Silicic volcanic eruptions range in style from gently effusive to highly explosive, and may switch style unpredictably during a single eruption. Direct observations of subaerial rhyolitic eruptions (Chaiten 2008, Cordón Caulle 2011–2012, Chile) challenged long-standing paradigms of explosive and effusive eruptive styles and led to the formulation of new models of hybrid activity. However, the processes that govern such hybrid explosive–effusive activity remain poorly understood. Here, we bring together observations of the well-studied 2011–2012 Cordón Caulle eruption with new textural and petrologic data on erupted products, and video and still imagery of the eruption. We infer that all of the activity – explosive, effusive, and hybrid – was fed by explosive fragmentation at depth, and that effusive behaviour arose from sticking and sintering, in the shallow vent region, of the clastic products of deeper, cryptic fragmentation. We use a scaling approach to determine that there is sufficient time available, during emplacement, for diffusive pyroclast degassing and sintering to produce a degassed plug that occludes the shallow conduit, feeding clastogenic, apparently effusive, lava-like deposits. Based on evidence from Cordón Caulle, and from other similar eruptions, we further argue that hybrid explosive–effusive activity is driven by episodic gas-fracking of the occluding lava plug, fed by the underlying pressurized ash- and pyroclast-laden region. The presence of a pressurized pocket of ash-laden gas within the conduit provides a mechanism for generation of harmonic tremor, and for syn-eruptive laccolith intrusion, both of which were features of the Cordón Caulle eruption. We conclude that the cryptic fragmentation models is more consistent with available evidence than the prevailing model for effusion of silicic lava that assume coherent non-fragmental rise of magma from depth to the surface without wholesale explosive fragmentation.
The increased risk of coastal flooding associated with climate-change driven sea level rise threatens to displace communities and cause substantial damage to infrastructure. Site-specific adaptation planning is necessary to mitigate the negative impacts of flooding on coastal residents and the built environment. Cost-benefit analyses used to evaluate coastal adaption strategies have traditionally focused on economic considerations, often overlooking potential demographic impacts that can directly influence vulnerability in coastal communities. Here, we present a transferable framework that couples hydrodynamic modeling of flooding driven by sea level rise and storm scenarios with site-specific building stock and census block-level demographic data. We assess the efficacy of multiple coastal adaptation strategies at reducing flooding, economic damages, and impacts to the local population. We apply this framework to evaluate a range of engineered, nature-based, and hybrid adaptation strategies for a portion of Santa Monica Bay, California. Overall, we find that dual approaches that provide protection along beaches using dunes or seawalls and along inlets using sluice gates perform best at reducing or eliminating flooding, damages, and population impacts. Adaptation strategies that include a sluice gate and partial or no protection along the beach are effective at reducing flooding around inlets but can exacerbate flooding elsewhere, leading to unintended impacts on residents. Our results also indicate trade-offs between economic and social risk-reduction priorities. The proposed framework allows for a comprehensive evaluation of coastal protection strategies across multiple objectives. Understanding how coastal adaptation strategies affect hydrodynamic, economic, and social factors at a local scale can enable more effective and equitable planning approaches.
Nest site selection has consequences for hatching success by mediating the temperature and moisture conditions that eggs experience during the incubation period. Understanding the potentially complex pathways by which nest placement influences these abiotic mediators, and therefore hatching success, is important for predicting which nests will be successful and which may require management action. We studied the effects of loggerhead sea turtle (Caretta caretta) nest site selection on hatching success by linking nest placement characteristics to hatching success through a structural equation model. We monitored 170 nests on Ossabaw Island, Georgia, during the summers of 2017 and 2018 and tracked nest conditions throughout the incubation period. Temperature had a complex effect on hatching success—nests had higher hatching rates if they were exposed to higher mean temperatures but also if they experienced both extremely high (>34°C) and extremely low (<26.5°C) temperatures, suggesting that temperature variability plays a role in determining nest outcomes beyond the mean temperature. Likewise, hatching success declined with a higher incidence of nests being inundated by tides. We found that nests placed at the highest elevations had the highest hatching success rates, likely because those nests had a much lower chance of being washed over by high tides and had higher mean temperatures. Nests were also more successful when placed in greater amounts of vegetation, again because vegetated nests were generally warmer and were associated with fewer washover events. These results shed light on the mechanisms behind selection for certain nest site characteristics and can guide the relocation of nests as a conservation action.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps14197","usgsCitation":"Whitesell, M., Hunter, E.A., Rostal, D., and Carroll, J., 2022, Direct and indirect pathways for environmental drivers of hatching success in the loggerhead sea turtle: Marine Ecology Progress Series, v. 701, p. 119-132, https://doi.org/10.3354/meps14197.","productDescription":"14 p.","startPage":"119","endPage":"132","ipdsId":"IP-139067","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481071,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.3354/meps14197","text":"External Repository"},{"id":480923,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Ossabaw Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.16544988349773,\n 31.87085846584084\n ],\n [\n -81.16544988349773,\n 31.71610084390467\n ],\n [\n -81.03274894641083,\n 31.71610084390467\n ],\n [\n -81.03274894641083,\n 31.87085846584084\n ],\n [\n -81.16544988349773,\n 31.87085846584084\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"701","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Whitesell, Mattie J.","contributorId":348695,"corporation":false,"usgs":false,"family":"Whitesell","given":"Mattie J.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":923704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rostal, David C.","contributorId":348698,"corporation":false,"usgs":false,"family":"Rostal","given":"David C.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":923706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carroll, John M.","contributorId":348701,"corporation":false,"usgs":false,"family":"Carroll","given":"John M.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":923707,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70256614,"text":"70256614 - 2022 - Natural resource system size can be used for managing recreational use","interactions":[],"lastModifiedDate":"2024-08-26T16:58:03.87962","indexId":"70256614","displayToPublicDate":"2022-11-23T11:52:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Natural resource system size can be used for managing recreational use","docAbstract":"Outdoor recreation provides societal benefits that are often measured by the amount of use natural resource systems receive. Still, the amount of resource use natural resource systems receive is often unknown or unstudied. Monitoring and quantifying resource use is often logistically difficult and costly but is paramount to optimize societal benefits. Identifying a simple and readily available metric that can indicate the quantity of recreational use of natural resource systems would benefit natural resource management. Using recreational angler participation data during an 11-year study period from 73 public waterbodies in Nebraska, USA, we developed a resource size-use model that demonstrates the ability of natural resource system size to indicate the quantity of recreational use they receive. We demonstrate how resource size-use models can estimate use for unsampled systems, produce broad-scale estimations of use, guide the allocation of resources, and predict how changes in resource system size may affect use. Resource size-use models provide opportunities to manage recreational use, which has been previously elusive for social-ecological systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.109711","usgsCitation":"Kane, D.S., Pope, K.L., Koupal, K.D., Pegg, M., Chizinski, C., and Kaemingk, M.A., 2022, Natural resource system size can be used for managing recreational use: Ecological Indicators, v. 145, 109711, 7 p., https://doi.org/10.1016/j.ecolind.2022.109711.","productDescription":"109711, 7 p.","ipdsId":"IP-136542","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445826,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2022.109711","text":"Publisher Index Page"},{"id":433163,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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kilometers from the epicenter. What remains unexplained is the large amplitude and intensity of some responses. Following the 2004 Mw 9.1 Sumatra earthquake, groundwater 3,200 km from the epicenter erupted violently from a well and formed a water fountain reaching a height exceeding 60 m. We model the relevant processes by combining tidal analysis of groundwater level with numerical simulations using a two-dimensional finite-element model. We suggest that the eruption resulted from a combination of factors, including a rapid increase of crustal permeability and runaway CO2 exsolution and bubble nucleation induced by the passage of seismic waves. Our results may have implications for some engineering applications such as oil production and CO2 sequestration, and the eruption of hydrothermal features such as geysers.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022GL101239","usgsCitation":"Yan, X., Shi, Z., Wang, C., Ingebritsen, S.E., and Manga, M., 2022, Violent groundwater eruption triggered by a distant earthquake: Geophysical Research Letters, v. 49, no. 23, e2022GL101239, 10 p., https://doi.org/10.1029/2022GL101239.","productDescription":"e2022GL101239, 10 p.","ipdsId":"IP-141694","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":445834,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022gl101239","text":"Publisher Index Page"},{"id":410471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 115.816667,\n 24.916667\n ],\n [\n 115.816667,\n 24.75\n ],\n [\n 116.033333,\n 24.75\n ],\n [\n 116.033333,\n 24.916667\n ],\n [\n 115.816667,\n 24.916667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"23","noUsgsAuthors":false,"publicationDate":"2022-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Yan, Xin","contributorId":299915,"corporation":false,"usgs":false,"family":"Yan","given":"Xin","email":"","affiliations":[],"preferred":false,"id":859007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shi, Zheming","contributorId":299913,"corporation":false,"usgs":false,"family":"Shi","given":"Zheming","email":"","affiliations":[{"id":64978,"text":"China University of Geosciences - Beijing","active":true,"usgs":false}],"preferred":false,"id":859008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Chi-Yuen","contributorId":131171,"corporation":false,"usgs":false,"family":"Wang","given":"Chi-Yuen","email":"","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. 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Establishment of invasive Burmese pythons (Python molurus bivittatus) in the Greater Everglades Ecosystem, Florida USA has led to local precipitous declines (> 90%) of mesomammal populations and is also a major threat to native populations of reptiles and birds. Efforts to control this species are ongoing but are hampered by the lack of access to and information on the expected biological patterns of pythons in southern Florida. We present data from more than 4,000 wild Burmese pythons that were removed in southern Florida over 26 years (1995–2021), the most robust dataset representing this invasive population to date. We used these data to characterize Burmese python size distribution, size at maturity, clutch size, and seasonal demographic and reproductive trends. We broadened the previously described size ranges by sex and, based on our newly defined size-stage classes, showed that males are smaller than females at sexual maturity, confirmed a positive correlation between maternal body size and potential clutch size, and developed predictive equations to facilitate demographic predictions. We also refined the annual breeding season (approx.100 days December into March), oviposition timing (May), and hatchling emergence and dispersal period (July through October) using correlations of capture morphometrics with observations of seasonal gonadal recrudescence (resurgence) and regression. Determination of reproductive output and timing can inform population models and help managers arrest population growth by targeting key aspects of python life history. These results define characteristics of the species in Florida and provide an enhanced understanding of the ecology and reproductive biology of Burmese pythons in their invasive Everglades range.
