{"pageNumber":"450","pageRowStart":"11225","pageSize":"25","recordCount":184800,"records":[{"id":70238819,"text":"70238819 - 2021 - Are drought indices and climate data good indicators of ecologically relevant soil moisture dynamics in drylands?","interactions":[],"lastModifiedDate":"2022-12-13T13:06:04.143849","indexId":"70238819","displayToPublicDate":"2021-11-16T07:01:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Are drought indices and climate data good indicators of ecologically relevant soil moisture dynamics in drylands?","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab010\" class=\"abstract author\" lang=\"en\"><div id=\"as010\"><p id=\"sp0010\">Droughts are disproportionately impacting global dryland regions where ecosystem health and function are tightly coupled to moisture availability. Drought severity is commonly estimated using algorithms such as the standardized precipitation-evapotranspiration index (SPEI), which can estimate climatic water balance impacts at various hydrologic scales by varying computational length. However, the performance of these metrics as indicators of soil moisture dynamics at ecologically relevant scales, across soil depths, and in consideration of broader scale ecohydrological processes, requires more attention. In this study, we tested components of climatic water balance, including SPEI and SPEI computation lengths, to recreate multi-decadal and periodic soil-moisture patterns across soil profiles at 866 sites in the western United States. Modeling results show that SPEI calculated over the prior 12-months was the most predictive computation length and could recreate changes in moisture availability within the soil profile over longer periods of time and for annual recharge of deeper soil moisture stores. SPEI was slightly less successful with recreating spring surface-soil moisture availability, which is key to dryland ecosystems dominated by winter precipitation. Meteorological drought indices like SPEI are intended to be convenient and generalized indicators of meteorological water deficit. However, the inconsistent ability of SPEI to recreate ecologically relevant patterns of soil moisture at regional scales suggests that process-based models, and the larger data requirements they involve, remain an important tool for dryland ecohydrology</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2021.108379","usgsCitation":"Barnard, D., Germino, M., Bradford, J., O’Connor, R., Andrews, C.M., and Shriver, R.K., 2021, Are drought indices and climate data good indicators of ecologically relevant soil moisture dynamics in drylands?: Ecological Indicators, v. 133, 108379, 8 p., https://doi.org/10.1016/j.ecolind.2021.108379.","productDescription":"108379, 8 p.","ipdsId":"IP-123393","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":450195,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2021.108379","text":"Publisher Index Page"},{"id":436116,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MZKCWZ","text":"USGS data release","linkHelpText":"Standardized Precipitation-Evapotranspiration Index for western United States, 2001-2014, derived from gridMET climate estimates"},{"id":410357,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.6058382513936,\n              39.23869657680433\n            ],\n            [\n              -111.6058382513936,\n              45.4634532299672\n            ],\n            [\n              -121.44540957944166,\n              45.4634532299672\n            ],\n            [\n              -121.44540957944166,\n              39.23869657680433\n            ],\n            [\n              -111.6058382513936,\n              39.23869657680433\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"133","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barnard, David 0000-0003-1877-3151","orcid":"https://orcid.org/0000-0003-1877-3151","contributorId":218008,"corporation":false,"usgs":true,"family":"Barnard","given":"David","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":858783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":858784,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":858785,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Connor, Rory 0000-0002-6473-0032","orcid":"https://orcid.org/0000-0002-6473-0032","contributorId":222832,"corporation":false,"usgs":true,"family":"O’Connor","given":"Rory","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":858786,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andrews, Caitlin M. 0000-0003-4593-1071 candrews@usgs.gov","orcid":"https://orcid.org/0000-0003-4593-1071","contributorId":192985,"corporation":false,"usgs":true,"family":"Andrews","given":"Caitlin","email":"candrews@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":858787,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shriver, Robert K 0000-0002-4590-4834","orcid":"https://orcid.org/0000-0002-4590-4834","contributorId":222834,"corporation":false,"usgs":false,"family":"Shriver","given":"Robert","email":"","middleInitial":"K","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":858788,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70226146,"text":"sir20215082 - 2021 - Factors affecting uncertainty of public supply, self-supplied domestic, irrigation, and thermoelectric water-use data, 1985–2015—Evaluation of information sources, estimation methods, and data variability","interactions":[],"lastModifiedDate":"2022-01-24T16:51:46.274711","indexId":"sir20215082","displayToPublicDate":"2021-11-15T17:10:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5082","displayTitle":"Factors Affecting Uncertainty of Public Supply, Self-Supplied Domestic, Irrigation, and Thermoelectric Water-Use Data, 1985–2015—Evaluation of Information Sources, Estimation Methods, and Data Variability","title":"Factors affecting uncertainty of public supply, self-supplied domestic, irrigation, and thermoelectric water-use data, 1985–2015—Evaluation of information sources, estimation methods, and data variability","docAbstract":"<p>The U.S. Geological Survey (USGS) Water-Use Program is responsible for compiling and disseminating the Nation's water-use data. Working in cooperation with local, State, and Federal agencies, the USGS has collected and published national water-use estimates every 5 years, beginning in 1950. These water-use data may vary because of actual changes in water use, because of changes in estimation methods, or because of errors. Comparison and interpretation of these data is difficult without first determining the factors that contribute to data variability. This report describes factors that may affect data quality and documents ways to investigate the variability of public supply, self-supplied domestic, irrigation, and thermoelectric water-use data for the 1985–2015 compilations.</p><p>The USGS produces national water-use estimates for various categories of water use for every county in the United States. Knowledge about the sources of data for county estimates is important because factors such as estimation methodology and reporting affect data uncertainty Determination of meaningful patterns and trends in the data are contingent on the use of consistent methodology throughout the period of interest. With the many ways that water-use data have been collected, assembled, and estimated, multiple factors likely contribute to data uncertainty, Data used to produce these estimates may be furnished from agencies that collect information from entities who report water use; gaps in reported data are typically estimated to achieve a comprehensive county estimate. For example, public supply and thermoelectric category data are based primarily on furnished site-specific data; whereas crop irrigation is often furnished or estimated at the county scale. Public supply deliveries for domestic use and self-supplied domestic withdrawals are most often estimated by USGS personnel using per capita use rate coefficients. Irrigation may be estimated using crop water requirements, application rates, or other soil water balance methods when furnished reported data are not available.</p><p>Rates, percentages, medians, and interquartile ranges were used to investigate variability in the water-use data among States, regions, and years. The purposes of these evaluations were to (1) identify extreme values that may reflect changes in information sources, estimation methods, or errors; (2) indicate areas of variable or consistent values that are unexpected; and (3) indicate areas where values change because of local climate or other factors. Where factors are identified that contribute to data variability, such as a change in methodology, additional work could determine uncertainty because of these factors.</p><p>These evaluations identified the availability of information that is needed to address data limitations. Factors such as estimation methodology affect data quality. Some updates to method codes assigned in 2015 and assignment of method codes to earlier compilation datasets for all categories would provide much needed metadata for users of the data. Improvements in data documentation describing sources of information and estimation methods and additional metadata information from agencies and entities that furnish water-use data, would enable a more complete understanding and depiction of water-use patterns and trends. Additional metadata are needed for users of the data to better understand the water-use data and interpret changes in water use across the United States and with time.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215082","usgsCitation":"Luukkonen, C.L., Belitz, K., Sullivan, S.L., and Sargent, P., 2021, Factors affecting uncertainty of public supply, self-supplied domestic, irrigation, and thermoelectric water-use data, 1985–2015—Evaluation of information sources, estimation methods, and data variability: U.S. Geological Survey Scientific Investigations Report 2021–5082, 78 p., https://doi.org/10.3133/sir20215082.","productDescription":"Report: ix, 78 p.; Database; Data Release","onlineOnly":"Y","ipdsId":"IP-123556","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":391626,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TA1DI9","text":"USGS data release","linkHelpText":"Public supply, self-supplied domestic, irrigation, and thermoelectric water-use data from 5-year compilation datasets from 1985 to 2015 used to assess data variability and uncertainty"},{"id":391625,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5082/sir20215082.pdf","text":"Report","size":"26.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5082"},{"id":391624,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5082/coverthb.jpg"},{"id":391627,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System—","linkHelpText":"USGS water data for the Nation: U.S. Geological Survey National Water Information System database, accessed July 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        31.50362930577303\n            ],\n            [\n              -76.81640625,\n              34.07086232376631\n            ],\n            [\n              -75.16845703124999,\n              35.263561862152095\n            ],\n            [\n              -75.498046875,\n              37.055177106660814\n            ],\n            [\n              -73.58642578125,\n              39.90973623453719\n            ],\n            [\n              -71.3671875,\n              40.84706035607122\n            ],\n            [\n              -69.63134765625,\n              40.9964840143779\n            ],\n            [\n              -70.0048828125,\n              42.342305278572816\n            ],\n            [\n              -70.3564453125,\n              42.89206418807337\n            ],\n            [\n              -67.2802734375,\n              44.37098696297173\n            ],\n            [\n              -67.0166015625,\n              44.69989765840318\n            ],\n            [\n              -66.796875,\n              44.902577996288876\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.56640625,\n              18.771115062337024\n            ],\n            [\n              -154.68749999999997,\n              19.642587534013032\n            ],\n            [\n              -156.9287109375,\n              21.453068633086783\n            ],\n            [\n              -159.521484375,\n              22.43134015636061\n            ],\n            [\n              -160.5322265625,\n              21.983801417384697\n            ],\n            [\n              -159.9609375,\n              21.207458730482642\n            ],\n            [\n              -158.291015625,\n              20.92039691397189\n            ],\n            [\n              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Information Relevant to the Water-Use Data Elements for the 2015 Compilation</li><li>Assessment of the Variability of Water-Use Data Values by State and Category</li><li>Assessment of the Variability of Water-Use Data by Region and Compilation Year</li><li>Guidance for Additional Uncertainty Assessments and Water-Use Compilations</li><li>Summary</li><li>References Cited</li><li>Glossary</li><li>Appendix 1</li></ul>","publishedDate":"2021-11-15","noUsgsAuthors":false,"publicationDate":"2021-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Luukkonen, Carol L. 0000-0001-7056-8599","orcid":"https://orcid.org/0000-0001-7056-8599","contributorId":208181,"corporation":false,"usgs":true,"family":"Luukkonen","given":"Carol","email":"","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826639,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Samantha L. 0000-0002-9462-0029","orcid":"https://orcid.org/0000-0002-9462-0029","contributorId":205316,"corporation":false,"usgs":true,"family":"Sullivan","given":"Samantha","email":"","middleInitial":"L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sargent, Pierre","contributorId":268785,"corporation":false,"usgs":false,"family":"Sargent","given":"Pierre","email":"","affiliations":[{"id":55660,"text":"U.S. Geological Survey, retired","active":true,"usgs":false}],"preferred":false,"id":826641,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70226211,"text":"70226211 - 2021 - Impacts of climate change on groundwater availability and spring flows: Observations from the highly productive Medicine Lake Highlands/Fall River Springs Aquifer System","interactions":[],"lastModifiedDate":"2022-01-25T17:14:22.195081","indexId":"70226211","displayToPublicDate":"2021-11-15T07:34:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of climate change on groundwater availability and spring flows: Observations from the highly productive Medicine Lake Highlands/Fall River Springs Aquifer System","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Medicine Lake Highlands/Fall River Springs Aquifer System, located in northeastern California, is home to some of the largest first-order springs in the United States. This work assesses the likely effects of projected climate change on spring flow. Four anticipated climate futures (GFDL A2, GFDL B1, CCSM4 rcp 8.5, CNRM rcp 8.5) for California, which predict a range of conditions (generally warming and transitioning from snow to rain with variable amounts of total precipitation), are postulated to affect groundwater recharge primarily by changing evapotranspiration. The linkages between climate variables and spring flow are evaluated using a water balance model that represents the physics of evapotranspiration and recharge, the Basin Characterization Model. Three of the four climate scenarios (GFDL A2, GFDL B1, CCSM4 rcp 8.5) project that by the year 2100, groundwater recharge (and consequently decreased spring flow) will decrease by 27%, 21%, and 9%, respectively. The fourth scenario (CNRM rcp 8.5) showed an increase in recharge of 32% due to a significant increase in precipitation (27%). Evapotranspiration increases due to a shift in the type of precipitation and a longer growing season. While the likelihood of each scenario is outside the scope of this work, unless total precipitation increases dramatically in the future, increased temperatures and decreasing precipitation will likely result in reduced spring flows, along with warmer water temperatures in downstream habitats.