Aquifer flow systems near seawater interfaces can be complicated by density-driven flows and the formation of stagnation zones, which inevitably introduces uncertainty into groundwater age-dating. While age-dating has proved effective to understand the seawater intrusion and aquifer salinization process in coastal aquifers, further efforts are needed to propagate model and data uncertainty to the uncertainty associated with the inferred age distributions. This study was performed in a coastal aquifer located close to the Yellow Sea, South Korea, where there is a decreasing trend of groundwater levels due to recent heavy exploitation, raising a warning of induced seawater intrusion. We inferred the groundwater age distributions in wells around the intrusion zone and estimated the uncertainty associated with the inference based on multiple age tracers including 3H, tritiogenic 3He, radiogenic 4He, CFC-11, CFC-12 and CFC-113 using Bayesian inference. We examined various models representing the age distributions including traditional parametric Lumped Parameter Models (LPMs) and two non-parametric “shape-free” models. The results showed that the mean ages at the study site ranged from 10.9 to 522.5 y. Complex, multimodal distributions of ages occurred near a seawater intrusion area and upland recharge zones, implying converging paths of a wide range of different ages in those regions. In particular, the age distributions estimated near the seawater intrusion interface were characterized by heavy-tailed mixing structures with elevated concentrations of 4He. This likely indicates density-driven upward flow at the seawater intrusion interface, forcing old groundwater rich in 4He into the shallow aquifer. The Bayesian inference estimated large uncertainties particularly for the old age distributions, which was attributed partly to the gradual accumulation of 4He in groundwater. The Bayesian inference improved understanding of flow dynamics at a complex seawater interface and identified opportunities to further reduce uncertainty of old water age estimates that characterize upwelling groundwater near the interface.
The ability to quantify structural uncertainty in geological models that incorporate geophysical data is affected by two primary sources of uncertainty: geophysical parameter uncertainty and uncertainty in the relationship between geophysical parameters and geological properties of interest. Here, we introduce an open-source, trans-dimensional Bayesian Markov chain Monte Carlo (McMC) algorithm GeoBIPy—Geophysical Bayesian Inference in Python—for robust uncertainty analysis of time-domain or frequency-domain airborne electromagnetic (AEM) data. The McMC algorithm provides a robust assessment of geophysical parameter uncertainty using a trans-dimensional approach that lets the AEM data inform the level of model complexity necessary by allowing the number of model layers itself to be an unknown parameter. Additional components of the Bayesian algorithm allow the user to solve for parameters such as data errors or corrections to the measured instrument height above ground. Probability distributions for a user-specified number of lithologic classes are developed through posterior clustering of McMC-derived resistivity models. Estimates of geological model structural uncertainty are thus obtained through the joint probability of geophysical parameter uncertainty and the uncertainty in the definition of each class. Examples of the implementation of this algorithm are presented for both time-domain and frequency-domain AEM data acquired in Nebraska, USA.
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\"}}]}","volume":"224","issue":"17","noUsgsAuthors":false,"publicationDate":"2020-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":798227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foks, N. Leon 0000-0002-4907-3679","orcid":"https://orcid.org/0000-0002-4907-3679","contributorId":239959,"corporation":false,"usgs":false,"family":"Foks","given":"N. Leon","affiliations":[{"id":48073,"text":"Apogee Engineering, LLC; Contracted to USGS","active":true,"usgs":false}],"preferred":false,"id":798228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":798229,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70212679,"text":"70212679 - 2021 - Environmental gradients of selection for an alpine-obligate bird, the white-tailed ptarmigan (Lagopus leucura)","interactions":[],"lastModifiedDate":"2021-01-19T16:51:01.09122","indexId":"70212679","displayToPublicDate":"2020-08-17T07:30:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1890,"text":"Heredity","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Environmental gradients of selection for an alpine-obligate bird, the white-tailed ptarmigan (Lagopus leucura)","title":"Environmental gradients of selection for an alpine-obligate bird, the white-tailed ptarmigan (Lagopus leucura)","docAbstract":"The warming climate will expose alpine species adapted to a highly seasonal, harsh environment to novel environmental conditions. A species can shift their distribution, acclimate, or adapt in response to a new climate. Alpine species have little suitable habitat to shift their distribution, and the limits of acclimation will likely be tested by climate change in the long-term. Adaptive genetic variation may provide the raw material for species to adapt to this changing environment. Here, we use a genomic approach to describe adaptive divergence in an alpine-obligate species, the white-tailed ptarmigan (Lagopus leucura), a species distributed from Alaska to New Mexico, across an environmentally variable geographic range. Previous work has identified genetic structure and morphological, behavioral, and physiological differences across the species’ range; however, those studies were unable to determine the degree to which adaptive divergence is correlated with local variation in environmental conditions. We used a genome-wide dataset generated from 95 white-tailed ptarmigan distributed throughout the species’ range and genotype–environment association analyses to identify the genetic signature and environmental drivers of local adaptation. We detected associations between multiple environmental gradients and candidate adaptive loci, suggesting ptarmigan populations may be locally adapted to the plant community composition, elevation, local climate, and to the seasonality of the environment. Overall, our results suggest there may be groups within the species’ range with genetic variation that could be essential for adapting to a changing climate and helpful in guiding conservation action.
","language":"English","publisher":"Nature","doi":"10.1038/s41437-020-0352-6","usgsCitation":"Zimmerman, S.J., Aldridge, C., Langin, K.M., Wann, G.T., Cornman, R.S., and Oyler-McCance, S.J., 2021, Environmental gradients of selection for an alpine-obligate bird, the white-tailed ptarmigan (Lagopus leucura): Heredity, v. 126, p. 117-131, https://doi.org/10.1038/s41437-020-0352-6.","productDescription":"16 p.","startPage":"117","endPage":"131","onlineOnly":"N","ipdsId":"IP-113643","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":454482,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41437-020-0352-6","text":"Publisher Index Page"},{"id":377878,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","state":"Alaska, Washington, Montana, Colorado, New Mexico, Yukon, British Columbia, 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0000-0003-3926-6941","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":213471,"corporation":false,"usgs":false,"family":"Aldridge","given":"Cameron L.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":797276,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langin, Kathryn M. 0000-0002-1799-1942","orcid":"https://orcid.org/0000-0002-1799-1942","contributorId":239569,"corporation":false,"usgs":false,"family":"Langin","given":"Kathryn","email":"","middleInitial":"M.","affiliations":[{"id":47923,"text":"United States Geological Survey","active":true,"usgs":false}],"preferred":false,"id":797277,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wann, Gregory T 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Wounding records have been maintained for 70 years under the assumption that they are a reliable and accurate reflection of sea lamprey damage inflicted on fish populations. However, two key assumptions underpinning the use of these data need thorough evaluation: sea lamprey wounds follow a predictable healing progression, and individuals classify wounds accurately and reliably. To assess these assumptions, we conducted a workshop where experienced professionals examined lake trout with known sea lamprey wounds. For most lake trout, pictures were taken at regular intervals during the healing process. Our evaluation of wound pictures found high variability in healing times and wound progressions that did not conform to the currently used classification system. Participants’ wound classification agreement and accuracy were low and misclassification rates were high for most wound types. Training provided during the workshops did not markedly improve these metrics. We assessed wound classification accuracy for the first time and found assumptions of high accuracy and agreement are not met. We recommend misclassification rates be incorporated into models using wound data, sensitivity analyses be conducted to assess the potential impact of wound misclassification on estimates of key metrics (such as sea lamprey-induced mortality for lake trout), and alternative biomarkers be developed to quantify wound status with greater accuracy and precision.
