854939592806915\n ],\n [\n -106.4502878998906,\n 31.709153308763334\n ],\n [\n -106.44524373222445,\n 31.760633532310962\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ikard, Scott 0000-0002-8304-4935","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":201775,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Teeple, Andrew 0000-0003-1781-8354 apteeple@usgs.gov","orcid":"https://orcid.org/0000-0003-1781-8354","contributorId":193061,"corporation":false,"usgs":true,"family":"Teeple","given":"Andrew","email":"apteeple@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862806,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70255559,"text":"70255559 - 2021 - Monthly river temperature trends across the US confound annual changes","interactions":[],"lastModifiedDate":"2024-06-24T11:20:26.360545","indexId":"70255559","displayToPublicDate":"2021-09-16T06:06:47","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Monthly river temperature trends across the US confound annual changes","docAbstract":"

Climate variations and human modifications of the water cycle continue to alter the Earth's surface water and energy exchanges. It is therefore critical to ascertain how these changes impact water quality and aquatic ecosystem habitat metrics such as river temperatures. Though river temperature trend analyses exist in the literature, studies on seasonal trends in river temperatures across large spatial extents, e.g. the contiguous United States (US), are limited. As we show through both annual and monthly trend analyses for 20 year (n = 138 sites) and 40 year (n = 40 sites) periods, annual temperature trends across the US mask extensive monthly variability. While most sites exhibited annual warming trends, these annual trends obscured sub-annual cooling trends at many sites. Monthly trend anomalies were spatially organized, with persistent regional patterns at both reference and human-impacted sites. The largest warming and cooling anomalies happened at human impacted sites and during summer months. Though our analysis points to coherence in trends as well as the overall impact of human activity in driving these patterns, we did not investigate the impact of river temperature observation accuracy on reported trends, an area needed for future work. Overall, these patterns emphasize the need to consider sub-annual behavior when managing the ecological impacts of river temperature throughout lotic networks.

","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ac2289","usgsCitation":"Kelleher, C., Golden, H.E., and Archfield, S.A., 2021, Monthly river temperature trends across the US confound annual changes: Environmental Research Letters, v. 16, 104006, 10 p., https://doi.org/10.1088/1748-9326/ac2289.","productDescription":"104006, 10 p.","ipdsId":"IP-130039","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":450807,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ac2289","text":"Publisher Index Page"},{"id":430440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -129.57106419384183,\n 51.98412232384288\n ],\n [\n -129.57106419384183,\n 24.426025005896022\n ],\n [\n -65.41090794384175,\n 24.426025005896022\n ],\n [\n -65.41090794384175,\n 51.98412232384288\n ],\n [\n -129.57106419384183,\n 51.98412232384288\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2021-09-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Kelleher, Christa","contributorId":242798,"corporation":false,"usgs":false,"family":"Kelleher","given":"Christa","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":904669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Golden, Heather E.","contributorId":202423,"corporation":false,"usgs":false,"family":"Golden","given":"Heather","email":"","middleInitial":"E.","affiliations":[{"id":36429,"text":"USEPA ORD","active":true,"usgs":false}],"preferred":false,"id":904670,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":904671,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224252,"text":"ofr20211081 - 2021 - Kelp forest monitoring at Naval Base Ventura County, San Nicolas Island, California—Fall 2019, sixth annual repor","interactions":[],"lastModifiedDate":"2021-09-16T11:50:21.374636","indexId":"ofr20211081","displayToPublicDate":"2021-09-15T13:31:12","publicationYear":"2021","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":"2021-1081","displayTitle":"Kelp Forest Monitoring at Naval Base Ventura County, San Nicolas Island, California: Fall 2019, Sixth Annual Report","title":"Kelp forest monitoring at Naval Base Ventura County, San Nicolas Island, California—Fall 2019, sixth annual repor","docAbstract":"

The U.S. Geological Survey conducts ecological monitoring of rocky subtidal communities at four permanent sites around San Nicolas Island. The sites—Nav Fac 100, West End, Dutch Harbor, and Daytona 100—were based on ones that had been monitored since 1980 by the U.S. Geological Survey and, in cooperation with the U.S. Navy, were combined or expanded in 2014 for better comparability with monitoring programs conducted at the other California Channel Islands. At the sites, we counted a suite of kelps and invertebrates on benthic band transects, measured bottom cover of algae and sessile invertebrate species in quadrats, and counted and sized fish on swimming transects. Holdfast diameter and number of stipes of giant kelp (Macrocystis pyrifera) were recorded on these transects and size data were collected for urchins, sea stars, and shelled mollusks. Bottom temperatures were recorded at hourly intervals by archival data loggers that were deployed at the sites. Typically, this monitoring work is conducted semi-annually, in fall and spring. Because the spring 2020 trip was cancelled due to the Coronavirus Disease 2019 pandemic, this report focuses primarily on data collected in fall 2019 and makes comparisons with data collected in previous years, beginning in fall 2014.

The sites are distributed around the island and differ in their physical and ecological characteristics. Nav Fac 100, situated on the north side of San Nicolas Island, has a relatively low benthic profile. The invasive brown alga Sargassum horneri was first observed at this site in 2015. West End, to the southwest of the island, also lacks much bottom relief but has more crevice habitat associated with boulders. For almost three decades, West End has been a focal point for the small, but growing, population of southern sea otters (Enhydra lutris nereis) at the island. Dutch Harbor, on the south side, has many high relief rocky reefs and had the greatest fish and non-motile invertebrate densities. Daytona 100, on the southeast side, has moderate relief and has remained a patchwork of kelp and sea urchin dominated areas.

There were no major changes at the sites since spring 2019, but some trends observed during the last few years continued whereas others changed. Red urchins continued a declining trend (observed during the last 4 years) at Daytona 100. The wavy turban snail (Megastraea undosa) began to increase rapidly at Nav Fav 100 in 2015 and has subsequently been increasing at the other sites as well, after more than a decade of very low numbers at all sites. Sea star wasting syndrome, which has devastated multiple species of sea stars along the Pacific coast of North America, affected most species at San Nicolas Island in the year prior to the fall 2014 sampling. Since then, there has been a reduction in the number of bat stars (Patiria miniata), and very few sea stars of other species have been observed. There has been a slight recovery of P. miniata since 2016 but little sign of change in other species. All the sites had a slight decline in the densities of purple urchins following an increase during the previous 2 years. Long-term data are presented to illustrate trends and changes during almost four decades of monitoring this dynamic system.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211081","collaboration":"Prepared in cooperation with the U.S. Navy","programNote":"Wildlife Program","usgsCitation":"Kenner, M.C., and Tomoleoni, J., 2021, Kelp forest monitoring at Naval Base Ventura County, San Nicolas Island, California—Fall 2019, sixth annual report: U.S. Geological Survey Open-File Report 2021–1081, 97 p., https://doi.org/10.3133/ofr20211081.","productDescription":"ix, 97 p.","numberOfPages":"97","onlineOnly":"Y","ipdsId":"IP-128532","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":389297,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1081/covrthb.jpg"},{"id":389298,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1081/ofr20211081.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":389299,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1081/ofr20211081.xml"},{"id":389300,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1081/images"}],"country":"California","otherGeospatial":"Naval Base Ventura County, San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.59304809570312,\n 33.20824398778792\n ],\n [\n -119.42138671875,\n 33.20824398778792\n ],\n [\n -119.42138671875,\n 33.29724715520414\n ],\n [\n -119.59304809570312,\n 33.29724715520414\n ],\n [\n -119.59304809570312,\n 33.20824398778792\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2021-09-15","noUsgsAuthors":false,"publicationDate":"2021-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kenner, Michael C. 0000-0003-4659-461X","orcid":"https://orcid.org/0000-0003-4659-461X","contributorId":208151,"corporation":false,"usgs":true,"family":"Kenner","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":823359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tomoleoni, Joseph A. 0000-0001-6980-251X jtomoleoni@usgs.gov","orcid":"https://orcid.org/0000-0001-6980-251X","contributorId":167551,"corporation":false,"usgs":true,"family":"Tomoleoni","given":"Joseph","email":"jtomoleoni@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":823360,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70223926,"text":"sir20215091 - 2021 - Evaluation of hydrologic simulation models for fields with subsurface drainage to mitigated wetlands in Barnes, Dickey, and Sargent Counties, North Dakota","interactions":[],"lastModifiedDate":"2021-09-16T11:37:37.283212","indexId":"sir20215091","displayToPublicDate":"2021-09-15T08:47:15","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":"2021-5091","displayTitle":"Evaluation of Hydrologic Simulation Models for Fields with Subsurface Drainage to Mitigated Wetlands in Barnes, Dickey, and Sargent Counties, North Dakota","title":"Evaluation of hydrologic simulation models for fields with subsurface drainage to mitigated wetlands in Barnes, Dickey, and Sargent Counties, North Dakota","docAbstract":"

Proper identification of wetlands, along with a better understanding of the hydrology of mitigated wetlands, is needed to assist with conservation efforts aimed at maintaining the productivity and ecological function (wetland mitigation) of agricultural lands. The U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service, completed a study to evaluate two models for simulating hydrologic conditions in fields with subsurface drainage to mitigated wetlands at several sites in North Dakota. These two models were evaluated as possible tools for water resource managers to use for designing wetland mitigation projects in the area in the future.

The Soil-Plant-Atmosphere-Water (SPAW) model simulates the daily hydrologic water budgets of agricultural landscapes by two linked routines, one for farm fields (field hydrology) and one for impoundments such as wetlands and ponds (pond model). The DRAINMOD model was used in conjunction with the SPAW model because although the SPAW model can be used to simulate the hydrology of small drainage basins containing wetlands, the SPAW model does not contain routines to simulate drainage, either subsurface drainage or surface (drainage ditches), that can directly affect the wetland hydrology. The wetlands in the study areas in this report are all downstream from and adjacent to drained agricultural fields. SPAW and DRAINMOD models were developed and calibrated at three study areas (study areas B, D, and S) to evaluate how the models simulated field-scale hydrologic characteristics and the water balance in wetlands from January 1, 2003, through December 31, 2018.

The SPAW model developed for study area B included five modeled fields in the field hydrology portion of SPAW that contributed inflow to one wetland simulated in the pond model portion of SPAW. Simulated wetland water depths were most similar to water depths measured at site BWET1, with an absolute mean error of 0.10 foot and a root mean square error of 0.14 foot. Site BWET2 had slightly larger errors, with an absolute mean error of 0.22 foot and a root mean square error of 0.28 foot. Simulated water depths were similar to the pattern of measured water depths at BWET1 and BWET2 from about mid-April 2018 through about mid-September 2018, but overpredicted water depths in the fall from about mid-September 2018 through about mid-October 2018.

The SPAW model developed for study area D included six modeled fields in the field hydrology portion of SPAW that contributed inflow to five wetlands connected in series in the pond model portion of SPAW. Simulated water depths compared relatively well to water depths in the five wetlands, with the absolute mean error ranging from 0.17 foot (DWET1) to 0.39 foot (DWET2), and the root mean square error ranging from 0.28 foot (DWET1) to 0.56 foot (DWET5).

The SPAW model developed for study area S included one modeled field in the field hydrology portion of SPAW that contributed inflow to one wetland in the pond model portion of SPAW. Among the SPAW models developed for the three study areas, the model for study area S had the best comparison between simulated and measured water depths, with an absolute mean error of 0.06 foot and a root mean square error of 0.10 foot.

