{"pageNumber":"605","pageRowStart":"15100","pageSize":"25","recordCount":165309,"records":[{"id":70209677,"text":"70209677 - 2020 - A critical assessment of human-impact indices based on anthropogenic pollen indicators","interactions":[],"lastModifiedDate":"2020-04-21T14:49:32.79993","indexId":"70209677","displayToPublicDate":"2020-04-19T09:46:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"A critical assessment of human-impact indices based on anthropogenic pollen indicators","docAbstract":"Anthropogenic pollen indicators in pollen records are an established tool for reconstructing the history of human impacts on vegetation and landscapes. They are also used to disentangle the influence of human activities and climatic variability on ecosystems. The comprehensive anthropogenic pollen-indicator approach developed by Behre (1981) has been widely used, including beyond its original geographical scope of Central and Western Europe. Uncritical adoption of this approach for other areas is risky because adventives (plants introduced with agriculture) in Central Europe can be apophytes (native plants favoured by human disturbances) in other regions. This problem can be addressed by identifying region-specific, anthropogenic-indicator pollen types and/or developing region-specific, human-impact indices from pollen assemblages. However, understanding of regional variation in the timing and intensity of human impacts is limited by the lack of standardization, validation and intercomparison of such regional approaches. Here we review the most common European anthropogenic pollen-indicator approaches to assess their performance at six sites spanning a continental gradient over the boreal, temperate and Mediterranean biomes. Specifically, we evaluate the human-indicator approaches by using independent archaeological evidence and models. We present new insights into how these methodologies can assist in the interpretation of pollen records as well as into how a careful selection of pollen types and/or indices according to the specific geographical scope of each study is key to obtain meaningful reconstructions of anthropogenic activity through time. The evaluated approaches generally perform better in the regions for which they were developed. However, we find marked differences in their capacity to identify human impact, while some approaches do not perform well even in the regions for which they were developed, others might be used, with due caution, outside their original areas or biomes. We conclude that alongside the increasing wealth of pollen datasets a need to develop novel tools may assist numeric human impact reconstructions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2020.106291","collaboration":"","usgsCitation":"Deza-Araujo, M., Morales-Molino, C., Tinner, W., Henne, P., Heitz, C., Pezzatti, G.B., Hafner, A., and Conedera, M., 2020, A critical assessment of human-impact indices based on anthropogenic pollen indicators: Quaternary Science Reviews, v. 236, https://doi.org/10.1016/j.quascirev.2020.106291.","productDescription":"106291, 12 p.","startPage":"","ipdsId":"IP-115699","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":457030,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2020.106291","text":"Publisher Index Page"},{"id":374154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"236","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Deza-Araujo, Mara 0000-0001-9628-771X","orcid":"https://orcid.org/0000-0001-9628-771X","contributorId":224223,"corporation":false,"usgs":false,"family":"Deza-Araujo","given":"Mara","email":"","affiliations":[{"id":40840,"text":"Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL)","active":true,"usgs":false}],"preferred":false,"id":787479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morales-Molino, Cesar 0000-0002-9464-862X","orcid":"https://orcid.org/0000-0002-9464-862X","contributorId":224224,"corporation":false,"usgs":false,"family":"Morales-Molino","given":"Cesar","email":"","affiliations":[{"id":38843,"text":"University of Bern, Switzerland","active":true,"usgs":false}],"preferred":false,"id":787480,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tinner, Willy 0000-0001-7352-0144","orcid":"https://orcid.org/0000-0001-7352-0144","contributorId":169167,"corporation":false,"usgs":false,"family":"Tinner","given":"Willy","email":"","affiliations":[{"id":25430,"text":"University of Bern","active":true,"usgs":false}],"preferred":false,"id":787481,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Henne, Paul D. 0000-0003-1211-5545 phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":787482,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heitz, Caroline 0000-0001-7188-6775","orcid":"https://orcid.org/0000-0001-7188-6775","contributorId":224225,"corporation":false,"usgs":false,"family":"Heitz","given":"Caroline","email":"","affiliations":[{"id":38843,"text":"University of Bern, Switzerland","active":true,"usgs":false}],"preferred":false,"id":787483,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pezzatti, Gianni B 0000-0003-2564-3435","orcid":"https://orcid.org/0000-0003-2564-3435","contributorId":224226,"corporation":false,"usgs":false,"family":"Pezzatti","given":"Gianni","email":"","middleInitial":"B","affiliations":[{"id":40840,"text":"Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL)","active":true,"usgs":false}],"preferred":false,"id":787484,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hafner, Albert 0000-0003-2159-8569","orcid":"https://orcid.org/0000-0003-2159-8569","contributorId":224227,"corporation":false,"usgs":false,"family":"Hafner","given":"Albert","email":"","affiliations":[{"id":38843,"text":"University of Bern, Switzerland","active":true,"usgs":false}],"preferred":false,"id":787485,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Conedera, Marco 0000-0003-3980-2142","orcid":"https://orcid.org/0000-0003-3980-2142","contributorId":194727,"corporation":false,"usgs":false,"family":"Conedera","given":"Marco","email":"","affiliations":[],"preferred":false,"id":787486,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70209696,"text":"70209696 - 2020 - Inferring surface flow velocities in sediment-laden Alaskan rivers from optical image sequences acquired from a helicopter","interactions":[],"lastModifiedDate":"2020-04-21T16:53:17.461883","indexId":"70209696","displayToPublicDate":"2020-04-18T11:48:25","publicationYear":"2020","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":"Inferring surface flow velocities in sediment-laden Alaskan rivers from optical image sequences acquired from a helicopter","docAbstract":"<p><span>The remote, inaccessible location of many rivers in Alaska creates a compelling need for remote sensing approaches to streamflow monitoring. Motivated by this objective, we evaluated the potential to infer flow velocities from optical image sequences acquired from a helicopter deployed above two large, sediment-laden rivers. Rather than artificial seeding, we used an ensemble correlation particle image velocimetry (PIV) algorithm to track the movement of boil vortices that upwell suspended sediment and produce a visible contrast at the water surface. This study introduced a general, modular workflow for image preparation (stabilization and geo-referencing), preprocessing (filtering and contrast enhancement), analysis (PIV), and postprocessing (scaling PIV output and assessing accuracy via comparison to field measurements). Applying this method to images acquired with a digital mapping camera and an inexpensive video camera highlighted the importance of image enhancement and the need to resample the data to an appropriate, coarser pixel size and a lower frame rate. We also developed a Parameter Optimization for PIV (POP) framework to guide selection of the interrogation area (IA) and frame rate for a particular application. POP results indicated that the performance of the PIV algorithm was highly robust and that relatively large IAs (64–320 pixels) and modest frame rates (0.5–2 Hz) yielded strong agreement (</span><span>&nbsp;</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><mrow><msup><mi>R</mi><mn>2</mn></msup><mo>&amp;gt;</mo><mn>0</mn><mo>.</mo><mn>9</mn></mrow></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=\"mrow\"><span id=\"MathJax-Span-5\" class=\"msup\"><i><span id=\"MathJax-Span-6\" class=\"mi\">R</span></i><sup><span id=\"MathJax-Span-7\" class=\"mn\">2</span></sup></span><span id=\"MathJax-Span-8\" class=\"mo\">&gt;</span><span id=\"MathJax-Span-9\" class=\"mn\">0</span><span id=\"MathJax-Span-10\" class=\"mo\">.</span><span id=\"MathJax-Span-11\" class=\"mn\">9</span></span></span></span></span></span></span><span>&nbsp;</span><span>) between remotely sensed velocities and field measurements. Similarly, analysis of the sensitivity of PIV accuracy to image sequence duration showed that dwell times as short as 16 s would be sufficient at a frame rate of 1 Hz and could be cut in half if the frame rate were doubled. The results of this investigation indicate that helicopter-based remote sensing of velocities in sediment-laden rivers could contribute to noncontact streamgaging programs and enable reach-scale mapping of flow fields.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs12081282","collaboration":"","usgsCitation":"Legleiter, C.J., and Kinzel, P.J., 2020, Inferring surface flow velocities in sediment-laden Alaskan rivers from optical image sequences acquired from a helicopter: Remote Sensing, v. 12, no. 8, https://doi.org/10.3390/rs12081282.","productDescription":"1282, 28 p.","startPage":"","ipdsId":"IP-117094","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":457033,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.3390/rs12081282","text":"External Repository"},{"id":437023,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IJ20O4","text":"USGS data release","linkHelpText":"Field measurements of flow velocity and optical image sequences acquired from the Salcha and Tanana Rivers in Alaska in 2018 and 2019 and used for particle image velocimetry (PIV)"},{"id":374163,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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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":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":787549,"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":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":787550,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227153,"text":"70227153 - 2020 - Distribution and abundance of Westslope Cutthroat Trout in relation to habitat characteristics at multiple spatial scales","interactions":[],"lastModifiedDate":"2022-01-03T15:42:50.022639","indexId":"70227153","displayToPublicDate":"2020-04-18T09:36:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Distribution and abundance of Westslope Cutthroat Trout in relation to habitat characteristics at multiple spatial scales","docAbstract":"<p><span>The distribution and relative abundance of Westslope Cutthroat Trout (WCT)&nbsp;</span><i>Oncorhynchus clarkii lewisi</i><span>&nbsp;in relation to habitat characteristics remain unknown across large portions of the species’ range. The goals of this research were to provide a foundational understanding of WCT distribution and relative abundance related to habitat characteristics in tributaries of the St. Maries River, Idaho—a highly altered watershed. The basin drains an area of approximately 1,863&nbsp;km</span><sup>2</sup><span>&nbsp;and has a longitudinal elevation difference of about 207&nbsp;m. Backpack electrofishing and habitat assessments were conducted at 68 reaches in 35 different tributaries of the St. Maries River in 2017 and 2018. Habitat was measured at small (reach-level) and large (watershed-level) scales. A total of 652 WCT was sampled from 52 of 68 total reaches. Habitat characteristics varied by age-class, but most WCT were estimated to be age 0 and age 1. Logistic regression models indicated that the presence of age-0 WCT was positively related to stream gradient and elevation, but negatively related to water temperature, road density, fine substrate, stream depth, and the presence of Brook Trout (BKT)&nbsp;</span><i>Salvelinus fontinalis</i><span>. The relative abundance of age-0 WCT was positively associated with road density and inversely related to wetted width, canopy cover, and elevation. The presence of age-1 and older (age-1+) WCT was positively related to gradient, canopy cover, and elevation, but negatively associated with road density, temperature, stream depth, and the presence of BKT. Relative abundance of age-1+WCT was positively associated with gradient, large substrate, canopy cover, and road density. Conversely, the relative abundance of age-1+WCT was inversely related to wetted width and elevation. This research indicates that WCT populations can persist in response to altered landscapes when suitable habitat exists. However, unmitigated threats, such as nonnative species competition (e.g., BKT), hybridization with Rainbow Trout&nbsp;</span><i>O. mykiss</i><span>, habitat loss, and habitat fragmentation, pose persistent complications to WCT abundance in locations where populations appear robust but their actual abundance is unknown.