In this work, we utilize a transect of core top, mid- to late Holocene, sediments from the Eastern Siberian Sea to the central Arctic Ocean, spanning gradients in upper-ocean water column properties, to examine regional planktic foraminiferal species abundances and geochemistry. We present species- and morphotype-specific foraminiferal assemblages at these sites and stable isotope analyses of neogloboquadrinids. We find little variation in planktic species populations, and only small variations in N. pachyderma morphotype distributions, between sites. Spatial averages of N. pachyderma morphotype and N. incompta δ18O values show no significant differences, suggesting a similar calcification depth for all morphotypes of N. pachyderma and N. incompta across our sites, which we estimate to be between ∼ 50–150 m. Values of δ18O of a group of unencrusted specimens delineate a shallower calcification habitat. Neogloboquadrina pachyderma-2 Mg/Ca values yield temperatures outside the range of observations using available calibration equations, pointing toward the need for more Arctic-specific Mg/Ca-temperature calibrations.
Global changes in climate and land use are threatening natural ecosystems, biodiversity, and the ecosystem services people rely on. This is why it is necessary to track and monitor spatiotemporal change at a level of detail that can inform science, management, and policy development. The current constellation of multiple Landsat and Sentinel-2 satellites collecting imagery at predominantly
Estimating vital rates of avian species is important to understand population dynamics and develop potential conservation strategies that target rates for management. Avian species have reduced potential for high annual fecundity in alpine ecosystems due to a short breeding window and harsh weather conditions. We located nests from Southern White-tailed Ptarmigan (Lagopus leucura altipetens) across six study sites in the Southern Rocky Mountains of Colorado to estimate daily nest survival from 2013–2017. We used a known-fate hierarchical nest survival model and fit several covariates, including environmental conditions representing daily weather events and shrub cover, to describe variation in daily survival and derive estimates of nest success. We located and monitored 198 nests from 128 radio-marked ptarmigan hens. The mean nest success estimated as a derived parameter from daily nest survival was 45.6% (95% credible interval [CI]: 31.2–59.6%) and ranged from 40.3% to 50.3% across sites. Variation in daily nest survival was poorly described by the covariates we fit (95% CI of most slope coefficients overlapped 0), although there was some support for a negative effect of relative elevation (nests at lower elevations within a site survived at higher rates) and a positive effect of nest age (older nests survived at higher rates). We examined how variation in nest success was likely to influence the finite rate of population growth using a simple simulation with an age-transition matrix parameterized with previously reported fecundity and survival estimates. We found that the finite growth rate was predicted to increase 18.7% when evaluated from the lower to upper 95% CI estimated values of nest success, conditional on the other vital rates used in our simulation. We discuss the broader implications of these findings in the context of managing for nest survival of Southern White-tailed Ptarmigan.
","language":"English","publisher":"Resilience Alliance","doi":"10.5751/ACE-02566-190104","usgsCitation":"Wann, G.T., Seglund, A.E., Street, P.A., Parker, N.J., Nelson, S.L., Runge, J.P., Braun, C.E., and Aldridge, C.L., 2024, Estimates of Southern White-tailed Ptarmigan daily nest survival from multiple sites in the Southern Rocky Mountains of Colorado: Avian Conservation and Ecology, v. 19, no. 1, 4, 14 p., https://doi.org/10.5751/ACE-02566-190104.","productDescription":"4, 14 p.","ipdsId":"IP-153968","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":467042,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.5751/ace-02566-190104","text":"Publisher Index Page"},{"id":464593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Southern Rocky Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.04311121117411,\n 41.012655687234144\n ],\n [\n -109.04311121117411,\n 36.91934059975698\n ],\n [\n -104.69133822114236,\n 36.91934059975698\n ],\n [\n -104.69133822114236,\n 41.012655687234144\n ],\n [\n -109.04311121117411,\n 41.012655687234144\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wann, Gregory T. 0000-0001-9076-7819 wanng@usgs.gov","orcid":"https://orcid.org/0000-0001-9076-7819","contributorId":3855,"corporation":false,"usgs":true,"family":"Wann","given":"Gregory","email":"wanng@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":919595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seglund, Amy E.","contributorId":218686,"corporation":false,"usgs":false,"family":"Seglund","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":919596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Street, Phillip A.","contributorId":346426,"corporation":false,"usgs":false,"family":"Street","given":"Phillip","email":"","middleInitial":"A.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":919597,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parker, Nicholas J.","contributorId":341574,"corporation":false,"usgs":false,"family":"Parker","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":919598,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, Shelley L.","contributorId":346576,"corporation":false,"usgs":false,"family":"Nelson","given":"Shelley","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":919599,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Runge, Jonathan P.","contributorId":196756,"corporation":false,"usgs":false,"family":"Runge","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":919600,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Braun, Clait E.","contributorId":200013,"corporation":false,"usgs":false,"family":"Braun","given":"Clait","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":919601,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":919602,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70263244,"text":"70263244 - 2024 - Individual-based ecological particle tracking model (ECO-PTM) for simulating juvenile chinook salmon migration and survival through the Sacramento – San Joaquin Delta","interactions":[],"lastModifiedDate":"2025-02-03T15:49:36.99796","indexId":"70263244","displayToPublicDate":"2024-01-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Individual-based ecological particle tracking model (ECO-PTM) for simulating juvenile chinook salmon migration and survival through the Sacramento – San Joaquin Delta","docAbstract":"Recovery of endangered salmon species in the Central Valley of California amidst prolonged drought and climate change necessitates innovative water management actions that balance species recovery and California's water demands. We describe an individual-based ecological particle tracking model (ECO-PTM) that can be used to assess the efficacy of proposed actions. Based on a random walk theory, the model tracks individual particles’ travel time, routing and survival in a flow field simulated by the Delta Simulation Model 2 hydrodynamic module (DSM2 HYDRO). The random walk particles are parameterized to have fish-like swimming behaviors, including upstream/downstream swimming, probabilistic holding behaviors, and stochastic swimming velocities. Particle routing at key junctions is based on well-established statistical models, and route-specific survival is calculated using the XT mean free-path length model. Behavioral parameters were estimated by fitting several competing models to a multiyear dataset of travel times from acoustic tagged juvenile salmon. The model’s baseline simulations under historical flow conditions from 1991 to 2016 successfully replicated essential relationships between salmon outmigration survival and hydrodynamic conditions, consistent with previous studies and the STARS (Survival Travel Time and Routing Simulation) statistical simulation model. Simulation results for management scenarios revealed multifaceted influences on fish survival, including Delta flow, flow at key junctions, route alterations, seasons, and water year characteristics. Importantly, these results highlight ECO-PTM’s potential to predict fish survival outcomes of proposed actions, serving as a foundation for informed future research, decision-making, and effective management strategies to enhance the survival prospects of out-migrating salmonids within the Sacramento-San Joaquin Delta ecosystem.","language":"English","publisher":"eScholarship","doi":"10.15447/sfews.2024v22iss4art4","usgsCitation":"Wang, X., Perry, R.W., Pope, A., Jackson, D., and Hance, D., 2024, Individual-based ecological particle tracking model (ECO-PTM) for simulating juvenile chinook salmon migration and survival through the Sacramento – San Joaquin Delta: San Francisco Estuary and Watershed Science, v. 22, no. 4, 4, 23 p., https://doi.org/10.15447/sfews.2024v22iss4art4.","productDescription":"4, 23 p.","ipdsId":"IP-163182","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":486828,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2024v22iss4art4","text":"Publisher Index Page"},{"id":481609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento – San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.56056300774354,\n 