DRAINMOD models were developed and calibrated at the three study areas and provided inflow from subsurface drainage discharge to the SPAW models for simulating water levels in wetlands in the study areas. The calibrated DRAINMOD model for study area B showed the variability of hydrologic processes in the modeled field throughout the wide range of hydrologic conditions from January 1, 2003, through December 31, 2018. In general, the discharge through the modeled subsurface drainage system was in the spring and early summer (April through June) most years, with little to no discharge later in the year. Although the subsurface drainage system in study area D was the most complex among the three study areas and was simplified into a uniform system within DRAINMOD, simulated water table depths at study area D correlated better to measured water table depths compared to results from the model applications at the other two study areas. Simulated water table depths had an absolute mean error of 0.30 foot and root mean square error of 0.37 foot at site DGW1 and an absolute mean error of 0.29 foot and a root mean square error of 0.34 foot at site DGW2. Although the subsurface drainage system in study area S was the simplest and the modeled field was the smallest among the three study areas, simulated water table depths at study area S did not correlate as well to measured water table depths compared to results from the model applications at the other two study areas.

The SPAW and DRAINMOD model applications at the three study areas in southeast North Dakota adequately simulated the hydrologic processes for fields with subsurface drainage that are connected to adjacent wetlands. However, more measured data would be needed to fully evaluate the models throughout the range of possible climatic conditions.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215091","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service","usgsCitation":"Galloway, J.M., Tatge, W.S., and Wheeling, S.L., 2021, Evaluation of hydrologic simulation models for fields with subsurface drainage to mitigated wetlands in Barnes, Dickey, and Sargent Counties, North Dakota: U.S. Geological Survey Scientific Investigations Report 2021–5091, 58 p., https://doi.org/10.3133/sir20215091.","productDescription":"Report: vi, 58 p.; Dataset","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-128613","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":389200,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5091/images"},{"id":389199,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5091/sir20215091.xml","size":"386 kB","linkFileType":{"id":8,"text":"xml"}},{"id":389198,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":389196,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5091/coverthb.jpg"},{"id":389197,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5091/sir20215091.pdf","text":"Report","size":"5.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5091"}],"country":"United States","state":"North Dakota","county":"Barnes County, Dickey County, Sargent County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-97.961,47.241],[-97.7061,47.2402],[-97.7071,47.1529],[-97.7062,47.0665],[-97.7059,46.9792],[-97.6839,46.9792],[-97.683,46.6294],[-97.81,46.6297],[-97.9059,46.6293],[-97.9357,46.6294],[-98.0349,46.6293],[-98.1889,46.6297],[-98.2868,46.63],[-98.3152,46.63],[-98.4396,46.6296],[-98.4412,46.9789],[-98.4685,46.9788],[-98.4677,47.2402],[-97.9958,47.2411],[-97.9764,47.2412],[-97.961,47.241]]],[[[-98.0095,45.9355],[-98.164,45.9356],[-98.1849,45.9355],[-98.3472,45.9355],[-98.3537,45.9355],[-98.7267,45.9373],[-98.7273,45.9373],[-99.0021,45.9393],[-99.0054,45.9393],[-99.0073,46.0262],[-99.0061,46.1132],[-99.0054,46.2002],[-99.0049,46.2822],[-98.9154,46.2821],[-98.7878,46.2805],[-98.755,46.281],[-98.6622,46.2812],[-98.5359,46.2817],[-98.5024,46.2808],[-98.2859,46.2816],[-98.2524,46.2815],[-98.1616,46.2818],[-98.1314,46.2813],[-98.0366,46.2809],[-98.009,46.2814],[-97.9096,46.2823],[-97.8826,46.2827],[-97.5333,46.2819],[-97.4063,46.2823],[-97.2833,46.2822],[-97.2615,46.2822],[-97.2618,46.196],[-97.2603,45.9985],[-97.231,45.9951],[-97.2313,45.936],[-97.3576,45.936],[-97.3773,45.936],[-97.4826,45.9359],[-97.605,45.9356],[-97.755,45.9356],[-97.9775,45.9351],[-98.0017,45.9355],[-98.0095,45.9355]]]]},\"properties\":{\"name\":\"Barnes\",\"state\":\"ND\"}}]}","contact":"

Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503

1608 Mountain View Road
Rapid City, SD 57702

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-09-15","noUsgsAuthors":false,"publicationDate":"2021-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Galloway, Joel M. 0000-0002-9836-9724 jgallowa@usgs.gov","orcid":"https://orcid.org/0000-0002-9836-9724","contributorId":1562,"corporation":false,"usgs":true,"family":"Galloway","given":"Joel","email":"jgallowa@usgs.gov","middleInitial":"M.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tatge, Wyatt S. 0000-0003-4414-2492","orcid":"https://orcid.org/0000-0003-4414-2492","contributorId":239544,"corporation":false,"usgs":true,"family":"Tatge","given":"Wyatt","email":"","middleInitial":"S.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wheeling, Spencer L. 0000-0003-4411-6526","orcid":"https://orcid.org/0000-0003-4411-6526","contributorId":221899,"corporation":false,"usgs":true,"family":"Wheeling","given":"Spencer","email":"","middleInitial":"L.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823301,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224581,"text":"70224581 - 2021 - Forest resistance to extended drought enhanced by prescribed fire in low elevation forests of the Sierra Nevada","interactions":[],"lastModifiedDate":"2021-09-29T13:34:40.402512","indexId":"70224581","displayToPublicDate":"2021-09-15T08:29:26","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1689,"text":"Forests","active":true,"publicationSubtype":{"id":10}},"title":"Forest resistance to extended drought enhanced by prescribed fire in low elevation forests of the Sierra Nevada","docAbstract":"

Prescribed fire reduces fire hazards by removing dead and live fuels (small trees and shrubs). Reductions in forest density following prescribed fire treatments (often in concert with mechanical treatments) may also lessen competition so that residual trees might be more likely to survive when confronted with additional stressors, such as drought. The current evidence for these effects is mixed and additional study is needed. Previous work found increased tree survivorship in low elevation forests with a recent history of fire during the early years of an intense drought (2012 to 2014) in national parks in the southern Sierra Nevada. We extend these observations through additional years of intense drought and continuing elevated tree mortality through 2017 at Sequoia and Kings Canyon National Parks. Relative to unburned sites, we found that burned sites had lower stem density and had lower proportions of recently dead trees (for stems ≤47.5 cm dbh) that presumably died during the drought. Differences in recent tree mortality among burned and unburned sites held for both fir (white fir and red fir) and pine (sugar pine and ponderosa pine) species. Unlike earlier results, models of individual tree mortality probability supported an interaction between plot burn status and tree size, suggesting the effect of prescribed fire was limited to small trees. We consider differences with other recent results and discuss potential management implications including trade-offs between large tree mortality following prescribed fire and increased drought resistance. 

","language":"English","publisher":"MDPI","doi":"10.3390/f12091248","usgsCitation":"van Mantgem, P., Caprio, A., Stephenson, N.L., and Das, A., 2021, Forest resistance to extended drought enhanced by prescribed fire in low elevation forests of the Sierra Nevada: Forests, v. 12, no. 9, 1248, 11 p., https://doi.org/10.3390/f12091248.","productDescription":"1248, 11 p.","ipdsId":"IP-129596","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":450811,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/f12091248","text":"Publisher Index Page"},{"id":436200,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W1CKTF","text":"USGS data release","linkHelpText":"Forest Structure Data for Burned and Unburned Sites at Sequoia and Kings Canyon National Parks"},{"id":389949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Kings Canyon National Park, Sequoia National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.30352783203125,\n 36.69485094156225\n ],\n [\n -118.41888427734374,\n 37.03325468997236\n ],\n [\n -118.69903564453124,\n 37.21939331752986\n ],\n [\n -118.828125,\n 37.23907530202184\n ],\n [\n -118.85559082031249,\n 37.19533058280065\n ],\n [\n -118.75946044921874,\n 37.07271048132943\n ],\n [\n -118.80615234374999,\n 36.95208671786997\n ],\n [\n -118.91601562499999,\n 36.91915611148194\n ],\n [\n -118.89953613281249,\n 36.84446074079564\n ],\n [\n -118.95996093749999,\n 36.78949107451841\n ],\n [\n -118.98193359375,\n 36.756490329505176\n ],\n [\n -118.970947265625,\n 36.619936625629215\n ],\n [\n -118.91601562499999,\n 36.59127365634205\n ],\n [\n -118.89404296875,\n 36.49859745028132\n ],\n [\n -118.75946044921874,\n 36.47209813242351\n ],\n [\n -118.76495361328125,\n 36.32176422120382\n ],\n [\n -118.53424072265625,\n 36.29741818650811\n ],\n [\n -118.57818603515625,\n 36.405810193726765\n ],\n [\n -118.46282958984374,\n 36.319551259461186\n ],\n [\n -118.2403564453125,\n 36.48314061639213\n ],\n [\n -118.30352783203125,\n 36.69485094156225\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"van Mantgem, Phillip J. 0000-0002-3068-9422","orcid":"https://orcid.org/0000-0002-3068-9422","contributorId":204320,"corporation":false,"usgs":true,"family":"van Mantgem","given":"Phillip J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":824161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caprio, Anthony C.","contributorId":35863,"corporation":false,"usgs":false,"family":"Caprio","given":"Anthony C.","affiliations":[],"preferred":false,"id":824162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stephenson, Nathan L. 0000-0003-0208-7229 nstephenson@usgs.gov","orcid":"https://orcid.org/0000-0003-0208-7229","contributorId":2836,"corporation":false,"usgs":true,"family":"Stephenson","given":"Nathan","email":"nstephenson@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":824163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Das, Adrian 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":201236,"corporation":false,"usgs":true,"family":"Das","given":"Adrian","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":824164,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70232160,"text":"70232160 - 2021 - Fish response to successive clearcuts in a second-growth forest from the central Coast range of Oregon","interactions":[],"lastModifiedDate":"2022-06-09T13:42:26.457253","indexId":"70232160","displayToPublicDate":"2021-09-15T08:25:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Fish response to successive clearcuts in a second-growth forest from the central Coast range of Oregon","docAbstract":"

Research dating back to the 1950 s has documented negative effects from harvesting of primeval forests on stream ecosystems of the Pacific Northwest. By the early 1990 s, state and federal forest practice rules governing timber harvest were modified throughout North America to better protect aquatic habitats and biotic resources, principally salmonids. These rules inspired a generation of studies using a before-after-control-impact (BACI) design to document the capacity of contemporary timber harvest rules to protect salmonids in headwater streams of second-growth forests. One important unanswered question concerns the potential effects of successive clearcuts in second growth forests. Consequently, we used a paired watershed approach to evaluate the effects of two successive clearcut harvests in the Alsea Watershed, site of the seminal Alsea Watershed Study that was conducted from 1958 to 1973, on relative biomass, movement, survival, and distribution of coastal cutthroat trout (Oncorhynchus clarkii clarkii) and three physical habitat characteristics (pool area and depth, and water temperature). Although the total clearcut harvest encompassed 87% of the treatment catchment in six years, no negative effects of logging were detected for either age-1 + coastal cutthroat trout or habitat variables. Comparisons between the harvested and reference catchments suggested the survival of coastal cutthroat trout (>94 mm fork length) and total catchment relative biomass of age-1+ (i.e., > 80 mm) exhibited similar patterns, increasing from the pre-logging period (2006–2009) through the Phase I post-logging period (2009–2014), and decreasing to levels observed in the pre-logging period during the Phase II post-logging period (2014–2017). Additionally, there was no evidence for differences in movement of coastal cutthroat trout related to the harvesting treatment. In terms of habitat variables, there was a relative increase in annual total pool area in the harvested catchment during the Phase II post-logging period, but there was no evidence the 7-day moving mean maximum stream temperature changed after the Phase I and Phase II harvests. Moreover, stream water temperatures never exceeded the criterion designed to protect core coldwater habitat for salmonids (16 °C). As such, it is unlikely that cutthroat trout experienced thermal stress following either harvest. More generally, results from this and other recent studies suggest that forest practice rules developed in conjunction with current best management practices for logging in headwater catchments have substantially improved outcomes for stream biota relative to unregulated forest harvest, at least for short periods of time after logging (i.e., ≤ 8 years).