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University","active":true,"usgs":false}],"preferred":false,"id":796468,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":796469,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Treska, Ted","contributorId":141105,"corporation":false,"usgs":false,"family":"Treska","given":"Ted","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796470,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fischer, Gregory J.","contributorId":178010,"corporation":false,"usgs":false,"family":"Fischer","given":"Gregory","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":796471,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70212861,"text":"70212861 - 2021 - Elemental and radionuclide exposures and uptakes by small rodents, invertebrates, and vegetation at active and post-production uranium mines in the Grand Canyon watershed","interactions":[],"lastModifiedDate":"2021-02-03T21:05:48.109321","indexId":"70212861","displayToPublicDate":"2020-08-13T20:16:28","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1226,"text":"Chemosphere","active":true,"publicationSubtype":{"id":10}},"title":"Elemental and radionuclide exposures and uptakes by small rodents, invertebrates, and vegetation at active and post-production uranium mines in the Grand Canyon watershed","docAbstract":"The effects of breccia pipe uranium mining in the Grand Canyon watershed (Arizona) on ecological and cultural resources are largely unknown. We characterized the exposure of biota to uranium and co-occurring ore body elements during active ore production and at a site where ore production had recently concluded. Our results indicate that biota have taken up uranium and other elements (e.g., arsenic, cadmium, copper, molybdenum, uranium) from exposure to ore and surficial contamination, like blowing dust. Results indicate the potential for prolonged exposure to elements and radionuclides upon conclusion of active ore production. Mean radium-226 in deer mice was up to 4 times greater than uranium-234 and uranium-238 in those same samples; this may indicate a potential for, but does not necessarily imply, radium-226 toxicity. Soil screening benchmarks for uranium and molybdenum and other toxicity thresholds for arsenic, copper, selenium, uranium (e.g., growth effects) were exceeded in vegetation, invertebrates, and rodents (Peromyscus spp., Thomomys bottae, Tamias dorsalis, Dipodomys deserti). However, the prevalence and severity of microscopic lesions in rodent tissues (as direct evidence of biological effects of uptake and exposure) could not be definitively linked to mining. Our data indicate that land managers might consider factors like species, seasonal changes in environmental concentrations, and bioavailability, when determining mine permitting and remediation in the Grand Canyon watershed. Ultimately, our results will be useful for site-specific ecological risk analysis and can support future decisions regarding the mineral extraction withdrawal in the Grand Canyon watershed and elsewhere.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2020.127908","usgsCitation":"Cleveland, D.M., Hinck, J.E., and Lankton, J.S., 2021, Elemental and radionuclide exposures and uptakes by small rodents, invertebrates, and vegetation at active and post-production uranium mines in the Grand Canyon watershed: Chemosphere, v. 263, Article: 127908, 15 p.; Data release, https://doi.org/10.1016/j.chemosphere.2020.127908.","productDescription":"Article: 127908, 15 p.; Data release","ipdsId":"IP-118076","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":454487,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemosphere.2020.127908","text":"Publisher Index Page"},{"id":378086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":378184,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94OVQO9","text":"USGS data release","linkHelpText":"Chemical analyses and histopathology of organisms and plants collected from breccia pipe uranium mine sites in the Grand Canyon watershed, 2015-2020"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.961181640625,\n 35.67514743608467\n ],\n [\n -111.02783203125,\n 35.67514743608467\n ],\n [\n -111.02783203125,\n 36.94989178681327\n ],\n [\n -113.961181640625,\n 36.94989178681327\n ],\n [\n -113.961181640625,\n 35.67514743608467\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"263","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cleveland, Danielle M. 0000-0003-3880-4584 dcleveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3880-4584","contributorId":187471,"corporation":false,"usgs":true,"family":"Cleveland","given":"Danielle","email":"dcleveland@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":797718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hinck, Jo Ellen 0000-0002-4912-5766 jhinck@usgs.gov","orcid":"https://orcid.org/0000-0002-4912-5766","contributorId":2743,"corporation":false,"usgs":true,"family":"Hinck","given":"Jo","email":"jhinck@usgs.gov","middleInitial":"Ellen","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":797719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lankton, Julia S. 0000-0002-6843-4388 jlankton@usgs.gov","orcid":"https://orcid.org/0000-0002-6843-4388","contributorId":5888,"corporation":false,"usgs":true,"family":"Lankton","given":"Julia","email":"jlankton@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":797720,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216477,"text":"70216477 - 2021 - Integrating the evidence for a terrestrial carbon sink caused by increasing atmospheric CO2","interactions":[],"lastModifiedDate":"2021-10-26T16:04:40.658298","indexId":"70216477","displayToPublicDate":"2020-08-12T07:12:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"title":"Integrating the evidence for a terrestrial carbon sink caused by increasing atmospheric CO2","docAbstract":"Atmospheric carbon dioxide concentration ([CO2]) is increasing, which increases leaf‐scale photosynthesis and intrinsic water‐use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO2] increase and thus climate change. However, ecosystem CO2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO2]‐driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO2] (iCO2) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre‐industrial times. Established theory, supported by experiments, indicates that iCO2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO2 responses are high in comparison to experiments and predictions from theory. Plant mortality and soil carbon iCO2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO2, albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.
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0000-0002-0110-3381","orcid":"https://orcid.org/0000-0002-0110-3381","contributorId":245075,"corporation":false,"usgs":false,"family":"Voelker","given":"Steve","email":"","middleInitial":"L","affiliations":[{"id":49085,"text":"Department of Environmental and Forest Biology, State University of New York College of Environmental Science and Forestry, Syracuse, NY, 13210 USA","active":true,"usgs":false}],"preferred":false,"id":805302,"contributorType":{"id":1,"text":"Authors"},"rank":60},{"text":"Whelan, Mary E 0000-0002-2067-1835","orcid":"https://orcid.org/0000-0002-2067-1835","contributorId":245076,"corporation":false,"usgs":false,"family":"Whelan","given":"Mary","email":"","middleInitial":"E","affiliations":[{"id":49086,"text":"Department of Environmental Sciences, Rutgers University, 14 College Farm Road, New Brunswick, NJ, 08901 USA","active":true,"usgs":false}],"preferred":false,"id":805303,"contributorType":{"id":1,"text":"Authors"},"rank":61},{"text":"Zuidema., Peiter A 0000-0001-8100-1168","orcid":"https://orcid.org/0000-0001-8100-1168","contributorId":245077,"corporation":false,"usgs":false,"family":"Zuidema.","given":"Peiter","email":"","middleInitial":"A","affiliations":[{"id":49087,"text":"Forest Ecology and Forest Management group, Wageningen University, PO Box 47, Wageningen, 6700 AA the Netherlands","active":true,"usgs":false}],"preferred":false,"id":805304,"contributorType":{"id":1,"text":"Authors"},"rank":62}]}} ,{"id":70211942,"text":"70211942 - 2021 - Forest density intensifies the importance of snowpack to growth in water-limited pine forests","interactions":[],"lastModifiedDate":"2021-01-19T16:06:39.699255","indexId":"70211942","displayToPublicDate":"2020-08-04T12:10:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Forest density intensifies the importance of snowpack to growth in water-limited pine forests","docAbstract":"Warming climate and resulting declines in seasonal snowpack have been associated with drought stress and tree mortality in seasonally snow‐covered watersheds worldwide. Meanwhile, increasing forest density has further exacerbated drought stress due to intensified tree‐tree competition. Using a uniquely detailed dataset of population‐level forest growth (n=2495 sampled trees), we examined how inter‐annual variability in growth relates to snow volume across a range of forest densities (e.g., competitive environments) in sites spanning a broad aridity gradient across the United States. Forest growth was positively related to snowpack in water‐limited forests located at low latitude, and this relationship was intensified by forest density. However, forest growth was negatively related to snowpack in a higher latitude more energy‐limited forest, and this relationship did not interact with forest density. Future reductions in snowpack may have contrasting consequences, as growth may respond positively in energy‐limited forests and negatively in water‐limited forests; however, these declines may be mitigated by reducing stand density through forest thinning.