{"pageNumber":"193","pageRowStart":"4800","pageSize":"25","recordCount":40778,"records":[{"id":70236746,"text":"70236746 - 2022 - A graphical causal model for resolving species identity effects and biodiversity–ecosystem function correlations: Reply","interactions":[],"lastModifiedDate":"2022-09-19T11:54:02.485184","indexId":"70236746","displayToPublicDate":"2021-11-20T06:52:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A graphical causal model for resolving species identity effects and biodiversity–ecosystem function correlations: Reply","docAbstract":"

No abstract available.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3593","usgsCitation":"Schoolmaster, D., Zirbel, C.R., and Cronin, J.P., 2022, A graphical causal model for resolving species identity effects and biodiversity–ecosystem function correlations: Reply: Ecology, v. 103, no. 2, e03593, 17 p., https://doi.org/10.1002/ecy.3593.","productDescription":"e03593, 17 p.","ipdsId":"IP-129779","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":406942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"103","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Schoolmaster, Donald 0000-0003-0910-4458","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":202356,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":852077,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zirbel, Chad R 0000-0002-9289-1722","orcid":"https://orcid.org/0000-0002-9289-1722","contributorId":224302,"corporation":false,"usgs":false,"family":"Zirbel","given":"Chad","email":"","middleInitial":"R","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":852078,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cronin, James P. 0000-0001-6791-5828 jcronin@usgs.gov","orcid":"https://orcid.org/0000-0001-6791-5828","contributorId":5834,"corporation":false,"usgs":true,"family":"Cronin","given":"James","email":"jcronin@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":852079,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70226953,"text":"70226953 - 2022 - Correspondence analysis for mineral commodity research: An example workflow for mineralized calderas, southwest United States","interactions":[],"lastModifiedDate":"2022-03-15T16:40:05.579972","indexId":"70226953","displayToPublicDate":"2021-11-19T07:08:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2832,"text":"Natural Resources Research","onlineIssn":"1573-8981","printIssn":"1520-7439","active":true,"publicationSubtype":{"id":10}},"title":"Correspondence analysis for mineral commodity research: An example workflow for mineralized calderas, southwest United States","docAbstract":"

Historical mine and mineral deposit datasets are routinely used to inform quantitative mineral assessment models, but they also can contain a wealth of supplementary qualitative information that is generally underutilized. We present a workflow that uses correspondence analysis, an exploratory tool commonly applied to multivariate abundance data, to better utilize qualitative data in these historical datasets. The workflow involves extraction of qualitative information on ore mineralogy from a mineral deposit database, attaches those data to a target geological feature, and analyzes the underlying data structure with correspondence analysis and hierarchical clustering. The output of correspondence analysis is inversely weighted to the relative frequency of ore minerals, and therefore rare mineral species (i.e., those with unusually low frequencies) can disproportionately contribute to the total variance of the dataset. We present a novel technique for aggregating frequencies of rare mineral species that minimizes this effect. We apply this workflow to evaluate how ore mineral assemblages in former and active mines vary in spatial relation to silicic calderas in the southwestern United States. The most common ore mineral associations observed spatially and genetically associated to calderas include those related to polymetallic, base metal-rich systems and epithermal Au–Ag systems. Three other groups of mineralized calderas were identified, including: (1) Hg–Sb mineralized calderas in the northern Great Basin and western Nevada volcanic field; (2) calderas associated with elevated abundances of Mn oxides/hydroxides, fluorite, and Be-minerals, mostly in eastern Utah and New Mexico; and (3) calderas with numerous U ± F deposits, which are located in central Colorado, the eastern Great Basin and in northern Nevada. The latter three groups are associated with economically significant critical mineral resources, including the Li resources of the McDermitt complex and Be associated with the Spor Mountain on the margin of the Thomas caldera complex. We conclude that correspondence analysis is a promising technique that can enhance data exploration of the qualitative information held within mineral deposit datasets. Consequently, it could have numerous applications for mineral potential mapping, resource assessment projects, and characterization of mineral systems.


","language":"English","publisher":"Springer","doi":"10.1007/s11053-021-09963-w","usgsCitation":"Rosera, J.M., and Coleman, D.S., 2022, Correspondence analysis for mineral commodity research: An example workflow for mineralized calderas, southwest United States: Natural Resources Research, v. 31, p. 9-36, https://doi.org/10.1007/s11053-021-09963-w.","productDescription":"28 p.","startPage":"9","endPage":"36","ipdsId":"IP-130118","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":393297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.541015625,\n 31.12819929911196\n ],\n [\n -102.48046875,\n 31.12819929911196\n ],\n [\n -102.48046875,\n 42.16340342422401\n ],\n [\n -124.541015625,\n 42.16340342422401\n ],\n [\n -124.541015625,\n 31.12819929911196\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","noUsgsAuthors":false,"publicationDate":"2021-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosera, Joshua Mark 0000-0003-3807-5000","orcid":"https://orcid.org/0000-0003-3807-5000","contributorId":270284,"corporation":false,"usgs":true,"family":"Rosera","given":"Joshua","email":"","middleInitial":"Mark","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":828923,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coleman, Drew S","contributorId":192880,"corporation":false,"usgs":false,"family":"Coleman","given":"Drew","email":"","middleInitial":"S","affiliations":[],"preferred":false,"id":828924,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70226722,"text":"70226722 - 2022 - Identifying factors that affect mountain lake sensitivity to atmospheric nitrogen deposition across multiple scales","interactions":[],"lastModifiedDate":"2021-12-07T12:54:56.960495","indexId":"70226722","displayToPublicDate":"2021-11-19T06:46:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Identifying factors that affect mountain lake sensitivity to atmospheric nitrogen deposition across multiple scales","docAbstract":"

Increased nitrogen (N) deposition rates over the past century have affected both North American and European mountain lake ecosystems. Ecological sensitivity of mountain lakes to N deposition varies, however, because chemical and biological responses are modulated by local watershed and lake properties. We evaluated predictors of mountain lake sensitivity to atmospheric N deposition across North American and European mountain ranges and included as response variables dissolved inorganic N (DIN = N\"singleNH4+ + N\"singleNO3–) concentrations and phytoplankton biomass. Predictors of these responses were evaluated at three different spatial scales (hemispheric, regional, subregional) using regression tree, random forest, and generalized additive model (GAM) analysis. Analyses agreed that Northern Hemisphere mountain lake DIN was related to N deposition rates and smaller scale spatial variability (e.g., regional variability between North American and European lakes, and subregional variability between mountain ranges). Analyses suggested that DIN, N deposition, and subregional variability were important for Northern Hemisphere mountain lake phytoplankton biomass. Together, these findings highlight the need for finer-scale, subregional analyses (by mountain range) of lake sensitivity to N deposition. Subregional analyses revealed differences in predictor variables of lake sensitivity. In addition to N deposition rates, lake and watershed features such as land cover, bedrock geology, maximum lake depth (Zmax), and elevation were common modulators of lake DIN. Subregional phytoplankton biomass was consistently positively related with total phosphorus (TP) in Europe, while North American locations showed variable relationships with N or P. This study reveals scale-dependent watershed and lake characteristics modulate mountain lake ecological responses to atmospheric N deposition and provides important context to inform empirically based management strategies.


","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2021.117883","usgsCitation":"Burpee, B., Saros, J., Nanus, L., Baron, J., Brahney, J., Christianson, K., Gantz, T., Heard, A., Hundey, B., Koinig, K., Kopacek, J., Moser, K., Nydick, K., Oleksy, I., Sadro, S., Sommaruga, R., Vinebrooke, R., and Williams, J., 2022, Identifying factors that affect mountain lake sensitivity to atmospheric nitrogen deposition across multiple scales: Water Research, v. 209, 117883, 13 p., https://doi.org/10.1016/j.watres.2021.117883.","productDescription":"117883, 13 p.","ipdsId":"IP-129777","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":392565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"209","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burpee, Benjamin","contributorId":269807,"corporation":false,"usgs":false,"family":"Burpee","given":"Benjamin","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":827955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saros, Jasmine","contributorId":269808,"corporation":false,"usgs":false,"family":"Saros","given":"Jasmine","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":827956,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nanus, Leora","contributorId":269809,"corporation":false,"usgs":false,"family":"Nanus","given":"Leora","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":827957,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baron, Jill S. 0000-0002-5902-6251","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":215101,"corporation":false,"usgs":true,"family":"Baron","given":"Jill S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":827958,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brahney, Janice","contributorId":269810,"corporation":false,"usgs":false,"family":"Brahney","given":"Janice","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":827959,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Christianson, Kyle","contributorId":269811,"corporation":false,"usgs":false,"family":"Christianson","given":"Kyle","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":827960,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gantz, Taylor","contributorId":269812,"corporation":false,"usgs":false,"family":"Gantz","given":"Taylor","email":"","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":827961,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Heard, Andi","contributorId":269813,"corporation":false,"usgs":false,"family":"Heard","given":"Andi","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":827962,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hundey, Beth","contributorId":269814,"corporation":false,"usgs":false,"family":"Hundey","given":"Beth","email":"","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":827963,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Koinig, Karin","contributorId":269815,"corporation":false,"usgs":false,"family":"Koinig","given":"Karin","email":"","affiliations":[{"id":17993,"text":"University of Innsbruck","active":true,"usgs":false}],"preferred":false,"id":827964,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kopacek, Jiri","contributorId":269817,"corporation":false,"usgs":false,"family":"Kopacek","given":"Jiri","email":"","affiliations":[{"id":56037,"text":"České Budějovice, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":827965,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Moser, Katrina","contributorId":269819,"corporation":false,"usgs":false,"family":"Moser","given":"Katrina","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":827966,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Nydick, Koren","contributorId":269821,"corporation":false,"usgs":false,"family":"Nydick","given":"Koren","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":827967,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Oleksy, Isabella A.","contributorId":269822,"corporation":false,"usgs":false,"family":"Oleksy","given":"Isabella A.","affiliations":[{"id":33412,"text":"Cary Institute for Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":827968,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sadro, Steven","contributorId":269824,"corporation":false,"usgs":false,"family":"Sadro","given":"Steven","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":827969,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Sommaruga, Ruben","contributorId":269827,"corporation":false,"usgs":false,"family":"Sommaruga","given":"Ruben","email":"","affiliations":[{"id":17993,"text":"University of Innsbruck","active":true,"usgs":false}],"preferred":false,"id":827970,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Vinebrooke, Rolf","contributorId":269829,"corporation":false,"usgs":false,"family":"Vinebrooke","given":"Rolf","email":"","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":827971,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Williams, Jason","contributorId":269831,"corporation":false,"usgs":false,"family":"Williams","given":"Jason","affiliations":[{"id":6912,"text":"Idaho Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":827972,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70226560,"text":"70226560 - 2022 - Predicting coastal impacts by wave farms: A comparison of wave-averaged and wave-resolving models","interactions":[],"lastModifiedDate":"2021-11-29T11:59:05.179476","indexId":"70226560","displayToPublicDate":"2021-11-19T05:56:11","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9933,"text":"Renewable Energy","active":true,"publicationSubtype":{"id":10}},"title":"Predicting coastal impacts by wave farms: A comparison of wave-averaged and wave-resolving models","docAbstract":"