","language":"English","publisher":"Pensoft","doi":"10.3897/neobiota.78.93788","usgsCitation":"Currylow, A.F., Falk, B., Yackel Adams, A.A., Romagosa, C., Josimovich, J., Rochford, M., Cherkiss, M., Nafus, M., Hart, K., Mazzotti, F., Snow, R.W., and Reed, R., 2022, Size distribution and reproductive phenology of the invasive Burmese python (Python molurus bivittatus) in the Greater Everglades Ecosystem, Florida, USA: NeoBiota, v. 78, p. 129-158, https://doi.org/10.3897/neobiota.78.93788.","productDescription":"30 p.","startPage":"129","endPage":"158","ipdsId":"IP-144474","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":445837,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/neobiota.78.93788","text":"Publisher 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0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":220333,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":857550,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mazzotti, Frank J.","contributorId":12358,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12604,"text":"Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, 3205 College Avenue, University of Florida, Davie, FL 33314, USA","active":true,"usgs":false}],"preferred":false,"id":857551,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Snow, Ray W.","contributorId":76449,"corporation":false,"usgs":false,"family":"Snow","given":"Ray","email":"","middleInitial":"W.","affiliations":[{"id":13415,"text":"Everglades National Park","active":true,"usgs":false}],"preferred":false,"id":857552,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Reed, Robert 0000-0001-8349-6168","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":267796,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":857553,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70238560,"text":"70238560 - 2022 - A review of current capabilities and science gaps in water supply data, modeling, and trends for water availability assessments in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2022-11-29T13:18:15.018564","indexId":"70238560","displayToPublicDate":"2022-11-23T07:12:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"A review of current capabilities and science gaps in water supply data, modeling, and trends for water availability assessments in the Upper Colorado River Basin","docAbstract":"Over the past century, piñon and juniper trees have encroached into sagebrush steppe lands of the interior United States, and managers have for many years removed trees to stimulate the favored understory. While consistent understory response to tree removal in these semiarid lands suggests that trees outcompete other plants for water, no studies have linked increased soil water to understory response after tree removal. We tested the hypothesis that tree removal at six sagebrush steppe sites increased soil water, leading to increased understory plant cover. Using a structural equation model, we found that before tree removal, trees suppressed shrubs (standardized coefficient [SC] = −0.87), perennial deep-rooted (SC = −0.50) and shallow-rooted bunchgrasses (SC = −0.36), but had no influence on cheatgrass. The model explained between 2% (cheatgrass) and 40% (shrubs) of pretreatment cover variation. Measurement of the same plots six years post-treatment showed that most cover variation was due directly to plant growth, with standardized coefficients between 0.51 (perennial shallow-rooted grasses) and 0.72 (cheatgrass). Competition between cheatgrass and perennial deep-rooted grasses was evident, with perennials having twice the influence on cheatgrass than vice-versa (SC = −0.24 vs. −0.11). Spring soil water (wet-degree days) increased significantly after tree removal, measured as cumulative over 6 years (SC = 0.30), and in the early Spring of year six (SC = 0.16). Treatment-induced increase of cumulative Spring wet degree-days explained variation in shrub cover at year 6 (SC = 0.12) and the increase of early Spring wet degree-days at year 6 led to increases in perennial deep-rooted grasses (SC = 0.24) and cheatgrass (SC = 0.23). We detected no influence of Spring wet degree-days on perennial shallow-rooted grasses. The post-treatment model explained between 34% (shallow-rooted perennial grasses) and 69% (deep-rooted perennial grasses) of variation in understory cover. Most variation was explained by re-measurement of the same populations, followed by treatment effects mediated through increased soil water availability, soil factors, and direct effects of the treatment itself. In conclusion, our model is consistent with the a priori hypothesis that additional wet degree-days due to tree removal is a significant mechanism behind observed increases in understory cover.
Flat Creek, a tributary to the Snake River in northwestern Wyoming, is an important source of irrigation water, fish and wildlife habitat, and local recreation. Since 1996, a section of Flat Creek within the town of Jackson has failed to meet Wyoming Department of Environmental Quality’s surface-water-quality standards for total suspended solids and turbidity required by its State water-use classification. Wyoming Department of Environmental Quality water-quality standards prohibit increases of greater than 10 nephelometric turbidity units (NTU) because of human activities in streambodies of Wyoming. Sediment loading from urban stormwater runoff is hypothesized in previous publications to be the primary cause of impairment, but the relative fine sediment contributions from various sources have not been quantified.
In cooperation with the Teton Conservation District, the U.S. Geological Survey began a pilot study in the Flat Creek drainage basin to investigate the use of continuous turbidity measurements to predict suspended-sediment concentrations, loads, and sources through the town of Jackson, Wyoming. The predictions were based on turbidity measurements collected every 15 minutes during parts of water years 2019 and 2020. Analysis of differences in the more than 15,000 turbidity measurements coincident between upstream and downstream streamgages indicated that differences of 10 formazin nephelometric units (FNU) or greater composed about 1 percent of the total accepted measurements during the 2019 and 2020 measurement periods. The median difference in measured turbidity between coincident records at the upstream and downstream streamgages in 2019 was 0.20 FNU and the median difference in 2020 was 0.0 FNU.
Calculations of mean total sediment loads in Flat Creek during 2019 and 2020 indicate substantially more suspended-sediment was in Flat Creek below the town of Jackson than above town. Mean total calculated suspended-sediment loads at the upstream streamgage were 26 percent in 2019 and 21 percent in 2020 of the mean total suspended-sediment loads at the downstream streamgage. For measurements occurring at the same time (coincident), mean calculated suspended-sediment loads entering the town of Jackson from Flat Creek were 39 percent in 2019 and 35 percent in 2020 of those loads exiting town in Flat Creek. Incorporating statistical model uncertainty, mean differences between predicted suspended-sediment loads could potentially be zero. The annual period of operations of the South Park Supply Ditch, which diverts water into Flat Creek from the Gros Ventre River, constituted between 91 and 90 percent of the total calculated suspended-sediment load at the upstream streamgage, and between 88 and 87 percent of the loads at the downstream streamgage for coincident periods of record in 2019 and 2020, respectively. However, in the absence of simultaneous continuous monitoring and resulting measurements at the outlet of the South Park Supply Ditch, no robust method was available to quantify suspended-sediment loads from the ditch.
