{"pageNumber":"165","pageRowStart":"4100","pageSize":"25","recordCount":46660,"records":[{"id":70228908,"text":"sir20225016 - 2022 - Linear regression model documentation for computing water-quality constituent concentrations using continuous real-time water-quality data for the Republican River, Clay Center, Kansas, July 2018 through March 2021","interactions":[],"lastModifiedDate":"2026-04-09T16:18:48.528935","indexId":"sir20225016","displayToPublicDate":"2022-02-24T06:52:45","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5016","displayTitle":"Linear Regression Model Documentation for Computing Water-Quality Constituent Concentrations using Continuous Real-Time Water-Quality Data for the Republican River, Clay Center, Kansas, July 2018 through March 2021","title":"Linear regression model documentation for computing water-quality constituent concentrations using continuous real-time water-quality data for the Republican River, Clay Center, Kansas, July 2018 through March 2021","docAbstract":"

The Republican River is the primary inflow to Milford Lake and drains areas of Kansas, Nebraska, and Colorado. Milford Lake has been listed as impaired and designated hypereutrophic by the Kansas Department of Health and Environment because of excessive nutrient loading. Milford Lake had confirmed harmful algal blooms every summer from 2011 through 2017 and in 2020 and 2021.

In the lower Republican River drainage basin, the Regional Conservation Partnership Program, administered by the Natural Resources Conservation Service, provides reimbursement to agricultural producers that implement best management practices intended to decrease sediment and nutrient runoff and loading into Milford Lake. Sediment and nutrient loads could potentially be driving factors in the development of harmful algal blooms in the reservoir.

Since July 2018, the U.S. Geological Survey, in cooperation with the Kansas Water Office, has collected continuous and discrete water-quality data at the Republican River at Clay Center, Kansas, streamgage (U.S. Geological Survey station 06856600), which is about 15 river miles upstream from Milford Lake. This report documents site-specific regression models for the computation of continuous concentrations of suspended sediment, total nitrogen, total phosphorus, and total carbon developed using continuous and discrete data collected from July 24, 2018, the date of continuous water-quality monitor installation, through March 31, 2021. The objective of this study is to characterize sediment and nutrient transport in the Milford Lake drainage basin before, during, and after best management practice implementation using the models described in this report.

The explanatory variable turbidity explained a high amount (72–96 percent) of the variance in suspended-sediment, total nitrogen, total phosphorus, and total carbon concentrations. Statistical plots for the four selected models showed the desired normality and homoscedasticity in residuals, and model standard error ratios indicated that recomputing each selected model after removing a randomly selected 10 percent of the data did not substantially change model coefficients.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225016","collaboration":"Prepared in cooperation with the Kansas Water Office","usgsCitation":"Leiker, B.M., 2022, Linear regression model documentation for computing water-quality constituent concentrations using continuous real-time water-quality data for the Republican River, Clay Center, Kansas, July 2018 through March 2021: U.S. Geological Survey Scientific Investigations Report 2022–5016, 13 p., https://doi.org/10.3133/sir20225016.","productDescription":"Report: vi, 13 p.; 4 Appendixes; Dataset","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-133566","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":396373,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5016/sir20225016_appendix1.pdf","text":"Appendix 1","size":"846 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5016 Appendix 1","linkHelpText":"—Model Archive Summary for Suspended Sediment at U.S. Geological Survey Station 06856600, Republican River at Clay Center, Kansas, during July 2018 through March 2021"},{"id":396372,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5016/sir20225016.pdf","text":"Report","size":"3.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5016"},{"id":396371,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5016/coverthb.jpg"},{"id":396377,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5016/images"},{"id":396374,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5016/sir20225016_appendix2.pdf","text":"Appendix 2","size":"788 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5016 Appendix 2","linkHelpText":"—Model Archive Summary for Total Nitrogen at U.S. Geological Survey Station 06856600, Republican River at Clay Center, Kansas, during July 2018 through March 2021"},{"id":396375,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5016/sir20225016_appendix3.pdf","text":"Appendix 3","size":"681 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5016 Appendix 3","linkHelpText":"—Model Archive Summary for Total Phosphorus at U.S. Geological Survey Station 06856600, Republican River at Clay Center, Kansas, during July 2018 through March 2021"},{"id":396376,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5016/sir20225016_appendix4.pdf","text":"Appendix 4","size":"757 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5016 Appendix 4","linkHelpText":"—Model Archive Summary for Total Carbon at U.S. Geological Survey Station 06856600, Republican River at Clay Center, Kansas, during July 2018 through March 2021"},{"id":396378,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5016/sir20225016.XML","linkFileType":{"id":8,"text":"xml"}},{"id":396379,"rank":9,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"—USGS water data for the Nation"},{"id":502367,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112525.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Kansas","city":"Clay Center","otherGeospatial":"Republican River drainage basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.8170166015625,\n 39.03838632847035\n ],\n [\n -96.767578125,\n 39.172658670429946\n ],\n [\n -96.866455078125,\n 39.35129035526705\n ],\n [\n -97.01202392578125,\n 39.5146359327835\n ],\n [\n -97.0147705078125,\n 39.65857056750545\n ],\n [\n -96.99829101562499,\n 39.76632525654491\n ],\n [\n -97.14385986328125,\n 39.87601941962116\n ],\n [\n -97.4102783203125,\n 39.8992015115692\n ],\n [\n -97.74810791015625,\n 39.905522539728544\n ],\n [\n -97.92938232421875,\n 39.90762941952987\n ],\n [\n -98.22601318359375,\n 39.78954439311165\n ],\n [\n -98.228759765625,\n 39.65222681530652\n ],\n [\n -97.83050537109375,\n 39.50615988027491\n ],\n [\n -97.51190185546874,\n 39.42346418978382\n ],\n [\n -97.2344970703125,\n 39.3130504637139\n ],\n [\n -96.98181152343749,\n 39.034119526392836\n ],\n [\n -96.84997558593749,\n 39.00211029922515\n ],\n [\n -96.8170166015625,\n 39.03838632847035\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-02-24","noUsgsAuthors":false,"publicationDate":"2022-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Leiker, Brianna M. 0000-0002-9896-681X bleiker@usgs.gov","orcid":"https://orcid.org/0000-0002-9896-681X","contributorId":250677,"corporation":false,"usgs":true,"family":"Leiker","given":"Brianna","email":"bleiker@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":835859,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70249535,"text":"70249535 - 2022 - Gas hydrate saturation estimates, gas hydrate occurrence, and reservoir characteristics based on well log data from the hydrate-01 stratigraphic test well, Alaska North Slope","interactions":[],"lastModifiedDate":"2023-10-13T11:55:23.88273","indexId":"70249535","displayToPublicDate":"2022-02-24T06:50:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12564,"text":"Journal of Energy and Fuels","active":true,"publicationSubtype":{"id":10}},"title":"Gas hydrate saturation estimates, gas hydrate occurrence, and reservoir characteristics based on well log data from the hydrate-01 stratigraphic test well, Alaska North Slope","docAbstract":"

The Hydrate-01 Stratigraphic Test Well was drilled at the Kuparuk 7-11-12 site on the Alaska North Slope in December 2018. Sonic log data provide compressional (P) and shear (S) slowness from which we determine gas hydrate saturation (Sgh) estimates using effective medium theory. The sonic Sgh estimates compare favorably with Sgh estimated from resistivity and nuclear magnetic resonance (NMR) logs, showing that gas hydrate occupies up to approximately 90% of the pore space in the target reservoir sands. The informally named B1 sand (2294 feet below mean sea level) shows lower VP/VS ratios than the D1 sand (2770 feet below mean sea level), with the lower part of the B1 sand showing lower VP/VS ratios than the upper part of the B1 sand. This corresponds to a stiffer, or more “cemented”, behavior for the lower B1 sand and less cemented behavior for the D1 sand. This trend could be due to differences in the reservoirs themselves or in the gas hydrate morphology or to both factors. We observe that the presence of gas hydrate in the upper B1 sand has greater impact on hydraulic permeability (measurements suggest a greater difference between intrinsic and effective permeability) than in the D1 sand, possibly related to gas hydrate morphology but more likely due simply to higher gas hydrate saturations in the upper B1 sand. Analyses of Sgh relative to porosity, shale fraction, and intrinsic permeability show that reservoir quality (as represented by these three metrics) exerts control on gas hydrate saturation. Grain size and mineralogy data show somewhat smaller grains and better sorting in the D1 reservoir relative to the upper B1 reservoir and smaller grains and greater clay fraction in the lower B1 reservoir relative to the other two reservoir zones. Together, these data suggest that reservoir characteristics play a role in the observed VP/VS patterns, but gas hydrate morphology (possibly varying with saturation) must also be considered.

","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.energyfuels.1c04100","usgsCitation":"Haines, S.S., Collett, T., Yoneda, J., Shimoda, N., Boswell, R., and Okinaka, N., 2022, Gas hydrate saturation estimates, gas hydrate occurrence, and reservoir characteristics based on well log data from the hydrate-01 stratigraphic test well, Alaska North Slope: Journal of Energy and Fuels, v. 36, no. 6, p. 3040-3050, https://doi.org/10.1021/acs.energyfuels.1c04100.","productDescription":"11 p.","startPage":"3040","endPage":"3050","ipdsId":"IP-134723","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":488384,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1846339","text":"Publisher Index Page"},{"id":421901,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"North Slope","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -166.25520216218266,\n 68.80086293372801\n ],\n [\n -140.23957716218266,\n 68.80086293372801\n ],\n [\n -140.23957716218266,\n 71.87061572563644\n ],\n [\n -166.25520216218266,\n 71.87061572563644\n ],\n [\n -166.25520216218266,\n 68.80086293372801\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"36","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Haines, Seth S. 0000-0003-2611-8165 shaines@usgs.gov","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":1344,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","email":"shaines@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy 0000-0002-7598-4708","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":220806,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":886101,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yoneda, Jun","contributorId":330871,"corporation":false,"usgs":false,"family":"Yoneda","given":"Jun","affiliations":[{"id":79061,"text":"AIST Japan","active":true,"usgs":false}],"preferred":false,"id":886102,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shimoda, Naoyuki","contributorId":330872,"corporation":false,"usgs":false,"family":"Shimoda","given":"Naoyuki","affiliations":[{"id":39359,"text":"JOGMEC","active":true,"usgs":false}],"preferred":false,"id":886103,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boswell, Ray","contributorId":330873,"corporation":false,"usgs":false,"family":"Boswell","given":"Ray","affiliations":[{"id":78878,"text":"DOE NETL","active":true,"usgs":false}],"preferred":false,"id":886104,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Okinaka, Norihiro","contributorId":330874,"corporation":false,"usgs":false,"family":"Okinaka","given":"Norihiro","affiliations":[{"id":39359,"text":"JOGMEC","active":true,"usgs":false}],"preferred":false,"id":886105,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229679,"text":"70229679 - 2022 - Toward scoping reviews of individual bird species","interactions":[],"lastModifiedDate":"2022-06-16T15:20:19.012263","indexId":"70229679","displayToPublicDate":"2022-02-24T06:11:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"title":"Toward scoping reviews of individual bird species","docAbstract":"

Scoping reviews, in which the literature on a given topic is systematically collated and summarized, aid literature searches and highlight knowledge gaps on a given topic, thus hastening scientific progress and informing conservation efforts. Because much research and conservation is targeted at the species level, ornithology and bird conservation would benefit from scoping reviews of individual species. We present and apply a framework for scoping reviews for three disparate raptor species: California Condor Gymnogyps californianus, Harpy Eagle Harpia harpyja and Gyrfalcon Falco rusticolus. We consulted expert panels to develop appropriate search strings and lists of essential literature, i.e. ‘benchmark articles’. We searched Web of Science, Scopus and Google Scholar. Searches for California Condor, Harpy Eagle and Gyrfalcon returned 268, 138 and 343 articles, respectively, that discuss, review or collect empirical data for the focal species. Our searches returned all benchmark articles identified by species experts, indicating that the searches captured the most important work on each species. We coded each study according to the topic addressed, country and month in which data were collected. We also coded threats, stresses and conservation actions addressed by studies, following definitions used by the International Union for the Conservation of Nature (IUCN) during Red List assessments. Literature summaries for each species include the number of studies addressing certain topics, monthly timing of research and global maps of research focus. Our coding scheme revealed important knowledge gaps for each species. Effects of conservation actions on wild individuals were less studied for California Condors. Harpy Eagles were less studied outside of Brazil and Panama, and Gyrfalcons were less studied outside of their breeding season. Scoping reviews of the world's bird species would help to identify critical knowledge gaps, thereby aiding the global effort to assuage the sixth mass extinction.