","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2021.119447","usgsCitation":"Bateman, D.S., Chelgren, N., Gresswell, R.E., Dunham, J.B., Hockman-Wert, D., Leer, D.W., and Bladon, K., 2021, Fish response to successive clearcuts in a second-growth forest from the central Coast range of Oregon: Forest Ecology and Management, v. 496, 119447, 15 p., https://doi.org/10.1016/j.foreco.2021.119447.","productDescription":"119447, 15 p.","ipdsId":"IP-130611","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":450813,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2021.119447","text":"Publisher Index Page"},{"id":401979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Alsea River Watershed, Drift Creek, Flynn Creek, Needle Branch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.0143585205078,\n 44.38865427337759\n ],\n [\n -123.79737854003905,\n 44.38865427337759\n ],\n [\n -123.79737854003905,\n 44.524416083679924\n ],\n [\n -124.0143585205078,\n 44.524416083679924\n ],\n [\n -124.0143585205078,\n 44.38865427337759\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"496","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bateman, D. S.","contributorId":292361,"corporation":false,"usgs":false,"family":"Bateman","given":"D.","email":"","middleInitial":"S.","affiliations":[{"id":62882,"text":"Department of Forest Engineering, Resources, and Management, College of Forestry, Oregon State University, Corvallis, OR","active":true,"usgs":false}],"preferred":false,"id":844391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chelgren, Nathan 0000-0003-0944-9165 nchelgren@usgs.gov","orcid":"https://orcid.org/0000-0003-0944-9165","contributorId":3134,"corporation":false,"usgs":true,"family":"Chelgren","given":"Nathan","email":"nchelgren@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":844392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gresswell, Robert E. 0000-0003-0063-855X bgresswell@usgs.gov","orcid":"https://orcid.org/0000-0003-0063-855X","contributorId":152031,"corporation":false,"usgs":true,"family":"Gresswell","given":"Robert","email":"bgresswell@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":844393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":844394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hockman-Wert, David 0000-0003-2436-6237 dhockman-wert@usgs.gov","orcid":"https://orcid.org/0000-0003-2436-6237","contributorId":3891,"corporation":false,"usgs":true,"family":"Hockman-Wert","given":"David","email":"dhockman-wert@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":844395,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leer, D. W.","contributorId":292363,"corporation":false,"usgs":false,"family":"Leer","given":"D.","email":"","middleInitial":"W.","affiliations":[{"id":62882,"text":"Department of Forest Engineering, Resources, and Management, College of Forestry, Oregon State University, Corvallis, OR","active":true,"usgs":false}],"preferred":false,"id":844396,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bladon, K. D.","contributorId":292364,"corporation":false,"usgs":false,"family":"Bladon","given":"K. D.","affiliations":[{"id":62882,"text":"Department of Forest Engineering, Resources, and Management, College of Forestry, Oregon State University, Corvallis, OR","active":true,"usgs":false}],"preferred":false,"id":844397,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70226460,"text":"70226460 - 2021 - Could climate change benefit invasive snakes? Modelling the potential distribution of the California Kingsnake in the Canary Islands","interactions":[],"lastModifiedDate":"2021-11-18T12:45:30.779819","indexId":"70226460","displayToPublicDate":"2021-09-15T06:43:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Could climate change benefit invasive snakes? Modelling the potential distribution of the California Kingsnake in the Canary Islands","docAbstract":"

The interaction between climate change and biological invasions is a global conservation challenge with major consequences for invasive species management. However, our understanding of this interaction has substantial knowledge gaps; this is particularly relevant for invasive snakes on islands because they can be a serious threat to island ecosystems. Here we evaluated the potential influence of climate change on the distribution of invasive snakes on islands, using the invasion of the California kingsnake (Lampropeltis californiae) in Gran Canaria. We analysed the potential distribution of L. californiae under current and future climatic conditions in the Canary Islands, with the underlying hypothesis that the archipelago might be suitable for the species under these climate scenarios. Our results indicate that the Canary Islands are currently highly suitable for the invasive snake, with increased suitability under the climate change scenarios tested here. This study supports the idea that invasive reptiles represent a substantial threat to near-tropical regions, and builds on previous studies suggesting that the menace of invasive reptiles may persist or even be exacerbated by climate change. We suggest future research should continue to fill the knowledge gap regarding invasive reptiles, in particular snakes, to clarify their potential future impacts on global biodiversity.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2021.112917","usgsCitation":"Piquet, J.C., Warren, D.L., Bolanos, J.F., Rivero, J.M., Gallo-Barneto, R., Cabrera-Perez, M.A., Fisher, R., Fisher, S.R., Rochester, C.J., Hinds, B., Nogales, M., and Lopez-Darias, M., 2021, Could climate change benefit invasive snakes? Modelling the potential distribution of the California Kingsnake in the Canary Islands: Journal of Environmental Management, v. 294, 112917, 8 p., https://doi.org/10.1016/j.jenvman.2021.112917.","productDescription":"112917, 8 p.","ipdsId":"IP-130137","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":450819,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2021.112917","text":"Publisher Index Page"},{"id":391854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Canary Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -18.6328125,\n 27.29368922485238\n ],\n [\n -12.98583984375,\n 27.29368922485238\n ],\n [\n -12.98583984375,\n 29.535229562948444\n ],\n [\n -18.6328125,\n 29.535229562948444\n ],\n [\n -18.6328125,\n 27.29368922485238\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"294","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Piquet, Julien C","contributorId":269379,"corporation":false,"usgs":false,"family":"Piquet","given":"Julien","email":"","middleInitial":"C","affiliations":[{"id":55955,"text":"Instituto de Productos Naturales y Agrobiología, Tenerife, Canary Islands, Spain","active":true,"usgs":false}],"preferred":false,"id":826982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warren, Dan L","contributorId":269380,"corporation":false,"usgs":false,"family":"Warren","given":"Dan","email":"","middleInitial":"L","affiliations":[{"id":55958,"text":"Senckenberg Biodiversity and Climate Research Centre (BiK-F), Frankfurt, Germany","active":true,"usgs":false}],"preferred":false,"id":826983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bolanos, Jorge Fernando Saavedra","contributorId":269381,"corporation":false,"usgs":false,"family":"Bolanos","given":"Jorge","email":"","middleInitial":"Fernando Saavedra","affiliations":[{"id":55959,"text":"Área de Medio Ambiente. Gestión y Planeamiento Territorial y Ambiental,Gran Canaria, Canary Islands, Spain","active":true,"usgs":false}],"preferred":false,"id":826984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rivero, Jose Miguel Sanchez","contributorId":269382,"corporation":false,"usgs":false,"family":"Rivero","given":"Jose","email":"","middleInitial":"Miguel Sanchez","affiliations":[{"id":55960,"text":"Gestión y Planeamiento Territorial y Ambiental, Gran Canaria, Canary Islands, Spain","active":true,"usgs":false}],"preferred":false,"id":826985,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gallo-Barneto, Ramon","contributorId":269383,"corporation":false,"usgs":false,"family":"Gallo-Barneto","given":"Ramon","email":"","affiliations":[{"id":55960,"text":"Gestión y Planeamiento Territorial y Ambiental, Gran Canaria, Canary Islands, Spain","active":true,"usgs":false}],"preferred":false,"id":826986,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cabrera-Perez, Miguel Angel","contributorId":269384,"corporation":false,"usgs":false,"family":"Cabrera-Perez","given":"Miguel","email":"","middleInitial":"Angel","affiliations":[{"id":55961,"text":"Dirección General de Protección de la Naturaleza, Gobierno de Canarias, Las Palmas, Gran Canaria, Canary Islands, Spain","active":true,"usgs":false}],"preferred":false,"id":826987,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":826988,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fisher, Sam R","contributorId":269385,"corporation":false,"usgs":false,"family":"Fisher","given":"Sam","email":"","middleInitial":"R","affiliations":[{"id":55962,"text":"Southwestern College","active":true,"usgs":false}],"preferred":false,"id":826989,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rochester, Carlton J. 0000-0002-0625-4496","orcid":"https://orcid.org/0000-0002-0625-4496","contributorId":207764,"corporation":false,"usgs":true,"family":"Rochester","given":"Carlton","email":"","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":826990,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hinds, Brian","contributorId":269386,"corporation":false,"usgs":false,"family":"Hinds","given":"Brian","email":"","affiliations":[{"id":55963,"text":"Herpetological Education and Research Project, Whittier, CA","active":true,"usgs":false}],"preferred":false,"id":826991,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Nogales, Manuel","contributorId":269387,"corporation":false,"usgs":false,"family":"Nogales","given":"Manuel","email":"","affiliations":[{"id":55964,"text":"Instituto de Productos Naturales y Agrobiología, Canary Islands, Spain","active":true,"usgs":false}],"preferred":false,"id":826992,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lopez-Darias, Marta","contributorId":269388,"corporation":false,"usgs":false,"family":"Lopez-Darias","given":"Marta","email":"","affiliations":[{"id":55964,"text":"Instituto de Productos Naturales y Agrobiología, Canary Islands, Spain","active":true,"usgs":false}],"preferred":false,"id":826993,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70229079,"text":"70229079 - 2021 - Modeling moose habitat use by age, sex, and season in Vermont, USA using high-resolution lidar and national land cover data","interactions":[],"lastModifiedDate":"2022-02-28T15:25:39.969747","indexId":"70229079","displayToPublicDate":"2021-09-14T09:13:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":693,"text":"Alces","active":true,"publicationSubtype":{"id":10}},"title":"Modeling moose habitat use by age, sex, and season in Vermont, USA using high-resolution lidar and national land cover data","docAbstract":"

Moose (Alces alces) populations have experienced unprecedented declines along the southern periphery of their range, including Vermont, USA. Habitat management may be used to improve the status of the population and health of individuals. To date, however, Vermont wildlife managers have been challenged to effectively use this important tool due to the lack of fine-scale information on moose space use and habitat characteristics. To assess habitat use, we combined more than 40,000 moose locations collected from radio-collared individuals (n = 74), recent land cover data, and high resolution, 3-dimensional lidar (light detection and ranging) data to develop Resource Utilization Functions (RUF) by age (mature and young adult), season (dormant and growth), and sex. Each RUF linked home range use to average habitat conditions within 400 m or 1 km of each 30 m2 pixel within the home range. Across analyses, the top RUF models included both composition (as measured through the National Land Cover Database) and structure (as measured through lidar) variables, and significantly outperformed models that excluded lidar variables. These findings support the notion that lidar is an effective tool for improving the ability of models to estimate patterns of habitat use, especially for larger bodied mammals. Generally speaking, female moose actively used areas with proportionally more regenerating forest (i.e., forage < 3.0 m) and more mature forest (i.e., canopy structure > 6.0 m), while males actively used more high elevation, mixed forest types. Further, moose exhibited important seasonal differences in habitat use that likely reflect temporal changes in energetic and nutritional requirements and behavior across the year. Moose used areas with proportionally more regenerating forest (i.e., forage < 3.0 m) during the growth period and female moose had strong positive associations with lidar-derived canopy structure during the growth (but not the dormant) period. Ultimately, the resultant maps of habitat use provide a means of informing management activities (e.g., the restoration or alteration of habitats to benefit moose) and policies around land use that may contribute to population recovery.

