The United States Atlantic Outer Continental Shelf (OCS) has considerable offshore wind energy potential. Capturing that resource is part of a broader effort to reduce CO2 emissions. While few turbines have been constructed in U.S. waters, over a dozen currently planned offshore wind projects have the potential to displace marine birds, potentially leading to effective habitat loss. We focused on three diving birds identified in Europe to be vulnerable to displacement. Our research aimed to determine their potential exposure to areas designated or proposed for offshore wind development along the Atlantic OCS.
Satellite tracking technology was used to determine the spatial and temporal use and movement patterns of Surf Scoters (Melanitta perspicillata), Red‐throated Loons (Gavia stellata) and Northern Gannets (Morus bassanus), and calculate their exposure to each offshore wind area. We tagged 236 adults in 2012–2015 on the Atlantic OCS from New Jersey to North Carolina; an additional 147 birds tagged in previous tracking studies were integrated into our analyses. Tracking data were analysed in two‐week intervals using dynamic Brownian bridge movement models to develop composite spatial utilization distributions. For each species, these distributions were then used to calculate the spatio‐temporal exposure to each offshore wind area.
Surf Scoters and Red‐throated Loons were exposed to offshore wind areas almost exclusively during migration because these species were distributed among coastal and inshore waters during winter months. In contrast, Northern Gannets ranged over a much larger area, reaching farther offshore and south in winter, thus exhibited the greatest exposure to extant offshore wind areas.
Results of this study provide better understanding of how diving birds use current and potential future offshore wind areas on the Atlantic OCS, and can inform permitting, risk assessment and pre‐ and post‐construction impact assessments of offshore energy infrastructure.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13168","usgsCitation":"Stenhouse, I.J., Berlin, A., Gilbert, A.T., Goodale, M., Gray, C.O., Montevecchi, W.A., Savoy, L., and Spiegel, C.S., 2020, Assessing the exposure of three diving bird species to offshore wind areas on the U.S. Atlantic Outer Continental Shelf using satellite telemetry: Diversity and Distributions, v. 26, no. 12, p. 1703-1714, https://doi.org/10.1111/ddi.13168.","productDescription":"12 p.","startPage":"1703","endPage":"1714","ipdsId":"IP-115177","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":455173,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13168","text":"Publisher Index Page"},{"id":378982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Atlantic Outer Continental Shelf","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.84912109375,\n 34.90395296559004\n ],\n [\n -78.46435546874999,\n 33.815666308702774\n ],\n [\n -78.02490234374999,\n 33.43144133557529\n ],\n [\n -77.40966796874999,\n 32.99023555965106\n ],\n [\n -76.28906249999999,\n 32.76880048488168\n ],\n [\n -74.81689453125,\n 33.24787594792436\n ],\n [\n -73.41064453125001,\n 33.68778175843934\n ],\n [\n -71.96044921875001,\n 35.60371874069731\n ],\n [\n -70.97167968749999,\n 38.30718056188316\n ],\n [\n -70.048828125,\n 41.11246878918088\n ],\n [\n -71.03759765625,\n 41.60722821271717\n ],\n [\n -72.48779296874999,\n 41.52502957323799\n ],\n [\n -73.23486328124999,\n 40.896905775860006\n ],\n [\n -76.04736328125,\n 38.58252615935333\n ],\n [\n -76.552734375,\n 37.56199695314352\n ],\n [\n -76.83837890624999,\n 36.42128244364947\n ],\n [\n -77.84912109375,\n 34.90395296559004\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stenhouse, Iain J","contributorId":242039,"corporation":false,"usgs":false,"family":"Stenhouse","given":"Iain","email":"","middleInitial":"J","affiliations":[{"id":37436,"text":"Biodiversity Research Institute","active":true,"usgs":false}],"preferred":false,"id":800421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berlin, Alicia 0000-0002-5275-3077 aberlin@usgs.gov","orcid":"https://orcid.org/0000-0002-5275-3077","contributorId":168416,"corporation":false,"usgs":true,"family":"Berlin","given":"Alicia","email":"aberlin@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":800422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilbert, Andrew T","contributorId":242040,"corporation":false,"usgs":false,"family":"Gilbert","given":"Andrew","email":"","middleInitial":"T","affiliations":[{"id":37436,"text":"Biodiversity Research Institute","active":true,"usgs":false}],"preferred":false,"id":800423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goodale, M Wing","contributorId":242041,"corporation":false,"usgs":false,"family":"Goodale","given":"M Wing","affiliations":[{"id":37436,"text":"Biodiversity Research Institute","active":true,"usgs":false}],"preferred":false,"id":800424,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gray, Carrie O","contributorId":242042,"corporation":false,"usgs":false,"family":"Gray","given":"Carrie","email":"","middleInitial":"O","affiliations":[{"id":37436,"text":"Biodiversity Research Institute","active":true,"usgs":false}],"preferred":false,"id":800425,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Montevecchi, William A","contributorId":242043,"corporation":false,"usgs":false,"family":"Montevecchi","given":"William","email":"","middleInitial":"A","affiliations":[{"id":26965,"text":"Memorial University of Newfoundland","active":true,"usgs":false}],"preferred":false,"id":800426,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Savoy, Lucas","contributorId":171896,"corporation":false,"usgs":false,"family":"Savoy","given":"Lucas","affiliations":[{"id":6928,"text":"BioDiversity Research Institute, Gorham, ME 04038","active":true,"usgs":false}],"preferred":false,"id":800427,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Spiegel, Caleb S.","contributorId":216938,"corporation":false,"usgs":false,"family":"Spiegel","given":"Caleb","email":"","middleInitial":"S.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":800428,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70214614,"text":"ofr20201103 - 2020 - Annotated bibliography of scientific research on greater sage-grouse published from 2015 to 2019","interactions":[{"subject":{"id":70195366,"text":"ofr20181008 - 2018 - Annotated bibliography of scientific research on greater sage-grouse published since January 2015","indexId":"ofr20181008","publicationYear":"2018","noYear":false,"title":"Annotated bibliography of scientific research on greater sage-grouse published since January 2015"},"predicate":"SUPERSEDED_BY","object":{"id":70214614,"text":"ofr20201103 - 2020 - Annotated bibliography of scientific research on greater sage-grouse published from 2015 to 2019","indexId":"ofr20201103","publicationYear":"2020","noYear":false,"title":"Annotated bibliography of scientific research on greater sage-grouse published from 2015 to 2019"},"id":1}],"lastModifiedDate":"2020-10-01T17:06:53.237674","indexId":"ofr20201103","displayToPublicDate":"2020-09-30T17:33:34","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1103","displayTitle":"Annotated Bibliography of Scientific Research on Greater Sage-Grouse Published from 2015 to 2019","title":"Annotated bibliography of scientific research on greater sage-grouse published from 2015 to 2019","docAbstract":"The greater sage-grouse (Centrocercus urophasianus; hereafter GRSG) has been a focus of scientific investigation and management action for the past two decades. The 2015 U.S. Fish and Wildlife Service listing determination of “not warranted” was in part due to a large-scale collaborative effort to develop strategies to conserve GRSG populations and their habitat and to reduce threats to both. New scientific information augments existing knowledge and can help inform updates or modifications to existing plans for managing GRSG and sagebrush ecosystems. However, the sheer number of scientific publications can be a challenge for managers tasked with evaluating and determining the need for potential updates to existing planning documents. To assist in this process, the U.S. Geological Survey (USGS) has reviewed and summarized the scientific literature published since January 1, 2015. The first GRSG literature summary was published early in 2018. Here we provide an update to that document by adding summaries of articles published between January 6, 2018 and October 2, 2019.
To identify articles and reports published about GRSG, we first conducted a structured search of three reference databases (Web of Science, Scopus, and Google Scholar) using the search term “greater sage-grouse.” We refined the initial list of products by (1) removing duplicates, (2) excluding products that were not published as research or scientific review articles in peer-reviewed journals or as formal technical reports, and (3) retaining only those products for which GRSG or their habitat was a research focus.