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10450","usgsCitation":"Heckel, J.W., Quist, M.C., Watkins, C.J., and Dux, A.M., 2020, Distribution and abundance of Westslope Cutthroat Trout in relation to habitat characteristics at multiple spatial scales: North American Journal of Fisheries Management, v. 40, no. 4, p. 893-909, https://doi.org/10.1002/nafm.10450.","productDescription":"17 p,","startPage":"893","endPage":"909","ipdsId":"IP-107683","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":393744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"St. Maries River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.707763671875,\n              46.878968335076856\n            ],\n            [\n              -115.631103515625,\n              46.878968335076856\n            ],\n            [\n              -115.631103515625,\n              47.372314620566925\n            ],\n            [\n              -116.707763671875,\n              47.372314620566925\n            ],\n            [\n              -116.707763671875,\n              46.878968335076856\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"40","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-04-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Heckel, John W","contributorId":270716,"corporation":false,"usgs":false,"family":"Heckel","given":"John","email":"","middleInitial":"W","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":829822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":829821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watkins, Carson J.","contributorId":171708,"corporation":false,"usgs":false,"family":"Watkins","given":"Carson","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":829823,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dux, Andrew M.","contributorId":212798,"corporation":false,"usgs":false,"family":"Dux","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":829824,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70211836,"text":"70211836 - 2020 - Using value of information to prioritize research needs for migratory bird management under climate change: A case study using federal land acquisition in the United States","interactions":[],"lastModifiedDate":"2020-08-07T20:52:19.472499","indexId":"70211836","displayToPublicDate":"2020-04-17T15:49:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1023,"text":"Biological Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Using value of information to prioritize research needs for migratory bird management under climate change: A case study using federal land acquisition in the United States","docAbstract":"<p><span>In response to global habitat loss, many governmental and non‐governmental organizations have implemented land acquisition programs to protect critical habitats permanently for priority species. The ability of these protected areas to meet future management objectives may be compromised if the effects of climate change are not considered in acquisition decisions. Unfortunately, the effects of climate change on ecological systems are complex and plagued by uncertainty, making it difficult for organizations to prioritize research needs to improve decision‐making. Herein, we demonstrate the use of qualitative value of information analysis to identify and prioritize which sources of uncertainty should be reduced to improve land acquisition decisions to protect migratory birds in the face of climate change. The qualitative value of information analysis process involves four steps: (</span><i>i<span>&nbsp;</span></i><span>) articulating alternative hypotheses; (</span><i>ii<span>&nbsp;</span></i><span>) determining the magnitude of uncertainty regarding each hypothesis; (</span><i>iii<span>&nbsp;</span></i><span>) evaluating the relevance of each hypothesis to acquisition decision‐making; and (</span><i>iv<span>&nbsp;</span></i><span>) assessing the feasibility of reducing the uncertainty surrounding each hypothesis through research and monitoring. We demonstrate this approach using the objectives of 3 U.S. federal land acquisition programs that focus on migratory bird management. We used a comprehensive literature review, expert elicitation, and professional judgement to evaluate 11 hypotheses about the effect of climate change on migratory birds. Based on our results, we provide a list of priorities for future research and monitoring to reduce uncertainty and improve land acquisition decisions for the programs considered in our case study. Reducing uncertainty about how climate change will influence the spatial distribution of priority species and biotic homogenization were identified as the highest priorities for future research due to both the value of this information for improving land acquisition decisions and the feasibility of reducing uncertainty through research and monitoring. Research on how changes in precipitation patterns and winter severity will influence migratory bird abundance is also expected to benefit land acquisition decisions. By contrast, hypotheses about phenology and migration distance were identified as low priorities for research. By providing a rigorous and transparent approach to prioritizing research, we demonstrate that qualitative value of information is a valuable tool for prioritizing research and improving management decisions in other complex, high‐uncertainty cases where traditional quantitative value of information analysis is not possible. Given the inherent complexity of ecological systems under climate change, and the difficulty of identifying management‐relevant research priorities, we expect this approach to have wide applications within the field of natural resource management.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/brv.12602","usgsCitation":"Rushing, C.S., Rubenstein, M.A., Lyons, J.E., and Runge, M.C., 2020, Using value of information to prioritize research needs for migratory bird management under climate change: A case study using federal land acquisition in the United States: Biological Reviews, v. 95, no. 4, p. 1109-1130, https://doi.org/10.1111/brv.12602.","productDescription":"22 p.","startPage":"1109","endPage":"1130","ipdsId":"IP-111311","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":377204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"95","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Rushing, Clark S","contributorId":237020,"corporation":false,"usgs":false,"family":"Rushing","given":"Clark","email":"","middleInitial":"S","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":795310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rubenstein, Madeleine A. 0000-0001-8569-781X mrubenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-8569-781X","contributorId":203206,"corporation":false,"usgs":true,"family":"Rubenstein","given":"Madeleine","email":"mrubenstein@usgs.gov","middleInitial":"A.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":795311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":795312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":795313,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70205557,"text":"sim3440 - 2020 - Bedrock geologic map of the Mount Ascutney 7.5- x 15-minute quadrangle, Windsor County, Vermont, and Sullivan County, New Hampshire","interactions":[],"lastModifiedDate":"2020-04-30T13:49:33.821916","indexId":"sim3440","displayToPublicDate":"2020-04-17T15:35:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3440","displayTitle":"Bedrock Geologic Map of the Mount Ascutney 7.5- x 15-Minute Quadrangle, Windsor County, Vermont, and Sullivan County, New Hampshire","title":"Bedrock geologic map of the Mount Ascutney 7.5- x 15-minute quadrangle, Windsor County, Vermont, and Sullivan County, New Hampshire","docAbstract":"<p>The bedrock geology of the Mount Ascutney 7.5- x 15-minute quadrangle consists of highly deformed and metamorphosed Mesoproterozoic through Devonian metasedimentary and meta-igneous rocks intruded by rocks of the Mesozoic White Mountain Igneous Suite. In the west, Mesoproterozoic gneisses of the Mount Holly Complex are the oldest rocks and form the northeastern flank of the Chester dome. The allochthonous Cambrian through Ordovician rocks include the Moretown and Cram Hill Formations and the North River Igneous Suite; these rocks structurally overlie the Chester dome along the Keyes Mountain thrust fault. Silurian and Devonian metasedimentary and metavolcanic rocks of the Connecticut Valley trough (CVT) unconformably overlie the pre-Silurian rocks. The easternmost extent of the CVT in New Hampshire is exposed in the Meriden antiform. Ordovician to Silurian and Devonian metasedimentary rocks of the Bronson Hill anticlinorium structurally overlie the CVT along the Monroe thrust fault. The oldest part of the Bronson Hill anticlinorium, called the Bronson Hill arc, consists of Ordovician metamorphosed volcanic, plutonic, and sedimentary rocks of the Ammonoosuc Volcanics, the Partridge Formation, and the Oliverian Plutonic Suite. The rocks of the Bronson Hill arc may be partly correlative with the pre-Silurian rocks above the Chester dome and are exposed in two fault-bounded structural belts (Cornish City and Claremont belts) and in the Sugar River dome. Collectively, these belts form the regional Orfordville anticlinorium, Hardscrabble synclinorium, and the western part of the broader Bronson Hill anticlinorium in western New Hampshire. Silurian to Devonian metasedimentary rocks of the Clough Quartzite, and Fitch and Littleton Formations unconformably overlie the rocks of the Bronson Hill arc. Devonian granitic and pegmatitic dikes and sills of the New Hampshire Plutonic Suite intruded previously deformed rocks. Post-tectonic Cretaceous plutonic and volcanic rocks of the Ascutney Mountain Intrusive Complex underlie Mount Ascutney. Because of the historically significant scientific research, and its prominence in the landscape, Mount Ascutney is commonly regarded as Vermont’s most famous volcano.</p><p>The bedrock geology was mapped to study the tectonic history of the area and to provide a framework for ongoing characterization of the bedrock of Vermont and New Hampshire. This Scientific Investigations Map of the Mount Ascutney 7.5- x 15-minute quadrangle consists of sheets 1 and 2 as well as a geographic information system (GIS) database that includes bedrock geologic units, faults, outcrops, structural geologic information, geochemistry, and photographs. Sheet 1 of the report includes a bedrock geologic map, a correlation of map units, and a description of map units. Sheet 2 includes a discussion of the geology, references, three cross sections from the geologic map on sheet 1, igneous rock geochemistry results of the main map units from the Mount Ascutney stock, a tectonic map showing major structural features, and a structural domain map showing the orientation and distribution of brittle features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3440","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey; State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey; and the National Park Service","usgsCitation":"Walsh, G.J., Valley, P.M., Thompson, P.J., Ratcliffe, N.M., Proctor, B.P., and Sicard, K.R., 2020, Bedrock geologic map of the Mount Ascutney 7.5- x 15-minute quadrangle, Windsor County, Vermont, and Sullivan County, New Hampshire (ver. 1.1, April 2020): U.S. Geological Survey Scientific Investigations Map 3440, 2 sheets, scale 1:24,000, https://doi.org/10.3133/sim3440.","productDescription":"2 Sheets: 61.00 x 40.81 inches and 57.00 x 40.50 inches; Read Me; Spatial Data; Metadata; Companion Files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-090096","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":374082,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3440/versionHist.txt","text":"Version History","size":"2.17 KB","linkFileType":{"id":2,"text":"txt"}},{"id":374079,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3440/coverthb4.jpg"},{"id":374081,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_sheet2.pdf","text":"Sheet 2","size":"27.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":""},{"id":374080,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_sheet1.pdf","text":"Sheet 1","size":"26.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3440"},{"id":374083,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_readme.txt","text":"Read Me","size":"13.1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":374087,"rank":9,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_openaccess.zip","text":"Open Access","size":"6.09 MB","linkFileType":{"id":6,"text":"zip"}},{"id":374086,"rank":8,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_metadata.zip","text":"Metadata","size":"366 KB","linkFileType":{"id":6,"text":"zip"}},{"id":374085,"rank":7,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_database.zip","text":"Database","size":"6.58 MB","linkFileType":{"id":6,"text":"zip"}},{"id":374084,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_basemap.zip","text":"Base Map","size":"43.7 MB","linkFileType":{"id":6,"text":"zip"}},{"id":374088,"rank":10,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_photos.zip","text":"Photos","size":"577 MB","linkFileType":{"id":6,"text":"zip"}}],"country":"United States","state":"New Hampshire, Vermont","county":"Sullivan County, Windsor County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -72.5,\n              43.375\n            ],\n            [\n              -72.25,\n              43.375\n            ],\n            [\n              -72.25,\n              43.5\n            ],\n            [\n              -72.5,\n              43.5\n            ],\n            [\n              -72.5,\n              43.375\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"","edition":"Version 1.1: April 2020; Version 1.0: April 2020","contact":"<p><a href=\"https://www.usgs.gov/centers/fbgc\" data-mce-href=\"https://www.usgs.gov/centers/fbgc\">Florence Bascom Geoscience Center</a><br>U.S. Geological Survey<br>926A National Center<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2020-04-10","revisedDate":"2020-04-17","noUsgsAuthors":false,"publicationDate":"2020-04-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Walsh, Gregory J. 0000-0003-4264-8836 gwalsh@usgs.gov","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":873,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory","email":"gwalsh@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":771632,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Valley, Peter M. 0000-0002-9957-0403 pvalley@usgs.gov","orcid":"https://orcid.org/0000-0002-9957-0403","contributorId":4809,"corporation":false,"usgs":true,"family":"Valley","given":"Peter","email":"pvalley@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":771639,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Peter J.","contributorId":56523,"corporation":false,"usgs":true,"family":"Thompson","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":771640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ratcliffe, Nicholas M. 0000-0002-7922-5784 nratclif@usgs.gov","orcid":"https://orcid.org/0000-0002-7922-5784","contributorId":4167,"corporation":false,"usgs":true,"family":"Ratcliffe","given":"Nicholas","email":"nratclif@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":771641,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Proctor, Brooks P. 0000-0002-4878-8728 bproctor@usgs.gov","orcid":"https://orcid.org/0000-0002-4878-8728","contributorId":219209,"corporation":false,"usgs":false,"family":"Proctor","given":"Brooks","email":"bproctor@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":771642,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sicard, Karri R. 0000-0003-4062-8030","orcid":"https://orcid.org/0000-0003-4062-8030","contributorId":219210,"corporation":false,"usgs":false,"family":"Sicard","given":"Karri","email":"","middleInitial":"R.","affiliations":[],"preferred":true,"id":771651,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70228644,"text":"70228644 - 2020 - Preliminary investigation of the critically imperiled Caney Mountain cave crayfish Orconectes stygocaneyi Hobbs III, 2001 (Decapoda: Cambaridae) in Missouri, USA","interactions":[],"lastModifiedDate":"2022-02-16T20:51:34.474746","indexId":"70228644","displayToPublicDate":"2020-04-17T14:43:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5290,"text":"Freshwater Crayfish","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Preliminary investigation of the critically imperiled Caney Mountain cave crayfish <i>Orconectes stygocaneyi </i>Hobbs III, 2001 (Decapoda: Cambaridae) in Missouri, USA","title":"Preliminary investigation of the critically imperiled Caney Mountain cave crayfish Orconectes stygocaneyi Hobbs III, 2001 (Decapoda: Cambaridae) in Missouri, USA","docAbstract":"<p><span>The Caney Mountain cave crayfish (</span><i>Orconectes stygocaneyi</i><span>) is one of North America's rarest crayfish, endemic to one cave in southern Missouri, USA. The species is listed as 'critically imperiled' by Missouri, and 'threatened' by the American Fisheries Society. Previously, only 15 crayfish have been observed in Mud Cave, and only two have been collected (for original species description). We aimed to collect the first natural history data on the species and search adjacent caves and springs for additional populations. Twelve visual searches and supplemental trapping over four years, in all seasons, yielded 69&nbsp;</span><i>O. stygocaneyi</i><span>&nbsp;(including 11 young-of-year) observations and capture of 22 crayfish, including one ovigerous female. Visual searches of nearby caves and springs yielded no&nbsp;</span><i>O. stygocaneyi</i><span>&nbsp;records. However, multiple surveys of those caves and springs, using environmental DNA detected the species in one additional cave adjacent to Mud Cave, but only during spring high flow events when the caves may be ephemerally connected.