","language":"English","publisher":"North American Moose Conference and Workshop","usgsCitation":"Blouin, J., Debow, J., Rosenblatt, E., Alexander, C., Gieder, K., Fortin, N., Murdoch, J., and Donovan, T.M., 2021, Modeling moose habitat use by age, sex, and season in Vermont, USA using high-resolution lidar and national land cover data: Alces, v. 57, p. 71-98.","productDescription":"28 p.","startPage":"71","endPage":"98","ipdsId":"IP-121680","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":396552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396550,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://alcesjournal.org/index.php/alces/article/view/295"}],"country":"United 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\"}}]}","volume":"57","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Blouin, Joshua","contributorId":276322,"corporation":false,"usgs":false,"family":"Blouin","given":"Joshua","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":836422,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Debow, Jacob","contributorId":276321,"corporation":false,"usgs":false,"family":"Debow","given":"Jacob","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":836423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenblatt, Elias","contributorId":276324,"corporation":false,"usgs":false,"family":"Rosenblatt","given":"Elias","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":836424,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alexander, Cedric","contributorId":278589,"corporation":false,"usgs":false,"family":"Alexander","given":"Cedric","affiliations":[],"preferred":false,"id":836425,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gieder, Katherina","contributorId":280056,"corporation":false,"usgs":false,"family":"Gieder","given":"Katherina","affiliations":[{"id":27622,"text":"Vermont Fish and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":836426,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fortin, Nicholas","contributorId":287139,"corporation":false,"usgs":false,"family":"Fortin","given":"Nicholas","affiliations":[],"preferred":false,"id":836490,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Murdoch, James","contributorId":276325,"corporation":false,"usgs":false,"family":"Murdoch","given":"James","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":836427,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":836421,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70225676,"text":"70225676 - 2021 - An eddy-resolving numerical model to study turbulent flow, sediment and bed evolution using detached eddy simulation in a lateral separation zone at the field-scale","interactions":[],"lastModifiedDate":"2021-11-02T11:46:57.154677","indexId":"70225676","displayToPublicDate":"2021-09-14T06:44:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6503,"text":"Journal of Geophysical Research Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"An eddy-resolving numerical model to study turbulent flow, sediment and bed evolution using detached eddy simulation in a lateral separation zone at the field-scale","docAbstract":"

Turbulence-resolving simulations elucidate key elements of fluid dynamics and sediment transport in fluvial environments. This research presents a feasible strategy for applying state-of-the-art computational fluid mechanics to the study of sediment transport and morphodynamic processes in lateral separation zones, which are common features in canyon rivers where massive lateral flow separation causes large-scale turbulence that controls sediment erosion and deposition. An eddy-resolving model was developed and tested at the field-scale, coupling a viscous flow and sediment transport solver using Detached Eddy Simulation techniques. A morphodynamic model was applied to the viscous flow/sediment solver to calculate erosion and deposition. A simulation of turbulence was performed at the grid resolution for a straight channel to determine the relative contributions of modeled and resolved diffusivity. The time-dependent, energetically important, correlative, non-stationary signals of the simulated quantities were captured at the lateral separation zone. Strong periodic signals featured by high amplitude were found at the separation zone, while low frequency pulsations were observed at the reattachment zone of the lateral separation zone. Interactions between the eddies and the loose bed boundaries resulted in erosion of sediment at the main channel followed by deposition at the primary eddy and eddy bars.

tions elucidate key elements of fluid dynamics and sediment transport in fluvial environments. This research presents a feasible strategy for applying state-of-the-art computational fluid mechanics to the study of sediment transport and morphodynamic processes in lateral separation zones, which are common features in canyon rivers where massive lateral flow separation causes large-scale turbulence that controls sediment erosion and deposition. An eddy-resolving model was developed and tested at the field scale, coupling viscous flow and sediment transport solver using Detached Eddy Simulation (DES) techniques. A morphodynamic model was applied to the viscous flow/sediment solver to calculate erosion and deposition. A simulation of turbulence was performed at the grid resolution for a straight channel to determine the relative contributions of modeled and resolved diffusivity. The time-dependent, energetically important, correlative non-stationary signals of the simulated quantities were captured at the lateral separation zone. Strong periodic signals featured by high amplitude were found at the separation zone, while low frequency pulsations were observed at the reattachment zone of the lateral separation zone. Interactions between the eddies and the loose bed boundaries resulted in massive erosion of sediment at the main channel followed by deposition at the primary eddy and eddy bars.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JF006149","usgsCitation":"Alvarez, L.V., and Grams, P.E., 2021, An eddy-resolving numerical model to study turbulent flow, sediment and bed evolution using detached eddy simulation in a lateral separation zone at the field-scale: Journal of Geophysical Research Earth Surface, v. 126, no. 10, e2021JF006149, 29 p., https://doi.org/10.1029/2021JF006149.","productDescription":"e2021JF006149, 29 p.","ipdsId":"IP-128083","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":391260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.1484375,\n 36.474306755095235\n ],\n [\n -110.89599609375,\n 36.474306755095235\n ],\n [\n -110.89599609375,\n 37.020098201368114\n ],\n [\n -112.1484375,\n 37.020098201368114\n ],\n [\n -112.1484375,\n 36.474306755095235\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","issue":"10","noUsgsAuthors":false,"publicationDate":"2021-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Alvarez, Laura V.","contributorId":178431,"corporation":false,"usgs":false,"family":"Alvarez","given":"Laura","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":826186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grams, Paul E. 0000-0002-0873-0708","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":216115,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":826187,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70223869,"text":"sir20215081 - 2021 - Storage capacity and sedimentation characteristics of Loch Lomond Reservoir, California, 2019","interactions":[],"lastModifiedDate":"2021-09-14T16:44:19.744785","indexId":"sir20215081","displayToPublicDate":"2021-09-13T07:29:23","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":"2021-5081","displayTitle":"Storage Capacity and Sedimentation Characteristics of Loch Lomond Reservoir, California, 2019","title":"Storage capacity and sedimentation characteristics of Loch Lomond Reservoir, California, 2019","docAbstract":"

In May of 2019, Loch Lomond Reservoir was surveyed by the U.S. Geological Survey (USGS) in cooperation with the city of Santa Cruz to assess the current storage capacity and sedimentation rates in the reservoir. Survey methods combined sonar soundings to measure bathymetry and lidar scans with GPS data to measure near-shore topography and sediment bed samples to understand reservoir bed-material
size. The survey data produced a bare-earth digital elevation model (DEM) of the reservoir at a resolution of 1 square meter or better to elevations at or above the reservoir spillway elevation, providing the coverage needed to estimate storage capacity. Additionally, the USGS compared the current survey to storage estimates from historical surveys—particularly the most recent survey in 2009—to evaluate storage capacity trends. Lastly, a hindcast estimate of scaled sediment yield using sediment yields from the San Lorenzo River (USGS station 11160500)—where the San Lorenzo River watershed encompasses the Loch Lomond Reservoir watershed—were used to compare indirect estimates of storage loss to direct storage loss.

The 2019 survey resulted in a measured storage capacity of 8,770±50 acre-feet. The differences in storage between 2009 and 2019 varied substantially by depth. In shallow areas with depths less than 30 ft (at full reservoir), such as the very upstream end of the reservoir, storage loss (sediment deposition) dominated with a loss of about 68 acre-feet from 2009 to 2019. In areas deeper than 30 ft, persistent small storage gains over a wide range of depths totaled 82 acre-feet from 2009 to 2019.

Storage loss estimates derived from estimated watershed sediment yields and reservoir characteristics were similar to storage losses computed from past surveys. This hindcasting produced an estimate of about 500 acre-feet of total storage loss for the history of the reservoir, or an average of about 8–9 acre-feet/year during the 60-year period. For the period 2009–2019, the hindcast produced an estimated total storage loss of 42 acre-feet, which is broadly consistent with the 68 acre-feet of storage loss computed for shallow areas based on the repeat surveys.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215081","collaboration":"Prepared in cooperation with the city of Santa Cruz","programNote":"Water Availability and Use Science Program","usgsCitation":"Whealdon-Haught, D.R., Wright, S.A., and Marineau, M.D., 2021, Storage capacity and sedimentation characteristics of Loch Lomond Reservoir, California, 2019: U.S. Geological Survey Scientific Investigations Report 2021-5081, 28 p., https://doi.org/10.3133/sir20215081.","productDescription":"Report: vii, 28 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-120568","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":389073,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5081/covrthb.jpg"},{"id":389074,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5081/sir20215081.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":389075,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5081/sir20215081.xml"},{"id":389076,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5081/images"},{"id":389147,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91BUQWP","linkHelpText":"Loch Lomond Reservoir 2019 Survey Data"}],"country":"United States","state":"California","otherGeospatial":"Loch Lomond Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.07509994506836,\n 37.10091974583046\n ],\n [\n -122.05415725708008,\n 37.10091974583046\n ],\n [\n -122.05415725708008,\n 37.130897691327746\n ],\n [\n -122.07509994506836,\n 37.130897691327746\n ],\n [\n -122.07509994506836,\n 37.10091974583046\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2021-09-13","noUsgsAuthors":false,"publicationDate":"2021-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Whealdon-Haught, Daniel R. 0000-0002-8923-1512","orcid":"https://orcid.org/0000-0002-8923-1512","contributorId":193160,"corporation":false,"usgs":false,"family":"Whealdon-Haught","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":823045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marineau, Mathieu D. 0000-0002-6568-0743 mmarineau@usgs.gov","orcid":"https://orcid.org/0000-0002-6568-0743","contributorId":4954,"corporation":false,"usgs":true,"family":"Marineau","given":"Mathieu","email":"mmarineau@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823047,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70226498,"text":"70226498 - 2021 - Assessment of multiple ecosystem metabolism methods in an estuary","interactions":[],"lastModifiedDate":"2021-11-22T13:21:39.355414","indexId":"70226498","displayToPublicDate":"2021-09-13T07:12:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9929,"text":"Limnology & Oceanography: Methods","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of multiple ecosystem metabolism methods in an estuary","docAbstract":"

Ecosystem metabolism is a key ecological attribute and easy to describe, but quantifying metabolism in estuaries is challenging. Properly scaling measurements through time and space requires consideration of hydrodynamics and mixing water from heterogeneous sources, making any estimation uncertain. Here, we compared three methods for modeling ecosystem metabolism in a portion of the Sacramento-San Joaquin Delta. Metabolism estimates based on laboratory incubations, continuous in situ buoys, and an oxygen isotope approach all indicated the system was net heterotrophic, and calculated rates were comparable in magnitude when averaged over the 2-month study. Daily metabolic rates based on in situ buoys were the most variable, likely due to horizontal and vertical advection and poor portrayal of the dissolved oxygen budget. After temporally averaging in situ buoy estimates or smoothing the dissolved oxygen time series for tidal effects, rates were more comparable to the other methods, which may be necessary to account for tidal advection and unbalanced contributions from subhabitats within the metabolic footprint. Incubation-based rates represent the finest temporal and spatial scale and only account for pelagic processes, which may explain why incubation-based rates were lower than the other two methods. The oxygen isotope method provided temporally and spatially integrated rates that were bracketed by the other two methods and may be a valuable tool in systems matching the model requirements. Because uncertainty arises in each method from a number of assumptions and scaling calculations, the resolution of metabolic rates in estuaries is likely coarser and more variable than in other aquatic ecosystems.