Wave energy converters (WECs) will have to be arranged into arrays of many devices to extract commercially viable amounts of energy. To understand the potential coastal impacts of WEC arrays, most research to date has relied on wave-averaged models given their computational efficiency. However, it is unknown how accurate wave-averaged model predictions are given a lack of validation data and their inherent simplifications of various hydrodynamic processes (e.g., diffraction). This paper compares the predictions of coastal wave farm impacts from a coupled wave-averaged and flow model (Delft3D-SNL-SWAN), to a wave-resolving wave-flow model (SWASH) that intrinsically accounts for more of the relevant physics. Model predictions were compared using an idealized coastal bathymetry over a range of wave conditions and wave farm geometries. Both models predicted the largest impacts (changes to the nearshore hydrodynamics) for large and dense wave farms located close to the shore (1 km) and the smallest impacts for the small and widely spaced farm at a greater offshore distance (3 km). However, the wave-resolving model generally predicted somewhat larger impacts (i.e., changes to the nearshore wave heights, mean velocities and mean water levels). We also found that coupling the wave-averaged model to a flow model resulted in more realistic downstream predictions than the stand-alone wave-averaged model.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.renene.2021.11.048","usgsCitation":"David, D.R., Rijnsdorp, D.P., Hansen, J., Lowe, R.J., and Buckley, M.L., 2022, Predicting coastal impacts by wave farms: A comparison of wave-averaged and wave-resolving models: Renewable Energy, v. 183, p. 764-780, https://doi.org/10.1016/j.renene.2021.11.048.","productDescription":"17 p.","startPage":"764","endPage":"780","ipdsId":"IP-127957","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":392172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"183","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"David, Daniel R.","contributorId":269522,"corporation":false,"usgs":false,"family":"David","given":"Daniel","email":"","middleInitial":"R.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":827356,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rijnsdorp, Dirk P.","contributorId":261463,"corporation":false,"usgs":false,"family":"Rijnsdorp","given":"Dirk","email":"","middleInitial":"P.","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":827357,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Jeff E.","contributorId":146437,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff E.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":827358,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lowe, Ryan J.","contributorId":152265,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":827359,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":827360,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229753,"text":"70229753 - 2022 - Combining fixed-location count data and movement data to estimate abundance of a lake sturgeon spawning run","interactions":[],"lastModifiedDate":"2022-06-01T15:13:31.917051","indexId":"70229753","displayToPublicDate":"2021-11-18T10:02:32","publicationYear":"2022","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":"Combining fixed-location count data and movement data to estimate abundance of a lake sturgeon spawning run","docAbstract":"

Estimating abundance of migrating fishes is challenging. While sonars can be deployed continuously, improper assumptions about unidirectional migration and complete spatial coverage can lead to inaccurate estimates. To address these challenges, we present a framework for combining fixed-location count data from a dual-frequency identification sonar (DIDSON) with movement data from acoustic telemetry to estimate spawning run abundance of lake sturgeon (Acipenser fulvescens). Acoustic telemetry data were used to estimate the probability of observing a lake sturgeon on the DIDSON and to determine the probability that a lake sturgeon passing the DIDSON site had passed the site previously during the season. Combining probabilities with DIDSON counts, using a Bayesian integrated model, we estimated the following abundances: 99 (42–215 credible interval, CI) in 2017, 131 (82–248 CI) in 2018, and 92 (47–184 CI) in 2019. Adding movement data generated better inferences on count data by incorporating fish behavior (e.g., multiple migrations in a single season) and its uncertainty into abundance estimates. This framework can be applied to count and movement data to estimate abundance of spawning runs of other migratory fishes in riverine systems.

","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2021-0140","usgsCitation":"Izzo, L., Zydlewski, G.B., and Parrish, D.L., 2022, Combining fixed-location count data and movement data to estimate abundance of a lake sturgeon spawning run: Canadian Journal of Fisheries and Aquatic Sciences, v. 79, no. 6, p. 925-935, https://doi.org/10.1139/cjfas-2021-0140.","productDescription":"11 p.","startPage":"925","endPage":"935","ipdsId":"IP-127748","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":449533,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/51632","text":"External Repository"},{"id":397240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Winooski River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.28910827636717,\n 44.3768766587829\n ],\n [\n -72.93342590332031,\n 44.3768766587829\n ],\n [\n -72.93342590332031,\n 44.54448397425684\n ],\n [\n -73.28910827636717,\n 44.54448397425684\n ],\n [\n -73.28910827636717,\n 44.3768766587829\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"79","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Izzo, Lisa K.","contributorId":288673,"corporation":false,"usgs":false,"family":"Izzo","given":"Lisa K.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":838211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zydlewski, Gayle Barbin","contributorId":288674,"corporation":false,"usgs":false,"family":"Zydlewski","given":"Gayle","email":"","middleInitial":"Barbin","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":838212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":838210,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70226893,"text":"70226893 - 2022 - Directional selection shifts trait distributions of planted species in dryland restoration","interactions":[],"lastModifiedDate":"2022-03-28T16:31:35.115055","indexId":"70226893","displayToPublicDate":"2021-11-18T06:28:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Directional selection shifts trait distributions of planted species in dryland restoration","docAbstract":"
  1. The match between species trait values and local abiotic filters can restrict community membership. An often-implicit assumption of this relationship is that abiotic filters select for a single locally optimal strategy, though difficulty in isolating effects of the abiotic environment from those of dispersal limitation and biotic interactions has resulted in few empirical tests of this assumption. Similar constraints have made it difficult to assess whether the type and intensity of abiotic filters shift along gradients of environmental harshness, as predicted by the stress-dominance hypothesis.
  2. We planted 9,216 plants of 29 perennial grass and forb species that had a range of functional trait values and were assigned to a warm, intermediate or cool temperature tolerance pool across eight sites on the Colorado Plateau. We compared the distributions of traits of surviving individuals to null distributions to evaluate whether there were shifts in trait means and variation. Borrowing from phenotypic selection concepts in evolutionary biology, we assessed support for stabilizing, directional and disruptive abiotic filtering of trait distributions and whether these types of filtering varied with initial species pool.
  3. Functional composition was significantly different from null distributions for nearly all traits at all sites, with trait variation more restricted in harsher abiotic conditions, supporting the stress-dominance hypothesis. Contrary to expectations, we primarily found evidence for directional selection, which increased in frequency in warm species pools while disruptive selection was found more often in cool and intermediate species pools.
  4. Synthesis. This study provides a controlled experimental approach to test the effect of the abiotic environment on plant trait filtering. We found that opportunistic strategies allowing for rapid water acquisition during favourable periods improved survival at warmer sites. Species with these strategies may be expected to benefit from increasing aridity and may be selected for active management efforts. More generally, the prevalence of directional selection may have important implications for dynamic vegetation models that rely on trait distributions for translating environmental variation into ecosystem processes.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2745.13816","usgsCitation":"Balazs, K.R., Munson, S.M., Havrilla, C.A., and Butterfield, B.J., 2022, Directional selection shifts trait distributions of planted species in dryland restoration: Journal of Ecology, v. 110, no. 3, p. 540-552, https://doi.org/10.1111/1365-2745.13816.","productDescription":"13 p.","startPage":"540","endPage":"552","ipdsId":"IP-126175","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":449538,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":393088,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"110","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Balazs, Kathleen R.","contributorId":223214,"corporation":false,"usgs":false,"family":"Balazs","given":"Kathleen","email":"","middleInitial":"R.","affiliations":[{"id":24810,"text":"Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":828669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":828670,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Havrilla, Caroline Ann 0000-0003-3913-0980","orcid":"https://orcid.org/0000-0003-3913-0980","contributorId":228882,"corporation":false,"usgs":true,"family":"Havrilla","given":"Caroline","email":"","middleInitial":"Ann","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":828671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":828672,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265770,"text":"70265770 - 2022 - New insights on faulting and intrusion processes during the June 2007, East Rift Zone eruption of Kilauea volcano, Hawai'i","interactions":[],"lastModifiedDate":"2025-04-16T13:17:34.472644","indexId":"70265770","displayToPublicDate":"2021-11-12T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"New insights on faulting and intrusion processes during the June 2007, East Rift Zone eruption of Kilauea volcano, Hawai'i","docAbstract":"

The East Rift Zone (ERZ) of Kīlauea Volcano, Hawai'i, represents one of the most volcanically active regions in the world. The 2007 Father's Day (FD) dike intrusion, eruption, and accompanying slow-slip event (SSE) has been previously modeled using geodetic data to constrain the geometry of the intrusion and the timing and magnitude of the SSE. Here, we perform inversions of three interferometric synthetic aperture radar (InSAR) datasets and a new intensity offset tracking dataset to assess the effect of integrating intensity cross-correlation offsets into inversion problems and explore additional potential models for the intrusion geometry of the FD event based on this additional data. The overall lowest misfit single Okada model for all datasets opens 2.3 m, strikes 73 degrees while dipping sub-vertically at 83 degrees, and extends approximately 2.9 km to the ENE and 2.4 km downdip. The differences are minor between complex en-echelon distributed Okada and decollement model of (Montgomery-Brown et al., 2010) or 3D-MBEM breaching models including multiple surface breaches and free-slipping decollement movement. Finally, we examine the static Coulomb stress changes for the proposed decollement fault created by our preferred model and a representative model of deep rift opening and find that deep rift zones dilation, not shallow ERZ intrusions, are likely modulating slip on the decollement.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107425","usgsCitation":"Leeburn, J., Wauthier, C., Montgomery-Brown, E.K., and Gonzalez-Santana, J., 2022, New insights on faulting and intrusion processes during the June 2007, East Rift Zone eruption of Kilauea volcano, Hawai'i: Journal of Volcanology and Geothermal Research, v. 421, 107425, 14 p., https://doi.org/10.1016/j.jvolgeores.2021.107425.","productDescription":"107425, 14 p.","ipdsId":"IP-125424","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488262,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2021.107425","text":"Publisher Index Page"},{"id":484584,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.2908512348302,\n 19.41341967491155\n ],\n [\n -155.2908512348302,\n 19.401793724963014\n ],\n [\n -155.27525765813795,\n 19.401793724963014\n ],\n [\n -155.27525765813795,\n 19.41341967491155\n ],\n [\n -155.2908512348302,\n 19.41341967491155\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"421","noUsgsAuthors":false,"publicationDate":"2021-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Leeburn, J.","contributorId":353406,"corporation":false,"usgs":false,"family":"Leeburn","given":"J.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":933489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wauthier, C.","contributorId":353409,"corporation":false,"usgs":false,"family":"Wauthier","given":"C.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":933490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Montgomery-Brown, Emily K. 0000-0001-6787-2055","orcid":"https://orcid.org/0000-0001-6787-2055","contributorId":214074,"corporation":false,"usgs":true,"family":"Montgomery-Brown","given":"Emily","email":"","middleInitial":"K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":933491,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gonzalez-Santana, J.","contributorId":353412,"corporation":false,"usgs":false,"family":"Gonzalez-Santana","given":"J.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":933492,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70226473,"text":"70226473 - 2022 - An evaluation of the timing accuracy of global and regional seismic stations and networks","interactions":[],"lastModifiedDate":"2022-01-06T17:31:51.70211","indexId":"70226473","displayToPublicDate":"2021-11-10T07:36:44","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"An evaluation of the timing accuracy of global and regional seismic stations and networks","docAbstract":"