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2211","usgsCitation":"Gleason, K.E., Bradford, J., D’Amato, A.W., Fraver, S., Palik, B.J., and Battaglia, M.A., 2021, Forest density intensifies the importance of snowpack to growth in water-limited pine forests: Ecological Applications, v. 31, no. 1, e02211, 12 p., https://doi.org/10.1002/eap.2211.","productDescription":"e02211, 12 p.","ipdsId":"IP-092237","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":454503,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2211","text":"Publisher Index Page"},{"id":377424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-09-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Gleason, Kelly Erika 0000-0001-5619-7568 kgleason@usgs.gov","orcid":"https://orcid.org/0000-0001-5619-7568","contributorId":238040,"corporation":false,"usgs":true,"family":"Gleason","given":"Kelly","email":"kgleason@usgs.gov","middleInitial":"Erika","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":795903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":795904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"D’Amato, Anthony W.","contributorId":28140,"corporation":false,"usgs":false,"family":"D’Amato","given":"Anthony","email":"","middleInitial":"W.","affiliations":[{"id":13478,"text":"Department of Forest Resources, University of Minnesota, St. Paul, Minnesota (Correspondence to: russellm@umn.edu)","active":true,"usgs":false},{"id":6735,"text":"University of Vermont, Rubenstein School of Environment and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":795905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fraver, Shawn","contributorId":91379,"corporation":false,"usgs":false,"family":"Fraver","given":"Shawn","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":795906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Palik, Brian J.","contributorId":190301,"corporation":false,"usgs":false,"family":"Palik","given":"Brian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":795907,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Battaglia, Michael A.","contributorId":228827,"corporation":false,"usgs":false,"family":"Battaglia","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":795908,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70218475,"text":"70218475 - 2021 - Identifying sources and year classes contributing to invasive grass carp in the Laurentian Great Lakes","interactions":[],"lastModifiedDate":"2021-03-01T15:41:18.367287","indexId":"70218475","displayToPublicDate":"2020-08-02T09:31:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Identifying sources and year classes contributing to invasive grass carp in the Laurentian Great Lakes","docAbstract":"Relative contributions of aquaculture-origin and naturally-reproduced grass carp (Ctenopharyngodon idella) in the Laurentian Great Lakes have been unknown. We assessed occurrence and distribution of aquaculture-origin and wild grass carp in the Great Lakes using ploidy and otolith stable oxygen isotope (δ18O) data. We inferred natal river and dispersal from natal location for wild grass carp using otolith microchemistry and estimated ages of wild and aquaculture-origin fish to infer years in which natural reproduction and introductions occurred. Otolith δ18O indicated that the Great Lakes contain a mixture of wild grass carp and both diploid and triploid, aquaculture-origin grass carp. Eighty-eight percent of wild fish (n = 49 of 56) were caught in the Lake Erie basin. Otolith microchemistry indicated that most wild grass carp likely originated in the Sandusky or Maumee rivers where spawning has previously been confirmed, but results suggested recruitment from at least one other Great Lakes tributary may have occurred. Three fish showed evidence of movement between their inferred natal river in western Lake Erie and capture locations in other lakes in the Great Lakes basin. Age estimates indicated that multiple year classes of wild grass carp are present in the Lake Erie basin, recruitment to adulthood has occurred, and introductions of aquaculture-origin fish have happened over multiple years. Knowledge of sources contributing to grass carp in the Great Lakes basin will be useful for informing efforts to prevent further introductions and spread and to develop strategies to contain and control natural recruitment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2020.07.008","usgsCitation":"Whitledge, G.W., Chapman, D., Farver, J., Herbst, S., Mandrak, N.E., Miner, J., Pangle, K.L., and Kocovsky, P., 2021, Identifying sources and year classes contributing to invasive grass carp in the Laurentian Great Lakes: Journal of Great Lakes Research, v. 47, no. 1, p. 14-28, https://doi.org/10.1016/j.jglr.2020.07.008.","productDescription":"15 p.","startPage":"14","endPage":"28","ipdsId":"IP-114172","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":454505,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2020.07.008","text":"Publisher Index Page"},{"id":436677,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99ZC08Q","text":"USGS data release","linkHelpText":"Development of an age estimation method for Grass Carp from North America"},{"id":383687,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan, New York, Ohio, Ontario","otherGeospatial":"Cuyahoga River, Grand River, Lake Erie, Lake St. Clair, Maumee River, Niagara River, Portage River, River Raisin, Sandusky River, Welland Canal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.5947265625,\n 41.08763212467916\n ],\n [\n -78.3544921875,\n 41.08763212467916\n ],\n [\n -78.3544921875,\n 44.42593442145313\n ],\n [\n -84.5947265625,\n 44.42593442145313\n ],\n [\n -84.5947265625,\n 41.08763212467916\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Whitledge, Gregory W.","contributorId":205604,"corporation":false,"usgs":false,"family":"Whitledge","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":32417,"text":"Southern Illinois University-Carbondale","active":true,"usgs":false}],"preferred":false,"id":811130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":811131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farver, John","contributorId":223527,"corporation":false,"usgs":false,"family":"Farver","given":"John","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":811132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herbst, Seth","contributorId":252926,"corporation":false,"usgs":false,"family":"Herbst","given":"Seth","affiliations":[{"id":50471,"text":"Michigan Department of Natural Resources, Lansing, MI","active":true,"usgs":false}],"preferred":false,"id":811133,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mandrak, Nicholas E.","contributorId":177869,"corporation":false,"usgs":false,"family":"Mandrak","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":811134,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miner, Jeffrey G.","contributorId":252927,"corporation":false,"usgs":false,"family":"Miner","given":"Jeffrey G.","affiliations":[{"id":50472,"text":"Department of Biological Sciences, Bowling Green State University, Bowling Green, OH","active":true,"usgs":false}],"preferred":false,"id":811135,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pangle, Kevin L.","contributorId":205579,"corporation":false,"usgs":false,"family":"Pangle","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":37116,"text":"Department of Biology, Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":811136,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kocovsky, Patrick 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":811137,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70213321,"text":"70213321 - 2021 - Lake trout growth is sensitive to spring temperature in southwest Alaska lakes","interactions":[],"lastModifiedDate":"2020-12-23T18:46:36.427896","indexId":"70213321","displayToPublicDate":"2020-07-30T10:32:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Lake trout growth is sensitive to spring temperature in southwest Alaska lakes","docAbstract":"In high‐latitude lakes, air temperature is an important driver of ice cover thickness and duration, which in turn influence water temperature and primary production supporting lake consumers and predators. In lieu of multidecadal observational records necessary to assess the response of lakes to long‐term warming, we used otolith‐based growth records from a long‐lived resident lake fish, lake trout (Salvelinus namaycush), as a proxy for production. Lake trout were collected from seven deep, oligotrophic lakes in Lake Clark National Park and Preserve on in southwest Alaska that varied in the presence of marine‐derived nutrients (MDN) from anadromous sockeye salmon (Oncorhynchus nerka). Linear mixed‐effects models were used to partition variation in lake trout growth by age and calendar‐year and model comparisons tested for a mean increase in lake trout growth with sockeye salmon presence. Year effects from the best mixed‐effects model were subsequently compared to indices of temperature, lake ice, and regional indices of sockeye salmon escapement. A strong positive correlation between annual lake trout growth and temperature suggested that warmer springs, earlier lake ice break‐up, and a longer ice‐free growing season increase lake trout growth via previously identified bottom‐up increases in production with warming. Accounting for differences in the presence or annual escapement of sockeye salmon with available data did not improve model fit. Collectively with other studies, the results suggest that productivity of subarctic lakes has benefitted from warming spring temperatures and that temperature can synchronise otolith growth across lakes with and without sockeye salmon MDN.