Spatial capture‐recapture (SCR) has emerged as the industry standard for estimating population density by leveraging information from spatial locations of repeat encounters of individuals. The precision of density estimates depends fundamentally on the number and spatial configuration of traps. Despite this knowledge, existing sampling design recommendations are heuristic and their performance remains untested for most practical applications. To address this issue, we propose a genetic algorithm that minimizes any sensible, criteria‐based objective function to produce near‐optimal sampling designs. To motivate the idea of optimality, we compare the performance of designs optimized using three model‐based criteria related to the probability of capture. We use simulation to show that these designs out‐perform those based on existing recommendations in terms of bias, precision, and accuracy in the estimation of population size. Our approach, available as a function in the R package oSCR, allows conservation practitioners and researchers to generate customized and improved sampling designs for wildlife monitoring.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3262","usgsCitation":"Dupont, G., Royle, J.A., Nawaz, M., and Sutherland, C., 2021, Optimal sampling design for spatial capture‐recapture: Ecology, v. 102, no. 3, e03262, https://doi.org/10.1002/ecy.3262.","productDescription":"e03262","ipdsId":"IP-118217","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":454202,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecy.3262","text":"External Repository"},{"id":380979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"102","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Dupont, Gates","contributorId":245387,"corporation":false,"usgs":false,"family":"Dupont","given":"Gates","email":"","affiliations":[{"id":49179,"text":"University of Massachusetts-Amherst","active":true,"usgs":false}],"preferred":false,"id":806101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":806102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nawaz, Muhammad Ali","contributorId":245388,"corporation":false,"usgs":false,"family":"Nawaz","given":"Muhammad Ali","affiliations":[{"id":49180,"text":"Snow Leopard Trust","active":true,"usgs":false}],"preferred":false,"id":806103,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sutherland, Chris","contributorId":245389,"corporation":false,"usgs":false,"family":"Sutherland","given":"Chris","affiliations":[{"id":49181,"text":"Univ. Massachusetts-Amherst","active":true,"usgs":false}],"preferred":false,"id":806104,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217180,"text":"70217180 - 2021 - Is there enough water? How bearish and bullish outlooks are linked to decision-maker perspectives on environmental flows","interactions":[],"lastModifiedDate":"2021-01-11T14:32:11.466282","indexId":"70217180","displayToPublicDate":"2020-11-26T08:27:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Is there enough water? How bearish and bullish outlooks are linked to decision-maker perspectives on environmental flows","docAbstract":"Policies that mandate environmental flows (e-flows) can be powerful tools for freshwater conservation, but implementation of these policies faces many hurdles. To better understand these challenges, we explored two key questions: (1) What additional data are needed to implement e-flows? and (2) What are the major socio-political barriers to implementing e-flows? We surveyed water and natural resource decision makers in the semi-arid Red River basin, Texas-Oklahoma, USA, and used social network analysis to analyze their communication patterns. Most respondents agreed that e-flows can provide important benefits and identified the same data needs. However, respondents sharply in their beliefs on other issues, and a clustering analysis revealed two distinct groups of decision makers. One cluster of decision makers tended to be bearish, or pessimistic, and believed that: current flow conditions are not adequate, there are many serious socio-political barriers to implementation, water conflicts will likely increase in the future, and climate change is likely to exacerbate these issues. The other cluster of respondents was bullish, or optimistic: they foresaw fewer future water conflicts and fewer socio-political barriers to implementation. Despite these differences, both clusters largely identified the same data needs and barriers to e-flows implementation. Our social network analysis revealed that the frequency of communication between clusters was not significantly different than the frequency of communication within clusters. Overall, our results suggest that the different perspectives of decision-makers could complicate efforts to implement e-flows and proactively plan for climate change. However, there are opportunities for collaboration on addressing common data needs and barriers to implementation. Overall, our study provides a key socio-environmental perspective on e-flows implementation from a semi-arid and socio-politically complex river basin and contextualizes the many challenges facing e-flows implementation in river basins globally.
Freshwater mussels of the order Unionida are a widely distributed taxon that are important in maintaining freshwater ecosystems and are also highly imperiled throughout the world. Monitoring of mussel populations with environmental DNA (eDNA) is an attractive alternative to traditional methods because it is noninvasive and requires less labor and taxonomic knowledge from field personnel. We developed eDNA metabarcoding assays specific to freshwater mussels and tested them at six sites in the Clinch River, located in the southeastern United States. Our objective was to determine the utility of eDNA metabarcoding for future monitoring of mussel populations and restoration efforts in this watershed. Two metabarcoding assays that target the mitochondrial DNA regions of the cytochrome c oxidase subunit I (COI) and NADH dehydrogenase subunit (ND1) genes were developed and tested. Our assays appear to be order specific, amplifying members from the two families found in North America, Unionidae and Margaritiferidae, while not amplifying nontarget fish or other bivalve species. From the field collected samples, our assays together detected 19 species, eight of which are listed as federally endangered. The assays also detected 42%, 58%, and 54% of the species identified by recent quantitative visual mussel surveys at three sampling sites. Increased sampling effort by processing a greater water volume or number of samples will likely increase species detections. These eDNA metabarcoding assays may enable enhanced monitoring of freshwater mussel assemblages and subsequently inform conservation efforts.
Occupancy methods propelled the quantitative study of species distributions forward by separating the observation process, or the imperfect detectability of species, from the ecological processes of interest governing species distributions. Occupancy studies come at a cost, however: the collection of additional data to account for nondetections at sites where the species is present. The most common occupancy designs (repeated measures designs) require repeat visits to sites or the use of multiple observers or detection methods. Time‐to‐detection methods have been identified as a potentially efficient alternative, requiring only one visit to each site by a single observer. A comparison of time‐to‐detection methods to repeated measures designs for visual encounter surveys would allow researchers to evaluate whether time‐to‐detection methods might be appropriate for their study system and can inform optimal survey design. We collected time‐to‐detection data during two different repeated measures design occupancy surveys for four amphibians and compared the performance of time‐to‐detection methods to the other designs using the location (potential bias) and precision of posterior distributions for occurrence parameters. We further used results of time‐to‐detection surveys to optimize survey design. Time‐to‐detection methods performed best for species that are widespread and have high detection probabilities and rates, but performed less well for cryptic species with lower probability of occurrence or whose detection was strongly affected by survey conditions. In all cases single surveys were most efficient in terms of person‐hours expended, but under some conditions the survey duration required to achieve high detection probabilities would be prohibitively long for a single survey. Regardless of occupancy survey design, time‐to‐detection methods provide important information that can be used to optimize surveys, allowing researchers and resource managers to efficiently achieve monitoring and conservation goals. Collecting time‐to‐detection data while conducting repeated measures occupancy surveys requires only small modifications to field methods but could have large benefits in terms of time spent surveying in the long‐term.
In the past two decades, Salt Plains National Wildlife Refuge has been increasingly recognized as important habitat for both breeding and migratory shorebirds. North American snowy plovers Charadrius nivosus in particular rely on the nearly 5,000-ha salt flat at Salt Plains National Wildlife Refuge, which thousands use as breeding and stopover habitat. Elsewhere on the Southern Great Plains, decadal declines up to 75% within snowy plover subpopulations have been documented and attributed to vegetation encroachment, increased rates of nest predation, and decreased availability of fresh surface water. Despite many attempts to estimate this species' abundance across the continent, to date, no known attempt at distance sampling of snowy plovers has occurred. To address this paucity of data, we assessed feasibility of distance sampling methods to accurately estimate snowy plover abundance and detectability. Distance sampling surveys (2017–2018) indicated high detection probability (P = 0.80) and the population abundance estimate across the salt flat extrapolated to 3,307 individuals. The distance-sampling population abundance estimate is lower than population abundance estimates determined by two previous studies within the past decade but far greater than 2,105 estimated for a study in 2006. Overall, distance sampling snowy plovers at Salt Plains National Wildlife Refuge proved to be an effective addition to pre-established survey protocols but further investigation is needed to compare accuracy and precision of methods used in this study, annual surveys conducted by Salt Plains National Wildlife Refuge, and other potential snowy plover surveys.