We summarized the contents of each product by using a consistent structure (background, objectives, methods, location, findings, and implications) and assessed the content of each product relevant to a list of 31 management topics. These topics include GRSG biology and habitat characteristics along with potential management actions, land uses, and environmental factors related to GRSG management and conservation. We also noted which articles/reports created new geospatial data.
Our original search, conducted on January 7, 2018, and the application of our criteria, resulted in the inclusion of 169 published products (2 of these products were published corrections to journal articles). This update adds summaries of 69 products published between then and October 2, 2019. The management topics most commonly addressed were GRSG behavior or demographics and GRSG habitat selection or habitat characteristics at broad or site scales. Few products addressed captive breeding, recreation, wild horses and burros, and range management structures (including fences). The management topics with the largest increase in representation between the 2018 GRSG literature summary and this update were GRSG survival and GRSG population estimates or targets, which were each addressed in 16 percent of products in the original literature summary document, but were addressed in 30 and 33 percent, respectively, of newly summarized products. Topics with the largest declines in representation were conifer expansion, - 17 to 10 percent, and new geospatial data, -31 to 21 percent. We include in this annotated bibliography the full citation, Digital Object Identifier (DOI), product summary, and management topics addressed by each product. The online version of this bibliography (https://apps.usgs.gov/gsgbib/index.php) is searchable by topic and location and includes links to journal landing pages for each original publication.
A substantial body of literature has been compiled on research explicitly related to the conservation, management, monitoring, and assessment of GRSG. These studies may inform planning and management actions that seek to balance conservation, economic, and social objectives and manage diverse resource uses and values across the western United States.
The review process for this product included requesting input on each summary from one or more authors of the original peer-reviewed article or report and a formal review of the entire document by three independent reviewers for the original document and by two independent reviewers for the updated document and, subsequently, the USGS Bureau Approving Official. This process is consistent with USGS Fundamental Science Practices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201103","usgsCitation":"Carter, S.K., Arkle, R.S., Bencin, H.L., Harms, B.R., Manier, D.J., Johnston, A.N., Phillips, S.L., Hanser, S.E., and Bowen, Z.H., 2020, Annotated bibliography of scientific research on greater sage-grouse published from 2015 to 2019: U.S. Geological Survey Open-File Report 2020–1103, 264 p., https://doi.org/10.3133/ofr20201103.","productDescription":"v, 264 p.","onlineOnly":"Y","ipdsId":"IP-117994","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":378931,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://apps.usgs.gov/gsgbib/index.php","text":"Interactive, searchable version —","description":"Related Work - Interactive, searchable version","linkHelpText":"Annotated Bibliography of Scientific Research on Greater Sage-Grouse Published since January 2015"},{"id":378930,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1103/ofr20201103.pdf","text":"Report","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1103"},{"id":378929,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1103/coverthb.jpg"},{"id":378932,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181017","text":"Open-File Report 2018-1017 —","description":"Related Work - OFR 2018-1017","linkHelpText":"Greater Sage-Grouse Science (2015–17)—Synthesis and Potential Management Implications"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Kansas, Montana, Nebraska, New Mexico, North Dakota, Oklahoma, Oregon, South Dakota, Texas, Utah, Washington, Wyoming","otherGeospatial":"Greater sage-grouse Management Zones","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.71679687499999,\n 32.54681317351514\n ],\n [\n -101.337890625,\n 34.95799531086792\n ],\n [\n -101.07421875,\n 52.482780222078226\n ],\n [\n -126.12304687500001,\n 50.233151832472245\n ],\n [\n -124.71679687499999,\n 32.54681317351514\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
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Climate change vulnerability assessments and associated adaptation strategies and actions connect existing climate science with possible effects on natural resources and highlight potential responses. However, these assessments, which are commonly generated for large regional areas, suggest management options in general terms without guidance for choosing among strategies and actions under specific circumstances. Meanwhile, land and resource management plans1 often address smaller geographies, and management actions must address specific rather than general situations. Thus, there is a need for tools that enable managers to bridge the gap by downscaling assessments, plans, and data generated at regional scales to identify adaptation actions and strategies appropriate for smaller management units and project-level planning.
To address this need, we have developed a tool–the Climate Adaptation Integration Tool (CAIT)–that helps resource managers use climate science and assessments, along with local knowledge, to identify those adaptation strategies and actions most appropriate for a given site or situation. Specifically, we provide:
The CAIT is meant to help managers integrate climate change science and assessments into management decisions. The CAIT also serves as a way for managers to document how they have incorporated climate change information into their decision-making and why certain actions were selected over others. A particular strength of the CAIT is that it leads to potential solutions (that is, adaptation strategies and actions) without inflexibly prescribing actions. This flexibility enables managers to incorporate other factors and constraints to create workable management plans and projects that strengthen their ability to achieve long-term conservation goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6C2","usgsCitation":"Kershner, J., Woodward, A., and Torregrosa, A., 2020, Integrating climate change considerations into natural resource planning—An implementation guide: U.S. Geological Survey Techniques and Methods, book 6, chap. C2, 58 p., https://doi.org/10.3133/tm6C2.","productDescription":"v, 58 p.","onlineOnly":"Y","ipdsId":"IP-106677","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":378927,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/6c2/coverthb.jpg"},{"id":378928,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/6c2/tm6c2.pdf","text":"Report","size":"3.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-C2"}],"contact":"Forest and Rangeland Ecosystem Science Center
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A long history of mining and widespread metals contamination in the Coeur d’Alene River watershed and downstream into the Spokane River has led to the area’s designation as a Superfund site and to extensive, ongoing (as of 2020) remedial actions. Long-term water-quality and streamflow data, collected by the U.S. Geological Survey for up to 29 years at 20 sampling sites in the Coeur d’Alene, Spokane and St. Joe River watersheds, were analyzed to evaluate the impact of remedial actions on metals in surface water. Analyses focused on total and dissolved cadmium, zinc and lead. Trends in total phosphorus, total nitrogen and dissolved orthophosphate were also evaluated; although these nutrients are not constituents of concern for the Superfund site, they are important to the health of Coeur d’Alene Lake.
Dissolved cadmium, zinc and lead concentrations were compared to ambient water-quality criteria at 20 sample sites. For the 12 sites with the most extensive data records, Weighted Regressions on Time, Discharge and Season (WRTDS) models were developed to estimate flow-normalized annual mean concentrations and flow-normalized annual total loads; these results were used to evaluate trends because flow-normalization dampens the impact of interannual streamflow variability on concentrations and loads. WRTDS models with Kalman filtering (WRTDS_K) were developed to estimate annual mean concentrations and annual total loads; these results were used to evaluate spatial patterns in constituent sources. Models were developed for total and dissolved cadmium, lead, and zinc; total phosphorus and nitrogen; and dissolved orthophosphate, although not all constituents were modeled for all sites due to limited sample sizes. Bootstrapped confidence intervals were constructed to determine the statistical likelihood of trends and the slope of trends in flow-normalized concentrations and loads during the period of record (13–29 years, depending on the site), water years 1999–2009, and water years 2009–18.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205096","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Zinsser, L.M., 2020, Trends in concentration, loads, and sources of trace metals and nutrients in the Spokane River Watershed, northern Idaho, water years 1990-2018: U.S. Geological Survey Scientific Investigations Report 2020–5096, 58 p., https://doi.org/10.3133/sir20205096.","productDescription":"Report: vii, 58 p.; Appendix 1-2; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-116912","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":378922,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5096/coverthb.jpg"},{"id":378923,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5096/sir20205096.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5096"},{"id":378924,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5096/sir20205096_appendix1.pdf","text":"Appendix 1","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5096 Appendix 1"},{"id":378925,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5096/sir20205096_appendix2.pdf","text":"Appendix 2","size":"35.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5096 Appendix 2"},{"id":378926,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91LNE8J","text":"USGS data release","description":"USGS Data Release","linkHelpText":"WRTDS annual concentrations, loads and statistical trend likelihoods for sites in the Spokane River watershed, water years 1990-2018"}],"country":"United States","state":"Idaho","otherGeospatial":"Spokane River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.18017578125,\n 46.98025235521883\n ],\n [\n -114.80712890625,\n 46.98025235521883\n ],\n [\n -114.80712890625,\n 48.29781249243716\n ],\n [\n -117.18017578125,\n 48.29781249243716\n ],\n [\n -117.18017578125,\n 46.98025235521883\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
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We estimate annualized earthquake loss associated with over 600,000 bridges located throughout the contiguous United States. Each year, the Federal Highway Administration, in partnership with State Departments of Transportation, undertake a massive exercise to update the National Bridge Inventory (NBI) by combining data from states, federal agencies, local jurisdictions, and tribal governments. The NBI captures pertinent details related to individual bridges (e.g., their usage, repairs, or retrofits). We make use of the 2018 NBI that contain the necessary engineering attributes needed to assign the appropriate Hazus bridge class for each bridge, which can then be used for engineering risk analyses. Basic structural data, component dimensions, and regional replacement cost factors are used to develop an economic exposure model. This is a significant improvement over previous replacement costs, and as a result of this study, results are now available within the Federal Emergency Management Agency’s Hazus platform. Earthquake hazard is defined using the U.S. Geological Survey’s 2018 National Seismic Hazard Model. For each bridge location, we obtain an earthquake shaking hazard curve defined in terms of spectral acceleration at a vibration period of 1.0 sec, ensuring that it properly reflects the site-specific soil conditions. We then integrate it with the bridge-specific fragility curve to compute annual probabilities of exceeding various damage states. Next, we perform economic loss analyses using the repair costs associated with specific damage states, resulting in an estimate of mean total annual financial loss for each bridge; this long-term measure of seismic risk enables us to illustrate the distribution of overall financial risk with respect to geographical region, era of construction, or type of bridge.
