In spite of overall improvements in air and water quality, biological stress from low pH and high concentrations of inorganic aluminum continue to impact fish and fish habitat in northeastern North America, with independent and interactive effects on individuals, populations and communities. Integrative indicators can therefore be useful in monitoring both impact and recovery across multiple scales. Using coupled water chemistry (pH, conductivity, and base cation and inorganic aluminum concentration), geographic (site elevation and watershed area) and biological (fish diversity, fish abundance, gill aluminum concentration and gill physiology) data, we developed an integrated indicator of acid aluminum stress across the White and Green mountains in central New England, USA. As has been established in a number of previous studies, preliminary analysis clearly indicated that across all sites, inorganic aluminum concentration was consistently greatest during the spring season. Structural Equation modelling (SEM) revealed that toxic conditions (concurrent low pH and high concentrations of inorganic aluminum) were well summarized with an integrated toxicity score, related to both base cation concentrations and elevation, with sites at higher elevations more likely to experience toxic conditions as well as low base cation concentrations. As hypothesized, fish diversity and abundance were negatively related to toxicity score. In spite of considerable variation among individuals, gill aluminum was positively related to toxicity score for both Atlantic salmon and brook trout. Observed elevated gill aluminum levels associated with reduced gill metabolic activity in Atlantic salmon smolts from impacted systems likely result in impaired osmoregulatory function and seawater tolerance. Overall, our results suggest that the integrated toxicity score metric is strongly associated with a syndrome of physiological stress, reduced abundance, and low species diversity for stream fishes in New England and can likely serve as a reliable indicator of continued impairment or recovery of acid-aluminum vulnerable systems in this ecoregion.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.109480","usgsCitation":"Zdasiuk, B.J., Chen, C.Y., McCormick, S.D., Nislow, K., Singley, J.G., and Kelly, J.T., 2022, Evaluating acid-aluminum stress in streams of the Northeastern U.S. at watershed, fish community and physiological scales: Ecological Indicators, v. 144, 109480, 12 p., https://doi.org/10.1016/j.ecolind.2022.109480.","productDescription":"109480, 12 p.","ipdsId":"IP-138154","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446353,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2022.109480","text":"Publisher Index Page"},{"id":408282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Hampshire, Vermont","otherGeospatial":"Ammonoosuc basin, Merrimack basin, Saco River basin, West River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.80502319335938,\n 42.837709559849614\n ],\n [\n -72.54684448242188,\n 42.837709559849614\n ],\n [\n -72.54684448242188,\n 43.03577208929465\n ],\n [\n -72.80502319335938,\n 43.03577208929465\n ],\n [\n -72.80502319335938,\n 42.837709559849614\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.9879150390625,\n 43.757208878849376\n ],\n [\n -71.08978271484375,\n 43.757208878849376\n ],\n [\n -71.08978271484375,\n 44.5063000997406\n ],\n [\n -71.9879150390625,\n 44.5063000997406\n ],\n [\n -71.9879150390625,\n 43.757208878849376\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"144","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zdasiuk, Benjamin J","contributorId":297871,"corporation":false,"usgs":false,"family":"Zdasiuk","given":"Benjamin","email":"","middleInitial":"J","affiliations":[{"id":39657,"text":"Dartmouth College","active":true,"usgs":false}],"preferred":false,"id":854525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Celia Y.","contributorId":145630,"corporation":false,"usgs":false,"family":"Chen","given":"Celia","email":"","middleInitial":"Y.","affiliations":[{"id":16179,"text":"Dartmouth College, Hanover NH","active":true,"usgs":false}],"preferred":false,"id":854526,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854527,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nislow, Keith H.","contributorId":276357,"corporation":false,"usgs":false,"family":"Nislow","given":"Keith H.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":854528,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singley, Joel G","contributorId":297873,"corporation":false,"usgs":false,"family":"Singley","given":"Joel","email":"","middleInitial":"G","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":854529,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelly, John T.","contributorId":212827,"corporation":false,"usgs":false,"family":"Kelly","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":38688,"text":"Department of Biology & Environmental Science, University of New Haven","active":true,"usgs":false}],"preferred":false,"id":854530,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70236125,"text":"ofr20201143 - 2022 - Eelgrass (Zostera marina) and seaweed abundance along the coast of Nunivak Island, Yukon Delta National Wildlife Refuge, Alaska, 2010","interactions":[],"lastModifiedDate":"2022-09-26T15:51:47.675735","indexId":"ofr20201143","displayToPublicDate":"2022-09-23T13:19:03","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":"2020-1143","displayTitle":"Eelgrass (Zostera marina) and Seaweed Abundance Along the Coast of Nunivak Island, Yukon Delta National Wildlife Refuge, Alaska, 2010","title":"Eelgrass (Zostera marina) and seaweed abundance along the coast of Nunivak Island, Yukon Delta National Wildlife Refuge, Alaska, 2010","docAbstract":"Eelgrass (<em>Zostera marina</em>) is a highly productive seagrass that plays an essential role in the health of the estuarine and coastal ecosystems; however, information about its abundance and distribution is insufficient in the Bering Sea along the Yukon Delta National Wildlife Refuge. We inventoried the spatial extent and abundance of eelgrass and seaweed in Duchikthluk and Shoal bays on Nunivak Island in July 2010. Using Landsat Thematic Mapper imagery, we estimated the spatial extent of eelgrass to be 1,232 hectares in Duchikthluk Bay and 40 hectares in Shoal Bay. The overall accuracy of the assessments was high (86–87 percent) based on ground truthing using field reference points. We used point-sampling methodology to assess eelgrass abundance relative to the presence of associated seaweeds and selected macro-invertebrates within each of bays. Eelgrass was found at water depths ranging from 0.1 to 2.9 meters across both bays, but the greatest density (>75 percent cover) occurred primarily in moderate to deep water (0.7–1.4 meters) in Duchikthluk Bay and deeper water (>2 meters) in Shoal Bay. The mean aboveground biomass was 39.4±4.0 grams per meter squared in Duchikthluk Bay. The eelgrass biomass was greater (67.6±11.0 grams per meter squared) in Shoal Bay, but this estimate was based on a small sample size (n=3). Seaweeds, representing six species, occurred in low abundance across both bays and were primarily associated with eelgrass. Gastropods were the most common macro-invertebrate, occurring at 45 percent of field points in Duchikthluk Bay.
Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
A working group of experts with diverse professional backgrounds and disciplinary expertise was assembled to conceptualize a spatially explicit conservation design to support and inform the Sagebrush Conservation Strategy Part 2. The goal was to leverage recent advancements in remotely sensed landcover products to develop spatially and temporally explicit maps of sagebrush rangeland condition and landscape threats. In addition, the group sought to provide a common basis for understanding the state of sagebrush rangelands through time.
First, the study team developed a spatially explicit model to assess geographic patterns in sagebrush ecological integrity and used this model to identify core sagebrush areas (CSAs), growth opportunity areas (GOAs), and other rangeland areas (ORAs) across the biome. Among the identified rangelands, 33.4 million acres were classified as CSAs; 84.3 million acres as GOAs; and 127.2 million acres as ORAs as of 2020. Second, the team sought to demonstrate the ecological relevance of the identified CSAs and GOAs by comparing these data with independent datasets for sagebrush obligate species of conservation concern. Geographical patterns in sagebrush ecological integrity were strongly associated with the occurrence of high-priority species and also displayed clear links to population performance for greater sage-grouse. Third, the team parsed out the type, location, and acres of primary threats within the different categories (CSAs, GOAs, and ORAs) to help focus active management by identifying places where multiagency and organization efforts can protect CSAs and GOAs that have higher levels of integrity with lower cumulative threats. The assessment of the condition of the sagebrush biome (that is, the location, amount, and conservation status) indicated that complex ecosystem function problems are driving ~73 percent of the demonstrated threats within the CSAs and GOAs (rather than point-source problems, such as human development). Fourth, the team developed trend estimates for the identified CSAs and GOAs and three selected primary threats (invasive annual grasses, conifer encroachment, and human modification) to the sagebrush biome from 2001 to 2020. Results showed that an average of 1.3 million acres per year have transitioned to ORAs at an annual rate of −1.34 percent. Fifth, the team developed an approach to integrate climate change effects into the threat-based landscape conservation design and conducted an initial assessment on the magnitude of near-term climate effects in the context of observed historical trends. The team’s analysis suggests that climate change alone is unlikely to be the dominant threat to sagebrush ecological integrity in the next few decades, although interactions of climate with wildfire and invasive annual grasses may be an important threat, especially in the longer term.
