The goal of the Louisiana Barrier Island Comprehensive Monitoring (BICM) program is to provide long-term data on coastal Louisiana for monitoring change and assisting in coastal management. This study (carried out under Coastal Protection and Restoration Authority contract number 2000339324, BICM2—Chenier TopoBathy DEM) builds upon the previous BICM physical assessment of the Chenier Plain region using bathymetric data from three periods (1930, 2007, and 2017) to develop digital elevation models for historical and current periods. In addition to bathymetric datasets, the study includes light detection and ranging elevation measurements along the coastline to produce elevation datasets for the 2007 and 2017 periods. This report describes the methods used to acquire, process, and produce these products.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221014","collaboration":"Prepared in cooperation with Coastal Protection and Restoration Authority of Louisiana","programNote":"Louisiana Barrier Island Comprehensive Monitoring Program 2015–2020","usgsCitation":"Flocks, J.G., Forde, A.S., and Bernier, J.C., 2022, Chenier Plain region bathymetric and topographic datasets: Methodology report: U.S. Geological Survey Open-File Report 2022–1014, 21 p., https://doi.org/10.3133/ofr20221014.","productDescription":"vii, 21 p.","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-122902","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":501759,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112530.htm","linkFileType":{"id":5,"text":"html"}},{"id":396683,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1014/ofr20221014.pdf","text":"Report","size":"6.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1014"},{"id":396682,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1014/coverthb.jpg"},{"id":396685,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1014/images/"},{"id":396684,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1014/ofr20221014.XML"},{"id":396704,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221014/full","text":"Report","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Chenier Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.85620117187499,\n 29.439597566602902\n ],\n [\n -92.1258544921875,\n 29.439597566602902\n ],\n [\n -92.1258544921875,\n 29.8\n ],\n [\n -93.85620117187499,\n 29.8\n ],\n [\n -93.85620117187499,\n 29.439597566602902\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
We use a suite of historical earthquakes to quantitatively determine earthquake early warning (EEW) alert threshold strategies for a range of shaking intensity targets for EEW in the U.S. West Coast. The current method for calculating alert regions for the ShakeAlert EEW System does not take into account variabilities and uncertainties in shaking distribution. As a result, if the modified Mercalli intensity (MMI) level used to determine the extent of the alert region (the alert threshold) is the same as the target intensity threshold, the alert region will be too small to include all locations that require alerts even if earthquake source parameters are estimated accurately. Missed alerts can be reduced by using a lower alert threshold than the target threshold. This expands the alert region, increasing the number of precautionary alerts issued to people who experience shaking below the target level. We determine alert thresholds that optimize this tradeoff between missed and precautionary alerts for target thresholds of MMI 4.0-6.0 using a ShakeMap catalog of 143 M5.0-7.3 earthquakes as ground truth. We examine the quality of each alerting strategy relative to the target MMI, where we define alert quality metrics in terms of both the area and population alerted. Optimal alert thresholds maximize correct alerts while limiting most precautionary alerts to regions that are likely to still feel some shaking. We find these optimal alert thresholds also maximize warning times. This analysis presents a quantitative framework ShakeAlert can use to communicate alerting strategies and performance expectations to ShakeAlert users.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EF002515","usgsCitation":"Saunders, J.K., Minson, S.E., and Baltay Sundstrom, A.S., 2022, How low should we alert? Quantifying intensity threshold alerting strategies for earthquake early warning in the United States: Earth's Future, v. 10, no. 3, e2021EF002515, 20 p., https://doi.org/10.1029/2021EF002515.","productDescription":"e2021EF002515, 20 p.","ipdsId":"IP-130454","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":489935,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021ef002515","text":"Publisher Index Page"},{"id":482033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"10","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Saunders, Jessie Kate 0000-0001-5340-6715","orcid":"https://orcid.org/0000-0001-5340-6715","contributorId":290634,"corporation":false,"usgs":true,"family":"Saunders","given":"Jessie","email":"","middleInitial":"Kate","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baltay, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":927334,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229816,"text":"70229816 - 2022 - Identifying factors linked with persistence of reintroduced populations: Lessons learned from 25 years of amphibian translocations","interactions":[],"lastModifiedDate":"2022-03-18T14:39:48.68884","indexId":"70229816","displayToPublicDate":"2022-03-03T09:34:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Identifying factors linked with persistence of reintroduced populations: Lessons learned from 25 years of amphibian translocations","docAbstract":"Conservation translocations are increasingly used to help recover imperiled species. However, success of establishing populations remains low, especially for amphibians. Identifying factors associated with translocation success can help increase efficiency and efficacy of recovery efforts. Since the 1990s, several captive and semi-captive facilities have produced Chiricahua Leopard Frogs (Rana chiricahuensis) to establish or augment wild populations in Arizona and New Mexico, USA. During this same time, personnel associated with several programs surveyed translocation and non-translocation sites for presence of amphibians. We used 25 years (1995–2019) of survey and translocation data for the federally threatened Chiricahua Leopard Frog to identify factors linked with population persistence. Our dataset included approximately 40,642 egg masses or animals translocated in 314 events to 115 distinct sites and > 5800 visual encounter surveys from 641 sites; 120 of these sites were also surveyed with environmental DNA methods in 2018. We used a hierarchical dynamic occupancy model that accounted for imperfect detection to identify patch- and landscape-level attributes associated with site occupancy, and then used predictions from that model to evaluate factors associated with population persistence at translocation sites. Across all sites, extinction probability for Chiricahua Leopard Frogs was higher in lotic (stream) than lentic (pond) habitats and when Western Tiger Salamanders (Ambystoma mavortium) were present. Restoration of sites specifically for frog conservation reduced extinction probability. Colonization of unoccupied sites increased moderately with increasing numbers of translocation sites within 2 km, indicating a benefit of translocation efforts beyond sites where frogs were stocked. At translocation sites, persistence was greater in lentic than lotic habitats and was negatively correlated with the proportion of years tiger salamanders were present. Increasing numbers of translocation events, especially of late-stage larvae, increased persistence. There was little difference in population persistence based on whether stock was from captive, semi-captive, or wild sources, but translocations during the dry season (January—July) succeeded more than those after the typical arrival of summer rains (August—December). Based on the number of years translocation sites were predicted to be occupied, 2 or more translocations produced, on average, a > 4-yr increase in predicted occupancy compared to sites without translocations. While translocations have increased the number of populations across the landscape, continued management of water availability and threats such as invasive predators and disease remain critical to recovery of the Chiricahua Leopard Frog.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02078","usgsCitation":"Hossack, B., Howell, P., Owens, A., Cobos, C., Goldberg, C.S., Hall, D.L., Hedwall, S., MacVean, S., McCaffery, M., McCall, A.H., Mosley, C., Oja, E.B., Rorabaugh, J.C., Sigafus, B., and Sredl, M.J., 2022, Identifying factors linked with persistence of reintroduced populations: Lessons learned from 25 years of amphibian translocations: Global Ecology and Conservation, v. 35, e02078, 22 p., https://doi.org/10.1016/j.gecco.2022.e02078.","productDescription":"e02078, 22 p.","ipdsId":"IP-135486","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":448603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02078","text":"Publisher Index Page"},{"id":397306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.35717773437499,\n 31.325486676506983\n ],\n [\n -106.0400390625,\n 31.325486676506983\n ],\n [\n -106.0400390625,\n 35.10193405724606\n ],\n [\n -112.35717773437499,\n 35.10193405724606\n ],\n [\n -112.35717773437499,\n 31.325486676506983\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":838451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howell, Paige E.","contributorId":173495,"corporation":false,"usgs":false,"family":"Howell","given":"Paige E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":838452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Owens, Audrey K","contributorId":288932,"corporation":false,"usgs":false,"family":"Owens","given":"Audrey K","affiliations":[{"id":61907,"text":"AGFD","active":true,"usgs":false}],"preferred":false,"id":838453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cobos, C","contributorId":288933,"corporation":false,"usgs":false,"family":"Cobos","given":"C","email":"","affiliations":[{"id":38107,"text":"Turner Endangered Species Fund","active":true,"usgs":false}],"preferred":false,"id":838454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldberg, Caren S.","contributorId":76879,"corporation":false,"usgs":false,"family":"Goldberg","given":"Caren","email":"","middleInitial":"S.","affiliations":[{"id":5132,"text":"Washington State University, Pullman","active":true,"usgs":false}],"preferred":false,"id":838455,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hall, David L.","contributorId":222395,"corporation":false,"usgs":false,"family":"Hall","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":838456,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hedwall, Shaula","contributorId":288934,"corporation":false,"usgs":false,"family":"Hedwall","given":"Shaula","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":838457,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"MacVean, Susi","contributorId":288935,"corporation":false,"usgs":false,"family":"MacVean","given":"Susi","email":"","affiliations":[{"id":61907,"text":"AGFD","active":true,"usgs":false}],"preferred":false,"id":838458,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McCaffery, Magnus","contributorId":288936,"corporation":false,"usgs":false,"family":"McCaffery","given":"Magnus","email":"","affiliations":[{"id":38107,"text":"Turner Endangered Species