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S.","contributorId":265964,"corporation":false,"usgs":false,"family":"Yen","given":"S.","email":"","middleInitial":"S.","affiliations":[{"id":54842,"text":"Caltrans Division of Research, Innovation and System Information","active":true,"usgs":false}],"preferred":false,"id":823873,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bausch, D.","contributorId":265965,"corporation":false,"usgs":false,"family":"Bausch","given":"D.","affiliations":[{"id":54845,"text":"NiyamIT Inc.","active":true,"usgs":false}],"preferred":false,"id":823874,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lin, Kuo-wan 0000-0002-7520-8151 klin@usgs.gov","orcid":"https://orcid.org/0000-0002-7520-8151","contributorId":1539,"corporation":false,"usgs":true,"family":"Lin","given":"Kuo-wan","email":"klin@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":823875,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":823876,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":823877,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rozelle, J.","contributorId":265966,"corporation":false,"usgs":false,"family":"Rozelle","given":"J.","affiliations":[{"id":30786,"text":"FEMA","active":true,"usgs":false}],"preferred":false,"id":823878,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70217168,"text":"70217168 - 2020 - Impacts of grade control structure installations on hydrology and sediment transport as an adaptive management strategy","interactions":[],"lastModifiedDate":"2021-01-08T15:59:46.702087","indexId":"70217168","displayToPublicDate":"2020-09-30T09:44:59","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7504,"text":"Final Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"ST-2017-1751-01","title":"Impacts of grade control structure installations on hydrology and sediment transport as an adaptive management strategy","docAbstract":"The goal of this research was to examine the impacts of Grade Control Structure (GCS) installations at the Heard Scout Pueblo (HSP) study site in the City of Phoenix, Arizona, USA. The study site is around a high-use trail system and is comprised of eroded and incised channels that conduct high flows and associated sediments into a residential neighborhood downstream, a noted stormwater control problem. We established baseline conditions associated with rainfall/runoff response before structures were installed so we could have some data for comparison afterwards.
Innovative monitoring equipment, including video cameras and pressure transducers (to calculate discharge); digital terrain models, sediment samplers and sediment chains (to measure erosion and deposition); soil moisture sensors in monitoring wells (to document infiltration and potential recharge); and weather stations (to track temperature and relative humidity) were established and a small Unmanned Aircraft System (sUAS) survey was completed by July, 11, 2017, in time for the typical summer monsoon season which officially runs from June 15th to September 30th. Only one pre-GCS installation rain event incurred a significant flow event (October 13, 2018).
Natural Channel Design (NCD), a landscape restoration company with decades of experience, was hired through a competitive bid process to develop a novel layout of ~30 GCS installations (sills, modified one-rock dams (ORD), and plugs, as well as a modified Zuni-bowl). The American Conservation Experience (ACE) hand-built the structures based on these designs in the main channel from November 13, 2018 through December 1, 2018. ACE built another ten structures in locations adjacent to the channel from January 15 through January 18, 2019. NCD worked with the landscape forensics to identify a historic channel and reinstate it using GCS.
A surface-water model was also applied, using some of the baseline measurements (terrain and hydraulic conductivity) to track the flows of water and potential infiltration associated with rainfall events before GCS installation, to assist NCD in their design. The same model was applied using the installed GCS locations to simulate impacts of the structures on flow and infiltration. Our model was able to predict the slight reduction and delay in peak flows for small events and simulate infiltration, which was measured and occurred in the channel. Results demonstrated that structures could increase infiltration by ~15% over time. More data describing geomorphology and hydrology after repeated rainfall events will allow for increased analyses.
Innovative monitoring, including the large‐scale particle image velocimetry (LSPIV) were invaluable to this research. Given the arid-land location and added drought conditions, the water levels were not high enough to compute, even using the continuous slope-area method, so discharge was calculated solely using the LSPIV. The careful redundancy of data acquisition is extremely important when studying dryland hydrology.
Weather data indicated that the HSP GCS installations created roughly a three-degree microclimate cooling effect for at least two days following rainfall events, as compared with the untreated channel. The cooling was attributed to increased moisture, evaporation, and latent heat expulsion from the evaporation.
","language":"English","publisher":"Bureau of Reclamation","usgsCitation":"Tosline, D., Norman, L., Greimann, B.P., Cederberg, J., Huang, V., and Ruddell, B., 2020, Impacts of grade control structure installations on hydrology and sediment transport as an adaptive management strategy: Final Report ST-2017-1751-01, iv, 65 p.","productDescription":"iv, 65 p.","ipdsId":"IP-121918","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":382021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":382013,"type":{"id":15,"text":"Index Page"},"url":"https://data.usbr.gov/catalog/4414/item/6298"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.09899902343749,\n 33.293803558346596\n ],\n [\n -111.9784927368164,\n 33.293803558346596\n ],\n [\n -111.9784927368164,\n 33.38529959859565\n ],\n [\n -112.09899902343749,\n 33.38529959859565\n ],\n [\n -112.09899902343749,\n 33.293803558346596\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tosline, Deborah","contributorId":247510,"corporation":false,"usgs":false,"family":"Tosline","given":"Deborah","affiliations":[{"id":49564,"text":"Reclamation, Hydrologist / Program Manager","active":true,"usgs":false}],"preferred":false,"id":807809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":807810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Greimann, Blair P.","contributorId":247511,"corporation":false,"usgs":false,"family":"Greimann","given":"Blair","email":"","middleInitial":"P.","affiliations":[{"id":49565,"text":"Reclamation, Hydraulic Engineer","active":true,"usgs":false}],"preferred":false,"id":807811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cederberg, Jay 0000-0001-6649-7353","orcid":"https://orcid.org/0000-0001-6649-7353","contributorId":219724,"corporation":false,"usgs":true,"family":"Cederberg","given":"Jay","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807812,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huang, Victor","contributorId":247512,"corporation":false,"usgs":false,"family":"Huang","given":"Victor","email":"","affiliations":[{"id":49565,"text":"Reclamation, Hydraulic Engineer","active":true,"usgs":false}],"preferred":false,"id":807813,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ruddell, Benjamin L.","contributorId":247513,"corporation":false,"usgs":false,"family":"Ruddell","given":"Benjamin L.","affiliations":[{"id":49567,"text":"Northern Arizona University, Professor","active":true,"usgs":false}],"preferred":false,"id":807814,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227669,"text":"70227669 - 2020 - Assessing the efficacy of protected and multiple-use lands for bird conservation in the U.S.","interactions":[],"lastModifiedDate":"2022-01-26T15:41:46.426505","indexId":"70227669","displayToPublicDate":"2020-09-30T09:36:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the efficacy of protected and multiple-use lands for bird conservation in the U.S.","docAbstract":"Setting land aside has long been a primary approach for protecting biodiversity; however, the efficacy of this approach has been questioned. We examined whether protecting lands positively influences bird species in the U.S., and thus overall biodiversity. We used the North American Breeding Bird Survey and Protected Areas Database of the U.S. to assess effects of protected and multiple-use lands on the prevalence and long-term population trends of imperiled and non-imperiled bird species. We evaluated whether both presence and proportional area of protected and multiple-use lands surrounding survey routes affected prevalence and population trends for imperiled and non-imperiled species. Regarding presence of these lands surrounding these survey routes, our results suggest that imperiled and non-imperiled species are using the combination of protected and multiple-use lands more than undesignated lands. We found no difference between protected and multiple-use lands. Mean population trends were negative for imperiled species in all land categories and did not differ between the land categories. Regarding proportion of protected lands surrounding the survey routes, we found that neither the prevalence nor population trends of imperiled or non-imperiled species was positively associated with any land category. We conclude that, although many species (in both groups) tend to be using these protected and multiple-use lands more frequently than undesignated lands, this protection does not appear to improve population trends. Our results may be influenced by external pressures (e.g., habitat fragmentation), the size of protected lands, the high mobility of birds that allows them to use a combination of all land categories, and management strategies that result in similar habitat between protected and multiple-use lands, or our approach to detect limited relationships. Overall, our results suggest that the combination of protected and multiple-use lands is insufficient, alone, to prevent declines in avian biodiversity at a national scale.