&nbsp;</span><i>Orconectes stygocaneyi</i><span>'s distribution is among the most restricted of any North American crayfish, and further evaluation of its conservation status designations might be warranted. Long term conservation of&nbsp;</span><i>O. stygocaneyi</i><span>&nbsp;would benefit from management practices promoting sustained, unimpacted surface runoff within Mud Cave's recharge area.</span></p>","language":"English","publisher":"International Association of Astacology","doi":"10.5869/fc.2020.v25-1.047","usgsCitation":"DiStefano, R., Ashley, D., Brewer, S.K., Mouser, J., and Neimiller, M., 2020, Preliminary investigation of the critically imperiled Caney Mountain cave crayfish Orconectes stygocaneyi Hobbs III, 2001 (Decapoda: Cambaridae) in Missouri, USA: Freshwater Crayfish, v. 25, no. 1, p. 47-57, https://doi.org/10.5869/fc.2020.v25-1.047.","productDescription":"11 p.","startPage":"47","endPage":"57","ipdsId":"IP-113351","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":396037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Mud Lake","volume":"25","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"DiStefano, Robert  J.","contributorId":213268,"corporation":false,"usgs":false,"family":"DiStefano","given":"Robert  J.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":834913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashley, D.C.","contributorId":244487,"corporation":false,"usgs":false,"family":"Ashley","given":"D.C.","email":"","affiliations":[{"id":48915,"text":"Missouri Western State University","active":true,"usgs":false}],"preferred":false,"id":834914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mouser, J.B.","contributorId":244447,"corporation":false,"usgs":false,"family":"Mouser","given":"J.B.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":834916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neimiller, M.","contributorId":279385,"corporation":false,"usgs":false,"family":"Neimiller","given":"M.","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":834917,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70211909,"text":"70211909 - 2020 - Millennial-scale climate and human drivers of environmental change and fire activity in a dry, mixed-conifer forest of northwestern Montana","interactions":[],"lastModifiedDate":"2020-08-11T18:31:53.806671","indexId":"70211909","displayToPublicDate":"2020-04-17T13:25:21","publicationYear":"2020","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":"Millennial-scale climate and human drivers of environmental change and fire activity in a dry, mixed-conifer forest of northwestern Montana","docAbstract":"<p><span>Warm summer temperatures and longer fire seasons are promoting larger, and in some cases, more fires that are severe in low- and mid-elevation, dry mixed-conifer forests of the Northern Rocky Mountains (NRM). Long-term historical fire conditions and human influence on past fire activity are not well understood for these topographically and biophysically heterogeneous forests. We developed reconstructions of millennial-scale fire activity, vegetation change, and human presence at Black Lake, a small closed-basin lake on the Flathead Indian Reservation in the Mission Valley, Northwestern Montana, United States. Fossil pollen, charcoal, and biomarkers associated with human presence were used to evaluate the interaction between climate variability, fire activity, vegetation change and human activity for the past 7000 years. Comparisons among multiple proxies suggest climate variability acted as the primary control on fire activity and vegetation change from the early Holocene until the late Holocene when records suggest fire activity and climate variability decoupled. Specific biomarkers (5β-stanols including coprostanol and epi-coprostanol) associated with human presence indicate humans were present within the Black Lake watershed for thousands of years, although the inferred intensity of human presence is highly variable. A strong relationship between climate variability and fire activity during the early and mid-Holocene weakens during the last few thousand years, suggesting possible increased influence of humans in mediating fire activity in recent millennia, and/or a shift in the interaction between the distribution and abundance of woody fuel and fire severity. Human-set fires during the cooler and wetter late Holocene may have been aimed at maintaining important cultural resources associated with the heterogeneous mosaic of mixed conifer forests within the Black Lake watershed. The paleoenvironmental reconstruction at Black Lake corroborates archeological records that show humans were present within the Black Lake watershed for over 7000 years. Further research is needed to evaluate the evidence for this continuous presence and the possible role that people played in shaping fire regimes and vegetation within low- to mid-elevation mixed-conifer ecosystems of the NRM.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/ffgc.2020.00044","usgsCitation":"McWethy, D.B., Alt, M., Argiriadis, E., Battistel, D., Everett, R.G., and Pederson, G.T., 2020, Millennial-scale climate and human drivers of environmental change and fire activity in a dry, mixed-conifer forest of northwestern Montana: Frontiers in Forests and Global Change, v. 3, 44, 16 p., https://doi.org/10.3389/ffgc.2020.00044.","productDescription":"44, 16 p.","ipdsId":"IP-113284","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":457040,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffgc.2020.00044","text":"Publisher Index Page"},{"id":377364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Black Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.33162689208984,\n              47.85907299252274\n            ],\n            [\n              -114.31686401367188,\n              47.85907299252274\n            ],\n            [\n              -114.31686401367188,\n              47.868631827737\n            ],\n            [\n              -114.33162689208984,\n              47.868631827737\n            ],\n            [\n              -114.33162689208984,\n              47.85907299252274\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"McWethy, David B.","contributorId":207232,"corporation":false,"usgs":false,"family":"McWethy","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":795763,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alt, Mio","contributorId":237993,"corporation":false,"usgs":false,"family":"Alt","given":"Mio","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":795764,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Argiriadis, Elana","contributorId":237994,"corporation":false,"usgs":false,"family":"Argiriadis","given":"Elana","email":"","affiliations":[{"id":47673,"text":"Ca’ Foscari University of Venice","active":true,"usgs":false}],"preferred":false,"id":795765,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Battistel, Dario","contributorId":205865,"corporation":false,"usgs":false,"family":"Battistel","given":"Dario","email":"","affiliations":[{"id":37181,"text":"Department of Environmental Science, Informatics and Statistics, Ca' Foscari University of Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":795766,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Everett, Richard G.","contributorId":221184,"corporation":false,"usgs":false,"family":"Everett","given":"Richard","email":"","middleInitial":"G.","affiliations":[{"id":37636,"text":"Salish Kootenai College","active":true,"usgs":false}],"preferred":false,"id":795767,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":795768,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70220209,"text":"70220209 - 2020 - Seasonal manganese transport in the hyporheic zone of a snowmelt-dominated river (East River, Colorado)","interactions":[],"lastModifiedDate":"2021-04-27T17:16:33.696458","indexId":"70220209","displayToPublicDate":"2020-04-17T12:10:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal manganese transport in the hyporheic zone of a snowmelt-dominated river (East River, Colorado)","docAbstract":"<p><span>Manganese (Mn) plays a critical role in river-water quality because Mn-oxides serve as sorption sites for contaminant metals. The aim of this study is to understand the seasonal cycling of Mn in an alpine streambed that experiences large spring snowmelt events and the potential responses to changes in snowmelt timing and magnitude. To address this goal, annual variations in river-water/groundwater interaction and Mn</span><sub>(aq)</sub><span>&nbsp;transport were measured and modeled in the bed of East River, Colorado, USA. In observations and numerical models, oxygenated river water containing dissolved organic carbon (DOC) mixes with groundwater rich in Mn</span><sub>(aq)</sub><span>&nbsp;in the streambed. The mixing depth increases during spring snowmelt when river discharge increases, leading to a greater DOC supply to the hyporheic zone and net respiration of Mn-oxides, despite an enhanced supply of oxygen. As groundwater upwelling resumes during the subsequent baseflow period, Mn</span><sub>(aq)</sub><span>-rich groundwater mixes with oxygenated river water, resulting in net accumulation of Mn-oxides until the bed freezes in winter. To explore potential responses of Mn transport to different climate-induced hydrological regimes, three hydrograph scenarios were numerically modeled (historic, low-snow, and storm) for the Rocky Mountain region. In a warming climate, Mn</span><sub>(aq)</sub><span>&nbsp;export to the river decreases, and Mn</span><sub>(aq)</sub><span>&nbsp;oxidation is favored in the upper streambed sediments over more of the year. One important implication is that the streambed may have an increased sorption capacity for metals over more of the year, leading to potential changes in river-water quality.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10040-020-02146-6","usgsCitation":"Bryant, S., Sawyer, A., Briggs, M., Saup, C., Nelson, A.R., Wilkins, M.J., Christensen, J.R., and Williams, K.H., 2020, Seasonal manganese transport in the hyporheic zone of a snowmelt-dominated river (East River, Colorado): Hydrogeology Journal, v. 28, p. 1323-1341, https://doi.org/10.1007/s10040-020-02146-6.","productDescription":"19 p.","startPage":"1323","endPage":"1341","ipdsId":"IP-115069","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":385333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"East River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.95238709449768,\n              38.92190699243362\n            ],\n            [\n              -106.94936156272888,\n              38.92190699243362\n            ],\n            [\n              -106.94936156272888,\n              38.923893566458055\n            ],\n            [\n              -106.95238709449768,\n              38.923893566458055\n            ],\n            [\n              -106.95238709449768,\n              38.92190699243362\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"28","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Bryant, S.","contributorId":222764,"corporation":false,"usgs":false,"family":"Bryant","given":"S.","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":814777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sawyer, A.","contributorId":222761,"corporation":false,"usgs":false,"family":"Sawyer","given":"A.","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":814778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":257637,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":814779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saup, C.","contributorId":222763,"corporation":false,"usgs":false,"family":"Saup","given":"C.","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":814780,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, A. R","contributorId":193402,"corporation":false,"usgs":false,"family":"Nelson","given":"A.","email":"","middleInitial":"R","affiliations":[],"preferred":false,"id":814781,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilkins, M. J.","contributorId":176779,"corporation":false,"usgs":false,"family":"Wilkins","given":"M.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":814782,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Christensen, J. R.","contributorId":204686,"corporation":false,"usgs":false,"family":"Christensen","given":"J.","email":"","middleInitial":"R.","affiliations":[{"id":36974,"text":"U.S. Environmental Protection Agency, National Exposure Research Laboratory, Las Vegas, NV","active":true,"usgs":false}],"preferred":false,"id":814783,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, K. H.","contributorId":176777,"corporation":false,"usgs":false,"family":"Williams","given":"K.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":814784,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70208957,"text":"sim3451 - 2020 - Geologic map of the Homestake Reservoir 7.5′ quadrangle, Lake, Pitkin, and Eagle Counties, Colorado","interactions":[],"lastModifiedDate":"2020-04-30T13:51:00.671496","indexId":"sim3451","displayToPublicDate":"2020-04-17T11:50:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3451","title":"Geologic map of the Homestake Reservoir 7.5′ quadrangle, Lake, Pitkin, and Eagle Counties, Colorado","docAbstract":"<p>The Homestake Reservoir 7.5' quadrangle lies at the northwestern end of the Upper Arkansas Valley, and headwaters of the Arkansas River, and the Roaring Fork, Fryingpan, and Eagle Rivers of the Colorado River system.&nbsp; The quadrangle lies within tectonic provinces of the 1.4 giga-annum (Ga) Picuris orogeny and includes the late Paleozoic Ancestral Rockies, Late Cretaceous-Paleocene Laramide orogeny, Oligocene-to-Miocene and Pliocene? volcanism, and Miocene to the present Rio Grande rift extensional tectonics. In the eastern half of the quadrangle, high-angle, east-dipping, Neogene normal faults displace Proterozoic rocks, and locally Miocene-to-Pliocene? volcanic rocks.