A moving average filter was used to identify and isolate short-duration (minutes to hours) spikes in turbidity at the downstream streamgage that were likely caused by overland flow and urban runoff. Suspended-sediment loads during urban runoff constituted about 8 and 10 percent of the total calculated suspended-sediment loads at the downstream streamgage (Flat Creek below Cache Creek, near Jackson, Wyoming; U.S. Geological Survey streamgage 13018350), and 6 and 4 percent of the loads calculated for the record coincident with the upstream streamgage in 2019 and 2020, respectively. Estimated suspended-sediment loads at the upstream streamgage during urban runoff events for the coincident period of record constitute 32 and 40 percent of the total estimated suspended-sediment loads at the downstream streamgage in 2019 and 2020, respectively, indicating sediment loads from urban runoff may contribute less than 10 percent, even as little as 5 percent, of the total sediment load exiting the town of Jackson on Flat Creek. Estimation of the proportion of suspended-sediment loads at the upstream site that originate from the South Park Supply Ditch or Cache Creek can only be done with assumptions but have the potential to be equivalent to or greater than calculated suspended-sediment loads associated with urban runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221103","collaboration":"Prepared in cooperation with the Teton Conservation District","programNote":"Water Mission Area","usgsCitation":"Alexander, J.S., Girard, C., Campbell, J., Ellison, C., Gosselin, E., and Smith, E., 2022, Using continuous measurements of turbidity to predict suspended-sediment concentrations, loads, and sources in Flat Creek through the town of Jackson, Wyoming, 2019−20 — A pilot study: U.S. Geological Survey Open-File Report 2022–1103, 29 p., https://doi.org/10.3133/ofr20221103.","productDescription":"Report: viii, 29 p.; Dataset","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-136294","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":409367,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":409366,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1103/images"},{"id":409364,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1103/ofr20221103.pdf","text":"Report","size":"2.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1103"},{"id":409365,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1103/ofr20221103.XML"},{"id":409363,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1103/coverthb.jpg"},{"id":501840,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113833.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","city":"Jackson","otherGeospatial":"Flat Creek drainage basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.72880406891166,\n 43.5011735765672\n ],\n [\n -110.8241704639435,\n 43.5011735765672\n ],\n [\n -110.8241704639435,\n 43.42146497765464\n ],\n [\n -110.72880406891166,\n 43.42146497765464\n ],\n [\n -110.72880406891166,\n 43.5011735765672\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Extensive drainage of peatlands in the southeastern United States coastal plain for the purposes of agriculture and timber harvesting has led to large releases of soil carbon as carbon dioxide (CO2) due to enhanced peat decomposition. Growth in mechanisms that provide financial incentives for reducing emissions from land use and land-use change could increase funding for hydrological restoration that reduces peat CO2 emissions from these ecosystems. Measuring soil respiration and physical drivers across a range of site characteristics and land use histories is valuable for understanding how CO2 emissions from peat decomposition may respond to raising water table levels. We combined measurements of total soil respiration, depth to water table from soil surface, and soil temperature from drained and restored peatlands at three locations in eastern North Carolina and one location in southeastern Virginia to investigate relationships among total soil respiration and physical drivers, and to develop models relating total soil respiration to parameters that can be easily measured and monitored in the field.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s13021-022-00219-5","usgsCitation":"Swails, E.E., Ardon, M., Krauss, K., Peralta, A., Emmanuel, R.E., Helton, A., Morse, J., Gutenberg, L., Cormier, N., Shoch, D., Settlemyer, S., Soderholm, E., Boutin, B.P., Peoples, C., and Ward, S., 2022, Response of soil respiration to changes in soil temperature and water table level in drained and restored peatlands of the southeastern United States: Carbon Balance and Management, v. 17, 18, 10 p., https://doi.org/10.1186/s13021-022-00219-5.","productDescription":"18, 10 p.","ipdsId":"IP-127982","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":445847,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13021-022-00219-5","text":"Publisher Index 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D.","contributorId":299545,"corporation":false,"usgs":false,"family":"Shoch","given":"D.","email":"","affiliations":[{"id":64873,"text":"TerraCarbon LLC, Illinois","active":true,"usgs":false}],"preferred":false,"id":858009,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Settlemyer, Scott","contributorId":299546,"corporation":false,"usgs":false,"family":"Settlemyer","given":"Scott","email":"","affiliations":[{"id":64873,"text":"TerraCarbon LLC, Illinois","active":true,"usgs":false}],"preferred":false,"id":858010,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Soderholm, Eric","contributorId":298011,"corporation":false,"usgs":false,"family":"Soderholm","given":"Eric","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":858011,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Boutin, Brian P.","contributorId":299547,"corporation":false,"usgs":false,"family":"Boutin","given":"Brian","email":"","middleInitial":"P.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":858012,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Peoples, Chuck","contributorId":299548,"corporation":false,"usgs":false,"family":"Peoples","given":"Chuck","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":858013,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Ward, Sara","contributorId":299549,"corporation":false,"usgs":false,"family":"Ward","given":"Sara","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":858014,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70238379,"text":"sim3499 - 2022 - Bathymetric map and surface area and capacity table for Table Rock Lake near Branson, Missouri, 2020","interactions":[],"lastModifiedDate":"2026-04-01T15:32:32.708876","indexId":"sim3499","displayToPublicDate":"2022-11-18T10:30:21","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3499","displayTitle":"Bathymetric Map and Surface Area and Capacity Table for Table Rock Lake near Branson, Missouri, 2020","title":"Bathymetric map and surface area and capacity table for Table Rock Lake near Branson, Missouri, 2020","docAbstract":"Table Rock Lake was completed in 1958 on the White River in southwestern Missouri and northwestern Arkansas for flood control, hydroelectric power, public water supply, and recreation. The surface area of Table Rock Lake is about 42,400 acres, and about 715 miles of shoreline are at the conservation pool level (915 feet above the North American Vertical Datum of 1988). Sedimentation in reservoirs can result in reduced water storage capacity and a reduction in usable aquatic habitat; therefore, accurate and up-to-date estimates of reservoir water capacity are important for managing pool levels, power generation, recreation, and downstream aquatic habitat. Many of the lakes operated by the U.S. Army Corps of Engineers are periodically surveyed to monitor bathymetric changes that affect water capacity. In October and November 2020, the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, completed one such survey of Table Rock Lake using a multibeam echosounder. The echosounder data were combined with U.S. Geological Survey 1/3 arc-second digital elevation model data and light detection and ranging (lidar) data, where present, to prepare a bathymetric map and a surface area and capacity table up to the flood pool elevation of 931 feet above the North American Vertical Datum of 1988.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3499","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Southwestern Division, Little Rock District","usgsCitation":"Huizinga, R.J., Rivers, B.C., and Richards, J.M., 2022, Bathymetric map and surface area and capacity table for Table Rock Lake near Branson, Missouri, 2020: U.S. Geological Survey Scientific Investigations Map 3499, 3 sheets, https://doi.org/10.3133/sim3499.","productDescription":"3 Sheets: 40.00 × 48.00 inches or smaller; Data Release","onlineOnly":"Y","ipdsId":"IP-137684","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501939,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113828.htm","linkFileType":{"id":5,"text":"html"}},{"id":409452,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sim3499/full","text":"Report"},{"id":409450,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FAFJZG","text":"USGS data release","linkHelpText":"Bathymetric and supporting data for Table Rock Lake near Branson, Missouri, 2020"},{"id":409449,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3499/images"},{"id":409448,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3499/sim3499.XML"},{"id":409447,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3499/sim3499_sheet03.pdf","text":"Sheet 3","size":"3.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3499 sheet 3"},{"id":409446,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3499/sim3499_sheet02.pdf","text":"Sheet 2","size":"3.13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3499 sheet 2"},{"id":409445,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3499/sim3499_sheet01.pdf","text":"Sheet 1","size":"4.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3499 sheet 1"},{"id":409444,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3499/coverthb.jpg"}],"country":"United States","state":"Missouri","city":"Branson","otherGeospatial":"Table Rock Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.46162698604762,\n 36.673080825378904\n ],\n [\n -93.46162698604762,\n 36.45192970827965\n ],\n [\n -93.25043226339268,\n 36.45192970827965\n ],\n [\n -93.25043226339268,\n 36.673080825378904\n ],\n [\n -93.46162698604762,\n 36.673080825378904\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Biological nitrogen fixation represents the largest natural flux of new nitrogen (N) into terrestrial ecosystems, providing a critical N source to support net primary productivity of both natural and agricultural systems. When they are common, symbiotic associations between plants and bacteria can add more than 100 kg N ha−1 y−1 to ecosystems. Yet, these associations are uncommon in many terrestrial ecosystems. In most cases, N inputs derive from more cryptic sources, including mutualistic and/or free-living microorganisms in soil, plant litter, decomposing roots and wood, lichens, insects, and mosses, among others. Unfortunately, large gaps remain in the understanding of cryptic N fixation. We conducted a literature review to explore rates, patterns, and controls of cryptic N fixation in both unmanaged and agricultural ecosystems. Our analysis indicates that, as is common with N fixation, rates are highly variable across most cryptic niches, with N inputs in any particular cryptic niche ranging from near zero to more than 20 kg ha−1 y−1. Such large variation underscores the need for more comprehensive measurements of N fixation by organisms not in symbiotic relationships with vascular plants in terrestrial ecosystems, as well as identifying the factors that govern cryptic N fixation rates. We highlight several challenges, opportunities, and priorities in this important research area, and we propose a conceptual model that posits an interacting hierarchy of biophysical and biogeochemical controls over N fixation that should generate valuable new hypotheses and research.