","language":"English","publisher":"Wiley","doi":"10.1111/ibi.13051","usgsCitation":"McClure, C.J., Szymczycha, Z., Anderson, D.L., Aguiar-Silva, F.H., Schulwitz, S., Dunn, L., Henderson, M.T., Camacho, L., de Jesus Vargas Gonzalez, J., Parish, C.N., Buechley, E., D’Elia, J., Wilbur, S., Johansen, K., Johnson, D.L., Moller, S., Pokrovsky, I., and Katzner, T., 2022, Toward scoping reviews of individual bird species: Ibis, v. 164, p. 835-845, https://doi.org/10.1111/ibi.13051.","productDescription":"11 p.","startPage":"835","endPage":"845","ipdsId":"IP-131159","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":448699,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ibi.13051","text":"Publisher Index Page"},{"id":397049,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"164","noUsgsAuthors":false,"publicationDate":"2022-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"McClure, Christopher J W","contributorId":257266,"corporation":false,"usgs":false,"family":"McClure","given":"Christopher","email":"","middleInitial":"J W","affiliations":[{"id":36583,"text":"The Peregrine Fund","active":true,"usgs":false}],"preferred":false,"id":837899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Szymczycha, Zackery","contributorId":288434,"corporation":false,"usgs":false,"family":"Szymczycha","given":"Zackery","email":"","affiliations":[{"id":61761,"text":"The Peregrine Fund, University of Idaho","active":true,"usgs":false}],"preferred":false,"id":837900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, David L","contributorId":288435,"corporation":false,"usgs":false,"family":"Anderson","given":"David","email":"","middleInitial":"L","affiliations":[{"id":36583,"text":"The Peregrine Fund","active":true,"usgs":false}],"preferred":false,"id":837901,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aguiar-Silva, Francisca Helena","contributorId":288436,"corporation":false,"usgs":false,"family":"Aguiar-Silva","given":"Francisca","email":"","middleInitial":"Helena","affiliations":[{"id":61762,"text":"Universidade de São Paulo, Instituto Nacional de Pesquisas da Amazônia","active":true,"usgs":false}],"preferred":false,"id":837902,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schulwitz, Sarah","contributorId":288437,"corporation":false,"usgs":false,"family":"Schulwitz","given":"Sarah","email":"","affiliations":[{"id":36583,"text":"The Peregrine Fund","active":true,"usgs":false}],"preferred":false,"id":837903,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dunn, Leah","contributorId":217944,"corporation":false,"usgs":false,"family":"Dunn","given":"Leah","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":837904,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Henderson, MIchael T","contributorId":288438,"corporation":false,"usgs":false,"family":"Henderson","given":"MIchael","email":"","middleInitial":"T","affiliations":[{"id":36583,"text":"The Peregrine Fund","active":true,"usgs":false}],"preferred":false,"id":837905,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Camacho, Leticia","contributorId":288439,"corporation":false,"usgs":false,"family":"Camacho","given":"Leticia","email":"","affiliations":[{"id":36583,"text":"The Peregrine Fund","active":true,"usgs":false}],"preferred":false,"id":837906,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"de Jesus Vargas Gonzalez, Jose","contributorId":288440,"corporation":false,"usgs":false,"family":"de Jesus Vargas Gonzalez","given":"Jose","email":"","affiliations":[{"id":36583,"text":"The Peregrine Fund","active":true,"usgs":false}],"preferred":false,"id":837907,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Parish, Chris N.","contributorId":206082,"corporation":false,"usgs":false,"family":"Parish","given":"Chris","email":"","middleInitial":"N.","affiliations":[{"id":37235,"text":"The Peregrin Fund","active":true,"usgs":false}],"preferred":false,"id":837908,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Buechley, Evan R.","contributorId":245086,"corporation":false,"usgs":false,"family":"Buechley","given":"Evan R.","affiliations":[],"preferred":false,"id":837909,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"D’Elia, Jesse 0000-0002-1843-8495","orcid":"https://orcid.org/0000-0002-1843-8495","contributorId":244237,"corporation":false,"usgs":false,"family":"D’Elia","given":"Jesse","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":837910,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wilbur, Sanford","contributorId":288441,"corporation":false,"usgs":false,"family":"Wilbur","given":"Sanford","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":837911,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Johansen, Kenneth","contributorId":288442,"corporation":false,"usgs":false,"family":"Johansen","given":"Kenneth","email":"","affiliations":[{"id":61765,"text":"Raptor Group Finnmark","active":true,"usgs":false}],"preferred":false,"id":837912,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Johnson, Devin L","contributorId":288443,"corporation":false,"usgs":false,"family":"Johnson","given":"Devin","email":"","middleInitial":"L","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":837913,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Moller, Soren","contributorId":288444,"corporation":false,"usgs":false,"family":"Moller","given":"Soren","email":"","affiliations":[{"id":61766,"text":"Roskilde University","active":true,"usgs":false}],"preferred":false,"id":837914,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Pokrovsky, Ivan","contributorId":243491,"corporation":false,"usgs":false,"family":"Pokrovsky","given":"Ivan","email":"","affiliations":[],"preferred":false,"id":837915,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":837916,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70228891,"text":"70228891 - 2022 - INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States","interactions":[],"lastModifiedDate":"2022-02-23T14:30:43.942294","indexId":"70228891","displayToPublicDate":"2022-02-23T08:21:34","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7774,"text":"PLoSOne","active":true,"publicationSubtype":{"id":10}},"title":"INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States","docAbstract":"Narrowing the communication and knowledge gap between producers and users of scientific data is a longstanding problem in ecological conservation and land management. Decision support tools (DSTs), including websites or interactive web applications, provide platforms that can help bridge this gap. DSTs can most effectively disseminate and translate research results when producers and users collaboratively and iteratively design content and features. One data resource seldom incorporated into DSTs are species distribution models (SDMs), which can produce spatial predictions of habitat suitability. Outputs from SDMs can inform management decisions, but their complexity and inaccessibility can limit their use by resource managers or policy makers. To overcome these limitations, we present the Invasive Species Habitat Tool (INHABIT), a novel, web-based DST built with R Shiny to display spatial predictions and tabular summaries of habitat suitability from SDMs for invasive plants across the contiguous United States. INHABIT provides actionable science to support the prevention and management of invasive species. Two case studies demonstrate the important role of end user feedback in confirming INHABIT’s credibility, utility, and relevance.","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0263056","usgsCitation":"Engelstad, P., Jarnevich, C.S., Hogan, T., Sofaer, H., Pearse, I., Sieracki, J., Frakes, N., Sullivan, J., Young, N.E., Prevey, J.S., Belamaric, P.N., and Laroe, J.M., 2022, INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States: PLoSOne, v. 17, no. 2, p. 1-15, https://doi.org/10.1371/journal.pone.0263056.","productDescription":"e0263056, 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-127738","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":448709,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0263056","text":"Publisher Index 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Terri","contributorId":240929,"corporation":false,"usgs":false,"family":"Hogan","given":"Terri","email":"","affiliations":[{"id":48162,"text":"National Park Service, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":835792,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sofaer, Helen 0000-0002-9450-5223","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":216681,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835793,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":211154,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835794,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sieracki, Jennifer","contributorId":236914,"corporation":false,"usgs":false,"family":"Sieracki","given":"Jennifer","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":true,"id":835795,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Frakes, Neil","contributorId":177303,"corporation":false,"usgs":false,"family":"Frakes","given":"Neil","email":"","affiliations":[],"preferred":false,"id":835796,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sullivan, Julia","contributorId":238757,"corporation":false,"usgs":false,"family":"Sullivan","given":"Julia","email":"","affiliations":[{"id":47756,"text":"Student contractor to the U.S. Geological Survey Fort Collins Science Center","active":true,"usgs":false}],"preferred":false,"id":835797,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Young, Nicholas E.","contributorId":189060,"corporation":false,"usgs":false,"family":"Young","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":835798,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Prevey, Janet S. 0000-0003-2879-6453","orcid":"https://orcid.org/0000-0003-2879-6453","contributorId":222702,"corporation":false,"usgs":true,"family":"Prevey","given":"Janet","email":"","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835799,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Belamaric, Pairsa Nicole 0000-0001-7529-0370","orcid":"https://orcid.org/0000-0001-7529-0370","contributorId":267846,"corporation":false,"usgs":true,"family":"Belamaric","given":"Pairsa","email":"","middleInitial":"Nicole","affiliations":[{"id":47756,"text":"Student contractor to the U.S. Geological Survey Fort Collins Science Center","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835800,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Laroe, Jillian Marie 0000-0002-1429-9811","orcid":"https://orcid.org/0000-0002-1429-9811","contributorId":279978,"corporation":false,"usgs":true,"family":"Laroe","given":"Jillian","email":"","middleInitial":"Marie","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835801,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70230068,"text":"70230068 - 2022 - Volcano geodesy using InSAR in 2020: The past and next decades","interactions":[],"lastModifiedDate":"2022-03-28T13:27:51.732662","indexId":"70230068","displayToPublicDate":"2022-02-22T08:25:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Volcano geodesy using InSAR in 2020: The past and next decades","docAbstract":"

The study of volcano deformation has grown significantly through they year 2020 since the development of interferometric synthetic aperture radar (InSAR) in the 1990s. This relatively new data source, which provides evidence of changes in subsurface magma storage and pressure without the need for ground-based equipment, has matured during the past decade. It now provides a means to address previously inaccessible questions and offers input to increasingly complex models of magmatic processes. Here, we review how technological advances in InSAR during 2010-2020 have facilitated our ability to monitor and interpret volcanic processes, primarily through rapid and accurate observations of the changing surfaces at active volcanoes worldwide. Specifically, we examine how current systems achieve excellent resolution in time and space, provide global coverage, and generate products that are easy to use by non-specialists—factors that have often limited the practical study of volcanoes using radar measurements. We also look to the future, offering our perspective about how advancements in technology and data management in the decade to come will increase the value and accessibility of InSAR applied to the geodetic study of volcanoes and monitoring of hazardous volcanic processes. New developments will include the launch of additional satellites by both public space agencies and private companies, as well as implementation of algorithms for exploiting the growing volumes of data. To meet their full potential, these efforts will require coordination between data users and data providers so that the relevant imagery is acquired, made available to volcanologists in a timely fashion, and utilized to assess and mitigate volcanic hazards.

","language":"English","publisher":"Springer","doi":"10.1007/s00445-022-01531-1","usgsCitation":"Poland, M., and Zebker, H., 2022, Volcano geodesy using InSAR in 2020: The past and next decades: Bulletin of Volcanology, v. 84, no. 3, 27, 8 p., https://doi.org/10.1007/s00445-022-01531-1.","productDescription":"27, 8 p.","ipdsId":"IP-133322","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":397694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"84","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Poland, Michael 0000-0001-5240-6123","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":49920,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":838942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zebker, Howard 0000-0001-9931-5237","orcid":"https://orcid.org/0000-0001-9931-5237","contributorId":289333,"corporation":false,"usgs":false,"family":"Zebker","given":"Howard","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":838943,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70251316,"text":"70251316 - 2022 - Permeability measurement and prediction with nuclear magnetic resonance analysis of gas hydrate-bearing sediments recovered from Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well","interactions":[],"lastModifiedDate":"2024-02-03T14:13:07.268011","indexId":"70251316","displayToPublicDate":"2022-02-22T08:06:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17149,"text":"Energy and Fuels Journal","active":true,"publicationSubtype":{"id":10}},"title":"Permeability measurement and prediction with nuclear magnetic resonance analysis of gas hydrate-bearing sediments recovered from Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well","docAbstract":"

Permeability of porous media, such as oil and gas reservoirs, is the crucial material parameter for predicting their hydraulic behavior. A nuclear magnetic resonance (NMR) analyzer is widely used as a powerful tool to predict permeability of various media. NMR T2 (transverse or spin–spin) relaxation time distribution, which is related to pore size distribution, gives the information to allow calculation of effective (initial) permeability. In this study, we investigate effective, intrinsic (absolute), and relative water and gas permeabilities of hydrate-bearing pressure core samples. These samples were recovered from the Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well by sidewall pressure coring and then analyzed in a laboratory using both fluid flow test and NMR analyzer. The peak of the NMR T2 distribution was measured at 10–20 ms using a laboratory NMR analyzer, which compares well with in situ measurements obtained via logging while drilling NMR data for two samples with high gas hydrate saturations (Sh = 76% and 74%). Further, comparison of laboratory NMR T2 distribution after hydrate dissociation revealed that the hydrate existed in large pore spaces. Effective permeabilities predicted by the Timur-Coates (TC) model and the Schlumberger-Doll-Research (SDR) model, with T2 cutoff 33 ms, were about an order of magnitude less than the laboratory measured values. Alternative TC model-based calculations with the T2 cutoff reduced to 10 ms and a newly developed hydraulic radius model better matched the laboratory data. For the analysis of the intrinsic permeabilities, the TC model with a T2 cutoff of 33 ms and SDR model were greater than the laboratory derived values, while the hydraulic radius model more closely matched the laboratory-derived values. In addition, permeability measurements were also made relative to gas and water under constant three-phase flow (water–gas–hydrate) conditions. After hydrate dissociation, a relative permeability curve was developed for each of the analyzed core samples based on the Corey petrophysical model. The results indicate that the gas permeability changed rapidly at high water saturation around 90%. Thus, we infer that the selection of relative reservoir parameters should focus on the higher water saturation conditions.