38.494229534007104\n ],\n [\n -121.56056300774354,\n 37.898481687362576\n ],\n [\n -121.08815089836878,\n 37.898481687362576\n ],\n [\n -121.08815089836878,\n 38.494229534007104\n ],\n [\n -121.56056300774354,\n 38.494229534007104\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"22","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Xiaochun","contributorId":225264,"corporation":false,"usgs":false,"family":"Wang","given":"Xiaochun","email":"","affiliations":[{"id":41085,"text":"California Department of Water Resources, Sacramento, CA, 95819","active":true,"usgs":false}],"preferred":false,"id":925998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":925999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pope, Adam C. 0000-0002-7253-2247","orcid":"https://orcid.org/0000-0002-7253-2247","contributorId":223237,"corporation":false,"usgs":true,"family":"Pope","given":"Adam","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":926000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Doug","contributorId":315556,"corporation":false,"usgs":false,"family":"Jackson","given":"Doug","email":"","affiliations":[{"id":68352,"text":"QEDA Consulting, LLC., 4007 Densmore Avenue N., Seattle, WA, 98103","active":true,"usgs":false}],"preferred":false,"id":926001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hance, Dalton 0000-0002-4475-706X","orcid":"https://orcid.org/0000-0002-4475-706X","contributorId":220179,"corporation":false,"usgs":true,"family":"Hance","given":"Dalton","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":926002,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70264034,"text":"70264034 - 2024 - Seroprevalence, blood chemistry, and patterns of canine parvovirus, distemper virus, plague, and tularemia in free-ranging coyotes (Canis latrans) in northern New Mexico, USA.","interactions":[],"lastModifiedDate":"2025-04-15T13:45:35.626902","indexId":"70264034","displayToPublicDate":"2024-01-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Seroprevalence, blood chemistry, and patterns of canine parvovirus, distemper virus, plague, and tularemia in free-ranging coyotes (Canis latrans) in northern New Mexico, USA.","docAbstract":"Wildlife diseases have implications for ecology, conservation, human health, and health of domestic animals. They may impact wildlife health and population dynamics. Exposure rates of coyotes (Canis latrans) to pathogens such as Yersinia pestis, the cause of plague, may reflect prevalence rates in both rodent prey and human populations. We captured coyotes in north-central New Mexico during 2005–2008 and collected blood samples for serologic surveys. We tested for antibodies against canine distemper virus (CDV, Canine morbillivirus), canine parvovirus (CPV, Carnivore protoparvovirus), plague, tularemia (Francisella tularensis), and for canine heartworm (Dirofilaria immitis) antigen. Serum biochemistry variables that fell outside reference ranges were probably related to capture stress. We detected antibodies to parvovirus in 32/32 samples (100%), and to Y. pestis in 26/31 (84%). More than half 19/32 (59%) had antibodies against CDV, and 5/31 (39%) had antibodies against F. tularensis. We did not detect any heartworm antigens (n = 9). Pathogen prevalence was similar between sexes and among the three coyote packs in the study area. Parvovirus exposure appeared to happen early in life, and prevalence of antibodies against CDV increased with increasing age class. Exposure to Y. pestis and F. tularensis occurred across all age classes. The high coyote seroprevalence rates observed for CPV, Y. pestis, and CDV may indicate high prevalence in sympatric vertebrate populations, with implications for regional wildlife conservation as well as risk to humans via zoonotic transmission.
","language":"English","publisher":"BioOne","doi":"10.7589/jwd-d-22-00079","usgsCitation":"White, L., Gifford, S., Kaufman, G., Gese, E., Peyton, M.A., Parmenter, R., and Cain, J.W., 2024, Seroprevalence, blood chemistry, and patterns of canine parvovirus, distemper virus, plague, and tularemia in free-ranging coyotes (Canis latrans) in northern New Mexico, USA.: Journal of Wildlife Diseases, v. 160, no. 1, p. 14-25, https://doi.org/10.7589/jwd-d-22-00079.","productDescription":"12 p.","startPage":"14","endPage":"25","ipdsId":"IP-142335","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488241,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7589/jwd-d-22-00079","text":"Publisher Index Page"},{"id":482912,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","county":"Sandoval 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Leah M.","contributorId":351814,"corporation":false,"usgs":false,"family":"White","given":"Leah M.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":929538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gifford, Susan","contributorId":351817,"corporation":false,"usgs":false,"family":"Gifford","given":"Susan","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":929539,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaufman, Gail","contributorId":351820,"corporation":false,"usgs":false,"family":"Kaufman","given":"Gail","affiliations":[{"id":84055,"text":"U.S Forest Service","active":true,"usgs":false}],"preferred":false,"id":929540,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gese, Eric","contributorId":338002,"corporation":false,"usgs":false,"family":"Gese","given":"Eric","affiliations":[{"id":81067,"text":"USDS","active":true,"usgs":false}],"preferred":false,"id":929541,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peyton, Mark A.","contributorId":197603,"corporation":false,"usgs":false,"family":"Peyton","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":929542,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parmenter, Robert R.","contributorId":351821,"corporation":false,"usgs":false,"family":"Parmenter","given":"Robert R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":929543,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":929544,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70264095,"text":"70264095 - 2024 - Merging integrated population models and individual-based models to project population dynamics of recolonizing species","interactions":[],"lastModifiedDate":"2025-03-06T15:59:15.6884","indexId":"70264095","displayToPublicDate":"2024-01-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Merging integrated population models and individual-based models to project population dynamics of recolonizing species","docAbstract":"Recolonizing species exhibit unique population dynamics, namely dispersal to and colonization of new areas, that have important implications for management. A resulting challenge is how to simultaneously model demographic and movement processes so that recolonizing species can be accurately projected over time and space. We introduce a framework for spatially explicit projection modeling that harnesses the rigorous parameter estimation made possible by an integrated population model (IPM) and the flexible movement modeling made possible by an individual-based model (IBM). Our framework has two components: [1] a Bayesian IPM-driven age- and state-structured population model that governs the population state process and estimation of demographic rates, and [2] an IBM-driven spatial model that allows for the projection of dispersal and habitat colonization. We applied this model framework to estimate current and project future dynamics of gray wolves (Canis lupus) in Washington State, USA. We used data from 74 telemetered wolves and yearly pup and pack counts to parameterize the model, and then projected statewide dynamics over 50 years. Mean population growth was 1.29 (95 % Bayesian Credible Interval = 1.26–1.33) during initial recolonization from 2009 to 2020 and decreased to 1.02 (95 % Prediction Interval = 0.98–1.04) in the projection period (2021–2070). Our results suggest that gray wolves have an ~100 % probability of colonizing the last of Washington State's three specified recovery regions by 2030, regardless of alternative assumptions about how dispersing wolves select new territories. Our spatially explicit projection model can be used to project the dynamics of any species for which spatial spread is an important driver of population dynamics.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2023.110340","usgsCitation":"Petracca, L., Gardner, B., Maletzke, B., and Converse, S.J., 2024, Merging integrated population models and individual-based models to project population dynamics of recolonizing species: Biological Conservation, v. 289, 110340, 14 p., https://doi.org/10.1016/j.biocon.2023.110340.","productDescription":"110340, 14 p.","ipdsId":"IP-151020","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":482973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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times decrease dispersal but increase mortality of translocated scaled quail","docAbstract":"Scaled quail (Callipepla squamata) decline caused by habitat loss and fragmentation increased interest in translocation to reestablish populations. Yet factors determining translocation success are poorly understood. We tested hypotheses concerning the influence of source population and variation in delayed release strategy (1–9 weeks) on mortality and dispersal of wild-caught, translocated scaled quail. We trapped and translocated quail from 2016–2017 from source populations in the Edwards Plateau and Rolling Plains ecoregions to a large contiguous (>40,000 ha) release site in Knox County, Texas, USA. We evaluated mortality and dispersal of translocated females as a function of source population, holding time prior to release, age, release location, and year using a multi-state mark-recapture model with state uncertainty. Scaled quail translocated within the Rolling Plains were more likely to exhibit philopatry to the release site. Quail with longer holding times had higher mortality but lower dispersal rates. The Edwards Plateau is a suitable source site for translocation in the Rolling Plains. The reduced dispersal but higher mortality of translocated scaled quail associated with longer holding times creates a decision tradeoff for managers.