","language":"English","publisher":"Springer","doi":"10.1007/s10021-022-00804-2","usgsCitation":"Cleveland, C., Reis, C., Perakis, S.S., Dynarski, K.A., Batterman, S., Crews, T., Gei, M., Gundale, M.J., Menge, D., Peoples, M., Reed, S., Salmon, V., Soper, F.M., Taylor, B., Turner, M., and Wurzburger, N., 2022, Exploring the role of cryptic nitrogen fixers in terrestrial ecosystems: A frontier in nitrogen cycling research: Ecosystems, v. 25, p. 1653-1669, https://doi.org/10.1007/s10021-022-00804-2.","productDescription":"17 p.","startPage":"1653","endPage":"1669","ipdsId":"IP-123016","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":467145,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1899843","text":"External Repository"},{"id":410106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","noUsgsAuthors":false,"publicationDate":"2022-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Cleveland, Cory","contributorId":257259,"corporation":false,"usgs":false,"family":"Cleveland","given":"Cory","affiliations":[{"id":48908,"text":"U Montana","active":true,"usgs":false}],"preferred":false,"id":858329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reis, Carla R. G.","contributorId":240660,"corporation":false,"usgs":false,"family":"Reis","given":"Carla R. G.","affiliations":[{"id":48124,"text":"Center for Earth System Science, National Institute for Space Research (INPE), Av. dos Astronautas 1758, São José dos Campos, São Paulo 12227-010, Brazil","active":true,"usgs":false}],"preferred":false,"id":858330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":858331,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dynarski, Katherine A 0000-0001-5101-9666","orcid":"https://orcid.org/0000-0001-5101-9666","contributorId":225403,"corporation":false,"usgs":false,"family":"Dynarski","given":"Katherine","email":"","middleInitial":"A","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":858332,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Batterman, Sarah","contributorId":299670,"corporation":false,"usgs":false,"family":"Batterman","given":"Sarah","email":"","affiliations":[{"id":51995,"text":"Cary Inst","active":true,"usgs":false}],"preferred":false,"id":858333,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crews, Timothy","contributorId":299673,"corporation":false,"usgs":false,"family":"Crews","given":"Timothy","email":"","affiliations":[{"id":64924,"text":"The Land Institute","active":true,"usgs":false}],"preferred":false,"id":858334,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gei, Maga","contributorId":299674,"corporation":false,"usgs":false,"family":"Gei","given":"Maga","email":"","affiliations":[{"id":64927,"text":"Association for Tropical Biology and Conservation","active":true,"usgs":false}],"preferred":false,"id":858335,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gundale, Michael J.","contributorId":299675,"corporation":false,"usgs":false,"family":"Gundale","given":"Michael","middleInitial":"J.","affiliations":[{"id":64928,"text":"SLU","active":true,"usgs":false}],"preferred":false,"id":858336,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Menge, Duncan 0000-0003-4736-9844","orcid":"https://orcid.org/0000-0003-4736-9844","contributorId":241126,"corporation":false,"usgs":false,"family":"Menge","given":"Duncan","email":"","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":858337,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Peoples, Mark","contributorId":257258,"corporation":false,"usgs":false,"family":"Peoples","given":"Mark","email":"","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":858338,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":858339,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Salmon, Verity","contributorId":298812,"corporation":false,"usgs":false,"family":"Salmon","given":"Verity","email":"","affiliations":[],"preferred":false,"id":858340,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Soper, Fiona M.","contributorId":207085,"corporation":false,"usgs":false,"family":"Soper","given":"Fiona","email":"","middleInitial":"M.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":858341,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Taylor, Benton 0000-0002-9834-9192","orcid":"https://orcid.org/0000-0002-9834-9192","contributorId":245071,"corporation":false,"usgs":false,"family":"Taylor","given":"Benton","email":"","affiliations":[{"id":49081,"text":"Smithsonian Environmental Research Center, Edgewater, MD, 21037 USA","active":true,"usgs":false}],"preferred":false,"id":858342,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Turner, Monica","contributorId":193037,"corporation":false,"usgs":false,"family":"Turner","given":"Monica","affiliations":[],"preferred":false,"id":858343,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wurzburger, Nina","contributorId":299676,"corporation":false,"usgs":false,"family":"Wurzburger","given":"Nina","email":"","affiliations":[{"id":27235,"text":"U Georgia","active":true,"usgs":false}],"preferred":false,"id":858344,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70257255,"text":"70257255 - 2022 - Rainforest carnivore ecology in a managed forest reserve: Differential seasonal correlates between habitat components and relative abundance","interactions":[],"lastModifiedDate":"2024-08-14T12:04:58.815419","indexId":"70257255","displayToPublicDate":"2022-11-18T07:04:02","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Rainforest carnivore ecology in a managed forest reserve: Differential seasonal correlates between habitat components and relative abundance","docAbstract":"Studies of relationships between seasons and Neotropical carnivore distributions tend to focus on water and prey availability without considering other habitat components such as escape, foraging, and resting cover. Our goal was to evaluate habitat characteristics that may be important for predicting the seasonal (dry or rainy) relative abundance of four commonly captured Neotropical carnivores (i.e., jaguar [Panthera onca], puma [Puma concolor], ocelot [Leopardus pardalis], and grey fox [Urocyon cinereoargenteus]) in Chiquibul Forest Reserve in Belize, Central America. We used trail camera data and random-effect Poisson models to investigate how prey ratios (number of prey detections/total detections), cover (e.g., logs and stumps used for hiding cover from predators), vegetation structure, and environmental site characteristics (e.g., site harvest-history, slope, aspect) were related to carnivore relative abundance. Both prey ratios and vegetation structure appeared in supported models more frequently than other environmental site characteristics and were negatively correlated with carnivore relative abundance. Supported models differed for each season for all species except jaguars for which mammalian prey ratios and prey cover at sites was always negatively correlated with jaguar relative abundance. Carnivores appeared to avoid sites where vegetation created ideal escape and hiding cover for prey even though prey may be less abundant. Our data suggest that vegetation structure and composition can create conditions conducive to carnivore foraging and that these characteristics can differ by season in the tropics.
The 21–22 June 2019 eruption of Raikoke volcano, Russia, provided an opportunity to explore how spatial trends in volcanic lightning locations provide insights into pulsatory eruption dynamics. Using satellite-derived plume heights, we examine the development of lightning detected by Vaisala’s Global Lightning Dataset (GLD360) from eleven, closely spaced eruptive pulses. Results from one-dimensional plume modeling show that the eruptive pulses with maximum heights 9–16.5 km above sea level were capable of producing ice in the upper troposphere, which contributed variably to electrification and volcanic lightning. A key finding is that lightning locations not only followed the main dispersal direction of these ash plumes, but also tracked a lower-level cloud derived from pyroclastic density currents. We show a positive relationship between umbrella cloud expansion and the area over which lightning occurs (the ‘lightning footprint’). These observations suggest useful metrics to characterize ongoing eruptive activity in near real-time.