Fund","active":true,"usgs":false}],"preferred":false,"id":838459,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McCall, A. Hunter","contributorId":288937,"corporation":false,"usgs":false,"family":"McCall","given":"A.","email":"","middleInitial":"Hunter","affiliations":[{"id":48661,"text":"Private","active":true,"usgs":false}],"preferred":false,"id":838460,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mosley, C","contributorId":288938,"corporation":false,"usgs":false,"family":"Mosley","given":"C","email":"","affiliations":[{"id":61907,"text":"AGFD","active":true,"usgs":false}],"preferred":false,"id":838461,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Oja, Emily Bea 0000-0002-8621-9665","orcid":"https://orcid.org/0000-0002-8621-9665","contributorId":261164,"corporation":false,"usgs":true,"family":"Oja","given":"Emily","email":"","middleInitial":"Bea","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":838462,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rorabaugh, James C.","contributorId":191978,"corporation":false,"usgs":false,"family":"Rorabaugh","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":838463,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sigafus, Brent H. 0000-0002-7422-8927","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":264740,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":838464,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sredl, Michael J","contributorId":288939,"corporation":false,"usgs":false,"family":"Sredl","given":"Michael","email":"","middleInitial":"J","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":838465,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70229202,"text":"tm6A62 - 2022 - Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6","interactions":[],"lastModifiedDate":"2022-03-03T17:29:27.921518","indexId":"tm6A62","displayToPublicDate":"2022-03-03T09:21:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A62","displayTitle":"Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6","title":"Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6","docAbstract":"This report describes the skeletal storage, compaction and subsidence (CSUB) package of MODFLOW 6. The CSUB package simulates the vertical compaction of compressible sediments and land subsidence. The package simulates groundwater storage changes and elastic compaction in coarse-grained aquifer sediments. The CSUB package also simulates groundwater storage changes and elastic and inelastic compaction in fne-grained, compressible interbeds, or in extensive confning units. The package can account for effective stress-dependent changes in storage properties. The CSUB package can also explicitly account for the contribution of water compressibility to groundwater storage changes.
Compaction of compressible sediments is formulated using Terzaghi’s elastoplastic model and assumes the total compaction is a small fraction of the total initial thickness of compressible sediments. Compaction is controlled by head or pore-pressure changes and overburden stress changes associated with water-table changes, and thus by effective stress changes within coarse-and fne-grained compressible sediments. If the stress in a compressible unit is less than the preconsolidation stress, compaction is elastic (recoverable). If the stress in a compressible sediment is greater than the preconsolidation stress, compaction is inelastic (irrecoverable) and permanent land subsidence occurs.
The propagation of head changes within fne-grained, compressible interbeds is represented numerically using a transient, one-dimensional (vertical) groundwater fow equation. This equation accounts for delayed release of water from storage or uptake of water into storage in the interbeds. Vertical hydraulic conductivity, elastic and inelastic skeletal specifc storage, and interbed thickness control the timing of interbed storage changes. Interbeds that are thin, have a relatively large vertical hydraulic conductivity, or relatively small specifc-storage values equilibrate quickly with heads/pore pressures in surrounding coarse-grained sediments and can be represented as no-delay interbeds that use the simulated groundwater head in a cell to calculate interbed compaction and do not need to be solved numerically using a vertically discretized interbed and the vertical groundwater fow equation.
In addition to the applicability to confned groundwater fow systems, several features of the CSUB package make it applicable to shallow, unconfned groundwater fow systems. Geostatic stress can be treated as a function of water-table elevation, and compaction is a function of computed changes in effective stress. The porosity, void ratio, and thickness of shallow and deep coarse-grained aquifer sediments, fne-grained interbeds, and extensive confning units can vary in time based on calculated strain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A62","usgsCitation":"Hughes, J.D., Leake, S.A., Galloway, D.L., and White, J.T., 2022, Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6: U.S. Geological Survey Techniques and Methods, book 6, chap. A62, 57 p., https://doi.org/10.3133/tm6A62.","productDescription":"Report: vi, 57 p.; Software Release","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114536","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":396667,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A55","text":"Techniques and Methods 6-A55","linkHelpText":"- Documentation for the MODFLOW 6 Groundwater Flow Model"},{"id":396668,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A56","text":"Techniques and Methods 6-A56","linkHelpText":"- Documentation for the “XT3D” option in the Node Property Flow (NPF) Package of MODFLOW 6"},{"id":396669,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A57","text":"Techniques and Methods 6-A57","linkHelpText":"- Documentation for the MODFLOW 6 framework"},{"id":396639,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/a62/coverthb.jpg"},{"id":396642,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/F76Q1VQV","text":"USGS software release","linkHelpText":"- MODFLOW 6: USGS Modular Hydrologic Model"},{"id":396640,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a62/tm6a62.pdf","text":"Report","size":"5.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-A62"},{"id":396641,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A61","text":"Techniques and Methods 6-A61","linkHelpText":"- Documentation for the MODFLOW 6 Groundwater Transport Model"}],"contact":"Director, Integrated Modeling and Prediction Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Dr., MS 411
Reston, VA 20192-0002
This report documents a new Groundwater Transport (GWT) Model for MODFLOW 6. The GWT Model simulates three-dimensional transport of a single chemical species in fowing groundwater based on a generalized control-volume fnite-difference approach. Although each GWT Model is only able to represent a single chemical species, multiple GWT Models may be invoked within a single MODFLOW 6 simulation to represent solute transport of multiple non-interacting chemical species. The GWT Model is designed to work with the Groundwater Flow (GWF) Model for MODFLOW 6, which simulates transient, three-dimensional groundwater fow. The version of the GWT model documented here must use the same spatial discretization used by the GWF Model; however, that spatial discretization can be represented by regular MODFLOW grids consisting of layers, rows, and columns, or by more general unstructured grids. The GWT Model simulates (1) advective transport, (2) the combined hydrodynamic dispersion processes of velocity-dependent mechanical dispersion and molecular diffusion, (3) adsorption and absorption (collectively referred to as sorption) of solutes by the aquifer matrix, (4) transfer between the mobile domain and one or more immobile domains, (5) frst-or zero-order solute decay or production, (6) mixing from groundwater sources and sinks, and (7) direct addition of solute mass. The GWT Model can also represent advective solute transport through advanced package features, such as streams, lakes, multi-aquifer wells, and the unsaturated zone. If the GWF Model application uses the Water Mover (MVR) Package to connect fow packages, then solute transport between these packages can also be represented. The transport processes described in this report have been implemented in a fully implicit manner and are solved in a system of equations using iterative numerical methods. The present version of the GWT Model for MODFLOW 6 does not have an option to calculate steady-state transport solutions; if a steady-state solution is required, then transient evolution of the solute must be represented using multiple time steps until no further changes in solute concentrations are detected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A61","usgsCitation":"Langevin, C.D., Provost, A.M., Panday, Sorab, and Hughes, J.D., 2022, Documentation for the MODFLOW 6 Groundwater Transport Model: U.S. Geological Survey Techniques and Methods, book 6, chap. A61, 56 p., https://doi.org/10.3133/tm6A61.","productDescription":"Report: vi, 56 p.; Software Release","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-120850","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":396637,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A62","text":"Techniques and Methods 6-A62","linkHelpText":"- Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6"},{"id":396666,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A57","text":"Techniques and Methods 6-A57","linkHelpText":"- Documentation for the MODFLOW 6 framework"},{"id":396665,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A56","text":"Techniques and Methods 6-A56","linkHelpText":"- Documentation for the “XT3D” option in the Node Property Flow (NPF) Package of MODFLOW 6"},{"id":396664,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A55","text":"Techniques and Methods 6-A55","linkHelpText":"- Documentation for the MODFLOW 6 Groundwater Flow Model"},{"id":396635,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/a61/coverthb2.jpg"},{"id":396636,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a61/tm6a61.pdf","text":"Report","size":"3.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-A61"},{"id":396638,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/F76Q1VQV","text":"USGS software release","linkHelpText":"- MODFLOW 6: USGS Modular Hydrologic Model"}],"contact":"Director, Integrated Modeling and Prediction Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Dr., MS 411
Reston, VA 20192-0002
Coastal marshes are globally important, carbon dense ecosystems simultaneously maintained and threatened by sea-level rise. Warming temperatures may increase wetland plant productivity and organic matter accumulation, but temperature-modulated feedbacks between productivity and decomposition make it difficult to assess how wetlands and their thick, organic rich soils will respond to climate warming. Here, we actively increased aboveground plant-surface and below-ground soil temperatures in two marsh plant communities, and found that a moderate amount of warming (1.7°C above ambient temperatures) consistently maximized root growth, marsh elevation gain, and below-ground carbon accumulation. Marsh elevation loss observed at higher temperatures was associated with increased carbon mineralization and increased microtopographic heterogeneity, a potential early warning signal of marsh drowning. Maximized elevation and below-ground carbon accumulation for moderate warming scenarios uniquely suggest linkages between metabolic theory of individuals and landscape-scale ecosystem resilience and function, but our work indicates nonpermanent benefits as global temperatures continue to rise.