</p></div></div>","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12976","usgsCitation":"Mancewicz, L., Davisson, L., Wheelock, S.J., Burns, E., Poulson, S.R., and Tyler, S.W., 2021, Impacts of climate change on groundwater availability and spring flows: Observations from the highly productive Medicine Lake Highlands/Fall River Springs Aquifer System: Journal of the American Water Resources Association, v. 57, no. 6, p. 1021-1036, https://doi.org/10.1111/1752-1688.12976.","productDescription":"16 p.","startPage":"1021","endPage":"1036","ipdsId":"IP-118875","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":450199,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/1752-1688.12976","text":"External Repository"},{"id":391792,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Medicine Lake Highlands/Fall River Springs Aquifer System","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.091064453125,\n              40.8865244080599\n            ],\n            [\n              -121.26434326171875,\n              40.8865244080599\n            ],\n            [\n              -121.26434326171875,\n              41.65239288426812\n            ],\n            [\n              -122.091064453125,\n              41.65239288426812\n            ],\n            [\n              -122.091064453125,\n              40.8865244080599\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"57","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Mancewicz, Lauren K","contributorId":268887,"corporation":false,"usgs":false,"family":"Mancewicz","given":"Lauren K","affiliations":[{"id":16704,"text":"University of Nevada - Reno","active":true,"usgs":false}],"preferred":false,"id":826896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davisson, L.","contributorId":268888,"corporation":false,"usgs":false,"family":"Davisson","given":"L.","email":"","affiliations":[{"id":55710,"text":"ML Davisson & Associates, Inc.","active":true,"usgs":false}],"preferred":false,"id":826897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wheelock, Shawn J","contributorId":268889,"corporation":false,"usgs":false,"family":"Wheelock","given":"Shawn","email":"","middleInitial":"J","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":826898,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Erick R. 0000-0002-1747-0506","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":225412,"corporation":false,"usgs":true,"family":"Burns","given":"Erick R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":826899,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poulson, Simon R.","contributorId":187411,"corporation":false,"usgs":false,"family":"Poulson","given":"Simon","email":"","middleInitial":"R.","affiliations":[{"id":33648,"text":"Department of Geological Sciences and Engineering, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":826900,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tyler, Scott W.","contributorId":188141,"corporation":false,"usgs":false,"family":"Tyler","given":"Scott","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":826901,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70226191,"text":"70226191 - 2021 - A practical solution: The Anthropocene is a geological event, not a formal epoch","interactions":[],"lastModifiedDate":"2024-12-19T23:22:33.67191","indexId":"70226191","displayToPublicDate":"2021-11-15T06:45:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1582,"text":"Episodes","active":true,"publicationSubtype":{"id":10}},"title":"A practical solution: The Anthropocene is a geological event, not a formal epoch","docAbstract":"<div id=\"origin_a\" class=\"origin_a\"><div class=\"inner_content\"><div id=\"body00\" class=\"origin_section03\"><div id=\"fulltext_Area\" class=\"go_section\"><p>The Anthropocene has yet to be defined in a way that is functional both to the international geological community and to the broader fields of environmental and social sciences. Formally defining the Anthropocene as a chronostratigraphical series and geochronological epoch with a precise global start date would drastically reduce the Anthropocene’s utility across disciplines. Instead, we propose the Anthropocene be defined as a geological event, thereby facilitating a robust geological definition linked with a scholarly framework more useful to and congruent with the many disciplines engaging with human-environment interactions. Unlike formal epochal definitions, geological events can recognize the spatial and temporal heterogeneity and diverse social and environmental processes that interact to produce anthropogenic global environmental changes. Consequently, an Anthropocene Event would incorporate a far broader range of transformative human cultural practices and would be more readily applicable across academic fields than an Anthropocene Epoch, while still enabling a robust stratigraphic characterization.</p></div></div></div></div>","language":"English","publisher":"International Union of Geological Sciences","doi":"10.18814/epiiugs/2021/021029","usgsCitation":"Gibbard, P., Bauer, A.M., Edgeworth, M., Ruddiman, W.F., Gill, J.L., Merritts, D.J., Finney, S.C., Edwards, L.E., Walker, M.J., Maslin, M., and Ellis, E.C., 2021, A practical solution: The Anthropocene is a geological event, not a formal epoch: Episodes, v. 45, no. 4, p. 349-357, https://doi.org/10.18814/epiiugs/2021/021029.","productDescription":"9 p.","startPage":"349","endPage":"357","ipdsId":"IP-125676","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":450200,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.18814/epiiugs/2021/021029","text":"Publisher Index Page"},{"id":391734,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gibbard, Philip","contributorId":268859,"corporation":false,"usgs":false,"family":"Gibbard","given":"Philip","email":"","affiliations":[{"id":55697,"text":"Scott Polar Research Institute, University of Cambridge, Cambridge, CB2 1ER, UK","active":true,"usgs":false}],"preferred":false,"id":826824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bauer, Andrew M","contributorId":268860,"corporation":false,"usgs":false,"family":"Bauer","given":"Andrew","email":"","middleInitial":"M","affiliations":[{"id":55699,"text":"Department of Anthropology, Stanford University, Stanford, CA 94305, USA","active":true,"usgs":false}],"preferred":false,"id":826825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edgeworth, Matthew","contributorId":268861,"corporation":false,"usgs":false,"family":"Edgeworth","given":"Matthew","email":"","affiliations":[{"id":55700,"text":"School of Archaeology and Ancient History, University of Leicester, Leicester LE1 7RH, UK","active":true,"usgs":false}],"preferred":false,"id":826826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruddiman, William F","contributorId":268862,"corporation":false,"usgs":false,"family":"Ruddiman","given":"William","email":"","middleInitial":"F","affiliations":[{"id":40362,"text":"Department of Environmental Sciences, University of Virginia, Charlottesville, VA 22904, USA","active":true,"usgs":false}],"preferred":false,"id":826827,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gill, Jacquelyn L.","contributorId":265257,"corporation":false,"usgs":false,"family":"Gill","given":"Jacquelyn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":826828,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Merritts, Dorothy J.","contributorId":268863,"corporation":false,"usgs":false,"family":"Merritts","given":"Dorothy","email":"","middleInitial":"J.","affiliations":[{"id":55702,"text":"Department of Earth and Environment, Franklin and Marshall College, Post Office Box 3003, Lancaster, PA 17604, USA","active":true,"usgs":false}],"preferred":false,"id":826829,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Finney, Stanley C.","contributorId":167284,"corporation":false,"usgs":false,"family":"Finney","given":"Stanley","email":"","middleInitial":"C.","affiliations":[{"id":24675,"text":"California State University at Long Beach","active":true,"usgs":false}],"preferred":false,"id":826830,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Edwards, Lucy E. 0000-0003-4075-3317 leedward@usgs.gov","orcid":"https://orcid.org/0000-0003-4075-3317","contributorId":2647,"corporation":false,"usgs":true,"family":"Edwards","given":"Lucy","email":"leedward@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":826831,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Walker, Michael J.C.","contributorId":268864,"corporation":false,"usgs":false,"family":"Walker","given":"Michael","email":"","middleInitial":"J.C.","affiliations":[{"id":55703,"text":"Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, Wales","active":true,"usgs":false}],"preferred":false,"id":826832,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Maslin, Mark","contributorId":268865,"corporation":false,"usgs":false,"family":"Maslin","given":"Mark","email":"","affiliations":[{"id":55704,"text":"University College, London & Nat'l History Museum, Denmark","active":true,"usgs":false}],"preferred":false,"id":826833,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ellis, Erle C.","contributorId":268866,"corporation":false,"usgs":false,"family":"Ellis","given":"Erle","middleInitial":"C.","affiliations":[{"id":55705,"text":"Department of Geography and Environmental Systems, University of Maryland, Baltimore County, Baltimore, Maryland 21250, USA","active":true,"usgs":false}],"preferred":false,"id":826834,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70229198,"text":"70229198 - 2021 - Syn-eruptive hydration of volcanic ash records pyroclast-water interaction in explosive eruptions","interactions":[],"lastModifiedDate":"2022-03-02T12:48:25.371404","indexId":"70229198","displayToPublicDate":"2021-11-15T06:39:51","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Syn-eruptive hydration of volcanic ash records pyroclast-water interaction in explosive eruptions","docAbstract":"<div class=\"article-section__content en main\"><p>Magma-water interaction can dramatically influence the explosivity of volcanic eruptions. However, syn- and post-eruptive diffusion of external (non-magmatic) water into volcanic glass remains poorly constrained and may bias interpretation of water in juvenile products. Hydrogen isotopes in ash from the 2009 eruption of Redoubt Volcano, Alaska, record syn-eruptive hydration by vaporized glacial meltwater. Both ash aggregation and hydration occurred in the wettest regions of the plume, which resulted in the removal and deposition of the most hydrated ash in proximal areas &lt;50&nbsp;km from the vent. Diffusion models show that the high temperatures of pyroclast-water interactions (&gt;400°C) are more important than the cooling rate in facilitating hydration. These observations suggest that syn-eruptive glass hydration occurred where meltwater was entrained at high temperature, in the plume margins near the vent. Ash in the drier plume interior remained insulated from entrained meltwater until it cooled sufficiently to avoid significant hydration.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL094141","usgsCitation":"Hudak, M.R., Bindeman, I.N., Loewen, M.W., and Giachetti, T., 2021, Syn-eruptive hydration of volcanic ash records pyroclast-water interaction in explosive eruptions: Geophysical Research Letters, v. 48, no. 23, e2021GL094141, 8 p., https://doi.org/10.1029/2021GL094141.","productDescription":"e2021GL094141, 8 p.","ipdsId":"IP-129298","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":450202,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021gl094141","text":"Publisher Index Page"},{"id":396643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"23","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hudak, Michael R. 0000-0002-0583-5424","orcid":"https://orcid.org/0000-0002-0583-5424","contributorId":287589,"corporation":false,"usgs":false,"family":"Hudak","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":836914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bindeman, Ilya N.","contributorId":175500,"corporation":false,"usgs":false,"family":"Bindeman","given":"Ilya","email":"","middleInitial":"N.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":836915,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loewen, Matthew W. 0000-0002-5621-285X","orcid":"https://orcid.org/0000-0002-5621-285X","contributorId":213321,"corporation":false,"usgs":true,"family":"Loewen","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":836916,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giachetti, Thomas 0000-0003-1360-6768","orcid":"https://orcid.org/0000-0003-1360-6768","contributorId":287591,"corporation":false,"usgs":false,"family":"Giachetti","given":"Thomas","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":836917,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70226182,"text":"70226182 - 2021 - Context dependency of disease-mediated competitive release in bat assemblages following white-nose syndrome","interactions":[],"lastModifiedDate":"2021-11-16T12:58:22.531567","indexId":"70226182","displayToPublicDate":"2021-11-14T06:56:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Context dependency of disease-mediated competitive release in bat assemblages following white-nose syndrome","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>White-nose syndrome (WNS) has caused dramatic declines of several cave-hibernating bat species in North America since 2006, which has increased the activity of non-susceptible species in some geographic areas or during times of night formerly occupied by susceptible species—indicative of disease-mediated competitive release (DMCR). Yet, this pattern has not been evaluated across multiple bat assemblages simultaneously or across multiple years since WNS onset. We evaluated whether WNS altered spatial and temporal niche partitioning in bat assemblages at four locations in the eastern United States using long-term datasets of bat acoustic activity collected before and after WNS arrival. Activity of WNS-susceptible bat species decreased by 79–98% from pre-WNS levels across the four study locations, but only one of our four study sites provided strong evidence supporting the DMCR hypothesis in bats post-WNS. These results suggest that DMCR is likely dependent on the relative difference in activity by susceptible and non-susceptible species groups pre-WNS and the relative decline of susceptible species post-WNS allowing for competitive release, as well as the amount of time that had elapsed post-WNS. Our findings challenge the generality of WNS-mediated competitive release between susceptible and non-susceptible species and further highlight declining activity of some non-susceptible species, especially<span>&nbsp;</span><i>Lasiurus borealis</i>, across three of four locations in the eastern United States. These results underscore the broader need for conservation efforts to address the multiple potential interacting drivers of bat declines on both WNS-susceptible and non-susceptible species.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3825","usgsCitation":"Bombaci, S., Russell, R., St. Germain, M.J., Dobony, C., Ford, W., Loeb, S., and Jachowski, D., 2021, Context dependency of disease-mediated competitive release in bat assemblages following white-nose syndrome: Ecosphere, v. 12, no. 11, e03825, 15 p., https://doi.org/10.1002/ecs2.3825.","productDescription":"e03825, 15 p.","ipdsId":"IP-111761","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":450204,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecs2.3825","text":"External Repository"},{"id":391739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Bombaci, Sara","contributorId":268816,"corporation":false,"usgs":false,"family":"Bombaci","given":"Sara","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":826736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Robin E. 0000-0001-8726-7303","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":219536,"corporation":false,"usgs":true,"family":"Russell","given":"Robin E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":826740,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"St. Germain, Michael J.","contributorId":25959,"corporation":false,"usgs":false,"family":"St. Germain","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":826737,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dobony, Christopher A.","contributorId":264897,"corporation":false,"usgs":false,"family":"Dobony","given":"Christopher A.","affiliations":[{"id":54576,"text":"DoD","active":true,"usgs":false}],"preferred":false,"id":826741,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":826738,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loeb, Susan","contributorId":204263,"corporation":false,"usgs":false,"family":"Loeb","given":"Susan","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":826739,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jachowski, David S.","contributorId":228814,"corporation":false,"usgs":false,"family":"Jachowski","given":"David S.