","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-20-041","usgsCitation":"Heath-Acre, K., Conway, W.C., Boal, C.W., Collins, D., Hensley, G., Johnson, W., and Schmidt, P.M., 2021, Detectability and abundance of snowy plovers at Salt Plains National Wildlife Refuge, Oklahoma: Journal of Fish and Wildlife Management, v. 12, no. 1, p. 50-60, https://doi.org/10.3996/JFWM-20-041.","productDescription":"11 p.","startPage":"50","endPage":"60","ipdsId":"IP-119304","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":454211,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-20-041","text":"Publisher Index Page"},{"id":396436,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Salt Plains National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.30841064453125,\n 36.67172341847759\n ],\n [\n -98.12713623046875,\n 36.67172341847759\n ],\n [\n -98.12713623046875,\n 36.85984517196147\n ],\n [\n -98.30841064453125,\n 36.85984517196147\n ],\n [\n -98.30841064453125,\n 36.67172341847759\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Heath-Acre, K. M.","contributorId":280036,"corporation":false,"usgs":false,"family":"Heath-Acre","given":"K. M.","affiliations":[{"id":57413,"text":"Texas Tech University Lubbock","active":true,"usgs":false}],"preferred":false,"id":835924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, W. C.","contributorId":280037,"corporation":false,"usgs":false,"family":"Conway","given":"W.","email":"","middleInitial":"C.","affiliations":[{"id":57413,"text":"Texas Tech University Lubbock","active":true,"usgs":false}],"preferred":false,"id":835925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":835926,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collins, D. P.","contributorId":276303,"corporation":false,"usgs":false,"family":"Collins","given":"D. P.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":835927,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hensley, G.","contributorId":280038,"corporation":false,"usgs":false,"family":"Hensley","given":"G.","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":835928,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, W. P.","contributorId":280039,"corporation":false,"usgs":false,"family":"Johnson","given":"W. P.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":835929,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmidt, P. M.","contributorId":280040,"corporation":false,"usgs":false,"family":"Schmidt","given":"P.","email":"","middleInitial":"M.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":835930,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224617,"text":"70224617 - 2021 - Warming and microbial uptake influence the fate of added soil carbon across a Hawai'ian weathering gradient","interactions":[],"lastModifiedDate":"2021-09-30T11:45:11.03798","indexId":"70224617","displayToPublicDate":"2020-11-23T06:42:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3416,"text":"Soil Biology and Biochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Warming and microbial uptake influence the fate of added soil carbon across a Hawai'ian weathering gradient","docAbstract":"Tropical forest soils contain some of the largest carbon (C) stocks on Earth, yet the effects of warming on the fate of fresh C entering tropical soils are still poorly understood. This research sought to understand how the fate of fresh C entering soils is influenced by warming, soil weathering status, and C chemistry. We hypothesized that compounds that are quickly incorporated into microbial biomass (i.e., greater C use efficiency [CUE]) subsequently have longer-term (255 days) retention in soil. We also hypothesized that relatively weathered soils with greater sorptive capacity also retain more fresh C in the short and longer-terms, and that C in these soils is more resistant to weathering loss compared with less weathered soils. We tested these hypotheses by adding two 13C-labeled compounds (glucose and glycine) to three tropical forest soils from a weathering gradient in Hawai'i, and then incubating soils at ambient (16 °C), +5 °C, and +10 °C for 255 days. We found that 255-day 13C retention in mineral soil across sites and temperatures was best predicted by two factors: initial retention of 13C in mineral soil and initial microbial 13CUE (Adjusted R2 = 0.78). Carbon compound type influenced 13C initial retention, with greater glucose-13C retention versus glycine-13C retention in mineral soils and microbial biomass, corresponding to greater glucose-13C retention in soil at 255 days. Warming had a negative longer-term effect on the retention of 13C only in the least-weathered soil, supporting our hypothesis. These results show that initial retention of fresh C in soils via mineral sorption and microbial uptake is a strong predictor of longer-term retention, indicating that immediate C losses are a major hurdle for soil C storage. Also, retention of fresh C appears most sensitive to warming in less-weathered tropical soils, supporting the idea that mineral sorption may provide some protections against warming. Understanding the interaction between soil sorptive properties and warming for C cycling could improve predictions of forest-climate feedbacks for tropical regions.
Climate warming is expected to have substantial impacts on native trout across the Rocky Mountains, but there is little understanding of how these changes affect future distributions of co-occurring native fishes within population strongholds. We used mixed-effects logistic regression to investigate the role of abiotic (e.g., temperature) and biotic factors (bull trout presence, Salvelinus confluentus) on distributions of westslope cutthroat trout (Oncorhynchus clarkii lewisi; WCT) in the North Fork Flathead River, USA and Canada. The probability of WCT presence increased with stream temperature and decreased with channel gradient and bull trout presence, yet the effect of bull trout was reduced with increasing pool densities. Combining this model with spatially explicit stream temperature projections, we predict a 29% increase in suitable habitat under high emissions through 2075, with gains at mid-elevation sites predicted to exceed bull trout thermal tolerances and high-elevation sites expected to become more thermally suitable for WCT. Our study illustrates the importance of considering abiotic and biotic drivers to assess species response to climate change, helping to guide local-scale climate adaptation and management.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2020-0099","usgsCitation":"Heinle, K., Eby, L., Muhlfeld, C.C., Steed, A., Jones, L., D’Angelo, V.S., Whiteley, A.R., and Hubblewhite, M., 2021, Influence of water temperature and biotic interactions on the distribution of westslope cutthroat trout (Oncorhynchus clarkii lewisi) in a population stronghold under climate change: Canadian Journal of Fisheries and Aquatic Sciences, v. 78, no. 4, p. 444-456, https://doi.org/10.1139/cjfas-2020-0099.","productDescription":"13 p.","startPage":"444","endPage":"456","ipdsId":"IP-111700","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":387127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alberta, British Columbia, Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.9996337890625,\n 47.98256841921405\n ],\n [\n -113.49426269531249,\n 47.97889140226657\n ],\n [\n -113.6700439453125,\n 48.34894812401375\n ],\n [\n -113.895263671875,\n 48.669198799260045\n ],\n [\n -114.730224609375,\n 49.57510247172322\n ],\n [\n -114.993896484375,\n 49.61070993807422\n ],\n [\n -115.103759765625,\n 49.396675075193976\n ],\n [\n -114.4940185546875,\n 48.585692256886624\n ],\n [\n -113.9996337890625,\n 47.98256841921405\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Heinle, Kadie","contributorId":260877,"corporation":false,"usgs":false,"family":"Heinle","given":"Kadie","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":819032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eby, Lisa A","contributorId":251751,"corporation":false,"usgs":false,"family":"Eby","given":"Lisa A","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":819033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":819034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Steed, Amber","contributorId":124596,"corporation":false,"usgs":false,"family":"Steed","given":"Amber","affiliations":[{"id":5133,"text":"Montana Fish Wildlife and Parks, Kalispell, Montana 59901","active":true,"usgs":false}],"preferred":false,"id":819035,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Leslie","contributorId":260953,"corporation":false,"usgs":false,"family":"Jones","given":"Leslie","affiliations":[],"preferred":false,"id":819200,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"D’Angelo, Vincent S. 0000-0003-1244-8091 vdangelo@usgs.gov","orcid":"https://orcid.org/0000-0003-1244-8091","contributorId":224823,"corporation":false,"usgs":true,"family":"D’Angelo","given":"Vincent","email":"vdangelo@usgs.gov","middleInitial":"S.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":819036,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Whiteley, Andrew R.","contributorId":150155,"corporation":false,"usgs":false,"family":"Whiteley","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":819037,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hubblewhite, Mark","contributorId":260878,"corporation":false,"usgs":false,"family":"Hubblewhite","given":"Mark","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":819038,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216733,"text":"70216733 - 2021 - Small mammal responses to wetland restoration in the Greater Everglades ecosystem","interactions":[],"lastModifiedDate":"2021-04-08T14:17:17.479018","indexId":"70216733","displayToPublicDate":"2020-11-22T07:56:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Small mammal responses to wetland restoration in the Greater Everglades ecosystem","docAbstract":"Wetlands have experienced dramatic losses in extent around the world, disrupting ecosystem function, habitat, and biodiversity. In Florida’s Greater Everglades, a massive restoration effort costing billions of dollars and spanning multiple decades is underway. As Everglades restoration is implemented in incremental projects, scientists and planners monitor the outcomes of projects. In this study, we evaluated the progress of a restoration project in the southwestern Everglades. We aimed to determine whether the presence and density of small mammals differed between areas with hydrologic restoration of the ecosystem and areas without restoration. Our three focal species were: marsh rice rat (Oryzomys palustris), hispid cotton rat (Sigmodon hispidus), and cotton mouse (Peromyscus gossypinus). Using spatially explicit capture‐recapture models, we found greater densities of cotton mouse in restored habitat and lower densities of hispid cotton rat in sites with higher water levels. Additionally, we found an increase in the presence of the marsh rice rat in restored areas compared to unrestored, but captures were too low to reliably assess significance. Our study provides evidence that ongoing restoration in the southwestern Everglades is already impacting the small mammal community.