Clock accuracy is a basic parameter of any seismic station and has become increasingly important for seismology as the community seeks to refine structures and dynamic processes of the Earth. In this study, we measure the arrival time differences of moderate repeating earthquakes with magnitude 5.0–5.9 in the time range of 1991–2017 at the same seismic stations by cross‐correlating their highly similar waveforms and thereby identify potential timing errors from the outliers of the measurements. The method has very high precision of about 10 ms and shows great potential to be used for routine inspection of the timing accuracy of historical and future digital seismic data. Here, we report 5131 probable cases of timing errors from 451 global and regional stations available from the Incorporated Research Institutions for Seismology Data Management Center, ranging from several tens of milliseconds to over 10 s. Clock accuracy seems to be a prevailing problem in permanent stations with long‐running histories. Although most of the timing errors have already been tagged with low timing quality, there are quite a few exceptions, which call for greater attention from network operators and the seismological community. In addition, seismic studies, especially those on temporal changes of the Earth’s media from absolute arrival times, should be careful to avoid misinterpreting timing errors as temporal changes, which is indeed a problem in some previous studies of the Earth’s inner core boundary.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220210232","usgsCitation":"Yang, Y., Song, X., and Ringler, A.T., 2022, An evaluation of the timing accuracy of global and regional seismic stations and networks: Seismological Research Letters, v. 93, no. 1, p. 161-172, https://doi.org/10.1785/0220210232.","productDescription":"12 p.","startPage":"161","endPage":"172","ipdsId":"IP-133453","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":391915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"93","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Yang, Ying","contributorId":146330,"corporation":false,"usgs":false,"family":"Yang","given":"Ying","email":"","affiliations":[{"id":16673,"text":"Bond Life Sciences Center, University of Missouri, Columbia, MO","active":true,"usgs":false}],"preferred":false,"id":827036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Song, Xiaodong","contributorId":269403,"corporation":false,"usgs":false,"family":"Song","given":"Xiaodong","email":"","affiliations":[{"id":55969,"text":"Institute of Theoretical and Applied Geophysics, Peking University, Beijing, China; Hebei Hongshan Geophysical National Observation and Research Station, Peking University, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":827037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":3946,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":827038,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70226614,"text":"70226614 - 2022 - Riverscape approaches in practice: Perspectives and applications","interactions":[],"lastModifiedDate":"2022-03-15T16:16:03.600707","indexId":"70226614","displayToPublicDate":"2021-11-10T06:49:44","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1023,"text":"Biological Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Riverscape approaches in practice: Perspectives and applications","docAbstract":"

Landscape perspectives in riverine ecology have been undertaken increasingly in the last 30 years, leading aquatic ecologists to develop a diverse set of approaches for conceptualizing, mapping and understanding ‘riverscapes’. Spatiotemporally explicit perspectives of rivers and their biota nested within the socio-ecological landscape now provide guiding principles and approaches in inland fisheries and watershed management. During the last two decades, scientific literature on riverscapes has increased rapidly, indicating that the term and associated approaches are serving an important purpose in freshwater science and management. We trace the origins and theoretical foundations of riverscape perspectives and approaches and examine trends in the published literature to assess the state of the science and demonstrate how they are being applied to address recent challenges in the management of riverine ecosystems. We focus on approaches for studying and visualizing rivers and streams with remote sensing, modelling and sampling designs that enable pattern detection as seen from above (e.g. river channel, floodplain, and riparian areas) but also into the water itself (e.g. aquatic organisms and the aqueous environment). Key concepts from landscape ecology that are central to riverscape approaches are heterogeneity, scale (resolution, extent and scope) and connectivity (structural and functional), which underpin spatial and temporal aspects of study design, data collection and analysis. Mapping of physical and biological characteristics of rivers and floodplains with high-resolution, spatially intensive techniques improves understanding of the causes and ecological consequences of spatial patterns at multiple scales. This information is crucial for managing river ecosystems, especially for the successful implementation of conservation, restoration and monitoring programs. Recent advances in remote sensing, field-sampling approaches and geospatial technology are making it increasingly feasible to collect high-resolution data over larger scales in space and time. We highlight challenges and opportunities and discuss future avenues of research with emerging tools that can potentially help to overcome obstacles to collecting, analysing and displaying these data. This synthesis is intended to help researchers and resource managers understand and apply these concepts and approaches to address real-world problems in freshwater management.

","language":"English","publisher":"Wiley","doi":"10.1111/brv.12810","usgsCitation":"Torgersen, C.E., Le Pichon, C., Fullerton, A.H., Dugdale, S.J., Duda, J.J., Giovannini, F., Tales, E., Belliard, J., Branco, P., Bergeron, N.E., Roy, M.L., Tonolla, D., Lamouroux, N., Capra, H., and Baxter, C.V., 2022, Riverscape approaches in practice: Perspectives and applications: Biological Reviews, v. 97, no. 2, p. 481-504, https://doi.org/10.1111/brv.12810.","productDescription":"24 p.","startPage":"481","endPage":"504","ipdsId":"IP-126568","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":449553,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.inrae.fr/hal-03523099","text":"External Repository"},{"id":392293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":827492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Le Pichon, Celine","contributorId":177136,"corporation":false,"usgs":false,"family":"Le Pichon","given":"Celine","email":"","affiliations":[],"preferred":false,"id":827493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fullerton, Aimee H.","contributorId":146936,"corporation":false,"usgs":false,"family":"Fullerton","given":"Aimee","email":"","middleInitial":"H.","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":827494,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dugdale, Stephen J.","contributorId":269592,"corporation":false,"usgs":false,"family":"Dugdale","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":56000,"text":"School of Geography, University of Nottingham, University Park, Nottingham, NG7 2RD, UK","active":true,"usgs":false}],"preferred":false,"id":827495,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":827496,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Giovannini, Floriane","contributorId":269593,"corporation":false,"usgs":false,"family":"Giovannini","given":"Floriane","email":"","affiliations":[{"id":56001,"text":"INRAE, DRISE (Department of Research, Economic Intelligence, Strategy and Evaluation), 1 rue Pierre-Gilles de Gennes, CS 10030, 92761 Antony, France","active":true,"usgs":false}],"preferred":false,"id":827497,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tales, Evelyne","contributorId":177137,"corporation":false,"usgs":false,"family":"Tales","given":"Evelyne","email":"","affiliations":[],"preferred":false,"id":827498,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Belliard, Jerome","contributorId":177138,"corporation":false,"usgs":false,"family":"Belliard","given":"Jerome","email":"","affiliations":[],"preferred":false,"id":827499,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Branco, Paulo","contributorId":269594,"corporation":false,"usgs":false,"family":"Branco","given":"Paulo","email":"","affiliations":[{"id":56002,"text":"Centro de Estudos Florestais, Instituto Superior de Agronomia, Universidade de Lisboa, 1349-017 Lisboa, Portugal","active":true,"usgs":false}],"preferred":false,"id":827500,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bergeron, Normand E.","contributorId":173374,"corporation":false,"usgs":false,"family":"Bergeron","given":"Normand","email":"","middleInitial":"E.","affiliations":[{"id":27216,"text":"INRS, Quebec","active":true,"usgs":false}],"preferred":false,"id":827501,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Roy, Mathieu L.","contributorId":269595,"corporation":false,"usgs":false,"family":"Roy","given":"Mathieu","email":"","middleInitial":"L.","affiliations":[{"id":56004,"text":"INRS (Institut national de la recherche scientifique), Centre Eau Terre Environnement, 490, rue de la Couronne, Québec (Québec) G1K 9A9, Canada","active":true,"usgs":false}],"preferred":false,"id":827502,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Tonolla, Diego","contributorId":150694,"corporation":false,"usgs":false,"family":"Tonolla","given":"Diego","email":"","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":827503,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lamouroux, Nicolas","contributorId":269596,"corporation":false,"usgs":false,"family":"Lamouroux","given":"Nicolas","email":"","affiliations":[{"id":56005,"text":"INRAE, UR RIVERLY, 5 rue de la Doua, BP 32108, 69616 Villeurbanne Cedex, France","active":true,"usgs":false}],"preferred":false,"id":827504,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Capra, Herve","contributorId":269597,"corporation":false,"usgs":false,"family":"Capra","given":"Herve","email":"","affiliations":[{"id":56005,"text":"INRAE, UR RIVERLY, 5 rue de la Doua, BP 32108, 69616 Villeurbanne Cedex, France","active":true,"usgs":false}],"preferred":false,"id":827505,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Baxter, Colden V.","contributorId":172293,"corporation":false,"usgs":false,"family":"Baxter","given":"Colden","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":827506,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70229158,"text":"70229158 - 2022 - Proportions, timing, and re-equilibration progress during the 1959 Summit Eruption of Kīlauea: An example of magma mixing processes operating during OIB petrogenesis","interactions":[],"lastModifiedDate":"2022-03-01T12:45:14.255925","indexId":"70229158","displayToPublicDate":"2021-11-04T06:42:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2420,"text":"Journal of Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Proportions, timing, and re-equilibration progress during the 1959 Summit Eruption of Kīlauea: An example of magma mixing processes operating during OIB petrogenesis","docAbstract":"

Petrographic and chemical analysis of scoria samples collected during the 1959 Kīlauea summit eruption illustrates the progress of thermal and chemical homogenization of the melts, and the gradual growth and/or re-equilibration of olivine phenocrysts, over the course of the eruption. Glass compositions show that thermal equilibration was largely complete within the span of the eruption, whereas chemical homogenization was a work in progress. The olivine phenocryst population, known to contain conspicuous antecrystic components, is also hybrid within the euhedral population. The bulk of the olivine reached the level of the erupting magma on November 18–19, 1959. Zoning patterns in olivine phenocrysts show that initially unzoned grains developed normal zoning by the end of the eruption. Reverse zoning in relatively Fe-rich olivine phenocrysts (interpreted as cognate to the stored magma) was progressively eliminated from November 21 to December 19, 1959, by diffusive re-equilibration between crystals and melt. Toward the end of the eruption, the only olivine composition in direct contact with the melt was Fo84–86, with the original rim compositional heterogeneity gone in 4–5 weeks’ time. Activity in December 1959 differed from that in November, as high fountaining events were more closely spaced and almost all samples were picritic, with bulk MgO ≥16·5 wt%. Three different levels were in play during the 1959 eruption: a deep source for high-MgO melts and forsteritic (Fo87–89) olivines, an intermediate source for the bulk of the stored magma, and a shallower source for the most differentiated magma. This model is consistent with geophysical, petrological and chemical observations. Comparison of the 1959 eruption with results from older explosive deposits suggests that stored and recharge melts and olivine from the deeper parts of Kīlauea’s plumbing are similar in composition to those observed or inferred in the 1959 eruption, so they behave similarly during extrusive and explosive periods alike.