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12566","usgsCitation":"von Biela, V.R., Black, B.A., Young, D.B., van der Sleen, P., Bartz, K.K., and Zimmerman, C.E., 2021, Lake trout growth is sensitive to spring temperature in southwest Alaska lakes: Ecology of Freshwater Fish, v. 30, no. 1, p. 88-99, https://doi.org/10.1111/eff.12566.","productDescription":"12 p.","startPage":"88","endPage":"99","ipdsId":"IP-108517","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":436679,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92YV00Z","text":"USGS data release","linkHelpText":"Lake Trout Otolith Growth Increment Measurements, Lake Clark National Park and Preserve, Alaska, 1979-2012"},{"id":378510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Lake Clark National Park and Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.852294921875,\n 59.58441353704829\n ],\n [\n -152.127685546875,\n 59.58441353704829\n ],\n [\n -152.127685546875,\n 61.59071955121135\n ],\n [\n -154.852294921875,\n 61.59071955121135\n ],\n [\n -154.852294921875,\n 59.58441353704829\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"von Biela, Vanessa R. 0000-0002-7139-5981 vvonbiela@usgs.gov","orcid":"https://orcid.org/0000-0002-7139-5981","contributorId":3104,"corporation":false,"usgs":true,"family":"von Biela","given":"Vanessa","email":"vvonbiela@usgs.gov","middleInitial":"R.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":799026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Black, Bryan A.","contributorId":68448,"corporation":false,"usgs":false,"family":"Black","given":"Bryan","email":"","middleInitial":"A.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":799027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Daniel","contributorId":58468,"corporation":false,"usgs":false,"family":"Young","given":"Daniel","affiliations":[{"id":35763,"text":"National Park Service, Lake Clark National Park and Preserve, Port Alsworth, AK","active":true,"usgs":false}],"preferred":false,"id":799028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van der Sleen, Peter","contributorId":203860,"corporation":false,"usgs":false,"family":"van der Sleen","given":"Peter","email":"","affiliations":[{"id":36731,"text":"University of Texas Marine Science Institute","active":true,"usgs":false}],"preferred":false,"id":799029,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bartz, Krista K.","contributorId":200705,"corporation":false,"usgs":false,"family":"Bartz","given":"Krista","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":799030,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":799031,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70211173,"text":"70211173 - 2021 - Trapping of suspended sediment by submerged aquatic vegetation in a tidal freshwater region: Field observations and long-term trends","interactions":[],"lastModifiedDate":"2021-03-19T20:16:25.981098","indexId":"70211173","displayToPublicDate":"2020-07-14T12:23:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Trapping of suspended sediment by submerged aquatic vegetation in a tidal freshwater region: Field observations and long-term trends","docAbstract":"Widespread invasion by non-native, submerged aquatic vegetation (SAV) may modify the sediment budget of an estuary, reducing the availability of inorganic sediment required by marshes to maintain their position in the tidal frame. The instantaneous trapping rate of suspended sediment in SAV patches in an estuary has not previously been quantified via field observations. In this study, flows of water and suspended sediment through patches of invasive SAV were measured at three tidally forced, freshwater sites, all located within the Sacramento-San Joaquin Delta in California. An acoustic Doppler current profiler deployed from a roving vessel provided velocity and backscatter data used to quantify fluxes of both water and suspended sediment. Sediment trapping efficiency, defined as instantaneous net trapped flux divided by incident flux, was positive in 24 of 29 cases, averaging + 5%. Coupled with 3 years of measured sediment flux data at one site, this suggests that trapping averages 3.7 kg m−2 year−1. This estimate compares favorably with the mean mass accumulation rate of 3.8 kg m−2 year−1 estimated from dated sediment cores collected at the study sites. Long-term measurements made upstream reveal a strong negative trend (− 1.8% year−1) in suspended sediment concentration, and intra-annual changes in both suspended sediment concentration and percent fines. The large footprint and high spatial density of invasive SAV coupled with declining sediment supply are diminishing downstream suspended sediment concentrations, potentially reducing the resiliency of marshes in the Delta and lower estuary to future sea-level rise.
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Measurements using modern noble-gas mass spectrometers are now producing 40Ar/39Ar dates with analytical uncertainties of ∼0.1%, thereby providing precise time constraints for a wide range of geologic and extraterrestrial processes. Analyses of increasingly smaller subsamples have revealed age dispersion in many materials, including some minerals used as neutron fluence monitors. Accordingly, interpretive strategies are evolving to address observed dispersion in dates from a single sample. Moreover, inferring a geologically meaningful “age” from a measured “date” or set of dates is dependent on the geological problem being addressed and the salient assumptions associated with each set of data. We highlight requirements for collateral information that will better constrain the interpretation of 40Ar/39Ar data sets, including those associated with single-crystal fusion analyses, incremental heating experiments, and in situ analyses of microsampled domains. To ensure the utility and viability of published results, we emphasize previous recommendations for reporting 40Ar/39Ar data and the related essential metadata, with the amendment that data conform to evolving standards of being findable, accessible, interoperable, and reusable (FAIR) by both humans and computers. Our examples provide guidance for the presentation and interpretation of 40Ar/39Ar dates to maximize their interdisciplinary usage, reproducibility, and longevity.
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This paper describes a methodology to predict larval drift using a Lagrangian particle-tracking (LPT) model with passive and active behavioural components loosely coupled to a quasi-three-dimensional hydraulic model. In the absence of measured larval drift, a heuristic approach is presented for the larval drift of two species of interest, white sturgeon (Acipenser transmontanus) and burbot (Lota lota), in the Kootenai River, Idaho. Previous studies found that many fish species prefer certain vertical zones within the water column; sturgeon tend to be found near the bottom and burbot close to the water surface. Limiting the vertical movement of larvae is incorporated into the active component of the LPT model. The results illustrate a pattern of drift where secondary flow in meander bends and other zones of flow curvature redistributes particles toward the outside of the bend for surface drifters and toward the inside of the bend for bottom drifters. This pattern periodically reinforces the intersection of drifting larvae with channel margins in meander bends. In the absence of measured larval drift data, the model provides a tool for hypothesis testing and a guide to both field and laboratory experiments to further define the role of active behaviour in drifting larvae.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/24705357.2019.1709102","usgsCitation":"McDonald, R.R., and Nelson, J.M., 2021, A Lagrangian particle-tracking approach to modelling larval drift in rivers: Journal of Ecohydraulics, v. 6, no. 1, p. 17-35, https://doi.org/10.1080/24705357.2019.1709102.","productDescription":"19 p.","startPage":"17","endPage":"35","ipdsId":"IP-102070","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":502662,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":436681,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K1U4O0","text":"USGS data release","linkHelpText":"fluvial-particle, U.S. Geological Survey software release"},{"id":415416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.1478357988205,\n 48.69782150172384\n ],\n [\n -116.12731836897655,\n 48.73211652626813\n ],\n [\n -116.32565352413204,\n 48.71948423713994\n ],\n [\n -116.34753878263186,\n 48.78261395455223\n ],\n [\n -116.35574575456924,\n 48.936497382156176\n ],\n [\n -116.41319455813164,\n 48.99935415693781\n ],\n [\n -116.58964445478699,\n 49.00025153683018\n ],\n [\n -116.55544873838093,\n 48.94907507626053\n ],\n [\n -116.45012593185005,\n 48.894249080754236\n ],\n [\n -116.43644764528761,\n 48.82135431506677\n ],\n [\n -116.4255050160379,\n 48.72038664873716\n ],\n [\n -116.33112483875708,\n 48.669826665231625\n ],\n [\n -116.1478357988205,\n 