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.13332","usgsCitation":"Romanach, S., D’Acunto, L., Chapman, J., and Hanson, M., 2021, Small mammal responses to wetland restoration in the Greater Everglades ecosystem: Restoration Ecology, v. 29, no. 3, e13332, 9 p., https://doi.org/10.1111/rec.13332.","productDescription":"e13332, 9 p.","ipdsId":"IP-114410","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":454216,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.13332","text":"Publisher Index Page"},{"id":436633,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BWA7RD","text":"USGS data release","linkHelpText":"Small mammal captures at the Picayune Strand State Forest, October 2014 - April 2016"},{"id":380947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.97448730468749,\n 25.035838555635017\n ],\n [\n -79.903564453125,\n 25.035838555635017\n ],\n [\n -79.903564453125,\n 26.59343927024179\n ],\n [\n -81.97448730468749,\n 26.59343927024179\n ],\n [\n -81.97448730468749,\n 25.035838555635017\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Romanach, Stephanie 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":220761,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":806009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Acunto, Laura 0000-0001-6227-0143","orcid":"https://orcid.org/0000-0001-6227-0143","contributorId":215343,"corporation":false,"usgs":true,"family":"D’Acunto","given":"Laura","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":806010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chapman, Julia","contributorId":245353,"corporation":false,"usgs":false,"family":"Chapman","given":"Julia","affiliations":[],"preferred":false,"id":806011,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanson, Matthew R 0000-0002-2859-3878","orcid":"https://orcid.org/0000-0002-2859-3878","contributorId":245354,"corporation":false,"usgs":false,"family":"Hanson","given":"Matthew R","affiliations":[],"preferred":false,"id":806012,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216501,"text":"70216501 - 2021 - A comparison of plant communities in restored, old field, and remnant coastal prairies","interactions":[],"lastModifiedDate":"2021-04-08T14:15:43.570497","indexId":"70216501","displayToPublicDate":"2020-11-22T07:41:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of plant communities in restored, old field, and remnant coastal prairies","docAbstract":"Temperate grasslands are experiencing worldwide declines due to habitat conversion. Grassland restoration efforts are employed to compensate for these losses. However, there is a need to better understand the ecological effects of grassland restoration and management practices. We investigated the effects of three different grassland management regimes on plant communities of coastal prairie ecosystems in southwest Louisiana (USA). We compared old fields, prairie remnants, and restored prairies. Coastal prairies are a unique type of grassland historically present across southeast Texas and southwest Louisiana. Old fields represent former coastal prairie habitats allowed to revegetate naturally without active management. Remnant coastal prairies are small, isolated patches of comparatively intact prairie. Restored coastal prairies have been actively restored by planting native coastal prairie vegetation and managed with prescribed burning, mowing, and/or removal of invasive non‐native species. Our work was conducted in 3 old fields, 4 remnants, and 4 restored prairies. Old fields were dominated by non‐native species with low conservation value, whereas remnant prairies were dominated by native species with high conservation value. Remnants had a mean species richness of 75 species per site, which is higher than most other tallgrass prairie ecosystems in North America. Restored sites were dominated by native species with high conservation value, although the composition differed between restored and remnant sites. Collectively, our results: (1) reinforce the importance of identifying and preserving remnant coastal prairies; and (2) show that restoration of degraded coastal prairies is a viable strategy for supporting the persistence of these unique grassland ecosystems.","language":"English","publisher":"Wiley","doi":"10.1111/rec.13325","usgsCitation":"Feher, L., Allain, L., Osland, M., Pigott, E., Reid, C., and Latiolais, N., 2021, A comparison of plant communities in restored, old field, and remnant coastal prairies: Restoration Ecology, v. 29, no. 3, e13325, 11 p., https://doi.org/10.1111/rec.13325.","productDescription":"e13325, 11 p.","ipdsId":"IP-120471","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":380738,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.1253662109375,\n 29.649868677972304\n ],\n [\n -91.7962646484375,\n 29.649868677972304\n ],\n [\n -91.7962646484375,\n 30.92107637538488\n ],\n [\n -94.1253662109375,\n 30.92107637538488\n ],\n [\n -94.1253662109375,\n 29.649868677972304\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Feher, Laura 0000-0002-5983-6190","orcid":"https://orcid.org/0000-0002-5983-6190","contributorId":221894,"corporation":false,"usgs":true,"family":"Feher","given":"Laura","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":805466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allain, Larry 0000-0002-7717-9761","orcid":"https://orcid.org/0000-0002-7717-9761","contributorId":221930,"corporation":false,"usgs":true,"family":"Allain","given":"Larry","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":805467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osland, Michael 0000-0001-9902-8692","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":222814,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":805468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pigott, Elisabeth","contributorId":245154,"corporation":false,"usgs":false,"family":"Pigott","given":"Elisabeth","email":"","affiliations":[{"id":49096,"text":"Pigott Consulting at U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":805469,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reid, Christopher","contributorId":198739,"corporation":false,"usgs":false,"family":"Reid","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":805470,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Latiolais, Nicholas","contributorId":245156,"corporation":false,"usgs":false,"family":"Latiolais","given":"Nicholas","email":"","affiliations":[{"id":49098,"text":"Latiolais Consulting at U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":805471,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216934,"text":"70216934 - 2021 - Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model","interactions":[],"lastModifiedDate":"2021-03-05T21:07:22.044536","indexId":"70216934","displayToPublicDate":"2020-11-21T12:54:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7443,"text":"Quarterly Journal of the Royal Meteorological Society","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model","docAbstract":"The importance of wind energy as an alternative energy source has increased over the latest years with more focus on offshore winds. A good estimation of the offshore winds is thus of major importance for this industry. Up to now the effect of the wind–wave (mis)alignment has not yet been taken into account in coupled atmosphere–wave models to study the vertical wind profile and power production estimations of offshore wind farms. In this study the roughness length parametrization of Drennan et al. in 2003, and its extension addressing the wind–wave (mis)alignment proposed by Porchetta et al. in 2019, are investigated in the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model. This study shows that the yearly mean wind estimation at hub height (100 m) is improved by the roughness length parametrization of Porchetta et al. compared to Drennan. This is mainly due to the increased roughness of the former parametrization compare to the latter, even in aligned wind–wave conditions. This difference in roughness is caused by the dataset used to obtain the constants, deep‐water conditions versus mixed offshore conditions. Moreover, the roughness length parametrization of Porchetta et al. performs better in two of three alignment categories. Furthermore, similar model performances are obtained if we exclude the wind directions from the wind shadow zone of the measurement mast or the wind directions from the recently built Alpha Ventus wind farm, which is in close vicinity of the measurement mast. Investigating different wind conditions shows that the new roughness length parametrization of Porchetta et al. performs best for both offshore and onshore winds. Additionally, we show that the coupled model estimations of the vertical wind are only slightly affected by significant wave height estimations. Similar model performances for different accuracies of significant wave height estimations are presented. One exception is the perpendicular alignment category where the new roughness length of Porchetta et al. outperforms the roughness length of Drennan when investigating the wind estimations related to significant wave heights with a higher accuracy. The roughness length parametrization of Porchetta et al. reduced the power production overestimation of the coupled model from 5.7 to 2.8%. We also show that the standalone atmospheric model including the roughness length of Charnock in 1955 has a degraded performance compared to the coupled model including the roughness length parametrization of Porchetta et al. for yearly average wind profiles.