&nbsp; Many quartz veins and hydrothermally altered zones are exposed along the eastern flank of the quadrangle, indicative of the multiple tectonic episodes the region has experienced.&nbsp; The main intent of the map is to unravel the structural complexity by partitioning the structures and volcanism within the appropriate geologic interval.&nbsp; This ultimately permits accurate identification of geomorphic features suitable for chronologies related to landscape evolution studies, seismic and other natural hazard identification, ground and surface water modeling, and paleoclimatic studies.&nbsp; Within the western half of the quadrangle, Mesoproterozoic and Paleoproterozoic igneous and metamorphic rocks of 1.4 Ga St. Kevin Granite and 1.8–1.7 Ga Biotite gneiss and schist, respectively, are uplifted along the generally east-dipping, high-angle Sawatch fault system. In the northwest portion of the quadrangle, strands of the Homestake shear zone have been mapped, dated and assigned to the 1.4 Ga Picuris orogeny of northern New Mexico. <sup>10</sup>Be and <sup>26</sup>Al cosmogenic nuclide ages of the youngest glacial deposits indicate a last glacial maximum age of about 22–21 kilo-annum (ka) and complete deglaciation by about 14 kilo-annum, supported by chronologic studies in adjacent drainages. The Turquoise Lake impounding lateral and terminal moraine complex was deposited during late Pleistocene glacial maximum ~22–21 ka. No late Pleistocene tectonic activity is apparent within the quadrangle.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sim3451","collaboration":"","usgsCitation":"Ruleman, C.A., Frothingham, M.G., Brandt, T.R., Shaw, C.A., Caffee, M.W., Brugger, K.A., and Goehring, B.M., 2020, Geologic map of the Homestake Reservoir 7.5' quadrangle, Lake, Pitkin, and Eagle Counties, Colorado: U.S. Geological Survey Scientific Investigations Map 3451, scale 1:24,000, https://doi.org/10.3133/sim3451.","productDescription":"3 Sheets: 54.00 x 48.50 inches; Read Me; Data Release","onlineOnly":"Y","ipdsId":"IP-088811","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":373759,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3451/coverthb.jpg"},{"id":373763,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3451/sim3451_ReadMe.txt","text":" Read Me","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3451 read me"},{"id":373762,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3451/sim3451_georeferenced.pdf","text":"Geologic Map of the Homestake Reservoir 7.5' Quadrangle, Eagle, Lake, and Pitkin Counties, Colorado","size":"165 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3451 georeferenced","linkHelpText":"(interactive georeferenced map with the shaded relief and topographic base layers)"},{"id":373764,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ON6QBE","text":"USGS data release","linkHelpText":"Data release for Geologic Map of the Homestake Reservoir 7.5' quadrangle, Lake, Pitkin, and Eagle Counties, Colorado"},{"id":373760,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3451/sim3451.pdf","text":"Geologic Map of the Homestake Reservoir 7.5' Quadrangle, Eagle, Lake, and Pitkin Counties, Colorado","size":"72.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3451 print quality","linkHelpText":"(print quality)"},{"id":373761,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3451/sim3451_hillshade_base.pdf","text":"Geologic Map of the Homestake Reservoir 7.5' Quadrangle, Eagle, Lake, and Pitkin Counties, Colorado","size":"54.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3451 hillshade base","linkHelpText":"(map with the shaded relief base)"}],"country":"United States","state":"Colorado","county":"Eagle County, Lake County, Pitkin County","otherGeospatial":"Homestake Reservoir","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.5,\n             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cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":784191,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frothingham, Michael G. 0000-0002-3502-1931","orcid":"https://orcid.org/0000-0002-3502-1931","contributorId":223119,"corporation":false,"usgs":false,"family":"Frothingham","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":40675,"text":"Montana State University, Bozeman","active":true,"usgs":false}],"preferred":false,"id":784194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandt, Theodore R. 0000-0002-7862-9082 tbrandt@usgs.gov","orcid":"https://orcid.org/0000-0002-7862-9082","contributorId":1267,"corporation":false,"usgs":true,"family":"Brandt","given":"Theodore","email":"tbrandt@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":786415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shaw, Colin A. 0000-0002-5820-3973","orcid":"https://orcid.org/0000-0002-5820-3973","contributorId":223118,"corporation":false,"usgs":false,"family":"Shaw","given":"Colin","email":"","middleInitial":"A.","affiliations":[{"id":40675,"text":"Montana State University, Bozeman","active":true,"usgs":false}],"preferred":false,"id":784192,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caffee, Marc W. 0000-0002-6846-8967","orcid":"https://orcid.org/0000-0002-6846-8967","contributorId":193417,"corporation":false,"usgs":false,"family":"Caffee","given":"Marc","email":"","middleInitial":"W.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":786416,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goehring, Brent M. 0000-0001-6405-5156","orcid":"https://orcid.org/0000-0001-6405-5156","contributorId":203321,"corporation":false,"usgs":false,"family":"Goehring","given":"Brent","email":"","middleInitial":"M.","affiliations":[{"id":36600,"text":"Department of Earth and Environmental Sciences, Tulane University, New Orleans, LA","active":true,"usgs":false}],"preferred":false,"id":784195,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brugger, Keith A. 0000-0003-0869-920X","orcid":"https://orcid.org/0000-0003-0869-920X","contributorId":191621,"corporation":false,"usgs":false,"family":"Brugger","given":"Keith","email":"","middleInitial":"A.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":784193,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70209656,"text":"fs20193074 - 2020 - Indonesia and the United States team up to reduce impacts from dangerous volcanoes","interactions":[],"lastModifiedDate":"2026-01-27T18:39:45.180511","indexId":"fs20193074","displayToPublicDate":"2020-04-17T10:42:06","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-3074","displayTitle":"Indonesia and the United States Team up to Reduce Impacts from Dangerous Volcanoes","title":"Indonesia and the United States team up to reduce impacts from dangerous volcanoes","docAbstract":"<p>With 75 historically active volcanoes, Indonesia is the world’s most volcanically active nation. Its volcanoes are legendary throughout the world, with the notorious 19th-century eruptions at Mount Tambora (1815) and Krakatau (1883), and the eruption that created the giant Toba Caldera in Sumatra (75,000 years ago)—the Earth’s largest volcanic eruption in the past 100,000 years. Just in the past 20 years, more than 36 volcanoes have erupted, some multiple times, threatening millions of people. The Government of Indonesia responds to this daunting volcanic threat from Indonesia’s Center for Volcanology and Geologic Hazards Mitigation (CVGHM) offices in Bandung. From there, dozens of staff members coordinate operations at 77 small observatories spread out across the 5,000-kilometer-long archipelago that is Indonesia. For more than 50 years, the United States has worked in partnership with the Government of Indonesia to reduce the risk of volcanic eruptions and to save lives. Today, the two governments cooperate through an agreement between CVGHM and the U.S. Geological Survey’s Volcano Disaster Assistance Program (VDAP). Each year CVGHM and VDAP representatives convene to discuss priorities for the upcoming 12 months. They outline a series of training efforts, field campaigns, equipment deployments, and timely topics that require further exploration and development.</p>","language":"English, Indonesian","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193074","usgsCitation":"Lowenstern, J.B., Kasbani, Pallister, J.S., and Ramsey, D.W., 2020, Indonesia and the United States team up to reduce impacts from dangerous volcanoes: U.S. Geological Survey Fact Sheet 2019–3074, 4 p., https://doi.org/10.3133/fs20193074.","productDescription":"4 p.","ipdsId":"IP-107441","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":374102,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3074/fs20193074_ID.pdf","text":"Report – Indonesian","size":"6.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3074 Indonesian"},{"id":374100,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3074/fs20193074_EN.pdf","text":"Report – English","size":"6.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3074 English"},{"id":374099,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3074/coverthb.jpg"}],"country":"Indonesia, United States","contact":"<p><a href=\"https://volcanoes.usgs.gov/vhp/contact.html\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://volcanoes.usgs.gov/vhp/contact.html\">Contact Information</a><br><a href=\"https://volcanoes.usgs.gov/index.html\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://volcanoes.usgs.gov/index.html\">Volcano Science Center - Menlo Park</a><br>U.S. Geological Survey <br>345 Middlefield Road, MS 910<br>Menlo Park, CA 94025</p>","publishedDate":"2020-04-17","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Lowenstern, Jacob B. 0000-0003-0464-7779 jlwnstrn@usgs.gov","orcid":"https://orcid.org/0000-0003-0464-7779","contributorId":2755,"corporation":false,"usgs":true,"family":"Lowenstern","given":"Jacob","email":"jlwnstrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":787399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kasbani","contributorId":224216,"corporation":false,"usgs":false,"family":"Kasbani","given":"","affiliations":[{"id":39684,"text":"CVGHM Indonesia","active":true,"usgs":false}],"preferred":false,"id":787400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pallister, John S. 0000-0002-2041-2147 jpallist@usgs.gov","orcid":"https://orcid.org/0000-0002-2041-2147","contributorId":2024,"corporation":false,"usgs":true,"family":"Pallister","given":"John","email":"jpallist@usgs.gov","middleInitial":"S.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":787401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ramsey, David W. 0000-0003-1698-2523 dramsey@usgs.gov","orcid":"https://orcid.org/0000-0003-1698-2523","contributorId":3819,"corporation":false,"usgs":true,"family":"Ramsey","given":"David","email":"dramsey@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":787402,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70214078,"text":"70214078 - 2020 - HESS opinions: Beyond the long-term water balance: Evolving Budyko's supply–demand framework for the Anthropocene towards a global synthesis of land-surface fluxes under natural and human-altered watersheds","interactions":[],"lastModifiedDate":"2020-09-22T16:00:25.192871","indexId":"70214078","displayToPublicDate":"2020-04-17T10:02:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"HESS opinions: Beyond the long-term water balance: Evolving Budyko's supply–demand framework for the Anthropocene towards a global synthesis of land-surface fluxes under natural and human-altered watersheds","docAbstract":"<p><span>Global hydroclimatic conditions have been substantially altered over the past century by anthropogenic influences that arise from the warming global climate and from local/regional anthropogenic disturbances. Traditionally, studies have used coupling of multiple models to understand how land-surface water fluxes vary due to changes in global climatic patterns and local land-use changes. We argue that because the basis of the Budyko framework relies on the supply and demand concept, the framework could be effectively adapted and extended to quantify the role of drivers – both changing climate and local human disturbances – in altering the land-surface response across the globe. We review the Budyko framework, along with these potential extensions, with the intent of furthering the applicability of the framework to emerging hydrologic questions. Challenges in extending the Budyko framework over various spatio-temporal scales and the use of global datasets to evaluate the water balance at these various scales are also discussed.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-24-1975-2020","usgsCitation":"Sankarasubramanian, A., Wang, D., Archfield, S.A., Reitz, M., Vogel, R., Mazrooei, A., and Mukhopadhyaya, S., 2020, HESS opinions: Beyond the long-term water balance: Evolving Budyko's supply–demand framework for the Anthropocene towards a global synthesis of land-surface fluxes under natural and human-altered watersheds: Hydrology and Earth System Sciences, v. 24, p. 1975-1984, https://doi.org/10.5194/hess-24-1975-2020.","productDescription":"10 p.","startPage":"1975","endPage":"1984","ipdsId":"IP-116284","costCenters":[{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":457044,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-24-1975-2020","text":"Publisher Index Page"},{"id":378673,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Sankarasubramanian, A. 0000-0002-7668-1311","orcid":"https://orcid.org/0000-0002-7668-1311","contributorId":241034,"corporation":false,"usgs":false,"family":"Sankarasubramanian","given":"A.