48.69782150172384\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-05-12","publicationStatus":"PW","contributors":{"authors":[{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":868972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":868973,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70217892,"text":"70217892 - 2021 - Quantifying and mapping inundation regimes within a large river‐floodplain ecosystem for ecological and management applications","interactions":[],"lastModifiedDate":"2021-02-11T17:40:25.289588","indexId":"70217892","displayToPublicDate":"2020-04-17T06:32:29","publicationYear":"2021","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":"Quantifying and mapping inundation regimes within a large river‐floodplain ecosystem for ecological and management applications","docAbstract":"Spatial information on the distribution of ecosystem patterns and processes can be a critical component of designing and implementing effective management programs in river‐floodplain ecosystems. For example, translating how flood pulses detected within a stream gauge record are spatially manifested across a river‐valley bottom can be used to evaluate whether the current distribution of physical conditions has the potential to support priority habitats or if intervention is needed to meet desired goals. The size and complexity of large river‐floodplain systems can make mapping inundation dynamics a challenging task. We used a geospatial model to simulate 40 years (1972–2011) of daily surface‐water inundation depths for 11,331 km2 of the Upper Mississippi River System floodplain. We identified discrete inundation events at each 4‐m × 4‐m pixel in the model as sequential days of submergence. We then quantified and mapped four aspects of inundation regime – event frequency, duration, magnitude, and timing – for each pixel. The spatial distribution of inundation regime attributes varied within and among multiple levels of river organization, including navigation pools and geomorphic reaches, but only event timing exhibited a strong down‐river trend. Non‐linear relations among inundation attributes and their geospatial distributions likely reflect complex interactions among topographic, hydrologic, and anthropogenic constraints on flooding dynamics. Together, our results reveal spatial gradients in inundation dynamics not captured by hydrologic data alone. Characterizing such diversity in inundation dynamics is important for testing hypotheses about ecological processes, developing models of ecosystem functions, and informing management actions.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3628","usgsCitation":"Van Appledorn, M., De Jager, N.R., and Rohweder, J.J., 2021, Quantifying and mapping inundation regimes within a large river‐floodplain ecosystem for ecological and management applications: River Research and Applications, v. 37, no. 2, p. 241-255, https://doi.org/10.1002/rra.3628.","productDescription":"15 p.","startPage":"241","endPage":"255","ipdsId":"IP-113745","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":383139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.3955078125,\n 38.51378825951165\n ],\n [\n -88.154296875,\n 40.245991504199026\n ],\n [\n -86.572265625,\n 41.07935114946899\n ],\n [\n -86.7919921875,\n 41.50857729743935\n ],\n [\n -88.0224609375,\n 42.45588764197166\n ],\n [\n -89.3408203125,\n 44.213709909702054\n ],\n [\n -91.7578125,\n 45.85941212790755\n ],\n [\n -92.63671875,\n 46.195042108660154\n ],\n [\n -92.59277343749999,\n 47.724544549099676\n ],\n [\n -94.8779296875,\n 47.249406957888446\n ],\n [\n -95.9326171875,\n 47.30903424774781\n ],\n [\n -95.4052734375,\n 44.84029065139799\n ],\n [\n -93.6474609375,\n 42.13082130188811\n ],\n [\n -93.515625,\n 39.605688178320804\n ],\n [\n -90.3955078125,\n 38.51378825951165\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":810089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":810090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rohweder, Jason J. 0000-0001-5131-9773 jrohweder@usgs.gov","orcid":"https://orcid.org/0000-0001-5131-9773","contributorId":150539,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":810091,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210111,"text":"70210111 - 2021 - Carbon stock losses and recovery observed for a mangrove ecosystem following a major hurricane in Southwest Florida","interactions":[],"lastModifiedDate":"2021-02-17T22:21:56.760044","indexId":"70210111","displayToPublicDate":"2020-04-06T11:01:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Carbon stock losses and recovery observed for a mangrove ecosystem following a major hurricane in Southwest Florida","docAbstract":"Studies integrating mangrove in-situ observations and remote sensing analysis for specific sites often lack precise estimates of carbon stocks over time frames that include disturbance events. This study quantifies change in mangrove area from 1985 to 2018 with Landsat time series analysis, estimates above and belowground stored carbon using field data, and evaluates aboveground carbon stock changes after the 2004 Category 4, Hurricane Charley, in J.N. “Ding” Darling National Wildlife Refuge. Two allometric equation methods yielding similar results were used to estimate aboveground carbon content in three mangrove species found in the refuge. Aboveground carbon contained 67 (SE = 2) MgC ha−1 with a total refuge estimate of 74,504 MgC in 2018. Sediment contained 259 (SE = 28) MgC ha−1 for a total of 288,008 MgC in the refuge. The initial reduction in mangrove area caused by Hurricane Charley was between 0.6% and 5.3%, equivalent to between 427 MgC and 3,599 MgC under three different scenarios of carbon loss. As a result of the hurricane, approximately 61 ha of mangroves were disturbed, of which 24 ha had recovered by 2018, with 37 ha (~3% of the pre-hurricane mangrove area) still not recovered 14 years after the event. The 37 ha of mangroves that have not recovered are located in a tidally restricted area of the refuge. A longer recovery time in this area will likely result in a greater loss of carbon storage than in the rest of the refuge.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2020.106750","usgsCitation":"Peneva-Reed, E.I., Krauss, K., Bullock, E.L., Zhu, Z., Woltz, V., Drexler, J.Z., Conrad, J.R., and Stehman, S.V., 2021, Carbon stock losses and recovery observed for a mangrove ecosystem following a major hurricane in Southwest Florida: Estuarine, Coastal and Shelf Science, v. 248, 106750, 13 p., https://doi.org/10.1016/j.ecss.2020.106750.","productDescription":"106750, 13 p.","ipdsId":"IP-111057","costCenters":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"links":[{"id":374829,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"J.N. “Ding” Darling National Wildlife Refuge, Sanibel Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.16949462890624,\n 26.434609799691536\n ],\n [\n -82.0513916015625,\n 26.434609799691536\n ],\n [\n -82.0513916015625,\n 26.49577131935652\n ],\n [\n -82.16949462890624,\n 26.49577131935652\n ],\n [\n -82.16949462890624,\n 26.434609799691536\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"248","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peneva-Reed, Elitsa I. 0000-0002-4570-4701","orcid":"https://orcid.org/0000-0002-4570-4701","contributorId":202809,"corporation":false,"usgs":true,"family":"Peneva-Reed","given":"Elitsa","email":"","middleInitial":"I.","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":789169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":219804,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":789170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bullock, Eric L. 0000-0003-3279-6771","orcid":"https://orcid.org/0000-0003-3279-6771","contributorId":224710,"corporation":false,"usgs":false,"family":"Bullock","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":40922,"text":"Department of Earth & Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":789171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":789172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woltz, Victoria 0000-0001-7843-6486","orcid":"https://orcid.org/0000-0001-7843-6486","contributorId":223011,"corporation":false,"usgs":true,"family":"Woltz","given":"Victoria","email":"","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":789173,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789174,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conrad, Jeremy R.","contributorId":149347,"corporation":false,"usgs":false,"family":"Conrad","given":"Jeremy","email":"","middleInitial":"R.