","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.energyfuels.1c03810","usgsCitation":"Yoneda, J., Suzuki, K., Jin, Y., Ohtsuki, S., Collett, T.S., Boswell, R., Maehara, Y., and Okinaka, N., 2022, Permeability measurement and prediction with nuclear magnetic resonance analysis of gas hydrate-bearing sediments recovered from Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well: Energy and Fuels Journal, v. 36, no. 5, p. 2515-2529, https://doi.org/10.1021/acs.energyfuels.1c03810.","productDescription":"15 p.","startPage":"2515","endPage":"2529","ipdsId":"IP-135014","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":425357,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well","volume":"36","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Yoneda, Jun","contributorId":240073,"corporation":false,"usgs":false,"family":"Yoneda","given":"Jun","affiliations":[{"id":40273,"text":"National Institute of Advanced Industrial Science and Technology","active":true,"usgs":false}],"preferred":false,"id":894033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Suzuki, Kiyofumi","contributorId":240086,"corporation":false,"usgs":false,"family":"Suzuki","given":"Kiyofumi","affiliations":[{"id":39359,"text":"JOGMEC","active":true,"usgs":false}],"preferred":false,"id":894034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jin, Yusuke","contributorId":240045,"corporation":false,"usgs":false,"family":"Jin","given":"Yusuke","affiliations":[{"id":40273,"text":"National Institute of Advanced Industrial Science and Technology","active":true,"usgs":false}],"preferred":false,"id":894035,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ohtsuki, Satoshi","contributorId":150141,"corporation":false,"usgs":false,"family":"Ohtsuki","given":"Satoshi","email":"","affiliations":[{"id":17917,"text":"Japan Oil, Gas and Metals National Corporation","active":true,"usgs":false}],"preferred":false,"id":894036,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":894037,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boswell, Ray","contributorId":242633,"corporation":false,"usgs":false,"family":"Boswell","given":"Ray","affiliations":[{"id":34152,"text":"US Department of Energy","active":true,"usgs":false}],"preferred":false,"id":894038,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maehara, Yuki","contributorId":333830,"corporation":false,"usgs":false,"family":"Maehara","given":"Yuki","email":"","affiliations":[],"preferred":false,"id":894039,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Okinaka, Norihiro","contributorId":330874,"corporation":false,"usgs":false,"family":"Okinaka","given":"Norihiro","affiliations":[{"id":39359,"text":"JOGMEC","active":true,"usgs":false}],"preferred":false,"id":894040,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70230143,"text":"70230143 - 2022 - Validating predicted site response in sedimentary basins from 3D ground motion simulations","interactions":[],"lastModifiedDate":"2022-08-01T16:56:49.645761","indexId":"70230143","displayToPublicDate":"2022-02-22T07:17:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Validating predicted site response in sedimentary basins from 3D ground motion simulations","docAbstract":"

We introduce procedures to validate site response in sedimentary basins as predicted using ground motion simulations. These procedures aim to isolate contributions of site response to computed intensity measures relative to those from seismic source and path effects. In one of the validation procedures, simulated motions are analyzed in the same manner as earthquake recordings to derive non-ergodic site terms. This procedure compares the scaling with sediment isosurface depth of simulated versus empirical site terms (the latter having been derived in a separate study). A second validation procedure utilizes two sets of simulations, one that considers three-dimensional (3D) basin structure and a second that utilizes a one-dimensional (1D) representation of the crustal structure. Identical sources are used in both procedures, and after correcting for variable path effects, differences in ground motions are used to estimate site amplification in 3D basins. Such site responses are compared to those derived empirically to validate both the absolute levels and the depth scaling of site response from 3D simulations. We apply both procedures to southern California in a manner that is consistent between the simulated and empirical data (i.e. by using similar event locations and magnitudes). The results show that the 3D simulations overpredict the depth-scaling and absolute levels of site amplification in basins. However, overall patterns of site amplification with depth are similar, suggesting that future calibration may be able to remove observed biases.

","language":"English","publisher":"Sage Publications","doi":"10.1177/87552930211073159","usgsCitation":"Nweke, C.C., Stewart, J.P., Graves, R., Goulet, C.A., and Brandenberg, S.J., 2022, Validating predicted site response in sedimentary basins from 3D ground motion simulations: Earthquake Spectra, v. 38, no. 3, p. 2135-2161, https://doi.org/10.1177/87552930211073159.","productDescription":"27 p.","startPage":"2135","endPage":"2161","ipdsId":"IP-130609","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":397852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Nweke, Chukwuebuka C","contributorId":217352,"corporation":false,"usgs":false,"family":"Nweke","given":"Chukwuebuka","email":"","middleInitial":"C","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":839238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stewart, Jonathan P.","contributorId":100110,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":839239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":839240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":839241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brandenberg, Scott J","contributorId":217350,"corporation":false,"usgs":false,"family":"Brandenberg","given":"Scott","email":"","middleInitial":"J","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":839242,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70230435,"text":"70230435 - 2022 - Exploring genetic variation and population structure in a threatened species, Noturus placidus, with whole-genome sequence data","interactions":[],"lastModifiedDate":"2022-04-13T12:07:01.070311","indexId":"70230435","displayToPublicDate":"2022-02-22T07:00:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10550,"text":"G3: Genes, Genomes, Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Exploring genetic variation and population structure in a threatened species, Noturus placidus, with whole-genome sequence data","docAbstract":"

The Neosho madtom (Noturus placidus) is a small catfish, generally less than 3 inches in length, unique to the Neosho-Spring River system within the Arkansas River Basin. It was federally listed as threatened in 1990, largely due to habitat loss. For conservation efforts, we generated whole-genome sequence data from 10 Neosho madtom individuals originating from 3 geographically separated populations to evaluate genetic diversity and population structure. A Neosho madtom genome was de novo assembled, and genome size and content were assessed. Single nucleotide polymorphisms were assessed from de Bruijn graphs, and via reference alignment with both the channel catfish (Ictalurus punctatus) reference genome and Neosho madtom reference genome. Principal component analysis and structure analysis indicated weak population structure, suggesting fish from the 3 locations represent a single population. Using a novel method, genome-wide conservation and divergence between the Neosho madtom, channel catfish, and zebrafish (Danio rerio) was assessed by pairwise contig alignment, which demonstrated that genes important to embryonic development frequently had conserved sequences. This research in a threatened species with no previously published genomic resources provides novel genetic information to guide current and future conservation efforts and demonstrates that using whole-genome sequencing provides detailed information of population structure and demography using only a limited number of rare and valuable samples.

","language":"English","publisher":"Oxford Academic","doi":"10.1093/g3journal/jkac046","usgsCitation":"Whitacre, L.K., Wildhaber, M.L., Johnson, G., Durbin, H.J., Rowan, T.N., Peoria Tribe, Schnabel, R.D., Mhlanga-Mutangadura, T., Tabor, V.M., Fenner, D., and Decker, J.E., 2022, Exploring genetic variation and population structure in a threatened species, Noturus placidus, with whole-genome sequence data: G3: Genes, Genomes, Genetics, v. 12, no. 4, jkac046, 9 p., https://doi.org/10.1093/g3journal/jkac046.","productDescription":"jkac046, 9 p.","ipdsId":"IP-088642","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":448714,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/g3journal/jkac046","text":"Publisher Index Page"},{"id":435950,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MAPT9T","text":"USGS data release","linkHelpText":"Neosho Madtom (Noturus placidus) short read archive and whole genome sequence data"},{"id":398631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Kansas, Missouri, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.50390624999999,\n 36.35052700542763\n ],\n [\n -93.251953125,\n 36.35052700542763\n ],\n [\n -93.251953125,\n 37.99616267972814\n ],\n [\n -96.50390624999999,\n 37.99616267972814\n ],\n [\n -96.50390624999999,\n 36.35052700542763\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Whitacre, Lynsey K.","contributorId":290182,"corporation":false,"usgs":false,"family":"Whitacre","given":"Lynsey","email":"","middleInitial":"K.","affiliations":[{"id":62373,"text":"Informatics Institute, University of Missouri, Columbia, Missouri","active":true,"usgs":false}],"preferred":false,"id":840417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":840418,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Gary S.","contributorId":290183,"corporation":false,"usgs":false,"family":"Johnson","given":"Gary S.","affiliations":[{"id":62375,"text":"Department of Veterinary Pathobiology, College of Veterinary Medicine, University of Missouri, Columbia, Missouri","active":true,"usgs":false}],"preferred":false,"id":840419,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Durbin, Harly J.","contributorId":290215,"corporation":false,"usgs":false,"family":"Durbin","given":"Harly","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":840470,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rowan, Troy N.","contributorId":290216,"corporation":false,"usgs":false,"family":"Rowan","given":"Troy","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":840471,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peoria Tribe","contributorId":290217,"corporation":true,"usgs":false,"organization":"Peoria Tribe","id":840477,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schnabel, Robert D.","contributorId":290184,"corporation":false,"usgs":false,"family":"Schnabel","given":"Robert","email":"","middleInitial":"D.","affiliations":[{"id":62373,"text":"Informatics Institute, University of Missouri, Columbia, Missouri","active":true,"usgs":false}],"preferred":false,"id":840472,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mhlanga-Mutangadura, Tendai","contributorId":290186,"corporation":false,"usgs":false,"family":"Mhlanga-Mutangadura","given":"Tendai","email":"","affiliations":[{"id":62375,"text":"Department of Veterinary Pathobiology, College of Veterinary Medicine, University of Missouri, Columbia, Missouri","active":true,"usgs":false}],"preferred":false,"id":840473,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tabor, Vernon M.","contributorId":290187,"corporation":false,"usgs":false,"family":"Tabor","given":"Vernon","email":"","middleInitial":"M.","affiliations":[{"id":62378,"text":"U.S. Fish and Wildlife Service, Kansas Ecological Services Field Office, Manhattan, Kansas","active":true,"usgs":false}],"preferred":false,"id":840474,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fenner, Daniel","contributorId":290188,"corporation":false,"usgs":false,"family":"Fenner","given":"Daniel","email":"","affiliations":[{"id":62379,"text":"U.S. Fish and Wildlife Service, Oklahoma Ecological Services Field Office, Tulsa, Oklahoma","active":true,"usgs":false}],"preferred":false,"id":840475,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Decker, Jared E.","contributorId":290189,"corporation":false,"usgs":false,"family":"Decker","given":"Jared","email":"","middleInitial":"E.","affiliations":[{"id":62373,"text":"Informatics Institute, University of Missouri, Columbia, Missouri","active":true,"usgs":false}],"preferred":false,"id":840476,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70229676,"text":"70229676 - 2022 - Classifying behavior from short-interval biologging data: An example with GPS tracking of birds","interactions":[],"lastModifiedDate":"2022-03-14T11:43:03.554807","indexId":"70229676","displayToPublicDate":"2022-02-22T06:38:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Classifying behavior from short-interval biologging data: An example with GPS tracking of birds","docAbstract":"
  1. Recent advances in digital data collection have spurred accumulation of immense quantities of data that have potential to lead to remarkable ecological insight, but that also present analytic challenges. In the case of biologging data from birds, common analytical approaches to classifying movement behaviors are largely inappropriate for these massive data sets.
  2. We apply a framework for using K-means clustering to classify bird behavior using points from short time interval GPS tracks. K-means clustering is a well-known and computationally efficient statistical tool that has been used in animal movement studies primarily for clustering segments of consecutive points. To illustrate the utility of our approach, we apply K-means clustering to six focal variables derived from GPS data collected at 1–11 s intervals from free-flying bald eagles (Haliaeetus leucocephalus) throughout the state of Iowa, USA. We illustrate how these data can be used to identify behaviors and life-stage- and age-related variation in behavior.
  3. After filtering for data quality, the K-means algorithm identified four clusters in >2 million GPS telemetry data points. These four clusters corresponded to three movement states: ascending, flapping, and gliding flight; and one non-moving state: perching. Mapping these states illustrated how they corresponded tightly to expectations derived from natural history observations; for example, long periods of ascending flight were often followed by long gliding descents, birds alternated between flapping and gliding flight.
  4. The K-means clustering approach we applied is both an efficient and effective mechanism to classify and interpret short-interval biologging data to understand movement behaviors. Furthermore, because it can apply to an abundance of very short, irregular, and high-dimensional movement data, it provides insight into small-scale variation in behavior that would not be possible with many other analytical approaches.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8395","usgsCitation":"Bergen, S., Huso, M., Duerr, A., Braham, M.A., Katzner, T., Schmuecker, S., and Miller, T.A., 2022, Classifying behavior from short-interval biologging data: An example with GPS tracking of birds: Ecology and Evolution, v. 12, no. 2, e08395, 15 p., https://doi.org/10.1002/ece3.8395.","productDescription":"e08395, 15 p.","ipdsId":"IP-127197","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":448716,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.8395","text":"External Repository"},{"id":435952,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HZZZ26","text":"USGS data release","linkHelpText":"Data derived from GPS tracking of free-flying bald eagles (Haliaeetus leucocephalus), Iowa, USA"},{"id":397052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Bergen, Silas","contributorId":288432,"corporation":false,"usgs":false,"family":"Bergen","given":"Silas","email":"","affiliations":[{"id":61757,"text":"Winona State University","active":true,"usgs":false}],"preferred":false,"id":837890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huso, Manuela 0000-0003-4687-6625 mhuso@usgs.gov","orcid":"https://orcid.org/0000-0003-4687-6625","contributorId":223969,"corporation":false,"usgs":true,"family":"Huso","given":"Manuela","email":"mhuso@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":837891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duerr, A. 0000-0002-6145-8897","orcid":"https://orcid.org/0000-0002-6145-8897","contributorId":257045,"corporation":false,"usgs":false,"family":"Duerr","given":"A.","email":"","affiliations":[{"id":38830,"text":"Bloom Research Inc.","active":true,"usgs":false}],"preferred":false,"id":837892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braham, Missy A","contributorId":288433,"corporation":false,"usgs":false,"family":"Braham","given":"Missy","email":"","middleInitial":"A","affiliations":[{"id":61759,"text":"Conservation Science Global, Inc.","active":true,"usgs":false}],"preferred":false,"id":837893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":837894,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schmuecker, Sara","contributorId":213247,"corporation":false,"usgs":false,"family":"Schmuecker","given":"Sara","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":837895,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller, Tricia A.","contributorId":190591,"corporation":false,"usgs":false,"family":"Miller","given":"Tricia","email":"","middleInitial":"A.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":837896,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228918,"text":"70228918 - 2022 - Analyzing the effects of land cover change on the water balance for case study watersheds in different forested ecosystems in the USA","interactions":[],"lastModifiedDate":"2022-02-24T18:00:28.672968","indexId":"70228918","displayToPublicDate":"2022-02-21T11:57:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Analyzing the effects of land cover change on the water balance for case study watersheds in different forested ecosystems in the USA","docAbstract":"

We analyzed impacts of interannual disturbance on the water balance of watersheds in different forested ecosystem case studies across the United States from 1985 to 2016 using a remotely sensed long-term land cover monitoring record (U.S. Geological Survey Land Change Monitoring, Assessment, and Projection (LCMAP) Collection 1.0 Science products), gridded precipitation and evaporation data, and streamgaging data using paired watersheds (high and low disturbance). LCMAP products were used to quantify the timing and degree of interannual disturbance and to gain a better understanding of how land cover change affects the water balance of disturbed watersheds. In this paper, we present how LCMAP science products can be used to improve knowledge for hydrologic modeling, climate research, and forest management. Anthropogenic influences (e.g., dams and irrigation diversions) often minimize the impacts of land cover change on water balance dynamics when compared to interannual fluctuations of hydroclimatic events (e.g., drought and flooding). Our findings show that each watershed exhibits a complex suite of influences involving climate variables and other factors that affect each of their water balances differently when land cover change occurs. In this study, forests within arid to semi-arid climates experience greater water balance effects from land cover change than watersheds where water is less limited. 