","language":"English","publisher":"Oxford University Press","doi":"10.1093/petrology/egab091","usgsCitation":"Helz, R.L., 2022, Proportions, timing, and re-equilibration progress during the 1959 Summit Eruption of Kīlauea: An example of magma mixing processes operating during OIB petrogenesis: Journal of Petrology, v. 63, no. 1, egab091, 22 p., https://doi.org/10.1093/petrology/egab091.","productDescription":"egab091, 22 p.","ipdsId":"IP-118456","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":396590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.35354614257812,\n 19.361680514501174\n ],\n [\n -155.17364501953125,\n 19.361680514501174\n ],\n [\n -155.17364501953125,\n 19.467887015196908\n ],\n [\n -155.35354614257812,\n 19.467887015196908\n ],\n [\n -155.35354614257812,\n 19.361680514501174\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"63","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Helz, Rosalind L. 0000-0003-1550-0684 rhelz@usgs.gov","orcid":"https://orcid.org/0000-0003-1550-0684","contributorId":1952,"corporation":false,"usgs":true,"family":"Helz","given":"Rosalind","email":"rhelz@usgs.gov","middleInitial":"L.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":836801,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70225685,"text":"70225685 - 2022 - Estimating abundance, temporary emigration and the pattern of density dependence in a cyclic snowshoe hare population in Yukon, Canada","interactions":[],"lastModifiedDate":"2022-01-25T17:09:13.595621","indexId":"70225685","displayToPublicDate":"2021-11-03T08:07:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating abundance, temporary emigration and the pattern of density dependence in a cyclic snowshoe hare population in Yukon, Canada","docAbstract":"
Estimates of demographic parameters based on capture-mark-recapture (CMR) methods may be biased when some individuals in the population are temporarily unavailable for capture (temporary emigration). We estimated snowshoe hare abundance, apparent survival, and probability of temporary emigration in a population of snowshoe hares (Lepus americanus Erxleben 1777) in the Yukon using Pollock’s robust design CMR model, and population density using spatially-explicit CMR models. Survival rates strongly varied among cyclic phases, seasons, and across five population cycles. We found strong evidence that temporary emigration was Markovian (i.e., non-random), suggesting that it varied among individuals that were temporary emigrant in the previous sampling period and those that were present in the sampled area. The probability of temporary emigration for individuals that were in the study area during the previous sampling occasion (γ´´) varied among cycles. Probability that individuals that were temporarily absent from the sampled area would remain temporary emigrants (γ´) showed strongly seasonal pattern, low in winter and high during summers. Snowshoe hare population density ranged from 0.017 (0.015–0.05) hares/ha to 4.43 (3.90–5.00) hares/ha and large-scale cyclical fluctuation. Autocorrelation functions and autoregressive analyses revealed that our study population exhibited statistically significant cyclic fluctuations, with a periodicity of 9-10 years.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjz-2021-0139","usgsCitation":"Oli, M.K., Kenny, A.J., Boonstra, R., Boutin, S., Chaudhary, V., Hines, J.E., and Krebs, C., 2022, Estimating abundance, temporary emigration and the pattern of density dependence in a cyclic snowshoe hare population in Yukon, Canada: Canadian Journal of Zoology, v. 100, no. 1, p. 36-45, https://doi.org/10.1139/cjz-2021-0139.","productDescription":"10 p.","startPage":"36","endPage":"45","ipdsId":"IP-127809","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":449562,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjz-2021-0139","text":"External Repository"},{"id":391314,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Yukon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -140.2734375,\n 60.37042901631508\n ],\n [\n -138.69140625,\n 60.06484046010452\n ],\n [\n -123.48632812499999,\n 60.06484046010452\n ],\n [\n -124.541015625,\n 60.88770004207789\n ],\n [\n -126.5625,\n 60.930432202923335\n ],\n [\n -128.583984375,\n 62.226996036319726\n ],\n [\n -131.1328125,\n 64.28275952823394\n ],\n [\n -132.451171875,\n 65.44000165965534\n ],\n [\n -133.2421875,\n 66.33750501996518\n ],\n [\n -133.9453125,\n 67.06743335108298\n ],\n [\n -135.615234375,\n 67.1016555307692\n ],\n [\n -136.40625,\n 68.78414378041504\n ],\n [\n -138.955078125,\n 69.68761843185617\n ],\n [\n -141.240234375,\n 69.77895177646761\n ],\n [\n -141.328125,\n 60.457217797743944\n ],\n [\n -140.2734375,\n 60.37042901631508\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"100","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oli, Madan K. 0000-0001-6944-0061","orcid":"https://orcid.org/0000-0001-6944-0061","contributorId":201302,"corporation":false,"usgs":false,"family":"Oli","given":"Madan","email":"","middleInitial":"K.","affiliations":[{"id":13453,"text":"University of Florida, Gainesville, FL","active":true,"usgs":false}],"preferred":false,"id":826244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kenny, Alice J","contributorId":268237,"corporation":false,"usgs":false,"family":"Kenny","given":"Alice","email":"","middleInitial":"J","affiliations":[{"id":55604,"text":"Univ. of British Columbia","active":true,"usgs":false}],"preferred":false,"id":826245,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boonstra, Rudy","contributorId":223009,"corporation":false,"usgs":false,"family":"Boonstra","given":"Rudy","affiliations":[],"preferred":false,"id":826246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boutin, Stan","contributorId":223010,"corporation":false,"usgs":false,"family":"Boutin","given":"Stan","email":"","affiliations":[],"preferred":false,"id":826247,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chaudhary, Vratika 0000-0001-7155-122X","orcid":"https://orcid.org/0000-0001-7155-122X","contributorId":238946,"corporation":false,"usgs":false,"family":"Chaudhary","given":"Vratika","email":"","affiliations":[{"id":47827,"text":"Univ. of FL.","active":true,"usgs":false}],"preferred":false,"id":826248,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":826249,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Krebs, Charles J","contributorId":146456,"corporation":false,"usgs":false,"family":"Krebs","given":"Charles J","affiliations":[{"id":16701,"text":"Dept. of Zoology, University of British Columbia, Vancouver","active":true,"usgs":false}],"preferred":false,"id":826250,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70226446,"text":"70226446 - 2022 - Magmatism, migrating topography, and the transition from Sevier shortening to Basin and Range extension, western United States","interactions":[],"lastModifiedDate":"2021-11-19T12:56:53.852331","indexId":"70226446","displayToPublicDate":"2021-11-02T07:06:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"Magmatism, migrating topography, and the transition from Sevier shortening to Basin and Range extension, western United States","docAbstract":"

The paleogeographic evolution of the western U.S. Great Basin from the Late Cretaceous to the Cenozoic is critical to understanding how the North American Cordillera at this latitude transitioned from Mesozoic shortening to Cenozoic extension. According to a widely applied model, Cenozoic extension was driven by collapse of elevated crust supported by crustal thicknesses that were potentially double the present ~30–35 km. This model is difficult to reconcile with more recent estimates of moderate regional extension (≤50%) and the discovery that most high-angle, Basin and Range faults slipped rapidly ca. 17 Ma, tens of millions of years after crustal thickening occurred. Here, we integrated new and existing geochronology and geologic mapping in the Elko area of northeast Nevada, one of the few places in the Great Basin with substantial exposures of Paleogene strata. We improved the age control for strata that have been targeted for studies of regional paleoelevation and paleoclimate across this critical time span. In addition, a regional compilation of the ages of material within a network of middle Cenozoic paleodrainages that developed across the Great Basin shows that the age of basal paleovalley fill decreases southward roughly synchronous with voluminous ignimbrite flareup volcanism that swept south across the region ca. 45–20 Ma. Integrating these data sets with the regional record of faulting, sedimentation, erosion, and magmatism, we suggest that volcanism was accompanied by an elevation increase that disrupted drainage systems and shifted the continental divide east into central Nevada from its Late Cretaceous location along the Sierra Nevada arc. The north-south Eocene–Oligocene drainage divide defined by mapping of paleovalleys may thus have evolved as a dynamic feature that propagated southward with magmatism. Despite some local faulting, the northern Great Basin became a vast, elevated volcanic tableland that persisted until dissection by Basin and Range faulting that began ca. 21–17 Ma. Based on this more detailed geologic framework, it is unlikely that Basin and Range extension was driven by Cretaceous crustal overthickening; rather, preexisting crustal structure was just one of several factors that that led to Basin and Range faulting after ca. 17 Ma—in addition to thermal weakening of the crust associated with Cenozoic magmatism, thermally supported elevation, and changing boundary conditions. Because these causal factors evolved long after crustal thickening ended, during final removal and fragmentation of the shallowly subducting Farallon slab, they are compatible with normal-thickness (~45–50 km) crust beneath the Great Basin prior to extension and do not require development of a strongly elevated, Altiplano-like region during Mesozoic shortening.

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\"}}]}","volume":"555","issue":"13","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lundstern, Jens-Erik 0000-0003-0000-8013","orcid":"https://orcid.org/0000-0003-0000-8013","contributorId":264189,"corporation":false,"usgs":true,"family":"Lundstern","given":"Jens-Erik","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":826935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Elizabeth L. 0000-0002-6190-4826","orcid":"https://orcid.org/0000-0002-6190-4826","contributorId":269348,"corporation":false,"usgs":false,"family":"Miller","given":"Elizabeth","email":"","middleInitial":"L.","affiliations":[{"id":55934,"text":"Stanford University Department of Geological Sciences","active":true,"usgs":false}],"preferred":false,"id":826936,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70228802,"text":"70228802 - 2022 - Natural inactivation of MS2, poliovirus type 1 and Cryptosporidium parvum in an anaerobic and reduced aquifer","interactions":[],"lastModifiedDate":"2022-02-22T13:16:37.319102","indexId":"70228802","displayToPublicDate":"2021-11-01T07:13:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2169,"text":"Journal of Applied Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Natural inactivation of MS2, poliovirus type 1 and Cryptosporidium parvum in an anaerobic and reduced aquifer","docAbstract":"

Aims

The study of microbial inactivation rates in aquifer systems has most often been determined in aerobic and oxidized systems. This study examined the inactivation (i.e. loss of infectivity) of MS2, poliovirus type 1 (PV1) and Cryptosporidium parvum in an anaerobic and reduced groundwater system that has been identified as storage zones for aquifer storage and recovery (ASR) facilities.

Methods and Results

Anaerobic and reduced (ORP < −250 mV) groundwater from an artesian well was diverted to an above-ground, flow-through mesocosm that contained diffusion chambers filled with MS2, PV1 or Cryptosporidium parvum. The respective infectivity assays were performed on microorganisms recovered from the diffusion chambers during 30- to 58-day experiments. The net reduction in infectivity was 5.73 log10 over 30 days for MS2, 5.00 log10 over 58 days for PV1 and 4.07 log10 over 37 days for C. parvum. The best fit inactivation model for PV1 was the log-linear model and the Weibull model for MS2 and C. parvum, with respective inactivation rates (95% confidence interval) of 0.19 (0.17–0.21) log10 day−1, 0.31 (0.19–0.89) log10 day−1 and 0.20 (0.14–0.37) log10 day−1.

Conclusions

The groundwater geochemical conditions in this aquifer enhanced the inactivation of MS2, PV1, and C. parvum at rates approximately 2.0–5.3-fold, 1.2–17.0-fold, and 4.5–5.6-fold greater, respectively, than those from published studies that used diffusion chambers in aerobic-to-anoxic groundwater systems, with positive redox potentials.