","language":"English","publisher":"Wiley","doi":"10.1002/lom3.10458","usgsCitation":"Loken, L.C., Van Nieuwenhuyse, E.E., Dahlgren, R.A., Kammel, L., Stumpner, P., Burau, J.R., and Sadro, S., 2021, Assessment of multiple ecosystem metabolism methods in an estuary: Limnology & Oceanography: Methods, v. 19, no. 11, p. 741-757, https://doi.org/10.1002/lom3.10458.","productDescription":"17 p.","startPage":"741","endPage":"757","ipdsId":"IP-128814","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":450828,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/05g263g3","text":"External Repository"},{"id":391974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6953125,\n 37.735969208590504\n ],\n [\n -121.124267578125,\n 37.735969208590504\n ],\n [\n -121.124267578125,\n 39.47860556892209\n ],\n [\n -122.6953125,\n 39.47860556892209\n ],\n [\n -122.6953125,\n 37.735969208590504\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Nieuwenhuyse, Erwin E 0000-0002-9032-2681","orcid":"https://orcid.org/0000-0002-9032-2681","contributorId":269423,"corporation":false,"usgs":false,"family":"Van Nieuwenhuyse","given":"Erwin","email":"","middleInitial":"E","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":827109,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dahlgren, Randy A 0000-0002-8961-875X","orcid":"https://orcid.org/0000-0002-8961-875X","contributorId":269424,"corporation":false,"usgs":false,"family":"Dahlgren","given":"Randy","email":"","middleInitial":"A","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":827110,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kammel, Leah 0000-0003-4613-0858","orcid":"https://orcid.org/0000-0003-4613-0858","contributorId":211840,"corporation":false,"usgs":true,"family":"Kammel","given":"Leah","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827111,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stumpner, Paul 0000-0002-0933-7895 pstump@usgs.gov","orcid":"https://orcid.org/0000-0002-0933-7895","contributorId":5667,"corporation":false,"usgs":true,"family":"Stumpner","given":"Paul","email":"pstump@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827112,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827113,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sadro, Steven 0000-0002-6416-3840","orcid":"https://orcid.org/0000-0002-6416-3840","contributorId":139662,"corporation":false,"usgs":false,"family":"Sadro","given":"Steven","email":"","affiliations":[{"id":12871,"text":"Marine Science Institute, University of California, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":827114,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70243718,"text":"70243718 - 2021 - Modeling watershed carbon dynamics as affected by land cover change and soil erosion","interactions":[],"lastModifiedDate":"2024-05-16T15:35:29.430932","indexId":"70243718","displayToPublicDate":"2021-09-11T08:50:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Modeling watershed carbon dynamics as affected by land cover change and soil erosion","docAbstract":"

Process-based ecosystem carbon cycle models typically incorporate vegetation growth, vegetation mortality, and soil respiration as well as the biotic and environmental drivers that influence these variables. However, few spatially explicit process models can efficiently incorporate the influence of land cover change and carbon lateral movement at regional scales or high spatial resolution. This study uses the Land Use and Carbon Scenario Simulator (LUCAS) to demonstrate the development of a fast ecosystem model that not only considers the basic carbon cycle but also incorporates the impact of land cover change, soil erosion, and soil deposition. As input to the LUCAS modeling framework, we used the integrated biosphere simulator (IBIS) to simulate a non-spatial reference carbon cycling scenario without considering land cover change for the Nisqually River watershed in the northwestern United States. We then used the Land Change Monitoring, Assessment, and Projection (LCMAP) remotely sensed 30-m sequential land cover data to generate annual land change history for the Nisqually River area from 1985 to 2017 and used the Unit Stream Powered Erosion and Deposition model (USPED) to estimate annual soil carbon lateral movement. Finally, we combined the annual carbon outputs from IBIS, the land change history from LCMAP, and the soil erosion and deposition from USPED within the LUCAS simulation framework. Results showed that from 1985 to 2017, along with the dynamic land cover changes, total ecosystem biomass carbon increased from 11.4 to 18.6 TgC, mainly due to forest growth. Total ecosystem soil carbon declined from 31.7 to 29.7 TgC, but the overall loss in soil carbon was not uniform across land cover types. Forestland (forest sector) and grassland lost carbon, while wetland, developed land and agricultural land gained carbon. Forest, grassland, and developed land lost 0.0553 TgC during the study period (1.73 Gg of C per year; 1 Gg = 0.001 Tg) from erosion, while wetland gained 0.0071 TgC (0.22 Gg C per year) from deposition. Agricultural land was neutral in terms of soil erosion.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2021.109724","usgsCitation":"Liu, J., Sleeter, B.M., Selmants, P., Diao, J., Zhou, Q., Worstell, B., and Moritsch, M.M., 2021, Modeling watershed carbon dynamics as affected by land cover change and soil erosion: Ecological Modelling, v. 459, 109724, 11 p., https://doi.org/10.1016/j.ecolmodel.2021.109724.","productDescription":"109724, 11 p.","ipdsId":"IP-129044","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":450838,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2021.109724","text":"Publisher Index Page"},{"id":436201,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A27GFH","text":"USGS data release","linkHelpText":"Simulated Nisqually River Watershed 30-m resolution 2017 ecosystem carbon variables from the LUCAS model"},{"id":417208,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.16253640390157,\n 47.168168689027254\n ],\n [\n -123.16253640390157,\n 46.28394294633836\n ],\n [\n -121.7181395192194,\n 46.28394294633836\n ],\n [\n -121.7181395192194,\n 47.168168689027254\n ],\n [\n -123.16253640390157,\n 47.168168689027254\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"459","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Jinxun 0000-0003-0561-8988 jxliu@usgs.gov","orcid":"https://orcid.org/0000-0003-0561-8988","contributorId":3414,"corporation":false,"usgs":true,"family":"Liu","given":"Jinxun","email":"jxliu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":873045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sleeter, Benjamin M. 0000-0003-2371-9571 bsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-9571","contributorId":3479,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","email":"bsleeter@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":873046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Selmants, Paul C. 0000-0001-6211-3957 pselmants@usgs.gov","orcid":"https://orcid.org/0000-0001-6211-3957","contributorId":192591,"corporation":false,"usgs":true,"family":"Selmants","given":"Paul","email":"pselmants@usgs.gov","middleInitial":"C.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":873047,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diao, Jiaojiao","contributorId":305505,"corporation":false,"usgs":false,"family":"Diao","given":"Jiaojiao","email":"","affiliations":[{"id":33416,"text":"Nanjing Forestry University, China","active":true,"usgs":false}],"preferred":false,"id":873048,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhou, Qiang 0000-0002-1282-8177","orcid":"https://orcid.org/0000-0002-1282-8177","contributorId":265886,"corporation":false,"usgs":false,"family":"Zhou","given":"Qiang","affiliations":[{"id":54817,"text":"AFDS, contractor to U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":873049,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Worstell, Bruce 0000-0001-8927-3336","orcid":"https://orcid.org/0000-0001-8927-3336","contributorId":305506,"corporation":false,"usgs":false,"family":"Worstell","given":"Bruce","affiliations":[{"id":66235,"text":"SGT Inc. Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":873050,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moritsch, Monica Mei Jeen 0000-0002-3890-1264","orcid":"https://orcid.org/0000-0002-3890-1264","contributorId":225210,"corporation":false,"usgs":true,"family":"Moritsch","given":"Monica","email":"","middleInitial":"Mei Jeen","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":873051,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70223695,"text":"sir20215084 - 2021 - Forecasting drought probabilities for streams in the northeastern United States","interactions":[],"lastModifiedDate":"2021-09-13T12:01:34.031419","indexId":"sir20215084","displayToPublicDate":"2021-09-10T14:10:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5084","displayTitle":"Forecasting Drought Probabilities for Streams in the Northeastern United States","title":"Forecasting drought probabilities for streams in the northeastern United States","docAbstract":"

Maximum likelihood logistic regression (MLLR) models for the northeastern United States forecast drought probability estimates for water flowing in rivers and streams using methods previously identified and developed. Streamflow data from winter months are used to estimate chances of hydrological drought during summer months. Daily streamflow data collected from 1,143 streamgages from April 1, 1877, through October 31, 2018, are used to provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February. This allows estimates of outcomes from 5 to 11 months ahead of their occurrence. Models specific to the northeastern United States were investigated and updated. The MLLR models of drought stream-flow probabilities utilize the explanatory power of temporally linked water flows. Models with strong drought streamflow probability correct-classification rates were produced for streams throughout the northeastern United States. A test of northeastern United States drought streamflow probability predictions found that overall correct-classification rates for drought streamflow probabilities in the northeastern United States exceeded 97 percent when predicting July 2019 drought probability using February 2019 monthly mean streamflow data. Using hydrological drought probability estimates in a water-management context informs understandings of possible future streamflow drought conditions in the northeastern United States, provides warnings of potential future drought conditions, and aids water-management decision making and responses to changing circumstances.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215084","usgsCitation":"Austin, S.H., 2021, Forecasting drought probabilities for streams in the northeastern United States: U.S. Geological Survey Scientific Investigations Report 2021–5084, 11 p., https://doi.org/10.3133/sir20215084.","productDescription":"Report: vi, 12 p.; Data Release","numberOfPages":"11","ipdsId":"IP-113685","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":388741,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5084/sir20215084.pdf","text":"Report","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5084"},{"id":388740,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5084/coverthb.jpg"},{"id":388742,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E3SK56","text":"USGS data release","linkHelpText":"Terms, statistics, and performance measures for maximum likelihood logistic regression models estimating hydrological drought probabilities in the northeastern United States (2019)"}],"country":"United States","state":"Connecticut, Delaware, Massachusetts, Maine, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Virginia, Vermont, West 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\"}}]}","contact":"

Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, Virginia 23228

","tableOfContents":"","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2021-09-02","noUsgsAuthors":false,"publicationDate":"2021-09-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Austin, Samuel H. 0000-0001-5626-023X saustin@usgs.gov","orcid":"https://orcid.org/0000-0001-5626-023X","contributorId":153,"corporation":false,"usgs":true,"family":"Austin","given":"Samuel","email":"saustin@usgs.gov","middleInitial":"H.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":822358,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70259936,"text":"70259936 - 2021 - A petrological and conceptual model of Mayon volcano (Philippines) as an example of an open-vent volcano","interactions":[],"lastModifiedDate":"2024-10-30T22:43:56.097024","indexId":"70259936","displayToPublicDate":"2021-09-10T06:54:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"A petrological and conceptual model of Mayon volcano (Philippines) as an example of an open-vent volcano","docAbstract":"