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Portal, California, USA","docAbstract":"

Wildfires frequently affect the steep hillslopes near El Portal, California (United States), a small community established during the California Gold Rush in the mid-1800s. In addition to the historical significance of El Portal, State Route 140 (SR 140) is a major transportation and economic corridor connecting the San Joaquin Valley to Yosemite National Park (YNP). In 2019, an estimated 4.5 million tourists visited and accessed YNP via SR 140. In the years after wildfires, the burned watersheds produced debris flows during intense rainfall, impacting the El Portal community and motorists traveling on SR 140 and local roads. The steepness of the hillslopes and confinement of the valley limit options for mitigating debris-flow risk. As such, emergency managers are left with evacuation orders or temporary road closures as the best options for risk reduction. The effectiveness of these options is highly dependent on establishing an accurate local rainfall intensity-duration threshold that officials can use to guide emergency response actions and timing. We present an overview of the rainfall conditions that initiated 12 post-fire debris-flow events near El Portal from 1991 to 2018 and objectively define rainfall intensity-duration thresholds from triggering rainfall rates. Our results highlight the modest rainfall rates that triggered debris flows in these steep watersheds, while radar data from more recent events (2012–2018) portray the spatial variability of intense rainfall in the area. Additional rainfall monitoring is needed to provide a robust rainfall threshold that will effectively mitigate risk for residents and motorists while minimizing the impact of road closures and evacuations.

","language":"English","publisher":"Association of Environmental & Engineering Geologists","doi":"10.2113/EEG-D-21-00031","usgsCitation":"De Graff, J.V., Staley, D.M., Stock, G., Takenaka, K., Gallegos, A., and Neptune, C., 2022, Rainfall triggering of post-fire debris flows over a 28-year period near El Portal, California, USA: Environmental and Engineering Geoscience, v. 28, no. 1, p. 133-145, https://doi.org/10.2113/EEG-D-21-00031.","productDescription":"14 p.","startPage":"133","endPage":"145","ipdsId":"IP-134684","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":483478,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"El Portal, Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.333,\n 38\n ],\n [\n -120.25,\n 38\n ],\n [\n -120.25,\n 37.333\n ],\n [\n -119.333,\n 37.333\n ],\n [\n -119.333,\n 38\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"28","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"De Graff, Jerome V.","contributorId":195393,"corporation":false,"usgs":false,"family":"De Graff","given":"Jerome","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":931121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":931122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stock, Greg M.","contributorId":258810,"corporation":false,"usgs":false,"family":"Stock","given":"Greg M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":931123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takenaka, Kellen","contributorId":352407,"corporation":false,"usgs":false,"family":"Takenaka","given":"Kellen","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":931124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gallegos, Alan L.","contributorId":352408,"corporation":false,"usgs":false,"family":"Gallegos","given":"Alan L.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":931125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Neptune, Chad K.","contributorId":352411,"corporation":false,"usgs":false,"family":"Neptune","given":"Chad K.","affiliations":[{"id":84211,"text":"California State University, Fresno CA USA","active":true,"usgs":false}],"preferred":false,"id":931126,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228780,"text":"70228780 - 2022 - Detrital zircon provenance of the Cretaceous-Neogene East Coast Basin reveals changing tectonic conditions and drainage reorganization along the Pacific margin of Zealandia","interactions":[],"lastModifiedDate":"2022-04-12T13:34:28.945014","indexId":"70228780","displayToPublicDate":"2022-02-21T08:56:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Detrital zircon provenance of the Cretaceous-Neogene East Coast Basin reveals changing tectonic conditions and drainage reorganization along the Pacific margin of Zealandia","docAbstract":"

The Upper Cretaceous–Pliocene strata of New Zealand record ~100 m.y. of Zealandia’s evolution, including development of the Hikurangi convergent margin and Alpine transform plate boundary. A comprehensive, new detrital zircon U-Pb data set (8315 analyses from 61 samples) was generated along a ~700 km transect of the East Coast Basin of New Zealand. Age distributions were analyzed and interpreted in terms of published data available for Cambrian–Cretaceous igneous and metasedimentary source terranes using a Monte Carlo mixture modeling approach. Results indicate a widespread Early Cretaceous transition in sediment source from the Gondwana interior to the Median Batholith magmatic arc prior to Late Cretaceous rifting from Antarctica. Submergence of Zealandia during a Late Cretaceous–Paleogene drift phase led to major drainage reorganization and the influx of Eastern Province sediment to the East Coast Basin. A long-lived sediment conduit that transported extraregional Western Province detritus to the south-central East Coast Basin may have developed along a structural precursor to the Alpine Fault. Marked Neogene increase of Upper Jurassic–Lower Cretaceous Torlesse Composite Terrane sediment to the central East Coast Basin resulted from exhumation of the Axial Ranges, convergence along the Hikurangi subduction margin, and concurrent development of the Alpine Fault. Concurrent influx of contemporaneous Neogene zircon in the northern East Coast Basin indicated the onset of subduction-related volcanism of the Northland–Coromandel Volcanic Arc. Middle Miocene–Pliocene exhumation and dextral translation of the Nelson region along the Alpine Fault resulted in the eastward routing of Western Province sediment to the central East Coast Basin. Finally, topography developed across the plate boundary and ultimately partitioned continental drainage of Zealandia, such that sediment from the Murihiku, Caples, and Rakaia Terranes in the Otago region was routed to the southern extent of the East Coast Basin. These results illuminate the evolution of the Zealandia continental drainage divide in response to the initiation of the Pacific-Australian plate boundary and demonstrate the power of mixture modeling and large data sets for deciphering sediment routing in dynamic tectonic environments.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02404.1","usgsCitation":"Gooley, J.T., and Nieminski, N.M., 2022, Detrital zircon provenance of the Cretaceous-Neogene East Coast Basin reveals changing tectonic conditions and drainage reorganization along the Pacific margin of Zealandia: Geosphere, v. 18, no. 2, p. 616-646, https://doi.org/10.1130/GES02404.1.","productDescription":"31 p.","startPage":"616","endPage":"646","ipdsId":"IP-125520","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":448721,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02404.1","text":"Publisher Index Page"},{"id":396221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 170.068359375,\n -47.04018214480665\n ],\n [\n 179.296875,\n -37.78808138412045\n ],\n [\n 173.935546875,\n -34.089061315849946\n ],\n [\n 172.44140625,\n -34.813803317113134\n ],\n [\n 173.49609375,\n -38.89103282648846\n ],\n [\n 170.947265625,\n -40.51379915504413\n ],\n [\n 165.76171875,\n -45.644768217751924\n ],\n [\n 168.57421875,\n -48.10743118848039\n ],\n [\n 170.068359375,\n -47.04018214480665\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Gooley, Jared T. 0000-0001-5620-3702","orcid":"https://orcid.org/0000-0001-5620-3702","contributorId":248710,"corporation":false,"usgs":true,"family":"Gooley","given":"Jared","email":"","middleInitial":"T.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":835452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nieminski, Nora Maria 0000-0002-4465-8731","orcid":"https://orcid.org/0000-0002-4465-8731","contributorId":279764,"corporation":false,"usgs":true,"family":"Nieminski","given":"Nora","email":"","middleInitial":"Maria","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":835453,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70229156,"text":"70229156 - 2022 - DSWEmod - The production of high-frequency surface water map composites from daily MODIS images","interactions":[],"lastModifiedDate":"2022-04-12T13:36:29.136585","indexId":"70229156","displayToPublicDate":"2022-02-21T06:51:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"DSWEmod - The production of high-frequency surface water map composites from daily MODIS images","docAbstract":"

Optical satellite imagery is commonly used for monitoring surface water dynamics, but clouds and cloud shadows present challenges in assembling complete water time series. To test whether the daily revisit rate of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery can reduce cloud obstruction and improve high-frequency surface water mapping, we compared map results derived from Landsat (30-m) and MODIS (250-m) data across the state of California for 2003–2019. We adapted the Dynamic Surface Water Extent (DSWE) model in Google Earth Engine to generate surface water map composites from MODIS imagery every 5, 10, 15, and 30 days, and compared products to monthly Landsat-based DSWE maps. Results for DSWEmod (DSWE MODIS) in California suggest that more than 5% data loss (cloud obstruction, etc.) was present in only 2% of the 15-day time series, as compared to 32% of the monthly Landsat DSWE time series. The five-day DSWEmod composites averaged 8.4% obscuration in the winter months. Area estimates derived from cloud-filtered MODIS and Landsat monthly products have the highest linear correlations compared to streamgage discharge records, suggesting that monthly scale analyses best explain the relationship between surface water area and general streamflow dynamics. Shorter-interval DSWEmod products have lower correlations but utility for understanding the timing of surface water peaks and past flood events.

","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12996","usgsCitation":"Soulard, C.E., Waller, E., Walker, J., Petrakis, R., and Smith, B.W., 2022, DSWEmod - The production of high-frequency surface water map composites from daily MODIS images: Journal of the American Water Resources Association, v. 58, no. 2, p. 248-268, https://doi.org/10.1111/1752-1688.12996.","productDescription":"21 p.","startPage":"248","endPage":"268","ipdsId":"IP-125002","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":489033,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12996","text":"Publisher Index Page"},{"id":435960,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QEDWAK","text":"USGS data release","linkHelpText":"DSWE_GEE v1.0.0"},{"id":435959,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RVPJWE","text":"USGS data release","linkHelpText":"DSWEmod surface water map composites generated from daily MODIS images - California"},{"id":396591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":836796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waller, Eric 0000-0002-9169-9210","orcid":"https://orcid.org/0000-0002-9169-9210","contributorId":220101,"corporation":false,"usgs":false,"family":"Waller","given":"Eric","affiliations":[],"preferred":false,"id":836797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walker, Jessica J. 0000-0002-3225-0317","orcid":"https://orcid.org/0000-0002-3225-0317","contributorId":207373,"corporation":false,"usgs":true,"family":"Walker","given":"Jessica J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":836798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Petrakis, Roy E. 0000-0001-8932-077X rpetrakis@usgs.gov","orcid":"https://orcid.org/0000-0001-8932-077X","contributorId":174623,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy","email":"rpetrakis@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":836799,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Britt Windsor 0000-0003-1556-2383","orcid":"https://orcid.org/0000-0003-1556-2383","contributorId":287481,"corporation":false,"usgs":true,"family":"Smith","given":"Britt","email":"","middleInitial":"Windsor","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":836800,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227767,"text":"sir20225005 - 2022 - Peak-flow and low-flow magnitude estimates at defined frequencies and durations for nontidal streams in Delaware","interactions":[],"lastModifiedDate":"2026-04-08T17:11:30.309284","indexId":"sir20225005","displayToPublicDate":"2022-02-18T09:45:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5005","displayTitle":"Peak-Flow and Low-Flow Magnitude Estimates at Defined Frequencies and Durations for Nontidal Streams in Delaware","title":"Peak-flow and low-flow magnitude estimates at defined frequencies and durations for nontidal streams in Delaware","docAbstract":"

Reliable estimates of the magnitude of peak flows in streams are required for the economical and safe design of transportation and water conveyance structures. In addition, reliable estimates of the magnitude of low flows at defined frequencies and durations are needed for meeting regulatory requirements, quantifying base flows in streams and rivers, and evaluating time of travel and dilution of toxic spills. This report, in cooperation with the Delaware Department of Transportation and the Delaware Geological Survey, presents methods for estimating the magnitude of peak flows and low flows at defined frequencies and durations on nontidal streams in Delaware, at locations both monitored by streamflow-gage sites and ungaged. Methods are presented for estimating (1) the magnitude of peak flows for return periods ranging from 2 to 500 years (50-percent to 0.2-percent annual-exceedance probability), and (2) the magnitude of low flows as applied to 7-, 14-, and 30-consecutive day low-flow periods with recurrence intervals of 2, 10, and 20 years (50-, 10-, and 5-percent annual non-exceedance probabilities). These methods are applicable to watersheds that exhibit a full range of development conditions in Delaware. The report also describes StreamStats, a web application that allows users to easily obtain peak-flow and low-flow magnitude estimates for user-selected locations in Delaware.