","language":"English","publisher":"Royal Meteorological Society","doi":"10.1002/qj.3948","usgsCitation":"Porchetta, S., Temel, O., Warner, J., Munoz-Esparza, J., Monbaliu, J., van Beeck, J., and van Lipzig, N., 2021, Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model: Quarterly Journal of the Royal Meteorological Society, v. 147, no. 735, p. 825-846, https://doi.org/10.1002/qj.3948.","productDescription":"22 p.","startPage":"825","endPage":"846","ipdsId":"IP-117950","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454221,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lirias.kuleuven.be/bitstream/123456789/685815/2/COAWST_QJRMetS_rkul.docx","text":"External Repository"},{"id":381447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"147","issue":"735","noUsgsAuthors":false,"publicationDate":"2020-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Porchetta, Sara","contributorId":245775,"corporation":false,"usgs":false,"family":"Porchetta","given":"Sara","email":"","affiliations":[{"id":49315,"text":"KU Leuven, Department Earth and Environmental Sciences, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Temel, O.","contributorId":245776,"corporation":false,"usgs":false,"family":"Temel","given":"O.","email":"","affiliations":[{"id":49316,"text":"Royal Observatory of Belgium, Brussels, Belgium","active":true,"usgs":false}],"preferred":false,"id":807017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munoz-Esparza, J.C.","contributorId":245777,"corporation":false,"usgs":false,"family":"Munoz-Esparza","given":"J.C.","email":"","affiliations":[{"id":16785,"text":"National Center for Atmospheric Research, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":807019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Monbaliu, J","contributorId":245778,"corporation":false,"usgs":false,"family":"Monbaliu","given":"J","email":"","affiliations":[{"id":49317,"text":"KULeuven, Department of Civil Engineering, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807020,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"van Beeck, J.","contributorId":245779,"corporation":false,"usgs":false,"family":"van Beeck","given":"J.","email":"","affiliations":[{"id":49319,"text":"KULeuven, Department Earth and Environmental Sciences, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807021,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"van Lipzig, N.","contributorId":245780,"corporation":false,"usgs":false,"family":"van Lipzig","given":"N.","email":"","affiliations":[{"id":49321,"text":"von Karman Institute for Fluid Dynamics, Sint-Genesius-Rode, Belgium","active":true,"usgs":false}],"preferred":false,"id":807022,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70225590,"text":"70225590 - 2021 - Increasing comparability among coral bleaching experiments","interactions":[],"lastModifiedDate":"2021-10-26T14:31:59.549345","indexId":"70225590","displayToPublicDate":"2020-11-21T09:22:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Increasing comparability among coral bleaching experiments","docAbstract":"Coral bleaching is the single largest global threat to coral reefs worldwide. Integrating the diverse body of work on coral bleaching is critical to understanding and combating this global problem. Yet investigating the drivers, patterns, and processes of coral bleaching poses a major challenge. A recent review of published experiments revealed a wide range of experimental variables used across studies. Such a wide range of approaches enhances discovery, but without full transparency in the experimental and analytical methods used, can also make comparisons among studies challenging. To increase comparability but not stifle innovation, we propose a common framework for coral bleaching experiments that includes consideration of coral provenance, experimental conditions, and husbandry. For example, reporting the number of genets used, collection site conditions, the experimental temperature offset(s) from the maximum monthly mean (MMM) of the collection site, experimental light conditions, flow, and the feeding regime will greatly facilitate comparability across studies. Similarly, quantifying common response variables of endosymbiont (Symbiodiniaceae) and holobiont phenotypes (i.e., color, chlorophyll, endosymbiont cell density, mortality, and skeletal growth) could further facilitate cross-study comparisons. While no single bleaching experiment can provide the data necessary to determine global coral responses of all corals to current and future ocean warming, linking studies through a common framework as outlined here, would help increase comparability among experiments, facilitate synthetic insights into the causes and underlying mechanisms of coral bleaching, and reveal unique bleaching responses among genets, species, and regions. Such a collaborative framework that fosters transparency in methods used would strengthen comparisons among studies that can help inform coral reef management and facilitate conservation strategies to mitigate coral bleaching worldwide.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2262","usgsCitation":"Grottoli, A., Toonen, R.J., van Woesik, R., Vega Thurber, R., Warner, M.E., McLachlan, R.H., Price, J., Bahr, K.D., Baums, I., Castillo, K., Coffroth, M.A., Cunning, R., Dobson, K., Donahue, M., Hench, J.L., Iglesias-Prieto, R., Kemp, D.W., Kenkel, C.D., Kline, D.I., Kuffner, I.B., Matthews, J., Mayfield, A., Padilla-Gamino, J., Palumbi, S.R., Voolstra, C., Weis, V.M., and Wu, H.C., 2021, Increasing comparability among coral bleaching experiments: Ecological Applications, v. 31, no. 4, e02262, 17 p., https://doi.org/10.1002/eap.2262.","productDescription":"e02262, 17 p.","ipdsId":"IP-114969","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454223,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2262","text":"Publisher Index Page"},{"id":390962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Grottoli, Andrea G.","contributorId":267953,"corporation":false,"usgs":false,"family":"Grottoli","given":"Andrea G.","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":825698,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Toonen, R. J.","contributorId":267954,"corporation":false,"usgs":false,"family":"Toonen","given":"R.","email":"","middleInitial":"J.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":825699,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Woesik, R.","contributorId":40820,"corporation":false,"usgs":false,"family":"van Woesik","given":"R.","email":"","affiliations":[],"preferred":false,"id":825700,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vega Thurber, R.","contributorId":267956,"corporation":false,"usgs":false,"family":"Vega Thurber","given":"R.","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":825701,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Warner, M. E.","contributorId":267959,"corporation":false,"usgs":false,"family":"Warner","given":"M.","email":"","middleInitial":"E.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":825702,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McLachlan, R. H.","contributorId":267962,"corporation":false,"usgs":false,"family":"McLachlan","given":"R.","email":"","middleInitial":"H.","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":825703,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Price, James","contributorId":156327,"corporation":false,"usgs":false,"family":"Price","given":"James","affiliations":[{"id":20318,"text":"Bureau of Ocean Energy Management","active":true,"usgs":false}],"preferred":false,"id":825704,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bahr, K. D.","contributorId":267966,"corporation":false,"usgs":false,"family":"Bahr","given":"K.","email":"","middleInitial":"D.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":825705,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Baums, I. B.","contributorId":267968,"corporation":false,"usgs":false,"family":"Baums","given":"I. B.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":825706,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Castillo, K.","contributorId":267971,"corporation":false,"usgs":false,"family":"Castillo","given":"K.","email":"","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":false,"id":825707,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Coffroth, M. A.","contributorId":267973,"corporation":false,"usgs":false,"family":"Coffroth","given":"M.","email":"","middleInitial":"A.","affiliations":[{"id":48981,"text":"State University of New York","active":true,"usgs":false}],"preferred":false,"id":825708,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Cunning, R.","contributorId":267976,"corporation":false,"usgs":false,"family":"Cunning","given":"R.","email":"","affiliations":[{"id":39376,"text":"Shedd Aquarium","active":true,"usgs":false}],"preferred":false,"id":825709,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dobson, K.","contributorId":267979,"corporation":false,"usgs":false,"family":"Dobson","given":"K.","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":825710,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Donahue, M.","contributorId":267982,"corporation":false,"usgs":false,"family":"Donahue","given":"M.","email":"","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":825711,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hench, James L.","contributorId":196320,"corporation":false,"usgs":false,"family":"Hench","given":"James","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":825712,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Iglesias-Prieto, R.","contributorId":267986,"corporation":false,"usgs":false,"family":"Iglesias-Prieto","given":"R.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":825713,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Kemp, D. W.","contributorId":267988,"corporation":false,"usgs":false,"family":"Kemp","given":"D.","email":"","middleInitial":"W.","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":825714,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Kenkel, C. D.","contributorId":267991,"corporation":false,"usgs":false,"family":"Kenkel","given":"C.","email":"","middleInitial":"D.","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":825715,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Kline, D. I.","contributorId":267994,"corporation":false,"usgs":false,"family":"Kline","given":"D.","email":"","middleInitial":"I.","affiliations":[{"id":12671,"text":"Smithsonian Tropical Research Institute","active":true,"usgs":false}],"preferred":false,"id":825716,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Kuffner, Ilsa B. 0000-0001-8804-7847 ikuffner@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7847","contributorId":3105,"corporation":false,"usgs":true,"family":"Kuffner","given":"Ilsa","email":"ikuffner@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":825717,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Matthews, Jessica","contributorId":198726,"corporation":false,"usgs":false,"family":"Matthews","given":"Jessica","email":"","affiliations":[],"preferred":false,"id":825718,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Mayfield, A.","contributorId":267999,"corporation":false,"usgs":false,"family":"Mayfield","given":"A.","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":825719,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Padilla-Gamino, J.","contributorId":268000,"corporation":false,"usgs":false,"family":"Padilla-Gamino","given":"J.","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":825720,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Palumbi, S. R.","contributorId":268003,"corporation":false,"usgs":false,"family":"Palumbi","given":"S.","email":"","middleInitial":"R.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":825721,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Voolstra, C. R.","contributorId":268006,"corporation":false,"usgs":false,"family":"Voolstra","given":"C. R.","affiliations":[{"id":55536,"text":"University of Konstanz","active":true,"usgs":false}],"preferred":false,"id":825722,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Weis, V. M.","contributorId":268008,"corporation":false,"usgs":false,"family":"Weis","given":"V.","email":"","middleInitial":"M.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":825723,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Wu, H. C.","contributorId":268011,"corporation":false,"usgs":false,"family":"Wu","given":"H.","email":"","middleInitial":"C.","affiliations":[{"id":55538,"text":"Leibniz Centre for Tropical Marine Research","active":true,"usgs":false}],"preferred":false,"id":825724,"contributorType":{"id":1,"text":"Authors"},"rank":27}]}} ,{"id":70216862,"text":"70216862 - 2021 - Review of trap-and-haul for managing Pacific salmonids (Oncorhynchus spp.) in impounded river systems","interactions":[],"lastModifiedDate":"2021-02-17T22:20:09.735913","indexId":"70216862","displayToPublicDate":"2020-11-21T07:39:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3278,"text":"Reviews in Fish Biology and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"Review of trap-and-haul for managing Pacific salmonids (Oncorhynchus spp.) in impounded river systems","docAbstract":"High-head dams are migration barriers for Pacific salmon Oncorhynchus spp. in many river systems and recovery measures for impacted stocks are limited. Trap-and-haul has been widely used in attempts to facilitate recovery but information from existing programs has not been synthesized to inform improvements to aid recovery of salmonids in systems with high-head dams. We reviewed 17 trap-and-haul programs regarding Pacific salmon to: (1) summarize information about facility design, operation and biological effects; (2) identify critical knowledge gaps; and (3) evaluate trap-and-haul as a current and future management tool. Existing programs are operated to address a range of management goals including restoring access to historical habitats, temporarily reducing exposure to dangerous in-river conditions, and reintroducing ecological processes upstream from dams. Information gathered from decades of operation on facility design criteria and fish handling protocols, and robust literature on fish collection and passage are available. While many aspects of trap-and-haul have been evaluated, effects on population productivity and sustainability remain poorly understood. Long-term and systematic studies of trap-and-haul outcomes are rare, and assessments can be confounded by concurrent management actions and broad ecological and climatic effects. Existing data suggest that performance and effectiveness vary among programs and over various time scales within programs. Although critical information gaps exist, trap-and-haul is an important management and conservation tool for providing Pacific salmonids access to historical habitats. Successful application of trap-and-haul programs requires long-term commitment and an adaptive management approach by dam owners and stakeholders, and careful planning of new programs.