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":799382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Dingbao","contributorId":166993,"corporation":false,"usgs":false,"family":"Wang","given":"Dingbao","email":"","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":799383,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":799384,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reitz, Meredith 0000-0001-9519-6103 mreitz@usgs.gov","orcid":"https://orcid.org/0000-0001-9519-6103","contributorId":196694,"corporation":false,"usgs":true,"family":"Reitz","given":"Meredith","email":"mreitz@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":799385,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vogel, Richard M","contributorId":241035,"corporation":false,"usgs":false,"family":"Vogel","given":"Richard M","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":799386,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mazrooei, Amirhossein","contributorId":241036,"corporation":false,"usgs":false,"family":"Mazrooei","given":"Amirhossein","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":799387,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mukhopadhyaya, Sudarshana","contributorId":241037,"corporation":false,"usgs":false,"family":"Mukhopadhyaya","given":"Sudarshana","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":799388,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70209734,"text":"70209734 - 2020 - A graphical causal model for resolving species identity effects and biodiversity–ecosystem function correlations","interactions":[],"lastModifiedDate":"2020-08-04T14:03:10.552315","indexId":"70209734","displayToPublicDate":"2020-04-17T09:21:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A graphical causal model for resolving species identity effects and biodiversity–ecosystem function correlations","docAbstract":"Identifying and clearly communicating the drivers of ecosystem function is a crucially important goal for both basic and applied ecology. This has proven difficult because the putative causes (e.g., environment, species identity, biodiversity, and functional traits) are numerous and correlated. The problem is exacerbated by a lack of a formal framework for unambiguously relating theoretical language to precise, quantitative expressions of that language. Using a formal framework for the graphical expression of complex causal hypotheses, we developed a causal diagram of the concepts required to comprehensively test whether hypothesized sets of functional traits mediate the relationship between community structure and ecosystem function. We then used causal analysis, simulations, and field data to develop and test analytical strategies for understanding how community structure influences ecosystem functions via functional traits. Formal causal analysis showed that biodiversity–ecosystem function correlations are non‐causal associations. Using simulations, we showed how biodiversity correlations and species identity effects can arise from misspecification or incomplete mediation by functional trait composites. We also found that different types of model misspecification result in different patterns of residuals, which may be used to diagnose gaps in functional trait hypotheses. Treating the model misspecifications eliminated associations between species identity or biodiversity and ecosystem function. Finally, we provide an example of the analysis of field data to demonstrate how to use these insights to conduct a research program that has the goal of understanding the mechanistic trait relationships that link community structure to ecosystem function.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3070","usgsCitation":"Schoolmaster, D.R., Zirbel, C.R., and Cronin, J.P., 2020, A graphical causal model for resolving species identity effects and biodiversity–ecosystem function correlations: Ecology, v. 101, no. 8, e03070, 14 p., https://doi.org/10.1002/ecy.3070.","productDescription":"e03070, 14 p.","ipdsId":"IP-113577","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":374218,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"101","issue":"8","noUsgsAuthors":false,"publicationDate":"2020-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Schoolmaster, Donald R. Jr. 0000-0003-0910-4458 schoolmasterd@usgs.gov","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":4746,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","suffix":"Jr.","email":"schoolmasterd@usgs.gov","middleInitial":"R.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":787702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zirbel, Chad R 0000-0002-9289-1722","orcid":"https://orcid.org/0000-0002-9289-1722","contributorId":224302,"corporation":false,"usgs":false,"family":"Zirbel","given":"Chad","email":"","middleInitial":"R","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":787703,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cronin, James P. 0000-0001-6791-5828 jcronin@usgs.gov","orcid":"https://orcid.org/0000-0001-6791-5828","contributorId":5834,"corporation":false,"usgs":true,"family":"Cronin","given":"James","email":"jcronin@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":787704,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70209245,"text":"gip197 - 2020 - PFAS in the environment","interactions":[],"lastModifiedDate":"2020-04-17T13:05:13.346934","indexId":"gip197","displayToPublicDate":"2020-04-17T09:10:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"197","displayTitle":"PFAS in the Environment","title":"PFAS in the environment","docAbstract":"<p>The U.S. Geological Survey (USGS) is working with Federal, State, and local partners to monitor and evaluate perfluoroalkyl and polyfluoroalkyl substances (PFAS) in the State’s groundwater and surface waters. PFAS are synthetic chemicals with widespread commercial and industrial use that can take a very long time to break down in the environment and may affect human health. The USGS in New York is working with experts across the Nation to develop and implement rigorous and innovative techniques to detect PFAS at concentrations as low as parts per trillion to help the public understand the spatial distribution and magnitude of PFAS contamination within the environment.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip197","collaboration":"","usgsCitation":"U.S. Geological Survey, 2020, PFAS in the environment: U.S. Geological Survey General Information Product 197, 2 p., https://doi.org/10.3133/gip197.","productDescription":"Postcard","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-114421","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":373952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/197/coverthb.jpg"},{"id":374090,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/197/gip197.pdf","text":"Report","size":"400 KB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"<p><a href=\"mailto:dc_ny@usgs.gov\" data-mce-href=\"mailto:dc_ny@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/ny-water\" data-mce-href=\"https://www.usgs.gov/centers/ny-water\">New York Water Science Center</a><br>U.S. Geological Survey<br>425 Jordan Road<br>Troy, NY 12180–8349</p>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2020-04-09","noUsgsAuthors":false,"publicationDate":"2020-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":147999,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":786626,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70208345,"text":"gip196 - 2020 - Microplastics","interactions":[],"lastModifiedDate":"2020-04-17T12:51:55.346267","indexId":"gip196","displayToPublicDate":"2020-04-17T09:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"196","displayTitle":"Microplastics","title":"Microplastics","docAbstract":"<p>The U.S. Geological Survey (USGS) is working with Federal, State, and local partners to monitor and evaluate microplastics in our lakes, rivers, and coastal waters. Microplastics are very small pieces of plastic, some-times so small that they cannot be seen with the naked eye. The USGS is taking an active role in monitoring and assessing our natural resources in New York and throughout the Nation. To support microplastics research, the USGS has created two laboratories to identify the type and quantity of microplastic particles in water, air, sediment, and animal life. These results will help decisionmakers learn about the presence and potential bioavailability of microplastics in ecosystems and public water supplies.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip196","collaboration":"","usgsCitation":"U.S. Geological Survey, 2020, Microplastics: U.S. Geological Survey General Information Product 196, 2 p., https://doi.org/10.3133/gip196.","productDescription":"Postcard","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-114413","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":373951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/196/coverthb.jpg"},{"id":374089,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/196/gip196.pdf","text":"Report","size":"330 KB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"<p><a href=\"mailto:dc_ny@usgs.gov\" data-mce-href=\"mailto:dc_ny@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/ny-water\" data-mce-href=\"https://www.usgs.gov/centers/ny-water\">New York Water Science Center</a><br>U.S. Geological Survey<br>425 Jordan Road<br>Troy, NY 12180–8349</p>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2020-04-08","noUsgsAuthors":false,"publicationDate":"2020-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":128240,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":786625,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70250893,"text":"70250893 - 2020 - Temporal magnetotellurics reveals mechanics of the 2012 Mount Tongariro, NZ eruption","interactions":[],"lastModifiedDate":"2024-01-11T14:37:49.410046","indexId":"70250893","displayToPublicDate":"2020-04-17T08:35:58","publicationYear":"2020","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":"Temporal magnetotellurics reveals mechanics of the 2012 Mount Tongariro, NZ eruption","docAbstract":"<div class=\"article-section__content en main\"><p>Monitoring dynamics of volcanic eruptions with geophysics is challenging. In August and November 2012, two small eruptions from Mount Tongariro provided a unique opportunity to image subsurface changes caused by the eruptions. A detailed magnetotelluric survey of the Tongariro volcanic complex completed prior to the eruption (2008–2010) provides the preeruption structure of the magmatic system. A subset of the initial measurement locations was reoccupied in June 2013. Significant changes were observed in phase tensor data at sites close to the eruptive center. Although subsurface electrical resistivity changed, the geometry of the preeruptive reservoir did not. These subsurface resistivity variations are interpreted as being predominantly caused by interaction of partial melt and the overlying brine layer causing volume reduction of the brine layer through phreatic eruption. The ability to detect significant changes associated with the magma reservoir suggests that magnetotellurics can be a valuable volcano monitoring tool.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GL086429","usgsCitation":"Hill, G.J., Bibby, H.M., Peacock, J., Wallin, E., Ogawa, Y., Caricchi, L., Keys, H., Bennie, S.L., and Avram, Y., 2020, Temporal magnetotellurics reveals mechanics of the 2012 Mount Tongariro, NZ eruption: Geophysical Research Letters, v. 47, no. 8, e2019GL086429, 9 p., https://doi.org/10.1029/2019GL086429.","productDescription":"e2019GL086429, 9 p.","ipdsId":"IP-110239","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":457050,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019gl086429","text":"Publisher Index Page"},{"id":424330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"Mount Tongariro","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              174.8917826692084,\n              -38.81720945582316\n            ],\n            [\n              174.8917826692084,\n              -39.76946066516869\n            ],\n            [\n              176.33099165358504,\n              -39.76946066516869\n            ],\n            [\n              176.33099165358504,\n              -38.81720945582316\n            ],\n            [\n              174.8917826692084,\n              -38.81720945582316\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"47","issue":"8","noUsgsAuthors":false,"publicationDate":"2020-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Hill, Graham J.","contributorId":333106,"corporation":false,"usgs":false,"family":"Hill","given":"Graham","email":"","middleInitial":"J.","affiliations":[{"id":79730,"text":"Czech Academy of Science","active":true,"usgs":false}],"preferred":false,"id":891953,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bibby, Hugh M.","contributorId":333107,"corporation":false,"usgs":false,"family":"Bibby","given":"Hugh","email":"","middleInitial":"M.","affiliations":[{"id":5111,"text":"GNS Science, New Zealand","active":true,"usgs":false}],"preferred":false,"id":891954,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":891955,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wallin, Erin L.","contributorId":333108,"corporation":false,"usgs":false,"family":"Wallin","given":"Erin L.","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":891956,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ogawa, Yasuo","contributorId":302663,"corporation":false,"usgs":false,"family":"Ogawa","given":"Yasuo","email":"","affiliations":[{"id":38251,"text":"Tokyo Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":891957,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caricchi, Luca 0000-0001-9051-2621","orcid":"https://orcid.org/0000-0001-9051-2621","contributorId":333109,"corporation":false,"usgs":false,"family":"Caricchi","given":"Luca","email":"","affiliations":[{"id":66013,"text":"University of Geneva, Switzerland","active":true,"usgs":false}],"preferred":false,"id":891958,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keys, Harry","contributorId":333110,"corporation":false,"usgs":false,"family":"Keys","given":"Harry","email":"","affiliations":[{"id":38703,"text":"New Zealand Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":891959,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bennie, Stewart L.","contributorId":333111,"corporation":false,"usgs":false,"family":"Bennie","given":"Stewart","email":"","middleInitial":"L.","affiliations":[{"id":5111,"text":"GNS Science, New Zealand","active":true,"usgs":false}],"preferred":false,"id":891960,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Avram, Yann","contributorId":333112,"corporation":false,"usgs":false,"family":"Avram","given":"Yann","email":"","affiliations":[{"id":79732,"text":"Phoenix Geophysics, Toronto, Canada","active":true,"usgs":false}],"preferred":false,"id":891961,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70209899,"text":"70209899 - 2020 - Modeling the supporting ecosystem services of depressional wetlands","interactions":[],"lastModifiedDate":"2020-10-28T15:24:41.697512","indexId":"70209899","displayToPublicDate":"2020-04-17T07:09:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the supporting ecosystem services of depressional wetlands","docAbstract":"We explored how a geographic information system modeling approach could be used to quantify supporting ecosystem services related to the type, abundance, and distribution of landscape components. Specifically, we use the Integrated Valuation of Ecosystem Services and Tradeoffs model to quantify habitats that support amphibians and birds, floral resources that support pollinators, native-plant communities that support regional biodiversity, and above- and below-ground carbon stores in the Des Moines Lobe ecoregion of the U.S. We quantified services under two scenarios, one that represented the 2012 Des Moines Lobe landscape, and one that simulated the conversion to crop production of wetlands and surrounding uplands conserved under the USDA Agricultural Conservation Easement Program (ACEP). While ACEP easements only covered 0.35% of the ecoregion, preserved wetlands and grasslands provided for 19,020 ha of amphibian habitat, 21,462 ha of grassland-bird habitat, 18,798 ha of high-quality native wetland plants, and 27,882 ha of floral resources for pollinators. Additionally, ACEP protected lands stored 257,722 tonnes of carbon that, if released, would result in costs in excess of 45-million USD. An integrated approach using results from a GIS-based model in combination with process-based model quantifications will facilitate more