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":789175,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stehman, Stephen V. 0000-0001-5234-2027","orcid":"https://orcid.org/0000-0001-5234-2027","contributorId":216812,"corporation":false,"usgs":false,"family":"Stehman","given":"Stephen","email":"","middleInitial":"V.","affiliations":[{"id":39524,"text":"College of Environmental Science and Forestry, State University of New York, Syracuse, NY 13210, USA","active":true,"usgs":false}],"preferred":false,"id":789176,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70228760,"text":"70228760 - 2021 - Fish diversity, endemism, threats, and conservation in the Jinsha River basin (upper Yangtze River), China","interactions":[],"lastModifiedDate":"2022-02-18T13:59:33.207865","indexId":"70228760","displayToPublicDate":"2020-03-25T07:50:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Fish diversity, endemism, threats, and conservation in the Jinsha River basin (upper Yangtze River), China","docAbstract":"The Jinsha River, which comprises the upper reaches of the Yangtze River, has among the highest freshwater fish biodiversity and endemism in China, but these characteristics have rarely been quantitatively evaluated at the basin scale. We used fish presence–absence data collected from the entire Jinsha River basin (JRB) from 1964 to 2017 to determine patterns in fish biodiversity. In total, 229 freshwater fish species from 9 orders, 26 families, and 110 genera were recorded. Of these species, 161 were endemic to China, with 94 species being endemic to the Yangtze River basin, and 39 species were threatened. Fish species richness was higher in the downstream river reaches and was higher in the main stem than in the tributaries. Overfishing, water pollution, and dam construction have been threatening fish diversity in the JRB for several decades. Conservation strategies similar to those used in North America may be applicable to the JRB to help protect native fishes in this important river basin. Such strategies include (1) assessment of several tributaries as fish reserves; (2) regular adjustment of turbine operations during the fish spawning period; and (3) regulation of the many co-occurring human stressors in the JRB.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10441","usgsCitation":"Liu, H.W., Guo, C., Qu, X., Xiong, F., Paukert, C.P., Chen, Y., and Sullivan, W., 2021, Fish diversity, endemism, threats, and conservation in the Jinsha River basin (upper Yangtze River), China: North American Journal of Fisheries Management, v. 41, no. 4, p. 967-984, https://doi.org/10.1002/nafm.10441.","productDescription":"18 p.","startPage":"967","endPage":"984","ipdsId":"IP-113887","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":396169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Jinsha River Basin (Upper Yangtze River)","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 90.5,\n 24.6\n ],\n [\n 105.25,\n 24.6\n ],\n [\n 105.25,\n 35.7333\n ],\n [\n 90.5,\n 35.7333\n ],\n [\n 90.5,\n 24.6\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-03-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, H. W.","contributorId":152164,"corporation":false,"usgs":false,"family":"Liu","given":"H.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":835337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guo, C.","contributorId":272911,"corporation":false,"usgs":false,"family":"Guo","given":"C.","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":835338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Qu, X.","contributorId":279670,"corporation":false,"usgs":false,"family":"Qu","given":"X.","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":835339,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xiong, F.","contributorId":279671,"corporation":false,"usgs":false,"family":"Xiong","given":"F.","affiliations":[{"id":57334,"text":"http://orcid.org/0000-0002-9369-8545","active":true,"usgs":false}],"preferred":false,"id":835340,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":835341,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chen, Y.","contributorId":272912,"corporation":false,"usgs":false,"family":"Chen","given":"Y.","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":835342,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sullivan, W.","contributorId":156266,"corporation":false,"usgs":false,"family":"Sullivan","given":"W.","affiliations":[],"preferred":false,"id":835343,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224613,"text":"70224613 - 2021 - Units recovery methods in compositional data analysis","interactions":[],"lastModifiedDate":"2021-09-30T11:55:22.832759","indexId":"70224613","displayToPublicDate":"2020-03-24T06:52:56","publicationYear":"2021","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":"Units recovery methods in compositional data analysis","docAbstract":"Compositional data carry relative information. Hence, their statistical analysis has to be performed on coordinates with respect to a log-ratio basis. Frequently, the modeler is required to back-transform the estimates obtained with the modeling to have them in the original units such as euros, kg or mg/liter. Approaches for recovering original units need to be formally introduced and its properties explored. Here, we formulate and analyze the properties of two procedures: a simple approach consisting of adding a residual part to the composition and an approach based on the use of an auxiliary variable. Both procedures are illustrated using a geochemical data set where the original units are recovered when spatial models are applied.
Ecologists have a limited understanding of the rangewide variation in movement behavior in freshwater fishes, but recent expansion of biotelemetry allows biologists to investigate how fish movement can help to predict behavioral shifts in response to changing environments. The Lake Sturgeon Acipenser fulvescens is a wide-ranging, migratory, coolwater species, making it a candidate species for studying patterns in movement ecology. We conducted a literature review and meta-analysis of seasonal movement data compiled from 38 Lake Sturgeon telemetry studies in North America to build an understanding of spatiotemporal variation in movement behavior. Lake Sturgeon movement studies were underrepresented for low-latitude populations in the Mississippi, Missouri, and Ohio/Tennessee River basins. Highest movement usually occurred during spring spawning migrations, whereas other populations exhibited their highest movement in the fall, potentially in order to overwinter near spawning grounds. Our meta-regression analysis indicated that latitude or summer maximum temperature best predicted standardized mean difference between spring and summer movement in Lake Sturgeon populations across the species’ range. Our results suggest that Lake Sturgeon populations at lower latitudes and those that experience warmer summer temperatures have lower summer movement relative to spring movement. Managers may use this information to prioritize actions promoting the conservation of seasonally important habitats for the continued recovery of migratory coolwater fish (e.g., Lake Sturgeon) that potentially experience stressful thermal conditions.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10416","usgsCitation":"Moore, M.J., Paukert, C.P., and Moore, T., 2021, Effects of latitude, season, and temperature on Lake Sturgeon movement: North American Journal of Fisheries Management, v. 41, no. 4, p. 916-928, https://doi.org/10.1002/nafm.10416.","productDescription":"13 p.","startPage":"916","endPage":"928","ipdsId":"IP-109393","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Michael J.","contributorId":274823,"corporation":false,"usgs":false,"family":"Moore","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":833347,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833348,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, T.","contributorId":257287,"corporation":false,"usgs":false,"family":"Moore","given":"T.","affiliations":[],"preferred":false,"id":833349,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219477,"text":"70219477 - 2021 - Limitations, lack of standardization, and recommended best practices in studies of renewable energy effects on birds and bats","interactions":[],"lastModifiedDate":"2021-04-12T12:01:31.478203","indexId":"70219477","displayToPublicDate":"2020-01-08T07:25:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Limitations, lack of standardization, and recommended best practices in studies of renewable energy effects on birds and bats","docAbstract":"Increasing global energy demand is fostering the development of renewable energy as an alternative to fossil fuels. However, renewable energy facilities may adversely affect wildlife. Facility siting guidelines recommend or require project developers complete pre‐ and postconstruction wildlife surveys to predict risk and estimate effects of proposed projects. Despite this, there are no published studies that have quantified the types of surveys used or how survey types are standardized within and across facilities. We evaluated 628 peer‐reviewed publications, unpublished reports, and citations, and we analyzed data from 525 of these sources (203 facilities: 193 wind and 10 solar) in the United States and Canada to determine the frequency of pre‐ and postconstruction surveys and whether that frequency changed over time; frequency of studies explicitly designed to allow before‐after or impact‐control analyses; and what types of survey data were collected during pre‐ and postconstruction periods and how those data types were standardized across periods and among facilities. Within our data set, postconstruction monitoring for wildlife fatalities and habitat use was a standard practice (n = 446 reports), but preconstruction estimation of baseline wildlife habitat use and mortality was less frequently reported (n = 84). Only 22% (n = 45) of the 203 facilities provided data from both pre‐ and postconstruction, and 29% (n = 59) had experimental study designs. Of 108 facilities at which habitat‐use surveys were conducted, only 3% estimated of detection probability. Thus, the available data generally preclude comparison of biological data across construction periods and among facilities. Use of experimental study designs and following similar field protocols would improve the knowledge of how renewable energy affects wildlife.