","language":"English","publisher":"Presses universitaires de Strasbourg","doi":"10.30909/vol.05.02.385395","usgsCitation":"Smith, C., Van Eaton, A.R., Schneider, D.J., Mastin, L.G., Matoza, R.S., McKee, K., and Maher, S., 2022, Spatial analysis of globally detected volcanic lightning from the June 2019 eruption of Raikoke volcano, Kuril Islands: Volcanica, v. 5, no. 2, p. 385-395, https://doi.org/10.30909/vol.05.02.385395.","productDescription":"11 p.","startPage":"385","endPage":"395","ipdsId":"IP-144250","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467146,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.30909/vol.05.02.385395","text":"Publisher Index Page"},{"id":466647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia","otherGeospatial":"Kuril Islands, Raikoke volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 153.22845752671452,\n 48.304580250458486\n ],\n [\n 153.22845752671452,\n 48.27759609075218\n ],\n [\n 153.27313900396035,\n 48.27759609075218\n ],\n [\n 153.27313900396035,\n 48.304580250458486\n ],\n [\n 153.22845752671452,\n 48.304580250458486\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Cassandra M.","contributorId":349097,"corporation":false,"usgs":false,"family":"Smith","given":"Cassandra M.","affiliations":[{"id":83431,"text":"NSF Postdoc, Alaska Volcano Observatory","active":true,"usgs":false}],"preferred":false,"id":924002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":924003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schneider, David J. 0000-0001-9092-1054 djschneider@usgs.gov","orcid":"https://orcid.org/0000-0001-9092-1054","contributorId":198601,"corporation":false,"usgs":true,"family":"Schneider","given":"David","email":"djschneider@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":924004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mastin, Larry G. 0000-0002-4795-1992","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":265985,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":924005,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Matoza, Robin S.","contributorId":257265,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","email":"","middleInitial":"S.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":924006,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McKee, Kathleen 0000-0003-3189-9189","orcid":"https://orcid.org/0000-0003-3189-9189","contributorId":265977,"corporation":false,"usgs":false,"family":"McKee","given":"Kathleen","email":"","affiliations":[{"id":54848,"text":"Earth and Planets Laboratory, Carnegie Institution for Science, Washington, DC, USA","active":true,"usgs":false}],"preferred":false,"id":924007,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maher, Sean","contributorId":265979,"corporation":false,"usgs":false,"family":"Maher","given":"Sean","affiliations":[{"id":54850,"text":"Department of Earth Science and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":924008,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70262035,"text":"70262035 - 2022 - Investigating impacts of small dams and dam removal on dissolved oxygen in streams","interactions":[],"lastModifiedDate":"2025-01-10T18:11:45.778127","indexId":"70262035","displayToPublicDate":"2022-11-17T10:54:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Investigating impacts of small dams and dam removal on dissolved oxygen in streams","docAbstract":"Small surface-release dams are prevalent across North American watersheds and can alter stream flow, thermal regimes, nutrient dynamics, and sediment transport. These dams are often implicated as a cause of negative water quality impacts—including reduced dissolved oxygen (DO)—and dam removal is increasingly employed to restore natural stream processes and improve DO. However, published impacts of small dams on DO vary widely across sites, and even less is known about the extent and timescale of DO recovery following removal. Therefore, we sought to quantify the effects of small dams and dam removal on DO and determine the dam, stream, and watershed characteristics driving inter-site variation in responses. We deployed continuous data loggers for 3 weeks during summer months in upstream (reference), impoundment, and downstream reaches at each of 15 dammed sites and collected equivalent data at 10 of those sites following dam removal. Prior to dam removal, most sites (60%) experienced a decrease in DO (an average of 1.15 mg/L lower) within the impoundment relative to upstream, but no consistent impacts on diel ranges or on downstream reaches. Before dam removal, 5 impacted stream reaches experienced minimum DO levels below acceptable water quality standards (<5 mg/L); after dam removal, 4 of 5 of these reaches met DO standards. Sites with wider impoundments relative to upstream widths and sites located in watersheds with more cultivated land experienced the greatest decreases in impoundment DO relative to upstream. Within one year following dam removal, impoundment DO recovered to upstream reference conditions at 80% of sites, with the magnitude of recovery strongly related to the magnitude of pre-removal impacts. These data suggest that broadly, small dams negatively affect stream DO, and the extent of effects are modulated by impoundment geometry and watershed characteristics. These results may help practitioners to prioritize restoration efforts at those sites where small dams are having outsized impacts, and therefore where the greatest water quality benefits may occur.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0277647","usgsCitation":"Abbott, K., Zaidel, P., Roy, A.H., Houle, K., and Nislow, K., 2022, Investigating impacts of small dams and dam removal on dissolved oxygen in streams: PLoS ONE, v. 17, no. 11, e0277647, 23 p., https://doi.org/10.1371/journal.pone.0277647.","productDescription":"e0277647, 23 p.","ipdsId":"IP-143494","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467147,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0277647","text":"Publisher Index Page"},{"id":466019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"17","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Abbott, Katherine M.","contributorId":347949,"corporation":false,"usgs":false,"family":"Abbott","given":"Katherine M.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":922764,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zaidel, Peter A.","contributorId":347950,"corporation":false,"usgs":false,"family":"Zaidel","given":"Peter A.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":922765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922766,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Houle, Kristopher M.","contributorId":347951,"corporation":false,"usgs":false,"family":"Houle","given":"Kristopher M.","affiliations":[{"id":83272,"text":"Massachusetts Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":922767,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nislow, Keith H.","contributorId":347953,"corporation":false,"usgs":false,"family":"Nislow","given":"Keith H.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":922768,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70230334,"text":"70230334 - 2022 - Preliminary national-scale seismic risk assessment of natural gas pipelines in the United States","interactions":[],"lastModifiedDate":"2023-05-16T21:05:04.159768","indexId":"70230334","displayToPublicDate":"2022-11-16T14:04:15","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Preliminary national-scale seismic risk assessment of natural gas pipelines in the United States","docAbstract":"Although the gas pipeline infrastructure in the United States is vulnerable to the seismic hazards of (i) strong ground shaking, and (ii) ground failures induced by surface faulting, liquefaction, or landslides, limited national guidance exists for operators to consistently evaluate the earthquake response of their pipelines. To provide additional information for stakeholders and establish more consistency at a national scale, we attempt to quantify seismic risk for gas transmission pipelines in the conterminous United States using a metric such as average annual loss, which helps readily distinguish geographic areas of high and low relative risk. Specifically, we integrate the 2018 National Pipeline Mapping System, the 2018 National Seismic Hazard Model, and several candidate models from the literature for estimating pipeline damage. Through this effort, we highlight major research needs for ultimately reducing the many uncertainties associated with a comprehensive seismic risk assessment of gas pipelines.
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Simon 0000-0003-3017-9585","orcid":"https://orcid.org/0000-0003-3017-9585","contributorId":241863,"corporation":false,"usgs":true,"family":"Kwong","given":"N.","email":"","middleInitial":"Simon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840006,"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":840007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baker, J. 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The typical AEL framework has been augmented with new replacement unit cost data and bridge-specific parameters for modifying default fragility curves. Earthquake hazard is defined using spectral acceleration hazard curves that account for location-specific soil conditions. Hazard is integrated with bridge-specific fragility curves to compute annual probabilities of exceeding various damage states. Further, economic loss for each bridge was estimated using the repair costs associated with specific damage states and indirect costs incurred from downtimes. Quantitative assessments of seismic risk, especially those that account for downtime-related impacts, enable us to illustrate the distribution of risk with respect to geographic region, era of construction, or type of bridge.
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Resident flycatchers were only found on two drainages in San Diego County, at San Dieguito and San Luis Rey Rivers, with 99 percent occurring on the San Luis Rey River. Resident flycatchers were detected at 18 percent of survey locations (Bonsall, Cleveland National Forest, Rey River Ranch, San Dieguito, and Vista Irrigation District [VID], and VID Lake Henshaw). Resident flycatchers were documented for the first time at Lake Henshaw, the only new location surveyed that supported flycatchers. We detected a minimum of 80 resident flycatchers from 2015 to 2019, most of these were upstream and downstream from Lake Henshaw. Transient flycatchers were found at 42 percent of survey locations; 38 transient individuals were detected at Agua Hedionda Creek, Otay River, San Diego River, San Dieguito River, and the San Luis Rey River.
Over the course of this study, 11 locations historically occupied by resident flycatchers were resurveyed; only 5 were found to have resident flycatchers: (1) Bonsall, (2) Cleveland National Forest, (3) Rey River Ranch, (4) San Dieguito, and (5) Vista Irrigation District. The number of resident flycatchers declined from previous high counts at all five locations. Collectively, the number of resident flycatcher territories within the historically occupied area of the upper San Luis Rey River downstream from Lake Henshaw (Cleveland National Forest, Rey River Ranch, and Vista Irrigation District) declined 71 percent between 1999 (48) and 2019 (14); 42 percent of the decline occurred between 1999 and 2016, with an additional decline (50 percent) occurring between 2016 and 2019. In 2016, the distribution of flycatcher territories at the historically occupied area of the upper San Luis Rey River changed relative to the distribution in 1999: the proportion of territories at Cleveland National Forest and Rey River Ranch decreased to 36 percent each, while Vista Irrigation District increased to 29 percent, creating a more equal distribution of territories across the historically occupied area. By 2019, the distribution changed relative to 2016, with most of the territories spread equally between Cleveland National Forest and Rey River Ranch (43 percent each), while the proportion of territories at Vista Irrigation District declined to 14 percent.
During countywide surveys, we documented the dispersal of two natal banded flycatchers; both were females that were originally banded as nestlings at Marine Corps Base Camp Pendleton and were seen for the first time as breeding adults. One of the females dispersed to San Dieguito, a distance of 41 kilometers, and a second female dispersed to Cleveland National Forest, a distance of 55 kilometers. We also documented the within-season movement of a uniquely banded male that was seen at the beginning of the 2017 breeding season at Bonsall and was later documented at San Dieguito, a movement distance of 31 kilometers.