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":826742,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70226573,"text":"70226573 - 2021 - Origin of the J-M Reef and Lower Banded series, Stillwater Complex, Montana, USA","interactions":[],"lastModifiedDate":"2021-11-29T12:47:16.345696","indexId":"70226573","displayToPublicDate":"2021-11-14T06:45:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3112,"text":"Precambrian Research","active":true,"publicationSubtype":{"id":10}},"title":"Origin of the J-M Reef and Lower Banded series, Stillwater Complex, Montana, USA","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab010\" class=\"abstract author\" lang=\"en\"><div id=\"as010\"><p id=\"sp0010\">The origin and parental magma for layered cumulates in the Lower Banded series (LBS) and the J-M Reef Pd-Pt deposit of the Stillwater Complex remains poorly constrained. We present whole-rock lithogeochemistry and mineral chemistry from LBS rocks collected from drill holes and surface samples from the Mountain View area of the complex that in total span nearly the entirety of the LBS stratigraphy. Excess S, Pt, and Pd in the noritic and gabbronoritic cumulates of the LBS indicate that small amounts of high tenor sulfide liquid generated at very low degrees of sulfide oversaturation were ubiquitous parts of the cumulate assemblage. We show that a simple two-stage thermodynamic model of assimilation-batch crystallization of a komatiitic parental magma in the lower crust, produces a close match to a common suite of fine-grained gabbronorite dikes and sills that intrude both the complex and its footwall. After fractionating ultramafic cumulates in the lower crust, the model contaminated komatiitic liquid produces upper crustal cumulates by batch crystallization<span>&nbsp;</span><i>en route</i><span>&nbsp;</span>to or at the level of the intrusion. The modeled rocks have compositions and mineral assemblages closely resembling pyroxenite of the Bronzitite zone and both norite and gabbronorite cumulates in the lower LBS. The trends from the Bronzitite zone through Norite zone I and Gabbronorite zone I can be understood as the result of deposition of crystals from successive batches of the same contaminated parental magma, with an upward trend toward greater amounts of cooling before the separation of crystals from liquid. The olivine-bearing suite of Olivine-bearing zone I, which includes the J-M Reef, can be modeled by partial remelting of the same norite and gabbronorite cumulates due to a temporarily increased flux of hot, moderately less contaminated LBS parental magma that infiltrated partially molten cumulates because its density exceeded that of the interstitial liquid. This model suggests that infiltration of hot Mg-rich parental liquid into moderately PGE-enriched footwall cumulates may be fundamental to the formation of the extremely high tenor sulfide mineralization in the J-M Reef ore zone, and perhaps other reef-type deposits worldwide. The same metal tenors that would require silicate/sulfide mass ratios (i.e., R-factors) of 10<sup>5</sup><span>&nbsp;</span>to 10<sup>6</sup><span>&nbsp;</span>in a single stage of equilibration would be attained during this second stage of interaction by the incremental infiltration and passage of LBS parental magma through previously sulfide saturated cumulate mush.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.precamres.2021.106457","usgsCitation":"Jenkins, M., Mungall, J.E., Zientek, M., Costin, G., and Yao, Z., 2021, Origin of the J-M Reef and Lower Banded series, Stillwater Complex, Montana, USA: Precambrian Research, v. 367, 106457, 21 p., https://doi.org/10.1016/j.precamres.2021.106457.","productDescription":"106457, 21 p.","ipdsId":"IP-131760","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":450208,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.precamres.2021.106457","text":"Publisher Index Page"},{"id":392178,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.478515625,\n              45.62172169252446\n            ],\n            [\n              -109.51171875,\n              45.120052841530544\n            ],\n            [\n              -109.259033203125,\n              45.36758436884978\n            ],\n            [\n              -110.25878906249999,\n              45.78284835197676\n            ],\n            [\n              -110.478515625,\n              45.62172169252446\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"367","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jenkins, Michael 0000-0002-4261-409X mjenkins@usgs.gov","orcid":"https://orcid.org/0000-0002-4261-409X","contributorId":172433,"corporation":false,"usgs":true,"family":"Jenkins","given":"Michael","email":"mjenkins@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":827387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mungall, James E. 0000-0001-9726-8545","orcid":"https://orcid.org/0000-0001-9726-8545","contributorId":269537,"corporation":false,"usgs":false,"family":"Mungall","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":827388,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zientek, Michael L. 0000-0002-8522-9626","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":210763,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":827389,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Costin, Gelu 0000-0003-3054-7886","orcid":"https://orcid.org/0000-0003-3054-7886","contributorId":269538,"corporation":false,"usgs":false,"family":"Costin","given":"Gelu","email":"","affiliations":[{"id":7173,"text":"Rice University","active":true,"usgs":false}],"preferred":false,"id":827390,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yao, Zhuo-sen 0000-0002-5075-0745","orcid":"https://orcid.org/0000-0002-5075-0745","contributorId":269539,"corporation":false,"usgs":false,"family":"Yao","given":"Zhuo-sen","email":"","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":827391,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70232163,"text":"70232163 - 2021 - Climatic aridity shapes post-fire interactions between Ceanothus spp. and Douglas-fir (Pseudotsuga menziesii) across the Klamath Mountains","interactions":[],"lastModifiedDate":"2022-06-09T13:21:53.228665","indexId":"70232163","displayToPublicDate":"2021-11-13T08:18:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1689,"text":"Forests","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Climatic aridity shapes post-fire interactions between <i>Ceanothus</i> spp. and Douglas-fir (<i>Pseudotsuga menziesii</i>) across the Klamath Mountains","title":"Climatic aridity shapes post-fire interactions between Ceanothus spp. and Douglas-fir (Pseudotsuga menziesii) across the Klamath Mountains","docAbstract":"<p><span>Climate change is leading to increased drought intensity and fire frequency, creating early-successional landscapes with novel disturbance–recovery dynamics. In the Klamath Mountains of northwestern California and southwestern Oregon, early-successional interactions between nitrogen (N)-fixing shrubs (</span><i><span class=\"html-italic\">Ceanothus</span></i><span>&nbsp;spp.) and long-lived conifers (Douglas-fir) are especially important determinants of forest development. We sampled post-fire vegetation and soil biogeochemistry in 57 plots along gradients of time since fire (7–28 years) and climatic water deficit (aridity). We found that&nbsp;</span><i><span class=\"html-italic\">Ceanothus</span></i><span>&nbsp;biomass increased, and Douglas-fir biomass decreased with increasing aridity. High aridity and&nbsp;</span><i><span class=\"html-italic\">Ceanothus</span></i><span>&nbsp;biomass interacted with lower soil C:N more than either factor alone.&nbsp;</span><i><span class=\"html-italic\">Ceanothus</span></i><span><i>&nbsp;</i>biomass was initially high after fire and declined with time, suggesting a large initial pulse of N-fixation that could enhance N availability for establishing Douglas-fir. We conclude that future increases in aridity and wildfire frequency will likely limit post-fire Douglas-fir establishment, though&nbsp;</span><i><span class=\"html-italic\">Ceanothus</span></i><span>&nbsp;may ameliorate some of these impacts through benefits to microclimate and soils. Results from this study contribute to our understanding of the effects of climate change and wildfires on interspecific interactions and forest dynamics. Management seeking to accelerate forest recovery after high-severity fire should emphasize early-successional conifer establishment while maintaining N-fixing shrubs to enhance soil fertility.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/f12111567","usgsCitation":"Cinoglu, D., Epstein, H., Tepley, A.J., Anderson-Teixeira, K.J., Thompson, J.R., and Perakis, S.S., 2021, Climatic aridity shapes post-fire interactions between Ceanothus spp. and Douglas-fir (Pseudotsuga menziesii) across the Klamath Mountains: Forests, v. 12, no. 11, 1567, 15 p., https://doi.org/10.3390/f12111567.","productDescription":"1567, 15 p.","ipdsId":"IP-133295","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":450213,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/f12111567","text":"Publisher Index Page"},{"id":401970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.47509765625,\n              40.622291783092706\n            ],\n            [\n              -122.431640625,\n              40.622291783092706\n            ],\n            [\n              -122.431640625,\n              42.342305278572816\n            ],\n            [\n              -124.47509765625,\n              42.342305278572816\n            ],\n            [\n              -124.47509765625,\n              40.622291783092706\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-11-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Cinoglu, Damla","contributorId":292365,"corporation":false,"usgs":false,"family":"Cinoglu","given":"Damla","email":"","affiliations":[{"id":34217,"text":"UT Austin","active":true,"usgs":false}],"preferred":false,"id":844406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Epstein, Howard E","contributorId":292366,"corporation":false,"usgs":false,"family":"Epstein","given":"Howard E","affiliations":[{"id":62885,"text":"UVA","active":true,"usgs":false}],"preferred":false,"id":844407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tepley, Alan J.","contributorId":139993,"corporation":false,"usgs":false,"family":"Tepley","given":"Alan","email":"","middleInitial":"J.","affiliations":[{"id":13346,"text":"University of Colorado at Boulder, Department of Geography","active":true,"usgs":false}],"preferred":false,"id":844408,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson-Teixeira, Kristina J. 0000-0001-8461-9713","orcid":"https://orcid.org/0000-0001-8461-9713","contributorId":150956,"corporation":false,"usgs":false,"family":"Anderson-Teixeira","given":"Kristina","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":844409,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Jonathan R.","contributorId":292368,"corporation":false,"usgs":false,"family":"Thompson","given":"Jonathan","email":"","middleInitial":"R.","affiliations":[{"id":37315,"text":"Harvard","active":true,"usgs":false}],"preferred":false,"id":844410,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":844411,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70226157,"text":"70226157 - 2021 - Depths inferred from velocities estimated by remote sensing: A flow resistance equation-based approach to mapping multiple river attributes at the reach scale","interactions":[],"lastModifiedDate":"2021-11-15T12:13:19.787666","indexId":"70226157","displayToPublicDate":"2021-11-13T06:10:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Depths inferred from velocities estimated by remote sensing: A flow resistance equation-based approach to mapping multiple river attributes at the reach scale","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">Remote sensing of flow conditions in stream channels could facilitate hydrologic data collection, particularly in large, inaccessible rivers. Previous research has demonstrated the potential to estimate flow velocities in sediment-laden rivers via particle image velocimetry (PIV). In this study, we introduce a new framework for also obtaining bathymetric information: Depths Inferred from Velocities Estimated by Remote Sensing (DIVERS). This approach is based on a flow resistance equation and involves several assumptions: steady, uniform, one-dimensional flow and a direct proportionality between the velocity estimated at a given location and the local water depth, with no lateral transfer of mass or momentum. As an initial case study, we performed PIV and inferred depths from videos acquired from a helicopter hovering at multiple waypoints along a large river in central Alaska. The accuracy of PIV-derived velocities was assessed via comparison to field measurements and the performance of an optimization-based approach to DIVERS specification of roughness</div>","language":"English","publisher":"MDPI","doi":"10.3390/rs13224566","usgsCitation":"Legleiter, C.J., and Kinzel, P.J., 2021, Depths inferred from velocities estimated by remote sensing: A flow resistance equation-based approach to mapping multiple river attributes at the reach scale: Remote Sensing, v. 13, no. 22, 4566, 34 p., https://doi.org/10.3390/rs13224566.","productDescription":"4566, 34 p.","ipdsId":"IP-129764","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":450216,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13224566","text":"Publisher Index Page"},{"id":436117,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A7J0AN","text":"USGS data release","linkHelpText":"Helicopter-based videos and field measurements of flow depth and velocity from the Tanana River, Alaska, acquired on July 24, 2019"},{"id":391672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Fairbanks","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -148.16162109375,\n              64.60503753178527\n            ],\n            [\n              -147.13989257812497,\n              64.60503753178527\n            ],\n            [\n              -147.13989257812497,\n              65.03042310440534\n            ],\n            [\n              -148.16162109375,\n              65.03042310440534\n            ],\n            [\n              -148.16162109375,\n              64.60503753178527\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"22","noUsgsAuthors":false,"publicationDate":"2021-11-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":826683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":826684,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70226134,"text":"sir20215127 - 2021 - Total phosphorus loadings for the Cedar River at Palo, Iowa, 2009–20","interactions":[],"lastModifiedDate":"2021-11-15T11:55:16.375506","indexId":"sir20215127","displayToPublicDate":"2021-11-12T18:05:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5127","displayTitle":"Total Phosphorus Loadings for the Cedar River at Palo, Iowa, 2009–20","title":"Total phosphorus loadings for the Cedar River at Palo, Iowa, 2009–20","docAbstract":"<p>In support of nutrient reduction efforts, total phosphorus loads and yields were computed using turbidity-surrogate and LOAD ESTimator (LOADEST) models for the Cedar River at Palo, Iowa, for January 1, 2009, to December 15, 2020. Sample data were used to create a total phosphorus concentration turbidity-surrogate model. Total phosphorus loads also were computed from two streamflow-based LOADEST load models for the periods 2009–20 and 2016–20. The 2009–20 model was used for comparison with previously published loads at this site. The 2016–20 LOADEST model was used with the turbidity-surrogate model before sensor deployment and during periods of missing sensor data to obtain a more complete annual total phosphorus load. This report presents computed loads and methods needed to compute site-specific loads accurately and track annual progress toward nutrient reduction goals within the State.