Deep learning (DL) models can accurately predict many hydrologic variables including streamflow and water temperature; however, these models have typically predicted hydrologic variables independently. This study explored the benefits of modeling two interdependent variables, daily average streamflow and daily average stream water temperature, together using multi-task DL. A multi-task scaling factor controlled the relative contribution of the auxiliary variable's error to the overall loss during training. Our experiments examined the improvement in prediction accuracy of the multi-task approach using paired streamflow and water temperature data from sites across the conterminous United States. Our results showed that for 56 out of 101 sites, the best performing multi-task models performed better overall than the single-task models in terms of Nash-Sutcliffe efficiency for predicting streamflow with single-site models. For 43 sites, the best multi-task, single-site models made no significant difference in predicting streamflow. The multi-task approach had a smaller effect when applied to a model trained with data from 101 sites together, significantly improving performance for only 17 sites. The multi-task scaling factor was consequential in determining to what extent the multi-task approach was beneficial. A naïve selection of this factor led to significantly worse-performing models for 3 of 101 sites when predicting streamflow as the primary variable, and 47 of 53 sites when predicting stream temperature as the primary variable. We conclude that a multi-task approach can make more accurate predictions by leveraging information from interdependent hydrologic variables, but only for some sites, variables, and model configurations.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021WR030138","usgsCitation":"Sadler, J.M., Appling, A.P., Read, J., Oliver, S.K., Jia, X., Zwart, J.A., and Kumar, V., 2022, Multi-task deep learning of daily streamflow and water temperature: Water Resources Research, v. 58, no. 4, e2021WR030138, 18 p., https://doi.org/10.1029/2021WR030138.","productDescription":"e2021WR030138, 18 p.","ipdsId":"IP-129032","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":448611,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021wr030138","text":"Publisher Index Page"},{"id":386338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sadler, Jeffrey Michael 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":260092,"corporation":false,"usgs":true,"family":"Sadler","given":"Jeffrey","email":"","middleInitial":"Michael","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":817231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":817232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":817233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":817235,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":817236,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kumar, Vipin","contributorId":237812,"corporation":false,"usgs":false,"family":"Kumar","given":"Vipin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":817237,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229180,"text":"70229180 - 2022 - Assessing mineral supply concentration from different perspectives through a case study of zinc","interactions":[],"lastModifiedDate":"2022-10-31T14:03:16.051554","indexId":"70229180","displayToPublicDate":"2022-03-02T11:25:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5502,"text":"Mineral Economics","onlineIssn":"2191-2211","printIssn":"2191-2203","active":true,"publicationSubtype":{"id":10}},"title":"Assessing mineral supply concentration from different perspectives through a case study of zinc","docAbstract":"Increasing demand for nonfuel mineral commodities has increased concerns regarding the reliability of their supplies. “Criticality” assessments over the past decade have attempted to capture this concern through a set of indicators, the most common of which quantifies the risk associated with market concentration by applying the Herfindahl-Hirschman Index (HHI) to the world production of a given commodity by country in a given year. Although this approach is useful, it inherently assumes that all of world production is available to the market and is thus potentially at risk. In this analysis, the HHI, as well as HHI weighted by country governance, is calculated for mined and refined zinc using the standard approach of using all world production data and comparing that to the HHI when using the best estimate of what is available to the world market. The results indicate that although the HHI of both mined and refined zinc world production has increased markedly over the past decade, the HHI for what is available to the market for mined and refined zinc has remained relatively constant and low, which is indicative of minimal supply risk. This is mainly owing to the fact that a large and increasing share of the world’s mined and refined zinc production comes from China, but that production supplies domestic consumption as well as small amounts of exports. As a result, the zinc materials that are available to the world market outside of China are produced by a relatively large and diverse set of countries. Although these analyses are specific to zinc, they are likely to be comparable for other commodities of which the largest producers are also the largest consumers and highlight the importance of examining different perspectives in criticality assessments.","language":"English","publisher":"Springer","doi":"10.1007/s13563-021-00291-2","usgsCitation":"Thomas, C.L., Nassar, N.T., and DeYoung, J., 2022, Assessing mineral supply concentration from different perspectives through a case study of zinc: Mineral Economics, v. 35, p. 6067-616, https://doi.org/10.1007/s13563-021-00291-2.","productDescription":"10 p.","startPage":"6067","endPage":"616","ipdsId":"IP-101409","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":448614,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13563-021-00291-2","text":"Publisher Index Page"},{"id":396657,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","noUsgsAuthors":false,"publicationDate":"2022-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, Christine L. 0000-0002-1391-6072","orcid":"https://orcid.org/0000-0002-1391-6072","contributorId":287564,"corporation":false,"usgs":false,"family":"Thomas","given":"Christine","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":836874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":197864,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","middleInitial":"T.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":836875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeYoung, John H. Jr. jdeyoung@usgs.gov","contributorId":190728,"corporation":false,"usgs":true,"family":"DeYoung","given":"John H.","suffix":"Jr.","email":"jdeyoung@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":836925,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228690,"text":"gip213 - 2022 - Visit the U.S. Geological Survey's National Water Dashboard","interactions":[],"lastModifiedDate":"2022-03-03T11:54:44.829334","indexId":"gip213","displayToPublicDate":"2022-03-02T11:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"213","displayTitle":"Visit the U.S. Geological Survey’s National Water Dashboard","title":"Visit the U.S. Geological Survey's National Water Dashboard","docAbstract":"The U.S. Geological Survey National Water Dashboard supplies critical information to decision makers, emergency managers, and the public during extreme hydrologic events (such as droughts and floods) and during normal hydrologic conditions. It informs decision making that can help protect lives and property before and during extreme hydrologic events. The National Water Dashboard draws upon the extensive site-specific hydrologic data housed in the U.S. Geological Survey National Water Information System database (https://doi.org/10.5066/F7P55KJN) and also links to the U.S. Geological Survey WaterAlert system, which provides users with instant and customized updates about water conditions. Overall, the National Water Dashboard is part of the U.S. Geological Survey's effort to respond to 21st century science needs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip213","usgsCitation":"Miller, M.P., Burley, T.E., and McCallum, B.E., 2022, Visit the U.S. Geological Survey's National Water Dashboard: U.S. Geological Survey General Information Product 213, 2 p., https://doi.org/10.3133/gip213.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-127330","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"links":[{"id":396097,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/213/coverthb.jpg"},{"id":396098,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/213/gip213.pdf","text":"Report","size":"319 KB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 213"}],"contact":"Associate Director, Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The U.S. Geological Survey National Water Dashboard supplies critical information to decision makers, emergency managers, and the public during extreme hydrologic events (such as droughts and floods) and during normal hydrologic conditions. It informs decision making that can help protect lives and property before and during extreme hydrologic events. The National Water Dashboard draws upon the extensive site-specific hydrologic data housed in the U.S. Geological Survey National Water Information System database (https://doi.org/10.5066/F7P55KJN) and also links to the U.S. Geological Survey WaterAlert system, which provides users with instant and customized updates about water conditions. Overall, the National Water Dashboard is part of the U.S. Geological Survey's effort to respond to 21st century science needs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223003","usgsCitation":"Miller, M.P., Burley, T.E., and McCallum, B.E., 2022, Water priorities for the Nation—The USGS National Water Dashboard: U.S. Geological Survey Fact Sheet 2022–3003, 2 p., https://doi.org/10.3133/fs20223003.