A spatial overlap analysis was performed and highlighted 45.8 million acres of shared priorities among existing conservation frameworks to help anchor and guide collaborative landscape-scale conservation of areas that still have no to low threats. This information is critical to provide context for decisions about the volume and nature of conservation actions and funding requirements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221081","collaboration":"Prepared in cooperation with the Western Association of Fish and Wildlife Agencies and the U.S. Fish and Wildlife Service","usgsCitation":"Doherty, K., Theobald, D.M., Bradford, J.B., Wiechman, L.A., Bedrosian, G., Boyd, C.S., Cahill, M., Coates, P.S., Creutzburg, M.K., Crist, M.R., Finn, S.P., Kumar, A.V., Littlefield, C.E., Maestas, J.D., Prentice, K.L., Prochazka, B.G., Remington, T.E., Sparklin, W.D., Tull, J.C., Wurtzebach, Z., and Zeller, K.A., 2022, A sagebrush conservation design to proactively restore America’s sagebrush biome: U.S. Geological Survey Open-File Report 2022–1081, 38 p., https://doi.org/10.3133/ofr20221081.","productDescription":"Report: viii, 38 p.; Data Release; 3 Figures: 7.99 × 6.10 inches or smaller","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-138940","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":407103,"rank":5,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2022/1081/ofr20221081_fig10.pdf","text":"Figure 10, full size","size":"5.46 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Conifer 2020"},{"id":407104,"rank":6,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2022/1081/ofr20221081_fig11.pdf","text":"Figure 11, full size","size":"9.45 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Human Modification 2020"},{"id":407025,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2022/1081/ofr20221081_fig09.pdf","text":"Figure 9, full size","size":"5.57 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Invasive Annual Grass 2020"},{"id":407023,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1081/ofr20221081.pdf","text":"Report","size":"32.4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":407022,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1081/coverthb.jpg"},{"id":407024,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94Y5CDV","text":"USGS data release","linkHelpText":"Biome-wide sagebrush core habitat and growth areas estimated from a threat-based conservation design"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.6845703125,\n 33\n ],\n [\n -101.25,\n 33\n ],\n [\n -101.25,\n 49\n ],\n [\n -121.6845703125,\n 49\n ],\n [\n -121.6845703125,\n 33\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Sagebrush Ecosystem Specialist
Land Management Research Program
Ecosystems Mission Area
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526
Arctic marine ecosystems are undergoing rapid physical and biological change associated with climate warming and loss of sea ice. Sea ice loss will impact many species through altered spatial and temporal availability of resources. In the Bering and Chukchi Seas, the Pacific walrus Odobenus rosmarus divergens is one species that could be impacted by rapid environmental change, and thus, population assessments are needed to monitor changes in the status of this ecologically and culturally important marine mammal. We conducted a 5 yr genetic mark-recapture study to estimate demographic parameters for the Pacific walrus. We developed a Bayesian multievent mark-recapture model to estimate walrus survival and abundance while accounting for age misclassification. We estimated the probability of juvenile annual survival as 0.63 (95% credible interval [CrI]: 0.39-0.87) and adult female annual survival as 0.90 (95% CrI: 0.74-1.00). We estimated total abundance as 257 193 (95% CrI: 171 138-366 366). We provide the first estimate of total Pacific walrus abundance since an aerial survey in 2006, which generated a substantially less precise total population size estimate (129 000; 95% CI: 55 000-507 000). The emerging ecosystem state in the northern Bering and Chukchi Seas will likely result in a decline in Pacific walrus abundance, but there is substantial uncertainty regarding the magnitude of the anticipated decline. Our demographic estimates provide critical information to evaluate future population trends of this subsistence resource vital to communities that border the Bering and Chukchi Seas in the USA and Russia.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/meps14131","usgsCitation":"Beatty, W., Lemons, P., Everett, J.P., Lewis, C.J., Taylor, R.L., Lynn, R.J., Sethi, S.A., Quakenbush, L.T., Citta, J.J., Kissling, M., Kryukova, N., and Wennburg, J.K., 2022, Estimating Pacific walrus abundance and survival with multievent mark-recapture models: Marine Ecology Progress Series, v. 697, p. 167-182, https://doi.org/10.3354/meps14131.","productDescription":"16 p.","startPage":"167","endPage":"182","ipdsId":"IP-137159","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":473,"text":"New York Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":446361,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps14131","text":"Publisher Index Page"},{"id":407409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","state":"Alaska","otherGeospatial":"Bering Sea, Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -179.9,\n 60.413852350464914\n ],\n [\n -159.2578125,\n 60.413852350464914\n ],\n [\n -159.2578125,\n 74\n ],\n [\n -179.9,\n 74\n ],\n [\n -179.9,\n 60.413852350464914\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"697","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Beatty, William S. 0000-0003-0013-3113","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":224795,"corporation":false,"usgs":true,"family":"Beatty","given":"William S.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":853039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lemons, Patrick R.","contributorId":288791,"corporation":false,"usgs":false,"family":"Lemons","given":"Patrick R.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":853040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Everett, Jason P.","contributorId":296986,"corporation":false,"usgs":false,"family":"Everett","given":"Jason","email":"","middleInitial":"P.","affiliations":[{"id":64270,"text":"U.S. Fish and Wildlife Service, Conservation Genetics Laboratory, Anchorage, Alaska 99503","active":true,"usgs":false}],"preferred":false,"id":853041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lewis, Cara J.","contributorId":288794,"corporation":false,"usgs":false,"family":"Lewis","given":"Cara","email":"","middleInitial":"J.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":853042,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":853043,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lynn, Robert J.","contributorId":288795,"corporation":false,"usgs":false,"family":"Lynn","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":853044,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sethi, Suresh A. 0000-0002-0053-1827","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":296987,"corporation":false,"usgs":false,"family":"Sethi","given":"Suresh","email":"","middleInitial":"A.","affiliations":[{"id":64271,"text":"U.S. Geological Survey, New York Cooperative Fish and Wildlife Research Unit, Ithaca, New York 14853","active":true,"usgs":false}],"preferred":false,"id":853045,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Quakenbush, Lori T.","contributorId":192737,"corporation":false,"usgs":false,"family":"Quakenbush","given":"Lori","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":853046,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Citta, John J.","contributorId":175350,"corporation":false,"usgs":false,"family":"Citta","given":"John","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":853047,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kissling, Michelle","contributorId":222160,"corporation":false,"usgs":false,"family":"Kissling","given":"Michelle","affiliations":[{"id":40501,"text":"U.S. Fish and Wildlife Service, Marine Mammals Management, 3000 Vintage Blvd., Suite 201, Juneau, AK 99801","active":true,"usgs":false}],"preferred":false,"id":853048,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kryukova, Natalia","contributorId":296988,"corporation":false,"usgs":false,"family":"Kryukova","given":"Natalia","email":"","affiliations":[{"id":64272,"text":"Kamchatka Branch of the Pacific Geographical Institute of Far Eastern Branch of Russian Academy of Sciences, Petropavlovsk-Kamchatsky, Russia, 683000","active":true,"usgs":false}],"preferred":false,"id":853049,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wennburg, John K.","contributorId":296989,"corporation":false,"usgs":false,"family":"Wennburg","given":"John","email":"","middleInitial":"K.","affiliations":[{"id":64270,"text":"U.S. Fish and Wildlife Service, Conservation Genetics Laboratory, Anchorage, Alaska 99503","active":true,"usgs":false}],"preferred":false,"id":853050,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70248069,"text":"70248069 - 2022 - Multi-objective modeling as a decision-support tool for free-roaming horse management","interactions":[],"lastModifiedDate":"2023-09-05T15:08:53.279712","indexId":"70248069","displayToPublicDate":"2022-09-22T10:04:21","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1914,"text":"Human-Wildlife Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Multi-objective modeling as a decision-support tool for free-roaming horse management","docAbstract":"Decisions related to controversial problems in natural resource management receive the greatest support when they account for multiple objectives of stakeholders in a structured and transparent fashion. In the United States, management of free-roaming horses (Equus caballus; horses) is a controversial multiple-objective problem because disparate stakeholder groups have varying objectives and opinions about how to manage fast-growing horse populations in ways that sustain both natural ecosystems and healthy horses. Despite much decision-support research on management alternatives that prevent excessive population size or cost, horse management decisions still receive resistance from a variety of stakeholder groups, potentially because decisions fail to explicitly or transparently account for multiple objectives of diverse stakeholders. Here, we used a predictive model for horse populations to evaluate the degree to which alternative management strategies involving removals and fertility control treatment with the immunocontraceptive vaccine PZP-22 maximize 4 objectives in horse management: maximize ecosystem health, maximize horse health, minimize effects on horse behavior, and minimize management cost. We simulated scenarios varying in management action, frequency, magnitude, and starting population size over a 10-year interval and evaluated scenario performance with a weighted multiple-objective utility reward function. Management involving high-magnitude removals along with PZP-22 treatment generally outperformed other alternatives by achieving higher reward relative to alternatives in 2 scenario analyses. Simulation of 1,372 scenarios at 5 starting population sizes generally found that management with biannual removals and 2 doses of PZP-22 treatment for half of eligible females during years 1 and 5 generated the most rewarding outcomes. However, a removal scenario with more frequent PZP-22 application generated the greatest reward when starting population size was already within target population size range. Our paper demonstrates how values and objectives of diverse stakeholders can be used to support management decisions in ways that might lead to greater acceptance of decisions by a broad array of stakeholder groups.