Many important ecological phenomena occur on large spatial scales and/or are unplanned and thus do not easily fit within analytical frameworks that rely on randomization, replication, and interspersed a priori controls for statistical comparison. Analyses of such large‐scale, natural experiments are common in the health and econometrics literature, where techniques have been developed to derive insight from large, noisy observational data sets. Here, we apply a technique from this literature, synthetic control, to assess landscape change with remote sensing data. The basic data requirements for synthetic control include (1) a discrete set of treated and untreated units, (2) a known date of treatment intervention, and (3) time series response data that include both pre‐ and post‐treatment outcomes for all units. Synthetic control generates a response metric for treated units relative to a no‐action alternative based on prior relationships between treated and unexposed groups. Using simulations and a case study involving a large‐scale brush‐clearing management event, we show how synthetic control can intuitively infer treatment effect sizes from satellite data, even in the presence of confounding noise from climate anomalies, long‐term vegetation dynamics, or sensor errors. We find that accuracy depends on the number and quality of potential control units, highlighting the importance of selecting appropriate control populations. Although we consider the synthetic control approach in the context of natural experiments with remote sensing data, we expect the methodology to have wider utility in ecology, particularly for systems with large, complex, and poorly replicated experimental units.
The efficiency of seepage meters, long considered a fixed property associated with the meter design, is not constant in highly permeable sediments. Instead, efficiency varies substantially with seepage bag fullness, duration of bag attachment, depth of meter insertion into the sediments, and seepage velocity. Tests conducted in a seepage test tank filled with isotropic sand with a hydraulic conductivity of about 60 m/d indicate that seepage meter efficiency varies widely and decreases unpredictably when the volume of the seepage bag is greater than about 65 to 70 percent full or less than about 15 to 20 percent full. Seepage generally decreases with duration of bag attachment even when operated in the mid-range of bag fullness. Stopping flow through the seepage meter during bag attachment or removal also results in a decrease in meter efficiency. Numerical modeling indicates efficiency is inversely related to hydraulic conductivity in highly permeable sediments. An efficiency close to 1 for a meter installed in sediment with a hydraulic conductivity of 1 m/d decreases to about 60 and then 10 percent when hydraulic conductivity is increased to 10 and 100 m/d, respectively. These large efficiency reductions apply only to high-permeability settings, such as wave- or tidally washed coarse sand or gravel, or fluvial settings with an actively mobile sand or gravel bed, where low resistance to flow through the porous media allows bypass flow around the seepage cylinder to readily occur. In more typical settings, much greater resistance to bypass flow suppresses small changes in meter resistance during inflation or deflation of seepage bags.
","language":"English","publisher":"MPDI","doi":"10.3390/w12113267","usgsCitation":"Rosenberry, D.O., Nieto-Lopez, J.M., Webb, R.M., and Muller, S., 2021, Variable seepage meter efficiency in high-permeability settings: Water, v. 12, no. 11, 3267, 22 p., https://doi.org/10.3390/w12113267.","productDescription":"3267, 22 p.","ipdsId":"IP-119819","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454229,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12113267","text":"Publisher Index Page"},{"id":436637,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93N8B2N","text":"USGS data release","linkHelpText":"Webb and Rosenberry, 2020, MODFLOW 2005 and MODPATH 5 model data sets used to evaluate seepage-meter efficiency in high-permeability settings"},{"id":436636,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93N8B2N","text":"USGS data release","linkHelpText":"Webb and Rosenberry, 2020, MODFLOW 2005 and MODPATH 5 model data sets used to evaluate seepage-meter efficiency in high-permeability settings"},{"id":436635,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SO2FVM","text":"USGS data release","linkHelpText":"Seepage meter efficiency in highly permeable settings source data (2020)"},{"id":436634,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SO2FVM","text":"USGS data release","linkHelpText":"Seepage meter efficiency in highly permeable settings source data (2020)"},{"id":384775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":813261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nieto-Lopez, Jose M 0000-0002-2596-6368","orcid":"https://orcid.org/0000-0002-2596-6368","contributorId":256817,"corporation":false,"usgs":false,"family":"Nieto-Lopez","given":"Jose","email":"","middleInitial":"M","affiliations":[{"id":51863,"text":"University of Malaga","active":true,"usgs":false}],"preferred":false,"id":813262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Richard M. 0000-0001-9531-2207 rmwebb@usgs.gov","orcid":"https://orcid.org/0000-0001-9531-2207","contributorId":1570,"corporation":false,"usgs":true,"family":"Webb","given":"Richard","email":"rmwebb@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muller, Sascha","contributorId":256818,"corporation":false,"usgs":false,"family":"Muller","given":"Sascha","email":"","affiliations":[{"id":12672,"text":"University of Copenhagen","active":true,"usgs":false}],"preferred":false,"id":813264,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216890,"text":"70216890 - 2021 - Record fledging count from a seven-egg clutch in the Cooper’s Hawk (Accipiter cooperii)","interactions":[],"lastModifiedDate":"2021-05-14T21:19:20.632428","indexId":"70216890","displayToPublicDate":"2020-11-20T16:42:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3784,"text":"Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Record fledging count from a seven-egg clutch in the Cooper’s Hawk (Accipiter cooperii)","title":"Record fledging count from a seven-egg clutch in the Cooper’s Hawk (Accipiter cooperii)","docAbstract":"Cooper's Hawks (Accipiter cooperii) typically lay 3–5 eggs per clutch, rarely 6 eggs, and there are 2 accounts of 7-egg clutches and 1 record of a maximum 8-egg clutch for the species. Brood sizes of 3–5 young are common and the previous maximum brood count is 6 young. However, in 2019, we found an urban nest in Stevens Point, Wisconsin, with 7 eggs that resulted in a record high of 7 fledglings. We genetically confirmed that the attending male sired all the offspring and the attending female laid all 7 eggs. Larger body size of the tending adults may have been a factor in the exceptional reproduction reported here.