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22498","usgsCitation":"Ruzicka, R., Rollins, D., Doherty, P.F., and Kendall, W.L., 2024, Longer holding times decrease dispersal but increase mortality of translocated scaled quail: Journal of Wildlife Management, v. 88, no. 1, e22498, 16 p., https://doi.org/10.1002/jwmg.22498.","productDescription":"e22498, 16 p.","ipdsId":"IP-151614","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487938,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22498","text":"Publisher Index Page"},{"id":485349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","county":"Knox County","otherGeospatial":"South Wichita River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.2487789756043,\n 34.08946446033667\n ],\n [\n -103.2487789756043,\n 31.880566287138876\n ],\n [\n -100.09201762067653,\n 31.880566287138876\n ],\n [\n -100.09201762067653,\n 34.08946446033667\n ],\n [\n -103.2487789756043,\n 34.08946446033667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"88","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-09-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruzicka, Rebekah E.","contributorId":354109,"corporation":false,"usgs":false,"family":"Ruzicka","given":"Rebekah E.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":935108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rollins, Dale","contributorId":140708,"corporation":false,"usgs":false,"family":"Rollins","given":"Dale","email":"","affiliations":[],"preferred":false,"id":935109,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doherty, Paul F. Jr.","contributorId":37636,"corporation":false,"usgs":false,"family":"Doherty","given":"Paul","suffix":"Jr.","email":"","middleInitial":"F.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":935110,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":935111,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70254281,"text":"70254281 - 2024 - Glacier National Park bumble bee survey report 2023","interactions":[],"lastModifiedDate":"2026-03-25T18:59:44.1231","indexId":"70254281","displayToPublicDate":"2023-12-31T13:55:33","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Glacier National Park bumble bee survey report 2023","docAbstract":"Glacier National Park's grasslands provide important contributions to the character and ecology of the park. In 1999-2001, Glacier National Park (hereafter, the park) established 155 permanent vegetation monitoring plots to inventory grassland vegetation communities east of the Continental Divide. In June of 2023, the Blackfeet Nation (Amskapi Piikuni) re-introduced a herd of free roaming bison on adjacent tribal land (the linnii Initiative), and those bison may enter the park. Because grasslands are important areas for bison grazing, and because biological communities have likely changed since the initial inventories, the park’s vegetation program began revisiting grassland monitoring plots in 2018. New data will provide insights into how these grasslands, and the wildlife that depend on them, have changed over the past two decades. Data on pollinators in these grasslands, however, are limited. Bison have been shown to influence plant communities, for example, by increasing herbaceous forb diversity and drought resilience (Elson and Hartnett 2017; Ratajczak et al. 2022). These changes directly influence resources available to foraging pollinators. To provide understanding of pollinators prior to bison reintroduction, bumble bee surveying at these grassland plots began in 2020 and has continued through 2023. Target sites for 2020-2022 focused on collecting data at plots where new vegetation surveys were recently completed to match current vegetation data with the bumble bee data.
","language":"English","publisher":"National Park Service","usgsCitation":"Dose, L.M., Gustilo, E., and Graves, T.A., 2024, Glacier National Park bumble bee survey report 2023, 10 p.","productDescription":"10 p.","ipdsId":"IP-163706","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":501543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501542,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2303748","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.50305495511051,\n 48.2333805603611\n ],\n [\n -113.21756937173382,\n 48.411528578442415\n ],\n [\n -113.45474201023127,\n 48.77753781447308\n ],\n [\n -113.60407293076683,\n 48.92781667996147\n ],\n [\n -113.59528875897055,\n 49.00278699707167\n ],\n [\n -114.47370593859102,\n 49.005668220091394\n ],\n [\n -114.14869158213136,\n 48.52510052384579\n ],\n [\n -114.08720237955801,\n 48.46980235225462\n ],\n [\n -113.9203031154302,\n 48.48144908533459\n ],\n [\n -113.65677796154424,\n 48.33859233831538\n ],\n [\n -113.58211250127644,\n 48.21875067035853\n ],\n [\n -113.50305495511051,\n 48.2333805603611\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dose, Lindsay Marie 0009-0009-0998-4484","orcid":"https://orcid.org/0009-0009-0998-4484","contributorId":335382,"corporation":false,"usgs":true,"family":"Dose","given":"Lindsay","middleInitial":"Marie","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":900865,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gustilo, Erica Sanderleaf Sarro 0000-0003-4982-5583","orcid":"https://orcid.org/0000-0003-4982-5583","contributorId":330270,"corporation":false,"usgs":true,"family":"Gustilo","given":"Erica Sanderleaf Sarro","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":900866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graves, Tabitha A. 0000-0001-5145-2400 tgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":5898,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha","email":"tgraves@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":900867,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70251861,"text":"70251861 - 2024 - Hawaiian volcanic ash, an airborne fomite for nontuberculous mycobacteria","interactions":[],"lastModifiedDate":"2024-03-04T17:06:59.247","indexId":"70251861","displayToPublicDate":"2023-12-30T11:06:18","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16135,"text":"GeoHealth","active":true,"publicationSubtype":{"id":10}},"title":"Hawaiian volcanic ash, an airborne fomite for nontuberculous mycobacteria","docAbstract":"Nontuberculous mycobacteria (NTM) are environmentally acquired opportunistic pathogens that can cause chronic lung disease. Within the U.S., Hawai'i shows the highest prevalence rates of NTM lung infections. Here, we investigated a potential role for active volcanism at the Kīlauea Volcano located on Hawai'i Island in promoting NTM growth and diversity. We recovered NTM that are known to cause lung disease from plumbing biofilms and soils collected from the Kīlauea environment. We also discovered viable Mycobacterium avium, Mycobacterium abscessus, and Mycobacterium intracellulare subsp. chimaera on volcanic ash collected during the 2018 Kīlauea eruption. Analysis of soil samples showed that NTM prevalence is positively associated with bulk content of phosphorus, sulfur, and total organic carbon. In growth assays, we showed that phosphorus utilization is essential for proliferation of Kīlauea-derived NTM, and demonstrate that NTM cultured with volcanic ash adhere to ash surfaces and remain viable. Ambient dust collected on O'ahu concurrent with the 2018 eruption contained abundant fresh volcanic glass, suggestive of inter-island ash transport. Phylogenomic analyses using whole genome sequencing revealed that Kīlauea-derived NTM are genetically similar to respiratory isolates identified on other Hawaiian Islands. Consequently, we posit that volcanic eruptions could redistribute environmental microorganisms over large scales. While additional studies are needed to confirm a direct role of ash in NTM dispersal, our results suggest that volcanic particulates harbor and can redistribute NTM and should therefore be studied as a fomite for these burgeoning, environmentally acquired respiratory infections.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023GH000889","usgsCitation":"Dawrs, S., Virdi, R., Norton, G., Elias, T., Hasan, N., Robinson, S., Matriz, J., Epperson, L.E., Glickman, C., Beagle, S., Crooks, J.L., Nelson, S.T., Chan, E., Damby, D., Strong, M., and Honda, J., 2024, Hawaiian volcanic ash, an airborne fomite for nontuberculous mycobacteria: GeoHealth, v. 8, no. 1, e2023GH000889, 15 p., https://doi.org/10.1029/2023GH000889.","productDescription":"e2023GH000889, 15 p.","ipdsId":"IP-132859","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":440832,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023gh000889","text":"Publisher Index Page"},{"id":426237,"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 \"coordinates\": [\n [\n [\n -155.4,\n 19.5\n ],\n [\n -155.4,\n 19.2\n ],\n [\n -155.09,\n 19.2\n ],\n [\n -155.09,\n 19.5\n ],\n [\n -155.4,\n 19.