</p><p>A comparison of loads from Weighted Regressions on Time, Discharge, and Season; LOADEST; and surrogate models indicated substantial differences at this site among these methods. Changes in both monitoring approaches (high-frequency sensor and surrogate data) and changes in load-calculation methods present potential challenges in assessing trends, such as assessment of load reduction.</p><p>Annual total phosphorus loads for the Cedar River at Palo, Iowa, ranged from 1,370 to 2,360 U.S. short tons per year for 2018–20, based on the turbidity-surrogate model with gaps in sensor data filled with the 2016–20 LOADEST model. Annual total phosphorus yields for the Cedar River ranged from 0.67 to 1.16 pounds per acre per year for 2018–20. Although this load estimate is lower than previous estimates for the benchmark period of 2006–10, when normalized by streamflow, nearly all the apparent reduction can be attributed to differences in the load-calculation methods.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215127","collaboration":"Prepared in cooperation with the City of Cedar Rapids","usgsCitation":"Garrett, J.D., 2021, Total phosphorus loadings for the Cedar River at Palo, Iowa, 2009–20: U.S. Geological Survey Scientific Investigations Report 2021–5127, 15 p., https://doi.org/10.3133/sir20215127.","productDescription":"Report vi, 15 p.: Database; Related Work","onlineOnly":"Y","ipdsId":"IP-127065","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":391620,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5127/coverthb.jpg"},{"id":391621,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5127/sir20215127.pdf","text":"Report","size":"2.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5127"},{"id":391622,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System—","linkHelpText":"U.S. Geological Survey National Water Information System database"},{"id":391623,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20185090","text":"Transport of nitrogen and phosphorus in the Cedar River Basin, Iowa and Minnesota, 2000–15"}],"country":"United States","state":"Palo","otherGeospatial":"Cedar River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.83197021484375,\n              42.02889410108475\n            ],\n            [\n              -91.71180725097655,\n              42.02889410108475\n            ],\n            [\n              -91.71180725097655,\n              42.09312731992276\n            ],\n            [\n              -91.83197021484375,\n              42.09312731992276\n            ],\n            [\n              -91.83197021484375,\n              42.02889410108475\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"http://www.usgs.gov/centers/cm-water/\" data-mce-href=\"http://www.usgs.gov/centers/cm-water/\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>400 South Clinton Street, Suite 269<br>Iowa City, IA 52240</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods for Data Collection and Computation</li><li>Water-Quality Sample and Sensor Data</li><li>Continuous Water-Quality Time-Series Data to Compute Nutrient Loadings</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2021-11-12","noUsgsAuthors":false,"publicationDate":"2021-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Garrett, Jessica D. 0000-0002-4466-3709 jgarrett@usgs.gov","orcid":"https://orcid.org/0000-0002-4466-3709","contributorId":4229,"corporation":false,"usgs":true,"family":"Garrett","given":"Jessica","email":"jgarrett@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826587,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70225933,"text":"sir20215106 - 2021 - Water and sediment chemistry of selected existing and potential habitats of the Mohave tui chub, Mojave National Preserve, California, 2018","interactions":[],"lastModifiedDate":"2021-11-15T11:47:37.497179","indexId":"sir20215106","displayToPublicDate":"2021-11-12T09:28:27","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5106","displayTitle":"Water and Sediment Chemistry of Selected Existing and Potential Habitats of the Mohave Tui Chub, Mojave National Preserve, California, 2018","title":"Water and sediment chemistry of selected existing and potential habitats of the Mohave tui chub, Mojave National Preserve, California, 2018","docAbstract":"<p>The Mohave tui chub (<i>Siphateles bicolor mohavensis</i>) was nearly extirpated from the Mojave River drainage in California by the mid-twentieth century and was listed as endangered in 1970. A source population of Mohave tui chub exists at MC Spring in Zzyzx, California, and has been used for several re-establishment efforts in previous decades. Two potential habitats in the Mojave National Preserve with perennial sources of water were identified by the National Park Service as candidates for additional Mohave tui chub re-establishment: West Pond and Rainbow Wells Pond. West Pond, an artificial pond at Zzyzx near MC Spring, contained a population of Mohave tui chub that died off in 1985 because of changes in water quality. The pond was rehabilitated in the past several years through re-excavation and by pumping fresh groundwater into the pond. Rainbow Wells Pond is an abandoned excavated mine site in the Cima Dome area. The bottom of the excavation intersects the water table, forming a pond. In cooperation with the National Park Service, the U.S. Geological Survey monitored water-quality conditions at West Pond and Rainbow Wells Pond for 1 year to characterize the suitability of spring habitat for re-establishment of Mohave tui chub populations. Data were also collected at three existing Mohave tui chub habitats in Mojave National Preserve to provide further information on the range of acceptable physical and chemical conditions. Initial water-quality results at West Pond indicate the pond has similar water quality as existing Mohave tui chub habitats. Initial water-quality results at Rainbow Wells Pond indicate the dissolved oxygen concentrations and springtime water temperatures are less than the long-term tolerable ranges for Mohave tui chub.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215106","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Earp, K.J., and Paul, A.P., 2021, Water and sediment chemistry of selected existing and potential habitats of the Mohave tui chub, Mojave National Preserve, California, 2018: U.S. Geological Survey Scientific Investigations Report 2021–5106, 26 p., https://doi.org/10.3133/sir20215106.","productDescription":"Report: v, 26 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-099414","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":391580,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","linkHelpText":"National Water Information System"},{"id":391576,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5106/covrthb.jpg"},{"id":391577,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5106/sir20215106.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":391578,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5106/sir20215106.xml"},{"id":391579,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5106/images"}],"country":"United States","state":"California","otherGeospatial":"Mojave National Preserve","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.2301025390625,\n              35.47409160773029\n            ],\n            [\n              -115.36193847656249,\n              35.54116627999815\n            ],\n            [\n              -115.59814453125001,\n              35.55457449014312\n            ],\n            [\n              -115.806884765625,\n              35.567980458012094\n            ],\n            [\n              -116.43859863281249,\n              35.38457160381764\n            ],\n            [\n              -116.55944824218749,\n              35.074964853989556\n            ],\n            [\n              -116.54296874999999,\n              34.79576153473033\n            ],\n            [\n              -116.16943359374999,\n              34.56085936708384\n            ],\n            [\n              -115.7080078125,\n              34.36611072883117\n            ],\n            [\n              -115.224609375,\n              34.261756524459805\n            ],\n            [\n              -114.72473144531251,\n              34.30260622622907\n            ],\n            [\n              -114.58740234375,\n              34.58347505599177\n            ],\n            [\n              -114.6368408203125,\n              34.84536693184101\n            ],\n            [\n              -114.6533203125,\n              35.016500995886005\n            ],\n            [\n              -115.2301025390625,\n              35.47409160773029\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_nv@usgs.gov\" data-mce-href=\"mailto:dc_nv@usgs.gov\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/nv-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/nv-water\">Nevada Water Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>2730 N. Deer Run Road<br>Carson City, Nevada 95819</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods of Study</li><li>Water and Sediment Chemistry</li><li>Suitability of Potential Habitats: Rainbow Wells Pond and West Pond</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2021-11-12","noUsgsAuthors":false,"publicationDate":"2021-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Earp, Katherine J. 0000-0002-5291-6737 kjearp@usgs.gov","orcid":"https://orcid.org/0000-0002-5291-6737","contributorId":223704,"corporation":false,"usgs":true,"family":"Earp","given":"Katherine","email":"kjearp@usgs.gov","middleInitial":"J.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paul, Angela P. 0000-0003-3909-1598 appaul@usgs.gov","orcid":"https://orcid.org/0000-0003-3909-1598","contributorId":2305,"corporation":false,"usgs":true,"family":"Paul","given":"Angela","email":"appaul@usgs.gov","middleInitial":"P.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826578,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70226175,"text":"70226175 - 2021 - Responses of American black bears to spring resources","interactions":[],"lastModifiedDate":"2021-11-16T13:04:24.026217","indexId":"70226175","displayToPublicDate":"2021-11-12T07:02:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Responses of American black bears to spring resources","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>In temperate regions of the world, food resources are seasonally limited, which causes some wildlife species to seek out nutrient-rich resources to better meet their caloric needs. Animals that utilize high-quality resources may reap fitness benefits as they prepare for mating, migration, or hibernation. American black bears (<i>Ursus americanus</i>) are omnivores that consume both plant and animal food resources to meet macronutrient needs. Black bears capitalize on high-quality food resources, such as soft mast in summer and hard mast during autumn, but we know less about the importance of resource quality during spring. Therefore, we sought to understand the relationship between the spatiotemporal variation in the availability of food and resource selection of black bears during spring. We also aimed to infer potential changes in foraging tactics, from opportunistic foraging to more active selection. Although black bears are described as opportunistic omnivores, we hypothesized they select areas with high-quality forage when available. We instrumented 7 black bears with GPS collars in 2017 and 2018 and estimated fine-scale resource selection with integrated step-selection functions. We found evidence that black bear movements were influenced by forage quality of vegetative food resources. However, we failed to find evidence that black bears actively alter their movements to take advantage of seasonal neonate elk. Although black bears represent a substantial cause of mortality for neonate elk, we found that black bears likely feed on neonates encountered opportunistically while traveling between patches of high-quality forage. Few studies have shown evidence of an omnivorous species capitalizing on spatiotemporal variation in forage quality, yet our data suggest this may be an important strategy for species with diverse diets, particularly where resources are seasonally limited.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3773","usgsCitation":"Bowersock, N.R., Litt, A.R., Merkle, J., Gunther, K.A., and van Manen, F.T., 2021, Responses of American black bears to spring resources: Ecosphere, v. 12, no. 11, e03773, 13 p., https://doi.org/10.1002/ecs2.3773.","productDescription":"e03773, 13 p.","ipdsId":"IP-119970","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":450219,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecs2.3773","text":"External Repository"},{"id":391742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","otherGeospatial":"Northern Range, Yellowstone National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.994873046875,\n              44.32384807250687\n            ],\n            [\n              -109.039306640625,\n              44.32384807250687\n            ],\n            [\n              -109.039306640625,\n              45.66780526567164\n            ],\n            [\n              -110.994873046875,\n              45.66780526567164\n            ],\n            [\n              -110.994873046875,\n              44.32384807250687\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Bowersock, Nathaniel R.","contributorId":268804,"corporation":false,"usgs":false,"family":"Bowersock","given":"Nathaniel","email":"","middleInitial":"R.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":826716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Litt, Andrea R.","contributorId":208358,"corporation":false,"usgs":false,"family":"Litt","given":"Andrea","email":"","middleInitial":"R.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":826717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merkle, Jerod A.","contributorId":264421,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod A.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":826718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gunther, Kerry A.","contributorId":84621,"corporation":false,"usgs":false,"family":"Gunther","given":"Kerry","email":"","middleInitial":"A.","affiliations":[{"id":5118,"text":"Yellowstone National Park, Yellowstone Center for Resources, Bear Management Office, P.O. Box 168, Yellowstone National Park, WY 82190","active":true,"usgs":false}],"preferred":false,"id":826719,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":826720,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70226891,"text":"70226891 - 2021 - Modeling scenarios for the management of axis deer in Hawai‘i","interactions":[],"lastModifiedDate":"2021-12-20T12:45:15.217793","indexId":"70226891","displayToPublicDate":"2021-11-12T06:41:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2990,"text":"Pacific Science","active":true,"publicationSubtype":{"id":10}},"title":"Modeling scenarios for the management of axis deer in Hawai‘i","docAbstract":"<div class=\"div0\"><div class=\"row ArticleContentRow\"><p id=\"ID0EF\" class=\"first\">Axis deer (<i>Axis axis</i>) are invasive species that threaten native ecosystems and agriculture on Maui Island. To mitigate negative effects, it is necessary to understand current abundance, population trajectory, and how to most effectively reduce the population. Our objectives were to examine the population history of Maui axis deer, estimate observed population growth, and use species-specific demographic parameters in a VORTEX population viability analysis to examine removal scenarios that would most effectively reduce the population. Only nine deer were introduced in 1959, but recent estimates of &gt;10,000 deer suggest population growth rates (<i>r</i>) ranging between 0.147 and 0.160 even though &gt;11,200 have been removed by hunters and resource managers. In VORTEX simulations, we evaluated an initial population size of 6,000 females and 4,000 males, reflecting the probable 3F:2M sex ratio, with annual removal rates of 10%, 20%, and 30% over a 10-year period. A removal rate of 10% resulted in a positive growth rate of 0.103 ± 0.001. A 20% removal rate resulted in only a slightly negative growth, while a 30% removal rate resulted in –0.130 ± 0.004. By increasing the ratio of females removed to 4F:1M in the 30% harvest scenario, the decline nearly doubled, resulting in –0.223 ± 0.004. Effectively reducing axis deer will most likely require an annual removal of approximately 20–30% of the population and with a greater proportion of females to increase the population decline. Selective removal of males may not only be inefficient, but also counterproductive to population reduction goals.