Mayon is a basaltic andesitic, open-vent volcano characterized by persistent passive degassing from the summit at 2463 m above sea level. Mid-size (<0.1 km3) and mildly explosive eruptions and occasional phreatic eruptions have occurred approximately every 10 years for over a hundred years. Mayon’s plumbing system structure, processes, and time scales driving its eruptions are still not well-known, despite being the most active volcano in the Philippines. We investigated the petrology and geochemistry of its crystal-rich lavas (~50 vol% phenocrysts) from nine historical eruptions between 1928 and 2009 and propose a conceptual model of the processes and magmatic architecture that led to the eruptions. The whole-rock geochemistry and mineral assemblage (plagioclase + orthopyroxene + clinopyroxene + Fe-Ti oxide ± olivine) of the lavas have remained remarkably homogenous (54 wt% SiO2,~4 wt% MgO) from 1928 to 2009. However, electron microscope images and microprobe analyses of the phenocrysts and the existence of three types of glomerocrysts testify to a range of magmatic processes, including long-term magma residence, magma mixing, crystallization, volatile fluxing, and degassing. Multiple mineral-melt geothermobarometers suggest a relatively thermally buffered system at 1050±25 °C, with several magma residence zones, ranging from close to the surface, through reservoirs at ~4–5 km, and as deep as ~ 20 km. Diffusion chronometry on >200 orthopyroxene crystals reveal magma mixing timescales that range from a few days to about 65 years, but the majority are shorter than the decadal inter-eruptive repose period. This implies that magma intrusion at Mayon has been nearly continuous over the studied time period, with limited crystal recycling from one eruption to the next. The variety of plagioclase textures and zoning patterns reflect fluxing of volatiles from depth to shallower melts through which they eventually reach the atmosphere through an open conduit. The crystal-rich nature of the erupted magmas may have developed during each inter-eruptive period. We propose that Mayon has behaved over almost 100 years as a steady state system, with limited variations in eruption frequency, degassing flux, magma composition, and crystal content that are mainly determined by the amount and composition of deep magma and volatile input in the system. We explore how Mayon volcano’s processes and working model can be related to other open-vent mafic and water-rich systems such as Etna, Stromboli, Villarrica, or Llaima. Finally, our understanding of open-vent, persistently active volcanoes is rooted in historical observations, but volcano behavior can evolve over longer time frames. We speculate that these volcanoes produce specific plagioclase textures that can be used to identify similar volcanic behavior in the geologic record.

","language":"English","publisher":"Springer","doi":"10.1007/s00445-021-01486-9","usgsCitation":"Ruth, D.C., and Costa, F., 2021, A petrological and conceptual model of Mayon volcano (Philippines) as an example of an open-vent volcano: Bulletin of Volcanology, v. 83, 62, 28 p., https://doi.org/10.1007/s00445-021-01486-9.","productDescription":"62, 28 p.","ipdsId":"IP-123082","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467226,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-021-01486-9","text":"Publisher Index Page"},{"id":463239,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Philippines","otherGeospatial":"Mayon volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 123.5101731400274,\n 13.501020877721444\n ],\n [\n 123.5101731400274,\n 13.33999591750549\n ],\n [\n 123.70654204522504,\n 13.33999591750549\n ],\n [\n 123.70654204522504,\n 13.501020877721444\n ],\n [\n 123.5101731400274,\n 13.501020877721444\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"83","noUsgsAuthors":false,"publicationDate":"2021-09-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruth, Dawn Catherine Sweeney 0000-0001-9369-9364","orcid":"https://orcid.org/0000-0001-9369-9364","contributorId":334908,"corporation":false,"usgs":true,"family":"Ruth","given":"Dawn","email":"","middleInitial":"Catherine Sweeney","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costa, Fidel","contributorId":184169,"corporation":false,"usgs":false,"family":"Costa","given":"Fidel","email":"","affiliations":[],"preferred":false,"id":916875,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227783,"text":"70227783 - 2021 - The potential of satellite remote sensing time series to uncover wetland phenology under unique challenges of tidal setting","interactions":[],"lastModifiedDate":"2022-01-31T16:09:37.311812","indexId":"70227783","displayToPublicDate":"2021-09-09T09:54:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"The potential of satellite remote sensing time series to uncover wetland phenology under unique challenges of tidal setting","docAbstract":"While growth history of vegetation within upland systems is well studied, plant phenology within coastal tidal systems is less understood. Landscape-scale, satellite-derived indicators of plant greenness may not adequately represent seasonality of vegetation biomass and productivity within tidal wetlands due to limitations of cloud cover, satellite temporal frequency and attenu-ation of plant signals by tidal flooding. However, understanding plant phenology is necessary to gain insight into aboveground biomass, photosynthetic activity, and carbon sequestration. In this study we use a modeling approach to estimate plant greenness throughout a year in tidal wet-lands located within the San Francisco Bay Area, USA. We used variables such as EVI history, temperature, and elevation to predict plant greenness on a 14-day timestep. We found this ap-proach accurately estimated plant greenness, with larger error observed within more dynamic restored wetlands, particularly at early post-restoration stages. We also found modeled EVI can be used as an input variable into greenhouse gas models, allowing for an estimate of carbon se-questration and gross primary production. Our strategy can be further developed in future re-search by assessing restoration and management effects on wetland phenological dynamics and through incorporating the entire Sentinel-2 time-series once it becomes available within Google Earth Engine.","language":"English","publisher":"MDPI","doi":"10.3390/rs13183589","collaboration":"=","usgsCitation":"Miller, G.J., Dronova, I., Oikawa, P., Knox, S., Windham-Myers, L., Shahan, J., and Stuart-Haëntjens, E., 2021, The potential of satellite remote sensing time series to uncover wetland phenology under unique challenges of tidal setting: Remote Sensing, v. 13, no. 18, p. 1-28, https://doi.org/10.3390/rs13183589.","productDescription":"3589, 28 p.","startPage":"1","endPage":"28","ipdsId":"IP-133045","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":450854,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13183589","text":"Publisher Index Page"},{"id":395144,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","otherGeospatial":"San Francisco Bay Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.728271484375,\n 37.276238364942955\n ],\n [\n -121.75872802734375,\n 37.276238364942955\n ],\n [\n -121.75872802734375,\n 38.26406296833961\n ],\n [\n -122.728271484375,\n 38.26406296833961\n ],\n [\n -122.728271484375,\n 37.276238364942955\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"18","noUsgsAuthors":false,"publicationDate":"2021-09-09","publicationStatus":"PW","contributors":{"editors":[{"text":"Bostater, Charles R. Jr.","contributorId":272837,"corporation":false,"usgs":false,"family":"Bostater","given":"Charles","suffix":"Jr.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":832310,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Miller, Gwendolyn Joelle 0000-0002-5712-945X","orcid":"https://orcid.org/0000-0002-5712-945X","contributorId":272606,"corporation":false,"usgs":false,"family":"Miller","given":"Gwendolyn","email":"","middleInitial":"Joelle","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":832226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dronova, Iryna 0000-0003-3339-3704","orcid":"https://orcid.org/0000-0003-3339-3704","contributorId":272607,"corporation":false,"usgs":false,"family":"Dronova","given":"Iryna","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":832227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oikawa, Patricia","contributorId":272608,"corporation":false,"usgs":false,"family":"Oikawa","given":"Patricia","affiliations":[{"id":56387,"text":"CSU East Bay","active":true,"usgs":false}],"preferred":false,"id":832228,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knox, Sara Helen 0000-0003-2255-5835","orcid":"https://orcid.org/0000-0003-2255-5835","contributorId":272609,"corporation":false,"usgs":false,"family":"Knox","given":"Sara Helen","affiliations":[{"id":56388,"text":"U. British Columbia","active":true,"usgs":false}],"preferred":false,"id":832229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Windham-Myers, Lisamarie","contributorId":272610,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":832230,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shahan, Julie","contributorId":272611,"corporation":false,"usgs":false,"family":"Shahan","given":"Julie","email":"","affiliations":[{"id":56387,"text":"CSU East Bay","active":true,"usgs":false}],"preferred":false,"id":832231,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stuart-Haëntjens, Ellen 0000-0001-9901-7643","orcid":"https://orcid.org/0000-0001-9901-7643","contributorId":265857,"corporation":false,"usgs":true,"family":"Stuart-Haëntjens","given":"Ellen","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832232,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70223891,"text":"70223891 - 2021 - The structure and volume of large geysers in Yellowstone National Park, USA and the mineralogy and chemistry of their silica sinter deposits","interactions":[],"lastModifiedDate":"2021-10-06T15:58:41.800728","indexId":"70223891","displayToPublicDate":"2021-09-09T07:50:23","publicationYear":"2021","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":"The structure and volume of large geysers in Yellowstone National Park, USA and the mineralogy and chemistry of their silica sinter deposits","docAbstract":"

Siliceous sinter is formed by biogenic and abiogenic opal deposition around hot springs and geysers. Using Structure-from-Motion photogrammetry we generated three-dimensional models of Giant and Castle Geysers from the Upper Geyser Basin of Yellowstone National Park. We use these models to calculate an approximate mass of sinter for each (~2 and ~ 5 kton, respectively) and estimate a range of plausible long-term deposition rates for Castle Geyser (470 to 940 kg·yr−1). We estimate ~2% of the silica discharged from Castle Geyser is deposited as sinter in the cone and proximal terraces. We collected 15 sinter samples following the stratigraphy of each geyser from an older terrace to a younger cone and examined them using a variety of analytical methods. We find that young opaline sinter with a water content of <12 wt% (from loss on ignition) contains higher concentrations of major and trace elements, notably As, Sb, Rb, Ga and Cs, relative to older dehydrated sinter. Rare earth element (REE) concentrations in sinter are 2–3 orders of magnitude higher than in the thermal water from which they are deposited. Sinter deposits are enriched in light REE, Gd and Yb when normalized to concentrations in thermal water and enriched in Eu, Tm, and Yb when normalized to the underlying rhyolite. Sinter samples with the highest REE concentrations are also enriched in organic material, implying either microbial uptake of REE, or that organic molecules are efficient ligands that form metal complexes.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107391","usgsCitation":"Churchill, D., Manga, M., Hurwitz, S., Peek, S., Damby, D., Conrey, R., Wood, J.R., McCleskey, R., Keller, W.E., Hosseini, B., and Hungerford, J.D., 2021, The structure and volume of large geysers in Yellowstone National Park, USA and the mineralogy and chemistry of their silica sinter deposits: Journal of Volcanology and Geothermal Research, v. 419, 107391, 17 p., https://doi.org/10.1016/j.jvolgeores.2021.107391.","productDescription":"107391, 17 p.","ipdsId":"IP-130151","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":450859,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2021.107391","text":"Publisher Index Page"},{"id":389139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.03881835937499,\n 43.43696596521823\n ],\n [\n -108.69873046875,\n 43.43696596521823\n ],\n [\n -108.69873046875,\n 45.01918507438176\n ],\n [\n -111.03881835937499,\n 45.01918507438176\n ],\n [\n -111.03881835937499,\n 43.43696596521823\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"419","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Churchill, Dakota 0000-0003-3382-5562","orcid":"https://orcid.org/0000-0003-3382-5562","contributorId":265639,"corporation":false,"usgs":false,"family":"Churchill","given":"Dakota","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":823143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manga, Michael 0000-0003-3286-4682","orcid":"https://orcid.org/0000-0003-3286-4682","contributorId":265640,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":823144,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peek, Sara 0000-0002-9770-6557","orcid":"https://orcid.org/0000-0002-9770-6557","contributorId":209971,"corporation":false,"usgs":true,"family":"Peek","given":"Sara","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823146,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Damby, David 0000-0002-3238-3961","orcid":"https://orcid.org/0000-0002-3238-3961","contributorId":206614,"corporation":false,"usgs":true,"family":"Damby","given":"David","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823147,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Conrey, Richard","contributorId":265641,"corporation":false,"usgs":false,"family":"Conrey","given":"Richard","affiliations":[{"id":54747,"text":"Hamilton College","active":true,"usgs":false}],"preferred":false,"id":823148,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wood, John R.","contributorId":265642,"corporation":false,"usgs":false,"family":"Wood","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":823149,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":205663,"corporation":false,"usgs":true,"family":"McCleskey","given":"R. Blaine","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":823150,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Keller, William E.","contributorId":265643,"corporation":false,"usgs":false,"family":"Keller","given":"William","email":"","middleInitial":"E.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":823151,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hosseini, Behnaz","contributorId":265644,"corporation":false,"usgs":false,"family":"Hosseini","given":"Behnaz","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":823152,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hungerford, Jefferson D.G.","contributorId":265645,"corporation":false,"usgs":false,"family":"Hungerford","given":"Jefferson","email":"","middleInitial":"D.G.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":823153,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70230349,"text":"70230349 - 2021 - Improvements to the Third Uniform California Earthquake Rupture Forecast ETAS Model (UCERF3‐ETAS)","interactions":[],"lastModifiedDate":"2024-01-24T16:40:40.565813","indexId":"70230349","displayToPublicDate":"2021-09-09T07:14:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10542,"text":"The Seismic Record","active":true,"publicationSubtype":{"id":10}},"title":"Improvements to the Third Uniform California Earthquake Rupture Forecast ETAS Model (UCERF3‐ETAS)","docAbstract":"