Peak-flow and low-flow magnitude estimates for ungaged sites are obtained using statistical regression analysis through a process known as regionalization, where information from a group of streamflow-gage sites within a region forms the basis for estimates for ungaged sites within the same region. Ninety-four streamflow-gage sites in and near Delaware with at least 10 years of nonregulated annual peak-flow data were used for the peak-flow regression analysis, a subset of the 121 sites for which peak-flow estimates were computed. These sites included both continuous-record streamflow-gage sites as well as partial record sites. Forty-five streamflow-gage sites with at least 10 years of nonregulated low-flow data available were used for the low-flow regression analyses, a subset of the 68 sites for which low-flow estimates were computed. Estimates for gaged sites are obtained by combining (1) the station peak-flow statistics (mean, standard deviation, and skew) and peak-flow estimates using the recent Bulletin 17C guidelines that incorporate the Expected Moments Algorithm with (2) regional estimates of peak-flow magnitude derived from regional regression equations and regional skew derived from sites with records greater than or equal to 35 years. Example peak-flow estimate calculations using the methods presented in the report are given for (1) ungaged sites, (2) gaged sites, (3) sites upstream or downstream from a gaged location, and (4) sites between gaged locations. Estimates for low-flow gaged sites are obtained by combining (1) the station low-flow statistics (mean, standard deviation, and skew) and low-flow estimates with (2) regional estimates of low-flow magnitude derived from regional regression equations. Example low-flow estimate calculations using the methods presented in the report are given for (1) ungaged sites, (2) gaged sites, (3) sites upstream or downstream from a gaged location, and (4) sites between gaged locations. A total of 54 sites in the Coastal Plain region were used to develop peak-flow regressions for the region and 40 sites were used for the Piedmont region. Similarly, 24 sites were used for low-flow regression equation development in the Coastal Plain, with 21 in the Piedmont. Peak and low-flow site inclusion in the Coastal Plain tended to be more restricted with tidal influence and ranges of basin characteristics, including drainage area, limiting regression equation development and application.

Regional regression equations for peak flows and low flows, as applicable to ungaged sites in the Piedmont and Coastal Plain Physiographic Provinces in Delaware, are presented. Peak-flow regression equations used variables that quantified drainage area, basin slope, percent area with well-drained soils, percent area with poorly drained soils, impervious area, and percent area of surface water storage in estimating peak-flow estimates, whereas low-flow regression equations used only drainage area and percent poorly drained soils in the estimation of low flows. Average standard errors for peak-flow regressions tended to be lower than those for low- flow regressions, with lower errors in the Piedmont region for both peak- and low-flow regressions. For peak-flow estimates, a sensitivity analysis of Piedmont regression equation estimates to changes in impervious area is also presented.

Additional topics associated with the analyses performed during the study are discussed, including (1) the availability and description of 32 basin and climatic characteristics considered during the development of the regional regression equations; (2) the treatment of increasing trends in the annual peak-flow series identified at 18 gaged sites and inclusion in or exclusion from the regional analysis; (3) regional skew analysis and determination of regression regions; (4) sample adjustments and removal of sites owing to regulation and redundancy; and (5) a brief comparison of peak- and low-flow estimates at gages used in previous studies.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225005","collaboration":"Prepared in cooperation with the Delaware Department of Transportation and the Delaware Geological Survey","usgsCitation":"Hammond, J.C., Doheny, E.J., Dillow, J.J.A., Nardi, M.R., Steeves, P.A., and Warner, D.L., 2022, Peak-flow and low-flow magnitude estimates at defined frequencies and durations for nontidal streams in Delaware: U.S. Geological Survey Scientific Investigations Report 2022–5005, 46 p., https://doi.org/10.3133/sir20225005.","productDescription":"Report: vi, 46 p.; 4 Data Releases","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127314","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":502293,"rank":10,"type":{"id":36,"text":"NGMDB Index 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\"}}]}","contact":"

Director, Maryland-Delaware-D.C. Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Catonsville, MD 21228

","tableOfContents":"","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2022-02-18","noUsgsAuthors":false,"publicationDate":"2022-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doheny, Edward J. 0000-0002-6043-3241","orcid":"https://orcid.org/0000-0002-6043-3241","contributorId":209742,"corporation":false,"usgs":true,"family":"Doheny","given":"Edward J.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dillow, Jonathan J.A. 0000-0001-7239-2654 jjdillow@usgs.gov","orcid":"https://orcid.org/0000-0001-7239-2654","contributorId":4207,"corporation":false,"usgs":true,"family":"Dillow","given":"Jonathan","email":"jjdillow@usgs.gov","middleInitial":"J.A.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nardi, Mark R. 0000-0002-7310-8050 mrnardi@usgs.gov","orcid":"https://orcid.org/0000-0002-7310-8050","contributorId":1859,"corporation":false,"usgs":true,"family":"Nardi","given":"Mark","email":"mrnardi@usgs.gov","middleInitial":"R.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832109,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Steeves, Peter A. 0000-0001-7558-9719 psteeves@usgs.gov","orcid":"https://orcid.org/0000-0001-7558-9719","contributorId":1873,"corporation":false,"usgs":true,"family":"Steeves","given":"Peter","email":"psteeves@usgs.gov","middleInitial":"A.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832110,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Warner, Daniel L.","contributorId":272562,"corporation":false,"usgs":false,"family":"Warner","given":"Daniel","email":"","middleInitial":"L.","affiliations":[{"id":33041,"text":"Delaware Geological Survey","active":true,"usgs":false}],"preferred":true,"id":832142,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228913,"text":"70228913 - 2022 - Partitioning ground motion uncertainty when conditioned on station data","interactions":[],"lastModifiedDate":"2022-03-28T16:55:10.476242","indexId":"70228913","displayToPublicDate":"2022-02-17T17:59:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Partitioning ground motion uncertainty when conditioned on station data","docAbstract":"

Rapid estimation of earthquake ground shaking and proper accounting of associated uncertainties in such estimates when conditioned on strong‐motion station data or macroseismic intensity observations are crucial for downstream applications such as ground failure and loss estimation. The U.S. Geological Survey ShakeMap system is called upon to fulfill this objective in light of increased near‐real‐time access to strong‐motion records from around the world. Although the station data provide a direct constraint on shaking estimates at specific locations, these data also heavily influence the uncertainty quantification at other locations. This investigation demonstrates methods to partition the within‐ (phi) and between‐event (tau) uncertainty estimates under the observational constraints, especially when between‐event uncertainties are heteroscedastic. The procedure allows the end users of ShakeMap to create separate between‐ and within‐event realizations of ground‐motion fields for downstream loss modeling applications in a manner that preserves the structure of the underlying random spatial processes.

","language":"English","publisher":"Seismological Society of America.","doi":"10.1785/0120210177","usgsCitation":"Engler, D.T., Worden, C., Thompson, E.M., and Jaiswal, K.S., 2022, Partitioning ground motion uncertainty when conditioned on station data: Bulletin of the Seismological Society of America, v. 112, no. 2, p. 1060-1079, https://doi.org/10.1785/0120210177.","productDescription":"20 p.","startPage":"1060","endPage":"1079","ipdsId":"IP-133182","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":396463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Engler, Davis T. 0000-0002-7133-3545","orcid":"https://orcid.org/0000-0002-7133-3545","contributorId":265962,"corporation":false,"usgs":true,"family":"Engler","given":"Davis","email":"","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":835872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Worden, Charles 0000-0003-1181-685X cbworden@usgs.gov","orcid":"https://orcid.org/0000-0003-1181-685X","contributorId":152042,"corporation":false,"usgs":true,"family":"Worden","given":"Charles","email":"cbworden@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":835873,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":835874,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":835875,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228751,"text":"ofr20221012 - 2022 - Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey flood risk management project area in San Diego County, California: Breeding activities and habitat use—2021 Annual report","interactions":[],"lastModifiedDate":"2022-03-03T18:48:35.560842","indexId":"ofr20221012","displayToPublicDate":"2022-02-17T12:21:26","publicationYear":"2022","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":"2022-1012","displayTitle":"Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey Flood Risk Management Project Area in San Diego County, California: Breeding Activities and Habitat Use—2021 Annual Report","title":"Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey flood risk management project area in San Diego County, California: Breeding activities and habitat use—2021 Annual report","docAbstract":"

Executive Summary

Surveys and monitoring for the endangered Least Bell’s Vireo (Vireo bellii pusillus; vireo) were done at the San Luis Rey Flood Risk Management Project Area (Project Area) in the city of Oceanside, San Diego County, California, between April 4 and August 4, 2021. We completed four protocol surveys during the breeding season, supplemented by weekly territory monitoring visits. We identified a total of 122 territorial male vireos; 111 were confirmed as paired and 8 were confirmed as single males. For the remaining three territories, we were unable to confirm pair status. Five transient vireos were detected in 2021. The vireo population in the Project Area decreased by 24 percent from 2020 to 2021. Vireo populations decreased across San Diego County, with a 14-percent decrease documented at Marine Corps Base Camp Pendleton (MCBCP); a 5-percent decrease on the Otay River; a 6-percent decrease on the middle San Luis Rey River; and a 44-percent decrease at Marine Corps Air Station (although this decrease was likely exaggerated by large-scale vegetation clearing that occurred prior to the 2021 breeding season).

We used an index of treatment (Treatment Index) to evaluate the impact of on-going vegetation clearing on the Project Area vireo population. The Treatment Index measures the cumulative effect of vegetation treatment within a territory (since 2005) by using the percent area treated weighted by the number of years since treatment. We found that the Treatment Index for unoccupied habitat was more than two times that of occupied habitat, indicating that vireos selected less treated habitat in which to settle.

We monitored vireo nests at three general site types: (1) within the flood channel where exotic and native vegetation removal has occurred regularly (Channel), (2) three sites next to the flood channel where limited exotic and native vegetation removal has occurred (Off-channel), and (3) three sites that have been actively restored by planting native vegetation (Restoration). Nesting activity was monitored in 85 territories, 8 of which were occupied by single males. Of the completed nests, 39 percent were successful, and nest success did not differ among the three sites. Clutch size was greater in the Channel than the Off-channel sites, and the proportion of hatchlings that fledged was greater in Off-channel sites than Channel and Restoration sites. There were no other nest-level differences detected among site types, nor were there any differences in territory-level measures of productivity (young fledged per pair, double-brooding) among the sites. Overall, breeding success and productivity were slightly lower in 2021 than in 2020, with 66 percent of pairs fledgling at least one young and pairs fledging an average of 1.9±1.7 young.

To investigate if the cumulative years of treatment had an impact on vireo reproductive effort, we looked at the effects of the Treatment Index on reproductive parameters. Results from generalized linear models indicated that treatment did not have an effect on vireo nesting effort or the number of vireo fledglings per pair produced in 2021. Similarly, our analysis of nest survival for 2021 revealed no effect of Treatment Index on daily survival rate.

Analysis of vegetation data collected at vireo nests from 2006 to 2021 did not indicate an effect of vegetation at the nest on daily survival rate. We also found no differences in nest-placement characteristics among site types or successful/unsuccessful nests.

Red/arroyo willow (Salix laevigata or Salix lasiolepis) was the species most commonly selected for nesting by vireos in all three site types. Black willow (Salix gooddingii) and mule fat (Baccharis salicifolia) also were commonly used. Vireos used a wider variety of species for nesting in Channel and Off-channel sites (seven and eight species, respectively) compared with Restoration sites (three species).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221012","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Los Angeles District","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Houston, Alexandra , Allen, L.D., Pottinger, R.E., and Kus, B.E., 2022, Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey flood risk management project area in San Diego County, California: Breeding activities and habitat use—2021 Annual report: U.S. Geological Survey Open-File Report 2022–1012, 79 p., https://doi.org/10.3133/ofr20221012.","productDescription":"viii, 79 p.","numberOfPages":"79","onlineOnly":"Y","ipdsId":"IP-135579","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":396128,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1012/covrthb.jpg"},{"id":396129,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1012/ofr20221012.pdf","text":"Report","size":"7 Mb"},{"id":396130,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1012/ofr20221012.xml"},{"id":396131,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1012/images"}],"country":"United States","state":"California","county":"San Diego County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.41500854492188,\n 33.19301824551205\n ],\n [\n -117.17056274414064,\n 33.19301824551205\n ],\n [\n -117.17056274414064,\n 33.288350918671775\n ],\n [\n -117.41500854492188,\n 33.288350918671775\n ],\n [\n -117.41500854492188,\n 33.19301824551205\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

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

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2022-02-17","noUsgsAuthors":false,"publicationDate":"2022-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Houston, Alexandra 0000-0002-8599-8265 ahouston@usgs.gov","orcid":"https://orcid.org/0000-0002-8599-8265","contributorId":139460,"corporation":false,"usgs":true,"family":"Houston","given":"Alexandra","email":"ahouston@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":835313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Lisa D. 0000-0002-6147-3165 ldallen@usgs.gov","orcid":"https://orcid.org/0000-0002-6147-3165","contributorId":196789,"corporation":false,"usgs":true,"family":"Allen","given":"Lisa","email":"ldallen@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":835314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pottinger, Ryan E. 0000-0002-0263-0300","orcid":"https://orcid.org/0000-0002-0263-0300","contributorId":212869,"corporation":false,"usgs":true,"family":"Pottinger","given":"Ryan","email":"","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":835315,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kus, Barbara E. 0000-0002-3679-3044 barbara_kus@usgs.gov","orcid":"https://orcid.org/0000-0002-3679-3044","contributorId":3026,"corporation":false,"usgs":true,"family":"Kus","given":"Barbara E.","email":"barbara_kus@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":835316,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228755,"text":"70228755 - 2022 - The global environmental agenda urgently needs a semantic web of knowledge","interactions":[],"lastModifiedDate":"2022-02-18T15:10:45.197958","indexId":"70228755","displayToPublicDate":"2022-02-17T09:08:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5897,"text":"Environmental Evidence","active":true,"publicationSubtype":{"id":10}},"title":"The global environmental agenda urgently needs a semantic web of knowledge","docAbstract":"

Progress in key social-ecological challenges of the global environmental agenda (e.g., climate change, biodiversity conservation, Sustainable Development Goals) is hampered by a lack of integration and synthesis of existing scientific evidence. Facing a fast-increasing volume of data, information remains compartmentalized to pre-defined scales and fields, rarely building its way up to collective knowledge. Today's distributed corpus of human intelligence, including the scientific publication system, cannot be exploited with the efficiency needed to meet current evidence synthesis challenges; computer-based intelligence could assist this task. Artificial Intelligence (AI)-based approaches underlain by semantics and machine reasoning offer a constructive way forward, but depend on greater understanding of these technologies by the science and policy communities and coordination of their use. By labelling web-based scientific information to become readable by both humans and computers, machines can search, organize, reuse, combine and synthesize information quickly and in novel ways. Modern open science infrastructure—i.e., public data and model repositories—is a useful starting point, but without shared semantics and common standards for machine actionable data and models, our collective ability to build, grow, and share a collective knowledge base will remain limited. The application of semantic and machine reasoning technologies by a broad community of scientists and decision makers will favour open synthesis to contribute and reuse knowledge and apply it toward decision making.