Significance and Impact of the Study

Geochemical conditions like those in the aquifer zone in this study can naturally and significantly reduce concentrations of microbial indicators and pathogens of human health concern in injected surface water. Appropriate storage times for injected surface water could complement above-ground engineered processes for microorganism removal and inactivation (e.g. filtration, disinfection) by naturally increasing overall microorganism log-inactivation rates of ASR facilities.

","language":"English","publisher":"Wiley","doi":"10.1111/jam.15349","usgsCitation":"Lisle, J.T., and Lukasic, G., 2022, Natural inactivation of MS2, poliovirus type 1 and Cryptosporidium parvum in an anaerobic and reduced aquifer: Journal of Applied Microbiology, v. 132, no. 3, p. 2464-2474, https://doi.org/10.1111/jam.15349.","productDescription":"11 p.","startPage":"2464","endPage":"2474","ipdsId":"IP-131012","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":396232,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"132","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Lisle, John T. 0000-0002-5447-2092 jlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-5447-2092","contributorId":2944,"corporation":false,"usgs":true,"family":"Lisle","given":"John","email":"jlisle@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":835536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lukasic, Geroge","contributorId":279834,"corporation":false,"usgs":false,"family":"Lukasic","given":"Geroge","email":"","affiliations":[{"id":57372,"text":"BCS Laboratories, Inc., Gainesville, FL","active":true,"usgs":false}],"preferred":false,"id":835537,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70226137,"text":"70226137 - 2022 - Tree mortality response to drought-density interactions suggests opportunities to enhance drought resistance","interactions":[],"lastModifiedDate":"2022-02-15T16:08:05.671364","indexId":"70226137","displayToPublicDate":"2021-11-01T06:53:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9913,"text":"Journal of Applied Ecology.","active":true,"publicationSubtype":{"id":10}},"title":"Tree mortality response to drought-density interactions suggests opportunities to enhance drought resistance","docAbstract":"

The future of dry forests around the world is uncertain given predictions that rising temperatures and enhanced aridity will increase drought-induced tree mortality. Using forest management and ecological restoration to reduce density and competition for water offers one of the few pathways that forests managers can potentially minimize drought-induced tree mortality. Competition for water during drought leads to elevated tree mortality in dense stands, although the influence of density on heat-induced stress, and the durations of hot or dry conditions that most impact mortality, remain unclear.

Understanding how competition interacts with hot-drought stress is essential to recognize how, where, and how much reducing density can help sustain dry forests in a rapidly changing world. Here, we integrated repeat measurements of 28,881 ponderosa pine trees across the western US (2000-2017) with soil moisture estimates from a water balance model to examine how annual mortality responds to competition, temperature and soil moisture conditions.

Tree mortality responded most strongly to basal area, and was elevated in places with high mean temperatures, unusually hot 7-year high temperature anomalies, and unusually dry 8-year low soil moisture anomalies. Mortality was also lower in places that experienced unusually wet 3-year soil moisture anomalies between measurements. Importantly, we found that basal area interacts with temperature and soil moisture, exacerbating mortality during times of stress imposed by high temperature or low moisture.

Synthesis and Applications: Our results imply that a 50% reduction in forest basal area could reduce drought-driven tree mortality by 20-80%. The largest impacts of density reduction are seen in areas with high current basal area and places that experience high temperatures and/or severe multiyear droughts. These interactions between competition and drought are critical to understand past and future patterns of tree mortality in the context of climate change, and provide information for resource managers seeking to enhance dry forest drought resistance.

","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.14073","usgsCitation":"Bradford, J., Shriver, R.K., Robles, M.D., McCauley, L., Andrews, C.M., Crimmins, M.A., and Bell, D.M., 2022, Tree mortality response to drought-density interactions suggests opportunities to enhance drought resistance: Journal of Applied Ecology., v. 59, no. 2, p. 549-559, https://doi.org/10.1111/1365-2664.14073.","productDescription":"11 p.","startPage":"549","endPage":"559","ipdsId":"IP-126821","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":449572,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.14073","text":"Publisher Index Page"},{"id":436042,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92HBML8","text":"USGS data release","linkHelpText":"Estimated tree mortality, basal area, climate, and drought conditions for ponderosa pine in forest inventory plots across the western U.S."},{"id":391609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":826597,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shriver, Robert K 0000-0002-4590-4834","orcid":"https://orcid.org/0000-0002-4590-4834","contributorId":222834,"corporation":false,"usgs":false,"family":"Shriver","given":"Robert","email":"","middleInitial":"K","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":826598,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robles, Marcos D.","contributorId":244893,"corporation":false,"usgs":false,"family":"Robles","given":"Marcos","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":826599,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCauley, Lisa A","contributorId":268774,"corporation":false,"usgs":false,"family":"McCauley","given":"Lisa A","affiliations":[{"id":55658,"text":"The Nature Conservancy, Center for Science and Public Policy, 1510 E Ft Lowell Road, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":826600,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andrews, Caitlin M. 0000-0003-4593-1071 candrews@usgs.gov","orcid":"https://orcid.org/0000-0003-4593-1071","contributorId":192985,"corporation":false,"usgs":true,"family":"Andrews","given":"Caitlin","email":"candrews@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":826601,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crimmins, Michael A.","contributorId":178238,"corporation":false,"usgs":false,"family":"Crimmins","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":826602,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bell, David M.","contributorId":191003,"corporation":false,"usgs":false,"family":"Bell","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":826603,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70262164,"text":"70262164 - 2022 - Bankfull shear velocity predicts embeddedness and silt cover in gravel streambeds","interactions":[],"lastModifiedDate":"2025-01-15T15:42:12.481821","indexId":"70262164","displayToPublicDate":"2021-10-28T09:33:57","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Bankfull shear velocity predicts embeddedness and silt cover in gravel streambeds","docAbstract":"

Excess fine sediment (<2 mm) deposition on gravel streambeds can degrade habitat quality for stream biota. Two measures of fine sediment deposition include embeddedness and silt cover (<62.5 μm). Embeddedness measures fine sediment in interstitial pore spaces, whereas silt cover, primarily deposited during low flows, measures fine sediment draped on the streambed's surface. Here, we demonstrate that a baseline level of embeddedness and a maximum value of silt cover can be predicted from bankfull shear velocity, which can be estimated from river channel and streamflow characteristics, independently of knowing the sediment supply. We derive an equation for bankfull shear velocity that only requires knowing bankfull flow, channel width, and channel slope, which can be readily obtained in the United States from freely available, remotely sensed data. We apply this methodology to data collected at 30 sites in the Piedmont region of Virginia and North Carolina. This work is an important step in developing statistical models of stream ecosystems in which geophysical variables can predict embeddedness and silt cover, which commonly limit biotic assemblages.

","language":"English","publisher":"Wiley","doi":"10.1002/rra.3878","usgsCitation":"Czuba, J., Hirschler, M., Pratt, E., Villamagna, A., and Angermeier, P., 2022, Bankfull shear velocity predicts embeddedness and silt cover in gravel streambeds: River Research and Applications, v. 38, no. 1, p. 59-68, https://doi.org/10.1002/rra.3878.","productDescription":"10 p.","startPage":"59","endPage":"68","ipdsId":"IP-127933","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467213,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/111948","text":"External Repository"},{"id":466418,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.6,\n 37.1\n ],\n [\n -80.6,\n 36.25\n ],\n [\n -79.5,\n 36.25\n ],\n [\n -79.5,\n 37.1\n ],\n [\n -80.6,\n 37.1\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"38","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Czuba, Jonathan A.","contributorId":348255,"corporation":false,"usgs":false,"family":"Czuba","given":"Jonathan A.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":923309,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hirschler, Mallory","contributorId":348256,"corporation":false,"usgs":false,"family":"Hirschler","given":"Mallory","affiliations":[{"id":35056,"text":"Plymouth State University","active":true,"usgs":false}],"preferred":false,"id":923310,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pratt, Elizabeth A.","contributorId":348257,"corporation":false,"usgs":false,"family":"Pratt","given":"Elizabeth A.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":923311,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Villamagna, Amy","contributorId":348258,"corporation":false,"usgs":false,"family":"Villamagna","given":"Amy","affiliations":[{"id":35056,"text":"Plymouth State University","active":true,"usgs":false}],"preferred":false,"id":923312,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Angermeier, Paul L. 0000-0003-2864-170X","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":204519,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923308,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70225740,"text":"70225740 - 2022 - Techniques to improve ecological interpretability of black box machine learning models","interactions":[],"lastModifiedDate":"2023-03-24T16:57:11.274452","indexId":"70225740","displayToPublicDate":"2021-10-28T08:45:07","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2151,"text":"Journal of Agricultural, Biological, and Environmental Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Techniques to improve ecological interpretability of black box machine learning models","docAbstract":"

Statistical modeling of ecological data is often faced with a large number of variables as well as possible nonlinear relationships and higher-order interaction effects. Gradient boosted trees (GBT) have been successful in addressing these issues and have shown a good predictive performance in modeling nonlinear relationships, in particular in classification settings with a categorical response variable. They also tend to be robust against outliers. However, their black-box nature makes it difficult to interpret these models. We introduce several recently developed statistical tools to the environmental research community in order to advance interpretation of these black-box models. To analyze the properties of the tools, we applied gradient boosted trees to investigate biological health of streams within the contiguous USA, as measured by a benthic macroinvertebrate biotic index. Based on these data and a simulation study, we demonstrate the advantages and limitations of partial dependence plots (PDP), individual conditional expectation (ICE) curves and accumulated local effects (ALE) in their ability to identify covariate–response relationships. Additionally, interaction effects were quantified according to interaction strength (IAS) and Friedman’s H2\">H2 statistic. Interpretable machine learning techniques are useful tools to open the black-box of gradient boosted trees in the environmental sciences. This finding is supported by our case study on the effect of impervious surface on the benthic condition, which agrees with previous results in the literature. Overall, the most important variables were ecoregion, bed stability, watershed area, riparian vegetation and catchment slope. These variables were also present in most identified interaction effects. In conclusion, graphical tools (PDP, ICE, ALE) enable visualization and easier interpretation of GBT but should be supported by analytical statistical measures. Future methodological research is needed to investigate the properties of interaction tests.      Supplementary materials accompanying this paper appear on-line.