informed decisions related to ecosystem service tradeoffs.","language":"English","publisher":"Springer","doi":"10.1007/s13157-020-01297-2","usgsCitation":"Mushet, D.M., and Roth, C.L., 2020, Modeling the supporting ecosystem services of depressional wetlands: Wetlands, v. 40, p. 1061-1069, https://doi.org/10.1007/s13157-020-01297-2.","productDescription":"9 p.","startPage":"1061","endPage":"1069","ipdsId":"IP-108440","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":457054,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13157-020-01297-2","text":"Publisher Index Page"},{"id":374483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Minnesota","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -95.9326171875,\n              43.34116005412307\n            ],\n            [\n              -95.20751953125,\n              41.31082388091818\n            ],\n            [\n              -93.84521484375,\n              41.09591205639546\n            ],\n            [\n              -93.22998046875,\n              41.52502957323801\n            ],\n            [\n              -94.02099609375,\n              43.50075243569041\n            ],\n            [\n              -93.44970703125,\n              44.05601169578525\n            ],\n            [\n              -93.7353515625,\n              44.55916341529182\n            ],\n            [\n              -94.72412109375,\n              45.01141864227728\n            ],\n            [\n              -95.82275390625,\n              44.793530904744074\n            ],\n            [\n              -95.9326171875,\n              43.34116005412307\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"40","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":788546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roth, Cali L. 0000-0001-9077-2765 croth@usgs.gov","orcid":"https://orcid.org/0000-0001-9077-2765","contributorId":174422,"corporation":false,"usgs":true,"family":"Roth","given":"Cali","email":"croth@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":788547,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70209476,"text":"70209476 - 2020 - Sea-level rise exponentially increases coastal flood frequency","interactions":[],"lastModifiedDate":"2020-06-03T00:37:25.280853","indexId":"70209476","displayToPublicDate":"2020-04-16T19:34:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Sea-level rise exponentially increases coastal flood frequency","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Sea-level rise will radically redefine the coastline of the 21<sup>st</sup><span>&nbsp;</span>century. For many coastal regions, projections of global sea-level rise by the year 2100 (e.g., 0.5–2 meters) are comparable in magnitude to today’s extreme but short-lived increases in water level due to storms. Thus, the 21<sup>st</sup><span>&nbsp;</span>century will see significant changes to coastal flooding regimes (where present-day, extreme-but-rare events become common), which poses a major risk to the safety and sustainability of coastal communities worldwide. So far, estimates of future coastal flooding frequency focus on endpoint scenarios, such as the increase in flooding by 2050 or 2100. Here, we investigate the continuous shift in coastal flooding regimes by quantifying continuous rates of increase in the occurrence of extreme water-level events due to sea-level rise. We find that the odds of exceeding critical water-level thresholds increases exponentially with sea-level rise, meaning that fixed amounts of sea-level rise of only ~1–10 cm in areas with a narrow range of present-day extreme water levels can double the odds of flooding. Combining these growth rates with established sea-level rise projections, we find that the odds of extreme flooding double approximately every 5 years into the future. Further, we find that the present-day 50-year extreme water level (i.e., 2% annual chance of exceedance, based on historical records) will be exceeded annually before 2050 for most (i.e., 70%) of the coastal regions in the United States. Looking even farther into the future, the present-day 50-year extreme water level will be exceeded almost every day during peak tide (i.e., daily mean higher high water) before the end of the 21<sup>st</sup><span>&nbsp;</span>century for 90% of the U.S. coast. Our findings underscore the need for immediate planning and adaptation to mitigate the societal impacts of future flooding.</p></div></div><div id=\"Sec1-section\" class=\"c-article-section\"><br></div>","language":"English","publisher":"Nature","doi":"10.1038/s41598-020-62188-4","usgsCitation":"Taherkhani, M., Vitousek, S., Barnard, P., Frazer, L.N., Anderson, T., and Fletcher, C., 2020, Sea-level rise exponentially increases coastal flood frequency: Scientific Reports, v. 10, 6466, 17 p., https://doi.org/10.1038/s41598-020-62188-4.","productDescription":"6466, 17 p.","ipdsId":"IP-105859","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":457056,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-020-62188-4","text":"Publisher Index Page"},{"id":375284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2020-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Taherkhani, Mohsen","contributorId":223951,"corporation":false,"usgs":false,"family":"Taherkhani","given":"Mohsen","affiliations":[{"id":18137,"text":"University of Illinois at Chicago","active":true,"usgs":false}],"preferred":false,"id":786689,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":786690,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":786691,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frazer, L Neil 0000-0001-9085-8470","orcid":"https://orcid.org/0000-0001-9085-8470","contributorId":223952,"corporation":false,"usgs":false,"family":"Frazer","given":"L","email":"","middleInitial":"Neil","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":786692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Tiffany","contributorId":223953,"corporation":false,"usgs":false,"family":"Anderson","given":"Tiffany","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":786693,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fletcher, Charles 0000-0002-7256-4783","orcid":"https://orcid.org/0000-0002-7256-4783","contributorId":223954,"corporation":false,"usgs":false,"family":"Fletcher","given":"Charles","email":"","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":786694,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70209613,"text":"sir20205034 - 2020 - Updated study reporting levels (SRLs) for trace-element data collected for the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project, October 2009–October 2018","interactions":[],"lastModifiedDate":"2020-04-20T14:38:56.39101","indexId":"sir20205034","displayToPublicDate":"2020-04-16T14:28:17","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5034","displayTitle":"Updated Study Reporting Levels (SRLs) for Trace-Element Data Collected for the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project, October 2009–October 2018","title":"Updated study reporting levels (SRLs) for trace-element data collected for the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project, October 2009–October 2018","docAbstract":"<p><span>Groundwater samples have been collected in California as part of statewide investigations of groundwater quality conducted by the U.S. Geological Survey for the Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project (PBP) since 2004. The GAMA-PBP is being conducted in cooperation with the California State Water Resources Control Board to assess and monitor the quality of groundwater resources used for public and domestic drinking-water supply and to improve public knowledge of groundwater quality in California. Quality-control samples (including but not limited to field, equipment, and source-solution blanks) were collected to evaluate and quantify the quality of the groundwater sample results.</span></p><p><span>The GAMA-PBP previously determined study reporting levels (SRLs) for trace-element results based primarily on field blanks collected in California from May 2004 through March&nbsp;2013. SRLs are raised reporting levels used to reduce the likelihood of reporting false detections attributable to contamination bias. The purpose of this report is to identify any changes in the pattern or magnitude of concentrations or detections in field blanks since the last evaluation that would require changing or ending the use of SRLs implemented in October&nbsp;2009. Constituents analyzed were aluminum, antimony, arsenic, barium, beryllium, boron, cadmium, chromium, hexavalent chromium, cobalt, copper, iron, lead, lithium, manganese, molybdenum, nickel, selenium, silver, strontium, thallium, uranium, vanadium, and zinc.</span></p><p><span>For this review, data from 167 field blanks collected from October&nbsp;2009 through October&nbsp;2018 by the GAMA-PBP for trace elements were compiled. Based on a consistent pattern of decreasing cobalt and manganese concentrations in field blanks from 2009 to 2013, the GAMA-PBP decided to reevaluate all trace-element SRLs, effectively setting an end date for previously defined SRLs. Beginning October&nbsp;2013, SRLs would be determined from field-blank data collected through October&nbsp;2018. The detection frequency and upper limit of potential contamination bias (BD-90/90) were determined from field blanks for each trace element. The BD-90/90, that is, the upper 90-percent confidence limit of the 90th percentile concentration of potential extrinsic contamination, was calculated by assuming the binomial probability distribution. These results were compared to each constituent’s detection limit to determine whether an SRL was necessary to minimize the potential for detections in the groundwater samples, attributed principally to contamination bias. Results of the evaluation were used to set SRLs for trace-element data collected by the GAMA-PBP between October&nbsp;2013 and October&nbsp;2018. Trace elements prescribed an SRL based on this review were hexavalent chromium, cobalt, copper, lead, and zinc. This review also resulted in the removal of SRLs from iron, manganese, molybdenum, and nickel. Although an SRL for hexavalent chromium could not be evaluated in the earlier reviews because the data were not collected regularly until 2015, one was established herein as 0.34 micrograms per liter (µg/L). The SRL for cobalt, as previously implemented, had been to reject all results; it was changed to 0.16 µg/L following a reduction in cobalt field-blank detection frequency resulting from mitigation steps, starting in 2014, aimed at reducing contamination bias introduced by high-capacity capsule filters used during sample collection. The SRL for copper did not change, and the SRL for lead changed very little based on this review. Lastly, the SRL for zinc was lowered from 6.2 µg/L to 3.9 µg/L.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205034","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment Program<br>Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Bennett, G.L. V, 2020, Updated study reporting levels (SRLs) for trace-element data collected for the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project, October 2009–October 2018: U.S. Geological Survey Scientific Investigations Report 2020–5034, 24 p., https://doi.org/​10.3133/​sir20205034.","productDescription":"Report: vi, 24 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-109950","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":374030,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5034/coverthb.jpg"},{"id":374031,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5034/sir20205034.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5034"},{"id":374032,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TRFPUO","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Blank results for trace-element data collected for the California Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project, October 2009–October 2018"}],"country":"United 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 \"}}]}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>, <a href=\"https://ca.water.usgs.gov\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a><br>U.S. Geological Survey<br>6000 J Street, Placer Hall<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Methods</li><li>Results</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishedDate":"2020-04-16","noUsgsAuthors":false,"publicationDate":"2020-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Bennett, George L. V V 0000-0002-6239-1604 georbenn@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-1604","contributorId":1373,"corporation":false,"usgs":true,"family":"Bennett","given":"George","suffix":"V","email":"georbenn@usgs.gov","middleInitial":"L. V","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787174,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70208867,"text":"ofr20201019 - 2020 - Science plan for improving three-dimensional seismic velocity models in the San Francisco Bay region, 2019–24","interactions":[],"lastModifiedDate":"2020-04-17T11:17:05.742879","indexId":"ofr20201019","displayToPublicDate":"2020-04-16T13:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1019","displayTitle":"Science Plan for Improving Three-Dimensional Seismic Velocity Models in the San Francisco Bay Region, 2019–24","title":"Science plan for improving three-dimensional seismic velocity models in the San Francisco Bay region, 2019–24","docAbstract":"<p>This five-year science plan outlines short-term and long-term goals for improving three-dimensional seismic velocity models in the greater San Francisco Bay region as well as how to foster a community effort in reaching those goals. The short-term goals focus on improving the current U.S. Geological Survey San Francisco Bay region geologic and seismic velocity model using existing data. The long-term goals focus on acquiring new data and leveraging better analytic tools to improve the model and characterize the uncertainty. The plan describes opportunities for contributions by members of the community to develop these seismic velocity models, provides current and potential users with general information on where efforts will likely be focused to improve these models and how new versions of the models will be released, and outlines funding needs and obstacles for improving and maintaining such models. Several aspects of this plan, including how to foster a community effort, are independent of the geographic region and apply to other similar efforts.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201019","collaboration":"","usgsCitation":"Aagaard, B.T., Graymer, R.W., Thurber, C.H., Rodgers, A.J., Taira, T., Catchings, R.D., Goulet, C.A., and Plesch, A., 2020, Science plan for improving three-dimensional seismic velocity models in the San Francisco Bay region, 2019–24:  U.S. Geological Survey Open-File Report 2020–1019, 37 p., https://doi.org/10.3133/ofr20201019.","productDescription":"vi, 37 p.","onlineOnly":"Y","ipdsId":"IP-112680","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":374023,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1019/coverthb.jpg"},{"id":374024,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1019/ofr20201019.pdf","text":"Report","size":"4.