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Dawrs, Stephanie","contributorId":334503,"corporation":false,"usgs":false,"family":"Dawrs","given":"Stephanie","email":"","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":895831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Virdi, Ravleen","contributorId":334504,"corporation":false,"usgs":false,"family":"Virdi","given":"Ravleen","email":"","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":895832,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Norton, Grant","contributorId":334505,"corporation":false,"usgs":false,"family":"Norton","given":"Grant","email":"","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":895833,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elias, Tamar 0000-0002-9592-4518 telias@usgs.gov","orcid":"https://orcid.org/0000-0002-9592-4518","contributorId":3916,"corporation":false,"usgs":true,"family":"Elias","given":"Tamar","email":"telias@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":895834,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hasan, Nabeeh","contributorId":334506,"corporation":false,"usgs":false,"family":"Hasan","given":"Nabeeh","email":"","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":895835,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robinson, Schuyler","contributorId":334507,"corporation":false,"usgs":false,"family":"Robinson","given":"Schuyler","email":"","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":895836,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matriz, Jobel","contributorId":334508,"corporation":false,"usgs":false,"family":"Matriz","given":"Jobel","email":"","affiliations":[{"id":80160,"text":"University of Hawai'i, Manoa","active":true,"usgs":false}],"preferred":false,"id":895837,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Epperson, L. Elaine","contributorId":334509,"corporation":false,"usgs":false,"family":"Epperson","given":"L.","email":"","middleInitial":"Elaine","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":895838,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Glickman, Cody","contributorId":334511,"corporation":false,"usgs":false,"family":"Glickman","given":"Cody","email":"","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":895839,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Beagle, Sean","contributorId":334513,"corporation":false,"usgs":false,"family":"Beagle","given":"Sean","email":"","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":895840,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Crooks, James L 0000-0002-0021-5701","orcid":"https://orcid.org/0000-0002-0021-5701","contributorId":264906,"corporation":false,"usgs":false,"family":"Crooks","given":"James","email":"","middleInitial":"L","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":895841,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Nelson, Stephen T.","contributorId":32078,"corporation":false,"usgs":true,"family":"Nelson","given":"Stephen","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":895842,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Chan, Edward","contributorId":334516,"corporation":false,"usgs":false,"family":"Chan","given":"Edward","email":"","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":895843,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Damby, David 0000-0002-3238-3961","orcid":"https://orcid.org/0000-0002-3238-3961","contributorId":206614,"corporation":false,"usgs":true,"family":"Damby","given":"David","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":895844,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Strong, Michael 0000-0002-3247-6260","orcid":"https://orcid.org/0000-0002-3247-6260","contributorId":264904,"corporation":false,"usgs":false,"family":"Strong","given":"Michael","email":"","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":895845,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Honda, Jennifer","contributorId":334520,"corporation":false,"usgs":false,"family":"Honda","given":"Jennifer","email":"","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":895846,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70251369,"text":"70251369 - 2024 - Variable climate-growth relationships of quaking aspen (Populus tremuloides) among Sky Island mountain ranges in the Great Basin, Nevada, USA","interactions":[],"lastModifiedDate":"2024-02-07T13:23:28.375501","indexId":"70251369","displayToPublicDate":"2023-12-30T07:21:42","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Variable climate-growth relationships of quaking aspen (Populus tremuloides) among Sky Island mountain ranges in the Great Basin, Nevada, USA","docAbstract":"The Great Basin is an arid province located in the interior western United States. The region encompasses millions of hectares and quaking aspen (Populus tremuloides Michx.) forests comprise a minor portion of the total area. However, montane aspen forests play a disproportionately large role in providing ecosystem services in the region, including water retention, biodiversity, wildlife habitat, livestock forage, and recreational uses. With warming temperatures, increasing evaporative demand, and heightened precipitation variability, the future of aspen has become a critical concern. Using dendroecological approaches, we assessed growth patterns of 20 aspen stands across three geographically isolated “sky island” mountain ranges spanning portions of the north-central Great Basin. We anticipated that the growth of Great Basin aspen would be strongly influenced by regional climatic patterns and largely in synchrony. Results revealed a more complex growth dynamic that varied among mountain ranges and across environmental gradients. In particular, aspen climate-growth relationships in the slightly dryer Ruby Mountains were strongly and positively correlated (r > 0.5) with previous fall to winter moisture availability. The Jarbidge Mountains had a positive but modest relationship with previous fall to winter moisture availability (r > 0.3). Climate-growth response in the Santa Rosa Mountains, the wettest range, showed no significant response to moisture availability during any time period examined but had greater tree-ring growth with warmer May temperatures. Although tree-ring centennial (1910 – 2010) growth trends were positive for all three mountain ranges, only the Santa Rosa Mountains maintained a positive recent growth trend (1970 – 2010). Moreover, distinct temporal shifts in tree growth-climate relationships in each mountain range suggest potentially unique aspen population adaptations to climate variability. For instance, in two of the mountain ranges, there was a shift from positive/neutral to negative growth relationships with temperature starting around the 1963 – 1987 time period, while tree growth also began simultaneously responding more positively to moisture availability. These growth shifts and observed enhanced sensitivities to monthly and seasonal climate variables over time may reflect dynamic tree growth responses caused by ongoing global climate change, but that may be tempered by local or regional factors, such as the relative availability and timing of soil moisture provided by spring snowmelt. A better understanding of biogeographic variation and causality in aspen growth could provide multiple management pathways governed by resilience characteristics in the face of future anthropogenic and climatic threats.
Quantifying carbon fluxes into and out of coastal soils is critical to meeting greenhouse gas reduction and coastal resiliency goals. Numerous ‘blue carbon’ studies have generated, or benefitted from, synthetic datasets. However, the community those efforts inspired does not have a centralized, standardized database of disaggregated data used to estimate carbon stocks and fluxes. In this paper, we describe a data structure designed to standardize data reporting, maximize reuse, and maintain a chain of credit from synthesis to original source. We introduce version 1.0.0. of the Coastal Carbon Library, a global database of 6723 soil profiles representing blue carbon-storing systems including marshes, mangroves, tidal freshwater forests, and seagrasses. We also present the Coastal Carbon Atlas, an R-shiny application that can be used to visualize, query, and download portions of the Coastal Carbon Library. The majority (4815) of entries in the database can be used for carbon stock assessments without the need for interpolating missing soil variables, 533 are available for estimating carbon burial rate, and 326 are useful for fitting dynamic soil formation models. Organic matter density significantly varied by habitat with tidal freshwater forests having the highest density, and seagrasses having the lowest. Future work could involve expansion of the synthesis to include more deep stock assessments, increasing the representation of data outside of the U.S., and increasing the amount of data available for mangroves and seagrasses, especially carbon burial rate data. We present proposed best practices for blue carbon data including an emphasis on disaggregation, data publication, dataset documentation, and use of standardized vocabulary and templates whenever appropriate. To conclude, the Coastal Carbon Library and Atlas serve as a general example of a grassroots F.A.I.R. (Findable, Accessible, Interoperable, and Reusable) data effort demonstrating how data producers can coordinate to develop tools relevant to policy and decision-making.