","language":"English","publisher":"Allen Press","doi":"10.1676/1559-4491-132.2.460","usgsCitation":"Rosenfield, R.N., Sonsthagen, S.A., Riddle-Berntsen, A.E., and Kuhel, E., 2021, Record fledging count from a seven-egg clutch in the Cooper’s Hawk (Accipiter cooperii): Wilson Journal of Ornithology, v. 132, no. 2, p. 460-463, https://doi.org/10.1676/1559-4491-132.2.460.","productDescription":"4 p.","startPage":"460","endPage":"463","ipdsId":"IP-113425","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":436639,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P914SGB1","text":"USGS data release","linkHelpText":"Genetic Data from Cooper's Hawks (Accipiter cooperii), North America"},{"id":436638,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P914SGB1","text":"USGS data release","linkHelpText":"Genetic Data from Cooper's Hawks (Accipiter cooperii), North America"},{"id":382527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Stevens Point","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.65427398681639,\n 44.46613109099745\n ],\n [\n -89.46338653564453,\n 44.46613109099745\n ],\n [\n -89.46338653564453,\n 44.593401045429374\n ],\n [\n -89.65427398681639,\n 44.593401045429374\n ],\n [\n -89.65427398681639,\n 44.46613109099745\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"132","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenfield, Robert N.","contributorId":94013,"corporation":false,"usgs":false,"family":"Rosenfield","given":"Robert","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":806746,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":806747,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Riddle-Berntsen, Ann Elizabeth 0000-0002-1925-0849","orcid":"https://orcid.org/0000-0002-1925-0849","contributorId":245652,"corporation":false,"usgs":true,"family":"Riddle-Berntsen","given":"Ann","email":"","middleInitial":"Elizabeth","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":806748,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuhel, Evan","contributorId":245653,"corporation":false,"usgs":false,"family":"Kuhel","given":"Evan","email":"","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":806749,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216564,"text":"70216564 - 2021 - Systematic characterization of morphotectonic variability along the Cascadia convergent margin: Implications for shallow megathrust behavior and tsunami hazards","interactions":[],"lastModifiedDate":"2021-02-04T00:04:42.827309","indexId":"70216564","displayToPublicDate":"2020-11-20T09:17:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Systematic characterization of morphotectonic variability along the Cascadia convergent margin: Implications for shallow megathrust behavior and tsunami hazards","docAbstract":"Studies of recent destructive megathrust earthquakes and tsunamis along subduction margins in Japan, Sumatra, and Chile have linked forearc morphology and structure to megathrust behavior. This connection is based on the idea that spatial variations in the frictional behavior of the megathrust influence the tectono-morphological evolution of the upper plate. Here we present a comprehensive examination of the tectonic geomorphology, outer wedge taper, and structural vergence along the marine forearc of the Cascadia subduction zone (offshore northwestern North America). The goal is to better understand geologic controls on outer wedge strength and segmentation at spatial scales equivalent to rupture lengths of large earthquakes (≥M 6.7), and to examine potential linkages with shallow megathrust behavior.
We use cross-margin profiles, spaced 25 km apart, to characterize along-strike variation in outer wedge width, steepness, and structural vergence (measured between the toe and the outer arc high). The width of the outer wedge varies between 17 and 93 km, and the steepness ranges from 0.9° to 6.5°. Hierarchical cluster analysis of outer wedge width and steepness reveals four distinct regions that also display unique patterns of structural vergence and shape of the wedge: Vancouver Island, British Columbia, Canada (average width, linear wedge, seaward and mixed vergence); Washington, USA (higher width, concave wedge, landward and mixed vergence); northern and central Oregon, USA (average width, linear and convex wedge, mixed and seaward vergence); and southern Oregon and northern California, USA (lower width, convex wedge, seaward and mixed vergence). Variability in outer wedge morphology and structure is broadly associated with along-strike megathrust segmentation inferred from differences in oceanic asthenospheric velocities, patterns of episodic tremor and slow slip, GPS models of plate locking, and the distribution of seismicity near the plate interface. In more detail, our results appear to delineate the extent, geometry, and lithology of dynamic and static backstops along the margin. Varying backstop configurations along the Cascadia margin are interpreted to represent material-strength contrasts within the wedge that appear to regulate the along- and across-strike taper and structural vergence in the outer wedge. We argue that the morphotectonic variability in the outer wedge may reflect spatial variations in shallow megathrust behavior occurring over roughly the last few million years. Comparing outer wedge taper along the Cascadia margin to a global compilation suggests that observations in the global catalog are not accurately representing the range of heterogeneity within individual margins and highlights the need for detailed margin-wide morphotectonic analyses of subduction zones worldwide.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02178.1","usgsCitation":"Watt, J., and Brothers, D.S., 2021, Systematic characterization of morphotectonic variability along the Cascadia convergent margin: Implications for shallow megathrust behavior and tsunami hazards: Geosphere, v. 17, no. 1, p. 95-117, https://doi.org/10.1130/GES02178.1.","productDescription":"19 p.","startPage":"95","endPage":"117","ipdsId":"IP-109931","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454235,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02178.1","text":"Publisher Index Page"},{"id":380781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, California, Oregon, Washington","otherGeospatial":"Cascadia subduction zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.01367187499999,\n 40.195659093364654\n ],\n [\n -123.50830078125,\n 41.623655390686395\n ],\n [\n -123.662109375,\n 44.6061127451739\n ],\n [\n -123.662109375,\n 47.100044694025215\n ],\n [\n -123.11279296875001,\n 48.69096039092549\n ],\n [\n -128.1005859375,\n 51.248163159055906\n ],\n [\n -128.84765625,\n 50.999928855859636\n ],\n [\n -127.46337890625001,\n 40.97989806962013\n ],\n [\n -126.03515625,\n 39.605688178320804\n ],\n [\n -124.01367187499999,\n 40.195659093364654\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Watt, Janet 0000-0002-4759-3814","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":221271,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Daniel S. 0000-0001-7702-157X dbrothers@usgs.gov","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":167089,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel","email":"dbrothers@usgs.gov","middleInitial":"S.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805622,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227051,"text":"70227051 - 2021 - Suspended-sediment Flux in the San Francisco Estuary; Part II: the Impact of the 2013–2016 California Drought and Controls on Sediment Flux","interactions":[],"lastModifiedDate":"2021-12-28T14:48:59.650241","indexId":"70227051","displayToPublicDate":"2020-11-20T08:46:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Suspended-sediment Flux in the San Francisco Estuary; Part II: the Impact of the 2013–2016 California Drought and Controls on Sediment Flux","docAbstract":"Recent modeling has demonstrated that sediment supply is one of the primary environmental variables that will determine the sustainability of San Francisco Estuary tidal marshes over the next century as sea level rises. Therefore, understanding the environmental controls on sediment flux within the San Francisco Estuary is crucial for optimal planning and management of tidal marsh restoration. Herein, we present suspended-sediment flux estimates from water year (WY) 2009–2016 from the San Francisco Estuary to investigate the environmental controls and impact of the record 2013–2016 California drought. During the recent drought, sediment flux into Lower South Bay, the southernmost subembayment of the San Francisco Estuary, increased by 345% from 114 kt/year from WY 2009 to 2011 to 508 kt/year from WY 2014 to 2016, while local tributary sediment flux declined from 209 to 51 kt/year. Total annual sediment flux from WY 2009 to 2011 and 2014 to 2016 can be predicted by total annual freshwater inflow from the Sacramento-San Joaquin Delta (R2 = 0.83, p < 0.01), the primary source of freshwater input into the San Francisco Estuary. The volume of freshwater inflow from the Sacramento-San Joaquin Delta is hypothesized to affect shoal-to-channel density gradients that affect sediment flux from broad, typically more saline and turbid shoals, to the main tidal-channel seaward of Lower South Bay. During the drought, freshwater inflow from the Sacramento-San Joaquin Delta decreased, and replacement of typically more saline shoal water was reduced. As a result, landward-increasing cross-channel density gradients enhanced shoal-to-channel advective flux that increased sediment available for tidal dispersion and drove an increase in net-landward sediment flux into Lower South Bay.
Geologists and petroleum engineers have struggled to identify the mechanisms that drive productivity in horizontal hydraulically fractured oil wells. The machine learning algorithms of Random Forest (RF), gradient boosting trees (GBT) and extreme gradient boosting (XGBoost) were applied to a dataset containing 7311 horizontal hydraulically fractured wells drilled into the middle member of the Bakken Formation from 2010 through 2017. The initial goal is to use these data‐driven machine learning algorithms to identify the most important explanatory predictors of well productivity within nine subareas and the composite area. Predictor variables representing initial gas production, the initial 180‐day water cut, and vertical depth vary spatially and are identified with geologically favorable areas. Well‐completion predictors include the well lateral length, number of fracture stages, volume of proppant per stage, and the volume of injected fluids per stage. The performance of methods is compared based on a common test sample. The analysis then examines the comparative predictive performance of the three algorithms for 1330 wells that had initiated production after the initial 7311 well sample had been producing. The computations of predictor importance identified the initial 180‐day water cut and the 30‐day initial gas production predictors as having a dominant influence in most subareas and for the composite area. The relative importance of well completion predictor variables, that is, the number of fracture stages per well, volume of injected proppant per stage, volume of injected fluids per stage, and lateral length, varied considerably across the subareas. For the common test or holdout sample, the models calibrated with the XGBoost algorithm had superior predictive power. The predictive power of all the algorithms trained on the data from the original sample suffered some loss when tested with a sample of wells that had started production after the end of that period. Implications of the empirical findings and strategies to mitigate loss of predictive power are discussed in the concluding section.