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1019"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.74999999999999,\n              36.527294814546245\n            ],\n            [\n              -120.498046875,\n              36.527294814546245\n            ],\n            [\n              -120.498046875,\n              39.11301365149975\n            ],\n            [\n              -123.74999999999999,\n              39.11301365149975\n            ],\n            [\n              -123.74999999999999,\n              36.527294814546245\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/geohazards\" data-mce-href=\"https://www.usgs.gov/centers/geohazards\">Geologic Hazards Science Center</a><br>U.S. Geological Survey<br>MS 966, Box 25046<br>Denver, CO 80225</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>2018 Workshop</li><li>Short-Term Goals</li><li>Long-Term Goals</li><li>Synergy with Other Efforts</li><li>Community Building</li><li>San Francisco Bay Region 3D Seismic Velocity Models</li><li>USGS San Francisco Bay Region 3D Seismic Velocity Model</li><li>Accuracy of Simulated Ground Motions for Moderate and Large Earthquakes</li><li>Related Efforts</li><li>Next Generation SCEC Community Seismic Velocity Models</li><li>Seismic Velocity Model Representation and Access</li><li>Short-Term Goals (Years 1–2)</li><li>Long-Term Goals (Year 3 and Beyond)</li><li>Community Model Building</li><li>References Cited</li><li>Appendix 1. 2018 San Francisco Bay Region Seismic Velocity Models for Seismic Hazard Assessment Workshop</li><li>Appendix 2. 2019 San Francisco Bay Region Seismic Velocity Models for Seismic Hazard Assessment Workshop</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2020-04-16","noUsgsAuthors":false,"publicationDate":"2020-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Aagaard, Brad T. 0000-0002-8795-9833 baagaard@usgs.gov","orcid":"https://orcid.org/0000-0002-8795-9833","contributorId":192869,"corporation":false,"usgs":true,"family":"Aagaard","given":"Brad","email":"baagaard@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":783743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graymer, Russell W. 0000-0003-4910-5682 rgraymer@usgs.gov","orcid":"https://orcid.org/0000-0003-4910-5682","contributorId":1052,"corporation":false,"usgs":true,"family":"Graymer","given":"Russell","email":"rgraymer@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":787118,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thurber, Clifford H. 0000-0002-4940-4618","orcid":"https://orcid.org/0000-0002-4940-4618","contributorId":73184,"corporation":false,"usgs":false,"family":"Thurber","given":"Clifford","email":"","middleInitial":"H.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":787155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodgers, Arthur J. 0000-0002-6784-5695","orcid":"https://orcid.org/0000-0002-6784-5695","contributorId":222984,"corporation":false,"usgs":false,"family":"Rodgers","given":"Arthur","email":"","middleInitial":"J.","affiliations":[{"id":13621,"text":"Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":783746,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taira, Taka’aki 0000-0002-6170-797X","orcid":"https://orcid.org/0000-0002-6170-797X","contributorId":222985,"corporation":false,"usgs":false,"family":"Taira","given":"Taka’aki","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":783747,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Catchings, Rufus D. 0000-0002-5191-6102 catching@usgs.gov","orcid":"https://orcid.org/0000-0002-5191-6102","contributorId":1519,"corporation":false,"usgs":true,"family":"Catchings","given":"Rufus","email":"catching@usgs.gov","middleInitial":"D.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":783748,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goulet, Christine A. 0000-0002-7643-357X","orcid":"https://orcid.org/0000-0002-7643-357X","contributorId":194805,"corporation":false,"usgs":false,"family":"Goulet","given":"Christine","email":"","middleInitial":"A.","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":787152,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Plesch, Andreas 0000-0002-3355-9199","orcid":"https://orcid.org/0000-0002-3355-9199","contributorId":187765,"corporation":false,"usgs":false,"family":"Plesch","given":"Andreas","email":"","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":783750,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70228369,"text":"70228369 - 2020 - AMMonitor: Remote monitoring of biodiversity in an adaptive framework with R","interactions":[],"lastModifiedDate":"2022-02-09T16:15:07.277377","indexId":"70228369","displayToPublicDate":"2020-04-16T10:11:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"AMMonitor: Remote monitoring of biodiversity in an adaptive framework with R","docAbstract":"<p>Ecological research and management programs are increasingly using autonomous monitoring units (AMUs) to collect large volumes of acoustic and/or photo data to address pressing management objectives or research goals. The data management requirements of an AMU-based monitoring effort are often overwhelming, with a considerable amount of processing to translate raw data into models and analyses that have research and management utility. We created the r package AMMonitor to simplify the process of moving from remotely collected data to analysis and results, using a comprehensive SQLite database for data management that tracks all components of a remote monitoring program. This framework enables the tracking of analyses and research/management objectives through time. We illustrate the AMMonitor approach with the example of evaluating an occurrence-based management objective for a target species. First, we provide an overview of the database and data management approach. Next, we illustrate a few available workflows: temporally adaptive sampling, automated detection of species sounds from acoustic recordings and aggregation of automated detections into an encounter history for use in an occupancy analysis, the outcome of which can be analysed with respect to the motivating management objective. Without a comprehensive framework for efficiently moving from raw remote monitoring data collection to results and analysis, monitoring programs are limited in their capacity to systematically characterize ecological processes and inform management decisions through time. AMMonitor provides an option for such a framework. Code, comprehensive documentation, and step-by-step examples are available online at https://code.usgs.gov/vtcfwru/AMMonitor<br></p>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.13397","usgsCitation":"Balantic, C., and Donovan, T.M., 2020, AMMonitor: Remote monitoring of biodiversity in an adaptive framework with R: Methods in Ecology and Evolution, v. 11, no. 7, p. 869-877, https://doi.org/10.1111/2041-210X.13397.","productDescription":"9 p.","startPage":"869","endPage":"877","ipdsId":"IP-111168","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":457059,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13397","text":"Publisher Index Page"},{"id":395673,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-05-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Balantic, Cathleen","contributorId":275317,"corporation":false,"usgs":false,"family":"Balantic","given":"Cathleen","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":833986,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833985,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70262015,"text":"70262015 - 2020 - AMMonitor 2: Remote monitoring of biodiversity in an adaptive framework in R","interactions":[],"lastModifiedDate":"2025-01-10T15:03:51.257364","indexId":"70262015","displayToPublicDate":"2020-04-16T08:53:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"AMMonitor 2: Remote monitoring of biodiversity in an adaptive framework in R","docAbstract":"<ol class=\"\"><li>Ecological research and management programs are increasingly using autonomous monitoring units (AMUs) to collect large volumes of acoustic and/or photo data to address pressing management objectives or research goals. The data management requirements of an AMU-based monitoring effort are often overwhelming, with a considerable amount of processing to translate raw data into models and analyses that have research and management utility.</li><li>We created the<span>&nbsp;</span><span class=\"smallCaps\">r</span><span>&nbsp;</span>package AMM<span class=\"smallCaps\">onitor</span><span>&nbsp;</span>to simplify the process of moving from remotely collected data to analysis and results, using a comprehensive SQLite database for data management that tracks all components of a remote monitoring program. This framework enables the tracking of analyses and research/management objectives through time.</li><li>We illustrate the AMM<span class=\"smallCaps\">onitor</span><span>&nbsp;</span>approach with the example of evaluating an occurrence-based management objective for a target species. First, we provide an overview of the database and data management approach. Next, we illustrate a few available workflows: temporally adaptive sampling, automated detection of species sounds from acoustic recordings and aggregation of automated detections into an encounter history for use in an occupancy analysis, the outcome of which can be analysed with respect to the motivating management objective.</li><li>Without a comprehensive framework for efficiently moving from raw remote monitoring data collection to results and analysis, monitoring programs are limited in their capacity to systematically characterize ecological processes and inform management decisions through time. AMM<span class=\"smallCaps\">onitor</span><span>&nbsp;</span>provides an option for such a framework. Code, comprehensive documentation and step-by-step examples are available online at<span>&nbsp;</span><a class=\"linkBehavior\" href=\"https://code.usgs.gov/vtcfwru/AMMonitor\" data-mce-href=\"https://code.usgs.gov/vtcfwru/AMMonitor\">https://code.usgs.gov/vtcfwru/AMMonitor</a></li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.13397","usgsCitation":"Balantic, C., and Donovan, T.M., 2020, AMMonitor 2: Remote monitoring of biodiversity in an adaptive framework in R: Methods in Ecology and Evolution, v. 11, no. 7, p. 869-877, https://doi.org/10.1111/2041-210X.13397.","productDescription":"9 p.","startPage":"869","endPage":"877","ipdsId":"IP-169539","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467293,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13397","text":"Publisher Index Page"},{"id":465981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-05-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Balantic, Cathleen","contributorId":275317,"corporation":false,"usgs":false,"family":"Balantic","given":"Cathleen","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":922979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922711,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70210267,"text":"70210267 - 2020 - Disk-integrated thermal properties of Ceres measured at the millimeter wavelengths","interactions":[],"lastModifiedDate":"2020-05-27T13:37:34.575335","indexId":"70210267","displayToPublicDate":"2020-04-16T08:34:28","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":914,"text":"Astronomical Journal","active":true,"publicationSubtype":{"id":10}},"title":"Disk-integrated thermal properties of Ceres measured at the millimeter wavelengths","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>We observed Ceres at three epochs in 2015 November and 2017 September and October with Atacama Large Millimeter/submillimeter Array (ALMA) 12 m array and in 2017 October with the ALMA Compact Array (ACA), all at ~265 GHz continuum (wavelengths of ~1.1 mm) to map the temperatures of Ceres over a full rotation at each epoch. We also used 2017 October ACA observations to search for HCN. The disk-averaged brightness temperature of Ceres is measured to be between 170 and 180 K during our 2017 observations. The rotational light curve of Ceres shows a double-peaked shape with an amplitude of about 4%. Our HCN search returns a negative result with an upper limit production rate of ~2&nbsp;<strong>×</strong>&nbsp;10<sup>24</sup><span>&nbsp;</span>molecules s<sup>−1</sup>, assuming globally uniform production and a Haser model. A thermophysical model suggests that Ceres's top layer has higher dielectric absorption than lunar-like materials at a wavelength of 1 mm. However, previous observations showed that the dielectric absorption of Ceres decreases toward longer wavelengths. Such distinct dielectric properties might be related to the hydrated phyllosilicate composition of Ceres and possibly abundant micrometer-sized grains on its surface. The thermal inertia of Ceres is constrained by our modeling as likely being between 40 and 160 thermal inertia units, much higher than previous measurements at infrared wavelengths. Modeling also suggests that Ceres's light curve is likely dominated by spatial variations in its physical or compositional properties that cause changes in Ceres's observed thermal properties and dielectric absorption as it rotates.</p></div>","language":"English","publisher":"American Astronomical Society","doi":"10.3847/1538-3881/ab8305","usgsCitation":"Li, J., Moullet, A., Titus, T.N., Hsieh, H.H., and Sykes, M.V., 2020, Disk-integrated thermal properties of Ceres measured at the millimeter wavelengths: Astronomical Journal, v. 159, no. 5, https://doi.org/10.3847/1538-3881/ab8305.","ipdsId":"IP-113850","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":457061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/1538-3881/ab8305","text":"Publisher Index Page"},{"id":375069,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"159","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Jian-Yang","contributorId":152191,"corporation":false,"usgs":false,"family":"Li","given":"Jian-Yang","email":"","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":789855,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moullet, Arielle","contributorId":224979,"corporation":false,"usgs":false,"family":"Moullet","given":"Arielle","email":"","affiliations":[{"id":41014,"text":"SOFIA/USRA, Moffett Field, CA","active":true,"usgs":false}],"preferred":false,"id":789856,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":789857,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hsieh, Henry H.","contributorId":224980,"corporation":false,"usgs":false,"family":"Hsieh","given":"Henry","email":"","middleInitial":"H.","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":789858,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sykes, Mark V.","contributorId":192200,"corporation":false,"usgs":false,"family":"Sykes","given":"Mark","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":789859,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70209607,"text":"fs20203024 - 2020 - Land change monitoring, assessment, and projection","interactions":[],"lastModifiedDate":"2020-05-13T19:58:38.057648","indexId":"fs20203024","displayToPublicDate":"2020-04-15T18:07:32","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3024","displayTitle":"Land Change Monitoring, Assessment, and Projection","title":"Land change monitoring, assessment, and projection","docAbstract":"<p>There is a pressing need to monitor and understand the rapid land change happening around the world. The U.S.