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-127299","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"links":[{"id":396067,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3003/coverthb2.jpg"},{"id":501482,"rank":4,"type":{"id":36,"text":"NGMDB Index 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U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Hydroclimate on ‘Uvea (Wallis et Futuna) is controlled by rainfall associated with the South Pacific Convergence Zone (SPCZ), the southern hemisphere's largest precipitation feature. To extend the short observational precipitation record, the hydrogen isotopic composition of the algal lipid biomarker dinosterol (δ2Hdinosterol) was measured in sediment cores from two volcanic crater lakes on ‘Uvea. The modern lakes differ morphologically and chemically but both contain freshwater within the photic zone, support phytoplankton communities inclusive of dinosterol-producing dinoflagellates, and experience identical climate conditions. δ2Hdinosterol values track lake water isotope ratios, ultimately controlled in the tropics by precipitation amount and evaporative enrichment. However, in 88-m-deep Lac Lalolalo a steadily decreasing trend in sedimentary δ2Hdinosterol values from −227‰ around year 988 CE to modern values as low as −303‰, suggests this lake's evolution from an active volcanic setting to the present system strongly influenced δ2Hdinosterol values. Although current hydrology and water isotope systematics may now reflect precipitation and evaporation in this lake, the interaction between these processes and large changes in basin morphology, geochemistry, and hydrology obstruct the recovery of a climate signal from Lac Lalolalo's sedimentary δ2Hdinosterol records. This work emphasizes the importance of site replication and the use of complementary climate reconstruction tools, especially when using molecular proxies that may be sensitive to more than one environmental parameter. Contrary to its neighbor, duplicate δ2Hdinosterol records from 23-m-deep Lac Lanutavake varied between −277‰ and −297‰ and indicate slightly drier conditions during the time-period known as the Medieval Climate Anomaly (MCA, 950–1250 CE). The δ2Hdinosterol signal in Lac Lanutavake was muted compared to published records from ‘Upolu (Samoa) and Efate (Vanuatu) indicating that ‘Uvea's location is not as sensitive to precipitation variability at sites farther from the SPCZ central axis. Lithogenic runoff proxies combined with δ2Hdinosterol support the interpretation of a relatively dry MCA on ‘Uvea, ‘Upolu, and Efate, potentially due to less intense precipitation, a contracted, or a more zonally oriented SPCZ.
The endangered mountain yellow-legged frog (Rana muscosa) has been reduced to <10 isolated populations in the wild. Due to frequent catastrophic events (floods, droughts, wildfires), the recent dynamics of these populations have been erratic, making the future of the species highly uncertain. In 2018, a recovery plan was developed to improve the species status by reducing the impacts of various threats (predation, disease, habitat destruction), as well as reinforcing wild populations through the reintroduction of captive-bred frogs. The short-term goal stated in this plan was to reach a minimum of 20 populations of 50 adults each (hereafter, the 20/50 target), before the species can be considered for downlisting from the U.S. Endangered Species Act. However, there is no guarantee that this 20/50 target will be sufficient to ensure the species persistence in the long run. Using 19 years of mark-recapture data, we estimated populations' demographic trends and assessed the viability of R. muscosa from a starting state of 20 populations of 50 adults each (i.e., the downlisting criteria). Our results reveal that, from this 20/50 state, the species has high chances of persistence only at a short time horizon (50 years). Moreover, >80% of populations would be extinct 50 years later. Therefore, the species will not be able to persist without implementation of the reintroduction program. We found that it is more important to increase the number of suitable sites occupied by R. muscosa than to simply reinforce or augment existing populations. Expanding the current distribution by establishing new populations at suitable sites, even after the “20 populations” mark has been reached, would increase the likelihood of the species' persistence in the longer term.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.12666","usgsCitation":"Chambert, T., Backlin, A.R., Gallegos, E., Baskerville-Bridges, B., and Fisher, R., 2022, Defining relevant conservation targets for the endangered Southern California distinct population segment of the mountain yellow-legged frog (Rana muscosa): Conservation Science and Practice, v. 4, no. 5, e12666, 10 p., https://doi.org/10.1111/csp2.12666.","productDescription":"e12666, 10 p.","ipdsId":"IP-136151","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":448619,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.12666","text":"Publisher Index Page"},{"id":397864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Palomar Mountain, San Bernardino Mountains, San Gabriel Mountains, San Jacinto Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.795166015625,\n 33.95247360616282\n ],\n [\n -116.49902343749999,\n 33.95247360616282\n ],\n [\n -116.49902343749999,\n 34.45674800347809\n ],\n [\n -118.795166015625,\n 34.45674800347809\n ],\n [\n -118.795166015625,\n 33.95247360616282\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.99615478515624,\n 33.35347332342168\n ],\n [\n -116.37268066406249,\n 33.35347332342168\n ],\n [\n -116.37268066406249,\n 33.95475186857191\n ],\n [\n -116.99615478515624,\n 33.95475186857191\n ],\n [\n -116.99615478515624,\n 33.35347332342168\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.96319580078125,\n 33.169743600216165\n ],\n [\n -116.74621582031249,\n 33.169743600216165\n ],\n [\n -116.74621582031249,\n 33.35347332342168\n ],\n [\n -116.96319580078125,\n 33.35347332342168\n ],\n [\n -116.96319580078125,\n 33.169743600216165\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-03-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Chambert, Thierry 0000-0002-9450-9080 tchambert@usgs.gov","orcid":"https://orcid.org/0000-0002-9450-9080","contributorId":191979,"corporation":false,"usgs":false,"family":"Chambert","given":"Thierry","email":"tchambert@usgs.gov","affiliations":[],"preferred":false,"id":839217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Backlin, Adam R. 0000-0001-5618-8426 abacklin@usgs.gov","orcid":"https://orcid.org/0000-0001-5618-8426","contributorId":3802,"corporation":false,"usgs":true,"family":"Backlin","given":"Adam","email":"abacklin@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":839218,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gallegos, Elizabeth 0000-0002-8402-2631 egallegos@usgs.gov","orcid":"https://orcid.org/0000-0002-8402-2631","contributorId":1528,"corporation":false,"usgs":true,"family":"Gallegos","given":"Elizabeth","email":"egallegos@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":839219,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baskerville-Bridges, Bradd","contributorId":289523,"corporation":false,"usgs":false,"family":"Baskerville-Bridges","given":"Bradd","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":839220,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":839221,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228943,"text":"sir20215086 - 2022 - Hydrogeology of aquifers within the Fairport-Lyons channel system and adjacent areas in Wayne, Ontario, and Seneca Counties, New York","interactions":[],"lastModifiedDate":"2026-04-02T19:34:37.460842","indexId":"sir20215086","displayToPublicDate":"2022-03-02T10:40:00","publicationYear":"2022","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":"2021-5086","displayTitle":"Hydrogeology of Aquifers Within the Fairport-Lyons Channel System and Adjacent Areas in Wayne, Ontario, and Seneca Counties, New York","title":"Hydrogeology of aquifers within the Fairport-Lyons channel system and adjacent areas in Wayne, Ontario, and Seneca Counties, New York","docAbstract":"A hydrogeologic investigation was undertaken by the U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation, within the areas shown in the Macedon, Palmyra, Newark, and Lyons 7.5-minute quadrangle maps that include parts of Wayne, Ontario, and Seneca Counties in New York. The most productive zone of aquifers within the study area is associated with the Fairport-Lyons glacial-stream channel (hereinafter referred to as the “Fairport-Lyons channel”) in southern Wayne County and adjacent areas. The Fairport-Lyons channel is a west-east-oriented bedrock channel that once served as the outlet for glacial Lake Dawson, which occupied the Genesee Valley near Rochester during the Pleistocene. The Fairport-Lyons channel and intersecting subsidiary channels are hereinafter referred to as the “Fairport-Lyons channel system.” Glacial meltwater eroded this shallow channel network into the underlying bedrock, and the channels subsequently filled with interlayered glaciofluvial sand and gravel and fine-grained lacustrine deposits. These sand and gravel deposits provide the only large supplies of groundwater in Wayne County under unconfined and confined conditions and serve a population of over 20,000 through a combination of domestic and municipal water supply wells. The largest reported well yield, 1,200 gallons per minute, is from an industrial supply well near Newark, N.Y. Much of the sand and gravel within the Fairport-Lyons channel system is generally thinly saturated; however, in three areas—near Macedon, Newark, and Lyons, N.Y.—the saturated thickness of the aquifer is sufficient to support groundwater yields adequate for municipal and industrial use, in part because of induced infiltration from the Erie Canal.