","language":"English","publisher":"BMC","doi":"10.1186/s13750-022-00258-y","usgsCitation":"Balbi, S., Bagstad, K.J., Magrach, A., Sanz, M.J., Aguilar-Amuchastegui, N., Guipponi, C., and Villa, F., 2022, The global environmental agenda urgently needs a semantic web of knowledge: Environmental Evidence, v. 11, 5, 6 p., https://doi.org/10.1186/s13750-022-00258-y.","productDescription":"5, 6 p.","ipdsId":"IP-126413","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":448740,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13750-022-00258-y","text":"Publisher Index Page"},{"id":396173,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2022-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Balbi, Stefano 0000-0001-8190-5968","orcid":"https://orcid.org/0000-0001-8190-5968","contributorId":208481,"corporation":false,"usgs":false,"family":"Balbi","given":"Stefano","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":835326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":835327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magrach, Ainhoa 0000-0003-2155-7556","orcid":"https://orcid.org/0000-0003-2155-7556","contributorId":208482,"corporation":false,"usgs":false,"family":"Magrach","given":"Ainhoa","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":835328,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanz, Maria Jose 0000-0003-0471-3094","orcid":"https://orcid.org/0000-0003-0471-3094","contributorId":279661,"corporation":false,"usgs":false,"family":"Sanz","given":"Maria","email":"","middleInitial":"Jose","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":835329,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aguilar-Amuchastegui, Naikoa 0000-0002-5072-0079","orcid":"https://orcid.org/0000-0002-5072-0079","contributorId":279662,"corporation":false,"usgs":false,"family":"Aguilar-Amuchastegui","given":"Naikoa","email":"","affiliations":[{"id":37767,"text":"World Wildlife Fund","active":true,"usgs":false}],"preferred":false,"id":835330,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Guipponi, Carlo","contributorId":279664,"corporation":false,"usgs":false,"family":"Guipponi","given":"Carlo","email":"","affiliations":[{"id":47673,"text":"Ca’ Foscari University of Venice","active":true,"usgs":false}],"preferred":false,"id":835331,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Villa, Ferdinando 0000-0002-5114-3007","orcid":"https://orcid.org/0000-0002-5114-3007","contributorId":208486,"corporation":false,"usgs":false,"family":"Villa","given":"Ferdinando","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":835332,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237304,"text":"70237304 - 2022 - Effects of weather variation on waterfowl migration: Lessons from a continental-scale generalizable avian movement and energetics model","interactions":[],"lastModifiedDate":"2022-10-07T12:24:33.871983","indexId":"70237304","displayToPublicDate":"2022-02-17T07:19:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Effects of weather variation on waterfowl migration: Lessons from a continental-scale generalizable avian movement and energetics model","docAbstract":"

We developed a continental energetics-based model of daily mallard (Anas platyrhynchos) movement during the non-breeding period (September to May) to predict year-specific migration and overwinter occurrence. The model approximates movements and stopovers as functions of metabolism and weather, in terms of temperature and frozen precipitation (i.e., snow). The model is a Markov process operating at the population level and is parameterized through a review of literature. We applied the model to 62 years of daily weather data for the non-breeding period. The average proportion of available habitat decreased as weather severity increased, with mortality decreasing as the proportion of available habitat increased. The most commonly used locations during the course of the non-breeding period were generally consistent across years, with the most inter-annual variation present in the overwintering area. Our model revealed that the distribution of mallards on the landscape changed more dramatically when the variation in daily available habitat was greater. The main routes for avian migration in North America were predicted by our simulations: the Atlantic, Mississippi, Central, and Pacific flyways. Our model predicted an average of 77.4% survivorship for the non-breeding period across all years (range = 76.4%–78.4%), with lowest survivorship during autumn (90.5 ± 1.4%), intermediate survivorship in winter (91.8 ± 0.7%), and greatest survivorship in spring (93.6 ± 1.1%). We provide the parameters necessary for exploration within and among other taxa to leverage the generalizability of this migration model to a broader expanse of bird species, and across a range of climate change and land use/land cover change scenarios.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8617","usgsCitation":"Aagaard, K., Lonsdorf, E.V., and Thogmartin, W.E., 2022, Effects of weather variation on waterfowl migration: Lessons from a continental-scale generalizable avian movement and energetics model: Ecology and Evolution, v. 12, no. 2, e8617, 17 p., https://doi.org/10.1002/ece3.8617.","productDescription":"e8617, 17 p.","ipdsId":"IP-098938","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":448743,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.8617","text":"External Repository"},{"id":408084,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Aagaard, Kevin 0000-0003-0756-2172","orcid":"https://orcid.org/0000-0003-0756-2172","contributorId":297403,"corporation":false,"usgs":false,"family":"Aagaard","given":"Kevin","affiliations":[{"id":40249,"text":"former UMESC employee","active":true,"usgs":false}],"preferred":false,"id":854092,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lonsdorf, Eric V.","contributorId":149495,"corporation":false,"usgs":false,"family":"Lonsdorf","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":17752,"text":"Chicago Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":854094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":854096,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228776,"text":"70228776 - 2022 - Atlantic circulation change still uncertain","interactions":[],"lastModifiedDate":"2022-03-18T15:13:49.075707","indexId":"70228776","displayToPublicDate":"2022-02-17T06:44:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Atlantic circulation change still uncertain","docAbstract":"

Deep oceanic overturning circulation in the Atlantic (Atlantic Meridional Overturning Circulation (AMOC)) is projected to decrease in the future in response to anthropogenic warming. Caesar et al.1 argue that an AMOC slowdown started in the nineteenth century and intensified during the mid-twentieth century. Although the argument and selected evidence proposed have some merits, we find that their conclusions might be different if a more complete array of data available in the North Atlantic region is considered. We argue that the strength of AMOC over recent centuries is still poorly constrained and the expected slowdown may not have started yet.

Recently, Moffa-Sánchez et al.2 compiled a comprehensive set of palaeoclimate proxy data from the North Atlantic and Arctic regions using objective criteria to identify high-quality datasets of ocean conditions that span the past two millennia (Fig. 1). Although no direct (singular) proxy for AMOC exists, the palaeoceanographic proxy data compiled by Moffa-Sánchez et al.2 highlight the spatial and temporal complexities of the ocean state in modern times and the recent past. When all the available proxy records potentially related to AMOC variability and twentieth century observational datasets are considered, the time history of the AMOC system becomes less certain. In contrast, selecting only a subset of proxy records that share similar trends, as performed by Caesar et al.1, provides an incomplete perspective on AMOC changes through time.

","language":"English","publisher":"Nature","doi":"10.1038/s41561-022-00896-4","usgsCitation":"Kilbourne, K., Wanamaker, A., Moffa-Sanchez, P., Reynolds, D.J., Amrhein, D.E., Butler, P.G., Goes, M., Jansen, M., Little, C.M., Mette, M.J., Moreno-Chamarro, E., Ortega, P., Otto-Bliesner, B., Rossby, T., Scourse, J., and Whitney, N.M., 2022, Atlantic circulation change still uncertain: Nature Geoscience, v. 15, p. 165-167, https://doi.org/10.1038/s41561-022-00896-4.","productDescription":"3 p.","startPage":"165","endPage":"167","ipdsId":"IP-129964","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467199,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/gsofacpubs/2234","text":"External Repository"},{"id":396160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Greenland, Iceland, Ireland, Morocco, Norway, Scotland, Wales","otherGeospatial":"Atlantic Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.671875,\n 31.353636941500987\n ],\n [\n -82.265625,\n 26.745610382199022\n ],\n [\n -8.7890625,\n 29.84064389983441\n ],\n [\n -10.8984375,\n 38.272688535980976\n ],\n [\n -7.734374999999999,\n 45.336701909968134\n ],\n [\n -4.21875,\n 53.9560855309879\n ],\n [\n 3.515625,\n 62.431074232920906\n ],\n [\n 9.84375,\n 64.92354174306496\n ],\n [\n 15.468749999999998,\n 68.9110048456202\n ],\n [\n 14.765625,\n 79.56054626376367\n ],\n [\n -33.75,\n 78.27820145542813\n ],\n [\n -61.52343749999999,\n 73.32785809840696\n ],\n [\n -65.390625,\n 59.355596110016315\n ],\n [\n -75.5859375,\n 44.59046718130883\n ],\n [\n -83.671875,\n 31.353636941500987\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2022-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Kilbourne, K. Halimeda","contributorId":279708,"corporation":false,"usgs":false,"family":"Kilbourne","given":"K. 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J.","contributorId":279711,"corporation":false,"usgs":false,"family":"Reynolds","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":57351,"text":"Centre for Geography and Environmental Sciences, University of Exeter, Penryn, Cornwall, TR10 9EZ, UK","active":true,"usgs":false}],"preferred":false,"id":835389,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Amrhein, Daniel E.","contributorId":279712,"corporation":false,"usgs":false,"family":"Amrhein","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":57353,"text":"Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA","active":true,"usgs":false}],"preferred":false,"id":835390,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Butler, Paul G.","contributorId":279713,"corporation":false,"usgs":false,"family":"Butler","given":"Paul","email":"","middleInitial":"G.","affiliations":[{"id":57351,"text":"Centre for Geography and 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M.","contributorId":279723,"corporation":false,"usgs":false,"family":"Whitney","given":"Nina","email":"","middleInitial":"M.","affiliations":[{"id":26904,"text":"Woods Hole Oceanographic Institution, USA","active":true,"usgs":false}],"preferred":false,"id":835401,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70228902,"text":"70228902 - 2022 - Wildfire probability models calibrated using past human and lightning ignition patterns can inform mitigation of post-fire hydrologic hazards","interactions":[],"lastModifiedDate":"2022-02-23T12:42:18.701658","indexId":"70228902","displayToPublicDate":"2022-02-17T06:40:06","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1799,"text":"Geomatics, Natural Hazards and Risk","active":true,"publicationSubtype":{"id":10}},"title":"Wildfire probability models calibrated using past human and lightning ignition patterns can inform mitigation of post-fire hydrologic hazards","docAbstract":"

Most wildfires are started by humans, however, geographic variation of potential ignition sources is not often explicitly accounted for in wildfire simulation modelling or risk assessments. In this study, we investigated how patterns of human and lightning ignitions can influence modelled fire simulations and demonstrate how these data can be used to assess post-fire flooding and sediment transport. We used historical ignition data (1992–2015) to characterize ignition patterns for thirteen mountain ranges in southern Arizona, United States, and developed FlamMap burn probability (BP) models for three scenarios: human ignition, lightning ignition, and random ignition. We then developed a watershed-scale case study assessing the impacts of ignition scenarios on post-fire hydrology using the KINEROS2 model that simulates runoff and erosion. BP models illustrated considerable differences in landscape fire risk between the three ignition scenarios. Results from the watershed model indicate the greatest impacts from the post-fire human ignition scenario, with a 10-fold increase in sediment discharge and four-fold increase in peak flow compared to pre-fire conditions. Our results show that consideration of ignition source and location is important for assessing fire risk, and our modelling approach provides a planning mechanism to identify locations most at risk to fire-induced flood hazards, where prevention and mitigation activities can be focused.