The 160-year history of oil and gas drilling in the United States has left a legacy of unplugged orphaned and abandoned wells, some of which are leaking methane and other hazardous chemicals into the environment. The locations of around 120,000 documented orphaned wells are currently known with the number of undocumented orphaned wells possibly ranging towards a million. The bulk of methane emissions originate from only 10 % of orphaned and abandoned wells, while the remaining wells have undetectable emissions. Understanding the sources of methane emissions from orphaned wells is key to estimating emission rates and prioritizing plugging. In this article, we identify key studies reporting methane emission measurements from orphaned and abandoned wells in the published literature and analyze previously published isotopic methane data to categorize the sources of methane emissions. Three primary geologic sources provide methane to a leaking well that can migrate from geologic formations into or along the wellbore to contaminate groundwater, the surface environment, and the atmosphere. These geologic sources of methane are petroleum (oil and gas) sourced reservoirs, coal seams, and methanogenesis occurring in and around the wellbore. Thermogenic petroleum gas reservoirs are associated with the highest emission rates measured to date. The next highest rates are from coalbed methane sources, while biogenic sources are the lowest based on the publicly available measured emissions data. Well conditions that could potentially enable methane transport include decay of the wellhead and surface infrastructure, wellbore deterioration from corrosive fluids in the subsurface, delamination of the casing and cement, damage from seismicity, and new fracture networks created by hydraulic fracturing of newly drilled neighboring wells. With an understanding of these geologic sources and well conditions, we can (1) better identify areas where high-emitting wells are likely to be present, (2) improve emission rate estimates from orphaned and abandoned wells, and (3) better prioritize wells for plugging.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2023.169584","usgsCitation":"Gianoutsos, N.J., Haase, K., and Birdwell, J.E., 2024, Geologic sources and well integrity impact methane emissions from orphaned and abandoned oil and gas wells: Science of the Total Environment, v. 912, 169584, 12 p., https://doi.org/10.1016/j.scitotenv.2023.169584.","productDescription":"169584, 12 p.","ipdsId":"IP-153476","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":440839,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2023.169584","text":"Publisher Index Page"},{"id":424190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -139.94431292840162,\n 54.37807159396496\n ],\n [\n -139.94431292840162,\n 27.394523308971372\n ],\n [\n -73.88969770976064,\n 27.394523308971372\n ],\n [\n -73.88969770976064,\n 54.37807159396496\n ],\n [\n -139.94431292840162,\n 54.37807159396496\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"912","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gianoutsos, Nicholas J. 0000-0002-6510-6549 ngianoutsos@usgs.gov","orcid":"https://orcid.org/0000-0002-6510-6549","contributorId":3607,"corporation":false,"usgs":true,"family":"Gianoutsos","given":"Nicholas","email":"ngianoutsos@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":891635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haase, Karl B. 0000-0002-6897-6494","orcid":"https://orcid.org/0000-0002-6897-6494","contributorId":216317,"corporation":false,"usgs":true,"family":"Haase","given":"Karl B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":891636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":891637,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70240773,"text":"70240773 - 2024 - Conventional rare earth element mineral deposits: The global landscape","interactions":[],"lastModifiedDate":"2024-01-12T15:25:32.908721","indexId":"70240773","displayToPublicDate":"2023-12-29T09:22:13","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Conventional rare earth element mineral deposits: The global landscape","docAbstract":"Four conventional mineral deposit types—carbonatite, alkaline igneous, heavy mineral sand, and regolith-hosted ion-adsorption clay deposits—currently supply global markets with the rare earth elements (REEs) and rare earth oxides (REOs) necessary to meet the technological needs of global communities. The unique properties of REEs make them useful in a wide variety of applications, such as alloys, batteries, catalysts, magnets, phosphors, and polishing compounds. Rare earth element minerals are complex in both composition and structure. Carbonate, oxide, silicate, and phosphate-type minerals contain highly variable amounts of rare earths. Most rare earth-bearing minerals contain mainly lighter rare earths, a mixture of all the rare earths, or only the heavier rare earths.
Diverse technological applications require the full range of light, middle, and heavy rare earths. The production of these elements, in particular the heavy rare earths, remains highly dependent on deposits from China. Diversification of rare earth supply chains is contingent on expanded knowledge of globally distributed resources and an understanding of the degree to which those resources have been explored and evaluated. The knowledge of tectonic setting, typical rock associations, deposit morphology, and deposit genesis has led to the discovery of many conventional-type rare earth deposit types. Recent developments are anticipated to result in further discoveries that have the potential to meet the ever-expanding applications of REEs and REOs to address modern societal needs.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Rare earth metals and minerals industries: Status and prospects","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","usgsCitation":"Foley, N.K., and Ayuso, R.A., 2024, Conventional rare earth element mineral deposits: The global landscape, chap. of Rare earth metals and minerals industries: Status and prospects, p. 17-56.","productDescription":"40 p.","startPage":"17","endPage":"56","ipdsId":"IP-138267","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":424380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Foley, Nora K. 0000-0003-0124-3509 nfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-0124-3509","contributorId":4010,"corporation":false,"usgs":true,"family":"Foley","given":"Nora","email":"nfoley@usgs.gov","middleInitial":"K.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":864786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ayuso, Robert A. 0000-0002-8496-9534 rayuso@usgs.gov","orcid":"https://orcid.org/0000-0002-8496-9534","contributorId":2654,"corporation":false,"usgs":true,"family":"Ayuso","given":"Robert","email":"rayuso@usgs.gov","middleInitial":"A.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":864787,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70231903,"text":"70231903 - 2024 - Energy-related rare earth element sources","interactions":[],"lastModifiedDate":"2024-01-12T15:12:45.934983","indexId":"70231903","displayToPublicDate":"2023-12-29T09:08:25","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"3","title":"Energy-related rare earth element sources","docAbstract":"Energy-related materials such as coal, coal-bearing wastes, and coal combustion products are traditionally thought of as sources or by-products of electric power generation. Increasingly, these materials are considered resources for their content of rare earth elements (REEs) and other useful constituents. In this chapter, we examine the distribution, modes of occurrence, and relative extractability of REEs from coal-derived materials. We also consider economic factors associated with recovery of REEs from these sources. While several coal-derived sources show promise for REE recovery at the pilot scale, in all cases, REE contents are much below those of primary ores, such that extraction and concentrating the REEs require new and innovative approaches that are largely developmental.
Among coal-related sources, fly ash is the most REE-enriched, as REEs from coal are strongly retained in these refractory solids remaining after coal combustion. Partitioning of coal-derived elements into fly ash has been known for decades but this has yet to be commercially exploited. A key drawback shown in this chapter is that a significant fraction of REEs in fly ash is contained in highly insoluble aluminosilicate glasses that make up the largest portion of this material. In addition to testing chemical or physical pretreatment approaches to help improve the extractability of REEs from fly ash, current research is applying modern analytical approaches to better understand the distribution of REEs on increasingly smaller scales, in the interest of targeting their recovery.