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Lynnette","contributorId":272176,"corporation":false,"usgs":false,"family":"Dornak","given":"L.","email":"","middleInitial":"Lynnette","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":831670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aycrigg, Jocelyn L.","contributorId":272177,"corporation":false,"usgs":false,"family":"Aycrigg","given":"Jocelyn L.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":831671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":831672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":831669,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228928,"text":"70228928 - 2020 - Using video survey to examine the effect of habitat on gag grouper encounter","interactions":[],"lastModifiedDate":"2022-03-08T14:43:20.629834","indexId":"70228928","displayToPublicDate":"2020-09-30T08:32:37","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Using video survey to examine the effect of habitat on gag grouper encounter","docAbstract":"Gag is a reef fish that was declared overfished in the Gulf of Mexico (GOM) in 2009. Although Gag are no longer listed as overfished, fisheries managers are concerned that stocks may not be recovering. Our objective was to identify habitat characteristics important to Gag, and their effect on the probability of Gag occurrence. We obtained data from three separate fisheries-independent video surveys that sampled in the eastern GOM from 2010-2017: the National Atmospheric and Oceanic Administration (NOAA) Panama City, FL Office, the NOAA Southeast Area Monitoring and Assessment Program, and the Florida Fish and Wildlife Research Institute. We ran a separate mixed effects logistic regression for each survey, and used Akaike’s Information Criteria to determine the best fitting models. Some variables - percent rock coverage, vertical relief, latitude, and depth - were present in all confidence models. Depth did not have the same relationship with Gag across all surveys, suggesting that shallower habitats (<50 m) might be more suitable for juveniles, whereas deeper habitats (>50 m) might be more suitable for adults. Managers may be able to help Gag and encourage their recovery by using these data to establish or expand protected areas throughout shallower waters.
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We analyzed the direct effect of shallow basin structures on shaking duration at a period of 2–10 s in the Los Angeles region through modeling small magnitude, shallow, and deep earthquake pairs. The source depth modulates the basin response, particularly the shaking duration, and these features are a function of path effect and not site condition. Three-dimensional simulations using the CVM-S4.26.M01 velocity model show good fitting to the initial portion of the waveforms at periods of 5 s and longer but fail to predict the long shaking duration during shallow events, especially at periods less than 5 s. Simulations using CVM-H do not match the timing of the initial arrivals as well as CVM-S4.26.M01, and the strong late arrivals in the CVM-H simulation travel with an apparent velocity slower than observed. A higher-quality factor than traditionally assumed may produce synthetics with longer durations but is unable to accurately match the amplitude and phase. Beamforming analysis using dense array data further reveals the long duration surface waves have the same back azimuth as the direct arrivals and are generated at the basin edges, while the later coda waves are scattered from off-azimuth directions, potentially due to strong, sharp boundaries offshore. Improving the description of these shallow basin structures and attenuation model will enhance our capability to predict long-period ground motions in basins.
Land use in Panama has changed dramatically with ongoing deforestation and conversion to cropland and cattle pastures, potentially altering the soil properties that drive the hydrological processes of infiltration and overland flow. We compared plot-scale overland flow generation between hillslopes in forested and actively cattle-grazed watersheds in Central Panama. Soil physical and hydraulic properties, soil moisture and overland flow data were measured along hillslopes of each land-use type. Soil characteristics and rainfall data were input into a simple, 1-D representative model, HYDRUS-1D, to simulate overland flow that we used to make inferences about overland flow response at forest and pasture sites. Runoff ratios (overland flow/rainfall) were generally higher at the pasture site, although no overall trends were observed between rainfall characteristics and runoff ratios across the two land uses at the plot scale. Saturated hydraulic conductivity (Ks) and bulk density were different between the forest and pasture sites (p < 10−4). Simulating overland flow in HYDRUS-1D produced more outputs similar to the overland flow recorded at the pasture site than the forest site. Results from our study indicate that, at the plot scale, Hortonian overland flow is the main driver for overland flow generation at the pasture site during storms with high-rainfall totals. We infer that the combination of a leaf litter layer and the activation of shallow preferential flow paths resulting in shallow saturation-excess overland flow are likely the main drivers for plot scale overland flow generation at the forest site. Results from this study contribute to the broader understanding of the delivery of freshwater to streams, which will become increasingly important in the tropics considering freshwater resource scarcity and changing storm intensities.
Characterizing pre- and post-fire fuels remains a key challenge for estimating biomass consumption and carbon emissions from wildfires. Airborne laser scanning (ALS) data have demonstrated effectiveness for estimating canopy, and to a lesser degree, surface fuel components at fine-scale (i.e., 30 m) across landscapes. Using pre- and post-fire ALS data and corresponding field data, this study estimated consumption of canopy fuel (ΔCF), understory fuel (ΔUF), total fuel (ΔTF), and canopy bulk density (ΔCBD) for the 2012 Pole Creek fire in Oregon, USA (10,760 ha), and portions of the 2011 Las Conchas fire in New Mexico, USA (4,934 ha). Additionally, the feasibility of predicting fuel consumption was tested using separate pre- and post-fire models (PrePost), models combining all pre- and post-fire data (Pooled), and models using all data from both fires (Global). Estimates of ΔTF were then compared to fire radiative energy (FRE, units: MJ) derived from Fire Radiative Power (FRP, units: MW) observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA Terra and Aqua satellites to mechanistically derive a biomass combustion coefficient (BCC, units: kg MJ−1). The PrePost and Pooled approaches yielded similar results at Las Conchas, but at Pole Creek insufficient pre-fire field data resulted in erroneous fuel consumption estimates outside the fire perimeter using the PrePost models. These results demonstrated that pre-fire field data were less important for these models than having field data which represent the full range of fuel conditions likely to exist across the landscape. Estimated total biomass consumed for the PrePost, Pooled, and Global models were 226 Gg, 224 Gg, and 224 Gg at Las Conchas, and 581 Gg, 713 Gg, and 552 Gg at Pole Creek. Comparisons between estimated ΔTF and FRE yielded an average BCC for both fires of 0.367 (s.d. ± 0.049) kg MJ−1 based on pixels with at least five MODIS observations. Both higher MODIS observations per pixel and accounting for canopy occlusion of FRE improved the relationship between ΔTF and MODIS-FRE. This study suggested a practical modelling approach for future efforts using only post-fire field observations and quantified a landscape-scale relationship between MODIS-derived FRE and fine-scale fuel consumption consistent with prior experiments.