","language":"English","publisher":"Wiley","doi":"10.1111/cobi.13457","usgsCitation":"Conkling, T., Loss, S.R., Diffendorfer, J., Duerr, A., and Katzner, T., 2021, Limitations, lack of standardization, and recommended best practices in studies of renewable energy effects on birds and bats: Conservation Biology, v. 35, no. 1, p. 64-76, https://doi.org/10.1111/cobi.13457.","productDescription":"13 p.","startPage":"64","endPage":"76","ipdsId":"IP-099190","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":384968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Conkling, Tara 0000-0003-1926-8106","orcid":"https://orcid.org/0000-0003-1926-8106","contributorId":217915,"corporation":false,"usgs":true,"family":"Conkling","given":"Tara","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loss, S. R. 0000-0002-8753-2995","orcid":"https://orcid.org/0000-0002-8753-2995","contributorId":257044,"corporation":false,"usgs":false,"family":"Loss","given":"S.","email":"","middleInitial":"R.","affiliations":[{"id":51965,"text":"Department of Natural Resource Ecology & Management, Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":813723,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":813724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duerr, A. 0000-0002-6145-8897","orcid":"https://orcid.org/0000-0002-6145-8897","contributorId":257045,"corporation":false,"usgs":false,"family":"Duerr","given":"A.","email":"","affiliations":[{"id":38830,"text":"Bloom Research Inc.","active":true,"usgs":false}],"preferred":false,"id":813725,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813726,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216098,"text":"70216098 - 2021 - Making Recursive Bayesian inference accessible","interactions":[],"lastModifiedDate":"2021-05-19T12:08:37.54648","indexId":"70216098","displayToPublicDate":"2019-11-04T13:50:20","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":747,"text":"American Statistician","active":true,"publicationSubtype":{"id":10}},"title":"Making Recursive Bayesian inference accessible","docAbstract":"Bayesian models provide recursive inference naturally because they can formally reconcile new data and existing scientific information. However, popular\nuse of Bayesian methods often avoids priors that are based on exact posterior distributions resulting from former studies. Two existing Recursive Bayesian methods\nare: Prior- and Proposal-Recursive Bayes. Prior-Recursive Bayes uses Bayesian\nupdating, fitting models to partitions of data sequentially, and provides a way\nto accommodate new data as they become available using the posterior from the\nprevious stage as the prior in the new stage based on the latest data. ProposalRecursive Bayes is intended for use with hierarchical Bayesian models and uses a\nset of transient priors in first stage independent analyses of the data partitions.\nThe second stage of Proposal-Recursive Bayes uses the posteriors from the first\nstage as proposals in an MCMC algorithm to fit the full model. We combine\nPrior- and Proposal-Recursive concepts to fit any Bayesian model, and often with\ncomputational improvements. We demonstrate our method with two case studies.\nOur approach has implications for big data, streaming data, and optimal adaptive\ndesign situations.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00031305.2019.1665584","usgsCitation":"Hooten, M., Johnson, D., and Brost, B., 2021, Making Recursive Bayesian inference accessible: American Statistician, v. 75, no. 2, p. 185-194, https://doi.org/10.1080/00031305.2019.1665584.","productDescription":"10 p.","startPage":"185","endPage":"194","ipdsId":"IP-101580","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":454561,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/1807.10981","text":"External Repository"},{"id":380171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-10-16","publicationStatus":"PW","contributors":{"authors":[{"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":804074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Devin S.","contributorId":244505,"corporation":false,"usgs":false,"family":"Johnson","given":"Devin S.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":804076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brost, Brian M.","contributorId":244504,"corporation":false,"usgs":false,"family":"Brost","given":"Brian M.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":804075,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223236,"text":"70223236 - 2021 - Selenium, mercury, and their molar ratios in sportfishes from drinking water reservoirs","interactions":[],"lastModifiedDate":"2021-08-19T17:03:30.060514","indexId":"70223236","displayToPublicDate":"2019-08-29T12:01:10","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2041,"text":"International Journal of Environmental Research and Public Health","active":true,"publicationSubtype":{"id":10}},"title":"Selenium, mercury, and their molar ratios in sportfishes from drinking water reservoirs","docAbstract":"Mercury (Hg) bioaccumulates in aquatic ecosystems and may pose a risk to humans who consume fish. Selenium (Se) has the ability to reduce Hg toxicity, but the current guidance for human consumption of fish is based on Hg concentration alone. The purpose of the present study was to examine the relationship between Se and Hg in freshwater sportfish, for which there is a paucity of existing data. We collected three species of fish from different trophic positions from two drinking water reservoirs in central North Carolina, USA, to assess Hg and Se concentrations in relation to fish total length and to compare two measures of the protective ability of Se, the Se:Hg molar ratio and Se health benefit value (HBVSe), to current guidance for Hg. According to the Se:Hg molar ratio, all of the low trophic position fish sampled and the middle trophic position fish sampled from one of the reservoirs were safe for consumption. The same number of fish were considered safe using the HBVSe. More fish were deemed unsafe when using the Se:Hg molar ratio and HBVSe than were considered unsafe when using the U.S. Environmental Protection Agency (USEPA) Hg threshold. These findings suggest that the measures of Se protection may be unnecessarily conservative or that the USEPA Hg threshold may not be sufficiently protective of human health, especially the health of sensitive populations like pregnant or nursing mothers and young children. Future examination of the Se:Hg molar ratio and HBVSe from a variety of fish tissue samples would help refine the accuracy of these measures so that they may be appropriately utilized in ecological and human health risk assessment.
","language":"English","publisher":"MDPI","doi":"10.3390/ijerph15091864","usgsCitation":"Johnson, T.K., LePrevost, C.E., Kwak, T.J., and Cope, W.G., 2021, Selenium, mercury, and their molar ratios in sportfishes from drinking water reservoirs: International Journal of Environmental Research and Public Health, v. 15, no. 9, 1864, 17 p., https://doi.org/10.3390/ijerph15091864.","productDescription":"1864, 17 p.","ipdsId":"IP-100876","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":454568,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ijerph15091864","text":"Publisher Index Page"},{"id":388174,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"9","noUsgsAuthors":false,"publicationDate":"2018-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Tara K. B.","contributorId":264411,"corporation":false,"usgs":false,"family":"Johnson","given":"Tara","email":"","middleInitial":"K. B.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":821488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LePrevost, C. E.","contributorId":264412,"corporation":false,"usgs":false,"family":"LePrevost","given":"C.","email":"","middleInitial":"E.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":821489,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":821490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cope, W. G.","contributorId":264384,"corporation":false,"usgs":false,"family":"Cope","given":"W.","email":"","middleInitial":"G.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":821491,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202002,"text":"70202002 - 2021 - Perspectives on the paleolimnology of the late Eocene Florissant lake from diatom and sedimentary evidence at Clare’s Quarry, Teller County, Colorado, USA","interactions":[{"subject":{"id":70202002,"text":"70202002 - 2021 - Perspectives on the paleolimnology of the late Eocene Florissant lake from diatom and sedimentary evidence at Clare’s Quarry, Teller County, Colorado, USA","indexId":"70202002","publicationYear":"2021","noYear":false,"chapter":"10","title":"Perspectives on the paleolimnology of the late Eocene Florissant lake from diatom and sedimentary evidence at Clare’s Quarry, Teller County, Colorado, USA"},"predicate":"IS_PART_OF","object":{"id":70225733,"text":"70225733 - 2021 - From saline to freshwater: The diversity of western lakes in space and time","indexId":"70225733","publicationYear":"2021","noYear":false,"title":"From saline to freshwater: The diversity of western lakes in space and time"},"id":1}],"isPartOf":{"id":70225733,"text":"70225733 - 2021 - From saline to freshwater: The diversity of western lakes in space and time","indexId":"70225733","publicationYear":"2021","noYear":false,"title":"From saline to freshwater: The diversity of western lakes in space and time"},"lastModifiedDate":"2021-11-08T18:11:04.142208","indexId":"70202002","displayToPublicDate":"2019-01-01T10:58:16","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"10","title":"Perspectives on the paleolimnology of the late Eocene Florissant lake from diatom and sedimentary evidence at Clare’s Quarry, Teller County, Colorado, USA","docAbstract":"The late Eocene Florissant Formation in central Colorado is a rich and diverse continental Lagerstätte yielding well-preserved fossil assemblages from lacustrine and fluvial facies. This investigation focused on the lacustrine facies at Clare’s Quarry and used biotic and abiotic evidence to characterize aspects of the lake and processes that resulted in the accumulation and preservation of the host rock and its fossils. Autecology of modern analogs representing the fossil diatom taxa was used to augment sedimentary data in characterizing the lake, propose peripheral habitats within the catchment area, and suggest a terrestrial source for mudstone units.