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215086","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Reynolds, R.J., Heisig, P.M., and Linsey, K.S., 2022, Hydrogeology of aquifers within the Fairport-Lyons channel system and adjacent areas in Wayne, Ontario, and Seneca Counties, New York: U.S. Geological Survey Scientific Investigations Report 2021–5086, 15 p., 2 pls., https://doi.org/10.3133/sir20215086.","productDescription":"Report v, 15 p.; 2 Plates: 36.00 x 24.00 inches and 36.00 x 60.00 inches; Data Release","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070043","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":502111,"rank":9,"type":{"id":36,"text":"NGMDB Index 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New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Understanding recruitment dynamics is an essential part of effective fisheries management, whether the focus is on conservation, harvest policy development, or invasive species control. We developed a model that estimates lake-wide Ricker stock-recruitment relations for invasive sea lampreys (Petromyzon marinus) in each of the five Laurentian Great Lakes to inform future control efforts. We fit adult-to-adult models, taking advantage of a long time series of lake-wide, adult, sea lamprey abundance estimates. We incorporated proportional contributions at age for the stock as well as additional explanatory variables sea lamprey weight, as a surrogate for fecundity, and lampricide quantity applied, as a surrogate for anthropogenic mortality, to explain residual recruitment variability. The best model incorporated equal cohort contributions from the adult stock (that matured 5, 6, and 7 years prior to recruitment), a single productivity parameter (
Glen Torridon is a topographic trough located on the slope of Aeolis Mons, Gale crater, Mars. It corresponds to what was previously referred to as the “clay-bearing unit”, due to the relatively strong spectral signatures of clay minerals (mainly ferric smectites) detected from orbit. Starting in January 2019, the Curiosity rover explored Glen Torridon for more than 700 sols (Martian days). The objectives of this campaign included acquiring a detailed understanding of the geologic context in which the clay minerals were formed and determining the intensity of aqueous alteration experienced by the sediments. Here, we present the major-element geochemistry of the bedrock as analyzed by the ChemCam instrument. Our results reveal that the two main types of bedrock exposures identified in the lower part of Glen Torridon are associated with distinct chemical compositions (K-rich and Mg-rich), for which we are able to propose mineralogical interpretations. Moreover, the topmost stratigraphic member exposed in the region displays a stronger diagenetic overprint, especially at two locations close to the unconformable contact with the overlying Stimson formation, where the bedrock composition significantly deviates from the rest of Glen Torridon. Overall, the values of the Chemical Index of Alteration determined with ChemCam are elevated by Martian standards, suggesting the formation of clay minerals through open system weathering. However, there is no indication that the alteration was stronger than in some terrains previously visited by Curiosity, which in turn implies that the enhanced orbital signatures are mostly controlled by non-compositional factors.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JE007103","usgsCitation":"Dehouck, E., Cousin, A., Mangold, N., Frydenvang, J., Gasnault, O., Forni, O., Rapin, W., Gasda, P.J., Caravaca, G., David, G., Bedford, C.C., Lasue, J., Meslin, P., Rammelkamp, K., Desjardins, M., Le Mouelic, S., Thorpe, M.T., Fox, V.K., Bennett, K.A., Bryk, A., Lanza, N.L., Maurice, S., and Wiens, R.C., 2022, Bedrock geochemistry and alteration history of the clay-bearing Glen Torridon region of Gale crater, Mars: Journal of Geophysical Research E: Planets, v. 127, no. 12, e2021JE007103, 29 p., https://doi.org/10.1029/2021JE007103.","productDescription":"e2021JE007103, 29 p.","ipdsId":"IP-134173","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":448627,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021je007103","text":"External 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William","contributorId":172305,"corporation":false,"usgs":false,"family":"Rapin","given":"William","email":"","affiliations":[{"id":27023,"text":"Institut de Recherche en Astrophysique et Planétologie","active":true,"usgs":false}],"preferred":false,"id":885087,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gasda, Patrick J.","contributorId":196313,"corporation":false,"usgs":false,"family":"Gasda","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":885088,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Caravaca, Gwenael","contributorId":293561,"corporation":false,"usgs":false,"family":"Caravaca","given":"Gwenael","email":"","affiliations":[{"id":63327,"text":"University Copenhagen","active":true,"usgs":false}],"preferred":false,"id":885089,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"David, 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Mouelic","given":"Stephane","affiliations":[],"preferred":false,"id":885096,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Thorpe, Michael T.","contributorId":261804,"corporation":false,"usgs":false,"family":"Thorpe","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":53022,"text":"Jacobs Technology","active":true,"usgs":false}],"preferred":false,"id":885097,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Fox, Valerie K.","contributorId":167652,"corporation":false,"usgs":false,"family":"Fox","given":"Valerie","email":"","middleInitial":"K.","affiliations":[{"id":24730,"text":"Department of Earth and Planetary Sciences, Washington University in St. Louis","active":true,"usgs":false}],"preferred":false,"id":885098,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Bennett, Kristen A. 0000-0001-8105-7129","orcid":"https://orcid.org/0000-0001-8105-7129","contributorId":237068,"corporation":false,"usgs":true,"family":"Bennett","given":"Kristen","email":"","middleInitial":"A.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":885099,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Bryk, Alexander","contributorId":237065,"corporation":false,"usgs":false,"family":"Bryk","given":"Alexander","email":"","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":885100,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Lanza, Nina L.","contributorId":140299,"corporation":false,"usgs":false,"family":"Lanza","given":"Nina","email":"","middleInitial":"L.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":885101,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Maurice, Sylvestre","contributorId":82626,"corporation":false,"usgs":false,"family":"Maurice","given":"Sylvestre","email":"","affiliations":[],"preferred":false,"id":885102,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Wiens, Roger C.","contributorId":140330,"corporation":false,"usgs":false,"family":"Wiens","given":"Roger","email":"","middleInitial":"C.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":885103,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70270788,"text":"70270788 - 2022 - Brook Floater restoration: Identifying locations to reintroduce or augment populations with propagated mussels","interactions":[],"lastModifiedDate":"2025-08-28T14:09:03.594606","indexId":"70270788","displayToPublicDate":"2022-03-02T09:01:08","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"CSS-141-2022","title":"Brook Floater restoration: Identifying locations to reintroduce or augment populations with propagated mussels","docAbstract":"In February 2020, we held a workshop where we sought to identify where states should reintroduce or augment brook floater to minimize the probability of extinction within a state. We focused on Massachusetts and Connecticut, two states with only a few, small populations still extant, that likely need population restoration to prevent statewide extirpation. We identified that restoration actions aimed at redundancy (number of populations), representation (number of occupied basins), and resiliency (population size) were constrained by resource availability such as limited broodstock , staff time, and budgets. Optimal restoration locations depended on habitat conditions, the status (viability) of nearby mussel populations, population size (number of individuals), and the location within watersheds; all important considerations in addressing population persistence. Restoration actions also accounted for the risk of disease transmission among mussels and fish, and the genetic health and diversity of mussel populations. The workshop identified the multiple, compounding uncertainties related to population restoration, identified information gaps critical to decision making, and charted a path forward to make decisions given uncertainties. The optimization approach developed can be used to select specific watersheds for restoration in any state, province, or region and can easily be adapted as new information becomes available.