The 2019 Ridgecrest, California earthquake sequence included Mw 6.4 and Mw 7.1 earthquakes that occurred on successive days beginning on 4 July 2019. These two largest earthquakes of the sequence occurred on orthogonal faults that ruptured the Earth’s surface. To better evaluate the 3D subsurface fault structure, (P- and S-wave) velocity, 3D and temporal variations in seismicity, and other important aspects of the earthquake sequence, we recorded aftershocks and ambient noise using up to 461 three-component nodal seismographs for about two months, beginning about one day after the Mw 7.1 mainshock. The ~ 30,000 Mw≥1 earthquakes that were recorded on the dense arrays provide an unusually large volume of data with which to evaluate the earthquake sequence. This report describes the recording arrays and is intended to provide metadata for researchers interested in evaluating various aspects of the 2019 Ridgecrest earthquake sequence using the nodal data set.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220200203","usgsCitation":"Catchings, R.D., Goldman, M., Steidl, J.H., Chan, J., Allam, A., Criley, C., Ma, Z., Langermann, D., Huddleston, G., McEvilly, A., Mongovin, D., and Ben-Zion, Y., 2020, Nodal seismograph recordings of the 2019 Ridgecrest Earthquake Sequence: Seismological Research Letters, v. 91, no. 6, p. 3622-3633, https://doi.org/10.1785/0220200203.","productDescription":"12 p.","startPage":"3622","endPage":"3633","ipdsId":"IP-116990","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United Staets","state":"California","city":"Ridgecrest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.84463534796981,\n 35.703354079218656\n ],\n [\n -117.84463534796981,\n 35.534977065306975\n ],\n [\n -117.55394107005387,\n 35.534977065306975\n ],\n [\n -117.55394107005387,\n 35.703354079218656\n ],\n [\n -117.84463534796981,\n 35.703354079218656\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"91","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Catchings, Rufus D. 0000-0002-5191-6102 catching@usgs.gov","orcid":"https://orcid.org/0000-0002-5191-6102","contributorId":1519,"corporation":false,"usgs":true,"family":"Catchings","given":"Rufus","email":"catching@usgs.gov","middleInitial":"D.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldman, Mark 0000-0002-0802-829X","orcid":"https://orcid.org/0000-0002-0802-829X","contributorId":205863,"corporation":false,"usgs":true,"family":"Goldman","given":"Mark","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927515,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steidl, Jamison Haase 0000-0003-0612-7654","orcid":"https://orcid.org/0000-0003-0612-7654","contributorId":239709,"corporation":false,"usgs":true,"family":"Steidl","given":"Jamison","email":"","middleInitial":"Haase","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chan, Joanne 0000-0002-2065-2423","orcid":"https://orcid.org/0000-0002-2065-2423","contributorId":205864,"corporation":false,"usgs":true,"family":"Chan","given":"Joanne","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927517,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allam, Amir A. 0000-0002-6447-0779","orcid":"https://orcid.org/0000-0002-6447-0779","contributorId":350962,"corporation":false,"usgs":false,"family":"Allam","given":"Amir A.","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":927518,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Criley, Coyn 0000-0002-0227-0165","orcid":"https://orcid.org/0000-0002-0227-0165","contributorId":223113,"corporation":false,"usgs":true,"family":"Criley","given":"Coyn","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927519,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ma, Zhenning","contributorId":350963,"corporation":false,"usgs":false,"family":"Ma","given":"Zhenning","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":927520,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Langermann, Daniel S.","contributorId":351005,"corporation":false,"usgs":false,"family":"Langermann","given":"Daniel S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":927677,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Huddleston, Garet Jax 0000-0002-2837-3947","orcid":"https://orcid.org/0000-0002-2837-3947","contributorId":350964,"corporation":false,"usgs":true,"family":"Huddleston","given":"Garet Jax","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927522,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McEvilly, Andrian T.","contributorId":351006,"corporation":false,"usgs":false,"family":"McEvilly","given":"Andrian T.","affiliations":[],"preferred":false,"id":927678,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mongovin, Daniel David Thomas 0000-0002-1623-2637","orcid":"https://orcid.org/0000-0002-1623-2637","contributorId":350965,"corporation":false,"usgs":true,"family":"Mongovin","given":"Daniel David Thomas","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927523,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ben-Zion, Yehuda 0000-0002-9602-2014","orcid":"https://orcid.org/0000-0002-9602-2014","contributorId":350966,"corporation":false,"usgs":false,"family":"Ben-Zion","given":"Yehuda","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":927525,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70214515,"text":"sir20205083 - 2020 - The Everglades Depth Estimation Network (EDEN) surface-water interpolation model, version 3","interactions":[],"lastModifiedDate":"2020-09-30T12:35:17.865835","indexId":"sir20205083","displayToPublicDate":"2020-09-29T12:47:07","publicationYear":"2020","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":"2020-5083","displayTitle":"The Everglades Depth Estimation Network (EDEN) Surface-Water Interpolation Model, Version 3","title":"The Everglades Depth Estimation Network (EDEN) surface-water interpolation model, version 3","docAbstract":"The Everglades Depth Estimation Network (EDEN) is an integrated network of water-level gages, interpolation models that estimate daily water-level data at ungaged locations, and applications that generate derived hydrologic data across the freshwater part of the Greater Everglades landscape. Version 3 (V3) of the EDEN interpolation surface-water model is the most recent update, replacing the version 2 (V2) model released in 2011.
The primary revision for the V3 model is the switch to the R programming language to create a more efficient and portable EDEN code relative to V2, without reliance on proprietary software. Using R, the interpolation script runs over 10 times faster and is more easily updated, for example, to accommodate changes in the gage network or to incorporate R software updates. Additional revisions made for the V3 model include updates to the interpolation model, the gage network, and groundwater-level estimations. The EDEN model domain in the Greater Everglades and Big Cypress National Preserve is divided into subdomains that are based on hydrologic boundaries. In the V3 model, the number of subdomains was increased from five to eight, which allows hydrologic boundaries, such as levees and canals, to be better represented in the interpolation scheme. Five pseudogages were added to constrain the water-level surface at subdomain boundaries. Changes made to the water-level gage network between the implementation of the V2 and V3 models are incorporated, and groundwater-level estimations are added, which are important information for hydrologic and ecological studies.
Summary model performance statistics indicate similar accuracy in water-level surfaces generated by the V3 and V2 models, with a root mean square error of 4.78 centimeters for both interpolation models against independent water-level measurements. Providing stability and continuity for the EDEN user community, the V3 model closely replicates the V2 model, with a root mean square difference of 3.87 centimeters for interpolated surfaces from April 1, 2014, to March 31, 2018. The additional groundwater levels provide a realistic estimate of the saturated groundwater surface continuous with the surface-water surface for Water Conservation Areas 2A and 2B from 2000 to 2011. This continuous surface is a more accurate estimation of the spatial distribution of water in the hydrologic system than before, providing needed information for ecological studies in areas where depth to water table affects habitats. Development of the EDEN V3 model advances the tools available to scientists and resource managers for guiding large-scale field operations, describing hydrologic changes, and supporting biological and ecological assessments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205083","collaboration":"USGS Greater Everglades Priority Ecosystems Science ProgramDirector, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The effects of climate on plant species ranges are well appreciated, but the effects of other processes, such as fire, on plant species distribution are less well understood. We used a dataset of 561 plots 0.1 ha in size located throughout Yosemite National Park, in the Sierra Nevada of California, USA, to determine the joint effects of fire and climate on woody plant species. We analyzed the effect of climate (annual actual evapotranspiration [AET], climatic water deficit [Deficit]) and fire characteristics (occurrence [BURN] for all plots, fire return interval departure [FRID] for unburned plots, and severity of the most severe fire [dNBR]) on the distribution of woody plant species.
Of 43 species that were present on at least two plots, 38 species occurred on five or more plots. Of those 38 species, models for the distribution of 13 species (34%) were significantly improved by including the variable for fire occurrence (BURN). Models for the distribution of 10 species (26%) were significantly improved by including FRID, and two species (5%) were improved by including dNBR. Species for which distribution models were improved by inclusion of fire variables included some of the most areally extensive woody plants. Species and ecological zones were aligned along an AET-Deficit gradient from cool and moist to hot and dry conditions.
In fire-frequent ecosystems, such as those in most of western North America, species distribution models were improved by including variables related to fire. Models for changing species distributions would also be improved by considering potential changes to the fire regime.