We completed nest monitoring activities along the upper San Luis Rey River near Lake Henshaw in Santa Ysabel, California from 2016 to 2019. Monitoring occurred at three locations: (1) Cleveland National Forest, (2) Rey River Ranch, and (3) Vista Irrigation District, collectively the upper San Luis Rey River monitoring area. The number of flycatcher territories monitored each year ranged from 14 to 27. We observed polygynous pairings (one male paired with multiple females) in all years, with the lowest rate of polygyny (number of polygynous pairs/total number of pairs) observed in 2016 (10 percent) and the highest in 2017 (70 percent). The proportion of paired males that were polygynous ranged from 5 to 54 percent between 2016 and 2019.
We monitored the nesting activity of 14–27 pairs annually during the course of the study. Most of the first nesting attempts were initiated during late May and early June. We monitored 18–41 Southwestern Willow Flycatcher nests per year from 2016 to 2019. Apparent nest success ranged from 11 to 37 percent and differed significantly by year, with higher success in 2016 and 2017 compared to 2018 and 2019. Predation was the presumed to be the primary source of nest failure, with 63–84 percent of failures annually attributed to predation. Although none of the failures were attributed to Brown-headed cowbird (Molothrus ater) parasitism, 4–27 percent of nests were parasitized annually from 2016 to 2019, with increased parasitism rates observed in 2018 and 2019 compared to 2016 and 2017. We “rescued” 11 parasitized nests between 2016 and 2019 by removing cowbird eggs; if those nests had been allowed to fail, apparent nest success would have been up to 45 percent lower annually.
Flycatcher egg clutch size ranged from 2.8±0.8 to 3.1±0.8 annually and did not vary significantly between years. The number of fledglings per pair ranged from 0.5±1.0 to 1.6±1.5 annually from 2016 to 2019. There was a significant difference in the number of young fledged per pair between years, with pairs in 2016 producing more than three times the number of fledglings compared to 2019. The percent of pairs fledging at least one young ranged from 18 to 62 percent annually but did not vary significantly by year.
Analysis of flycatcher daily nest survival rates suggested that both early and late winter precipitation influenced nest survival, with increases in early winter precipitation positively influencing nest survival and later winter precipitation negatively influencing nest survival. The second-best supported model included year, with the lowest daily nest survival occurring in 2018 and 2019.
A total of 119 flycatchers were newly banded over the course of this study; 36 adult flycatchers were banded with a unique color combination, and 83 nestlings (57 of which survived to fledging) were banded with a single band on the left or right leg. In addition, two adults that were banded before 2015 were observed in the monitoring area. Between 2015 and 2019, we accumulated 94 resights of 49 individual color-banded adult flycatchers that ranged in age from 1 to 8 years old.
Banding allowed us to examine differences in annual survivorship among flycatchers of different ages and sexes. We estimated annual survivorship of adult males to be 69±7 percent, which is higher than estimates of female survivorship (45±10 percent). Annual survivorship of first-year flycatchers ranged from 24 to 41 percent, which is roughly half the estimates calculated for adult flycatchers (52–75 percent). We found no evidence that precipitation in the previous breeding year had an effect on flycatcher survival.
We were also able to observe dispersal and movement among adults and first-year flycatchers. Average first-year dispersal distance was 3.1±2.6 kilometers, with the longest dispersal (8.5 kilometers) by a natal female dispersing from the monitoring area to Lake Henshaw. Of the first-year flycatchers, 65 percent returned to the monitoring area to establish an adult breeding territory, while the remaining 35 percent dispersed to Lake Henshaw.
Territory fidelity among adult flycatchers was high with 69±13 percent of returning adults occupying the same territory (or within 100 meters) from the previous year. There was no significant difference in territory fidelity between males and females, or across years. Nesting success in the previous year appeared to be a strong driver of territory fidelity, with adults more likely to return to the same territory following years when they successfully fledged young. The average between-year movement for returning adult flycatchers was 0.5±0.8 km. We documented the movement of two adult males from the monitoring area to Lake Henshaw. Between-year movement distances did not differ by sex or year.
Resident flycatchers in the upper San Luis Rey River monitoring area used five habitat types from 2016 to 2019: (1) willow-oak, (2) willow-ash, (3) oak-sycamore, (4) mixed willow riparian, and (5) willow-sycamore, with willow-oak the most commonly used habitat type. The most commonly recorded dominant species at flycatcher territories included coast live oak (Quercus agrifolia), red or arroyo willow (Salix laevigata or Salix lasiolepis), California sycamore (Platanus racemosa), and velvet ash (Fraxinus velutina).
In 2018, we anecdotally began to observe dead and dying oaks in the monitoring area, which we believe to be the result of goldspotted oak borer (Agrilus auroguttatus) infestation. At the conclusion of this study, we investigated the overall change in normalized difference vegetation index (NDVI) in flycatcher territories within the monitoring area. The greatest negative change in NDVI occurred in territories closest to Lake Henshaw, and many of the affected territories were no longer occupied in the later years of the study.
Flycatchers used 13 plant species for nesting at the monitoring area from 2016 to 2019; 70 percent of all nests were placed in coast live oak. None of the nest characteristics including host height, nest height, distance to the edge of the host, or distance to the edge of the vegetation clump where the nest was placed differed between years. In 2016, successful nests were placed higher than unsuccessful nests; no other within-year differences were observed.
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Sacramento, California 95819
This study evaluates the economic impacts of a Mw7.0 Hayward fault scenario earthquake on the greater San Francisco Bay Region’s economy and the California economy as a whole using a detailed multiregional, static computable general equilibrium model. Economic impacts in terms of Gross Regional Product (GRP) losses caused by both capital stock (building and content) damages and water and electricity utilities, and telecommunications-service disruptions are estimated. The results indicate that the total losses are primarily caused by capital stock damages. In the 6 months following the earthquake, total GRP losses are estimated to be $44.2 billion (4.2 percent of California’s projected baseline GRP over the period), but this result could be reduced by about 43 percent to $25.3 billion after factoring in microeconomic resilience tactics. The GRP losses associated with lifeline service disruptions are estimated to be $1.4 billion, which can be reduced by over 85 percent when resilience tactics are implemented. The most effective tactics are the ability to make up lost production by people working overtime or extra shifts (production recapture), making greater use of processes that do not need disrupted goods or services (production isolation), and substituting for disrupted supplies and services (input substitution), though their impact varies across the various causal factors influencing GRP losses.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Lifelines 2022","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Lifelines 2022","conferenceDate":"Jan 31-Feb 11, 2022","conferenceLocation":"Virtual","language":"English","doi":"10.1061/9780784484449.046","usgsCitation":"Sue Wing, I., Wei, D., Rose, A., and Wein, A., 2022, Economic consequences of the HayWired earthquake scenario, in Lifelines 2022, Virtual, Jan 31-Feb 11, 2022, p. 523-533, https://doi.org/10.1061/9780784484449.046.","productDescription":"11 p.","startPage":"523","endPage":"533","ipdsId":"IP-132809","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":416239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.98386509807902,\n 38.40622823110516\n ],\n [\n -122.98386509807902,\n 36.891902309301216\n ],\n [\n -121.44288105987195,\n 36.891902309301216\n ],\n [\n -121.44288105987195,\n 38.40622823110516\n ],\n [\n -122.98386509807902,\n 38.40622823110516\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Sue Wing, Ian","contributorId":304246,"corporation":false,"usgs":false,"family":"Sue Wing","given":"Ian","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":869872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wei, Dan","contributorId":248873,"corporation":false,"usgs":false,"family":"Wei","given":"Dan","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":869873,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rose, Adam","contributorId":248874,"corporation":false,"usgs":false,"family":"Rose","given":"Adam","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":869874,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wein, Anne 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":589,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":869875,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248899,"text":"70248899 - 2022 - Applying consequence-driven scenario selection to lifelines","interactions":[],"lastModifiedDate":"2023-09-25T14:52:47.193278","indexId":"70248899","displayToPublicDate":"2022-11-16T09:47:33","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Applying consequence-driven scenario selection to lifelines","docAbstract":"We present a new consequence-driven framework for earthquake scenario selection. For emergency managers, utility operators, policy makers, and other stakeholders, a scenario-based seismic risk assessment is often necessary for the purpose of emergency management and planning. In developing a scientifically defensible scenario, stakeholders can simulate a realistic event in order to pre-identify vulnerabilities in the system and support action to address these