Next-most REE-enriched among coal-related materials are solid waste products of coal mining and wastes from coal preparation, both of which are REE-enriched relative to coal itself. These waste coals concentrate mineralogical constituents that are excluded during mining or removed during coal preparation because they do not contribute to the heating value of coal for power generation. Recovery of REEs from coal waste has shown promise at the pilot scale and has the added benefit of converting a waste into useful constituents.
Total REE contents of commercial coals are, on average, much below the 300 parts per million interest level for REE recovery set by the U.S. Department of Energy (DOE). However, as reviewed in this chapter, certain horizons within coal beds show preferential REE enrichment and could be targeted by selective mining. Beyond this, certain coals are REE-enriched overall due to their unique geologic histories involving derivation from REE-enriched sediment sources, deposition of volcanic ash during coal formation, or interaction of coal with REE-bearing fluids.
Acidic drainage from abandoned coal mines is produced by the breakdown of pyrite (FeS2), which is unstable in oxygenated conditions. While these acidic fluids have lower REE contents than any of the coal-based solids described above, they are proportionally enriched in certain heavy rare earths, especially yttrium (Y). Precipitates from coal-based acid-mine drainage concentrate REEs to levels that are of interest for recovery, and these are also promising sources for extraction at the pilot scale.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Rare earth metals and minerals industries: Status and prospects","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","usgsCitation":"Kolker, A., Lefticariu, L., and Anderson, S.T., 2024, Energy-related rare earth element sources, chap. 3 of Rare earth metals and minerals industries: Status and prospects, p. 57-102.","productDescription":"46 p.","startPage":"57","endPage":"102","ipdsId":"IP-137470","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":424379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":424378,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/chapter/10.1007/978-3-031-31867-2_3"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kolker, Allan 0000-0002-5768-4533 akolker@usgs.gov","orcid":"https://orcid.org/0000-0002-5768-4533","contributorId":643,"corporation":false,"usgs":true,"family":"Kolker","given":"Allan","email":"akolker@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":844062,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lefticariu, Liliana 0000-0003-3413-654X","orcid":"https://orcid.org/0000-0003-3413-654X","contributorId":251875,"corporation":false,"usgs":false,"family":"Lefticariu","given":"Liliana","email":"","affiliations":[{"id":13212,"text":"Southern Illinois University","active":true,"usgs":false}],"preferred":false,"id":844063,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Steven T. 0000-0003-3481-3424 sanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-3481-3424","contributorId":2532,"corporation":false,"usgs":true,"family":"Anderson","given":"Steven","email":"sanderson@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":844064,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70250775,"text":"70250775 - 2024 - Hydrothermal monazite and xenotime chemistry as genetic discriminators for intrusion-related and orogenic gold deposits: Implications for an orogenic origin of the Pogo gold deposit, Alaska","interactions":[],"lastModifiedDate":"2024-05-20T15:17:04.532583","indexId":"70250775","displayToPublicDate":"2023-12-29T07:01:14","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2746,"text":"Mineralium Deposita","active":true,"publicationSubtype":{"id":10}},"title":"Hydrothermal monazite and xenotime chemistry as genetic discriminators for intrusion-related and orogenic gold deposits: Implications for an orogenic origin of the Pogo gold deposit, Alaska","docAbstract":"Attempts to geochemically distinguish between metamorphic-hydrothermal systems that form orogenic gold deposits and both reduced and oxidized magmatic-hydrothermal systems using isotopes or metal associations have proven ambiguous, particularly for orogenic gold and reduced intrusion-related gold systems. The absence of conclusive geochemical discriminators and the overlap in geologic characteristics have led to gold deposit models being potentially incorrectly applied, which in turn negatively affect regional mineral exploration and mine planning. In this study, in situ electron microprobe geochemical analyses of hydrothermal monazite and xenotime crystals associated with different types of gold-bearing deposits are shown to be effective geochemical discriminators. There are notable differences in mineral chemistry such as rare earth element (REE) profiles, total light REE, Dy, Er, Pr, Y, Nd/Sm, and La/Sm that distinguish monazite precipitated from metamorphic-hydrothermal fluids that form orogenic gold deposits and those precipitated from magmatic-hydrothermal fluids that form both porphyry Cu-Mo-Au and reduced intrusion-related gold deposits. Notable differences in overall xenotime abundances and concentrations of heavy REEs, Ca, and Sc are distinctive between the different deposit classes for xenotime. The origin of the controversially classified Pogo gold deposit, Tintina gold province, Alaska, which has been characterized as both a reduced intrusion-related and an orogenic gold deposit, is tested based upon the noted chemical differences associated with these hydrothermal phosphates. The findings of this study have implications for exploration and mine development in the Tintina gold province and other areas that contain deposits that are controversially classified as either orogenic or as magmatic-hydrothermal gold deposits.
Landsat 9 (L9) was launched on 27 September 2021. This spacecraft contained two instruments, the Operational Land Imager-2 (OLI-2) and Thermal Infrared Sensor-2 (TIRS-2), that allow for a continuation of the Landsat program and the mission to acquire multi-spectral observations of the globe on a moderate scale. Following a period of commissioning, during which time the spacecraft and instruments were initialized and set up for operations, with the initial calibration performed, the mission moved to an operational mode This operational mode involved the same cadence and methods that were performed for the Landsat 8 (L8) spacecraft and the two instruments onboard, the Operational Land Imager-1 (OLI-1) and Thermal Infrared Sensor-1 (TIRS-1), with respect to calibration, characterization, and validation. This paper discusses the geometric operational aspects of the L9 instruments during the first year of the mission and post-commissioning, and compares these same geometric activities performed for L8 during the same time frame. During this time, optical axes of the two sensors, OLI-1 and OLI-2, were adjusted to stay aligned with the spacecraft’s Attitude Control System (ACS), and the TIRS-1 and TIRS-2 instruments were adjusted to stay aligned with the OLI-1 and OLI-2 instruments, respectively. In this paper, the L9 operational adjustments are compared to the same operational aspects of L8 during this same time frame. The comparisons shown in this paper will demonstrate that both instruments aboard L8 and L9 performed very similar geometric qualities while fully meeting the expected requirements. This paper describes the geometric differences between the L9 imagery that was made available to the public prior to the reprocessing campaign that was performed using the new calibration updates to the sensor and to ACS and TIRS-to-OLI alignment parameters. This reprocessing campaign of L9 products involved data acquired from the launch of the spacecraft up to early 2023.