","language":"English","publisher":"Utah State University","doi":"10.26077/a6e8-0759","usgsCitation":"Folt, B.P., Schoenecker, K., and Ekernas, L.S., 2022, Multi-objective modeling as a decision-support tool for free-roaming horse management: Human-Wildlife Interactions, v. 16, no. 2, p. 233-250, https://doi.org/10.26077/a6e8-0759.","productDescription":"18 p.","startPage":"233","endPage":"250","ipdsId":"IP-134038","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":435684,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HRF1H9","text":"USGS data release","linkHelpText":"Multi-objective Modeling as a Decision-support Tool for Feral Horse Management"},{"id":420482,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Folt, Brian Patrick 0000-0003-2278-2018","orcid":"https://orcid.org/0000-0003-2278-2018","contributorId":328937,"corporation":false,"usgs":true,"family":"Folt","given":"Brian","email":"","middleInitial":"Patrick","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":202531,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881744,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ekernas, L. Stefan 0000-0002-9205-1985","orcid":"https://orcid.org/0000-0002-9205-1985","contributorId":223034,"corporation":false,"usgs":true,"family":"Ekernas","given":"L.","email":"","middleInitial":"Stefan","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881745,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238505,"text":"70238505 - 2022 - Laysan albatross exhibit complex behavioral plasticity in the subtropical and subarctic North Pacific Ocean","interactions":[],"lastModifiedDate":"2022-11-28T13:39:00.114514","indexId":"70238505","displayToPublicDate":"2022-09-22T07:34:30","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Laysan albatross exhibit complex behavioral plasticity in the subtropical and subarctic North Pacific Ocean","docAbstract":"Animals that regularly traverse habitat extremes between the subtropics and subarctic are expected to exhibit foraging behaviors that respond to changes in dynamic ocean habitats, and these behaviors may facilitate adaptations to novel and changing climates. During the chick-provisioning stage, Laysan albatross Phoebastria immutabilis parents regularly undertake short- and long-distance foraging trips throughout the vast central North Pacific Ocean. We examined GPS tracking data among chick-provisioning albatrosses in Hawai‘i to characterize habitats during short- and long-distance trips. The study period encompassed a marine heatwave (2014) and the cooling period after an extreme El Niño event (2016), enabling us to examine foraging habitats under novel and changing climates. First passage time and generalized additive mixed models indicated that during 183 short and 110 long trips (n = 32 birds), wind-assisted flight efficiency, proximity to productive areas, and moonlit-searching were important in both subtropical and subarctic habitats. Laysan albatross took foraging trips that had similar lengths and durations in 2014 and 2016 and visited similar areas, indicating that their foraging range did not expand in response to climatic variability. A strategy that uses similar foraging areas across years combined with reliance on environmental processes that enhance flight efficiency (wind) and that enable searching behaviors (moonlight) indicate that Laysan albatross exhibit complex behavioral plasticity that allows them to utilize subtropical and subarctic habitats affected by dynamic climate variability. This strategy may benefit their ability to respond to oceanographic and climatic change, including expanding warm water regions and changing atmospheric conditions influenced by global warming.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/meps14148","usgsCitation":"Gilmour, M.E., Felis, J.J., Hester, M.M., Young, L.C., and Adams, J., 2022, Laysan albatross exhibit complex behavioral plasticity in the subtropical and subarctic North Pacific Ocean: Marine Ecology Progress Series, v. 697, p. 125-147, https://doi.org/10.3354/meps14148.","productDescription":"23 p.","startPage":"125","endPage":"147","ipdsId":"IP-137932","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":446368,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps14148","text":"Publisher Index Page"},{"id":409685,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Hawaii","otherGeospatial":"Pacific Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -179.9,\n 35.095301697524135\n ],\n [\n -177.86550682042343,\n 28.860574564487507\n ],\n [\n -155.53062317940885,\n 20.809565675106214\n ],\n [\n -147.22958348721264,\n 19.95935891124141\n ],\n [\n -134.00475959018274,\n 35.360858467785576\n ],\n [\n -136.90695297728425,\n 50.99805127330757\n ],\n [\n -142.66136789996617,\n 59.0913410074362\n ],\n [\n -147.22441346291703,\n 60.36962329343831\n ],\n [\n -154.7675208704121,\n 56.641133852727194\n ],\n [\n -176.45903611138576,\n 54.11395665374428\n ],\n [\n -178,\n 52.825004330008824\n ],\n [\n -179.9,\n 35.095301697524135\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"697","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gilmour, Morgan Elizabeth 0000-0002-2618-1095","orcid":"https://orcid.org/0000-0002-2618-1095","contributorId":289509,"corporation":false,"usgs":true,"family":"Gilmour","given":"Morgan","email":"","middleInitial":"Elizabeth","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Felis, Jonathan J. 0000-0002-0608-8950 jfelis@usgs.gov","orcid":"https://orcid.org/0000-0002-0608-8950","contributorId":4825,"corporation":false,"usgs":true,"family":"Felis","given":"Jonathan","email":"jfelis@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hester, Michelle M. 0000-0002-0769-5904","orcid":"https://orcid.org/0000-0002-0769-5904","contributorId":197785,"corporation":false,"usgs":false,"family":"Hester","given":"Michelle","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":857664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, Lindsay C.","contributorId":149044,"corporation":false,"usgs":false,"family":"Young","given":"Lindsay","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":857665,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Josh 0000-0003-3056-925X","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":213442,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857666,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70259620,"text":"70259620 - 2022 - The biogeography of relative abundance of soil fungi versus bacteria in surface topsoil","interactions":[],"lastModifiedDate":"2024-10-17T12:03:37.308351","indexId":"70259620","displayToPublicDate":"2022-09-22T06:55:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1426,"text":"Earth System Science Data","active":true,"publicationSubtype":{"id":10}},"title":"The biogeography of relative abundance of soil fungi versus bacteria in surface topsoil","docAbstract":"Fungi and bacteria are the two dominant groups of soil microbial communities worldwide. By controlling the turnover of soil organic matter, these organisms directly regulate the exchange of carbon between the soil and the atmosphere. Fundamental differences in the physiology and life history of bacteria and fungi suggest that variation in the biogeography of soil fungal and bacterial relative abundance could drive striking differences in carbon decomposition and soil organic matter formation across different biomes. However, a lack of global and predictive information on the distribution of these organisms in terrestrial 45 ecosystems has prevented the inclusion of soil fungal and bacterial relative abundance and the associated processes into global biogeochemical models. Here, we used a global scale dataset in the top soil surface (>3000 distinct observations of soil fungal and bacterial abundance) to generate the first quantitative and spatially high resolution (1km) explicit map of soil fungal proportion, defined as fungi/fungi + bacteria, across terrestrial ecosystems. We reveal striking latitudinal trends where fungal dominance increases in cold and high latitude environments with large soil carbon stocks. There was strong non-linear response of fungal 50 dominance to environmental gradient, i.e., mean annual temperature (MAT) and net primary productivity (NPP). Fungi and bacteria dominated in regions with low and high MAT and NPP, respectively, thus representing slow vs. fast soil energy channels, a concept with a long history in soil ecology. These high-resolution models provide the first steps towards representing the major soil microbial groups and their functional differences in global biogeochemical models to improve predictions of soil organic matter turnover under current and future climate scenarios","language":"English","publisher":"Earth System Science Data","doi":"10.5194/essd-14-4339-2022","usgsCitation":"Yu, K., Hoogen, J.V., Wang, Z., Averill, C., Routh, D., Smith, G.R., Drenovsky, R.E., Scow, K., Mo, F., Waldrop, M., Yang, Y., Tang, W., De Vries, F., Bardgett, R., Manning, P., Bastida, F., Baer, S.G., Bach, E., Garcia, C.J., Wang, Q., Ma, L., Chen, B., He, X., Teurlinex, S., Heijboer, A., Bradley, J.A., and Crowther, T.W., 2022, The biogeography of relative abundance of soil fungi versus bacteria in surface topsoil: Earth System Science Data, v. 14, p. 4339-4350, https://doi.org/10.5194/essd-14-4339-2022.","productDescription":"12 p,","startPage":"4339","endPage":"4350","ipdsId":"IP-116714","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467161,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/essd-14-4339-2022","text":"Publisher Index Page"},{"id":462936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2022-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Yu, Kailiang","contributorId":221398,"corporation":false,"usgs":false,"family":"Yu","given":"Kailiang","email":"","affiliations":[{"id":40362,"text":"Department of Environmental Sciences, University of Virginia, Charlottesville, VA 22904, USA","active":true,"usgs":false}],"preferred":false,"id":915995,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoogen, Johan van den","contributorId":345210,"corporation":false,"usgs":false,"family":"Hoogen","given":"Johan","email":"","middleInitial":"van den","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":915996,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Zhiqiang","contributorId":345211,"corporation":false,"usgs":false,"family":"Wang","given":"Zhiqiang","email":"","affiliations":[{"id":82525,"text":"Chengdu University","active":true,"usgs":false}],"preferred":false,"id":915997,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Averill, Colin","contributorId":245299,"corporation":false,"usgs":false,"family":"Averill","given":"Colin","email":"","affiliations":[],"preferred":false,"id":915998,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Routh, Devin","contributorId":345212,"corporation":false,"usgs":false,"family":"Routh","given":"Devin","email":"","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":915999,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Gabriel Reuben","contributorId":345213,"corporation":false,"usgs":false,"family":"Smith","given":"Gabriel","email":"","middleInitial":"Reuben","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":916000,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Drenovsky, Rebecca E.","contributorId":345214,"corporation":false,"usgs":false,"family":"Drenovsky","given":"Rebecca","email":"","middleInitial":"E.","affiliations":[{"id":27555,"text":"John Carroll University","active":true,"usgs":false}],"preferred":false,"id":916001,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Scow, Kate M.","contributorId":345215,"corporation":false,"usgs":false,"family":"Scow","given":"Kate M.","affiliations":[{"id":82527,"text":"U. California Davis","active":true,"usgs":false}],"preferred":false,"id":916002,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mo, Fei","contributorId":344978,"corporation":false,"usgs":false,"family":"Mo","given":"Fei","email":"","affiliations":[{"id":82451,"text":"College of Agronomy, Northwest A&F University, Yangling, Xianyang, Shaanxi, 712100, China;","active":true,"usgs":false}],"preferred":false,"id":916003,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Waldrop, Mark 0000-0003-1829-7140","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":216769,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":916004,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Yang, Yuanhe","contributorId":247646,"corporation":false,"usgs":false,"family":"Yang","given":"Yuanhe","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":916005,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Tang, Weize","contributorId":345216,"corporation":false,"usgs":false,"family":"Tang","given":"Weize","email":"","affiliations":[],"preferred":false,"id":916006,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"De Vries, Franciska","contributorId":345217,"corporation":false,"usgs":false,"family":"De Vries","given":"Franciska","affiliations":[{"id":37958,"text":"University of Amsterdam","active":true,"usgs":false}],"preferred":false,"id":916007,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bardgett, Richard D.","contributorId":266148,"corporation":false,"usgs":false,"family":"Bardgett","given":"Richard D.","affiliations":[{"id":54928,"text":"School of Earth and 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they play in reducing stormwater runoff volume by using hydrologic processes such as interception (rainfall intercepted by tree canopy), evapotranspiration (the transfer of water from vegetation into the atmosphere) and infiltration (percolation of rainwater into the Earth’s soil). Early research into the effects of trees on urban stormwater runoff used simple estimates based on assumptions of canopy coverage and design storm criteria. In a review of available literature on how capable urban trees are at reducing runoff, the Center for Watershed Protection (2017) found only six studies; three of them used measured data from a single plot, and the other three used models. When identifying gaps in research on the role of trees in stormwater management, Kuehler and others (2017) highlighted the need for studies that scale the local effects of urban trees to the larger sewershed catchment area, allowing a more holistic understanding of the urban tree canopy effects on hydrology.