</p></div></div>","language":"English","publisher":"BioOne","doi":"10.2984/75.4.8","usgsCitation":"Hess, S.C., and Judge, S., 2021, Modeling scenarios for the management of axis deer in Hawai‘i: Pacific Science, v. 75, no. 4, p. 561-573, https://doi.org/10.2984/75.4.8.","productDescription":"13 p.","startPage":"561","endPage":"573","ipdsId":"IP-109382","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":450221,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2984/75.4.8","text":"Publisher Index Page"},{"id":436118,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QXKE7Y","text":"USGS data release","linkHelpText":"Maui Island Modeling Scenarios for the Management of Axis Deer 1959-2014"},{"id":393091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -160.56518554687497,\n              18.750309813140653\n            ],\n            [\n              -154.500732421875,\n              18.750309813140653\n            ],\n            [\n              -154.500732421875,\n              22.421184710331858\n            ],\n            [\n              -160.56518554687497,\n              22.421184710331858\n            ],\n            [\n              -160.56518554687497,\n              18.750309813140653\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"75","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hess, Steve C. 0000-0001-6403-9922 shess@usgs.gov","orcid":"https://orcid.org/0000-0001-6403-9922","contributorId":150366,"corporation":false,"usgs":true,"family":"Hess","given":"Steve","email":"shess@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":828661,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Judge, Seth 0000-0003-3832-3246","orcid":"https://orcid.org/0000-0003-3832-3246","contributorId":189965,"corporation":false,"usgs":false,"family":"Judge","given":"Seth","email":"","affiliations":[],"preferred":false,"id":828660,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70226147,"text":"70226147 - 2021 - Recent nitrogen storage and accumulation rates in mangrove soils exceed historic rates in the urbanized San Juan Bay Estuary (Puerto Rico, United States)","interactions":[],"lastModifiedDate":"2021-11-15T12:30:33.841543","indexId":"70226147","displayToPublicDate":"2021-11-12T06:27:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5860,"text":"Frontiers in Forests and Global Change","active":true,"publicationSubtype":{"id":10}},"title":"Recent nitrogen storage and accumulation rates in mangrove soils exceed historic rates in the urbanized San Juan Bay Estuary (Puerto Rico, United States)","docAbstract":"<div class=\"JournalAbstract\"><p class=\"mb0\">Tropical mangrove forests have been described as “coastal kidneys,” promoting sediment deposition and filtering contaminants, including excess nutrients. Coastal areas throughout the world are experiencing increased human activities, resulting in altered geomorphology, hydrology, and nutrient inputs. To effectively manage and sustain coastal mangroves, it is important to understand nitrogen (N) storage and accumulation in systems where human activities are causing rapid changes in N inputs and cycling. We examined N storage and accumulation rates in recent (1970 – 2016) and historic (1930 – 1970) decades in the context of urbanization in the San Juan Bay Estuary (SJBE, Puerto Rico), using mangrove soil cores that were radiometrically dated. Local anthropogenic stressors can alter N storage rates in peri-urban mangrove systems either directly by increasing N soil fertility or indirectly by altering hydrology (e.g., dredging, filling, and canalization). Nitrogen accumulation rates were greater in recent decades than historic decades at Piñones Forest and Martin Peña East. Martin Peña East was characterized by high urbanization, and Piñones, by the least urbanization in the SJBE. The mangrove forest at Martin Peña East fringed a poorly drained canal and often received raw sewage inputs, with N accumulation rates ranging from 17.7 to 37.9 g m<sup>–2</sup><span>&nbsp;</span>y<sup>–1</sup><span>&nbsp;</span>in recent decades. The Piñones Forest was isolated and had low flushing, possibly exacerbated by river damming, with N accumulation rates ranging from 18.6 to 24.2 g m<sup>–2</sup><span>&nbsp;</span>y<sup>–1</sup><span>&nbsp;</span>in recent decades. Nearly all (96.3%) of the estuary-wide mangrove N (9.4 Mg ha<sup>–1</sup>) was stored in the soils with 7.1 Mg ha<sup>–1</sup><span>&nbsp;</span>sequestered during 1970–2017 (0–18 cm) and 2.3 Mg ha<sup>–1</sup><span>&nbsp;</span>during 1930–1970 (19–28 cm). Estuary-wide mangrove soil N accumulation rates were over twice as great in recent decades (0.18 ± 0.002 Mg ha<sup>–1</sup>y<sup>–1</sup>) than historically (0.08 ± 0.001 Mg ha<sup>–1</sup>y<sup>–1</sup>). Nitrogen accumulation rates in SJBE mangrove soils in recent times were twofold larger than the rate of human-consumed food N that is exported as wastewater (0.08 Mg ha<sup>–1</sup><span>&nbsp;</span>y<sup>–1</sup>), suggesting the potential for mangroves to sequester human-derived N. Conservation and effective management of mangrove forests and their surrounding watersheds in the Anthropocene are important for maintaining water quality in coastal communities throughout tropical regions.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/ffgc.2021.765896","usgsCitation":"Wigand, C., Oczkowski, A., Branoff, B., Eagle, M.J., Hanson, A., Martin, R.M., Balogh, S., Miller, K., Huertas, E., Loffredo, J., and Watson, E., 2021, Recent nitrogen storage and accumulation rates in mangrove soils exceed historic rates in the urbanized San Juan Bay Estuary (Puerto Rico, United States): Frontiers in Forests and Global Change, v. 4, 765896, 16 p., https://doi.org/10.3389/ffgc.2021.765896.","productDescription":"765896, 16 p.","ipdsId":"IP-133587","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":450222,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffgc.2021.765896","text":"Publisher Index Page"},{"id":391677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico, San Juan Bay Estuary","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -66.1761474609375,\n              18.357132362517966\n            ],\n            [\n              -65.93650817871094,\n              18.357132362517966\n            ],\n            [\n              -65.93650817871094,\n              18.48807496255878\n            ],\n            [\n              -66.1761474609375,\n              18.48807496255878\n            ],\n            [\n              -66.1761474609375,\n              18.357132362517966\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"4","noUsgsAuthors":false,"publicationDate":"2021-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Wigand, Cathleen","contributorId":260715,"corporation":false,"usgs":false,"family":"Wigand","given":"Cathleen","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":826642,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oczkowski, Autumn","contributorId":260719,"corporation":false,"usgs":false,"family":"Oczkowski","given":"Autumn","email":"","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":826643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Branoff, Benjamin","contributorId":216871,"corporation":false,"usgs":false,"family":"Branoff","given":"Benjamin","affiliations":[{"id":39539,"text":"University of Puerto Rico, San Juan, PR","active":true,"usgs":false}],"preferred":false,"id":826644,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eagle, Meagan J. 0000-0001-5072-2755 meagle@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":242890,"corporation":false,"usgs":true,"family":"Eagle","given":"Meagan","email":"meagle@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826645,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hanson, Alana","contributorId":260718,"corporation":false,"usgs":false,"family":"Hanson","given":"Alana","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":826646,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Martin, Rose M.","contributorId":211671,"corporation":false,"usgs":false,"family":"Martin","given":"Rose","email":"","middleInitial":"M.","affiliations":[{"id":38313,"text":"Atlantic Ecology Division, Environmental Protection Agency, 27 Tarzwell Dr. Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":826647,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Balogh, Stephen","contributorId":260716,"corporation":false,"usgs":false,"family":"Balogh","given":"Stephen","email":"","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":826648,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Kenneth","contributorId":260717,"corporation":false,"usgs":false,"family":"Miller","given":"Kenneth","affiliations":[{"id":52655,"text":"General Dynamics Information Technology, 6361 Walker Lane, Suite 300 Alexandria, VA","active":true,"usgs":false}],"preferred":false,"id":826649,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Huertas, Evelyn","contributorId":260720,"corporation":false,"usgs":false,"family":"Huertas","given":"Evelyn","email":"","affiliations":[{"id":52656,"text":"US EPA, Caribbean Environmental Protection Division, Guaynabo, PR","active":true,"usgs":false}],"preferred":false,"id":826650,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Loffredo, Joseph","contributorId":260721,"corporation":false,"usgs":false,"family":"Loffredo","given":"Joseph","email":"","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":826651,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Watson, Elizabeth","contributorId":260722,"corporation":false,"usgs":false,"family":"Watson","given":"Elizabeth","affiliations":[{"id":52657,"text":"Department of Biodiversity, Earth & Environmental Sciences and The Academy of Natural Sciences, Drexel University, 1900 Benjamin Franklin Pkwy, Philadelphia, PA,","active":true,"usgs":false}],"preferred":false,"id":826652,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70226915,"text":"70226915 - 2021 - Hawaiian hoary bat acoustic surveys on Marine Corps Base Hawaii, 2019–2021","interactions":[],"lastModifiedDate":"2021-12-21T15:07:54.383157","indexId":"70226915","displayToPublicDate":"2021-11-11T09:02:04","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":295,"text":"Technical Report","active":false,"publicationSubtype":{"id":4}},"seriesNumber":"100","title":"Hawaiian hoary bat acoustic surveys on Marine Corps Base Hawaii, 2019–2021","docAbstract":"<p>The endangered Hawaiian hoary bat (<i>Lasiurus semotus,</i> Vespertilionidae, also known as <i>Aeorestes semotus</i> and ‘ōpe‘ape‘a) occurs on all the principal volcanic islands in Hawai‘i. Advances in acoustic bat monitoring techniques have contributed to the body of knowledge of bat activity and behavior in many areas of the State of Hawai‘i; however, there is still much that is unknown about the population and seasonal distribution of Hawaiian hoary bats on O‘ahu. A two-year acoustic survey for presence of Hawaiian hoary bats was conducted at 17 stations across four Marine Corps Base Hawaii (MCBH) properties on O‘ahu to document distribution, seasonal patterns, and foraging activity. Bats were confirmed present at all properties; MCBH Kaneohe Bay on Mōkapu Peninsula, Marine Corps Training Area Bellows (MCTAB) in Waimanalo, Camp H M Smith in Halawa Heights, and Puuloa Range Training Facility (RTF) on the ‘Ewa coastal plain. Hawaiian hoary bats were recorded in airspace at all four properties during important periods of Hawaiian hoary bat life history, including periods of pregnancy, lactation, and pup fledging; however, overall presence was low. Foraging activity as identified from characteristic feeding buzzes was very rare and was recorded on only three nights over the entire study. Within-night bat detection pooled for all nights and stations at each property showed that bat activity was mostly confined to the first several hours of the night at MCBH Kaneohe Bay and Puuloa RTF, whereas bat activity was spread throughout the night at Camp H M Smith and MCTAB. Overall, detection frequency was low (year 1 = 0.009, year 2 = 0.007, average = 0.008) at the study sites on O‘ahu compared to results from acoustic monitoring studies on the islands of Maui and Hawai‘i. However, the low rate of bat presence on MCBH properties is consistent with recent studies at other locations on the Island of O‘ahu. Monitoring the seasonal presence and distribution of Hawaiian hoary bats on MCBH facilities, especially at forest and wetland habitats, could contribute to the broader scientific understanding of islandwide distribution and behavior on O‘ahu, which is essential for species recovery planning and implementation of best management practices. </p>","language":"English","publisher":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","collaboration":"HI/Dept. of Land and Nat. Resources; DOI/U.S. Fish and Wildlife; DoD/Marine Corps Base Hawaii;  Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","usgsCitation":"Pinzari, C., Montoya-Aiona, K., Gross, D., and Courtot, K., 2021, Hawaiian hoary bat acoustic surveys on Marine Corps Base Hawaii, 2019–2021: Technical Report 100, iv, 29 p.","productDescription":"iv, 29 p.","ipdsId":"IP-132851","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":393176,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/10790/6798"},{"id":393190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"O'ahu","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -158.0108642578125,\n              21.220261047755002\n            ],\n            [\n              -157.6318359375,\n              21.220261047755002\n            ],\n            [\n              -157.6318359375,\n              21.54251136615996\n            ],\n            [\n              -158.0108642578125,\n              21.54251136615996\n            ],\n            [\n              -158.0108642578125,\n              21.220261047755002\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pinzari, Corinna A. 0000-0001-9794-7564","orcid":"https://orcid.org/0000-0001-9794-7564","contributorId":208455,"corporation":false,"usgs":false,"family":"Pinzari","given":"Corinna A.","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":828771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Montoya-Aiona, Kristina 0000-0002-1776-5443 kmontoya-aiona@usgs.gov","orcid":"https://orcid.org/0000-0002-1776-5443","contributorId":5899,"corporation":false,"usgs":true,"family":"Montoya-Aiona","given":"Kristina","email":"kmontoya-aiona@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":828772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gross, Danielle","contributorId":218186,"corporation":false,"usgs":false,"family":"Gross","given":"Danielle","email":"","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":828773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Courtot, Karen 0000-0002-8849-4054 kcourtot@usgs.gov","orcid":"https://orcid.org/0000-0002-8849-4054","contributorId":140002,"corporation":false,"usgs":true,"family":"Courtot","given":"Karen","email":"kcourtot@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":828774,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227485,"text":"70227485 - 2021 - Hazard-consistent seismic losses and collapse capacities for light-frame wood buildings in California and Cascadia","interactions":[],"lastModifiedDate":"2022-01-19T14:52:59.707307","indexId":"70227485","displayToPublicDate":"2021-11-11T08:43:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1101,"text":"Bulletin of Earthquake Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Hazard-consistent seismic losses and collapse capacities for light-frame wood buildings in California and Cascadia","docAbstract":"<p><span>We evaluate the seismic performance of modern seismically designed wood light-frame (WLF) buildings, considering regional seismic hazard characteristics that influence ground motion duration and frequency content and, thus, seismic risk. Results show that WLF building response correlates strongly with ground motion spectral shape but weakly with duration. Due to the flatter spectral shape of ground motions from subduction events, WLF buildings at sites affected by these earthquakes may experience double the economic losses for a given intensity of shaking, and collapse capacities may be reduced by up to 50%, compared to those at sites affected by crustal earthquakes. These differences could motivate significant increases in design values at sites affected by subduction earthquakes to achieve the uniform risk targets of the American Society of Civil Engineers (ASCE) 7 standard.