","language":"English","publisher":"Taylor and Frances","doi":"10.1080/19475705.2022.2039787","usgsCitation":"Villarreal, M.L., Norman, L., Yao, E., and Conrad, C., 2022, Wildfire probability models calibrated using past human and lightning ignition patterns can inform mitigation of post-fire hydrologic hazards: Geomatics, Natural Hazards and Risk, v. 13, no. 1, p. 568-590, https://doi.org/10.1080/19475705.2022.2039787.","productDescription":"23 p.","startPage":"568","endPage":"590","ipdsId":"IP-134069","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":448754,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/19475705.2022.2039787","text":"Publisher Index Page"},{"id":435962,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FYHDWZ","text":"USGS data release","linkHelpText":"Burn probability models calibrated using past human and lightning ignition patterns in the Madrean Sky Islands, Arizona"},{"id":396331,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":835829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":835830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yao, Erika","contributorId":280000,"corporation":false,"usgs":false,"family":"Yao","given":"Erika","email":"","affiliations":[{"id":57405,"text":"Contractor to Western Geographic Science Center","active":true,"usgs":false}],"preferred":false,"id":835831,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrad, Caroline Rose","contributorId":280001,"corporation":false,"usgs":true,"family":"Conrad","given":"Caroline Rose","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":835832,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228757,"text":"70228757 - 2022 - Mapping benthic algae and cyanobacteria in river channels from aerial photographs and satellite images: A proof-of-concept investigation on the Buffalo National River, AR, USA","interactions":[],"lastModifiedDate":"2022-02-18T15:26:51.293021","indexId":"70228757","displayToPublicDate":"2022-02-16T09:19:47","publicationYear":"2022","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":"Mapping benthic algae and cyanobacteria in river channels from aerial photographs and satellite images: A proof-of-concept investigation on the Buffalo National River, AR, USA","docAbstract":"

Although rivers are of immense practical, aesthetic, and recreational value, these aquatic habitats are particularly sensitive to environmental changes. Increasingly, changes in streamflow and water quality are resulting in blooms of bottom-attached (benthic) algae, also known as periphyton, which have become widespread in many water bodies of US national parks. Because these blooms degrade visitor experiences and threaten human and ecosystem health, improved methods of characterizing benthic algae are needed. This study evaluated the potential utility of remote sensing techniques for mapping variations in algal density in shallow, clear-flowing rivers. As part of an initial proof-of-concept investigation, field measurements of water depth and percent cover of benthic algae were collected from two reaches of the Buffalo National River along with aerial photographs and multispectral satellite images. Applying a band ratio algorithm to these data yielded reliable depth estimates, although a shallow bias and moderate level of precision were observed. Spectral distinctions among algal percent cover values ranging from 0 to 100% were subtle and became only slightly more pronounced when the data were aggregated to four ordinal levels. A bagged trees machine learning model trained using the original spectral bands and image-derived depth estimates as predictor variables was used to produce classified maps of algal density. The spatial and temporal patterns depicted in these maps were reasonable but overall classification accuracies were modest, up to 64.6%, due to a lack of spectral detail. To further advance remote sensing of benthic algae and other periphyton, future studies could adopt hyperspectral approaches and more quantitative, continuous metrics such as biomass.

","language":"English","publisher":"MDPI","doi":"10.3390/rs14040953","usgsCitation":"Legleiter, C.J., and Hodges, S.W., 2022, Mapping benthic algae and cyanobacteria in river channels from aerial photographs and satellite images: A proof-of-concept investigation on the Buffalo National River, AR, USA: Remote Sensing, v. 14, no. 4, 953, 28 p., https://doi.org/10.3390/rs14040953.","productDescription":"953, 28 p.","ipdsId":"IP-136035","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":448762,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14040953","text":"Publisher Index Page"},{"id":435963,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J5QXDJ","text":"USGS data release","linkHelpText":"Remotely sensed data and field measurements of water depth and percent cover of benthic algae from two reaches of the Buffalo National River in Arkansas acquired in August 2021"},{"id":396175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Buffalo National River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.438720703125,\n 35.917971791312816\n ],\n [\n -92.00225830078125,\n 35.917971791312816\n ],\n [\n -92.00225830078125,\n 36.22876574685929\n ],\n [\n -93.438720703125,\n 36.22876574685929\n ],\n [\n -93.438720703125,\n 35.917971791312816\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":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":835333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hodges, Shawn W 0000-0002-8950-7232","orcid":"https://orcid.org/0000-0002-8950-7232","contributorId":279667,"corporation":false,"usgs":false,"family":"Hodges","given":"Shawn","email":"","middleInitial":"W","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":835334,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70240948,"text":"70240948 - 2022 - Quantitative meta-analysis reveals no association between mercury contamination and body condition in birds","interactions":[],"lastModifiedDate":"2023-03-02T13:08:41.273057","indexId":"70240948","displayToPublicDate":"2022-02-16T07:06:13","publicationYear":"2022","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":"Quantitative meta-analysis reveals no association between mercury contamination and body condition in birds","docAbstract":"

Mercury contamination is a major threat to the global environment, and is still increasing in some regions despite international regulations. The methylated form of mercury is hazardous to biota, yet its sublethal effects are difficult to detect in wildlife. Body condition can vary in response to stressors, but previous studies have shown mixed effects of mercury on body condition in wildlife. Using birds as study organisms, we provide the first quantitative synthesis of the effect of mercury on body condition in animals. In addition, we explored the influence of intrinsic, extrinsic and methodological factors potentially explaining cross-study heterogeneity in results. We considered experimental and correlative studies carried out in adult birds and chicks, and mercury exposure inferred from blood and feathers. Most experimental investigations (90%) showed a significant relationship between mercury concentrations and body condition. Experimental exposure to mercury disrupted nutrient (fat) metabolism, metabolic rates, and food intake, resulting in either positive or negative associations with body condition. Correlative studies also showed either positive or negative associations, of which only 14% were statistically significant. Therefore, the overall effect of mercury concentrations on body condition was null in both experimental (estimate ± SE = 0.262 ± 0.309, 20 effect sizes, five species) and correlative studies (−0.011 ± 0.020, 315 effect sizes, 145 species). The single and interactive effects of age class and tissue type were accounted for in meta-analytic models of the correlative data set, since chicks and adults, as well as blood and feathers, are known to behave differently in terms of mercury accumulation and health effects. Of the 15 moderators tested, only wintering status explained cross-study heterogeneity in the correlative data set: free-ranging wintering birds were more likely to show a negative association between mercury and body condition. However, wintering effect sizes were limited to passerines, further studies should thus confirm this trend in other taxa. Collectively, our results suggest that (i) effects of mercury on body condition are weak and mostly detectable under controlled conditions, and (ii) body condition indices are unreliable indicators of mercury sublethal effects in the wild. Food availability, feeding rates and other sources of variation that are challenging to quantify likely confound the association between mercury and body condition in natura. Future studies could explore the metabolic effects of mercury further using designs that allow for the estimation and/or manipulation of food intake in both wild and captive birds, especially in under-represented life-history stages such as migration and overwintering.

","language":"English","publisher":"Wiley","doi":"10.1111/brv.12840","usgsCitation":"Carravieri, A., Vincze, O., Bustamante, P., Ackerman, J.T., Adams, E.M., Angelier, F., Chastel, O., Cherel, Y., Gilg, O., Golubova, E., Kitaysky, A., Luff, K., Seewagen, C.L., Strom, H., Will, A.P., Yannic, G., Giraudeau, M., and Fort, J., 2022, Quantitative meta-analysis reveals no association between mercury contamination and body condition in birds: Biological Reviews, v. 97, no. 4, p. 1253-1271, https://doi.org/10.1111/brv.12840.","productDescription":"19 p.","startPage":"1253","endPage":"1271","ipdsId":"IP-131356","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":448781,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/brv.12840","text":"Publisher Index Page"},{"id":413610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Carravieri, Alice 0000-0002-7740-843X","orcid":"https://orcid.org/0000-0002-7740-843X","contributorId":302760,"corporation":false,"usgs":false,"family":"Carravieri","given":"Alice","email":"","affiliations":[{"id":65546,"text":"Littoral Environnement et Sociétés","active":true,"usgs":false}],"preferred":false,"id":865390,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vincze, Orsolya 0000-0001-5789-2124","orcid":"https://orcid.org/0000-0001-5789-2124","contributorId":302761,"corporation":false,"usgs":false,"family":"Vincze","given":"Orsolya","email":"","affiliations":[{"id":65547,"text":"Hungarian Department of Biology and Ecology","active":true,"usgs":false}],"preferred":false,"id":865391,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bustamante, Paco","contributorId":201551,"corporation":false,"usgs":false,"family":"Bustamante","given":"Paco","email":"","affiliations":[{"id":36199,"text":"La Rochelle University","active":true,"usgs":false}],"preferred":false,"id":865392,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":865393,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Evan M.","contributorId":139994,"corporation":false,"usgs":false,"family":"Adams","given":"Evan","email":"","middleInitial":"M.","affiliations":[{"id":6928,"text":"BioDiversity Research Institute, Gorham, ME 04038","active":true,"usgs":false}],"preferred":false,"id":865394,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Angelier, Frederic","contributorId":293655,"corporation":false,"usgs":false,"family":"Angelier","given":"Frederic","email":"","affiliations":[{"id":63358,"text":"Centre d'Etudes Biologiques de Chizé (CEBC), UMR 7372 CNRS- La Rochelle Université, 79360 Villiers-en-Bois, France","active":true,"usgs":false}],"preferred":false,"id":865395,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chastel, Olivier","contributorId":293653,"corporation":false,"usgs":false,"family":"Chastel","given":"Olivier","email":"","affiliations":[{"id":63355,"text":"Centre d'Etudes Biologiques de Chizé (CEBC), UMR 7372 CNRS- La Rochelle Université, 79360 Villiers-en-Bois, France.","active":true,"usgs":false}],"preferred":false,"id":865396,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cherel, Yves 0000-0001-9469-9489","orcid":"https://orcid.org/0000-0001-9469-9489","contributorId":267388,"corporation":false,"usgs":false,"family":"Cherel","given":"Yves","email":"","affiliations":[{"id":55487,"text":"La Rochelle University, Villiers-en-Bois, France","active":true,"usgs":false}],"preferred":false,"id":865397,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gilg, Olivier","contributorId":169342,"corporation":false,"usgs":false,"family":"Gilg","given":"Olivier","email":"","affiliations":[],"preferred":false,"id":865398,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Golubova, Elena","contributorId":293663,"corporation":false,"usgs":false,"family":"Golubova","given":"Elena","email":"","affiliations":[{"id":63366,"text":"Laboratory of Ornithology, Institute of Biological Problems of the North, RU-685000 Magadan, Portovaya Str., 18, Russia","active":true,"usgs":false}],"preferred":false,"id":865399,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kitaysky, Alexander","contributorId":221846,"corporation":false,"usgs":false,"family":"Kitaysky","given":"Alexander","affiliations":[{"id":36971,"text":"University of Alaska","active":true,"usgs":false}],"preferred":false,"id":865400,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Luff, Katelyn 0000-0002-8897-5325","orcid":"https://orcid.org/0000-0002-8897-5325","contributorId":302762,"corporation":false,"usgs":false,"family":"Luff","given":"Katelyn","email":"","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":865401,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Seewagen, Chad L.","contributorId":302763,"corporation":false,"usgs":false,"family":"Seewagen","given":"Chad","email":"","middleInitial":"L.","affiliations":[{"id":65548,"text":"Great Hollow Nature Preserve and Ecological Research Center","active":true,"usgs":false}],"preferred":false,"id":865402,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Strom, Hallvard","contributorId":293678,"corporation":false,"usgs":false,"family":"Strom","given":"Hallvard","email":"","affiliations":[{"id":63362,"text":"Norwegian Polar Institute, Fram center, 9296 Tromsø, Norway","active":true,"usgs":false}],"preferred":false,"id":865403,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Will, Alexis P.","contributorId":302764,"corporation":false,"usgs":false,"family":"Will","given":"Alexis","email":"","middleInitial":"P.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":865404,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Yannic, Glenn","contributorId":293683,"corporation":false,"usgs":false,"family":"Yannic","given":"Glenn","email":"","affiliations":[{"id":63378,"text":"Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, 38000 Grenoble, France","active":true,"usgs":false}],"preferred":false,"id":865405,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Giraudeau, Mathieu","contributorId":302765,"corporation":false,"usgs":false,"family":"Giraudeau","given":"Mathieu","email":"","affiliations":[{"id":65546,"text":"Littoral Environnement et Sociétés","active":true,"usgs":false}],"preferred":false,"id":865406,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Fort, Jerome","contributorId":23344,"corporation":false,"usgs":false,"family":"Fort","given":"Jerome","email":"","affiliations":[],"preferred":false,"id":865407,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70241842,"text":"70241842 - 2022 - Molecular mechanisms of solid bitumen and vitrinite reflectance suppression explored using hydrous pyrolysis of artificial source rock","interactions":[],"lastModifiedDate":"2023-03-29T12:05:04.630383","indexId":"70241842","displayToPublicDate":"2022-02-15T07:01:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2958,"text":"Organic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Molecular mechanisms of solid bitumen and vitrinite reflectance suppression explored using hydrous pyrolysis of artificial source rock","docAbstract":"