The U.S. Department of the Interior recently included uranium (U) on a list of mineral commodities that are considered critical to economic and national security. The uses of U for commercial and residential energy production, defense applications, medical device technologies, and energy generation for space vehicles and satellites are known, but the environmental impacts of uranium extraction are not always well quantified. We conducted a screening-level ecological risk analysis based on exposure to mining-related elements via diets and incidental soil ingestion for terrestrial biota to provide context to chemical characterization and exposures at breccia pipe U mines in northern Arizona. Relative risks, calculated as hazard quotients (HQs), were generally low for all biological receptor models. Our models screened for risk to omnivores and insectivores (HQs>1) but not herbivores and carnivores. Uranium was not the driver of ecological risk; arsenic, cadmium, copper, and zinc were of concern for biota consuming ground-dwelling invertebrates. Invertebrate species composition should be considered when applying these models to other mining locations or future sampling at the breccia pipe mine sites. Dietary concentration thresholds (DCTs) were also calculated to understand food concentrations that may lead to ecological risk. The DCTs indicated that critical concentrations were not approached in our model scenarios, as evident in the very low HQs for most models. The DCTs may be used by natural resource and land managers as well as mine operators to screen or monitor for potential risk to terrestrial receptors as mine sites are developed and remediated in the future.
1. The effects of changing climate and disturbance on mountain forest carbon stocks vary with tree species distributions and over elevational gradients. Warming can increase carbon uptake by stimulating productivity at high elevations but also enhance carbon release by increasing respiration and the frequency, intensity, and size of wildfires.
2. To understand the consequences of climate change for temperate mountain forests, we simulated interactions among climate, wildfire, tree species, and their combined effects on regional carbon stocks in forests of the Greater Yellowstone Ecosystem, USA with the LANDIS‐II landscape change model. Simulations used historical climate and future potential climate represented by downscaled projections from five general circulation models (GCMs) that bracket the range of variability under the representative concentration pathway (RCP) 8.5 emissions scenario.
3. Total ecosystem carbon increased by 67% through 2100 in simulations with historical climate, and by 38 – 69% with GCM climate. Differences in carbon uptake among GCMs resulted primarily from variation in area burned, not productivity. Warming increased productivity by extending the growing season, especially near upper treeline, but did not offset biomass losses to fire. By 2100, simulated area burned increased by 27 – 215% under GCM climate, with the largest increases after 2050. With warming >3 °C in mean annual temperature, the increased frequency of large fires reduced live carbon stocks by 4 – 36% relative to the control, historical climate scenario. However, relative losses in total carbon were delayed under GCMs with large increases in summer precipitation and buffered by carbon retained in soils and the wood of fire‐killed trees. Increasing fire size limited seed dispersal, and reductions in soil moisture limited seedling establishment; both effects will likely constrain long‐term forest regeneration and carbon uptake.
4. Synthesis.Forests in the GYE can maintain a carbon sink through the mid‐century in a warming climate but continued warming may cause the loss of forest area, live aboveground biomass, and ultimately, ecosystem carbon. Future changes in carbon stocks in similar forests throughout western North America will depend on regional thresholds for extensive wildfire and forest regeneration and therefore, changes may occur earlier in drier regions.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2745.13559","usgsCitation":"Henne, P., Hawbaker, T., Scheller, R.M., Zhao, F.S., He, H.S., Xu, W., and Zhu, Z., 2021, Increased burning in a warming climate reduces carbon uptake in the Greater Yellowstone Ecosystem despite productivity gains: Journal of Ecology, v. 109, no. 3801, p. 1148-1169, https://doi.org/10.1111/1365-2745.13559.","productDescription":"22 p.","startPage":"1148","endPage":"1169","ipdsId":"IP-110024","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":454241,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2745.13559","text":"Publisher Index Page"},{"id":436640,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94IA5B3","text":"USGS data release","linkHelpText":"Landscape inputs and simulation output for the LANDIS-II model in the Greater Yellowstone Ecosystem"},{"id":380677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.32421875,\n 42.48019996901214\n ],\n [\n -108.19335937499999,\n 42.48019996901214\n ],\n [\n -108.19335937499999,\n 45.805828539928356\n ],\n [\n -112.32421875,\n 45.805828539928356\n ],\n [\n -112.32421875,\n 42.48019996901214\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"109","issue":"3801","noUsgsAuthors":false,"publicationDate":"2020-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Henne, Paul D. 0000-0003-1211-5545 phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":805422,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":805423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheller, Robert M. 0000-0002-7507-4499","orcid":"https://orcid.org/0000-0002-7507-4499","contributorId":245139,"corporation":false,"usgs":false,"family":"Scheller","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":805424,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhao, Feng S 0000-0003-4534-933X","orcid":"https://orcid.org/0000-0003-4534-933X","contributorId":245140,"corporation":false,"usgs":false,"family":"Zhao","given":"Feng","email":"","middleInitial":"S","affiliations":[{"id":49091,"text":"Central China Normal University","active":true,"usgs":false}],"preferred":false,"id":805425,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"He, Hong S","contributorId":218764,"corporation":false,"usgs":false,"family":"He","given":"Hong","email":"","middleInitial":"S","affiliations":[{"id":39904,"text":"University of Missouri, School of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":805426,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xu, Wenru","contributorId":245141,"corporation":false,"usgs":false,"family":"Xu","given":"Wenru","affiliations":[{"id":39904,"text":"University of Missouri, School of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":805427,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":805428,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70219104,"text":"70219104 - 2021 - It’s complicated…environmental DNA as a predictor of trout and char abundance in streams","interactions":[],"lastModifiedDate":"2021-04-08T15:19:49.595336","indexId":"70219104","displayToPublicDate":"2020-11-20T07:15:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"It’s complicated…environmental DNA as a predictor of trout and char abundance in streams","docAbstract":"Freshwater lenses underlying small ocean islands exhibit spatial variability and temporal fluctuations in volume, influencing ecologic management. For example, The Palmyra Atoll National Wildlife Refuge harbors one of the few surviving native stands of Pisonia grandis in the central Pacific Ocean, yet these trees face pressure from groundwater salinization, with little basic groundwater data to guide decision making. Adding to natural complexity, the geology of Palmyra was heavily altered by dredge and fill activities. Our study based at this atoll combines geophysical and hydrological field measurements from 2008 to 2019 with groundwater modeling to study the drivers of observed freshwater lens dynamics. Electromagnetic induction (EMI) field data were collected on the main atoll islands over repeat transects in 2008 following ‘strong’ La Niña conditions (wet) and in 2016 during ‘very strong’ El Niño conditions (dry). Shallow monitoring wells were installed adjacent to the geophysical transects in 2013 and screened within the fresh/saline groundwater transition zone. Temporal EMI and monitoring well data showed a strong contraction of the freshwater lens in response to El Niño conditions, and indicated a thicker lens toward the ocean side, an opposite spatial pattern to that observed for many other Pacific islands. On an outer islet where a stand of mature Pisonia trees exist, EMI surveys revealed only a thin (<3 m from land surface) layer of brackish groundwater during El Niño. Numerical groundwater simulations were performed for a range of permeability distributions and climate conditions at Palmyra. Results revealed that the observed atypical lens asymmetry is likely due to more efficient submarine groundwater discharge on the lagoon side as a result of lagoon dredging and filling with high-permeability material. Simulations also predict large decreases (40%) in freshwater lens volume during dry cycles and highlight threats to the Pisonia trees, yielding insight for atoll ecosystem management worldwide.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.143838","usgsCitation":"Briggs, M.A., Cantelon, J., Kurylyk, B., Kulongoski, J.T., Mills, A., and Lane, J., 2021, Small atoll fresh groundwater lenses respond to a combination of natural climatic cycles and human modified geology: Science of the Total Environment, v. 756, 143838, 14 p., https://doi.org/10.1016/j.scitotenv.2020.143838.","productDescription":"143838, 14 p.","ipdsId":"IP-124031","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454244,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.143838","text":"Publisher Index Page"},{"id":381317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Palmyra Atoll","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.11434364318848,\n 5.865525058703975\n ],\n [\n -162.04078674316406,\n 5.865525058703975\n ],\n [\n -162.04078674316406,\n 5.896261485744235\n ],\n [\n -162.11434364318848,\n 5.896261485744235\n ],\n [\n -162.11434364318848,\n 5.865525058703975\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"756","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cantelon, J","contributorId":245723,"corporation":false,"usgs":false,"family":"Cantelon","given":"J","email":"","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":806901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kurylyk, B.","contributorId":222758,"corporation":false,"usgs":false,"family":"Kurylyk","given":"B.","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":806902,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806903,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mills, Audrey","contributorId":245724,"corporation":false,"usgs":false,"family":"Mills","given":"Audrey","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":806904,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, John W. Jr. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":210076,"corporation":false,"usgs":true,"family":"Lane","given":"John W.","suffix":"Jr.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":806905,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70223679,"text":"70223679 - 2021 - Retrospective analysis of estrogenic endocrine disruption and land-use influences in the Chesapeake Bay watershed","interactions":[],"lastModifiedDate":"2021-09-01T13:08:24.257546","indexId":"70223679","displayToPublicDate":"2020-11-19T08:05:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1226,"text":"Chemosphere","active":true,"publicationSubtype":{"id":10}},"title":"Retrospective analysis of estrogenic endocrine disruption and land-use influences in the Chesapeake Bay watershed","docAbstract":"The Chesapeake Bay is the largest estuary in the United States and its watershed includes river drainages in six states and the District of Columbia. Sportfishing is of major economic interest, however, the rivers within the watershed provide numerous other ecological, recreational, cultural and economic benefits, as well as serving as a drinking water source for millions of people. Consequently, major fish kills and the subsequent finding of estrogenic endocrine disruption (intersex or testicular oocytes and plasma vitellogenin in male fishes) raised public and management concerns. Studies have occurred at various sites within the Bay watershed to document the extent and severity of endocrine disruption, identify risk factors and document temporal and spatial variability. Data from these focal studies, which began in 2004, were used in CART (classification and regression trees) analyses to better identify land use associations and potential management practices that influence estrogenic endocrine disruption. These analyses emphasized the importance of scale (immediate versus upstream catchment) and the complex mixtures of stressors which can contribute to surface water estrogenicity and the associated adverse effects of exposure. Both agricultural (percent cultivated, pesticide application, phytoestrogen cover crops) and developed (population density, road density, impervious surface) land cover showed positive relationships to estrogenic indicators, while percent forest and shrubs generally had a negative association. The findings can serve as a baseline for assessing ongoing restoration and management practices.