vulnerabilities. Selecting scenarios is particularly challenging for important population centers and critical infrastructure in stable tectonic environments, such as in the central and eastern United States, where uncertain long-term seismicity and unknown faults offer inadequate constraints. Notably, significant events in these so-called stable regions do occur (e.g., Nahanni, Canada, 1985, M6.9; Tennant Creek, Australia, 1998, M6.7). In regions of low seismicity, even moderate events can be consequential due to the higher vulnerability of buildings typical of such regions when compared to regions of higher seismicity. Furthermore, communicating seismic risk to stakeholders and the general public in these regions can be especially challenging due to the complexities of characterizing the hazard level. This framework has been developed to address these challenges for scenario selection in low seismic hazard regions. In this new approach, the analysis begins instead with the explicit definition of a consequence of concern to the specific stakeholder. This can range from a definition of loss (in lives, dollars, or another metric of interest), or a performance metric for critical infrastructure. The framework leverages United States Geological Survey software to run the hazard and consequence analysis. Driven by this stakeholder-defined consequence, an inversion analysis generates a complete event set of candidate scenarios that could breach this consequence. The final selection of a scenario, or family of scenarios, is then scientifically informed, but not limited by our lack of constraints in characterizing the hazard.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Lifelines","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Lifelines 2022","conferenceDate":"January 31 - February 11, 2022","conferenceLocation":"Online","language":"English","publisher":"American Society of Civil Engineers","usgsCitation":"Lin, Y.C., Wald, D.J., Thompson, E.M., and Lallemant, D., 2022, Applying consequence-driven scenario selection to lifelines, in Lifelines, Online, January 31 - February 11, 2022, p. 411-422.","productDescription":"12 p.","startPage":"411","endPage":"422","ipdsId":"IP-130792","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":421131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":421117,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://ascelibrary.org/doi/abs/10.1061/9780784484449.036","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":884130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":884131,"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":884132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":884133,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70247864,"text":"70247864 - 2022 - Conduit processes in crystal-rich dacitic magma and implications for eruptive cycles at Guagua Pichincha volcano, Ecuador","interactions":[],"lastModifiedDate":"2023-08-22T12:13:20.9477","indexId":"70247864","displayToPublicDate":"2022-11-16T07:09:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Conduit processes in crystal-rich dacitic magma and implications for eruptive cycles at Guagua Pichincha volcano, Ecuador","docAbstract":"Stratovolcanoes are commonly characterised by cyclic eruptive activity marked by transitions between dome-forming, Vulcanian, Subplinian and Plinian eruptions. Guagua Pichincha volcano (Ecuador) has been a location of such cyclicity for the past ~ 2000 years, with Plinian eruptions in the first and tenth centuries AD (Anno Domini/after Christ), and CE (Common Era) 1660, which were separated by dome-forming to Subplinian eruptions, such as the recent 1999–2001 eruption. These cycles are therefore a prominent example of effusive-explosive transitions at varying timescales. Here, we investigate the reasons for such shifts in activity by focusing on degassing and outgassing processes within the conduit. We have coupled a petrophysical and textural analysis of dacites from the CE 1660 Plinian eruption and the 1999–2001 dome-forming/Vulcanian eruption, with different percolation models in order to better understand the role of degassing on eruptive style. We demonstrate that the transition from dome-forming to Plinian activity is correlated with differences in phenocryst content and consequently in bulk viscosity. A lower initial phenocryst content and viscosity is inferred for the Plinian case, which promotes faster ascent, closed-system degassing, fragmentation and explosive activity. In contrast, dome-forming phases are promoted by a higher magma viscosity due to higher phenocryst content, with slower ascent enhancing gas escape and microlite crystallization, decreasing explosivity and yielding effusive activity.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-022-01612-1","usgsCitation":"Colombier, M., Bernard, B., Wright, H.M., Le Pennec, J., Caceres, F., Cimarelli, C., Heap, M.J., Samaniego, P., Vasseur, J., and Dingwell, D.B., 2022, Conduit processes in crystal-rich dacitic magma and implications for eruptive cycles at Guagua Pichincha volcano, Ecuador: Bulletin of Volcanology, v. 84, 105, 23 p., https://doi.org/10.1007/s00445-022-01612-1.","productDescription":"105, 23 p.","ipdsId":"IP-143030","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":445864,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-022-01612-1","text":"Publisher Index Page"},{"id":420006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ecuador","otherGeospatial":"Guagua Pichincha volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.96144509158114,\n 0.9806815363857169\n ],\n [\n -77.96144509158114,\n 0.45944639801014375\n ],\n [\n -77.4628312552756,\n 0.45944639801014375\n ],\n [\n -77.4628312552756,\n 0.9806815363857169\n ],\n [\n -77.96144509158114,\n 0.9806815363857169\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"84","noUsgsAuthors":false,"publicationDate":"2022-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Colombier, Mathieu","contributorId":328620,"corporation":false,"usgs":false,"family":"Colombier","given":"Mathieu","email":"","affiliations":[{"id":78422,"text":"LMU Munich","active":true,"usgs":false}],"preferred":false,"id":880777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernard, Benjamin","contributorId":178529,"corporation":false,"usgs":false,"family":"Bernard","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":880778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wright, Heather M. 0000-0001-9013-507X hwright@usgs.gov","orcid":"https://orcid.org/0000-0001-9013-507X","contributorId":3949,"corporation":false,"usgs":true,"family":"Wright","given":"Heather","email":"hwright@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":880779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Le Pennec, Jean-Luc","contributorId":315394,"corporation":false,"usgs":false,"family":"Le Pennec","given":"Jean-Luc","affiliations":[{"id":68303,"text":"CNRS, France","active":true,"usgs":false}],"preferred":false,"id":880780,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caceres, Francisco","contributorId":328621,"corporation":false,"usgs":false,"family":"Caceres","given":"Francisco","email":"","affiliations":[{"id":78422,"text":"LMU Munich","active":true,"usgs":false}],"preferred":false,"id":880781,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cimarelli, Corrado","contributorId":257017,"corporation":false,"usgs":false,"family":"Cimarelli","given":"Corrado","affiliations":[{"id":47800,"text":"Ludwig Maximilian University of Munich","active":true,"usgs":false}],"preferred":false,"id":880782,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heap, Michael J. 0000-0002-4748-735X","orcid":"https://orcid.org/0000-0002-4748-735X","contributorId":297882,"corporation":false,"usgs":false,"family":"Heap","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":64429,"text":"Université de Strasbourg","active":true,"usgs":false}],"preferred":false,"id":880783,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Samaniego, Pablo","contributorId":205724,"corporation":false,"usgs":false,"family":"Samaniego","given":"Pablo","email":"","affiliations":[{"id":37157,"text":"Université Clermont Auvergne, CNRS, IRD, OPGC, Laboratoire Magmas et Volcans, F-63000 Clermont-Ferrand, France","active":true,"usgs":false}],"preferred":false,"id":880784,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vasseur, Jeremie","contributorId":315405,"corporation":false,"usgs":false,"family":"Vasseur","given":"Jeremie","email":"","affiliations":[{"id":36958,"text":"LMU Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":880785,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dingwell, Donald B.","contributorId":201841,"corporation":false,"usgs":false,"family":"Dingwell","given":"Donald","email":"","middleInitial":"B.","affiliations":[{"id":36273,"text":"Ludwig-Maximilians-Universität (LMU) München","active":true,"usgs":false}],"preferred":false,"id":880786,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70256623,"text":"70256623 - 2022 - Lithology and disturbance drive cavefish and cave crayfish occurrence in the Ozark Highlands ecoregion","interactions":[],"lastModifiedDate":"2024-08-27T15:10:10.350182","indexId":"70256623","displayToPublicDate":"2022-11-15T09:58:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Lithology and disturbance drive cavefish and cave crayfish occurrence in the Ozark Highlands ecoregion","docAbstract":"Diverse communities of groundwater-dwelling organisms (i.e., stygobionts) are important for human wellbeing; however, we lack an understanding of the factors driving their distributions, making it difficult to protect many at-risk species. Therefore, our study objective was to determine the landscape factors related to the occurrence of cavefishes and cave crayfishes in the Ozark Highlands ecoregion, USA. We sampled cavefishes and cave crayfishes at 61 sampling units using both visual and environmental DNA surveys. We then modeled occurrence probability in relation to lithology and human disturbance while accounting for imperfect detection. Our results indicated that occurrence probability of cave crayfishes was negatively associated with human disturbance, whereas there was a weak positive relationship between cavefish occurrence and disturbance. Both cavefishes and cave crayfishes were more likely to occur in limestone rather than dolostone lithology. Our results indicate structuring factors are related to the distribution of these taxa, but with human disturbance as a prevalent modifier of distributions for cave crayfishes. Limiting human alteration near karst features may be warranted to promote the persistence of some stygobionts. Moreover, our results indicate current sampling efforts are inadequate to detect cryptic species; therefore, expanding sampling may be needed to develop effective conservation actions.