","language":"English","publisher":"Springer","doi":"10.1186/s42408-020-00079-9","usgsCitation":"van Wagtendonk, J., Moore, P., Yee, J.L., and Lutz, J.A., 2020, The distribution of woody species in relation to climate and fire in Yosemite National Park, California, USA: Fire Ecology, v. 16, 22, 23 p., https://doi.org/10.1186/s42408-020-00079-9.","productDescription":"22, 23 p.","ipdsId":"IP-117438","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":455198,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-020-00079-9","text":"Publisher Index Page"},{"id":379026,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.13549804687501,\n 36.94989178681327\n ],\n [\n -118.24584960937499,\n 36.94989178681327\n ],\n [\n -118.24584960937499,\n 38.272688535980976\n ],\n [\n -120.13549804687501,\n 38.272688535980976\n ],\n [\n -120.13549804687501,\n 36.94989178681327\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2020-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"van Wagtendonk, Jan W.","contributorId":189573,"corporation":false,"usgs":false,"family":"van Wagtendonk","given":"Jan W.","affiliations":[],"preferred":false,"id":800466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Peggy E","contributorId":242603,"corporation":false,"usgs":false,"family":"Moore","given":"Peggy E","affiliations":[{"id":48478,"text":"retired USGS WERC employee","active":true,"usgs":false}],"preferred":false,"id":800467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":800468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lutz, James A.","contributorId":139178,"corporation":false,"usgs":false,"family":"Lutz","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":12682,"text":"Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":800469,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70214528,"text":"70214528 - 2020 - The collection and analysis of Bay of Fundy sediment under contract between the association of US delegates to the Gulf of Maine Council on the marine environment and eastern Charlotte waterways for contaminant monitoring and analysis","interactions":[],"lastModifiedDate":"2020-09-30T15:15:04.870982","indexId":"70214528","displayToPublicDate":"2020-09-28T10:13:18","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"displayTitle":"The Collection and Analysis of Bay of Fundy Sediment Under Contract between the Association of US Delegates to the Gulf of Maine Council on the Marine Environment and Eastern Charlotte Waterways for Contaminant Monitoring and Analysis","title":"The collection and analysis of Bay of Fundy sediment under contract between the association of US delegates to the Gulf of Maine Council on the marine environment and eastern Charlotte waterways for contaminant monitoring and analysis","docAbstract":"This report presents data obtained through the EcoSystem Indicator Partnership (ESIP) which was established in 2006 to improve understanding and to inform researchers, managers, and citizens about the status and trends of ecosystem health in the Gulf of Maine (http://www.gulfofmaine.org/2/esip-homepage/). In its efforts to compile information on contaminant indicators in the Gulf of Maine, ESIP identified gaps in monitoring information and worked in partnership with the Gulf of Maine Council and other organizations to fill these gaps. The monitoring and data gaps identified by ESIP indicated that data on contaminants in intertidal/subtidal sediments were lacking for the Bay of Fundy. To address this data gap, the Association of US Delegates to the Gulf of Maine Council on the Marine Environment contracted Eastern Charlotte Waterways Inc., an independent non-governmental organization, to conduct a contaminant monitoring and analysis project funded by Environment and Climate Change Canada . This report summarizes the data produced from this sediment analysis project.","language":"English","publisher":"Gulf of Maine Council","collaboration":"Dalhousie University, US EPA, Bowdoin College, Lawrence LeBlanc Consulting","usgsCitation":"Latimer, J.S., Page, D., Elskus, A., LeBlanc, L., Harding, G., and Wells, P.G., 2020, The collection and analysis of Bay of Fundy sediment under contract between the association of US delegates to the Gulf of Maine Council on the marine environment and eastern Charlotte waterways for contaminant monitoring and analysis, 92 p.","productDescription":"92 p.","ipdsId":"IP-118574","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":378918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":378842,"type":{"id":15,"text":"Index Page"},"url":"https://gulfofmaine.org/public/gulf-of-maine-council-on-the-marine-environment/publications/"}],"country":"United States, Canada","otherGeospatial":"Gulf of Maine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.982421875,\n 41.65649719441145\n ],\n [\n -63.30322265625001,\n 41.65649719441145\n ],\n [\n -63.30322265625001,\n 46.118941506107056\n ],\n [\n -71.982421875,\n 46.118941506107056\n ],\n [\n -71.982421875,\n 41.65649719441145\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Latimer, James S","contributorId":222883,"corporation":false,"usgs":false,"family":"Latimer","given":"James","email":"","middleInitial":"S","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":799828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Page, David","contributorId":222884,"corporation":false,"usgs":false,"family":"Page","given":"David","email":"","affiliations":[{"id":33315,"text":"Bowdoin College","active":true,"usgs":false}],"preferred":false,"id":799829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elskus, Adria 0000-0003-1192-5124 aelskus@usgs.gov","orcid":"https://orcid.org/0000-0003-1192-5124","contributorId":130,"corporation":false,"usgs":true,"family":"Elskus","given":"Adria","email":"aelskus@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":799830,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LeBlanc, Lawrence A","contributorId":222882,"corporation":false,"usgs":false,"family":"LeBlanc","given":"Lawrence A","affiliations":[{"id":40617,"text":"Lawrence LeBlanc Consulting","active":true,"usgs":false}],"preferred":false,"id":799831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harding, Gareth","contributorId":222885,"corporation":false,"usgs":false,"family":"Harding","given":"Gareth","email":"","affiliations":[{"id":40618,"text":"Fisheries & Oceans, Bedford Institute of Oceanography","active":true,"usgs":false}],"preferred":false,"id":799832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wells, Peter G","contributorId":222886,"corporation":false,"usgs":false,"family":"Wells","given":"Peter","email":"","middleInitial":"G","affiliations":[{"id":40619,"text":"International Ocean Institute Canada, Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":799833,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70214530,"text":"70214530 - 2020 - Modeling soil porewater salinity in mangrove forests (Everglades, Florida, USA) impacted by hydrological restoration and a warming climate","interactions":[],"lastModifiedDate":"2020-09-30T14:56:14.381095","indexId":"70214530","displayToPublicDate":"2020-09-26T09:49:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Modeling soil porewater salinity in mangrove forests (Everglades, Florida, USA) impacted by hydrological restoration and a warming climate","docAbstract":"Hydrology is a critical driver controlling mangrove wetlands structural and functional attributes at different spatial and temporal scales. Yet, human activities have negatively affected hydrology, causing mangrove diebacks and coverage loss worldwide. In fact, the assessment of mangrove water budgets, impacted by natural and human disturbances, is limited due to a lack of long-term data and information that hinders our understanding of how changes in hydroperiod and salinity control mangrove productivity and spatial distribution. In this study, we implemented a mass balance-based hydrological model (RHYMAN) that explicitly considers groundwater discharge in the Shark River estuary (SRE, southwestern Everglades) located in a karstic geomorphic setting and influenced by regional hydrological restoration. We used long-term hydroperiod and porewater salinity (PWS) datasets obtained from 2004 to 2016 for model calibration and validation and to determine spatiotemporal variability in water levels and PWS at three riverine mangrove sites (downstream, SRS-6; midstream, SRS-5; upstream, SRS-4) along SRE. Model results agree with a distinct PWS pattern along the estuarine salinity gradient where the highest PWS occurs at SRS-6 (mean: 25, range: 22–30 ppt), followed by SRS-5 (17, 14–25 ppt) and SRS-4 (5, 3–13 ppt). A commensurate increase in PWS over a thirteen-year period indicates a long-term reduction in freshwater inflow coupled with sea-level rise (SLR). Increasing freshwater scenario simulation results show a significant reduction (17–27%) in PWS along the estuary in contrast with a high SLR scenario when salinity increases up to 1.1 to 2.5 times that of control values. Model results show that freshwater inflow and SLR are key drivers controlling mangrove wetlands PWS in this karstic coastal region. Given its relatively simple structure, this mass balance-based hydrological model could be used in other environmental settings to evaluate potential habitat and regime shifts due to changes in hydrology and PWS under regional hydrological restoration management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2020.109292","usgsCitation":"Zhao, X., Rivera-Monroy, V.H., Wang, H., Xue, Z., Tsai, C., Willson, C.S., Castañeda-Moya, E., and Twilley, R.R., 2020, Modeling soil porewater salinity in mangrove forests (Everglades, Florida, USA) impacted by hydrological restoration and a warming climate: Ecological Modelling, v. 436, 109292, 18 p., https://doi.org/10.1016/j.ecolmodel.2020.109292.","productDescription":"109292, 18 p.","ipdsId":"IP-117526","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":455213,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://repository.lsu.edu/civil_engineering_pubs/1184","text":"Publisher