The occurrence of the 4–6 July 2019 Mw 6.4 and Mw 7.1 Ridgecrest earthquake sequence provided the first full‐scale test of the network and telemetry readiness of the Southern California Seismic Network (SCSN), to support the ShakeAlert earthquake early warning (EEW) system in California. ShakeAlert is a U.S. Geological Survey (USGS)‐led collaboration to detect earthquakes and, when possible, to alert the public before the arrival of the strongest shaking. The SCSN performed well in its regional monitoring role for both the 4 July Mw 6.4 and the 6 July Mw 7.1 earthquakes. In the EEW role, it provided timely delivery of 5 s of P‐wave data to ShakeAlert, which issued its first alert 6.9 s after origin time. Data delivery at peak data volumes for many stations exhibited some latency, and, as a consequence, some data arrived too late for analysis by one of the EEW algorithms. We find that the average link bandwidth for each station was sufficient, because all waveform data were delivered automatically to the archive, but link capacity for many stations was insufficient for peak demand. We describe the performance of the data telemetry for the sequence, including cellular, radio, hybrid, and backhaul systems. Cellular‐based telemetry systems maintained low latency throughout strong shaking and after, but some stations, even at great distances, experienced subsequent brief increases in latency. Performance of radio links depended mostly on the signal strength of the link, with short‐distance direct shots to high‐bandwidth backhaul systems showing no latency impact, whereas stations on some long distance or marginal quality links suffered latencies of tens or hundreds of seconds. Improvements are being implemented to move telemetry links onto USGS and partner high‐bandwidth microwave systems, and to reduce dependency on less robust long‐distance radio shots.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220200211","usgsCitation":"Stubailo, I., Alvarez, M., Biasi, G., Bhadha, R., and Hauksson, E., 2021, Latency of waveform data delivery from the Southern California Seismic Network during the 2019 Ridgecrest earthquake sequence and its effect on ShakeAlert: Seismological Research Letters, v. 92, no. 1, p. 170-186, https://doi.org/10.1785/0220200211.","productDescription":"17 p.","startPage":"170","endPage":"186","ipdsId":"IP-115111","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121,\n 37\n ],\n [\n -121,\n 32\n ],\n [\n -114,\n 32\n ],\n [\n -114,\n 37\n ],\n [\n -121,\n 37\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"92","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Stubailo, Igor 0000-0001-7657-2783","orcid":"https://orcid.org/0000-0001-7657-2783","contributorId":350664,"corporation":false,"usgs":false,"family":"Stubailo","given":"Igor","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":926572,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alvarez, Mark 0000-0002-1361-5616","orcid":"https://orcid.org/0000-0002-1361-5616","contributorId":222021,"corporation":false,"usgs":true,"family":"Alvarez","given":"Mark","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926573,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biasi, Glenn 0000-0003-0940-5488 gbiasi@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-5488","contributorId":195946,"corporation":false,"usgs":true,"family":"Biasi","given":"Glenn","email":"gbiasi@usgs.gov","affiliations":[],"preferred":true,"id":926574,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bhadha, Rayomand","contributorId":350665,"corporation":false,"usgs":false,"family":"Bhadha","given":"Rayomand","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":926575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hauksson, Egill","contributorId":48174,"corporation":false,"usgs":false,"family":"Hauksson","given":"Egill","affiliations":[{"id":27150,"text":"Seismological Laboratory, California Institute of Technology, Pasadena, CA, USA","active":true,"usgs":false}],"preferred":false,"id":926576,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217186,"text":"70217186 - 2021 - The 2018 reawakening and eruption dynamics of Steamboat Geyser, the world’s tallest active geyser","interactions":[],"lastModifiedDate":"2021-01-11T16:11:26.62147","indexId":"70217186","displayToPublicDate":"2020-11-18T10:00:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"The 2018 reawakening and eruption dynamics of Steamboat Geyser, the world’s tallest active geyser","docAbstract":"Steamboat Geyser in Yellowstone National Park’s Norris Geyser Basin began a prolific sequence of eruptions in March 2018 after 34 y of sporadic activity. We analyze a wide range of datasets to explore triggering mechanisms for Steamboat’s reactivation and controls on eruption intervals and height. Prior to Steamboat’s renewed activity, Norris Geyser Basin experienced uplift, a slight increase in radiant temperature, and increased regional seismicity, which may indicate that magmatic processes promoted reactivation. However, because the geothermal reservoir temperature did not change, no other dormant geysers became active, and previous periods with greater seismic moment release did not reawaken Steamboat, the reason for reactivation remains ambiguous. Eruption intervals since 2018 (3.16 to 35.45 d) modulate seasonally, with shorter intervals in the summer. Abnormally long intervals coincide with weakening of a shallow seismic source in the geyser basin’s hydrothermal system. We find no relation between interval and erupted volume, implying unsteady heat and mass discharge. Finally, using data from geysers worldwide, we find a correlation between eruption height and inferred depth to the shallow reservoir supplying water to eruptions. Steamboat is taller because water is stored deeper there than at other geysers, and, hence, more energy is available to power the eruptions.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2020943118","usgsCitation":"Reed, M., Munoz-Saez, C., Hajimirza, S., Wu, S., Barth, A., Girona, T., Rasht-Behesht, M., Karplus, M., Hurwitz, S., and Manga, M., 2021, The 2018 reawakening and eruption dynamics of Steamboat Geyser, the world’s tallest active geyser: PNAS, v. 118, no. 2, e2020943118, 10 p., https://doi.org/10.1073/pnas.2020943118.","productDescription":"e2020943118, 10 p.","ipdsId":"IP-123913","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":454249,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2020943118","text":"Publisher Index Page"},{"id":382060,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Norris Geyser Basin, Steamboat Geyser, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.71465730667114,\n 44.71879196233473\n ],\n [\n -110.6957745552063,\n 44.71879196233473\n ],\n [\n -110.6957745552063,\n 44.73068351783913\n ],\n [\n -110.71465730667114,\n 44.73068351783913\n ],\n [\n -110.71465730667114,\n 44.71879196233473\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"118","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Reed, Mara","contributorId":247557,"corporation":false,"usgs":false,"family":"Reed","given":"Mara","affiliations":[],"preferred":false,"id":807890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munoz-Saez, Carolina","contributorId":131167,"corporation":false,"usgs":false,"family":"Munoz-Saez","given":"Carolina","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":807891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hajimirza, Sahand","contributorId":247558,"corporation":false,"usgs":false,"family":"Hajimirza","given":"Sahand","email":"","affiliations":[],"preferred":false,"id":807892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, Sin-Mei","contributorId":175479,"corporation":false,"usgs":false,"family":"Wu","given":"Sin-Mei","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":807893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barth, Anna","contributorId":247559,"corporation":false,"usgs":false,"family":"Barth","given":"Anna","email":"","affiliations":[],"preferred":false,"id":807894,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Girona, Tarsilo","contributorId":229679,"corporation":false,"usgs":false,"family":"Girona","given":"Tarsilo","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false},{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":true,"id":807895,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rasht-Behesht, Majid","contributorId":247560,"corporation":false,"usgs":false,"family":"Rasht-Behesht","given":"Majid","email":"","affiliations":[],"preferred":false,"id":807896,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Karplus, M.S","contributorId":205767,"corporation":false,"usgs":false,"family":"Karplus","given":"M.S","email":"","affiliations":[{"id":37164,"text":"University of Texas, El Paso","active":true,"usgs":false}],"preferred":false,"id":807897,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":807898,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Manga, Michael","contributorId":131168,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":807899,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ]}