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/css40468057","usgsCitation":"Roy, A.H., Bjerre, E., Cummings, J., Kalasz, K., Carmignani, J., Hazelton, P., Kern, M., Perkins, D., Saucier, L., Skorupa, A., Katz, R., and Coghlan, C.C., 2022, Brook Floater restoration: Identifying locations to reintroduce or augment populations with propagated mussels: Cooperator Science Series CSS-141-2022, ii, 18 p., https://doi.org/10.3996/css40468057.","productDescription":"ii, 18 p.","ipdsId":"IP-126392","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":494993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, 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Resources","active":true,"usgs":false}],"preferred":false,"id":947068,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kalasz, Kevin","contributorId":7121,"corporation":false,"usgs":true,"family":"Kalasz","given":"Kevin","affiliations":[],"preferred":false,"id":947069,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carmignani, Jason","contributorId":360465,"corporation":false,"usgs":false,"family":"Carmignani","given":"Jason","affiliations":[{"id":86008,"text":"Natural Heritage and Endangered Species Program","active":true,"usgs":false}],"preferred":false,"id":947070,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hazelton, Peter","contributorId":360449,"corporation":false,"usgs":false,"family":"Hazelton","given":"Peter","affiliations":[{"id":51525,"text":"Massachusetts Division of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":947071,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kern, Morgan","contributorId":360453,"corporation":false,"usgs":false,"family":"Kern","given":"Morgan","affiliations":[{"id":86005,"text":"SC Division of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":947072,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Perkins, David","contributorId":202066,"corporation":false,"usgs":true,"family":"Perkins","given":"David","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":947073,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Saucier, Laura","contributorId":360455,"corporation":false,"usgs":false,"family":"Saucier","given":"Laura","affiliations":[{"id":62986,"text":"Connecticut Department of Energy and Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":947074,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Skorupa, Ayla J.","contributorId":340492,"corporation":false,"usgs":false,"family":"Skorupa","given":"Ayla J.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":947075,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Katz, Rachel","contributorId":201422,"corporation":false,"usgs":false,"family":"Katz","given":"Rachel","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":947076,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Coghlan, Christy C.","contributorId":360458,"corporation":false,"usgs":false,"family":"Coghlan","given":"Christy","middleInitial":"C.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":947077,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70232562,"text":"70232562 - 2022 - An efficient, analytic solution using order statistics for probabilistic seismic‐hazard assessment without the Poisson assumption","interactions":[],"lastModifiedDate":"2022-07-07T11:46:57.706851","indexId":"70232562","displayToPublicDate":"2022-03-02T06:44:07","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"An efficient, analytic solution using order statistics for probabilistic seismic‐hazard assessment without the Poisson assumption","docAbstract":"Standard approaches to probabilistic seismic‐hazard assessment (PSHA) assume that earthquakes are random, independent events that follow a Poisson distribution of occurrences in a given time period (Cornell, 1968). To overcome the limitations of the Poisson assumption, such as ignoring earthquake clustering, we introduce an analytic method for PSHA that uses order statistics to allow for arbitrary distributions of earthquake occurrence. Cornell (1968) used the Poisson assumption to achieve a computationally efficient method that enables users to explore the impact of parameters used in earthquake occurrence and ground‐motion models. We apply our order statistics method to the highly clustered seismicity associated with caldera collapses at Kīlauea and explore the general implications of non‐Poisson behavior for PSHA. We find that non‐Poisson behavior has the greatest impact for high probabilities of exceedance, low‐mean rates of occurrence, and multiple exceedances. Those conditions can be important for applications such as operating standards for buildings and infrastructure engineering, standards for temporary structures and during construction, the insurance industry, the design of earthquake early warning, and to assess hazards due to clustered processes such as aftershock sequences and earthquake swarms. The commonly used rate of exceedance hides the difference between the hazard due to a non‐Poisson distribution and a Poisson distribution with the same mean rate of earthquakes. Thus, including non‐Poisson behavior in PSHA means that we must plot and discuss PSHA results as the probability and not the rate of exceedance.
In arid and semiarid environments, evapotranspiration (ET) is the primary discharge component in the water balance, with potential ET exceeding precipitation. For this reason, reliable estimates of ET are needed to construct accurate water budgets in these environments. Remote sensing affords the ability to provide fast, accurate, field-scale ET estimates, but these methods have largely been restricted to deep rooted (phreatophytic) plant communities underlain by shallow groundwater. We used 13 years of data from a 3-ha drainage lysimeter in a semiarid sagebrush steppe and Landsat normalized difference vegetation index (NDVI) data to calibrate a generalized least squares model capable of predicting vadose zone ET in a high elevation upland ecosystem. Annual precipitation was the best predictor of annual ET, as they were nearly balanced every year analysed (mean difference = 3 mm). We incorporated reference crop ET and a linear combination of NDVI and precipitation to capably predict ET on a subannual, lag-determined interval of 48 days, with a mean error of only 9.92% across all observations. To our knowledge, this is the first vegetation index-ET algorithm calibrated in a semiarid upland plant community using field-scale lysimetry. Vadose zone ET is particularly important at waste disposal sites in the Desert Southwest, where accurate and spatially explicit ET estimates are needed for monitoring potential mobilization and transport of contaminants past the root zone into local aquifers and for monitoring and modelling effects of recharge on flow and transport of contaminants in underlying aquifers.
The National Energy Technology Laboratory, the Japan Oil, Gas and Metals National Corporation, and the U.S. Geological Survey are leading an effort to conduct an extended gas hydrate production test in northern Alaska. The proposed production test required the drilling of an initial stratigraphic test well (STW) to confirm the geologic conditions of the proposed test site. This well was completed in January 2019 in cooperation with the Prudhoe Bay Unit Working Interest Owners. The Prudhoe Bay Unit Hydrate-01 STW was spudded on 10-December-2018. Downhole data acquisition was completed on 25-December-2018, and the rig was released on 01-January-2019. The Hydrate-01 STW was drilled in two sections, including the surface hole that was drilled to a depth of 2248 ft measured depth (MD) (685 m MD) and cased, and the production hole section that was drilled to a depth of 3558 ft MD (1084 m MD) and also cased. A thermally chilled mineral-oil-based mud was used in the main (production) hole section of the well to maintain wellbore stability and quality of the wellbore acquired data. The primary wellbore data were acquired using logging-while-drilling tools. A sidewall pressure core system was also deployed to gather grain size and other data needed for the design of the future production test wells. In addition to confirming the geologic conditions at the test site, the Hydrate-01 STW was designed to serve as a monitoring well during future field operations. Therefore, two sets of fiber-optic cables, each including a bundled distributed acoustic sensor (DAS) and a distributed temperature sensor (DTS), were clamped to the outside of the production casing and cemented in place. In March 2019, the project team acquired three-dimensional (3D) DAS vertical seismic profiling data in the Hydrate-01 STW. Temperature surveys were also acquired with the DTS as deployed in the Hydrate-01 STW during the completion of the well and nearly continuously since March-2019.
U.S. coastal economies and communities are facing an unprecedented and growing number of impacts to coastal ecosystems including beach and fishery closures, harmful algal blooms, loss of critical habitat, as well as shoreline damage. This paper synthesizes our present understanding of the dynamics of human and ecosystem health in coastal systems with a focus on the need to better understand nearshore physical process interactions with coastal pollutants and ecosystems (e.g. fate and transport, circulation, depositional environment, climate change). It is organized around two major topical areas and six subtopic areas: 1) Identifying and mitigating coastal pollutants, including fecal pollution, nutrients and harmful algal blooms, and microplastics; and 2) Resilient coastal ecosystems, which focuses on coastal fisheries, shellfish and natural and nature-based features (NNBF). Societal needs and the tools and technologies needed to address them are discussed for each subtopic. Recommendations for scientific research, observations, community engagement, and policies aim to help prioritize future research and investments. A better understanding of coastal physical processes and interactions with coastal pollutants and resilient ecosystems (e.g. fate and transport, circulation, depositional environment, climate change) is a critical need. Other research recommendations include the need to quantify potential threats to human and ecosystem health through accurate risk assessments and to quantify the resulting hazard risk reduction of natural and nature-based features; improve pollutant and ecosystem impacts forecasting by integrating frequent and new data points into existing and novel models; collect environmental data to calibrate and validate models to predict future impacts on coastal ecosystems and their evolution due to anthropogenic stressors (land-based pollution, overfishing, coastal development), climate change, and sea level rise; and develop lower cost and rapid response tools to help coastal managers better respond to pollutant and ecosystem threats.