We describe recent improvements to the Third Uniform California Earthquake Rupture Forecast ETAS Model (UCERF3‐ETAS), which continues to represent our most advanced and complete earthquake forecast in terms of relaxing segmentation assumptions and representing multifault ruptures, elastic‐rebound effects, and spatiotemporal clustering (the latter to represent aftershocks and otherwise triggered events). The two main improvements include adding aleatory variability in aftershock productivity and the option to represent off‐fault events with finite‐rupture surfaces. We also summarize the studies that led to these modifications, and reflect on how past and future uses of the model can improve our understanding of earthquake processes and the hazards and risks they pose.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320210017","usgsCitation":"Field, E.H., Milner, K.R., Page, M.T., Savran, W.H., and van der Elst, N., 2021, Improvements to the Third Uniform California Earthquake Rupture Forecast ETAS Model (UCERF3‐ETAS): The Seismic Record, v. 1, no. 2, p. 117-125, https://doi.org/10.1785/0320210017.","productDescription":"9 p.","startPage":"117","endPage":"125","ipdsId":"IP-131403","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":450861,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320210017","text":"Publisher Index Page"},{"id":398384,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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nvanderelst@usgs.gov","orcid":"https://orcid.org/0000-0002-3812-1153","contributorId":147858,"corporation":false,"usgs":true,"family":"van der Elst","given":"Nicholas","email":"nvanderelst@usgs.gov","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":840043,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223914,"text":"70223914 - 2021 - Estimating and forecasting time-varying groundwater recharge in fractured rock: A state-space formulation with preferential and diffuse flow to the water table","interactions":[],"lastModifiedDate":"2021-10-06T16:00:10.10863","indexId":"70223914","displayToPublicDate":"2021-09-09T07:11:15","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":"Estimating and forecasting time-varying groundwater recharge in fractured rock: A state-space formulation with preferential and diffuse flow to the water table","docAbstract":"

Rapid infiltration following precipitation may result in groundwater contamination from surface contaminants or pathogens. In fractured rock, contaminants can migrate rapidly to points of groundwater withdrawals. In contrast to the temporal availability of groundwater quality chemical indicators, meteorological and groundwater level observations are available in real-time to estimate time-varying recharge, which can act as a surrogate to identify periods of rapid infiltration that may indicate contamination susceptibility. Estimating recharge using methods, such as base-flow recession, unsaturated infiltration models, or Water-Table Fluctuations (WTF), cannot capitalize on currently available technologies and telecommunication infrastructure to conduct real-time recharge estimation at scales relevant to characterizing rapid infiltration. We present a linear, physics-based State-Space (SS) model of one-dimensional infiltration to estimate recharge, which includes preferential and diffuse-flow to the water table. The model can take advantage of real-time data for water-table altitude, precipitation, and evapotranspiration. Model parameters are calibrated over an observation period, and the Kalman Filter (KF) is subsequently applied to continuously update the observed (water-table altitude) and unobserved (groundwater recharge) system states and predict future states as new data become available. The SS/KF algorithm is demonstrated at the Masser Groundwater Recharge Site in Pennsylvania, USA and comparisons are made with recharge estimates from WTF methods. Model results indicate that the frequency of observations (daily versus sub-daily) dictates the allocation between preferential and diffuse flow. Additionally, because infiltration processes encompass many nonlinearities, model parameters estimated from observation periods need to be updated at least seasonally to account for changing recharge conditions.

","language":"English","publisher":"Wiley","doi":"10.1029/2020WR029110","usgsCitation":"Shapiro, A.M., and Day-Lewis, F., 2021, Estimating and forecasting time-varying groundwater recharge in fractured rock: A state-space formulation with preferential and diffuse flow to the water table: Water Resources Research, v. 57, no. 9, e2020WR029110, 30 p., https://doi.org/10.1029/2020WR029110.","productDescription":"e2020WR029110, 30 p.","ipdsId":"IP-122279","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":450863,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020wr029110","text":"Publisher Index Page"},{"id":436205,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VBR9V8","text":"USGS data release","linkHelpText":"Algorithms for model parameter estimation, state estimation, and forecasting applied to a State-Space model coupled with the Kalman Filter for one-dimensional vertical infiltration to fractured rock aquifers"},{"id":436204,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LLXCIC","text":"USGS data release","linkHelpText":"Water Level Altitude in Bedrock Wells and Meteorological Data at the Masser Groundwater Recharge Site between February 1 and December 31, 1999"},{"id":389205,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-09-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Shapiro, Allen M. 0000-0002-6425-9607 ashapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":2164,"corporation":false,"usgs":true,"family":"Shapiro","given":"Allen","email":"ashapiro@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":823234,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick 0000-0003-3526-886X","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":216359,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":823235,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70223784,"text":"70223784 - 2021 - Global drivers of avian haemosporidian infections vary across zoogeographical regions","interactions":[],"lastModifiedDate":"2021-11-16T15:41:14.844104","indexId":"70223784","displayToPublicDate":"2021-09-08T14:05:28","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Global drivers of avian haemosporidian infections vary across zoogeographical regions","docAbstract":"

Aim: Macroecological analyses provide valuable insights into factors that influence how parasites are distributed across space and among hosts. Amid large uncertainties that arise when generalizing from local and regional findings, hierarchical approaches applied to global datasets are required to determine whether drivers of parasite infection patterns vary across scales. We assessed global patterns of haemosporidian infections across a broad diversity of avian host clades and zoogeographical realms to depict hotspots of prevalence and to identify possible underlying drivers.

Location: Global.

Time period: 1994–2019.

Major taxa studied: Avian haemosporidian parasites (genera Plasmodium, Haemoproteus, Leucocytozoon and Parahaemoproteus).

Methods: We amalgamated infection data from 53,669 individual birds representing 2,445 species world-wide. Spatio-phylogenetic hierarchical Bayesian models were built to disentangle potential landscape, climatic and biotic drivers of infection probability while accounting for spatial context and avian host phylogenetic relationships.

Results: Idiosyncratic responses of the three most common haemosporidian genera to climate, habitat, host relatedness and host ecological traits indicated marked variation in host infection rates from local to global scales. Notably, host ecological drivers, such as migration distance for Plasmodium and Parahaemoproteus, exhibited predominantly varying or even opposite effects on infection rates across regions, whereas climatic effects on infection rates were more consistent across realms. Moreover, infections in some low-prevalence realms were disproportionately concentrated in a few local hotspots, suggesting that regional-scale variation in habitat and microclimate might influence transmission, in addition to global drivers.

Main conclusions: Our hierarchical global analysis supports regional-scale findings showing the synergistic effects of landscape, climate and host ecological traits on parasite transmission for a cosmopolitan and diverse group of avian parasites. Our results underscore the need to account for such interactions, in addition to possible variation in drivers across regions, to produce the robust inference required to predict changes in infection risk under future scenarios.