","language":"English","publisher":"Springer","doi":"10.1007/s13253-021-00479-7","usgsCitation":"Welchowski, T., Maloney, K.O., Mitchell, R., and Schmid, M., 2022, Techniques to improve ecological interpretability of black box machine learning models: Journal of Agricultural, Biological, and Environmental Statistics, v. 27, p. 175-197, https://doi.org/10.1007/s13253-021-00479-7.","productDescription":"23 p.","startPage":"175","endPage":"197","ipdsId":"IP-123921","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":449577,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13253-021-00479-7","text":"Publisher Index Page"},{"id":391510,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","noUsgsAuthors":false,"publicationDate":"2021-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Welchowski, Thomas","contributorId":268342,"corporation":false,"usgs":false,"family":"Welchowski","given":"Thomas","email":"","affiliations":[{"id":47552,"text":"University of Bonn, Germany","active":true,"usgs":false}],"preferred":false,"id":826461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":826462,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mitchell, Richard M.","contributorId":215406,"corporation":false,"usgs":false,"family":"Mitchell","given":"Richard M.","affiliations":[{"id":39239,"text":"USEPA, Washington D.C.","active":true,"usgs":false}],"preferred":false,"id":826463,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmid, Matthias","contributorId":236855,"corporation":false,"usgs":false,"family":"Schmid","given":"Matthias","affiliations":[{"id":47552,"text":"University of Bonn, Germany","active":true,"usgs":false}],"preferred":false,"id":826464,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70232173,"text":"70232173 - 2022 - Bayesian modeling can facilitate adaptive management in restoration","interactions":[],"lastModifiedDate":"2022-06-09T13:26:32.441978","indexId":"70232173","displayToPublicDate":"2021-10-28T08:22:51","publicationYear":"2022","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":"Bayesian modeling can facilitate adaptive management in restoration","docAbstract":"

There is an urgent need for near-term predictions of ecological restoration outcomes despite imperfect knowledge of ecosystems. Restoration outcomes are always uncertain but integrating Bayesian modeling into the process of adaptive management allows researchers and practitioners to explicitly incorporate prior knowledge of ecosystems into future predictions. Although barriers exist, employing qualitative expert knowledge and previous case studies can help narrow the range of uncertainty in forecasts. Software and processes that allow for repeatable methodologies can help bridge the existing gap between theory and application of Bayesian methods in adaptive management.

","language":"English","publisher":"Wiley","doi":"10.1111/rec.13596","usgsCitation":"Applestein, C., Caughlin, T.T., and Germino, M., 2022, Bayesian modeling can facilitate adaptive management in restoration: Restoration Ecology, v. 30, no. 4, e13596, 4 p., https://doi.org/10.1111/rec.13596.","productDescription":"e13596, 4 p.","ipdsId":"IP-132611","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":401973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Applestein, Cara 0000-0002-7923-8526","orcid":"https://orcid.org/0000-0002-7923-8526","contributorId":218010,"corporation":false,"usgs":true,"family":"Applestein","given":"Cara","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caughlin, T. Trevor","contributorId":218133,"corporation":false,"usgs":false,"family":"Caughlin","given":"T.","email":"","middleInitial":"Trevor","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":844467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844440,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70254666,"text":"70254666 - 2022 - Recursive Bayesian computation facilitates adaptive optimal design in ecological studies","interactions":[],"lastModifiedDate":"2024-06-06T12:15:39.819355","indexId":"70254666","displayToPublicDate":"2021-10-28T07:13:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Recursive Bayesian computation facilitates adaptive optimal design in ecological studies","docAbstract":"

Optimal design procedures provide a framework to leverage the learning generated by ecological models to flexibly and efficiently deploy future monitoring efforts. At the same time, Bayesian hierarchical models have become widespread in ecology and offer a rich set of tools for ecological learning and inference. However, coupling these methods with an optimal design framework can become computationally intractable. Recursive Bayesian computation offers a way to substantially reduce this computational burden, making optimal design accessible for modern Bayesian ecological models. We demonstrate the application of so-called prior-proposal recursive Bayes to optimal design using a simulated data binary regression and the real-world example of monitoring and modeling sea otters in Glacier Bay, Alaska. These examples highlight the computational gains offered by recursive Bayesian methods and the tighter fusion of monitoring and science that those computational gains enable.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3573","usgsCitation":"Leach, C.B., Perry, W., Eisaguirre, J., Womble, J., Bower, M.R., and Hooten, M., 2022, Recursive Bayesian computation facilitates adaptive optimal design in ecological studies: Ecology, v. 103, no. 2, e03573, 9 p., https://doi.org/10.1002/ecy.3573.","productDescription":"e03573, 9 p.","ipdsId":"IP-124675","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449580,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.3573","text":"Publisher Index Page"},{"id":429566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"103","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-11-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Leach, Clinton B.","contributorId":270703,"corporation":false,"usgs":false,"family":"Leach","given":"Clinton","email":"","middleInitial":"B.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":902193,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, William J.","contributorId":30960,"corporation":false,"usgs":true,"family":"Perry","given":"William J.","affiliations":[],"preferred":false,"id":902194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eisaguirre, Joseph M. 0000-0002-0450-8472","orcid":"https://orcid.org/0000-0002-0450-8472","contributorId":260861,"corporation":false,"usgs":false,"family":"Eisaguirre","given":"Joseph M.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":902195,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Womble, Jamie N.","contributorId":267709,"corporation":false,"usgs":false,"family":"Womble","given":"Jamie N.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":902196,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bower, Michael R.","contributorId":198632,"corporation":false,"usgs":false,"family":"Bower","given":"Michael","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":902197,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":902192,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70226527,"text":"70226527 - 2022 - The role of preexisting upper plate strike-slip faults during long-lived (ca. 30 Myr) oblique flat slab subduction, southern Alaska","interactions":[],"lastModifiedDate":"2021-11-23T14:16:17.67564","indexId":"70226527","displayToPublicDate":"2021-10-27T08:13:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"The role of preexisting upper plate strike-slip faults during long-lived (ca. 30 Myr) oblique flat slab subduction, southern Alaska","docAbstract":"

Upper plates of subduction zones commonly respond to flat slab subduction by structural reactivation, magmatic arc disruption, and foreland basin inversion. However, the role of active strike-slip faults in focusing convergent deformation and magmatism in response to oblique flat slab subduction remains less clear. Here, we present new detrital apatite fission-track (dAFT) ages from 12 modern catchments in the eastern Alaska Range, Alaska, USA, to reveal how the dextral Denali fault system has facilitated bedrock exhumation and topographic growth during ca. 30 Ma-to-present oblique flat slab subduction of the Yakutat oceanic plateau. Additionally, a 940 ka (40Ar/39Ar whole rock) basalt flow is spatially associated with Cenozoic structures, locally reset AFT ages and provides the first evidence for Quaternary volcanism along the southern flank of the eastern Alaska Range. We integrate our new data with other thermochronologic, geochronologic, and regional geologic datasets to show that (1) most high topography regions in southern Alaska have undergone rapid bedrock cooling and exhumation since ca. 30 Ma; (2) elevated terrain and young cooling are spatially associated with long-lived active strike-slip fault systems; (3) topographic growth associated with strike-slip fault deformation led to local inversion of basin systems and drainage reorganization; (4) the onset of oblique oceanic plateau subduction is coeval with a southward shift in arc magmatism from one region of active strike-slip faulting to another above the northeastern edge of the flat slab; and (5) Quaternary volcanism marks the revival of magmatism in the eastern Alaska Range above the geophysically imaged northeastern edge of the flat slab. Our analysis of the post-30 Ma geologic evolution of southern Alaska demonstrates that strike-slip fault systems that were active at the time of slab flattening evolved into transpression zones that focused bedrock cooling, rock exhumation, and topographic growth.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2021.117242","usgsCitation":"Waldien, T., Lease, R.O., Roeske, S., Benowitz, J., and O'Sullivan, P., 2022, The role of preexisting upper plate strike-slip faults during long-lived (ca. 30 Myr) oblique flat slab subduction, southern Alaska: Earth and Planetary Science Letters, v. 557, 117242, 12 p., https://doi.org/10.1016/j.epsl.2021.117242.","productDescription":"117242, 12 p.","ipdsId":"IP-133224","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":449588,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2021.117242","text":"Publisher Index Page"},{"id":392043,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.072265625,\n 57.18390185831188\n ],\n [\n -135.703125,\n 57.18390185831188\n ],\n [\n -135.703125,\n 63.93737246791484\n ],\n [\n -154.072265625,\n 63.93737246791484\n ],\n [\n -154.072265625,\n 57.18390185831188\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"557","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Waldien, Trevor","contributorId":269432,"corporation":false,"usgs":false,"family":"Waldien","given":"Trevor","email":"","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":827200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lease, Richard O. 0000-0003-2582-8966 rlease@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-8966","contributorId":5098,"corporation":false,"usgs":true,"family":"Lease","given":"Richard","email":"rlease@usgs.gov","middleInitial":"O.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":827201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roeske, Sarah","contributorId":269434,"corporation":false,"usgs":false,"family":"Roeske","given":"Sarah","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":827202,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benowitz, Jeff","contributorId":269436,"corporation":false,"usgs":false,"family":"Benowitz","given":"Jeff","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":827203,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O'Sullivan, Paul","contributorId":269438,"corporation":false,"usgs":false,"family":"O'Sullivan","given":"Paul","affiliations":[{"id":51089,"text":"Geosep Services","active":true,"usgs":false}],"preferred":false,"id":827204,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231451,"text":"70231451 - 2022 - Next-generation lampricides: A three-stage process to develop improved control tools for invasive sea lamprey","interactions":[],"lastModifiedDate":"2022-05-11T11:37:08.337092","indexId":"70231451","displayToPublicDate":"2021-10-26T06:34:51","publicationYear":"2022","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":"Next-generation lampricides: A three-stage process to develop improved control tools for invasive sea lamprey","docAbstract":"
Successful integrated management of the invasive predatory sea lamprey (Petromyzon marinus) in the Laurentian Great Lakes of North America is owed largely to the long history of beneficial use of two lampricides: 3-trifluoromethyl-4-nitrophenol (TFM) and 2′,5-dichloro-4′-nitrosalicylanilide (niclosamide). Ensuring continued successful sea lamprey control necessitates consideration of possible next-generation lampricides to supplement or replace current lampricides. This review identifies fifteen hallmarks of success for current lampricides to be used as design criteria in a search for next-generation lampricides. A three-stage research approach is outlined. Targeted research using omics, computer modelling, and high-throughput technology to define molecular mechanisms and high probability molecular targets for sea lamprey selective toxic action is crucial to prioritizing chemical candidates. Targeted delivery or identifying synergists to existing or new lampricides can provide increased efficiency and reduced environmental impact. Ultimate development of next-generation lampricides will rely on traditional toxicity testing methodologies to ensure safety and regulatory compliance.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2020-0316","usgsCitation":"Lantz, S., Adair, B., Amberg, J., Bergstedt, R.A., Boogaard, M.A., Bussy, U., Docker, M.F., Dunlop, E.S., Gonzalez, A., Hubert, T., Siefkes, M.J., Sullivan, P., Whyard, S., Wilkie, M.P., Young, B., and Muir, A.M., 2022, Next-generation lampricides: A three-stage process to develop improved control tools for invasive sea lamprey: Canadian Journal of Fisheries and Aquatic Sciences, v. 79, no. 4, p. 692-702, https://doi.org/10.1139/cjfas-2020-0316.","productDescription":"11 p.","startPage":"692","endPage":"702","ipdsId":"IP-093151","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":449593,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2020-0316","text":"Publisher Index Page"},{"id":400493,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"79","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lantz, Steve 0000-0002-0729-289X","orcid":"https://orcid.org/0000-0002-0729-289X","contributorId":291594,"corporation":false,"usgs":false,"family":"Lantz","given":"Steve","email":"","affiliations":[{"id":62723,"text":"New Mexico Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":842640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adair, Bob","contributorId":291595,"corporation":false,"usgs":false,"family":"Adair","given":"Bob","email":"","affiliations":[{"id":62726,"text":"U.S. Fish and Wildlife Service - Retired","active":true,"usgs":false}],"preferred":false,"id":842641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":842642,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bergstedt, Roger A. rbergstedt@usgs.gov","contributorId":291596,"corporation":false,"usgs":true,"family":"Bergstedt","given":"Roger","email":"rbergstedt@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":842643,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boogaard, Michael A. 0000-0002-5192-8437 mboogaard@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-8437","contributorId":865,"corporation":false,"usgs":true,"family":"Boogaard","given":"Michael","email":"mboogaard@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":842644,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bussy, Ugo","contributorId":150993,"corporation":false,"usgs":false,"family":"Bussy","given":"Ugo","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":842645,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Docker, Margaret F.","contributorId":195099,"corporation":false,"usgs":false,"family":"Docker","given":"Margaret","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":842646,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dunlop, Erin S.","contributorId":146961,"corporation":false,"usgs":false,"family":"Dunlop","given":"Erin","email":"","middleInitial":"S.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":842647,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gonzalez, Alex","contributorId":291597,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Alex","email":"","affiliations":[{"id":62726,"text":"U.S. Fish and Wildlife Service - Retired","active":true,"usgs":false}],"preferred":false,"id":842648,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hubert, Terrance 0000-0001-9712-1738","orcid":"https://orcid.org/0000-0001-9712-1738","contributorId":215420,"corporation":false,"usgs":false,"family":"Hubert","given":"Terrance","affiliations":[{"id":39242,"text":"UMESC (retired)","active":true,"usgs":false}],"preferred":false,"id":842649,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Siefkes, Michael J.","contributorId":222109,"corporation":false,"usgs":false,"family":"Siefkes","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":842650,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sullivan, Paul","contributorId":141103,"corporation":false,"usgs":false,"family":"Sullivan","given":"Paul","email":"","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":842651,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Whyard, Steve","contributorId":291598,"corporation":false,"usgs":false,"family":"Whyard","given":"Steve","email":"","affiliations":[{"id":62727,"text":"Department of Biological Science, University of Manitoba","active":true,"usgs":false}],"preferred":false,"id":842652,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Wilkie, Michael P.","contributorId":191045,"corporation":false,"usgs":false,"family":"Wilkie","given":"Michael","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":842653,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Young, Bradley","contributorId":291599,"corporation":false,"usgs":false,"family":"Young","given":"Bradley","affiliations":[{"id":62728,"text":"United States Fish and Wildlife Service,","active":true,"usgs":false}],"preferred":false,"id":842654,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Muir, Andrew M.","contributorId":176177,"corporation":false,"usgs":false,"family":"Muir","given":"Andrew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":842655,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70230213,"text":"70230213 - 2022 - Temperature-based modeling of incubation period to protect loggerhead hatchlings on an urban beach in Northwest Florida","interactions":[],"lastModifiedDate":"2022-04-05T15:19:54.312558","indexId":"70230213","displayToPublicDate":"2021-10-25T10:16:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2277,"text":"Journal of Experimental Marine Biology and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Temperature-based modeling of incubation period to protect loggerhead hatchlings on an urban beach in Northwest Florida","docAbstract":"