For these reasons, the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, U.S. Forest Service, and the University of Wisconsin, quantified the effect of removing urban street trees and their canopy on stormwater generation in a medium-density residential area. Using a paired-catchment experimental design, rainfall-runoff relations were characterized in two medium-density residential catchments in Fond du Lac, Wisconsin, during May through September in 2018–20. Results of the study are detailed in Selbig and others (2022).
During the calibration phase, hydrograph metrics from paired runoff events were used to develop the relation between the control and test catchments with street trees in place. The ability to measure changes to the rainfall-runoff response after removal of tree canopy was made possible by an aggressive tree removal program by the city as a response to rapid infestation from the Agrilus planipennis (emerald ash borer). In March 2020, a total of 31 street trees were removed at the onset of the treatment period, resulting in a loss of 2,990 square meters of canopy over streets, driveways, sidewalks, and grassed areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223074","usgsCitation":"Selbig, W.R., Loheide, S.P., II, Shuster, W., Scharenbroch, B.C., Coville, R.C., Kruegler, J., Avery, W., Haefner, R., and Nowak, D., 2022, Loss of street tree canopy increases stormwater runoff: U.S. Geological Survey Fact Sheet 2022–3074, 4 p., https://doi.org/10.3133/fs20223074.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-141242","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":407081,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3074/fs20223074.XML"},{"id":407082,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3074/images"},{"id":407157,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20223074/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":407079,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3074/coverthb.jpg"},{"id":407080,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3074/fs20223074.pdf","text":"Report","size":"1.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022–3074"},{"id":501510,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113526.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wisconsin","city":"Fond du Lac","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.494873046875,\n 43.72148995228582\n ],\n [\n -88.37127685546875,\n 43.72148995228582\n ],\n [\n -88.37127685546875,\n 43.82065657651688\n ],\n [\n -88.494873046875,\n 43.82065657651688\n ],\n [\n -88.494873046875,\n 43.72148995228582\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
Barrier islands and their associated backbarrier environments protect mainland population centers and infrastructure from storm impacts, support biodiversity, and provide long-term carbon storage, among other ecosystem services. Despite their socio-economic and ecological importance, the response of coupled barrier-marsh-lagoon environments to sea-level rise is poorly understood. Undeveloped barrier-marsh-lagoon systems typically respond to sea-level rise through the process of landward migration, driven by storm overwash and landward mainland marsh expansion. Such response, however, can be affected by human development and engineering activities such as lagoon dredging and shoreline stabilization. To better understand the difference in the response between developed and undeveloped barrier-marsh-lagoon environments to sea-level rise, we perform a local morphologic analysis that describes the evolution of Long Beach Island (LBI), New Jersey, over the last 182 years. We find that between 1840 and 1934 the LBI system experienced landward migration of all five boundaries, including 171 meters of shoreline retreat. Between the 1920s and 1950s, however, there was a significant shift in system behavior that coincided with the onset of groin construction, which was enhanced by beach nourishment and lagoon dredging practices. From 1934 to 2022 the LBI system experienced ~22 meters of shoreline progradation and a rapid decline in marsh platform extent. Additionally, we extend a morphodynamic model to describe the evolution of the system in terms of five geomorphic boundaries: the ocean shoreline and backbarrier-marsh interface, the seaward and landward lagoon-marsh boundaries, and the landward limit of the inland marsh. We couple this numerical modeling effort with the map analysis during the undeveloped phase of LBI evolution, between 1840 and 1934. Despite its simplicity, the modeling framework can describe the average cross-shore evolution of the barrier-marsh-lagoon system during this period without accounting for human landscape modifications, supporting the premise that natural processes were the key drivers of morphological change. Overall, these results suggest that anthropogenic effects have played a major role in the evolution of LBI over the past century by altering overwash fluxes and marsh-lagoon geometry; this is likely the case for other barrier-marsh-lagoon environments around the world.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2022.958573","usgsCitation":"Tenebruso, C., Nichols-O’Neill, S., Lorenzo-Trueba, J., Ciarletta, D.J., and Miselis, J.L., 2022, Undeveloped and developed phases in the centennial evolution of a barrier-marsh-lagoon system: The case of Long Beach Island, New Jersey: Frontiers in Marine Science, v. 9, 958573, 15 p., https://doi.org/10.3389/fmars.2022.958573.","productDescription":"958573, 15 p.","ipdsId":"IP-141531","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446374,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2022.958573","text":"Publisher Index Page"},{"id":409230,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Long Beach island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.07802920592502,\n 39.74949430937235\n ],\n [\n -74.11619642132992,\n 39.76972910720298\n ],\n [\n -74.32809027237006,\n 39.48488546642025\n ],\n [\n -74.27149750470127,\n 39.46863133845025\n ],\n [\n -74.07802920592502,\n 39.74949430937235\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2022-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Tenebruso, Christopher","contributorId":297141,"corporation":false,"usgs":false,"family":"Tenebruso","given":"Christopher","email":"","affiliations":[{"id":36592,"text":"Montclair State University","active":true,"usgs":false}],"preferred":false,"id":853509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nichols-O’Neill, Shane","contributorId":297142,"corporation":false,"usgs":false,"family":"Nichols-O’Neill","given":"Shane","email":"","affiliations":[{"id":36592,"text":"Montclair State University","active":true,"usgs":false}],"preferred":false,"id":853510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorenzo-Trueba, Jorge","contributorId":297143,"corporation":false,"usgs":false,"family":"Lorenzo-Trueba","given":"Jorge","affiliations":[{"id":36592,"text":"Montclair State University","active":true,"usgs":false}],"preferred":false,"id":853511,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ciarletta, Daniel J. 0000-0002-8555-2239","orcid":"https://orcid.org/0000-0002-8555-2239","contributorId":256700,"corporation":false,"usgs":true,"family":"Ciarletta","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":853512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":853513,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237705,"text":"70237705 - 2022 - Conflict of energies: Spatially modeling mule deer caloric expenditure in response to oil and gas development","interactions":[],"lastModifiedDate":"2022-10-31T14:56:21.921244","indexId":"70237705","displayToPublicDate":"2022-09-21T08:23:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Conflict of energies: Spatially modeling mule deer caloric expenditure in response to oil and gas development","docAbstract":"Wildlife avoid human disturbances, including roads and development. Avoidance and displacement of wildlife into less suitable habitat due to human development can affect their energy expenditures and fitness. The heart rate and oxygen uptake of large mammals varies with both natural aspects of their habitat (terrain, climate, predators, etc.) and anthropogenic influence (noise, light, fragmentation, etc.). Although incorporating physiological analyses of energetics can inform the impacts of both development and conservation, management decisions rarely incorporate individuals’ energetic requirements when deciding on locations for potential development.
We aimed to estimate the change in expected energy expenditure, numerically and spatially, for mule deer to traverse a landscape with varying levels of oil and gas development through time.
Using calculations of energy expenditure of mule deer (Odocoileus hemionus) by weight, in relation to physical terrain components, plus avoidance factors for anthropogenic disturbance, we developed a spatiotemporal model of the minimum energy required for mule deer to traverse a landscape. We compared expected energy expenditure across 12 study sites with increasing levels of oil and gas development and over time in our study area, on the northern Colorado Plateau of Utah.
We found that energy expenditure can be increased by development, regardless of terrain, through increased travel distance associated with avoidance behavior. Maximum median energy expenditure to traverse a 1400 ha sample area rose from 1135 to 1935 kilocalories, a 70% increase in energy required of a mule deer. There was a significant relationship between energy expenditure and the size of oil and gas development (p < 0.001), its compactness (p < 0.05), and its ‘thinness’ (p < 0.001), but not terrain ruggedness (p = 0.25).