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10518-021-01258-y","usgsCitation":"Chase, R.E., Liel, A.B., Luco, N., and Bullock, Z., 2021, Hazard-consistent seismic losses and collapse capacities for light-frame wood buildings in California and Cascadia: Bulletin of Earthquake Engineering, v. 19, p. 6615-6639, https://doi.org/10.1007/s10518-021-01258-y.","productDescription":"25 p.","startPage":"6615","endPage":"6639","ipdsId":"IP-129311","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":450224,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10518-021-01258-y","text":"Publisher Index Page"},{"id":394517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, California, Oregon Washington","city":"Anchorage, Eugene, Los Angeles, Portland, San Francisco, Seattle","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.43261718749999,\n              33.92740869431181\n            ],\n            [\n              -117.96844482421875,\n              33.92740869431181\n            ],\n            [\n              -117.96844482421875,\n              34.12317388304314\n            ],\n            [\n              -118.43261718749999,\n              34.12317388304314\n            ],\n            [\n              -118.43261718749999,\n              33.92740869431181\n            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          [\n              -122.38494873046875,\n              45.44471679159555\n            ],\n            [\n              -122.38494873046875,\n              45.60395019421033\n            ],\n            [\n              -122.76123046875,\n              45.60395019421033\n            ],\n            [\n              -122.76123046875,\n              45.44471679159555\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.1728744506836,\n              44.00343436215528\n            ],\n            [\n              -123.04309844970705,\n              44.00343436215528\n            ],\n            [\n              -123.04309844970705,\n              44.109281923355645\n            ],\n            [\n              -123.1728744506836,\n              44.109281923355645\n            ],\n            [\n              -123.1728744506836,\n              44.00343436215528\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.4591064453125,\n              47.47637579720933\n            ],\n            [\n              -122.24212646484375,\n              47.47637579720933\n            ],\n            [\n              -122.24212646484375,\n              47.758714187846294\n            ],\n            [\n              -122.4591064453125,\n              47.758714187846294\n            ],\n            [\n              -122.4591064453125,\n              47.47637579720933\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -150.08697509765622,\n              61.062272494474065\n            ],\n            [\n              -149.67498779296875,\n              61.062272494474065\n            ],\n            [\n              -149.67498779296875,\n              61.28739102214365\n            ],\n            [\n              -150.08697509765622,\n              61.28739102214365\n            ],\n            [\n              -150.08697509765622,\n              61.062272494474065\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"19","noUsgsAuthors":false,"publicationDate":"2021-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Chase, Robert Edward 0000-0002-8155-6830","orcid":"https://orcid.org/0000-0002-8155-6830","contributorId":271198,"corporation":false,"usgs":true,"family":"Chase","given":"Robert","email":"","middleInitial":"Edward","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":831149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liel, Abbie B.","contributorId":184158,"corporation":false,"usgs":false,"family":"Liel","given":"Abbie","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":831150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":831151,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bullock, Zach","contributorId":271199,"corporation":false,"usgs":false,"family":"Bullock","given":"Zach","email":"","affiliations":[{"id":56314,"text":"Department of Mechanical and Civil Engineering, California Institute of Technology, Pasadena, CA 91125","active":true,"usgs":false}],"preferred":false,"id":831152,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70229519,"text":"70229519 - 2021 - Mineral deposit discovery order and three-part quantitative assessments","interactions":[],"lastModifiedDate":"2022-03-11T13:08:11.334928","indexId":"70229519","displayToPublicDate":"2021-11-11T07:07:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Mineral deposit discovery order and three-part quantitative assessments","docAbstract":"<p id=\"sp0015\">Larger oil pools tending to be discovered earlier in an exploration play suggests the same pattern might exist for<span>&nbsp;</span><a class=\"topic-link\" title=\"Learn more about mineral deposits from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/mineral-deposit\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/mineral-deposit\">mineral deposits</a><span>&nbsp;</span>and could be used in predicting sizes of undiscovered deposits in mineral assessments. The volume of individual petroleum pools is highly correlated with surface projection area of pools in basins. The gradual additions to individual oil pool reserves over time adds to the appearance of larger pools being discovered earlier.</p><p id=\"sp0020\">Comparisons of surface projected areas of mineral deposits to their tonnages showed significant positive relationships in all 10 deposit types analyzed, suggesting that larger deposits should be discovered earlier than small deposits.</p><p id=\"sp0025\">Analysis of deposits consistent with three-part mineral assessments identified 9 combinations of mineral deposit types in large regions each containing multiple geological permissive tracts showing negative and 1 positive relationships of deposit size with discovery date significant at the 1% level. Twenty other tests of regions containing multiple permissive settings had either negative or positive relationships, none significantly different from those that might occur by chance. The large regions are mostly based on political boundaries. These results suggest mineral deposit discovery order is not the same as observed in oil pool exploration.</p><p id=\"sp0030\">The widely employed three-part quantitative<span>&nbsp;</span><a class=\"topic-link\" title=\"Learn more about mineral resource from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/mineral-resource\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/mineral-resource\">mineral resource</a><span>&nbsp;</span>assessments are an obvious choice to benefit from patterns of declining deposit sizes with order of discovery. The 30 tests of relationships of discovery dates to deposit sizes demonstrated here were performed with deposits consistent with those in three-part assessments, but the large areas are not consistent with permissive tracts used in these assessments because they also contain substantial non-permissive geology.</p><p id=\"sp0035\">In 100 permissive tracts assessed with three-part assessments of multiple deposit types located throughout the world, the median number of known well-explored deposits is 1 and 90 percent of tracts report less than 9 deposits. The number of well-explored deposits in three-part assessed tracts tends to be quite small, limiting any ability to recognize a discovery order versus size relationship.</p><p id=\"sp0040\">In a three-part assessment of undiscovered<span>&nbsp;</span>porphyry<span>&nbsp;</span>copper deposits of South America, only 7 of 26 delineated tracts contained more than 2 known deposits and only 1 had a significant negative relationship between tonnage of known deposits and year of discovery (p&nbsp;=&nbsp;0.04). Most predicted undiscovered deposits in this tract were expected to be under extensive unexplored post-mineralization cover, meaning the general grade and tonnage model should be applied because the discovery order process starts over. Projection of deposit sizes based on discovery order would provide a biased estimate of the undiscovered deposit sizes in this case. Thus, although a discovery order versus size relationship could exist in three-part mineral assessments, only rarely might the pattern be useful to predict sizes of undiscovered deposits.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2021.104566","usgsCitation":"Singer, D., and Zientek, M., 2021, Mineral deposit discovery order and three-part quantitative assessments: Ore Geology Reviews, v. 139, no. Part B, 104566, 9 p., https://doi.org/10.1016/j.oregeorev.2021.104566.","productDescription":"104566, 9 p.","ipdsId":"IP-127845","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467221,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.oregeorev.2021.104566","text":"Publisher Index Page"},{"id":397016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396983,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1016/j.oregeorev.2021.104566"}],"volume":"139","issue":"Part B","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Singer, Donald A. 0000-0001-6812-6441","orcid":"https://orcid.org/0000-0001-6812-6441","contributorId":288318,"corporation":false,"usgs":false,"family":"Singer","given":"Donald A.","affiliations":[],"preferred":false,"id":837729,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zientek, Michael L. 0000-0002-8522-9626","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":210763,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":837728,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70228315,"text":"70228315 - 2021 - Characterization of the biological, physical, and chemical properties of a toxic thin layer in a temperate marine system","interactions":[],"lastModifiedDate":"2022-02-08T13:03:32.116162","indexId":"70228315","displayToPublicDate":"2021-11-11T06:59:06","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10098,"text":"Marine Ecology Progress Series (MEPS)","active":true,"publicationSubtype":{"id":10}},"title":"Characterization of the biological, physical, and chemical properties of a toxic thin layer in a temperate marine system","docAbstract":"<p class=\"abstract_block\">The distribution of plankton in the ocean is patchy across a wide range of spatial and temporal scales. One type of oceanographic feature that exemplifies this patchiness is a ‘thin layer’. Thin layers are subsurface aggregations of plankton that range in vertical thickness from centimeters to a few meters, which may extend horizontally for kilometers and persist for days. We undertook a field campaign to characterize the biological, physical, and chemical properties of thin layers in Monterey Bay, California (USA), an area where these features can be persistent. The particle aggregates (marine snow) sampled in the study had several quantifiable properties indicating how the layer was formed and how its structure was maintained. Particles were more elongated above the layer, and then changed orientation angle and increased in size within the layer, suggesting passive accumulation of particles along a physical gradient. The shift in particle aggregate orientation angle near the pycnocline suggests that shear may also have played a role in generating the thin layer.<span>&nbsp;</span><i>Pseudo-nitzschia</i><span>&nbsp;</span>spp. were the most abundant phytoplankton within the thin layer. Further, both dissolved and particulate domoic acid were highest within the thin layer. We suggest that phosphate stress is responsible for the formation of<span>&nbsp;</span><i>Pseudo-nitzschia</i><span>&nbsp;</span>spp. aggregates. This stress together with increased nitrogen in the layer may lead to increased bloom toxicity in the subsurface blooms of<span>&nbsp;</span><i>Pseudo-nitzschia</i><span>&nbsp;</span>spp. Several zooplankton groups were observed to aggregate above and below the layer. With the knowledge that harmful algal bloom events can occur in subsurface thin layers, modified sampling methods to monitor for these hidden incubators could greatly improve the efficacy of early-warning systems designed to detect harmful algal blooms in coastal waters.