Sea turtle hatchlings face many natural and anthropogenic threats during their short journey to the water after emerging from nests. Reducing hatchling mortality is critical to population recovery of imperiled sea turtle species; however, protecting hatchlings is particularly challenging on beaches degraded by human development and disturbances, including artificial lighting. Managers need practical methods to reduce hatchling mortality without harming their natural behavior or development. To address this need, we describe an approach to reduce mortality of loggerhead hatchlings that relies on prediction of clutch incubation length and knowledge of hatchling emergence patterns. We developed models to predict incubation length utilizing sand temperature and nest depth data from 133 loggerhead nests laid on an urban beach in Northwest Florida from 2013 to 2020. Incubation length was predicted to within 2.2 days using mean sand temperatures measured just outside of the clutch. Predicted accuracy improved to 1.9 days using a 2-parameter model incorporating sand temperature and measured depth to the topmost eggs. Hatchlings emerged almost exclusively at night in a single large group with no evidence of asynchronous emergences. Emergence times were skewed toward the early evening, in contrast to loggerhead nests on the Florida Atlantic coast which tend to hatch near midnight. Using these prediction tools, monitoring efforts could be focused on days and times of expected emergence to enable protection of hatchlings emerging naturally from nests left in situ. The method used here, while not a substitute for recovery of degraded nesting habitat, provides a way to protect hatchlings that avoids disturbing the eggs with instruments or restraining the hatchlings with cages or screens.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jembe.2021.151647","usgsCitation":"Watson, K.P., and Lamont, M., 2022, Temperature-based modeling of incubation period to protect loggerhead hatchlings on an urban beach in Northwest Florida: Journal of Experimental Marine Biology and Ecology, v. 546, 151647, 10 p., https://doi.org/10.1016/j.jembe.2021.151647.","productDescription":"151647, 10 p.","ipdsId":"IP-127739","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":398117,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","county":"Bay County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.528564453125,\n 30.023921574501376\n ],\n [\n -85.8856201171875,\n 30.235340577517942\n ],\n [\n -85.92819213867188,\n 30.22466172703242\n ],\n [\n -85.59860229492188,\n 30.0286775329042\n ],\n [\n -85.54504394531249,\n 30.00013836058068\n ],\n [\n -85.528564453125,\n 30.023921574501376\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"546","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Watson, Kennard P.","contributorId":289668,"corporation":false,"usgs":false,"family":"Watson","given":"Kennard","email":"","middleInitial":"P.","affiliations":[{"id":62225,"text":"Panama City Beach Turtle Watch","active":true,"usgs":false}],"preferred":false,"id":839570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":222403,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":839571,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227255,"text":"70227255 - 2022 - Fatty acid profiles of feeding and fasting bears: Estimating calibration coefficients, the timeframe of diet estimates, and selective mobilization during hibernation","interactions":[],"lastModifiedDate":"2022-03-15T16:44:22.084218","indexId":"70227255","displayToPublicDate":"2021-10-23T07:27:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2226,"text":"Journal of Comparative Physiology B: Biochemical, Systemic, and Environmental Physiology","active":true,"publicationSubtype":{"id":10}},"title":"Fatty acid profiles of feeding and fasting bears: Estimating calibration coefficients, the timeframe of diet estimates, and selective mobilization during hibernation","docAbstract":"

Accurate information on diet composition is central to understanding and conserving carnivore populations. Quantitative fatty acid signature analysis (QFASA) has emerged as a powerful tool for estimating the diets of predators, but ambiguities remain about the timeframe of QFASA estimates and the need to account for species-specific patterns of metabolism. We conducted a series of feeding experiments with four juvenile male brown bears (Ursus arctos) to (1) track the timing of changes in adipose tissue composition and QFASA diet estimates in response to a change in diet and (2) quantify the relationship between consumer and diet FA composition (i.e., determine “calibration coefficients”). Bears were fed three compositionally distinct diets for 90–120 days each. Two marine-based diets were intended to approximate the lipid content and composition of the wild diet of polar bears (U. maritimus). Bear adipose tissue composition changed quickly in the direction of the diet and showed evidence of stabilization after 60 days. During hibernation, FA profiles were initially stable but diet estimates after 10 weeks were sensitive to calibration coefficients. Calibration coefficients derived from the marine-based diets were broadly similar to each other and to published values from marine-fed mink (Mustela vison), which have been used as a model for free-ranging polar bears. For growing bears on a high-fat diet, the temporal window for QFASA estimates was 30–90 days. Although our results reinforce the importance of accurate calibration, the similarities across taxa and diets suggest it may be feasible to develop a generalized QFASA approach for mammalian carnivores.