&nbsp;Geological Survey is developing a new capability, called Land Change Monitoring, Assessment, and Projection (LCMAP), to innovate the understanding of land change. This capability is the Earth Resources Observation and Science Center's foundation for an integrated U.S.&nbsp;Geological Survey-wide land change science framework. LCMAP supports the development of consistent data and land cover products spanning large geographic extents, over extended periods, and at a higher frequency than in the past. LCMAP provides solutions to the science and management communities’ growing need for an improved understanding of the fundamental drivers of land change, the consequences of change in human and natural systems, and feedbacks associated with land change processes.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203024","usgsCitation":"Rover, J., Brown, J.F., Auch, R.F., Sayler, K.L., Sohl, T.L., Tollerud, H.J., and Xian, G.Z., 2020, Land change monitoring, assessment, and projection: U.S. Geological Survey Fact Sheet 2020–3024, 4 p., https://doi.org/10.3133/fs20203024.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-115689 ","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":374013,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3024/coverthb.jpg"},{"id":374014,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3024/fs20203024.pdf","text":"Report","size":"16.1  MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–3024"}],"contact":"<p>Customer Service, <a data-mce-href=\"https://www.usgs.gov/centers/eros\" href=\"https://www.usgs.gov/centers/eros\">Earth Resources Observation and Science Center (EROS)</a><br>U.S. Geological Survey<br>47914 252d Street <br>Sioux Falls, SD 57198<br></p><p><a data-mce-href=\"https://www.usgs.gov/land-resources/eros/lcmap\" href=\"https://www.usgs.gov/land-resources/eros/lcmap\">https://www.usgs.gov/land-resources/eros/lcmap</a></p>","tableOfContents":"<ul><li>Monitoring</li><li>Assessment</li><li>Projection</li><li>LCMAP Land Change Story Example—Tornadoes of the 2011 Super Outbreak</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-04-15","noUsgsAuthors":false,"publicationDate":"2020-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Rover, Jennifer 0000-0002-3437-4030 jrover@usgs.gov","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":192333,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"jrover@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":787134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":787135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Auch, Roger F. 0000-0002-5382-5044 auch@usgs.gov","orcid":"https://orcid.org/0000-0002-5382-5044","contributorId":667,"corporation":false,"usgs":true,"family":"Auch","given":"Roger","email":"auch@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":787136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sayler, Kristi L. 0000-0003-2514-242X 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0000-0001-9507-4456","orcid":"https://orcid.org/0000-0001-9507-4456","contributorId":210820,"corporation":false,"usgs":true,"family":"Tollerud","given":"Heather","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":787139,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Xian, George Z. 0000-0001-5674-2204 xian@usgs.gov","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":2263,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"xian@usgs.gov","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":787140,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70207122,"text":"tm1D8 - 2020 - Passive sampling of groundwater wells for determination of water chemistry","interactions":[],"lastModifiedDate":"2020-04-16T11:28:30.827687","indexId":"tm1D8","displayToPublicDate":"2020-04-15T15:05:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1-D8","chapter":"","displayTitle":"Passive Sampling of Groundwater Wells for Determination of Water Chemistry","title":"Passive sampling of groundwater wells for determination of water chemistry","docAbstract":"<h1>Introduction</h1><p>Passive groundwater sampling is defined as the collection of a water sample from a well without the use of purging by a pump or retrieval by a bailer (Interstate Technology and Regulatory Council [ITRC], 2006; American Society for Testing and Materials [ASTM], 2014). No purging means that advection of water is not involved in collecting the water sample from the well. Passive samplers rely on diffusion as the primary process that drives their collection of chemical constituents. Diffusion is the transport of chemicals caused by the presence of a chemical gradient. Chemicals tend to move or diffuse from areas of higher concentration to areas of lower concentration to reach an average or equilibrium concentration. Passive sampling of groundwater relies on the ambient exchange of groundwater in the formation with water in the screened or open interval of a well. In this report, the term formation is used to describe all saturated hydrogeologic units that yield water to a well. If the well opening is unclogged and free of a film of deposits from physical turbidity or chemical precipitation, then the exchange of groundwater is likely adequate, and the water in the open interval will be representative of water in the formation. In some cases, the passive sample from the well opening can be more representative of groundwater from the formation than a sample collected by pumping if pumping induces mixing of water in the open interval with stagnant casing water that has undergone chemical alteration (Harte and others, 2018). In most cases, passive sampling will better represent the ambient groundwater chemistry flowing through the open interval of a well because pumping may capture water of different chemistry from downgradient or lateral areas that would not normally pass through the well. Three basic types of passive samplers are discussed in this report. The first type of passive sampler is the equilibrium-membrane type, which includes a semi-permeable membrane through which chemicals diffuse or permeate. Permeation is simply the process of water or chemicals moving through openings in the membrane. The authors contend that permeation is dominated by diffusion for many of the passive samplers discussed in this report. Some passive equilibrium-membrane-type samplers allow most types of chemical constituents through, whereas others allow the diffusion of only selected groups of chemicals. Once the chemical constituents are inside the membrane, they are retained by the equilibration of concentrations inside the sampler with those outside the sampler. The second type of passive sampler is an equilibrium-thief type, which has no semi-permeable membrane. Chemical constituents simply move through the openings in the body of the sampler either initially through advection and dispersion or over time primarily by diffusion. Chemical constituents reach equilibrium between the water in the sampler and the water in the well and are captured in the sampler when the sampler is closed. The third type of passive sampler is an accumulation-type sampler that contains sorptive media. Selected chemical constituents are sorbed onto the media that the sampler contains for later extraction and analysis. Although passive samplers have been available for more than 15 years (from present [2020]), their use by U.S. Geological Survey (USGS) hydrologists and hydrologic technicians to monitor groundwater quality largely has been limited to selected research studies. The authors believe that this may be the result of (1) a lack of exposure of most USGS personnel to passive samplers and the uses of these samplers and (2) the lack of a USGS-approved protocol for the proper use of these samplers by USGS personnel. This report is an effort to fill those two needs. The focus of this report is on hydraulic, hydrologic, and chemical considerations in the application of passive samplers and interpretation of groundwater chemistry results obtained using passive samplers in wells. This report describes the differences between purging and passive sampling methods in groundwater and explains how and why passive samplers work. The report points out the advantages and limitations of passive samplers in general and for each particular type of passive sampler. Important considerations to be taken into account prior to the use of passive samplers are discussed, such as defining the data-quality objectives, the water-quality constituents to be sampled, sample volumes required for analysis, well construction of the sampling network, and the geologic formations that will be sampled. Potential applications of passive samplers also are discussed, such as chemical-vertical profiling of wells. A general field protocol for the deployment, recovery, and sample collection using these devices is described, and some overall guidance for the practitioner with application examples is given. Comparison methods used to evaluate results from passive sampling versus purge sampling also are discussed.</p>","largerWorkTitle":"","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm1D8","collaboration":"","usgsCitation":"Imbrigiotta, T.E., and Harte, P.T., 2020, Passive sampling of groundwater wells for determination of water chemistry: U.S. Geological Survey Techniques and Methods, chap. 8, section D, book 1, 80 p., https://doi.org/10.3133/tm1d8.\n","productDescription":"ix, 80 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-082895","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":373983,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/01/d8/coverthb.jpg"},{"id":373984,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/01/d8/tm1d8.pdf","text":"Report","size":"4.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 1-D8"}],"publicComments":"This report is Chapter 8 of Section D: Water quality in Book 1: <em>Collection of water data by direct measurement</em>","contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p><p><a href=\"mailto:dc_nj@usgs.gov\" data-mce-href=\"mailto:dc_nj@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/nj-water\" data-mce-href=\"https://www.usgs.gov/centers/nj-water\">New Jersey Water Science Center</a><br>U.S. Geological Survey<br>3450 Princeton Pike, Suite 110<br>Lawrenceville, NJ 08648</p>","tableOfContents":"<ul><li>1.0 Introduction</li><li>2.0 Overview of Groundwater Sampling</li><li>3.0 Theory and Principles of Passive Sampling</li><li>4.0 Types of Passive Samplers</li><li>5.0 Considerations Prior to Use of Passive Diffusion Samplers</li><li>6.0 Decision Tools</li><li>7.0 Sampler Deployment, Retrieval, and Sample Collection</li><li>8.0 Data Reporting Procedures</li><li>9.0 Quality Assurance/Quality Control</li><li>10.0 Data Evaluation</li><li>Acknowledgments</li><li>11.0 References Cited</li><li>Appendix A. Case Studies</li><li>Appendix B. Field Form for Deployment and Retrieval of Passive Samplers</li><li>Appendix C. Well Label for Deployed Passive Samplers</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2020-04-15","noUsgsAuthors":false,"publicationDate":"2020-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Imbrigiotta, Thomas E. 0000-0003-1716-4768","orcid":"https://orcid.org/0000-0003-1716-4768","contributorId":221070,"corporation":false,"usgs":true,"family":"Imbrigiotta","given":"Thomas E.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":776903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harte, Philip T. 0000-0002-7718-1204","orcid":"https://orcid.org/0000-0002-7718-1204","contributorId":221071,"corporation":false,"usgs":true,"family":"Harte","given":"Philip T.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":776904,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70221836,"text":"70221836 - 2020 - Nutrient status of San Francisco Bay and its management implications","interactions":[],"lastModifiedDate":"2021-07-09T19:20:44.328704","indexId":"70221836","displayToPublicDate":"2020-04-15T14:14:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Nutrient status of San Francisco Bay and its management implications","docAbstract":"<p><span>Nutrient enrichment has degraded many of the world’s estuaries by amplifying algal production, leading to hypoxia/anoxia, loss of vascular plants and fish/shellfish habitat, and expansion of harmful blooms (HABs). Policies to protect coastal waters from the effects of nutrient enrichment require information to determine if a water body is impaired by nutrients and if regulatory actions are required. We compiled information to inform these decisions for San Francisco Bay (SFB), an urban estuary where the best path toward nutrient management is not yet clear. Our results show that SFB has high nutrient loadings, primarily from municipal wastewater; there is potential for high algal production, but that production is not fully realized; and SFB is not impaired by hypoxia or recurrent HABs. However, our assessment includes reasons for concern: nitrogen and phosphorus concentrations higher than those in other estuaries impaired by nutrient pollution, chronic presences of multiple algal toxins, a recent increase of primary production, and projected future hydroclimatic conditions that could increase the magnitude and frequency of algal blooms. Policymakers thus face the challenge of determining the appropriate protective policy for SFB. We identify three crucial next steps for meeting this challenge: (1) new research to determine if algal toxins can be reduced through nutrient management, (2) establish management goals as numeric targets, and (3) determine the magnitude of nutrient load reduction required to meet those targets. Our case study illustrates how scientific information can be acquired and communicated to inform policymakers about the status of nutrient pollution, its risks, and strategies for minimizing those risks.</span></p>","language":"English","publisher":"SpringerLink","doi":"10.1007/s12237-020-00737-w","usgsCitation":"Cloern, J.E., Schraga, T., Nejad, E., and Martin, C.A., 2020, Nutrient status of San Francisco Bay and its management implications: Estuaries and Coasts, v. 43, p. 1299-1317, https://doi.org/10.1007/s12237-020-00737-w.","productDescription":"19 p.","startPage":"1299","endPage":"1317","ipdsId":"IP-109047","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":457064,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-020-00737-w","text":"Publisher Index 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