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-022-21791-3","usgsCitation":"Mouser, J., Brewer, S.K., Niemiller, M., Mollenhauer, R., and Van Den Bussche, R.A., 2022, Lithology and disturbance drive cavefish and cave crayfish occurrence in the Ozark Highlands ecoregion: Scientific Reports, v. 12, 19559, 10 p., https://doi.org/10.1038/s41598-022-21791-3.","productDescription":"19559, 10 p.","ipdsId":"IP-136389","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445870,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-022-21791-3","text":"Publisher Index Page"},{"id":433200,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.19813639078185,\n 36.971706993010315\n ],\n [\n -94.76416998727156,\n 36.88121743833784\n ],\n [\n -94.9821977429566,\n 36.432177796608784\n ],\n [\n -94.29247532353017,\n 36.292055756716266\n ],\n [\n -93.663549105208,\n 36.467590353199\n ],\n [\n -93.75579161722848,\n 36.98846283086834\n ],\n [\n -94.19813639078185,\n 36.971706993010315\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2022-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Mouser, Joshua B.","contributorId":341406,"corporation":false,"usgs":false,"family":"Mouser","given":"Joshua B.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":908362,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niemiller, Matthew L.","contributorId":341407,"corporation":false,"usgs":false,"family":"Niemiller","given":"Matthew L.","affiliations":[{"id":81735,"text":"The University of Alabama in Huntsville","active":true,"usgs":false}],"preferred":false,"id":908363,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mollenhauer, Robert","contributorId":341408,"corporation":false,"usgs":false,"family":"Mollenhauer","given":"Robert","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908364,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Den Bussche, Ronald A.","contributorId":341409,"corporation":false,"usgs":false,"family":"Van Den Bussche","given":"Ronald","email":"","middleInitial":"A.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908365,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70238326,"text":"70238326 - 2022 - Towards real-time probabilistic ash deposition forecasting for New Zealand","interactions":[],"lastModifiedDate":"2022-11-16T13:09:21.164087","indexId":"70238326","displayToPublicDate":"2022-11-14T07:07:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3841,"text":"Journal of Applied Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Towards real-time probabilistic ash deposition forecasting for New Zealand","docAbstract":"Volcanic ashfall forecasts are highly dependent on eruption source parameters (ESPs) and synoptic weather conditions at the time and location of the eruption. In New Zealand, MetService and GNS Science have been jointly developing an ashfall forecast system that incorporates four-dimensional high-resolution numerical weather prediction (NWP) and ESPs into the HYSPLIT model, a state-of-the art hybrid Eulerian and Lagrangian dispersion model widely used for volcanic ash. However, these forecasts are based on discrete ESPs combined with a deterministic weather forecast and thus provide no information on output uncertainty. This shortcoming hinders stakeholder decision making, particularly near the geographical margin of forecasted ashfall and in areas with large gradients in forecasted ash deposition. Our study presents a new approach that incorporates uncertainty from both eruptive and meteorological inputs to deliver uncertainty in the model output. To this end, we developed probability density functions (PDFs) for three key ESPs (plume height, mass eruption rate, eruption duration) tailored to New Zealand’s volcanoes and combine them with NWP ensemble datasets to generate probabilistic ashfall forecasts using the HYSPLIT model. We show that the Latin Hypercube Sampling (LHS) technique can be used to representatively span this four-dimensional parameter space and allow us to add uncertainty quantification to rapid response forecast systems. For a case study of a hypothetical eruption at Tongariro, New Zealand we suggest that large parts of New Zealand’s North Island would not receive adequate warning for potential ashfall if uncertainties were not included in the forecasts. We also propose new probabilistic summary products to support public information and emergency responders decision making.
Oceanic crust formed at mid-ocean ridges may be later modified by off-ridge magmatism forming seamounts, guyots, and islands. We investigate processes associated with seamount formation in the Gulf of Alaska Seamount Province using two coincident seismic reflection/wide-angle profiles. A north-south profile crosses the Kodiak-Bowie Seamount Chain and Aja fracture zone (FZ), and an orthogonal east-west profile is located about 90 km south of the seamount chain over Pacific plate oceanic crust. Structure along the profile away from the seamount chain is consistent with typical oceanic crust. Crust in our study region is thinnest (about 5.6 km) at the Aja FZ. Unlike observations from active transform faults, no low-velocity anomaly is observed at the Aja FZ suggesting that the crustal velocities have recovered to normal values through crack closure and crack healing. Higher lower crustal velocities (∼7.3 and > 7.5 km/s) and thicker crust (∼8.5 and ∼7.0 km) are observed near the Pratt and Durgin Seamounts and at the intersection of the Kodiak-Bowie Seamount Chain linear trend, respectively. These observations are attributed to magmatic underplating associated with seamount province magmatism. Lithospheric thickness variations across the Aja FZ may form a barrier or impediment to magmatic flow. The thickest crust (8.5 km) along our two profiles is located on the younger side of the FZ, and we suggest that the majority of magmatism jumped south of the Aja FZ when thinner lithosphere was encountered by the Bowie hot spot. The crustal structure near the Kodiak-Bowie Seamount Chain is most similar to that of other seamounts and guyots that formed on similarly young lithosphere (8–12 Ma). Our results suggest that lithospheric thickness at the time of hot spot interaction has a large control on magmatic underplating at seamounts and seamount provinces.
Subduction zone accretionary prisms are commonly modeled as elastic structures where permanent deformation is accommodated by faulting and folding of otherwise elastic materials, yet accretionary prisms may exhibit other deformation styles over relatively short time scales. In this study, we use 6.5-year (2014–2021) Sentinel-1 interferometric synthetic aperture radar (InSAR) time-series of post-seismic deformation in the Makran accretionary prism of southeast Pakistan to characterize non-linear viscoelastic deformation within an active accretionary prism on short timescales (months to years). We constructed a series of 3-D finite-element models of the Makran subduction zone, including an accretionary prism, and constrained the elastic thickness of the upper wedge and the flow-law parameters (power-law exponent, activation enthalpy, and pre-exponential constant) of the lower wedge through forward model fits to the InSAR time-series. Our results show that the prism is elastically thin (8–12 km) and the non-linear viscoelastic relaxation of the deep portions of the prism alone can sufficiently explain the post-seismic surface deformation. Our best fitting flow-law parameters (n = 3.76 ± 0.39, Q = 82.2 ± 37.73 kJ mol−1, and A = 10−3.36±4.69) are consistent with triggering of low temperature dislocation creep within fluid-saturated siliciclastic rocks. We believe that the fluids necessary for this weakening originate from sedimentary underplating and/or the presence the hydrocarbons. The presence of power-law rheology within the lower wedge impacts the estimated plate coupling and the stress state in the subduction system, with respect to the conventional elastic wedge model, and hence should to be considered in future earthquake cycle models.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JB024493","usgsCitation":"Cheng, G., Barnhart, W.D., and Li, S., 2022, Power-law viscoelastic flow of the lower accretionary prism in the Makran subduction zone following the 2013 Baluchistan Earthquake: JGR Solid Earth, v. 127, no. 11, e2022JB024493, 17 p., https://doi.org/10.1029/2022JB024493.","productDescription":"e2022JB024493, 17 p.","ipdsId":"IP-139827","costCenters":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"links":[{"id":502088,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jb024493","text":"Publisher Index Page"},{"id":502012,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iran. Pakistan","otherGeospatial":"Makran accretionary prism","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 57.41648936499405,\n 30.69926527865796\n ],\n [\n 57.41648936499405,\n 24.018536636005464\n ],\n [\n 67.65925595369796,\n 24.018536636005464\n ],\n [\n 67.65925595369796,\n 30.69926527865796\n ],\n [\n 57.41648936499405,\n 30.69926527865796\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"127","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Cheng, Guo","contributorId":369215,"corporation":false,"usgs":false,"family":"Cheng","given":"Guo","affiliations":[],"preferred":false,"id":958498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnhart, William D. 0000-0003-0498-1697 wbarnhart@usgs.gov","orcid":"https://orcid.org/0000-0003-0498-1697","contributorId":294678,"corporation":false,"usgs":true,"family":"Barnhart","given":"William","email":"wbarnhart@usgs.gov","middleInitial":"D.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":958499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Shaoyang","contributorId":207597,"corporation":false,"usgs":false,"family":"Li","given":"Shaoyang","email":"","affiliations":[],"preferred":false,"id":958500,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}