","language":"English","publisher":"American Shore and Beach Preservation Association (ASBPA)","doi":"10.34237/1009018","usgsCitation":"Elko, N., Foster, D., Kleinheinz, G., Raubenheimer, B., Brander, S., Kinzelman, J., Kritzer, J.P., Munroe, D., Storlazzi, C.D., Sutula, M., Mercer, A., Coffin, S., Fraioli, C., Ginger, L., Morrison, E., Parent-Doliner, G., Akan, C., Canestrelli, A., DiBenedetto, M., Lang, J., and Simm, J., 2022, Human and ecosystem health in coastal systems: Shore and Beach, v. 90, no. 1, p. 64-91, https://doi.org/10.34237/1009018.","productDescription":"28 p.","startPage":"64","endPage":"91","ipdsId":"IP-137023","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":396764,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-02-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Elko, Nicole","contributorId":287920,"corporation":false,"usgs":false,"family":"Elko","given":"Nicole","affiliations":[{"id":61663,"text":"American Shore and Beach Preservation Association","active":true,"usgs":false}],"preferred":false,"id":837196,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster, Diane","contributorId":194421,"corporation":false,"usgs":false,"family":"Foster","given":"Diane","affiliations":[],"preferred":false,"id":837197,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kleinheinz, Gregory","contributorId":287921,"corporation":false,"usgs":false,"family":"Kleinheinz","given":"Gregory","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":837198,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Raubenheimer, Britt","contributorId":194340,"corporation":false,"usgs":false,"family":"Raubenheimer","given":"Britt","email":"","affiliations":[],"preferred":false,"id":837199,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brander, Suzanne","contributorId":287922,"corporation":false,"usgs":false,"family":"Brander","given":"Suzanne","email":"","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":837200,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kinzelman, Julie","contributorId":207713,"corporation":false,"usgs":false,"family":"Kinzelman","given":"Julie","affiliations":[{"id":37612,"text":"City of Racine Health Department","active":true,"usgs":false}],"preferred":false,"id":837201,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kritzer, Jacob P.","contributorId":287923,"corporation":false,"usgs":false,"family":"Kritzer","given":"Jacob","email":"","middleInitial":"P.","affiliations":[{"id":61666,"text":"Northeastern Regional Association of Coastal Ocean Observing Systems","active":true,"usgs":false}],"preferred":false,"id":837202,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Munroe, Daphne","contributorId":268069,"corporation":false,"usgs":false,"family":"Munroe","given":"Daphne","email":"","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":837203,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":837204,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sutula, Marta","contributorId":287924,"corporation":false,"usgs":false,"family":"Sutula","given":"Marta","affiliations":[{"id":13211,"text":"Southern California Coastal Water Research Project Authority","active":true,"usgs":false}],"preferred":false,"id":837205,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mercer, Annie","contributorId":287925,"corporation":false,"usgs":false,"family":"Mercer","given":"Annie","email":"","affiliations":[{"id":61663,"text":"American Shore and Beach Preservation Association","active":true,"usgs":false}],"preferred":false,"id":837206,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Coffin, Scott","contributorId":287926,"corporation":false,"usgs":false,"family":"Coffin","given":"Scott","email":"","affiliations":[{"id":12702,"text":"California State Water Resources Control Board","active":true,"usgs":false}],"preferred":false,"id":837207,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Fraioli, Carolyn","contributorId":287927,"corporation":false,"usgs":false,"family":"Fraioli","given":"Carolyn","email":"","affiliations":[{"id":61667,"text":"New York State Department of State","active":true,"usgs":false}],"preferred":false,"id":837208,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Ginger, Luke","contributorId":287928,"corporation":false,"usgs":false,"family":"Ginger","given":"Luke","email":"","affiliations":[{"id":61668,"text":"Heal the Bay","active":true,"usgs":false}],"preferred":false,"id":837209,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Morrison, Elise","contributorId":287929,"corporation":false,"usgs":false,"family":"Morrison","given":"Elise","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":837210,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Parent-Doliner, Gabrielle","contributorId":287930,"corporation":false,"usgs":false,"family":"Parent-Doliner","given":"Gabrielle","email":"","affiliations":[{"id":61669,"text":"Water Rangers","active":true,"usgs":false}],"preferred":false,"id":837211,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Akan, Cigdem","contributorId":287931,"corporation":false,"usgs":false,"family":"Akan","given":"Cigdem","email":"","affiliations":[{"id":61670,"text":"University of Northern Florida","active":true,"usgs":false}],"preferred":false,"id":837212,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Canestrelli, Alberto","contributorId":287932,"corporation":false,"usgs":false,"family":"Canestrelli","given":"Alberto","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":837213,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"DiBenedetto, Michelle","contributorId":287933,"corporation":false,"usgs":false,"family":"DiBenedetto","given":"Michelle","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":837214,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Lang, Jackelyn","contributorId":287934,"corporation":false,"usgs":false,"family":"Lang","given":"Jackelyn","email":"","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":837215,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Simm, Jonathan","contributorId":287935,"corporation":false,"usgs":false,"family":"Simm","given":"Jonathan","email":"","affiliations":[{"id":61671,"text":"H.R. Wallingford","active":true,"usgs":false}],"preferred":false,"id":837216,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70262486,"text":"70262486 - 2022 - Northern long-eared bats in the central Appalachians following white-nose syndrome: Failed maternity colonies?","interactions":[],"lastModifiedDate":"2025-01-23T21:34:17.142001","indexId":"70262486","displayToPublicDate":"2022-03-01T15:33:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3909,"text":"Journal of the Southeastern Association of Fish and Wildlife Agencies","active":true,"publicationSubtype":{"id":10}},"title":"Northern long-eared bats in the central Appalachians following white-nose syndrome: Failed maternity colonies?","docAbstract":"Northern long-eared bat (Myotis septentrionalis) populations have experienced severe declines in eastern North America from white-nose syndrome (WNS), yet potential secondary effects on maternity roosting and recruitment remain largely unknown. We documented female day- roosting at two locations in the central Appalachians of Virginia, Back Creek Mountain (BCM) and Rapidan Camp (RC), during 2015 and 2016, ap- proximately six years after the regional onset of WNS. We compared roost characteristics with available trees and roosts recorded prior to WNS at the Fernow Experimental Forest (FEF), West Virginia, in 2007 and 2008. Roosts at BCM were smaller than pre-WNS roosts but were otherwise similar in terms of stand condition and species use, though bats selected for red maple (Acer rubrum) at BCM rather than black locust (Robinia pseudoacacia) as at FEF. At RC, bats roosted almost exclusively in large eastern hemlock (Tsuga canadensis) snags (dbh x¯ = 50.13 cm, SD = 23.1) with high solar exposure that had been killed by the hemlock woolly adelgid (Adelges tsugae). The two observed strategies, selection of smaller, midstory trees at BCM and of dominant, exposed roosts at RC, correspond with pre-WNS observations of female northern long-eared bat roost use at similar sites. However, our re- sults suggest reliance on smaller roosts and canopy-dominant positions that better accommodate solitary individuals and small groups associated with smaller post-WNS colonies in terms of space and thermoregulatory benefits. Despite some observations of pregnant and lactating individuals, all three post-WNS colonies vacated roost networks in early June, and we observed no juveniles. Potential colony failure at BCM and RC is consistent with pre- dicted secondary physiological effects from WNS-induced population collapses, suggesting, if recruitment failed, northern long-eared bats may already be functionally extirpated in portions of the central Appalachians.