Index Page"},{"id":378913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.9085693359375,\n 25.06072125231416\n ],\n [\n -80.3814697265625,\n 25.06072125231416\n ],\n [\n -80.3814697265625,\n 26.48532391504829\n ],\n [\n -81.9085693359375,\n 26.48532391504829\n ],\n [\n -81.9085693359375,\n 25.06072125231416\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"436","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhao, Xiaochen","contributorId":219696,"corporation":false,"usgs":false,"family":"Zhao","given":"Xiaochen","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rivera-Monroy, Victor H. 0000-0003-2804-4139","orcid":"https://orcid.org/0000-0003-2804-4139","contributorId":200322,"corporation":false,"usgs":false,"family":"Rivera-Monroy","given":"Victor","email":"","middleInitial":"H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799835,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":219641,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":799836,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xue, Zuo 0000-0003-4018-0248","orcid":"https://orcid.org/0000-0003-4018-0248","contributorId":241655,"corporation":false,"usgs":false,"family":"Xue","given":"Zuo","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799837,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tsai, Cheng-Feng","contributorId":241949,"corporation":false,"usgs":false,"family":"Tsai","given":"Cheng-Feng","email":"","affiliations":[],"preferred":false,"id":799838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Willson, C. S.","contributorId":90440,"corporation":false,"usgs":false,"family":"Willson","given":"C.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":799839,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Castañeda-Moya, E. 0000-0001-7759-4351","orcid":"https://orcid.org/0000-0001-7759-4351","contributorId":241657,"corporation":false,"usgs":false,"family":"Castañeda-Moya","given":"E.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":799840,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Twilley, Robert R.","contributorId":34585,"corporation":false,"usgs":false,"family":"Twilley","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799841,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216169,"text":"70216169 - 2020 - Climate- versus geographic-dependent patterns in the spatial distribution ofmacroinvertebrate assemblages in New World depressional wetlands","interactions":[],"lastModifiedDate":"2023-03-27T17:09:04.907627","indexId":"70216169","displayToPublicDate":"2020-09-26T09:44:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Climate- versus geographic-dependent patterns in the spatial distribution ofmacroinvertebrate assemblages in New World depressional wetlands","docAbstract":"Analyses of biota at lower latitudes may presage impacts of climate change on biota at higher latitudes. Macroinvertebrate assemblages in depressional wetlands may be especially sensitive to climate change because weather‐related precipitation and evapotranspiration are dominant ecological controls on habitats, and organisms of depressional wetlands are temperature‐sensitive ectotherms. We aimed to better understand how wetland macroinvertebrate assemblages were structured according to geography and climate. To do so, we contrasted aquatic‐macroinvertebrate assemblage structure (family level) between subtropical and temperate depressional wetlands of North and South America using presence–absence data from 264 of these habitats across the continents and more‐detailed relative‐abundance data from 56 depressional wetlands from four case‐study locations (North Dakota and Georgia in North America; southern Brazil and Argentinian Patagonia in South America). Both data sets roughly partitioned wetland numbers equally between the two climatic zones and between the continents. We used ordination methods (PCA and NMDS) and tests of multivariate dispersion (PERMDISP) to assess the distribution and the homogeneity in variation in the composition of macroinvertebrate assemblages across climates and continents, respectively. We found that macroinvertebrate assemblage structures in the subtropical depressional wetlands of North and South America were similar to each other (at the family level), while assemblages in the North and South American temperate wetlands were unique from the subtropics, and from each other. Tests of homogeneity of multivariate dispersion indicated that family‐level assemblage structures were more homogeneous in wetlands from the subtropical than the temperate zones. Our study suggests that ongoing climate change may result in the homogenization of macroinvertebrate assemblage structures in temperate zones of North and South America, with those assemblages becoming enveloped by assemblages from the subtropics. Biotic homogenization, more typically associated with other kinds of anthropogenic factors, may also be affected by climate change.
Illegal killing of nongame wildlife is a global yet poorly documented problem. The prevalence and ecological consequences of illegal killing are often underestimated or completely unknown. We review the practice of legal recreational shooting and present data gathered from telemetry, surveys, and observations on its association with illegal killing of wildlife (birds and snakes) within conservation areas in Idaho, USA. In total, 33% of telemetered long‐billed curlews (Numenius americanus) and 59% of other bird carcasses found with known cause of death (or 32% of total) were illegally shot. Analysis of spatial distributions of illegal and legal shooting is consistent with birds being shot illegally in the course of otherwise legal recreational shooting, but snakes being intentionally sought out and targeted elsewhere, in locations where they congregate. Preliminary public surveys indicate that most recreational shooters find abhorrent the practice of illegal killing of wildlife. Viewed through this lens, our data may imply only a small fraction of recreational shooters is responsible for this activity. This study highlights a poorly known conservation problem that could have broad implications for some species and populations of wildlife.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.279","usgsCitation":"Katzner, T., Carlisle, J.D., Poessel, S.A., Thomason, E.C., Pauli, B.P., Pilliod, D.S., Belthoff, J.R., Heath, J.A., Parker, K.J., Warner, K.S., Hayes, H., Aberg, M., Ortiz, P., Amdor, S., Alsup, S., Coates, S.E., Miller, T.A., and Duran, Z.K., 2020, Illegal killing of nongame wildlife and recreational shooting in conservation areas: Conservation Science and Practice, v. 2, no. 11, e279, 15 p., https://doi.org/10.1111/csp2.279.","productDescription":"e279, 15 p.","ipdsId":"IP-117712","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":455217,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.279","text":"Publisher Index Page"},{"id":380846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.83959960937499,\n 43.14909399920127\n ],\n [\n -115.323486328125,\n 43.14909399920127\n ],\n [\n -115.323486328125,\n 43.92163712834673\n ],\n [\n -116.83959960937499,\n 43.92163712834673\n ],\n [\n -116.83959960937499,\n 43.14909399920127\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science 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University","active":true,"usgs":false}],"preferred":false,"id":805735,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Coates, Stephanie E.","contributorId":245282,"corporation":false,"usgs":false,"family":"Coates","given":"Stephanie","email":"","middleInitial":"E.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":805736,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Miller, Tricia A.","contributorId":190591,"corporation":false,"usgs":false,"family":"Miller","given":"Tricia","email":"","middleInitial":"A.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":805737,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Duran, Zoe K. 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T.","affiliations":[{"id":49127,"text":"Idaho Army National Guard","active":true,"usgs":false}],"preferred":false,"id":805738,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70214965,"text":"70214965 - 2020 - Integrating physical and economic data into experimental water accounts for the United States: Lessons and opportunities","interactions":[],"lastModifiedDate":"2020-10-03T15:10:16.780202","indexId":"70214965","displayToPublicDate":"2020-09-25T10:06:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1477,"text":"Ecosystem Services","active":true,"publicationSubtype":{"id":10}},"title":"Integrating physical and economic data into experimental water accounts for the United States: Lessons and opportunities","docAbstract":"Water management increasingly involves tradeoffs, making its accounting highly relevant in our interconnected world. Physical and economic data about water in many nations are becoming more widely integrated through application of the System of Environmental-Economic Accounts for Water (SEEA-Water), which enables the tracking of linkages between water and the economy. We present the first national and subnational SEEA-Water accounts for the United States. We compile accounts for water: (1) physical supply and use, (2) productivity, (3) quality, and (4) emissions for roughly the years 2000 to 2015. Total U.S. water use declined by 22% from 2000 to 2015, falling in 44 states though groundwater use increased in 21 states. Water-use reductions, combined with economic growth, led to increases in water productivity for the overall national economy (65%), mining (99%), and agriculture (68%). Surface-water quality trends were most evident at regional levels, and differed by water-quality constituent and region. This work provides (1) a baseline of recent historical water resource trends and their value in the U.S., and (2) a roadmap for the completion of future accounts for water, a critical ecosystem service. Our work also aids in the interpretation of ecosystem accounts in the context of long-term water resources trends.