","language":"English","publisher":"John Wiley & Sons","doi":"10.1111/geb.13390","usgsCitation":"Fecchio, A., Clark, N.J., Bell, J.A., Skeen, H., Lutz, H.L., De La Torre, G.M., Vaughan, J.A., Tkach, V.V., Schunck, F., Ferreira, F.C., Braga, E.M., Lugarini, C., Wamiti, W., Dispoto, J.H., Galen, S.C., Kirchgatter, K., Sagario, M.C., Cueto, V., Gonzalez-Acuna, D., Inumaru, M., Sato, Y., Schumm, Y.R., Quillfeldt, P., Pellegrino, I., Dharmarajan, G., Gupta, P., Robin, V.V., Ciloglu, A., Yildirim, A., Huang, X., Chapa-Vargas, L., Alvarez-Mendizabal, P., Santiago-Alarcon, D., Drovetski, S.V., Hellgren, O., Voelker, G., Ricklefs, R.E., Hackett, S., Collins, M.D., Weckstein, J.D., and Wells, K., 2021, Global drivers of avian haemosporidian infections vary across zoogeographical regions: Global Ecology and Biogeography, v. 30, no. 12, p. 2393-2406, https://doi.org/10.1111/geb.13390.","productDescription":"14 p.","startPage":"2393","endPage":"2406","temporalStart":"1994-01-01","temporalEnd":"2019-12-31","ipdsId":"IP-126030","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":450866,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1980622","text":"External Repository"},{"id":388968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-09-07","publicationStatus":"PW","contributors":{"editors":[{"text":"Kamath, Pauline","contributorId":198306,"corporation":false,"usgs":false,"family":"Kamath","given":"Pauline","affiliations":[],"preferred":false,"id":822778,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Fecchio, Alan 0000-0002-7319-0234","orcid":"https://orcid.org/0000-0002-7319-0234","contributorId":265372,"corporation":false,"usgs":false,"family":"Fecchio","given":"Alan","email":"","affiliations":[{"id":54651,"text":"Programa de Pós-Graduação em Ecologia e Conservação da Biodiversidade, Universidade Federal de Mato Grosso, Avenida Fernando Corrêa da Costa 2367, Cuiabá, MT, 78060900, Brazil","active":true,"usgs":false}],"preferred":false,"id":822666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Nicholas J.","contributorId":204867,"corporation":false,"usgs":false,"family":"Clark","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":16755,"text":"University of Queensland, Australia","active":true,"usgs":false}],"preferred":false,"id":822667,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bell, Jeffrey A","contributorId":265373,"corporation":false,"usgs":false,"family":"Bell","given":"Jeffrey","email":"","middleInitial":"A","affiliations":[{"id":52695,"text":"Department of Biology, University of North Dakota, Grand Forks, ND 58201, USA","active":true,"usgs":false}],"preferred":false,"id":822668,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skeen, Heather","contributorId":265374,"corporation":false,"usgs":false,"family":"Skeen","given":"Heather","email":"","affiliations":[{"id":54652,"text":"Committee on Evolutionary Biology, University of Chicago, Chicago, IL, 6063 and Negaunee Integrative Research Center, The Field Museum, Chicago, IL, 60605 USA","active":true,"usgs":false}],"preferred":false,"id":822669,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lutz, Holly L","contributorId":265375,"corporation":false,"usgs":false,"family":"Lutz","given":"Holly","email":"","middleInitial":"L","affiliations":[{"id":54653,"text":"Department of Surgery, University of Chicago, 5812 S. Ellis Ave., Chicago, IL 60637 and Integrative Research Center, Field Museum of Natural History, 1400 South Lake Shore Drive, Chicago, IL 60605 USA","active":true,"usgs":false}],"preferred":false,"id":822670,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"De La Torre, Gabriel M","contributorId":265384,"corporation":false,"usgs":false,"family":"De La Torre","given":"Gabriel","email":"","middleInitial":"M","affiliations":[{"id":54663,"text":"Programa de Pós-graduação em Ecologia e Conservação, Universidade Federal do Paraná, Curitiba, PR, Brazil","active":true,"usgs":false}],"preferred":false,"id":822681,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vaughan, Jefferson A","contributorId":265376,"corporation":false,"usgs":false,"family":"Vaughan","given":"Jefferson","email":"","middleInitial":"A","affiliations":[{"id":52695,"text":"Department of Biology, University of North Dakota, Grand Forks, ND 58201, USA","active":true,"usgs":false}],"preferred":false,"id":822671,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tkach, Vasyl V.","contributorId":190351,"corporation":false,"usgs":false,"family":"Tkach","given":"Vasyl","email":"","middleInitial":"V.","affiliations":[{"id":52695,"text":"Department of Biology, University of North Dakota, Grand Forks, ND 58201, USA","active":true,"usgs":false}],"preferred":false,"id":822672,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schunck, Fabio","contributorId":265377,"corporation":false,"usgs":false,"family":"Schunck","given":"Fabio","email":"","affiliations":[{"id":54654,"text":"Brazilian Committee for Ornithological Records – CBRO","active":true,"usgs":false}],"preferred":false,"id":822673,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ferreira, Francisco C","contributorId":265378,"corporation":false,"usgs":false,"family":"Ferreira","given":"Francisco","email":"","middleInitial":"C","affiliations":[{"id":54655,"text":"Center for Conservation Genomics, Smithsonian Conservation Biology Institute, Washington, DC, USA","active":true,"usgs":false}],"preferred":false,"id":822674,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Braga, Erika M","contributorId":265379,"corporation":false,"usgs":false,"family":"Braga","given":"Erika","email":"","middleInitial":"M","affiliations":[{"id":54658,"text":"Departamento de Parasitologia, Universidade Federal de Minas Gerais, Belo Horizonte, MG 31270-901, Brazil","active":true,"usgs":false}],"preferred":false,"id":822675,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lugarini, Camile","contributorId":265380,"corporation":false,"usgs":false,"family":"Lugarini","given":"Camile","email":"","affiliations":[{"id":54659,"text":"Centro Nacional de Pesquisa e Conservação de Aves Silvestres, Instituto Chico Mendes de Conservação da Biodiversidade, Florianópolis, SC, Brazil","active":true,"usgs":false}],"preferred":false,"id":822676,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wamiti, Wanyoike","contributorId":265381,"corporation":false,"usgs":false,"family":"Wamiti","given":"Wanyoike","email":"","affiliations":[{"id":54660,"text":"Zoology Department, National Museums of Kenya, P.O. 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D","contributorId":265391,"corporation":false,"usgs":false,"family":"Weckstein","given":"Jason","email":"","middleInitial":"D","affiliations":[{"id":54670,"text":"Department of Ornithology, Academy of Natural Sciences of Drexel University, Philadelphia, PA 19103, USA and Department of Biodiversity, Earth, and Environmental Sciences, Drexel University, Philadelphia, PA 19103, USA","active":true,"usgs":false}],"preferred":false,"id":822690,"contributorType":{"id":1,"text":"Authors"},"rank":40},{"text":"Wells, Konstans","contributorId":265392,"corporation":false,"usgs":false,"family":"Wells","given":"Konstans","email":"","affiliations":[{"id":54671,"text":"Department of Biosciences, Swansea University, Swansea, SA2 8PP UK","active":true,"usgs":false}],"preferred":false,"id":822691,"contributorType":{"id":1,"text":"Authors"},"rank":41}]}} ,{"id":70224627,"text":"70224627 - 2021 - Hotspot dune erosion on an intermediate beach","interactions":[],"lastModifiedDate":"2021-10-01T13:25:35.688431","indexId":"70224627","displayToPublicDate":"2021-09-08T08:21:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Hotspot dune erosion on an intermediate beach","docAbstract":"

A large, low pressure Nor’easter storm and Hurricane Joaquin contributed to multiple weeks of sustained, elevated wave and water level conditions along the southeastern Atlantic coast of the United States in Fall 2015. Sea level anomalies in excess of 1 m and offshore wave heights of up to 4 m were recorded during these storms, as observed at the U.S. Army Corps of Engineers’ Field Research Facility in Duck, NC, USA. In response to these energetic oceanographic conditions, there were highly variable morphologic changes to the dune over short spatial scales (<km) which included a range of responses from vertical dune scarping to no measureable response. The portion of the study area with the largest dune erosion occurred at a location fronted by an abnormally deep nearshore bathymetric feature, which altered surf-zone waves and hydrodynamics. The pre-storm beach and dune topography also varied throughout the study area, additionally influencing the frequency of dune collision and contributing to the spatially variable erosion patterns. This work uses field datasets and numerical modeling tools to investigate the causation of hotspot dune erosion at the Field Research Facility. Three different numerical models were tested against the available data in order to assess model skill at resolving complex spatial dune erosion patterns. The three models successfully reproduce the general spatial trends in alongshore variable responses, although not necessarily the details of profile response or net erosion magnitude. Analysis of the model outputs, in conjunction with the available field data, suggests that the observed hotspot dune erosion is related to a complex combination of both topographic and bathymetric controls on the processes driving dune erosion. Therefore, the most simplistic model tested, which only accounts for alongshore variations in topographic profile details, can only predict hotspot dune erosion in locations where steep beach and/or dune topography is the primary control on collisional dune impacts. The higher fidelity models, which account for feedback effects from subaqueous morphology, are similarly able to predict the locations of maximum hotspot erosion, but are sensitive to beach over-steepening and/or errors in wave runup calculations that can lead to over-prediction of simulated dune erosion. This work highlights that numerous existing tools are capable of identifying the foredune regions at most risk from hotspot erosion, as well as the need for continued research to improve representation of all relevant intra-storm morphodynamic processes.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2021.103998","usgsCitation":"Cohn, N., Brodie, K., Johnson, B., and Palmsten, M.L., 2021, Hotspot dune erosion on an intermediate beach: Coastal Engineering, v. 170, 103998, 21 p., https://doi.org/10.1016/j.coastaleng.2021.103998.","productDescription":"103998, 21 p.","ipdsId":"IP-124727","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":450872,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2021.103998","text":"Publisher Index Page"},{"id":390112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"170","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cohn, Nicholas","contributorId":266145,"corporation":false,"usgs":false,"family":"Cohn","given":"Nicholas","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":824404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brodie, Katherine","contributorId":266146,"corporation":false,"usgs":false,"family":"Brodie","given":"Katherine","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":824405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Bradley","contributorId":266147,"corporation":false,"usgs":false,"family":"Johnson","given":"Bradley","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":824406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palmsten, Margaret L. 0000-0002-6424-2338","orcid":"https://orcid.org/0000-0002-6424-2338","contributorId":239955,"corporation":false,"usgs":true,"family":"Palmsten","given":"Margaret","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":824407,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223889,"text":"70223889 - 2021 - Detrital signals of coastal erosion and fluvial sediment supply during glacio-eustatic sea-level rise, Southern California, USA","interactions":[],"lastModifiedDate":"2021-11-26T17:58:49.478553","indexId":"70223889","displayToPublicDate":"2021-09-08T08:14:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Detrital signals of coastal erosion and fluvial sediment supply during glacio-eustatic sea-level rise, Southern California, USA","docAbstract":"

Coastal erosion, including sea-cliff retreat, represents both an important component of some sediment budgets and a significant threat to coastal communities in the face of rising sea level. Despite the importance of predicting future rates of coastal erosion, few prehistoric constraints exist on the relative importance of sediment supplied by coastal erosion versus rivers with respect to past sea-level change. We used detrital zircon U-Pb geochronology as a provenance tracer of river and deep-sea fan deposits from the Southern California Borderland (United States) to estimate relative sediment contributions from rivers and coastal erosion from late Pleistocene to present. Mixture modeling of submarine canyon and fan samples indicates that detrital zircon was dominantly (55%–86%) supplied from coastal erosion during latest Pleistocene (ca. 13 ka) sea-level rise, with lesser contributions from rivers, on the basis of unique U-Pb age modes relative to local Peninsular Ranges bedrock sources. However, sediment that was deposited when sea level was stable at its highest and lowest points since the Last Glacial Maximum was dominantly supplied by rivers, suggesting decreased coastal erosion during periods of sea-level stability. We find that relative sediment supply from coastal erosion is strongly dependent on climate state, corroborating predictions of enhanced coastal erosion during future sea-level rise.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/G49430.1","usgsCitation":"Sharman, G.R., Covault, J.A., Stockli, D.F., Sickmann, Z., Malkowski, M., and Johnstone, S., 2021, Detrital signals of coastal erosion and fluvial sediment supply during glacio-eustatic sea-level rise, Southern California, USA: Geology, v. 49, no. 12, p. 1501-1505, https://doi.org/10.1130/G49430.1.","productDescription":"5 p.","startPage":"1501","endPage":"1505","ipdsId":"IP-125301","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":450875,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g49430.1","text":"Publisher Index Page"},{"id":389142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Southern California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.43261718749999,\n 32.55607364492026\n ],\n [\n -116.38916015624999,\n 32.55607364492026\n ],\n [\n -116.38916015624999,\n 33.815666308702774\n ],\n [\n -118.43261718749999,\n 33.815666308702774\n ],\n [\n -118.43261718749999,\n 32.55607364492026\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Sharman, Glenn R.","contributorId":196537,"corporation":false,"usgs":false,"family":"Sharman","given":"Glenn","email":"","middleInitial":"R.","affiliations":[{"id":34621,"text":"Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA","active":true,"usgs":false}],"preferred":false,"id":823134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Covault, Jacob A","contributorId":265637,"corporation":false,"usgs":false,"family":"Covault","given":"Jacob","email":"","middleInitial":"A","affiliations":[{"id":54745,"text":"Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX","active":true,"usgs":false}],"preferred":false,"id":823135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stockli, Daniel F. 0000-0001-7652-2129","orcid":"https://orcid.org/0000-0001-7652-2129","contributorId":254375,"corporation":false,"usgs":false,"family":"Stockli","given":"Daniel","email":"","middleInitial":"F.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":823136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sickmann, Zack","contributorId":265638,"corporation":false,"usgs":false,"family":"Sickmann","given":"Zack","email":"","affiliations":[{"id":54746,"text":"Institute for Geophysics, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX","active":true,"usgs":false}],"preferred":false,"id":823137,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Malkowski, Matthew A.","contributorId":221753,"corporation":false,"usgs":false,"family":"Malkowski","given":"Matthew A.","affiliations":[{"id":40415,"text":". Department of Geological Sciences, Stanford University, Stanford CA 94305","active":true,"usgs":false}],"preferred":false,"id":823138,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnstone, Samuel 0000-0002-3945-2499","orcid":"https://orcid.org/0000-0002-3945-2499","contributorId":207545,"corporation":false,"usgs":true,"family":"Johnstone","given":"Samuel","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":823139,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}