","language":"English","publisher":"Southeastern Association of Fish and Wildlife Agencies","usgsCitation":"Kalen, N., Muthersbaugh, M.S., Johnson, J., Silvis, A., and Ford, W., 2022, Northern long-eared bats in the central Appalachians following white-nose syndrome: Failed maternity colonies?: Journal of the Southeastern Association of Fish and Wildlife Agencies, v. 9, p. 159-167.","productDescription":"9 p.","startPage":"159","endPage":"167","ipdsId":"IP-131875","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480719,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://seafwa.org/journal/2022/northern-long-eared-bats-central-appalachians-following-white-nose-syndrome-failed","linkFileType":{"id":5,"text":"html"}},{"id":481111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.33428751101353,\n 39.425222908113994\n ],\n [\n -80.33428751101353,\n 37.77673487869805\n ],\n [\n -78.39513484183449,\n 37.77673487869805\n ],\n [\n -78.39513484183449,\n 39.425222908113994\n ],\n [\n -80.33428751101353,\n 39.425222908113994\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kalen, Nicholas J.","contributorId":286972,"corporation":false,"usgs":false,"family":"Kalen","given":"Nicholas J.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":924340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muthersbaugh, Michael S.","contributorId":270636,"corporation":false,"usgs":false,"family":"Muthersbaugh","given":"Michael","email":"","middleInitial":"S.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":924341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Joshua B.","contributorId":270675,"corporation":false,"usgs":false,"family":"Johnson","given":"Joshua B.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":924342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Silvis, Alexander","contributorId":270624,"corporation":false,"usgs":false,"family":"Silvis","given":"Alexander","affiliations":[{"id":56186,"text":"WV DNR","active":true,"usgs":false}],"preferred":false,"id":924343,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":924339,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70232317,"text":"70232317 - 2022 - Multiple resource limitation of dryland soil microbial carbon cycling on the Colorado Plateau","interactions":[],"lastModifiedDate":"2022-06-27T18:50:56.591006","indexId":"70232317","displayToPublicDate":"2022-03-01T14:50:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Multiple resource limitation of dryland soil microbial carbon cycling on the Colorado Plateau","docAbstract":"Understanding interactions among biogeochemical cycles is increasingly important as anthropogenic alterations of global climate and of carbon (C), nitrogen (N), and phosphorus (P) cycles interactively affect the Earth system. Ecosystem processes in the dryland biome, which makes up over 40% of Earth's terrestrial surface, are often distinctively sensitive to small changes in resource availability, likely because levels of many resources are low. However, data also suggest that simultaneous changes in the availability of multiple resources may be necessary to affect a response in these low-resource systems, offering an opportunity to test patterns and controls of co-limitation, serial limitation, and individual limitation in soil environments. While drylands may play a governing role in key aspects of Earth's C cycle, and while an improved understanding of resource limitation could substantially improve our forecasts of dryland responses to change, our understanding of interacting controls on soil C cycle processes remains notably poor in these dry systems. Here, we address multiple fundamental hypotheses of resource controls over ecosystem function to test how water, C, N, and P regulate soil C cycling individually and interactively in a dryland ecosystem on the Colorado Plateau. Using a series of laboratory incubations, we found that, while water, C, and N limited C cycling through serial limitation, water alone resulted in an extremely small respiratory response from target organisms, whereas water + C resulted in a dramatic increase in soil C cycling, suggesting a degree of functional co-limitation. Nitrogen additions alone resulted in no changes to soil C cycling, but when N was added in concert with water and C, N greatly increased soil C cycling rates relative to additions of water and C without N. Phosphorus additions had no effect on the C cycle either alone or synergistically. These patterns were consistent with the stoichiometry of the system and interactions among resources were surprising in ways that inform our understanding of critical theories in ecology, such as the Transient Maxima Hypothesis, supporting the suggestion that multiple resource limitation explains pulse-dynamic C cycling in drylands better than water limitation alone.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3671","usgsCitation":"Choi, R.T., Reed, S.C., and Tucker, C., 2022, Multiple resource limitation of dryland soil microbial carbon cycling on the Colorado Plateau: Ecology, v. 103, no. 6, e3671; 17 p., https://doi.org/10.1002/ecy.3671.","productDescription":"e3671; 17 p.","ipdsId":"IP-110874","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":448642,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.3671","text":"Publisher Index Page"},{"id":435940,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EEDPB0","text":"USGS data release","linkHelpText":"CO2 concentrations and microbial biomass data derived from incubation experiments on soils collected at Arches National Park in 2017 and 2018"},{"id":402544,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Arches National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.71427917480467,\n 38.84719484808292\n ],\n [\n -109.71359252929686,\n 38.839707613545144\n ],\n [\n -109.70466613769531,\n 38.838103103640364\n ],\n [\n -109.70603942871092,\n 38.832219591146746\n ],\n [\n -109.69573974609375,\n 38.832754476016575\n ],\n [\n -109.6929931640625,\n 38.825265722073624\n ],\n [\n -109.68612670898438,\n 38.82473078093276\n ],\n [\n -109.68475341796875,\n 38.804935133335775\n ],\n [\n -109.69367980957031,\n 38.80332983969899\n ],\n [\n -109.69711303710938,\n 38.77603431465469\n ],\n [\n -109.6826934814453,\n 38.77442837007637\n ],\n [\n -109.68475341796875,\n 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University","active":true,"usgs":false}],"preferred":false,"id":845240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845241,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tucker, Colin 0000-0002-4539-7780 ctucker@usgs.gov","orcid":"https://orcid.org/0000-0002-4539-7780","contributorId":167487,"corporation":false,"usgs":true,"family":"Tucker","given":"Colin","email":"ctucker@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845242,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229978,"text":"70229978 - 2022 - What drought means for southwestern landscapes","interactions":[],"lastModifiedDate":"2025-03-14T15:12:55.049862","indexId":"70229978","displayToPublicDate":"2022-03-01T11:48:27","publicationYear":"2022","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":8569,"text":"Boatman's Quarterly Review","active":true,"publicationSubtype":{"id":30}},"title":"What drought means for southwestern landscapes","docAbstract":"Introduction Each year, more than 20,000 people raft the Grand Canyon, many of whom will experience this iconic landscape for the first and only time. Visitors to our region for their once-in-a-lifetime Grand Canyon experience might be surprised to see forests and wetlands in addition to deserts. While locals are seeing changes to the Colorado Plateau woodlands, many visitors may not be able to distinguish between our normal desert landscapes (we have cactus!) and the increasingly dry and hot conditions we have experienced in recent decades. Helping visitors see these drought impacts could help communicate that climate change is not a problem for future generations but something affecting us now. The southwestern US (“Southwest”) is one of many dry regions around the world located within about 30 degrees of the equator. As global temperatures rise, these dry zones are getting drier and are likely expanding1. Dryland expansion and aridification alters water availability, which touches our lives and ecosystem health in the Southwest. This essay focuses on drought impacts on ecosystems across the Four-Corners region and Grand Canyon, with particular attention to the forests and woodlands that contribute, in part, to Colorado River flows.
","language":"English","publisher":"Grand Canyon River Guides","usgsCitation":"Samuels-Crow, K., Ogle, K., and Palmquist, E.C., 2022, What drought means for southwestern landscapes: Boatman's Quarterly Review, v. 35, no. 1, p. 16-19.","productDescription":"4 p.","startPage":"16","endPage":"19","ipdsId":"IP-137479","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":407799,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":483349,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.gcrg.org/bqr","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.85107421875,\n 34.415973384481866\n ],\n [\n -111.24755859375,\n 34.415973384481866\n ],\n [\n -111.24755859375,\n 36.94989178681327\n ],\n [\n -114.85107421875,\n 36.94989178681327\n ],\n [\n -114.85107421875,\n 34.415973384481866\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Samuels-Crow, Kimberly","contributorId":289104,"corporation":false,"usgs":false,"family":"Samuels-Crow","given":"Kimberly","email":"","affiliations":[{"id":62051,"text":"School of Informatics, Computing, and Cyber Systems; Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":838550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ogle, Kiona","contributorId":248351,"corporation":false,"usgs":false,"family":"Ogle","given":"Kiona","email":"","affiliations":[],"preferred":false,"id":838551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":838552,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}