As the energy costs of movement correlate across multiple species of large mammals, our analysis of the energetic cost, for mule deer, associated with development can serve as a quantitative representative of the impacts of oil and gas development for multiple mammals—including threatened or endangered species. Our bioenergetic cost-distance model provides a means of delineating impediments to efficient movement and can be used to quantify the expected energetic costs of proposed future developments. As wildlife are exposed to increasing anthropogenic stressors which reduce fitness, it is important to make strategic siting decisions to reduce energetic costs imposed by human activities.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-022-01521-w","usgsCitation":"Chambers, S.N., Villarreal, M.L., Duane, O.J., Munson, S.M., Stuber, E.F., Tyree, G., Waller, E.K., and Duniway, M.C., 2022, Conflict of energies: Spatially modeling mule deer caloric expenditure in response to oil and gas development: Landscape Ecology, v. 37, p. 2947-2961, https://doi.org/10.1007/s10980-022-01521-w.","productDescription":"15 p.","startPage":"2947","endPage":"2961","ipdsId":"IP-138879","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":505527,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.usu.edu/wild_facpub/3277","text":"External Repository"},{"id":435685,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99JGAYG","text":"USGS data release","linkHelpText":"Maps of mule deer avoidance areas based on density of oil and gas developments, Book Cliffs, Utah"},{"id":408538,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"northern Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.753173828125,\n 38.77978137804918\n ],\n [\n -109.072265625,\n 38.77978137804918\n ],\n [\n -109.072265625,\n 40.49709237269567\n ],\n [\n -110.753173828125,\n 40.49709237269567\n ],\n [\n -110.753173828125,\n 38.77978137804918\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","noUsgsAuthors":false,"publicationDate":"2022-09-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Chambers, Samuel Norton 0000-0002-9840-7989","orcid":"https://orcid.org/0000-0002-9840-7989","contributorId":297110,"corporation":false,"usgs":true,"family":"Chambers","given":"Samuel","email":"","middleInitial":"Norton","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":855075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":855076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duane, Olivia Jane Marie","contributorId":298083,"corporation":false,"usgs":true,"family":"Duane","given":"Olivia","email":"","middleInitial":"Jane Marie","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":855077,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":855078,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stuber, Erica Francis 0000-0002-2687-6874","orcid":"https://orcid.org/0000-0002-2687-6874","contributorId":298084,"corporation":false,"usgs":true,"family":"Stuber","given":"Erica","email":"","middleInitial":"Francis","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":855079,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tyree, Gayle L","contributorId":298085,"corporation":false,"usgs":false,"family":"Tyree","given":"Gayle L","affiliations":[{"id":64492,"text":"Plant and Environmental Sciences Department, New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":855080,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waller, Eric K","contributorId":298087,"corporation":false,"usgs":false,"family":"Waller","given":"Eric","email":"","middleInitial":"K","affiliations":[{"id":64493,"text":"Independent USGS contractor","active":true,"usgs":false}],"preferred":false,"id":855081,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":855082,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70232986,"text":"70232986 - 2022 - Evolution of design ground motions in California: NEHRP 2009 to 2020","interactions":[],"lastModifiedDate":"2023-01-13T17:53:46.459843","indexId":"70232986","displayToPublicDate":"2022-09-20T11:51:31","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Evolution of design ground motions in California: NEHRP 2009 to 2020","docAbstract":"The U.S. Geological Survey (USGS) National Seismic Hazard Model (NSHM) is used in construction codes, such as the National Earthquake Hazard Reduction Program (NEHRP) Provisions, to develop ground motions for structural and geotechnical design. When the NSHM is updated (e.g. changes to its earthquake rupture forecast or ground motion models), or the manner in which it is implemented in construction codes changes, design ground motion values can increase or decrease at a given location. This study presents an analysis of 21 sites in California to characterize how design ground motion values (SS, S1, SMS, SM1) have changed from the 2009 to 2015 to 2020 NEHRP Provisions. Four sites are presented in greater detail: two in Southern California and two in Northern California. The results show that significant changes in design ground motion values between NEHRP releases are explained by major changes in the NSHM science (e.g., inclusion of basin effects) and its use (e.g., for a broader range of site classes), but in ways that are difficult to ascertain beforehand. It is therefore likely that design ground motion values may continue to evolve between NSHM and construction code updates as the earthquake science and engineering field's understanding continues to advance.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings from the 12th national conference on earthquake engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"Jun 27 - Jul 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Waldvogel, S.E., Makdisi, A.J., Peralta, K.S., Mason, H., Luco, N., and Rezaeian, S., 2022, Evolution of design ground motions in California: NEHRP 2009 to 2020, in Proceedings from the 12th national conference on earthquake engineering, Salt Lake City, UT, Jun 27 - Jul 1, 2022, 5 p.","productDescription":"5 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pipelines","interactions":[],"lastModifiedDate":"2023-01-13T17:49:18.224903","indexId":"70233183","displayToPublicDate":"2022-09-20T11:47:34","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A theoretical framework for integrating ground failure models into regional seismic performance assessments of buried pipelines","docAbstract":"A variety of models exist for characterizing earthquake-induced ground failures, but application of these models towards regional seismic performance assessments of buried pipelines remains challenging. One challenge is that ground failures often occur at localized geospatial scales while buried pipelines are spatially distributed over long distances. In this study, we propose a theoretical framework to integrate ground failure models into such assessments. We demonstrate a proof of concept via a numerical example with an illustrative gas transmission network in southern California subjected to ground shaking from the 1994 M6.7 Northridge earthquake.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings from the 12th national conference on earthquake engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"Jun 27 - Jul 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Kwong, N.S., and Jaiswal, K.S., 2022, A theoretical framework for integrating ground failure models into regional seismic performance assessments of buried pipelines, in Proceedings from the 12th national conference on earthquake engineering, Salt Lake City, UT, Jun 27 - Jul 1, 2022, 5 p.","productDescription":"5 p.","ipdsId":"IP-134606","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":411891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":403884,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://12ncee.org/program/proceedings","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kwong, N. 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Site-specific values of ϕSS at permanent seismic network stations were estimated during our previous work [1]. Here we first fit a model to ϕSS conditioned on the time-averaged shear wave velocity in the upper 30 m (VS30). We observe that stations on soft soil have larger average variability in site response than those on rock, especially at short periods. We use regression kriging to spatially interpolate ϕSS to an even grid spacing, using the VS30-scaling as the background model [2]. This improves on previous work that used ordinary kriging for interpolation [1]. We find that ϕSS ranges from about 0.1 to 0.4 natural log units in our study area, representing variations in site response at single locations of a factor of 1.1 up to a factor of 1.5. There is both greater variability and more coherency in the variability for short-period site response than for long periods. We recommend using these ϕSS models with the site response models of [1] for applications where quantification of variability is needed, such as probabilistic seismic hazard analyses.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings from the 12th national conference on earthquake engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"Jun 27 - Jul 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Parker, G.A., Baltay Sundstrom, A.S., and Thompson, E.M., 2022, Spatially continuous models of aleatory variability in seismic site response for southern California, in Proceedings from the 12th national conference on earthquake engineering, Salt Lake City, UT, Jun 27 - Jul 1, 2022, 5 p.","productDescription":"5 p.","ipdsId":"IP-134370","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":411890,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":411887,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://12ncee.org/program/proceedings"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117,\n 35\n ],\n [\n -119,\n 35\n ],\n [\n -119,\n 33\n ],\n [\n -117,\n 33\n ],\n [\n -117,\n 35\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Parker, Grace Alexandra 0000-0002-9445-2571","orcid":"https://orcid.org/0000-0002-9445-2571","contributorId":237091,"corporation":false,"usgs":true,"family":"Parker","given":"Grace","email":"","middleInitial":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":848815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baltay, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":848816,"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":848817,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70234408,"text":"70234408 - 2022 - Performance of NGA-East GMMs and site amplification models relative to CENA ground motions","interactions":[],"lastModifiedDate":"2023-01-13T17:37:46.927262","indexId":"70234408","displayToPublicDate":"2022-09-20T11:33:49","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Performance of NGA-East GMMs and site amplification models relative to CENA ground motions","docAbstract":"We investigate bias in ground motions predicted for Central and Eastern North America (CENA) using ground motion models (GMMs) combined with site amplification models developed in the NGA-East project. Bias is anticipated because of de-coupled procedures used in the development of the GMMs and site amplification models. The NGA-East GMMs were mainly calibrated by adjusting CENA data to a reference site condition using a site amplification model appropriate for active tectonic regions. Hence, these GMMs are likely biased relative to the CENA reference site condition (3000 m/sec shear wave velocity). Moreover, the NGA-East site amplification model recommended for hazard applications contains a simulation-based term for amplification between the reference condition and time-averaged shear wave velocity VS30=760 m/sec, which is uncertain and has not been calibrated against data from sites with that reference condition. Using the NGA-East dataset, we apply mixed-effects residual analysis and identify that period-dependent bias in 5% damped response spectral acceleration is present across a wide frequency range, but is strongest (i.e., overestimating by a factor of 2) at short oscillator periods <0.2 sec. Ongoing work to remedy this bias consists of expanding the NGA-East dataset with more recent recordings and enhanced metadata, particularly regarding site conditions.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings from the 12th national conference on earthquake engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"Jun 27 - Jul 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Ramos-Sepulveda, M.E., Parker, G.A., Li, M., Ilhan, O., Hashash, Y.M., Rathje, E., and Stewart, J.P., 2022, Performance of NGA-East GMMs and site amplification models relative to CENA ground motions, in Proceedings from the 12th national conference on earthquake engineering, Salt Lake City, UT, Jun 27 - Jul 1, 2022, 4 p.","productDescription":"4 p.","ipdsId":"IP-134994","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":411886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":411885,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://12ncee.org/program/proceedings"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ramos-Sepulveda, Maria E.","contributorId":294748,"corporation":false,"usgs":false,"family":"Ramos-Sepulveda","given":"Maria","email":"","middleInitial":"E.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":848818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parker, Grace Alexandra 0000-0002-9445-2571","orcid":"https://orcid.org/0000-0002-9445-2571","contributorId":237091,"corporation":false,"usgs":true,"family":"Parker","given":"Grace","email":"","middleInitial":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":848819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Meibai","contributorId":294749,"corporation":false,"usgs":false,"family":"Li","given":"Meibai","email":"","affiliations":[{"id":34217,"text":"UT Austin","active":true,"usgs":false}],"preferred":false,"id":848820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ilhan, Okan","contributorId":294751,"corporation":false,"usgs":false,"family":"Ilhan","given":"Okan","email":"","affiliations":[{"id":63637,"text":"Ankara Bildirim Beyazıt University, Turkey","active":true,"usgs":false}],"preferred":false,"id":848821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hashash, Youssef M. 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update","interactions":[],"lastModifiedDate":"2024-02-28T17:14:07.040659","indexId":"70243540","displayToPublicDate":"2022-09-20T11:11:11","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Earthquake scenario development in the 2023 USGS NSHM update","docAbstract":"Earthquake scenarios are generally selected to serve a wide variety of local and regional needs ranging from testing a community’s ability to respond to earthquakes to developing proactive targeted mitigation strategies for minimizing impending risk. These deterministic scenarios can also be used to communicate seismic hazard and risk to audiences who are not well versed in more complex methods like probabilistic seismic hazard assessment (PSHA). Accordingly, the U.S. Geological Survey plans to produce a suite of scenarios to accompany the release of the 2023 update to the National Seismic Hazard Model (NSHM). The manuscript describes a preliminary framework for scenario development from hazard and risk/consequence perspectives. Historical seismicity-, hazard-, and consequence-based scenario selection techniques as well as other factors in scenario selection are discussed. The 2023 NSHM scenario development efforts aim to incorporate both hazard and risk considerations while working in close collaboration with local experts and stakeholders.","conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"June 27-July 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Chase, R.E., Jaiswal, K.S., and Petersen, M.D., 2022, Earthquake scenario development in the 2023 USGS NSHM update, 12th National Conference on Earthquake Engineering, Salt Lake City, UT, June 27-July 1, 2022, 5 p.","productDescription":"5 p.","ipdsId":"IP-134741","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":426077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":416947,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.eeri.org/what-we-offer/digital-library/?lid=12862"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chase, Robert Edward 0000-0002-8155-6830","orcid":"https://orcid.org/0000-0002-8155-6830","contributorId":271198,"corporation":false,"usgs":true,"family":"Chase","given":"Robert","email":"","middleInitial":"Edward","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":872281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":872282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":872283,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70247437,"text":"70247437 - 2022 - Earthquake scenario selection for portfolio holders in CEUS: A case study with Oklahoma DOT","interactions":[],"lastModifiedDate":"2024-02-28T17:04:27.503045","indexId":"70247437","displayToPublicDate":"2022-09-20T10:55:56","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Earthquake scenario selection for portfolio holders in CEUS: A case study with Oklahoma DOT","docAbstract":"Portfolio managers of spatially distributed assets in the central and eastern United States (CEUS) and other low- to moderate seismic hazard regions require scenario-based seismic risk assessment for the purpose of emergency management and planning. Uncertainties regarding the long-term seismicity of the region, unknown faults, and limited historical records complicate the selection of an earthquake scenario. Through a case study with the Oklahoma Department of Transportation (ODOT) and their portfolio of bridges, we look at one such exercise, which consists of two scenario earthquakes: one scenario earthquake selected from the U.S. Geological Survey Building Seismic Safety Commission (BSSC) scenario catalog, a magnitude (M) 7.2 event on the Meers fault, and a second aftershock selected by the consequence-driven earthquake scenario selection (Co-DESS) method. The latter is driven by ODOT’s desired service actions to be included during the earthquake drill; in this case, we identify an earthquake that is likely to trigger inspections for bridges across multiple districts, thereby testing not only inspection protocols but also coordination efforts between district groups. We find that the Co-DESS selected event is smaller in magnitude and offers different geographical options than selection through conventional selection methods, while still meeting necessary consequences for an effective earthquake exercise.
","conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"June 27-July 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Lin, Y.C., Rotche, L.L., Lin, K., Thompson, E.M., Lallemant, D., Peters, W., and Wald, D.J., 2022, Earthquake scenario selection for portfolio holders in CEUS: A case study with Oklahoma DOT, 12th National Conference on Earthquake Engineering, Salt Lake City, UT, June 27-July 1, 2022, 5 p.","productDescription":"5 p.","ipdsId":"IP-134897","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":426076,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":419563,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.eeri.org/what-we-offer/digital-library/?lid=12848","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lin, Yolanda C 0000-0002-0423-4248","orcid":"https://orcid.org/0000-0002-0423-4248","contributorId":317878,"corporation":false,"usgs":false,"family":"Lin","given":"Yolanda","email":"","middleInitial":"C","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":879626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rotche, L. L.","contributorId":317880,"corporation":false,"usgs":false,"family":"Rotche","given":"L.","email":"","middleInitial":"L.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":879627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lin, Kuo-wan 0000-0002-7520-8151 klin@usgs.gov","orcid":"https://orcid.org/0000-0002-7520-8151","contributorId":1539,"corporation":false,"usgs":true,"family":"Lin","given":"Kuo-wan","email":"klin@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":879628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":879629,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lallemant, David 0000-0001-5759-9972","orcid":"https://orcid.org/0000-0001-5759-9972","contributorId":290680,"corporation":false,"usgs":false,"family":"Lallemant","given":"David","email":"","affiliations":[{"id":16631,"text":"Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":879630,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peters, W.","contributorId":334405,"corporation":false,"usgs":false,"family":"Peters","given":"W.","affiliations":[],"preferred":false,"id":879631,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":879632,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70236045,"text":"70236045 - 2022 - Implementation of basin models and sediment depth terms in the 2023 update of the U.S. National Seismic Hazard Model: Example from Reno, Nevada","interactions":[],"lastModifiedDate":"2023-01-13T16:57:17.889035","indexId":"70236045","displayToPublicDate":"2022-09-20T10:51:36","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Implementation of basin models and sediment depth terms in the 2023 update of the U.S. National Seismic Hazard Model: Example from Reno, Nevada","docAbstract":"We present a framework to evaluate the inclusion of candidate basin depth models in the U.S. Geological Survey National Seismic Hazard Model. We compute intensity measures (peak and spectral amplitudes) from uniformly processed earthquake ground motions in and around the basin of interest and compare these to ground-motion model (GMM) estimates over a range of oscillator periods. The GMMs use depth to specific shear-wave velocity isosurfaces (Zx) as a proxy for basin depth. We quantify whether the GMM estimates using Zx from the candidate basin depth model outperform the default estimates based on VS30 (the time-averaged shear wave velocity in the upper 30 m). We partition GMM residuals into event and site terms and compare site terms for stations within the basin to non-basin sites. We apply this framework to the greater Reno, Nevada, region, which has shallow basin depths (less than 450 m) and empirical amplifications of up to a factor of 2.2 at 1.0 s. There are no strong trends in site terms with basin depth, and the use of Zx values from the new candidate basin model shows marginal improvement of GMM total residuals compared to the default VS30-based model (the condition of no relative basin amplification).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings from the 12th national conference on earthquake engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"Jun 27 - Jul 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Ahdi, S.K., Moschetti, M.P., Aagaard, B.T., Abernathy, K., Boyd, O.S., and Stephenson, W.J., 2022, Implementation of basin models and sediment depth terms in the 2023 update of the U.S. National Seismic Hazard Model: Example from Reno, Nevada, in Proceedings from the 12th national conference on earthquake engineering, Salt Lake City, UT, Jun 27 - Jul 1, 2022, 5 p.","productDescription":"5 p.","ipdsId":"IP-140743","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":411876,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":411875,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://12ncee.org/program/proceedings","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Nevada","city":"Reno","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.93834598508883,\n 39.62289066656979\n ],\n [\n -119.93834598508883,\n 39.395646949350606\n ],\n [\n -119.63341035528262,\n 39.395646949350606\n ],\n [\n -119.63341035528262,\n 39.62289066656979\n ],\n [\n -119.93834598508883,\n 39.62289066656979\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ahdi, Sean Kamran 0000-0003-0274-5180","orcid":"https://orcid.org/0000-0003-0274-5180","contributorId":265143,"corporation":false,"usgs":true,"family":"Ahdi","given":"Sean","email":"","middleInitial":"Kamran","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":849795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":849796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aagaard, Brad T. 0000-0002-8795-9833 baagaard@usgs.gov","orcid":"https://orcid.org/0000-0002-8795-9833","contributorId":192869,"corporation":false,"usgs":true,"family":"Aagaard","given":"Brad","email":"baagaard@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":849797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abernathy, Kaitlyn 0000-0002-0360-8519","orcid":"https://orcid.org/0000-0002-0360-8519","contributorId":295721,"corporation":false,"usgs":true,"family":"Abernathy","given":"Kaitlyn","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":849798,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":849799,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stephenson, William J. 0000-0001-8699-0786 wstephens@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-0786","contributorId":695,"corporation":false,"usgs":true,"family":"Stephenson","given":"William","email":"wstephens@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":849800,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70237207,"text":"70237207 - 2022 - Wildlife population dynamics","interactions":[],"lastModifiedDate":"2022-10-05T15:43:52.58506","indexId":"70237207","displayToPublicDate":"2022-09-20T10:42:46","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7","title":"Wildlife population dynamics","docAbstract":"In this chapter we provide an overview of some core concepts, describe exponential growth as the basic foundation for understanding population dynamics, and discuss some of the factors that can affect wildlife population dynamics. We then show how management insights that can be gained from analyzing the dynamics of individual age or stage classes, examine dynamics of multiple populations across a landscape, consider key aspects of monitoring wildlife population dynamics, and close with a case study applying many of the topics in the chapter. Throughout we stress a few key themes: (1) variation is as important as the mean in understanding population dynamics (embrace uncertainty!); (2) some of the most powerful insights into outcomes of wildlife management actions are nonintuitive, revealed by applying data to models; and (3) because different management actions influence population dynamics in different ways, we must understand population processes to identify the most effective actions to meet population objectives.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Wildlife management and conservation: Contemporary principles and practices","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Johns Hopkins University Press","usgsCitation":"Mills, L.S., and Johnson, H.E., 2022, Wildlife population dynamics, chap. 7 of Wildlife management and conservation: Contemporary principles and practices, p. 107-135.","productDescription":"19 p.","startPage":"107","endPage":"135","ipdsId":"IP-125277","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":407965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Second Edition","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mills, L. Scott","contributorId":236757,"corporation":false,"usgs":false,"family":"Mills","given":"L.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":853630,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Heather E. 0000-0001-5392-7676 hejohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5392-7676","contributorId":205919,"corporation":false,"usgs":true,"family":"Johnson","given":"Heather","email":"hejohnson@usgs.gov","middleInitial":"E.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":853631,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70247518,"text":"70247518 - 2022 - Estimates of kappa in the San Francisco Bay area","interactions":[],"lastModifiedDate":"2024-02-28T17:01:28.359377","indexId":"70247518","displayToPublicDate":"2022-09-20T10:35:10","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Estimates of kappa in the San Francisco Bay area","docAbstract":"Site characterization is a critical component of seismic hazards studies, especially in the development and use of ground motion models (GMMs). One such parameter, kappa (Κ0), represents local site attenuation and effectively describes regional variations in ground motion [1]. However, estimates of Κ0 are limited. We estimate the site parameter Κ0 for 296 broadband and accelerometer stations in the San Francisco Bay area using 225 local events with M>3.5. We first invert for kappa on the high-frequency slope of every record at a station, which represents full attenuation effects [2]. We then perform weighted regression of kappa versus distance to obtain expected kappa at the site (Κ0). We find that Κ0 varies extensively in the San Francisco Bay area, with values ranging from 0.004-0.113 s, thus representing the heterogeneous geologic conditions in the region. Κ0 estimates from this study will be useful to consider in future seismic hazard analyses and ground motion studies in the Bay Area.
","conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"June 27-July 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Nye, T.A., Sahakian, V., King, E., Baltay Sundstrom, A.S., and Klimasewski, A., 2022, Estimates of kappa in the San Francisco Bay area, 12th National Conference on Earthquake Engineering, Salt Lake City, UT, June 27-July 1, 2022, 5 p.","productDescription":"5 p.","ipdsId":"IP-134906","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":419688,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.eeri.org/what-we-offer/digital-library/?lid=12757"},{"id":426075,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.09855510328197,\n 38.47318654986222\n ],\n [\n -123.09855510328197,\n 37.02839058004079\n ],\n [\n -121.42077907357066,\n 37.02839058004079\n ],\n [\n -121.42077907357066,\n 38.47318654986222\n ],\n [\n -123.09855510328197,\n 38.47318654986222\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nye, Tara A.","contributorId":318228,"corporation":false,"usgs":false,"family":"Nye","given":"Tara","email":"","middleInitial":"A.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":879969,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sahakian, Valerie J.","contributorId":208097,"corporation":false,"usgs":false,"family":"Sahakian","given":"Valerie J.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":879970,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"King, E.L.","contributorId":255058,"corporation":false,"usgs":false,"family":"King","given":"E.L.","affiliations":[{"id":51407,"text":"Geological Survey of Canada, Dartmouth, Canada","active":true,"usgs":false}],"preferred":false,"id":879971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baltay, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":879972,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Klimasewski, Alexis","contributorId":219664,"corporation":false,"usgs":false,"family":"Klimasewski","given":"Alexis","email":"","affiliations":[{"id":40043,"text":"U. Oregon","active":true,"usgs":false}],"preferred":false,"id":879973,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70262389,"text":"70262389 - 2022 - Growth of complex volcanic ash aggregates in the Tierra Blanca Joven eruption of Ilopango Caldera, El Salvador","interactions":[],"lastModifiedDate":"2025-01-16T16:36:13.021459","indexId":"70262389","displayToPublicDate":"2022-09-20T10:26:36","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Growth of complex volcanic ash aggregates in the Tierra Blanca Joven eruption of Ilopango Caldera, El Salvador","docAbstract":"Aggregation processes control both the residence time and dispersal of volcanic ash during eruptions yet remain incompletely understood. The products of aggregation vary from simple ash clusters to large, complexly layered accretionary lapilli. Here we detail the micro-stratigraphy of a single population of accretionary lapilli that grew during the ∼431 CE Tierra Blanca Joven eruption from Ilopango Caldera, El Salvador. The accretionary lapilli were sampled 10 km from the caldera source within a sequence of ash-rich pyroclastic density current deposits and intercalated fall material, known as unit D, which is traceable >40 km from Ilopango. Scanning electron microscopy and image analysis reveal common facies that form distinct layers within the accretionary lapilli. Each facies is distinguished by quantitative and qualitative variations in particle size distribution, porosity, and particle fabric. We infer that these textures resulted from aggregation conditions that differed in terms of liquid water availability, particle concentration and grain size distributions. In our proposed model, a characteristic sequence of facies accreted from core to rim in the accretionary lapilli during passage through ash clouds generated by vent-derived plumes and pyroclastic density currents. The accretionary lapilli are mostly composed of smaller aggregates (ash clusters, ash pellets) and grew predominantly by accretion of already-formed aggregates, rather than by grain-by-grain accretion of individual particles. This finding is consistent with observations of rapid aggregate growth in volcanic plumes, suggesting a common evolutionary pathway for accretionary lapilli formation across diverse eruptions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2022.107670","usgsCitation":"Hoult, H., Brown, R., Van Eaton, A.R., Hernandez, W., Dobson, K., and Woodward, B., 2022, Growth of complex volcanic ash aggregates in the Tierra Blanca Joven eruption of Ilopango Caldera, El Salvador: Journal of Volcanology and Geothermal Research, v. 431, 107670, 14 p., https://doi.org/10.1016/j.jvolgeores.2022.107670.","productDescription":"107670, 14 p.","ipdsId":"IP-130466","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467162,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dro.dur.ac.uk/37183/","text":"Publisher Index Page"},{"id":466640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"El Salvador","otherGeospatial":"Ilopango caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.5,\n 13.9\n ],\n [\n -89.5,\n 13.5\n ],\n [\n -88.9,\n 13.5\n ],\n [\n -88.9,\n 13.9\n ],\n [\n -89.5,\n 13.9\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"431","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hoult, Henry","contributorId":349109,"corporation":false,"usgs":false,"family":"Hoult","given":"Henry","affiliations":[{"id":68342,"text":"Durham University, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":924017,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Richard J.","contributorId":191216,"corporation":false,"usgs":false,"family":"Brown","given":"Richard J.","affiliations":[],"preferred":false,"id":924018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":924019,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hernandez, Walter","contributorId":218214,"corporation":false,"usgs":false,"family":"Hernandez","given":"Walter","email":"","affiliations":[{"id":39782,"text":"Ministerio de Medio Ambiente y Recursos Naturales, San Salvador, El Salvador","active":true,"usgs":false}],"preferred":false,"id":924020,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dobson, Katherine J","contributorId":349112,"corporation":false,"usgs":false,"family":"Dobson","given":"Katherine J","affiliations":[{"id":68342,"text":"Durham University, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":924021,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Woodward, Bryan","contributorId":349113,"corporation":false,"usgs":false,"family":"Woodward","given":"Bryan","affiliations":[{"id":68342,"text":"Durham University, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":924022,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70236917,"text":"70236917 - 2022 - Earthquake early warning: Toward modeling optimal protective actions","interactions":[],"lastModifiedDate":"2023-01-13T18:00:20.141967","indexId":"70236917","displayToPublicDate":"2022-09-20T10:16:43","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Earthquake early warning: Toward modeling optimal protective actions","docAbstract":"Over the past few years early earthquake warning systems have been incorporated into earthquake preparation efforts in many locations around the globe. These systems provide an excellent opportunity for advanced warning of ground shaking and other hazards associated with earthquakes. This study aims to optimize this advanced warning for individuals inside a building when the alert is received. A conceptual framework is presented for modeling optimal protective actions during earthquakes when an earthquake early warning system is available to the individual. Various factors impacting the ability of an individual to take protective action are considered for the modeling process.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings from the 12th national conference on earthquake engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"Jun 27 - Jul 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Wood, M., Zhang, X., Zhao, X., McBride, S., Luco, N., Baldwin, D., and Covas, T., 2022, Earthquake early warning: Toward modeling optimal protective actions, in Proceedings from the 12th national conference on earthquake engineering, Salt Lake City, UT, Jun 27 - Jul 1, 2022, 6 p.","productDescription":"6 p.","ipdsId":"IP-134821","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":411873,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":411872,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://12ncee.org/program/proceedings","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, M.","contributorId":300884,"corporation":false,"usgs":false,"family":"Wood","given":"M.","email":"","affiliations":[],"preferred":false,"id":861618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, X.","contributorId":30193,"corporation":false,"usgs":true,"family":"Zhang","given":"X.","email":"","affiliations":[],"preferred":false,"id":861619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhao, X.","contributorId":68486,"corporation":false,"usgs":true,"family":"Zhao","given":"X.","email":"","affiliations":[],"preferred":false,"id":861620,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McBride, Sara K. 0000-0002-8062-6542","orcid":"https://orcid.org/0000-0002-8062-6542","contributorId":206933,"corporation":false,"usgs":true,"family":"McBride","given":"Sara K.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":852700,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":852701,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baldwin, D.","contributorId":300876,"corporation":false,"usgs":false,"family":"Baldwin","given":"D.","email":"","affiliations":[],"preferred":false,"id":861621,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Covas, T.","contributorId":300885,"corporation":false,"usgs":false,"family":"Covas","given":"T.","email":"","affiliations":[],"preferred":false,"id":861622,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70248894,"text":"70248894 - 2022 - Integrated strategies for enhanced rapid earthquake shaking, ground failure, and impact estimation employing remotely sensed and ground truth constraints","interactions":[],"lastModifiedDate":"2023-09-25T14:45:00.964132","indexId":"70248894","displayToPublicDate":"2022-09-20T09:42:14","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Integrated strategies for enhanced rapid earthquake shaking, ground failure, and impact estimation employing remotely sensed and ground truth constraints","docAbstract":"Estimating earthquake impacts using physical or empirical models is challenging because the three components of loss estimation-shaking, exposure, and vulnerabilities-entail inherent uncertainties. Loss modeling in near-real-time adds additional uncertainties, yet expectations for actionable information with a reasonable level of confidence in the results are real. The modeling approaches described herein augment inherently uncertain prior hazard and loss models with an integrated strategy for updating these priors with ground-truth observations, thereby greatly reducing their uncertainties. Two strategies are employed. Early reports of casualties are used in a Bayesian updating fashion to constrain the possible range of fatalities and to lower the prior models' uncertainties. Additionally, remotely sensed satellite radar data, in the form of a Damage Proxy Map (or DPM), are used in a Bayesian causal graph framework combined with machine learning to optimize the mapping among the physical processes that cause shaking-based building damage, landslides, and liquefaction to prior expectation models. The casual graph framework also affords the potential for removing anthropogenetic noise contained in the imagery. Ultimately, our two-fold model updating strategy will accommodate key ground-truth observations such as fatality reports, locations of building damage, and ground failure reports to converge on actual losses more rapidly.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings from the 12th national conference on earthquake engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"June 27 - July 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","usgsCitation":"Wald, D.J., Xu, S., Noh, H., Dimasaka, J., Jaiswal, K.S., Allstadt, K.E., and Engler, D.T., 2022, Integrated strategies for enhanced rapid earthquake shaking, ground failure, and impact estimation employing remotely sensed and ground truth constraints, in Proceedings from the 12th national conference on earthquake engineering, Salt Lake City, UT, June 27 - July 1, 2022, 5 p.","productDescription":"5 p.","ipdsId":"IP-134859","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":421130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":421115,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://eeri.org/what-we-offer/digital-library/?lid=13294","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":884119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xu, Susu","contributorId":300127,"corporation":false,"usgs":false,"family":"Xu","given":"Susu","email":"","affiliations":[{"id":65025,"text":"Stony Brook University, NY, USA","active":true,"usgs":false}],"preferred":false,"id":884120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Noh, H.","contributorId":330155,"corporation":false,"usgs":false,"family":"Noh","given":"H.","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":884121,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dimasaka, J.","contributorId":330154,"corporation":false,"usgs":false,"family":"Dimasaka","given":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":884122,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":884123,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":884124,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":884125,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237183,"text":"70237183 - 2022 - Potential effects of environmental conditions on prairie dog flea development and implications for sylvatic plague epizootics","interactions":[],"lastModifiedDate":"2022-10-17T16:39:15.527088","indexId":"70237183","displayToPublicDate":"2022-09-20T08:31:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1443,"text":"EcoHealth","active":true,"publicationSubtype":{"id":10}},"title":"Potential effects of environmental conditions on prairie dog flea development and implications for sylvatic plague epizootics","docAbstract":"Fleas are common ectoparasites of vertebrates worldwide and vectors of many pathogens causing disease, such as sylvatic plague in prairie dog colonies. Development of fleas is regulated by environmental conditions, especially temperature and relative humidity. Development rates are typically slower at low temperatures and faster at high temperatures, which are bounded by lower and upper thresholds where development is reduced. Prairie dogs and their associated fleas (mostly Oropsylla spp) live in burrows that moderate outside environmental conditions, remaining cooler in summer and warmer in winter. We found burrow microclimates were characterized by stable daily temperatures and high relative humidity, with temperatures increasing from spring through summer. We previously showed temperature increases corresponded with increasing off-host flea abundance. To evaluate how changes in temperature could affect future prairie dog flea development and abundance, we used development rates of O. montana (a species related to prairie dog fleas), determined how prairie dog burrow microclimates are affected by ambient weather, and combined these results to develop a predictive model. Our model predicts burrow temperatures and flea development rates will increase during the twenty-first century, potentially leading to higher flea abundance and an increased probability of plague epizootics if Y. pestis is present.