","language":"English","publisher":"MDPI","doi":"10.3390/rs16010133","usgsCitation":"Choate, M., Rengarajan, R., Hasan, N., Denevan, A., and Ruslander, K., 2024, Operational aspects of Landsat 8 and 9 geometry: Remote Sensing, v. 16, no. 1, 133, 34 p., https://doi.org/10.3390/rs16010133.","productDescription":"133, 34 p.","ipdsId":"IP-157652","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":467043,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs16010133","text":"Publisher Index Page"},{"id":462241,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-12-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Choate, Michael J. 0000-0002-8101-4994","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":251780,"corporation":false,"usgs":true,"family":"Choate","given":"Michael J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":913917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rengarajan, Rajagopalan 0000-0003-1860-7110","orcid":"https://orcid.org/0000-0003-1860-7110","contributorId":242014,"corporation":false,"usgs":false,"family":"Rengarajan","given":"Rajagopalan","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":913918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hasan, Nahid 0000-0002-0463-601X","orcid":"https://orcid.org/0000-0002-0463-601X","contributorId":292342,"corporation":false,"usgs":false,"family":"Hasan","given":"Nahid","email":"","affiliations":[{"id":40546,"text":"KBR, Contractor to the USGS Earth Resources Observation and Science (EROS) Center","active":true,"usgs":false}],"preferred":false,"id":913919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Denevan, Alex 0000-0002-1215-3261","orcid":"https://orcid.org/0000-0002-1215-3261","contributorId":270398,"corporation":false,"usgs":false,"family":"Denevan","given":"Alex","email":"","affiliations":[{"id":40546,"text":"KBR, Contractor to the USGS Earth Resources Observation and Science (EROS) Center","active":true,"usgs":false}],"preferred":false,"id":913920,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ruslander, Kathryn 0000-0003-3036-1731","orcid":"https://orcid.org/0000-0003-3036-1731","contributorId":330181,"corporation":false,"usgs":false,"family":"Ruslander","given":"Kathryn","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":913921,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70250749,"text":"70250749 - 2024 - Modular compositional learning improves 1D hydrodynamic lake model performance by merging process-based modeling with deep learning","interactions":[],"lastModifiedDate":"2024-01-02T12:32:07.209065","indexId":"70250749","displayToPublicDate":"2023-12-28T06:30:40","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5407,"text":"Journal of Advances in Modeling Earth Systems","active":true,"publicationSubtype":{"id":10}},"title":"Modular compositional learning improves 1D hydrodynamic lake model performance by merging process-based modeling with deep learning","docAbstract":"Hybrid Knowledge-Guided Machine Learning (KGML) models, which are deep learning models that utilize scientific theory and process-based model simulations, have shown improved performance over their process-based counterparts for the simulation of water temperature and hydrodynamics. We highlight the modular compositional learning (MCL) methodology as a novel design choice for the development of hybrid KGML models in which the model is decomposed into modular sub-components that can be process-based models and/or deep learning models. We develop a hybrid MCL model that integrates a deep learning model into a modularized, process-based model. To achieve this, we first train individual deep learning models with the output of the process-based models. In a second step, we fine-tune one deep learning model with observed field data. In this study, we replaced process-based calculations of vertical diffusive transport with deep learning. Finally, this fine-tuned deep learning model is integrated into the process-based model, creating the hybrid MCL model with improved overall projections for water temperature dynamics compared to the original process-based model. We further compare the performance of the hybrid MCL model with the process-based model and two alternative deep learning models and highlight how the hybrid MCL model has the best performance for projecting water temperature, Schmidt stability, buoyancy frequency, and depths of different isotherms. Modular compositional learning can be applied to existing modularized, process-based model structures to make the projections more robust and improve model performance by letting deep learning estimate uncertain process calculations.
Molecular tools are increasingly applied for assessing and monitoring biodiversity and informing conservation action. While recent developments in genetic and genomic methods provide greater sensitivity in analysis and the capacity to address new questions, they are not equally available to all practitioners: There is considerable bias across institutions and countries in access to technologies, funding, and training. Consequently, in many cases, more accessible traditional genetic data (e.g., microsatellites) are still utilized for making conservation decisions. Conservation approaches need to be pragmatic by tackling clearly defined management questions and using the most appropriate methods available, while maximizing the use of limited resources. Here we present some key questions to consider when applying the molecular toolbox for accessible and actionable conservation management. Finally, we highlight a number of important steps to be addressed in a collaborative way, which can facilitate the broad integration of molecular data into conservation.
Assessing the appropriateness of existing native plant materials can both determine which seed source to utilize for restoration projects, and identify locations for which new seed sources need to be developed. Here, we demonstrate an approach to meet these needs. This method identifies areas of high restoration need based on disturbance patterns, assesses the regional suitability of existing native plant materials based on climate similarity, and highlights geographic (and climatic) gaps where existing materials are likely unsuitable and where plant material development projects can be prioritized. We examined 12 high priority restoration species across the Colorado Plateau, a 38-million-ha region of the Intermountain West, United States to test our methodological pipeline. Fifty-four percent of the Colorado Plateau is disturbed by livestock grazing, wildfires that have burned in the past 20 years, or energy production from oil and gas wells, natural gas pipelines, and coal mines. Of the 28 commercially available plant materials for six of the focal species, only 3 have climate similarity that encompass more than 50% of the species modeled habitat on the Colorado Plateau. Across all commercial materials, most species (10 of 12) do not have any suitable plant material for 70% or more of their geographic range on the Colorado Plateau. Of those areas identified as not having any suitable plant materials, 47–56% are also disturbed. Our method provides usable, flexible protocols and spatially referenced data sources for optimizing the planning of new native plant materials in any region where restoration is needed and spatial data are available.
The Red Shiner Cyprinella lutrensis is one of the most prolific and ecologically destructive invasive fish species in the southwestern United States. The production and release of YY individuals as Trojan sex chromosome carriers can theoretically eradicate invasive fish populations by eventually eliminating phenotypic females.
The YY individuals are typically produced through hormonally induced sex reversals and selective breeding of subsequently feminized males. We tested three dosages of estradiol-17β (E2)-treated diets (50, 100, and 150 mg of E2 per kg of diet) administered to sexually immature Red Shiner for various durations to determine their effectiveness at feminizing Red Shiner cohorts. Survival, growth, and gonadal development were assessed for each treatment.
All E2 treatments had minimal, if any, detrimental effects on the growth and gonadal development of Red Shiner. The 50-mg dosage lasting from 2 to 120 days posthatch achieved a 100% feminization rate while using the lowest amount of E2; therefore, this dosage and treatment interval are recommended when attempting Red Shiner feminization under these rearing conditions. Feminization of males allowed for the spawning of neofemales (FXY) with wild-type males (MXY), which resulted in the first putative YY Red Shiner. The YY verification crosses (n = 20) resulted in predominately male offspring (189 males/191 offspring) except for (1) an intersex individual from an MYY × FXX cross with two previtellogenic oocytes in its testis and (2) a single female that may have resulted from an inbred cross between an XY male and a YY female or from an unknown autosomal or environmental effect on sexual phenotype.