","language":"English","publisher":"Springer","doi":"10.1007/s00360-021-01414-5","usgsCitation":"Thiemann, G.W., Rode, K.D., Erlenbach, J.A., Budge, S., and Robbins, C.T., 2022, Fatty acid profiles of feeding and fasting bears: Estimating calibration coefficients, the timeframe of diet estimates, and selective mobilization during hibernation: Journal of Comparative Physiology B: Biochemical, Systemic, and Environmental Physiology, v. 192, p. 379-395, https://doi.org/10.1007/s00360-021-01414-5.","productDescription":"17 p.","startPage":"379","endPage":"395","ipdsId":"IP-123610","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":393909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"192","noUsgsAuthors":false,"publicationDate":"2021-10-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Thiemann, Gregory W.","contributorId":83023,"corporation":false,"usgs":false,"family":"Thiemann","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":27291,"text":"York University, Toronto, ON","active":true,"usgs":false}],"preferred":false,"id":830127,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":830128,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erlenbach, Joy A 0000-0003-0347-3711","orcid":"https://orcid.org/0000-0003-0347-3711","contributorId":270917,"corporation":false,"usgs":false,"family":"Erlenbach","given":"Joy","email":"","middleInitial":"A","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":830129,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Budge, Suzanne","contributorId":84772,"corporation":false,"usgs":true,"family":"Budge","given":"Suzanne","affiliations":[],"preferred":false,"id":830130,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robbins, Charles T.","contributorId":32436,"corporation":false,"usgs":false,"family":"Robbins","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5132,"text":"Washington State University, Pullman","active":true,"usgs":false}],"preferred":false,"id":830131,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70226178,"text":"70226178 - 2022 - Biodiversity–productivity relationships in a natural grassland community vary under diversity loss scenarios","interactions":[],"lastModifiedDate":"2022-01-25T17:13:10.33195","indexId":"70226178","displayToPublicDate":"2021-10-22T07:00:34","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Biodiversity–productivity relationships in a natural grassland community vary under diversity loss scenarios","docAbstract":"
  1. Understanding the biodiversity–productivity relationship and underlying mechanisms in natural ecosystems under realistic diversity loss scenarios remains a major challenge for ecologists despite its importance for predicting impacts of rapid loss of biodiversity worldwide. Here we report the results of a plant functional group (PFG) removal experiment conducted on the Mongolian Plateau, the largest remaining natural grassland in the world.
  2. Our results demonstrated that the biodiversity–productivity relationship varied among positive linear, neutral and unimodal forms under different PFG loss patterns. Moreover, the form of this relationship with the same PFG loss pattern sometimes changed through time.
  3. The abundance of the remaining PFG(s) before removal and their compensation following the loss of other PFGs were two major mechanisms affecting the biodiversity–productivity relationship under diversity loss scenarios. The abundance effect promoted positive responses of productivity to biodiversity, but the compensation effect caused several biodiversity–productivity relationships, hinging on its direction (positive or negative) and strength. As indicated by the values of the compensation index, negative, zero and partial compensations contributed to the positive relationships, while full compensation resulted in a neutral relationship. Overcompensation at intermediate PFG richness levels created a unimodal curve in our system, but it could also lead to a negative linear relationship.
  4. Synthesis. Our experiment provides a vivid picture of how the form of the biodiversity–productivity relationship varies among different diversity loss patterns in a natural ecosystem. We argue that compensation by the remaining species, which is not revealed by synthesized biodiversity experiments, plays a critical role in shaping the form of this relationship when diversity is lost from existing systems. The direction and strength of compensation are highly dependent on extirpation scenarios. Thus, impacts of biodiversity loss on natural ecosystems are likely more complex than predicted by the canonical positive saturating curve obtained from the synthesized biodiversity experiments. We suggest that models forecasting the consequences of biodiversity declines on natural ecosystems should take into account diversity loss patterns and the ensuing compensation.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2745.13797","usgsCitation":"Pan, Q., Symstad, A., Bai, Y., Huang, J., Wu, J., Naeem, S., Chen, D., Tian, D., Wang, Q., and Han, X., 2022, Biodiversity–productivity relationships in a natural grassland community vary under diversity loss scenarios: Journal of Ecology, v. 110, no. 1, p. 210-220, https://doi.org/10.1111/1365-2745.13797.","productDescription":"11 p.","startPage":"210","endPage":"220","ipdsId":"IP-127248","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":449604,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2745.13797","text":"Publisher Index Page"},{"id":391741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"110","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Pan, Qingmin","contributorId":268807,"corporation":false,"usgs":false,"family":"Pan","given":"Qingmin","email":"","affiliations":[{"id":55672,"text":"Institute of Botany, Chinese Academy of Sciences, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":826721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":826722,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bai, Yongfei","contributorId":268808,"corporation":false,"usgs":false,"family":"Bai","given":"Yongfei","affiliations":[{"id":55672,"text":"Institute of Botany, Chinese Academy of Sciences, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":826723,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huang, Jianhui","contributorId":268809,"corporation":false,"usgs":false,"family":"Huang","given":"Jianhui","email":"","affiliations":[{"id":55672,"text":"Institute of Botany, Chinese Academy of Sciences, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":826724,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wu, Jianguo","contributorId":268810,"corporation":false,"usgs":false,"family":"Wu","given":"Jianguo","affiliations":[{"id":36436,"text":"Arizona State University, Tempe, AZ","active":true,"usgs":false}],"preferred":false,"id":826725,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Naeem, Shahid","contributorId":268811,"corporation":false,"usgs":false,"family":"Naeem","given":"Shahid","affiliations":[{"id":55675,"text":"Columbia University, New York, NY","active":true,"usgs":false}],"preferred":false,"id":826726,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chen, Dima","contributorId":268812,"corporation":false,"usgs":false,"family":"Chen","given":"Dima","affiliations":[{"id":55676,"text":"China Three Gorges University, Yichang, China","active":true,"usgs":false}],"preferred":false,"id":826727,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tian, Dashuan","contributorId":268813,"corporation":false,"usgs":false,"family":"Tian","given":"Dashuan","email":"","affiliations":[{"id":55677,"text":"Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":826728,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wang, Qibing","contributorId":268814,"corporation":false,"usgs":false,"family":"Wang","given":"Qibing","email":"","affiliations":[{"id":55672,"text":"Institute of Botany, Chinese Academy of Sciences, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":826729,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Han, Xingguo","contributorId":268815,"corporation":false,"usgs":false,"family":"Han","given":"Xingguo","affiliations":[{"id":55672,"text":"Institute of Botany, Chinese Academy of Sciences, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":826730,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70225520,"text":"70225520 - 2022 - Density structure of the island of Hawai’i and the implications for gravity-driven motion of the south flank of Kilauea volcano","interactions":[],"lastModifiedDate":"2021-12-10T17:03:53.974623","indexId":"70225520","displayToPublicDate":"2021-10-20T09:43:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Density structure of the island of Hawai’i and the implications for gravity-driven motion of the south flank of Kīlauea volcano","title":"Density structure of the island of Hawai’i and the implications for gravity-driven motion of the south flank of Kilauea volcano","docAbstract":"The discovery that large landslides dissected the Hawaiian islands, scattering debris over thousands of square kilometers of seafloor, changed our ideas of island growth and evolution. The evidence is consistent with catastrophic flank collapse during volcano growth, and draws our focus to the currently active island of Hawai’i, the volcanoes Mauna Loa and Kīlauea, and particularly to the actively-mobile south flank of Kīlauea volcano. Both the weight distribution and pressure within an extensive magma system are perceived to affect stability, but the role of gravitational body forces and island density distribution has not been quantitatively assessed. We use seismic velocities derived from tomography to model the density distribution of the island of Hawai’i and find that olivine-rich melts and rocks in Hawaiian volcanoes result in a close association of seismic velocity and density. The resultant density model reproduces more than 95% of the observed gravity disturbance signal wherever tomographic control exists and provides a basis for evaluating the body forces from gravity. We also find that if the decollement is weak, then gravitational body forces can produce slip that explains most seismo-tectonic and volcano-tectonic structural features of Kīlauea volcano. Where the decollement is in a state of incipient slip from this weight distribution, fluctuations in magma pressure can trigger accelerated slip on the decollement. Yet this is only true of the south flank of Kīlauea volcano. Though weight and magma distributions produce significant forces driving the west flank of Mauna Loa seaward, this flank is stable. Stability over the last decade indicates a strong foundation beneath the west flank of Mauna Loa, perhaps as a result of large debris avalanches that occurred there that scraped clay-rich sediments off of the decollement.","language":"English","publisher":"Oxford University Press","doi":"10.1093/gji/ggab398","usgsCitation":"Denlinger, R.P., and Flinders, A.F., 2022, Density structure of the island of Hawai’i and the implications for gravity-driven motion of the south flank of Kilauea volcano: Geophysical Journal International, v. 228, no. 3, p. 1793-1807, https://doi.org/10.1093/gji/ggab398.","productDescription":"15 p.","startPage":"1793","endPage":"1807","ipdsId":"IP-126754","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":449612,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggab398","text":"Publisher Index Page"},{"id":390674,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mount Kīlauea, Mount Mauna Loa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.6597900390625,\n 18.87510275035649\n ],\n [\n -155.50048828125,\n 19.108838815166006\n ],\n [\n -155.26153564453125,\n 19.251515342943254\n ],\n [\n -155.15441894531247,\n 19.233363381183896\n ],\n [\n -154.940185546875,\n 19.32669491605546\n ],\n [\n -154.77813720703125,\n 19.497664168139053\n ],\n [\n -154.80010986328125,\n 19.54426088484117\n ],\n [\n -154.96490478515625,\n 19.645174265699062\n ],\n [\n -154.97589111328125,\n 19.74343913716519\n ],\n [\n -155.07476806640625,\n 19.748609300218842\n ],\n [\n -155.08026123046875,\n 19.815806165386956\n ],\n [\n -155.0665283203125,\n 19.87522588708924\n ],\n [\n -155.26702880859375,\n 20.037870053952016\n ],\n [\n -155.48126220703125,\n 20.125576455270572\n ],\n [\n -155.56365966796875,\n 20.146206116089946\n ],\n [\n -155.59112548828122,\n 20.135891626114574\n ],\n [\n -155.753173828125,\n 20.259620485824865\n ],\n [\n -155.89599609375,\n 20.287961155077717\n ],\n [\n -155.91796874999997,\n 20.246736652244206\n ],\n [\n -155.92620849609375,\n 20.16425483433661\n ],\n [\n -155.84106445312497,\n 20.014645445341365\n ],\n [\n -155.91522216796875,\n 19.94236918954201\n ],\n [\n -155.94268798828125,\n 19.87005983797396\n ],\n [\n -155.99761962890625,\n 19.85714397875396\n ],\n [\n -156.0882568359375,\n 19.748609300218842\n ],\n [\n -155.906982421875,\n 19.295590314804254\n ],\n [\n -155.93719482421875,\n 19.134789188332523\n ],\n [\n -155.92620849609375,\n 19.05173366503917\n ],\n [\n -155.6597900390625,\n 18.87510275035649\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"228","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Denlinger, Roger P. 0000-0003-0930-0635 roger@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-0635","contributorId":2679,"corporation":false,"usgs":true,"family":"Denlinger","given":"Roger","email":"roger@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":825398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flinders, Ashton F. 0000-0003-2483-4635 aflinders@usgs.gov","orcid":"https://orcid.org/0000-0003-2483-4635","contributorId":196960,"corporation":false,"usgs":true,"family":"Flinders","given":"Ashton","email":"aflinders@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":153,"text":"California Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":825399,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70225562,"text":"70225562 - 2022 - Modeling seismic network detection thresholds using production picking algorithms","interactions":[],"lastModifiedDate":"2022-01-06T17:27:19.306006","indexId":"70225562","displayToPublicDate":"2021-10-20T05:53:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Modeling seismic network detection thresholds using production picking algorithms","docAbstract":"

Estimating the detection threshold of a seismic network (the minimum magnitude earthquake that can be reliably located) is a critical part of network design and can drive network maintenance efforts. The ability of a station to detect an earthquake is often estimated by assuming the spectral amplitude for an earthquake of a given size, assuming an attenuation relationship, and comparing the predicted amplitude with the average station background noise level. This approach has significant uncertainty because of unknown regional attenuation and complications in computing small event power spectra, and it fails to account for the specific capabilities of the automatic seismic phase picker used in monitoring. We develop a data‐driven approach to determine network detection thresholds using a multiband phase picking algorithm that is currently in use at the U.S. Geological Survey National Earthquake Information Center. We apply this picking algorithm to cataloged earthquakes to determine an empirical relationship of the observability of earthquakes as a function of magnitude and distance. Using this relationship, we produce maps of detection threshold using station spatial configuration and station noise levels. We show that quiet, well‐sited stations significantly increase the detection capabilities of a network compared with a network composed of many noisy stations. Because our method is data driven, it has two distinct advantages: (1) it is less dependent on theoretical assumptions of source spectra and models of regional attenuation, and (2) it can easily be applied to any seismic network. This tool allows for an objective approach to the management of stations in regional seismic networks.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220210192","usgsCitation":"Wilson, D.C., Wolin, E., Yeck, W.L., Anthony, R.E., and Ringler, A.T., 2022, Modeling seismic network detection thresholds using production picking algorithms: Seismological Research Letters, v. 93, no. 1, p. 149-160, https://doi.org/10.1785/0220210192.","productDescription":"12 p.","startPage":"149","endPage":"160","ipdsId":"IP-130188","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":436046,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97IK2EY","text":"USGS data release","linkHelpText":"Seismic Network Detection Modeling"},{"id":390946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.2744140625,\n 29.53522956294847\n ],\n [\n -74.6630859375,\n 29.49698759653577\n ],\n [\n -74.4873046875,\n 43.229195113965005\n ],\n [\n -91.2744140625,\n 43.48481212891603\n ],\n [\n -91.2744140625,\n 29.53522956294847\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"93","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-10-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolin, Emily 0000-0003-1610-1191","orcid":"https://orcid.org/0000-0003-1610-1191","contributorId":221834,"corporation":false,"usgs":true,"family":"Wolin","given":"Emily","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":825618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yeck, William L. 0000-0002-2801-8873 wyeck@usgs.gov","orcid":"https://orcid.org/0000-0002-2801-8873","contributorId":147558,"corporation":false,"usgs":true,"family":"Yeck","given":"William","email":"wyeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":825619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":3946,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825621,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}