</p>","language":"English","publisher":"Inter-Research","doi":"10.3354/meps13879","usgsCitation":"McManus, M., Greer, A.T., Timmerman, A.H., Sevadjian, J.C., Woodson, C.B., Cowen, R., Fong, D.A., Monismith, S.G., and Cheriton, O.M., 2021, Characterization of the biological, physical, and chemical properties of a toxic thin layer in a temperate marine system: Marine Ecology Progress Series (MEPS), v. 678, p. 17-35, https://doi.org/10.3354/meps13879.","productDescription":"19 p.","startPage":"17","endPage":"35","ipdsId":"IP-129200","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":450228,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps13879","text":"Publisher Index Page"},{"id":395606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"678","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McManus, Margaret A","contributorId":275122,"corporation":false,"usgs":false,"family":"McManus","given":"Margaret A","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":833672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Greer, Adam T","contributorId":275123,"corporation":false,"usgs":false,"family":"Greer","given":"Adam","email":"","middleInitial":"T","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":833673,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Timmerman, Amanda HV","contributorId":275126,"corporation":false,"usgs":false,"family":"Timmerman","given":"Amanda","email":"","middleInitial":"HV","affiliations":[{"id":39679,"text":"Scripps Institution of Oceanography, UCSD","active":true,"usgs":false}],"preferred":false,"id":833674,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sevadjian, Jeff C","contributorId":275129,"corporation":false,"usgs":false,"family":"Sevadjian","given":"Jeff","email":"","middleInitial":"C","affiliations":[{"id":39679,"text":"Scripps Institution of Oceanography, UCSD","active":true,"usgs":false}],"preferred":false,"id":833675,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woodson, C. Brock","contributorId":275132,"corporation":false,"usgs":false,"family":"Woodson","given":"C.","email":"","middleInitial":"Brock","affiliations":[{"id":56710,"text":"School of ECAM Engineering, University of Georgia","active":true,"usgs":false}],"preferred":false,"id":833676,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cowen, Robert","contributorId":275135,"corporation":false,"usgs":false,"family":"Cowen","given":"Robert","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":833677,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fong, Derek A","contributorId":275136,"corporation":false,"usgs":false,"family":"Fong","given":"Derek","email":"","middleInitial":"A","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":833678,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Monismith, Stephen G.","contributorId":196322,"corporation":false,"usgs":false,"family":"Monismith","given":"Stephen","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":833679,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":204459,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":833680,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70226847,"text":"70226847 - 2021 - Remotely sensed fine-fuel changes from wildfire and prescribed fire in a semi-arid grassland","interactions":[],"lastModifiedDate":"2021-12-15T12:40:09.70423","indexId":"70226847","displayToPublicDate":"2021-11-11T06:37:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5678,"text":"Fire","active":true,"publicationSubtype":{"id":10}},"title":"Remotely sensed fine-fuel changes from wildfire and prescribed fire in a semi-arid grassland","docAbstract":"<p><span>The spread of flammable invasive grasses, woody plant encroachment, and enhanced aridity have interacted in many grasslands globally to increase wildfire activity and risk to valued assets. Annual variation in the abundance and distribution of fine-fuel present challenges to land managers implementing prescribed burns and mitigating wildfire, although methods to produce high-resolution fuel estimates are still under development. To further understand how prescribed fire and wildfire influence fine-fuels in a semi-arid grassland invaded by non-native perennial grasses, we combined high-resolution Sentinel-2A imagery with in situ vegetation data and machine learning to estimate yearly fine-fuel loads from 2015 to 2020. The resulting model of fine-fuel corresponded to field-based validation measurements taken in the first (R</span><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;><semantics><msup><mrow /><mn>2</mn></msup></semantics></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"semantics\"><span id=\"MathJax-Span-4\" class=\"msup\"><span id=\"MathJax-Span-5\" class=\"mrow\"></span><span id=\"MathJax-Span-6\" class=\"mn\">2</span></span></span></span></span></span></span><span>&nbsp;= 0.52, RMSE = 218 kg/ha) and last year (R</span><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;><semantics><msup><mrow /><mn>2</mn></msup></semantics></math>\"><span id=\"MathJax-Span-7\" class=\"math\"><span><span id=\"MathJax-Span-8\" class=\"mrow\"><span id=\"MathJax-Span-9\" class=\"semantics\"><span id=\"MathJax-Span-10\" class=\"msup\"><span id=\"MathJax-Span-11\" class=\"mrow\"></span><span id=\"MathJax-Span-12\" class=\"mn\">2</span></span></span></span></span></span></span><span>&nbsp;= 0.63, RMSE = 196 kg/ha) of this 6-year study. Serial prediction of the fine-fuel model allowed for an assessment of the effect of prescribed fire (average reduction of −80 kg/ha 1-year post fire) and wildfire (−260 kg/ha 1-year post fire) on fuel conditions. Post-fire fine-fuel loads were significantly lower than in unburned control areas sampled just outside fire perimeters from 2015 to 2020 across all fires (</span><span class=\"html-italic\">t</span><span>&nbsp;= 1.67,&nbsp;</span><span class=\"html-italic\">p</span><span>&nbsp;&lt; 0.0001); however, fine-fuel recovery occurred within 3–5 years, depending upon burn and climate conditions. When coupled with detailed fuels data from field measurements, Sentinel-2A imagery provided a means for evaluating grassland fine-fuels at yearly time steps and shows high potential for extended monitoring of dryland fuels. Our approach provides land managers with a systematic analysis of the effects of fire management treatments on fine-fuel conditions and provides an accurate, updateable, and expandable solution for mapping fine-fuels over yearly time steps across drylands throughout the world</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/fire4040084","usgsCitation":"Wells, A.G., Munson, S.M., Sesnie, S., and Villarreal, M.L., 2021, Remotely sensed fine-fuel changes from wildfire and prescribed fire in a semi-arid grassland: Fire, v. 4, no. 4, 84, 22 p., https://doi.org/10.3390/fire4040084.","productDescription":"84, 22 p.","ipdsId":"IP-134126","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":450231,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fire4040084","text":"Publisher Index Page"},{"id":436120,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91U530P","text":"USGS data release","linkHelpText":"Remotely sensed fine-fuel data for Buenos Aires National Wildlife Refuge (BANWR) from 2015 to 2020"},{"id":436119,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9347I2H","text":"USGS data release","linkHelpText":"Remotely sensed fine fuel data for Buenos Aires National Wildlife Refuge (BANWR) from 2015 to 2020"},{"id":392940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Buenos Aires National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.61285400390625,\n              31.302021690136105\n            ],\n            [\n              -110.92071533203125,\n              31.302021690136105\n            ],\n            [\n              -110.92071533203125,\n              31.88921859876096\n            ],\n            [\n              -111.61285400390625,\n              31.88921859876096\n            ],\n            [\n              -111.61285400390625,\n              31.302021690136105\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"4","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Wells, Adam Gerhard 0000-0001-9675-4963","orcid":"https://orcid.org/0000-0001-9675-4963","contributorId":270137,"corporation":false,"usgs":true,"family":"Wells","given":"Adam","email":"","middleInitial":"Gerhard","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":828474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":828475,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sesnie, Steven","contributorId":239687,"corporation":false,"usgs":false,"family":"Sesnie","given":"Steven","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":true,"id":828476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":828477,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70225680,"text":"cir1486 - 2021 - Nitrogen in the Chesapeake Bay watershed—A century of change, 1950–2050","interactions":[],"lastModifiedDate":"2026-01-26T22:36:29.876041","indexId":"cir1486","displayToPublicDate":"2021-11-10T14:05:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1486","displayTitle":"Nitrogen in the Chesapeake Bay Watershed—A Century of Change, 1950–2050","title":"Nitrogen in the Chesapeake Bay watershed—A century of change, 1950–2050","docAbstract":"<h1>Foreword</h1><p>Sustaining the quality of the Nation’s water resources and the health of our diverse ecosystems depends on the availability of sound water-resources data and information to develop effective, science-based policies. Effective management of water resources also brings more certainty and efficiency to important economic sectors. Taken together, these actions lead to immediate and long-term economic, social, and environmental benefits that will make a difference to the lives of the almost 400 million people projected to live in the United States by 2050.</p><p>The Chesapeake Bay is the largest and most productive estuary in the United States and is a vital environmental and economic resource. Approximately half of the water volume of the Chesapeake Bay originates from streams and rivers that drain the 64,243 mi<sup>2</sup> Chesapeake Bay watershed. The Bay and its tributaries have been degraded by excessive nutrients, such as nitrogen, from contributing watersheds. Inputs of nitrogen to the Bay lead to increased algal growth, decreased dissolved oxygen, and declining fisheries. In 2000, the Chesapeake Bay was listed as impaired under the Clean Water Act and Total Maximum Daily Loads (TMDLs) for nutrients and sediment have been established to assist with management actions aimed at nutrient reductions. Effective nutrient management requires an understanding of past, present, and future nutrient sources, fate, and transport in the watershed.</p><p>The Chesapeake Bay community has been a pioneer in science, management, and regulation to improve water quality. Factors like climate, hydrology, source inputs, and management controls play a vital role in determining the delivery and magnitude of nitrogen inputs to the Bay. Science in the form of monitoring data, predictive tools, and interpretive reports can help inform decisions to better balance the use and control of nitrogen in coastal areas. The findings in this report can contribute to effective management of the Bay and its watershed by providing a synthesis of the understanding of how human activities and environmental change in the watershed in the past, present, and future will influence the export of nitrogen to the Bay.</p><p>We hope this publication will provide you with insights and information to meet your water resource needs and will foster increased civilian awareness and involvement in the protection and restoration of our Nation’s waters. The information in this report is intended primarily for those interested or involved in resource management and protection, conservation, regulation, and policymaking at the regional and national levels.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1486","programNote":"National Water-Quality Program","usgsCitation":"Clune, J.W., and Capel, P.D., eds., 2021, Nitrogen in the Chesapeake Bay watershed—A century of change, 1950–2050 (ver. 1.2, 2024): U.S. Geological Survey Circular 1486, 168 p., https://doi.org/10.3133/cir1486.","productDescription":"vi, 168 p.","numberOfPages":"168","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-109208","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic 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data-mce-href=\"https://www.usgs.gov/centers/pa-water\">Pennsylvania Water Science Center</a><br>U.S. Geological Survey<br>215 Limekiln Road<br>New Cumberland, PA 17070</p>","tableOfContents":"<ul><li>Foreword</li><li>Overview of Major Findings</li><li>Environmental Setting of the Chesapeake Bay Watershed</li><li>Nitrogen Setting of the Chesapeake Bay Watershed</li><li>Historical Setting of the Chesapeake Bay Watershed</li><li>Chapter 1. Changes in Nitrogen, Water Quality, and Management</li><li>Chapter 2. Nitrogen in Streams and Groundwater</li><li>Chapter 3. Changes in Climate</li><li>Chapter 4. Changes in Hydrology</li><li>Chapter 5. Changes in Atmospheric Deposition of Nitrogen</li><li>Chapter 6. Changes in Land Use</li><li>Chapter 7. Changes in Agricultural Water-Quality Management</li><li>Chapter 8. Changes in Water-Quality Management in Developed Areas</li><li>Chapter 9. Modeling the Effect of Nitrogen Loads from Multiple Changes in the Watershed</li><li>Chapter 10. Watershed Scale Changes in Nitrogen Export: Past and Future</li><li>Excess Nitrogen Impacts on Coastal Areas Across the Nation and the World</li><li>Final Thoughts</li><li>References Cited</li><li>Glossary</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2021-11-10","revisedDate":"2024-01-09","noUsgsAuthors":false,"publicationDate":"2021-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Clune, John W. 0000-0002-3563-1975 jclune@usgs.gov","orcid":"https://orcid.org/0000-0002-3563-1975","contributorId":173410,"corporation":false,"usgs":true,"family":"Clune","given":"John","email":"jclune@usgs.gov","middleInitial":"W.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Capel, Paul D. 0000-0003-1620-5185 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During water years 2016–20, the U.S. Geological Survey, in cooperation with the Illinois Environmental Protection Agency, operated continuous monitoring stations on eight major rivers in Illinois to better quantify nutrient and sediment loadings from the State of Illinois to the Mississippi River. This report estimates nitrate, phosphorus, and suspended-sediment loadings over that period, which can provide a benchmark against which to assess future changes in loading.</p><p>In addition, this report develops a new method for incorporating the uncertainty created by gaps in continuous datasets based on Bayesian machine learning. Data gaps are a common problem in continuous monitoring, and gap filling is necessary to quantify loadings and the uncertainty in loadings, which is essential if these results are to provide a benchmark for future studies. 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 \"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/cm-water\" data-mce-href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>405 N. Goodwin Ave.<br>Urbana, IL 61801</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Methods</li><li>Data Coverage</li><li>Streamflow and Discrete Water-Quality Data</li><li>Imputation Results</li><li>Comparison Among Model Forms</li><li>Loads and Yields</li><li>Continuous Monitoring and Discrete Sampling</li><li>Network Improvements</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Station Descriptions</li></ul>","publishedDate":"2021-11-10","noUsgsAuthors":false,"publicationDate":"2021-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Hodson, Timothy O. 0000-0003-0962-5130","orcid":"https://orcid.org/0000-0003-0962-5130","contributorId":78634,"corporation":false,"usgs":true,"family":"Hodson","given":"Timothy","email":"","middleInitial":"O.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terrio, Paul J. 0000-0002-1515-9570 pjterrio@usgs.gov","orcid":"https://orcid.org/0000-0002-1515-9570","contributorId":3313,"corporation":false,"usgs":true,"family":"Terrio","given":"Paul","email":"pjterrio@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peake, Colin S. 0000-0001-9712-1623","orcid":"https://orcid.org/0000-0001-9712-1623","contributorId":268354,"corporation":false,"usgs":true,"family":"Peake","given":"Colin","email":"","middleInitial":"S.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fazio, David J. 0000-0003-0254-5162","orcid":"https://orcid.org/0000-0003-0254-5162","contributorId":268355,"corporation":false,"usgs":true,"family":"Fazio","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826487,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70225748,"text":"sir20215050 - 2021 - Preliminary geohydrologic assessment of Buenos Aires National Wildlife Refuge, Altar Valley, southeastern Arizona","interactions":[],"lastModifiedDate":"2021-11-10T19:08:22.752141","indexId":"sir20215050","displayToPublicDate":"2021-11-10T09:09:24","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5050","displayTitle":"Preliminary Geohydrologic Assessment of Buenos Aires National Wildlife Refuge, Altar Valley, Southeastern Arizona","title":"Preliminary geohydrologic assessment of Buenos Aires National Wildlife Refuge, Altar Valley, southeastern Arizona","docAbstract":"<p>The Buenos Aires National Wildlife Refuge is located in the southern part of Altar Valley, southwest of Tucson in southeastern Arizona. The primary water-supply well at the Buenos Aires National Wildlife Refuge has experienced a two-decade decrease in groundwater levels in the well, as have other wells in the southern part of Altar Valley. In part to understand this trend, a study was undertaken by the U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, to summarize what is known about the geohydrologic system on the refuge and analyze groundwater-level trends and precipitation-groundwater correlations. In addition, available data were compiled where possible on the climate, land cover, soils, geology, and hydrology to provide a foundation for future modeling of the system.