The most commonly used parameter for thermal maturity calibration in basin modelling is mean random vitrinite reflectance (Ro). However, Ro suppression has been noted in samples containing a high proportion of liptinite macerals. This phenomenon has been demonstrated empirically using hydrous pyrolysis of artificial source rock containing various proportions of thermally immature Wyodak-Anderson coal and liptinite-rich kerogen from the Parachute Creek Member of the Green River Formation. Analysis of samples pyrolyzed at 330 °C for 72 h demonstrates that Ro values of both vitrinite and solid bitumen are suppressed in rocks containing liptinite-rich kerogen. Raman and micro-Fourier transform infrared (µ-FTIR) analyses were performed to investigate the mechanisms of suppression. Raman maturity proxies show decreased aromaticity in samples with suppressed Ro, particularly in solid bitumen, with aromaticity decreasing as the proportion of liptinite increases. The µ-FTIR proxy for aliphatic chain length and/or branching ratio is static in solid bitumen, yet increases slightly in vitrinite as the liptinite proportion increases. These spectroscopic results suggest slightly different suppression mechanisms for vitrinite and solid bitumen, with reduced C\"singleC bond cleavage and marginally reduced aromaticity in vitrinite with suppressed Ro, and strongly reduced aromaticity and C\"singleC bond cleavage in solid bitumen with suppressed Ro. These results support the hypothesis that the generation of free radicals during maturation slows aromatization and highlight the disadvantages of using solid bitumen Ro for maturity calibration in liptinite-rich samples. Furthermore, our results indicate that use of Raman data obtained from liptinite-rich samples may also result in suppressed maturity indicators, particularly if the macerals are not identified prior to analysis.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.orggeochem.2022.104371","usgsCitation":"Sanders, M.M., Jubb, A., Hackley, P.C., and Peters, K., 2022, Molecular mechanisms of solid bitumen and vitrinite reflectance suppression explored using hydrous pyrolysis of artificial source rock: Organic Geochemistry, v. 165, 104371, 12 p., https://doi.org/10.1016/j.orggeochem.2022.104371.","productDescription":"104371, 12 p.","ipdsId":"IP-134667","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":414885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"165","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sanders, Margaret M. 0000-0003-3505-874X","orcid":"https://orcid.org/0000-0003-3505-874X","contributorId":248709,"corporation":false,"usgs":true,"family":"Sanders","given":"Margaret","email":"","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":867904,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jubb, Aaron M. 0000-0001-6875-1079","orcid":"https://orcid.org/0000-0001-6875-1079","contributorId":201978,"corporation":false,"usgs":true,"family":"Jubb","given":"Aaron M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":867905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":867906,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peters, Kenneth E.","contributorId":10897,"corporation":false,"usgs":true,"family":"Peters","given":"Kenneth E.","affiliations":[],"preferred":false,"id":867907,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230491,"text":"70230491 - 2022 - Integration of vegetation classification with land cover mapping: Lessons from regional mapping efforts in the Americas","interactions":[],"lastModifiedDate":"2022-04-14T11:49:12.307184","indexId":"70230491","displayToPublicDate":"2022-02-15T06:48:04","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10551,"text":"Vegetation Classification and Survey","active":true,"publicationSubtype":{"id":10}},"title":"Integration of vegetation classification with land cover mapping: Lessons from regional mapping efforts in the Americas","docAbstract":"

Aims: Natural resource management and biodiversity conservation rely on inventories of vegetation that span multiple management or political jurisdictions. However, while remote sensing data and analytical tools have enabled production of maps at increasing spatial resolution and reliability, there are limited examples where national or continental-scaled maps are produced to represent vegetation at high thematic detail. We illustrate two examples that have bridged the gap between traditional land cover mapping and modern vegetation classification. Study area: Our two case studies include national (USA) and continental (North and South America) vegetation and land cover mapping. These studies span conditions from subpolar to tropical latitudes of the Americas. Methods: Both case studies used a supervised modeling approach with the International Vegetation Classification (IVC) to produce maps that provide for greater thematic detail. Georeferenced locations for these vegetation types are used by machine learning algorithms to train a predictive model and generate a distribution map. Results: The USA LANDFIRE (Landscape Fire and Resource Management Planning Tools Project) case study illustrates how a history of vegetation-based classification and availability of key inputs can come together to generate standard map products covering more than 9.8 million km2 that are unsurpassed anywhere in the world in terms of spatial and thematic resolution. That being said, it also remains clear that mapping at the thematic resolution of the IVC Group and finer resolution require very large and spatially balanced inputs of georeferenced samples. Even with extensive prior data collection efforts, these remain a key limitation. The NatureServe effort for the Americas - encompassing 22% of the global land surface - demonstrates methods and outputs suitable for worldwide application at continental scales. Conclusions: Continued collection of input data used in the case studies could enable mapping at these spatial and thematic resolutions around the globe.

","language":"English","publisher":"Pensoft","doi":"10.3897/VCS.67537","usgsCitation":"Comer, P.J., Hak, J.C., Dockter, D., and Smith, J., 2022, Integration of vegetation classification with land cover mapping: Lessons from regional mapping efforts in the Americas: Vegetation Classification and Survey, p. 29-43, https://doi.org/10.3897/VCS.67537.","productDescription":"15 p.","startPage":"29","endPage":"43","ipdsId":"IP-128344","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":448793,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/vcs.67537","text":"Publisher Index Page"},{"id":398727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Comer, Patrick J. 0000-0002-5869-2105","orcid":"https://orcid.org/0000-0002-5869-2105","contributorId":258190,"corporation":false,"usgs":false,"family":"Comer","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":840550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hak, Jon C","contributorId":290233,"corporation":false,"usgs":false,"family":"Hak","given":"Jon","email":"","middleInitial":"C","affiliations":[{"id":17658,"text":"NatureServe","active":true,"usgs":false}],"preferred":false,"id":840551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dockter, Daryn 0000-0003-1914-8657","orcid":"https://orcid.org/0000-0003-1914-8657","contributorId":216392,"corporation":false,"usgs":false,"family":"Dockter","given":"Daryn","affiliations":[],"preferred":false,"id":840552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Jim","contributorId":191054,"corporation":false,"usgs":false,"family":"Smith","given":"Jim","email":"","affiliations":[],"preferred":false,"id":840553,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70238946,"text":"70238946 - 2022 - Fishway Entrance Palisade","interactions":[],"lastModifiedDate":"2023-01-10T16:06:21.874488","indexId":"70238946","displayToPublicDate":"2022-02-14T10:01:03","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":9958,"text":"Final Technical Report","active":true,"publicationSubtype":{"id":1}},"title":"Fishway Entrance Palisade","docAbstract":"This technical report summarizes the work that was conducted by the University of Massachusetts Amherst and the United States Geological Survey (USGS), along with other project partners, on the Fishway Entrance Palisade (EP), a projected funded through the Department of Energy’s (DOE) funding opportunity titled ‘Innovative Solutions for Fish Passage at Hydropower Dams’ (DE‐FOA‐0001662). The period of performance ranged from September 1, 2018 through September 30, 2021. \n\nThe EP is a novel fish passage engineering technology designed to provide more favorable entry conditions for fish and to reduce costs relative to conventional fishway auxiliary water systems (AWS). The EP project has four primary components.\n\nFirst, the Northeast United States Auxiliary Water Systems Database was created (Northeast Fishway Auxiliary Water Systems Database Section). The database, developed with material provided by the U.S. Fish and Wildlife Service, contains information on fishway type (e.g., lift, Denil, pool and weir) and Auxiliary Water System (AWS) details (e.g., water conveyance method, diffuser type) for 60 hydroelectric sites in the region. Findings indicate that nearly 4 out of every 10 fishway in the region is a fish lift and approximately 1 out of every 4 is a Denil ladder. The remainder are a mix of vertical slot fishways, pool and weirs, and Ice Harbor fishways. Furthermore, over half of all AWS systems use floor diffusers to discharge the auxiliary (or attraction) water into the entrance of a fishway, whereas only 14% use wall diffusers.\n\nSecond, limited experiments on a conventional AWS with live, actively migrating fish were conducted at the USGS Easter Ecological Science Center (EESC) S.O. Conte Research Laboratory (Conventional Auxiliary Water System Experiments Section). This study determined how water velocity through a wall diffuser, without turning vanes or timber baffles to distribute the flow, affects the behavior and passage of adult American shad, a conservative surrogate species for migratory fish on the East Coast. Two gross diffuser velocity treatments were examined, 0.5 ft/s and 1.0 ft/s. These wall diffuser velocities represented current (0.5 ft/s) and past (1.0 ft/s) design criteria guidelines set forth by the USFWS North Atlantic-Appalachian Region (Rojas 2020; USFWS 2019). Six trials with a total of 151 American Shad were conducted in June of 2019 for the two treatments. \n\nNo differences in American shad passage efficiency were discovered between the two treatments, while approximately 3 in every 4 attempts were successful at passing the diffuser. While these results may appear to indicate that the generally accepted gross wall diffuser velocity criteria for American shad of 0.5 ft/s could be safely increased to 1.0 ft/s, further analysis is warranted. Furthermore, it is unknown how other migratory and resident fish species that traverse these structures would be impacted by such a change. \n\nStudying the wall diffuser hydraulics led to an important AWS observation. Without turning vanes or timber baffles in this study, doubling the diffuser area was insufficient at producing the type of flow field change one may expect by halving the gross diffuser velocity. Instead, the flow fields throughout each treatments study area were similar, which led to similar results in shad performance. This not only highlights the importance of installing flow guidance devices like turning vanes, but also to the importance of properly maintaining them, which can be costly.\n\nThird, more expansive experiments on the novel EP were conducted in the spring of 2019 and 2021 (Fishway Entrance Palisade Experiments). The goal of this study was to determine how adult American shad responded to a variety of conditions at a full-scale EP. A total of six treatments were examined by changing the average auxiliary channel velocity between 1.0 and 5.0 ft/s in intervals of 1.0 ft/s and by inserting/removing an entrance gate at the opening of the fishway. Thirty trials with a total of 1,273 shad were conducted over the two years.\n\nIn all treatments, at least ~7 out of every 10 fish successfully passed the EP diffuser and swam into the entrance channel within the 3.5-hour long trial, highlighting the general effectiveness of the novel AWS technology. In both study years, lower velocities through the EP diffuser led to increased shad performance, though performance peaked for the 2 ft/s velocity treatment. This treatment condition represents an approximate six-fold increase in gross diffuser velocity relative to conventional auxiliary water systems, which in turn presents opportunities for cost savings (e.g., reduction in diffuser size).\n\nShad performance, in general, was worse in 2019 than in 2021, potentially due to the different run timing when our trials were conducted (2019 trials occurred near the end of the migration season, unlike in 2021). Treatments in 2019 had approximately a 20% reduction in entrance efficiency by the trial end, including a 16.7% drop for the 3 ft/s velocity treatment in 2019 relative to 2021 (the only carryover treatment between years). \n\nLastly, adding an entrance gate caused a significant delay to entry. The time to 25% entry raised ~20 minutes from the near instantaneous 25% entry that was reported for the other treatments conducted in the same year (2021). Though by the end of the 3.5-hour trial, the overall entrance efficiency nearly matched those of the other 2021 treatments.\n\nThe fourth and final component of the EP project was an economic analysis that focused on the cost of attraction and environmental flows (Modeling Power Generation Losses Due to Environmental and Fish Passage Attraction Flows at a Run-Of-River Hydroelectric Operation in the Northeast). The study assessed the economic impact of meeting environmental flow requirements at a representative hydroelectric facility and fish lift in the Northeast. An initial finding of the study was that there is a paucity of published data on the costs of meeting attraction and environmental flows. This is due, in part, to the proprietary nature of this data. To explore the costs associated with these flows, three types of environmental flows were assessed: upstream fishway attraction flows, downstream fishway attraction flows, and habitat maintenance minimum flows. A physics-based model was developed and calibrated with three years of hourly generation and flow data as inputs. Gage flow inputs were adjusted and used to calculate power generated. To address hydrologic variability, the model was executed to simulate 30 years of historical flows.\n\nResults indicate that both interannual and seasonal climatic factors impact the costs of meeting environmental flow requirements. Generation potential is most strongly curtailed during dry years in terms of maximizing the capacity factor (the percent of time a plant generates at capacity). Dry years, and especially dry summers, have the most significant costs associated with mitigation flows. Of the three types of flows, habitat flows are most costly in terms of power production, followed by upstream attraction flows. Downstream attraction flows are least costly. This finding is the likely result of differences in both flow rates and duration of the seasonal requirement for each flow. Overall, environmental flows represented a 2-12% loss in annual generation, but losses during a dry summer can reach over 20%.","language":"English","publisher":"U.S. Department of Energy","doi":"10.2172/1905243","usgsCitation":"Mulligan, K., Palmer, R., Towler, B., Haro, A., Lake, B., Rojas, M., and Lotter, E., 2022, Fishway Entrance Palisade: Final Technical Report, 23 p., https://doi.org/10.2172/1905243.","productDescription":"23 p.","ipdsId":"IP-138003","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":448800,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1905243","text":"External Repository"},{"id":411632,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.05182598949801,\n 44.89319311674552\n ],\n [\n -68.3175817931259,\n 47.33465807108087\n ],\n [\n -69.24621769928491,\n 47.283640086042396\n ],\n [\n -70.6255546394362,\n 45.53467504444376\n ],\n [\n -73.37060956424577,\n 44.92914333096371\n ],\n [\n -83.12438010438365,\n 34.6176223177726\n ],\n [\n -80.40129683431417,\n 31.8360293402377\n ],\n [\n -75.74355199471707,\n 35.10791041480914\n ],\n [\n -75.21833415636709,\n 38.125898555273295\n ],\n [\n -72.87164643954584,\n 40.72488283550473\n ],\n [\n -69.8736057821464,\n 41.750002105411085\n ],\n [\n -70.47472444522607,\n 43.094355406979275\n ],\n [\n -67.05182598949801,\n 44.89319311674552\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mulligan, Kevin 0000-0002-3534-4239 kmulligan@usgs.gov","orcid":"https://orcid.org/0000-0002-3534-4239","contributorId":177024,"corporation":false,"usgs":true,"family":"Mulligan","given":"Kevin","email":"kmulligan@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":859308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmer, Richard","contributorId":202903,"corporation":false,"usgs":false,"family":"Palmer","given":"Richard","affiliations":[],"preferred":false,"id":859309,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Towler, Brett","contributorId":141164,"corporation":false,"usgs":false,"family":"Towler","given":"Brett","email":"","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":859310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haro, Alexander 0000-0002-7188-9172 aharo@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-9172","contributorId":139198,"corporation":false,"usgs":true,"family":"Haro","given":"Alexander","email":"aharo@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":859311,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lake, Bjorn","contributorId":300039,"corporation":false,"usgs":false,"family":"Lake","given":"Bjorn","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":859312,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rojas, Marcia","contributorId":300040,"corporation":false,"usgs":false,"family":"Rojas","given":"Marcia","email":"","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":859313,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lotter, Elizabeth","contributorId":300041,"corporation":false,"usgs":false,"family":"Lotter","given":"Elizabeth","email":"","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":859314,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}