","language":"English","publisher":"Springer","doi":"10.1007/s10393-022-01615-6","usgsCitation":"Samuel, M., Poje, J.E., Rocke, T.E., and Metzger, M.E., 2022, Potential effects of environmental conditions on prairie dog flea development and implications for sylvatic plague epizootics: EcoHealth, v. 19, p. 365-377, https://doi.org/10.1007/s10393-022-01615-6.","productDescription":"13 p.","startPage":"365","endPage":"377","ipdsId":"IP-136023","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":435688,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93TCY21","text":"USGS data release","linkHelpText":"Temperatures of black-tailed prairie dog burrows through the U.S. Great Plains"},{"id":407857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Colorado, Montana, New Mexico, North Dakota, South Dakota","otherGeospatial":"Buffalo Gap National Grassland, Bureau of Land Management land surrounding Roswell, Charles M. Russell National Wildlife Refuge, Lower Brule Sioux Reservation, Pueblo Chemical Depot, Theodore Roosevelt National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.841796875,\n 47.42437092240519\n ],\n [\n -106.09771728515625,\n 47.42437092240519\n ],\n [\n -106.09771728515625,\n 48.050545996347665\n ],\n [\n -107.841796875,\n 48.050545996347665\n ],\n [\n -107.841796875,\n 47.42437092240519\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.62579345703125,\n 46.84704298339386\n ],\n [\n -103.271484375,\n 46.84704298339386\n ],\n [\n -103.271484375,\n 47.0439255239614\n ],\n [\n -103.62579345703125,\n 47.0439255239614\n ],\n [\n -103.62579345703125,\n 46.84704298339386\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.48640441894531,\n 47.53806480221706\n ],\n [\n -103.23921203613281,\n 47.53806480221706\n ],\n [\n -103.23921203613281,\n 47.63717164223885\n ],\n [\n -103.48640441894531,\n 47.63717164223885\n ],\n [\n -103.48640441894531,\n 47.53806480221706\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.2440185546875,\n 43.014689161895184\n ],\n [\n -101.62078857421874,\n 43.014689161895184\n ],\n [\n -101.62078857421874,\n 44.01652134387754\n ],\n [\n -103.2440185546875,\n 44.01652134387754\n ],\n [\n -103.2440185546875,\n 43.014689161895184\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.118408203125,\n 43.99281450048989\n ],\n [\n -99.525146484375,\n 43.99281450048989\n ],\n [\n -99.525146484375,\n 44.31795304574349\n ],\n [\n -100.118408203125,\n 44.31795304574349\n ],\n [\n -100.118408203125,\n 43.99281450048989\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.41818237304688,\n 38.22307753495298\n ],\n [\n -104.2547607421875,\n 38.22307753495298\n ],\n [\n -104.2547607421875,\n 38.38795699631396\n ],\n [\n -104.41818237304688,\n 38.38795699631396\n ],\n [\n -104.41818237304688,\n 38.22307753495298\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.9139404296875,\n 32.974107959689235\n ],\n [\n -104.1119384765625,\n 32.974107959689235\n ],\n [\n -104.1119384765625,\n 33.696922692957685\n ],\n [\n -104.9139404296875,\n 33.696922692957685\n ],\n [\n -104.9139404296875,\n 32.974107959689235\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","noUsgsAuthors":false,"publicationDate":"2022-09-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Samuel, Michael D.","contributorId":206351,"corporation":false,"usgs":false,"family":"Samuel","given":"Michael D.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":853582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poje, Julia E.","contributorId":206595,"corporation":false,"usgs":false,"family":"Poje","given":"Julia","email":"","middleInitial":"E.","affiliations":[{"id":37348,"text":"Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin – Madison, Madison, WI, 53705","active":true,"usgs":false}],"preferred":false,"id":853583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":853584,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Metzger, Marco E.","contributorId":297166,"corporation":false,"usgs":false,"family":"Metzger","given":"Marco","email":"","middleInitial":"E.","affiliations":[{"id":64309,"text":"Vector-Borne Disease Section, California Department of Public Health, Ontario, California, 91764","active":true,"usgs":false}],"preferred":false,"id":853585,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70236827,"text":"sir20225087 - 2022 - Sixty years of channel adjustments to dams in the two segments of the Missouri National Recreational River, South Dakota and Nebraska","interactions":[],"lastModifiedDate":"2026-04-27T18:42:06.38109","indexId":"sir20225087","displayToPublicDate":"2022-09-20T06:44:21","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":"2022-5087","displayTitle":"Sixty Years of Channel Adjustments to Dams in the Two Segments of the Missouri National Recreational River, South Dakota and Nebraska","title":"Sixty years of channel adjustments to dams in the two segments of the Missouri National Recreational River, South Dakota and Nebraska","docAbstract":"The Missouri National Recreational River (MNRR) consists of two Missouri River segments managed by the National Park Service on the border of South Dakota and Nebraska. Both river segments are unchannelized and maintain much of their pre-dam channel form, but upstream dams have caused reductions in peak flow magnitudes and sediment supply. The 39-mile segment is located between Fort Randall and Gavins Point Dams, transitioning from a riverine process domain to a distributary delta process domain in the headwaters of Lewis and Clark Lake. The 59-mile segment, an entirely riverine process domain, is downstream from Gavins Point Dam, the most downstream main channel dam on the Missouri River, and upstream from a highly altered navigation channel extending more than 1,000 kilometers downstream to St. Louis, Missouri. The National Park Service seeks to preserve the outstandingly remarkable natural, cultural, and recreational values of the MNRR. There is a particular need to understand bank-erosion processes to guide management decisions related to bank-erosion controls.
Changes in channel shape, as measured in topographic cross sections surveyed every 5–10 years since the mid-20th century, document bed incision (bed-elevation lowering) in riverine process domains, a mix of aggradation and incision in the delta, and aggradation in Lewis and Clark Lake. Channel incision is greatest in the 59-mile segment, where mean thalweg (deepest point in a cross section) incision is 3.5 meters, and net incision in the thalweg greater than 5 meters was observed at a cross section 93 kilometers downstream from Gavins Point Dam. Analysis of topographic cross sections also indicates that rates of bed-elevation change since 1960 were lowest in the 39-mile river segment and in Lewis and Clark Lake. Rates of bed-elevation change were higher in the delta and 59-mile segments but lower in cross sections near Gavins Point Dam where the channel is confined by bank revetment on both banks and the bed has coarsened substantially since completion of the dam. Several large floods in recent decades, including a post-dam record flood event in 2011, scoured the bed and deposited large high-elevation sandbars in both river segments, especially in the 59-mile segment. Analysis of topographic cross-sections indicates the 2011 flood event caused substantial erosion and deposition, low magnitude net incision in the river segments and delta, and considerable sediment aggradation in the lake. Surveys taken after the 2011 flood in the 59-mile segment indicate a trend of sediment rearrangement and channel recovery following large floods, with the highest parts of the bed, sandbars, eroding and lowering while sediment was deposited on the deepest parts of the channel, which increased in elevation.
Inundation modeling results indicate that the narrower valley in the 39-mile segment results in a higher percentage of the flood plain being inundated by flooding relative to the 59-mile segment, which has a much wider valley. Likewise, bed incision in the 59-mile segment has increased channel capacity and resulted in a modern channel corridor inset into a higher flood-plain surface. The inset flood plain was inundated by the 2011 flood, but the pre-dam flood plain is rarely inundated. Analysis of channel boundaries over time indicates that pre-dam channel-migration rates were as much as five times larger than modern channel-migration rates in the 59-mile segment. Bank erosion in the 59-mile segment has primarily been into post-1894 channel deposits; bank-erosion rates are comparably very low in the 39-mile segment. Analysis of channel-migration zones indicates that most erosion is isolated to local hot spots and is used to establish predictions for 10 and 20 years into the future based on past movement rates in both MNRR segments. Long-term bed-elevation and planform trends indicate that rates of adjustment in the 59-mile segment are slowing and may be approaching a new equilibrium, but recent large floods and spatial variability contribute to considerable uncertainty. Additional monitoring of channel morphology would be needed to confirm trends observed in this analysis.
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U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201