More progeny tests with inbred and outbred crosses should be conducted to determine the prevalence of female offspring from YY individuals and how this may impact an eradication strategy featuring releases of YY Red Shiner.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/naaq.10314","usgsCitation":"Teal, C.N., Schill, D., Bauder, J.M., Fogelson, S.B., Fitzsimmons, K., Stewart, W., Culver, M., and Bonar, S.A., 2024, The effects of estradiol-17β on the sex reversal, survival, and growth of Red Shiner and its use in the development of YY individuals: North American Journal of Aquaculture, v. 86, no. 1, p. 110-129, https://doi.org/10.1002/naaq.10314.","productDescription":"20 p.","startPage":"110","endPage":"129","ipdsId":"IP-155076","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":498669,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/670656","text":"External Repository"},{"id":429775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-12-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Teal, Chad N.","contributorId":337952,"corporation":false,"usgs":false,"family":"Teal","given":"Chad","email":"","middleInitial":"N.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":902800,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schill, Daniel J.","contributorId":337953,"corporation":false,"usgs":false,"family":"Schill","given":"Daniel J.","affiliations":[{"id":61802,"text":"Fisheries Management Solutions","active":true,"usgs":false}],"preferred":false,"id":902801,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bauder, Javan Mathias 0000-0002-2055-5324","orcid":"https://orcid.org/0000-0002-2055-5324","contributorId":337814,"corporation":false,"usgs":true,"family":"Bauder","given":"Javan","email":"","middleInitial":"Mathias","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902802,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fogelson, Susan B.","contributorId":337954,"corporation":false,"usgs":false,"family":"Fogelson","given":"Susan","email":"","middleInitial":"B.","affiliations":[{"id":61804,"text":"Fishhead Labs","active":true,"usgs":false}],"preferred":false,"id":902803,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitzsimmons, Kevin","contributorId":337955,"corporation":false,"usgs":false,"family":"Fitzsimmons","given":"Kevin","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":902804,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stewart, William T.","contributorId":337956,"corporation":false,"usgs":false,"family":"Stewart","given":"William T.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":902805,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Culver, Melanie 0000-0001-5380-3059 mculver@usgs.gov","orcid":"https://orcid.org/0000-0001-5380-3059","contributorId":197693,"corporation":false,"usgs":true,"family":"Culver","given":"Melanie","email":"mculver@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902806,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902807,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70251352,"text":"70251352 - 2024 - How long have we been mistaken? Multi-tools shedding light into the systematics of the widespread deep-water genus Madrepora Linnaeus, 1758 (Scleractinia)","interactions":[],"lastModifiedDate":"2024-02-07T15:05:56.570052","indexId":"70251352","displayToPublicDate":"2023-12-23T08:41:38","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2779,"text":"Molecular Phylogenetics and Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"How long have we been mistaken? Multi-tools shedding light into the systematics of the widespread deep-water genus Madrepora Linnaeus, 1758 (Scleractinia)","title":"How long have we been mistaken? Multi-tools shedding light into the systematics of the widespread deep-water genus Madrepora Linnaeus, 1758 (Scleractinia)","docAbstract":"Deep-water coral reefs are found worldwide and harbor biodiversity levels that are comparable to their shallow-water counterparts. However, the genetic diversity and population structure of deep-water species remain poorly explored, and historical taxonomical issues still need to be resolved. Here we used microsatellite markers as well as ultraconserved elements (UCE) and exons to shed light on the population structure, genetic diversity, and phylogenetic position of the genus Madrepora, which contains M. oculata, one of the most widespread scleractinian species. Population structure of 107 samples from three Southwestern Atlantic sedimentary basins revealed the occurrence of a cryptic species, herein named M. piresae sp. nov. (authored by Kitahara, Capel and Zilberberg), which can be found in sympatry with M. oculata. Phylogeny reconstructions based on 134 UCEs and exon regions corroborated the population genetic data, with the recovery of two well-supported groups, and reinforced the polyphyly of the family Oculinidae. In order to better accommodate the genus Madrepora, while reducing taxonomical confusion associated with the name Madreporidae, we propose the monogeneric family Bathyporidae fam. nov. (authored by Kitahara, Capel, Zilberberg and Cairns). Our findings advance the knowledge on the widespread deep-water genus Madrepora, resolve a long-standing question regarding the phylogenetic position of the genus, and highlight the need of a worldwide review of the genus.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ympev.2023.107994","usgsCitation":"Capel, K.C., Zilberberg, C., Carpes, R.M., Morrison, C., Vaga, C.F., Quattrini, A., Quek, R.Z., Huang, D., Cairns, S.D., and Kitahara, M.V., 2024, How long have we been mistaken? Multi-tools shedding light into the systematics of the widespread deep-water genus Madrepora Linnaeus, 1758 (Scleractinia): Molecular Phylogenetics and Evolution, v. 191, 107994, 10 p., https://doi.org/10.1016/j.ympev.2023.107994.","productDescription":"107994, 10 p.","ipdsId":"IP-154239","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":425471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"191","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Capel, Katia C. C.","contributorId":333882,"corporation":false,"usgs":false,"family":"Capel","given":"Katia","email":"","middleInitial":"C. C.","affiliations":[{"id":79999,"text":"Center for Marine Biology, São Paulo University, São Sebastião, São Paulo, Brazil","active":true,"usgs":false}],"preferred":false,"id":894214,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zilberberg, Carla","contributorId":333883,"corporation":false,"usgs":false,"family":"Zilberberg","given":"Carla","email":"","affiliations":[{"id":80000,"text":"Department of Zoology, Institute of Biodiversity and Sustainability – Nupem, Federal University of Rio de Janeiro, Macaé, Rio de Janeiro, Brazil","active":true,"usgs":false}],"preferred":false,"id":894215,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carpes, Raphael M.","contributorId":333884,"corporation":false,"usgs":false,"family":"Carpes","given":"Raphael","email":"","middleInitial":"M.","affiliations":[{"id":80000,"text":"Department of Zoology, Institute of Biodiversity and Sustainability – Nupem, Federal University of Rio de Janeiro, Macaé, Rio de Janeiro, Brazil","active":true,"usgs":false}],"preferred":false,"id":894216,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morrison, Cheryl 0000-0001-9425-691X cmorrison@usgs.gov","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":202644,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","email":"cmorrison@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":894217,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vaga, Claudia F.","contributorId":333885,"corporation":false,"usgs":false,"family":"Vaga","given":"Claudia","email":"","middleInitial":"F.","affiliations":[{"id":80002,"text":"Center for Marine Biology, São Paulo University, São Sebastião, São Paulo, Brazil; Graduate Program in Zoology, Department of Zoology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil","active":true,"usgs":false}],"preferred":false,"id":894218,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Quattrini, Andrea M.","contributorId":333886,"corporation":false,"usgs":false,"family":"Quattrini","given":"Andrea M.","affiliations":[{"id":80003,"text":"Department of Invertebrate Zoology, Smithsonian Institution, Washington DC, United States of America","active":true,"usgs":false}],"preferred":false,"id":894219,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Quek, Randolph Z. B.","contributorId":333887,"corporation":false,"usgs":false,"family":"Quek","given":"Randolph","email":"","middleInitial":"Z. B.","affiliations":[{"id":80004,"text":"Department of Biological Sciences, National University of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":894220,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Huang, Danwei","contributorId":333888,"corporation":false,"usgs":false,"family":"Huang","given":"Danwei","email":"","affiliations":[{"id":80005,"text":"Department of Biological Sciences, National University of Singapore, Singapore; Lee Kong Chian Natural History Museum, National University of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":894221,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cairns, Stephen D.","contributorId":333889,"corporation":false,"usgs":false,"family":"Cairns","given":"Stephen","email":"","middleInitial":"D.","affiliations":[{"id":80003,"text":"Department of Invertebrate Zoology, Smithsonian Institution, Washington DC, United States of America","active":true,"usgs":false}],"preferred":false,"id":894222,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kitahara, Marcelo V.","contributorId":333890,"corporation":false,"usgs":false,"family":"Kitahara","given":"Marcelo","email":"","middleInitial":"V.","affiliations":[{"id":80006,"text":"Center for Marine Biology, São Paulo University; Graduate Program in Zoology, Department of Zoology, Institute of Biosciences, University of São Paulo; Department of Invertebrate Zoology, Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":894223,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70250692,"text":"70250692 - 2024 - Usurpation and brooding of Least Tern (Sternula antillarum) chicks by Common Terns (Sterna hirundo)","interactions":[],"lastModifiedDate":"2023-12-27T12:45:06.135111","indexId":"70250692","displayToPublicDate":"2023-12-23T06:43:37","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Usurpation and brooding of Least Tern (Sternula antillarum) chicks by Common Terns (Sterna hirundo)","docAbstract":"