heir value in the U.S., and (2) a roadmap for the completion of future accounts for water, a critical ecosystem service. Our work also aids in the interpretation of ecosystem accounts in the context of long-term water resources trends.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoser.2020.101182","usgsCitation":"Bagstad, K.J., Ancona, Z.H., Hass, J.L., Glynn, P.D., Wentland, S., Vardon, M., and Fay, J.P., 2020, Integrating physical and economic data into experimental water accounts for the United States: Lessons and opportunities: Ecosystem Services, v. 45, 101182, 21 p., https://doi.org/10.1016/j.ecoser.2020.101182.","productDescription":"101182, 21 p.","ipdsId":"IP-104799","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":455220,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoser.2020.101182","text":"Publisher Index Page"},{"id":436779,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TUTMAT","text":"USGS data release","linkHelpText":"Data release for Integrating physical and economic data into experimental water accounts for the 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kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":800450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ancona, Zachary H. 0000-0001-5430-0218 zancona@usgs.gov","orcid":"https://orcid.org/0000-0001-5430-0218","contributorId":5578,"corporation":false,"usgs":true,"family":"Ancona","given":"Zachary","email":"zancona@usgs.gov","middleInitial":"H.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":800451,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hass, Julie L.","contributorId":211867,"corporation":false,"usgs":false,"family":"Hass","given":"Julie","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":800452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glynn, Pierre D. 0000-0001-8804-7003 pglynn@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7003","contributorId":2141,"corporation":false,"usgs":true,"family":"Glynn","given":"Pierre","email":"pglynn@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":800453,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wentland, Scott","contributorId":211876,"corporation":false,"usgs":false,"family":"Wentland","given":"Scott","affiliations":[{"id":38340,"text":"Bureau of Economic Analysis","active":true,"usgs":false}],"preferred":false,"id":800454,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vardon, Michael","contributorId":211875,"corporation":false,"usgs":false,"family":"Vardon","given":"Michael","email":"","affiliations":[{"id":16807,"text":"Australian National University","active":true,"usgs":false}],"preferred":false,"id":800455,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fay, John P.","contributorId":207571,"corporation":false,"usgs":false,"family":"Fay","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":800456,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70214661,"text":"70214661 - 2020 - Harmonizing the Landsat ground reference with the Sentinel-2 Global Reference Image using space-based bundle adjustment","interactions":[],"lastModifiedDate":"2020-10-01T17:18:27.914365","indexId":"70214661","displayToPublicDate":"2020-09-24T12:14:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7131,"text":"MDPI Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Harmonizing the Landsat ground reference with the Sentinel-2 Global Reference Image using space-based bundle adjustment","docAbstract":"There is an ever-increasing need to use accurate and consistent geometric ground reference in the processing of remotely sensed data products as it reduces the burden on the end-users to account for the differences between the data products from different missions. In this regard, United States Geological Survey (USGS) initiated an effort to harmonize the Landsat ground reference with the Sentinel-2 Global Reference Image (GRI) to improve the co-registration between the data products of the two global medium-resolution missions. In this paper, we have discussed the process, results, and the improvements expected from this harmonization of two ground references using space-triangulation based bundle adjustment techniques. The ground coordinates of the Landsat reference library, consisting of 5 million Ground Control Points (GCPs) were adjusted in a series of four simultaneous bundle block adjustments using thousands of Landsat-8 (L8) scenes anchored with more than 300,000 control points extracted from the GRI dataset. The net adjustments to each of the four blocks, namely, Australia, Americas, Eurasia, and Islands, varied anywhere from 1 m to 13 m, depending on the accuracy of the GCPs in these blocks. The use of the GRI dataset in our bundle adjustment not only improved the absolute accuracy of the Landsat ground reference but\nwill also improve the co-registration between Sentinel-2 and Landsat terrain corrected products, as the European Space Agency plans to process the Sentinel-2 products using the GRI dataset. Independent validation of the Landsat products processed using harmonized GCPs with the GRI dataset indicated a global mis-registration error of less than 8 m Circular Error Probable at 90 % (CE90), an improvement from 25 meters prior to harmonization. The improvements to the Landsat products using the harmonized GCPs will be available to the public as part of Landsat Collection-2 processing by the end of 2020.","language":"English","publisher":"MDPI","doi":"10.3390/rs12193132","usgsCitation":"Rengarajan, R., Storey, J., and Choate, M.J., 2020, Harmonizing the Landsat ground reference with the Sentinel-2 Global Reference Image using space-based bundle adjustment: MDPI Remote Sensing, v. 12, no. 19, 3132, 26 p., https://doi.org/10.3390/rs12193132.","productDescription":"3132, 26 p.","ipdsId":"IP-121294","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":455232,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12193132","text":"Publisher Index Page"},{"id":378962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"19","noUsgsAuthors":false,"publicationDate":"2020-09-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Rengarajan, Rajagopalan 0000-0003-1860-7110","orcid":"https://orcid.org/0000-0003-1860-7110","contributorId":242014,"corporation":false,"usgs":false,"family":"Rengarajan","given":"Rajagopalan","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":800346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storey, James C. 0000-0002-6664-7232","orcid":"https://orcid.org/0000-0002-6664-7232","contributorId":242015,"corporation":false,"usgs":false,"family":"Storey","given":"James C.","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":800347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choate, Michael J. 0000-0002-8101-4994","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":216866,"corporation":false,"usgs":true,"family":"Choate","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":800348,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70214056,"text":"ofr20201096 - 2020 - Field evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor","interactions":[],"lastModifiedDate":"2022-10-25T13:56:58.33759","indexId":"ofr20201096","displayToPublicDate":"2020-09-24T11:47:39","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1096","displayTitle":"Field Evaluation of the Sequoia Scientific LISST-ABS Acoustic Backscatter Sediment Sensor","title":"Field evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor","docAbstract":"Sequoia Scientific’s LISST-ABS is a submersible acoustic instrument that measures the acoustic backscatter sensor (ABS) concentration at a point within a river, stream, or creek. Compared to traditional physical methods for measuring suspended-sediment concentration (SSC), sediment surrogates like the LISST-ABS offer continuous data that can be calibrated with physical SSC samples. Data were collected at 10 U.S. Geological Survey streamflow-gaging stations between January 10, 2016, and February 21, 2018, across the contiguous United States to test the accuracy and effectiveness of using the LISST-ABS as a surrogate for measuring the concentration of suspended sediment in a dynamic fluvial system. Correlation coefficients (Pearson’s r values) relating the ABS concentration and SSC from physical samples ranged from r = 0.718 to r = 0.956 at the 10 stations with the mean percentage of fines (percentage of the sediment less than 62.5 microns in diameter) ranging from 65 to 100 percent (with minimum and maximum values of 18 and 100 percent, respectively). The LISST-ABS instruments used in this field evaluation were factory-calibrated to accurately determine SSC for grains in the diameter range of 75–90 microns. Note that the sensor responds to grains of arbitrary sizes, but the accuracy varies at sizes other than this calibration size. For operational use, regression models could be determined for the ABS concentrations and SSC values or the instrument could be recalibrated to sediments for each fluvial environment. However, such calibrations were beyond the scope of this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201096","collaboration":"Federal Interagency Sedimentation Project and Observing Systems Division","usgsCitation":"Manaster, A.E., Straub, T.D., Wood, M.S., Bell, J.M., Dombroski, D.E., and Curran, C.A., 2020, Field evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor: U.S. Geological Survey Open-File Report 2020–1096, 26 p., https://doi.org/10.3133/ofr20201096.","productDescription":"Report: v, 26 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-116096","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":378643,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1096/coverthb.jpg"},{"id":378644,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1096/ofr20201096.pdf","text":"Report","size":"3.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1096"},{"id":378645,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LROJE4","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data for field evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor"}],"contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801