</p><p>Altar Valley is a sedimentary basin bounded by a mixture of Paleozoic to Tertiary sedimentary, volcanic, granitic, and metamorphic rocks. The valley fill is undifferentiated Tertiary to Quaternary sediments underlain by middle Miocene to Pliocene rocks that consist of moderately to strongly consolidated conglomerate and sandstone. Surface water, when present in the predominantly ephemeral streams of the valley, flows from south to north. Arivaca Creek has a cienega (or wetland) where groundwater surfaces before it flows as a short perennial reach out of Arivaca Basin. Groundwater maps compiled between 1934 and 2016 showed groundwater flowing from south to north. Before the 1980s, temporal patterns of groundwater levels in wells in Altar Valley varied substantially from one well to another. In the mid-1980s, comparatively high levels of precipitation occurred: the 1980s median value was 15.3 inches, whereas the median for the period of record was 13.2 inches. In addition, apparently corresponding groundwater level increases were seen in nearly all wells studied. After this initial increase, two different groundwater-level trends began to be observed in two spatially distinct sets of wells: in the northern part, groundwater levels were relatively steady, whereas in the southern part, groundwater levels declined from 10 to 20 feet between 1990 and 2019. Annual groundwater pumpage declined substantially in the northern part of the valley beginning in the early 1980s, but it began to increase again in the 1990s. Pumpage in the southern part has remained low and relatively steady compared to the northern part. Although the precise reasons for the declining groundwater levels in the southern part remain unclear, groundwater levels may be affected by factors such as climate cycles, long-term drought, and temperature-induced declines in recharge, resulting in increased evapotranspiration.</p><p>Preliminary analyses of two wells, one selected from each part of the valley, using linear regression and lag correlation to investigate correlation between annual precipitation and groundwater levels, showed a maximum correlation at a lag of about 17 years in the southern part of the valley and about 25 years in the northern part, indicating that, although variable sources and traveltimes of recharged water may be needed to propagate to each location, the strongest correlation at each well is with precipitation that was recharged 17 and 25 years prior to the groundwater response in that well. Assuming a constant flow of groundwater from the southern to the northern part of the valley, a decrease in recharge is expected to lead to a decrease in aquifer storage. As to the comparatively stable groundwater levels in the northern part, pumpage is still only about one-half what it was in the early 1980s, even though pumpage has increased there since the 1990s. Water levels in most wells in the northern part were drawn down prior to the decrease in pumping in the early 1980s, possibly owing to a combination of pumping and the nearly 20-year midcentury drought that occurred between 1940 and 1960. Water levels were in the process of recovering when the increase in pumping occurred in the 1990s. Because the water levels were recovering (increasing) instead of remaining static, the increased pumping may have only limited the recovery rather than causing a decrease in water levels, as a new quasi-equilibrium state may have been reached. Additional possible causes for the stable groundwater levels include (1) upgradient aquifer transmissivity that was high enough to offset pumping, (2) a low-permeability barrier, such as bedrock or clay, at the north end of the valley that caused groundwater pooling, (3) higher lateral inflow of groundwater in the northern part of the valley, (4) a delay in the effect of storage declines propagating from the south, or (5) some combination thereof.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215050","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Owen-Joyce, S.J., Callegary, J.B., and Rosebrough, A.E., 2021, Preliminary geohydrologic assessment of Buenos Aires National Wildlife Refuge, Altar Valley, southeastern Arizona: U.S. Geological Survey Scientific Investigations Report 2021–5050, 29 p., https://doi.org/10.3133/sir20215050.","productDescription":"Report: viii, 29 p.; Data Release","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-118417","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":391517,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5050/sir20215050.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":391518,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QST8OX","linkHelpText":"Groundwater well data and annual groundwater pumpage data (1984–2019) in Altar Valley, Arizona"},{"id":391516,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5050/covrthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Altar Valley, Buenos Aires National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.56341552734375,\n              31.459125370764387\n            ],\n            [\n              -111.34780883789062,\n              31.459125370764387\n            ],\n            [\n              -111.34780883789062,\n              31.81864727496152\n            ],\n            [\n              -111.56341552734375,\n              31.81864727496152\n            ],\n            [\n              -111.56341552734375,\n              31.459125370764387\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_az@usgs.gov\" data-mce-href=\"mailto:dc_az@usgs.gov\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/az-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/az-water\">Arizona Water Science Center</a><br><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>520 N. Park Avenue<br>Tucson, AZ 85719</p>","tableOfContents":"<ul><li>Acknowledgments&nbsp;&nbsp;</li><li>Abstract&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Aquifer Assessment&nbsp;&nbsp;</li><li>Altar Valley Precipitation–Groundwater Level Correlation&nbsp;&nbsp;</li><li>Summary&nbsp;&nbsp;</li><li>Selected References&nbsp;&nbsp;</li><li>Appendix 1. Selected Well Data in the Altar Valley, Arizona, Groundwater Area&nbsp;&nbsp;</li><li>Appendix 2. Annual Groundwater Pumpage in Altar Valley, Arizona, Between 1984 and 2019</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2021-11-10","noUsgsAuthors":false,"publicationDate":"2021-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Owen-Joyce, Sandra J. 0000-0002-4400-5618 sjowen@usgs.gov","orcid":"https://orcid.org/0000-0002-4400-5618","contributorId":5215,"corporation":false,"usgs":true,"family":"Owen-Joyce","given":"Sandra","email":"sjowen@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":826481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Callegary, James B. 0000-0003-3604-0517 jcallega@usgs.gov","orcid":"https://orcid.org/0000-0003-3604-0517","contributorId":2171,"corporation":false,"usgs":true,"family":"Callegary","given":"James","email":"jcallega@usgs.gov","middleInitial":"B.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826482,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosebrough, Amy Elizabeth","contributorId":268353,"corporation":false,"usgs":false,"family":"Rosebrough","given":"Amy","email":"","middleInitial":"Elizabeth","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":true,"id":826483,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250897,"text":"70250897 - 2021 - Bottom-up and top-down control on hydrothermal resources in the Great Basin: An example from Gabbs Valley, Nevada","interactions":[],"lastModifiedDate":"2024-01-11T14:33:28.409502","indexId":"70250897","displayToPublicDate":"2021-11-10T08:31:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Bottom-up and top-down control on hydrothermal resources in the Great Basin: An example from Gabbs Valley, Nevada","docAbstract":"<div class=\"article-section__content en main\"><p>The Great Basin in the western United States hosts various hydrothermal systems, including both active geothermal systems and ancient systems preserved as mineral deposits. New magnetotelluric and structural geologic data were collected in the Gabbs Valley area of western Nevada to demonstrate the advantage of imaging the full crustal column below known hydrothermal systems. Three-dimensional models are developed and jointly interpreted where the key findings are bottom-up and top-down controls on hydrothermal systems. Bottom-up control is dictated by weaknesses in the brittle-ductile transition that allow hydrothermal fluids to propagate into the crust; these are often collocated with Miocene volcanic structures. Top-down control is dominated by modern Walker Lane and Basin and Range tectonics that control fluid transport through the middle and upper crust. This study demonstrates that the characterization of regional mineral and geothermal resources is better informed by imaging lower crustal structures and preferential pathways to the surface.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL095009","usgsCitation":"Peacock, J., and Siler, D.L., 2021, Bottom-up and top-down control on hydrothermal resources in the Great Basin: An example from Gabbs Valley, Nevada: Geophysical Research Letters, v. 48, no. 23, e2021GL095009, 10 p., https://doi.org/10.1029/2021GL095009.","productDescription":"e2021GL095009, 10 p.","ipdsId":"IP-130794","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":489074,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021gl095009","text":"Publisher Index Page"},{"id":424328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"23","noUsgsAuthors":false,"publicationDate":"2021-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":891970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siler, Drew L. 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":203341,"corporation":false,"usgs":true,"family":"Siler","given":"Drew","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":891971,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70226173,"text":"70226173 - 2021 - Multilayer perceptrons (MLPs)","interactions":[],"lastModifiedDate":"2021-11-16T13:14:51.29369","indexId":"70226173","displayToPublicDate":"2021-11-10T07:14:03","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Multilayer perceptrons (MLPs)","docAbstract":"<div id=\"body\"><div class=\"content\"><p id=\"Par1\" class=\"Para\">Artificial neural networks (ANNs) are adaptable systems that can solve problems that are difficult to describe with a mathematical relationship. They seek relationships between different types of datasets with their abilities to learn either with supervision or without. ANNs recognize patterns between input and output space and generalize solutions, in a way simulating the human brain’s learning experience with many relatively simple individual processing elements, called neurons. Neurons are networked (network topology) in a number of ways depending on the problem type and complexity. One of the most widely used ANN learning techniques is supervised learning coupled with a multilayer perceptron (MLP) topology due to its flexible applicability to a wide range of modeling problems involving both general classification and regression. ANNs, due to this flexibility, have been applied to many fields since the 1990s and their theory, types (such as radial basis functions, random...</p></div></div>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of Mathematical Geosciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-26050-7_455-1","usgsCitation":"Karacan, C.O., 2021, Multilayer perceptrons (MLPs), chap. <i>of</i> Encyclopedia of Mathematical Geosciences, 3 p., https://doi.org/10.1007/978-3-030-26050-7_455-1.","productDescription":"3 p.","ipdsId":"IP-124707","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":391746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":826715,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70226717,"text":"70226717 - 2021 - Strong evidence for two disjunct populations of Black Scoters Melanitta americana in North America","interactions":[],"lastModifiedDate":"2021-12-07T13:05:27.13515","indexId":"70226717","displayToPublicDate":"2021-11-10T07:05:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3764,"text":"Wildfowl","onlineIssn":"2052-6458","printIssn":"0954-6324","active":true,"publicationSubtype":{"id":10}},"title":"Strong evidence for two disjunct populations of Black Scoters Melanitta americana in North America","docAbstract":"<div>Black Scoters<span>&nbsp;</span><i>Melanitta americana</i><span>&nbsp;</span>were marked with satellite transmitters on Atlantic and Pacific coasts of North America to examine continental-scale population delineation. Scoters marked on the different coasts did not overlap at any stage of the annual cycle, suggesting that birds in the two regions could be monitored and managed as separate populations: 1) an Atlantic population, which winters along the Atlantic coast and Great Lakes and breeds from northeast continental Canada westward to the Northwest Territories, and 2) a Pacific population, which winters along the Pacific coasts of Alaska, British Columbia and the Pacific northwest states, and breeds in western Alaska. Range maps for Black Scoter could reflect these distributions revealed by satellite telemetry. Our data provide new information on the distribution of Black Scoters in North America, which can be used to improve the design of future surveys.</div>","language":"English","publisher":"Wildfowl Journal","usgsCitation":"Bowman, T.D., Gilliland, S.G., Schamber, J.L., Flint, P.L., Esler, D., Boyd, W., Rosenberg, D.H., Savard, J.L., Perry, M., and Osenkowski, J.E., 2021, Strong evidence for two disjunct populations of Black Scoters Melanitta americana in North America: Wildfowl, v. 71, p. 179-192.","productDescription":"14 p.","startPage":"179","endPage":"192","ipdsId":"IP-121283","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":392567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":392559,"type":{"id":15,"text":"Index Page"},"url":"https://wildfowl.wwt.org.uk/index.php/wildfowl/article/view/2759"}],"country":"Canada, United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.57812499999999,\n              48.45835188280866\n            ],\n            [\n              -58.35937499999999,\n              48.45835188280866\n            ],\n            [\n              -58.35937499999999,\n              65.94647177615738\n            ],\n            [\n              -107.57812499999999,\n              65.94647177615738\n            ],\n            [\n              -107.57812499999999,\n              48.45835188280866\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -166.2890625,\n              57.136239319177434\n            ],\n            [\n              -155.390625,\n              57.136239319177434\n            ],\n            [\n              -155.390625,\n              69.03714171275197\n            ],\n            [\n              -166.2890625,\n              69.03714171275197\n            ],\n            [\n              -166.2890625,\n              57.136239319177434\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"71","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bowman, Timothy D.","contributorId":80779,"corporation":false,"usgs":false,"family":"Bowman","given":"Timothy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":827939,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilliland, Scott G.","contributorId":216936,"corporation":false,"usgs":false,"family":"Gilliland","given":"Scott","email":"","middleInitial":"G.","affiliations":[{"id":12590,"text":"Canadian Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":827940,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schamber, Jason L","contributorId":269800,"corporation":false,"usgs":false,"family":"Schamber","given":"Jason","email":"","middleInitial":"L","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":827941,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":827942,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esler, Daniel 0000-0001-5501-4555 desler@usgs.gov","orcid":"https://orcid.org/0000-0001-5501-4555","contributorId":5465,"corporation":false,"usgs":true,"family":"Esler","given":"Daniel","email":"desler@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":827943,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boyd, W. Sean","contributorId":241002,"corporation":false,"usgs":false,"family":"Boyd","given":"W. 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