The sedimentary and stratigraphic record at the study site reveals a lake with sufficient depth to allow bottom waters to remain isolated and anoxic for long periods. Sediments that accumulated in the lake produced distinct lacustrine lithofacies that are interpreted as representing at least three modes of origin: stable lake, pyroclastic, and mud turbidite sedimentation. Slow, suspension settling of fine clays and volcanic ash into a moderately deep, stable lake resulted in laminated shales. These laminated shales contain frustules of diatoms from planktic and benthic lake habitats; diatoms transported into the lake from streams and wetlands; fish, mollusks, ostracods, and insects; and plants from marginal and upslope environments. Intermittent volcanic eruptions produced air-fall ash and granular tuff that accumulated as interbeds within the lake shales. Periods of stable lake sedimentation were frequently interrupted by rapid influxes of suspended fine clays, perhaps as mud-dominated turbidites that prograded into the lake at intervals of high runoff triggered by climatic, volcanic, or tectonic events.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"From saline to freshwater: The diversity of western lakes in space and time","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2018.2536(10)","usgsCitation":"Benson, M., Smith, D.M., and Spaulding, S.A., 2021, Perspectives on the paleolimnology of the late Eocene Florissant lake from diatom and sedimentary evidence at Clare’s Quarry, Teller County, Colorado, USA, chap. 10 of From saline to freshwater: The diversity of western lakes in space and time, v. 536, 26 p., https://doi.org/10.1130/2018.2536(10).","productDescription":"26 p.","ipdsId":"IP-077030","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":361012,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","county":"Teller County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-105.3232,39.1307],[-105.274,39.1309],[-105.1607,39.1306],[-105.0503,39.1312],[-105.032,39.1311],[-105.026,39.0413],[-105.0296,38.8668],[-105.0502,38.8665],[-105.0674,38.8666],[-105.0671,38.7946],[-104.939,38.7949],[-104.9386,38.7808],[-104.9399,38.6938],[-104.9428,38.6938],[-104.9427,38.6648],[-104.9427,38.6621],[-104.9429,38.6503],[-104.9429,38.6467],[-104.9806,38.6479],[-104.9989,38.649],[-105.0507,38.6507],[-105.0696,38.6473],[-105.0755,38.646],[-105.0885,38.646],[-105.1657,38.6461],[-105.1845,38.6458],[-105.2222,38.6461],[-105.2387,38.6462],[-105.239,38.677],[-105.2394,38.6965],[-105.2741,38.6971],[-105.2765,38.6972],[-105.3119,38.6969],[-105.3319,38.697],[-105.3294,38.779],[-105.3292,38.867],[-105.3296,38.9535],[-105.3297,39.0116],[-105.3297,39.1308],[-105.3232,39.1307]]]},\"properties\":{\"name\":\"Teller\",\"state\":\"CO\"}}]}","volume":"536","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Benson, Mary Ellen 0000-0002-4424-0730","orcid":"https://orcid.org/0000-0002-4424-0730","contributorId":212794,"corporation":false,"usgs":true,"family":"Benson","given":"Mary Ellen","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":756608,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Dena M. 0000-0002-1689-7188","orcid":"https://orcid.org/0000-0002-1689-7188","contributorId":212795,"corporation":false,"usgs":false,"family":"Smith","given":"Dena","email":"","middleInitial":"M.","affiliations":[{"id":12642,"text":"National Science Foundation","active":true,"usgs":false}],"preferred":false,"id":756609,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spaulding, Sarah A. 0000-0002-9787-7743","orcid":"https://orcid.org/0000-0002-9787-7743","contributorId":212796,"corporation":false,"usgs":true,"family":"Spaulding","given":"Sarah","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":756610,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217687,"text":"70217687 - 2021 - Model structural uncertainty quantification and hydrogeophysical data integration using airborne electromagnetic data","interactions":[],"lastModifiedDate":"2021-02-08T18:00:13.597366","indexId":"70217687","displayToPublicDate":"2018-12-31T11:58:10","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Model structural uncertainty quantification and hydrogeophysical data integration using airborne electromagnetic data","docAbstract":"Airborne electromagnetic (AEM) dataare usedto estimate large-scale model structural geometry, i.e. the spatial distribution of different lithological units based on assumed or estimated resistivity-lithology relationships, and the uncertainty in those structures given imperfect measurements. Geophysically derived estimates of model structural uncertainty are then combined with hydrologic observations to assess the impact of model structural error on hydrologic calibration and prediction errors. Using a synthetic numerical model, we describe a sequential hydrogeophysical approach that: (1) uses Bayesian Markov chain Monte Carlo (McMC) methods to produce a robust estimate of uncertainty in electrical resistivity parameters, (2) combines geophysical parameter uncertainty estimates with borehole observations of lithology to produce probabilistic estimates of model structural uncertainty over the entire AEM survey area using geostatistical sequential indicator simulation algorithms, and (3) uses model structural estimates along with hydrologic observations to quantify both hydrologic parameter and prediction uncertainty using a second McMC sampling algorithm. Results of simulations will be presented that illustrate the complete workflow from geophysical parameter uncertainty analysis to the impact of model structural uncertainty on hydrologic parameter estimates.
","conferenceTitle":"7th International Workshop on Airborne Electromagnetics","conferenceDate":"June 17-20, 2018","conferenceLocation":"Kolding, Denmark","language":"English","publisher":"Aarhus University","usgsCitation":"Minsley, B.J., Christensen, N.K., Christensen, S., and Ley-Cooper, Y., 2021, Model structural uncertainty quantification and hydrogeophysical data integration using airborne electromagnetic data, 7th International Workshop on Airborne Electromagnetics, Kolding, Denmark, June 17-20, 2018, 4 p.","productDescription":"4 p.","ipdsId":"IP-095925","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":383107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383106,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.conferencemanager.dk/aem2018"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":809258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christensen, Nikolaj K","contributorId":199736,"corporation":false,"usgs":false,"family":"Christensen","given":"Nikolaj","email":"","middleInitial":"K","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":809259,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christensen, Steen","contributorId":199737,"corporation":false,"usgs":false,"family":"Christensen","given":"Steen","email":"","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":809260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ley-Cooper, Yusen","contributorId":248494,"corporation":false,"usgs":false,"family":"Ley-Cooper","given":"Yusen","email":"","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":809261,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221393,"text":"70221393 - 2021 - Streamflow, sediment transport, and geomorphic change during the 2011 flood on the Missouri River near Bismarck-Mandan, ND","interactions":[],"lastModifiedDate":"2021-06-15T10:36:19.944894","indexId":"70221393","displayToPublicDate":"2018-08-27T07:47:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2126,"text":"JAWRA","active":true,"publicationSubtype":{"id":10}},"title":"Streamflow, sediment transport, and geomorphic change during the 2011 flood on the Missouri River near Bismarck-Mandan, ND","docAbstract":"Geomorphic change from extreme events in large managed rivers has implications for river management. A steady-state, quasi-three-dimensional hydrodynamic model was applied to a 29-km reach of the Missouri River using 2011 flood data. Model results for an extreme flow (500-year recurrence interval [RI]) and an elevated managed flow (75-year RI) were used to assess sediment mobility through examination of the spatial distribution of boundary or bed shear stress (τb) and longitudinal patterns of average τb, velocity, and kurtosis of τb. Kurtosis of τb was used as an indicator of planform channel complexity and can be applied to other river systems. From differences in longitudinal patterns of sediment mobility for the two flows we can infer: (1) under extreme flow, the channel behaves as a single-thread channel controlled primarily by flow, which enhances the meander pattern; (2) under elevated managed flows, the channel behaves as multithread channel controlled by the interaction of flow with bed and channel topography, resulting in a more complex channel; and (3) for both flows, the model reach lacks a consistent pattern of deposition or erosion, which indicates migration of areas of erosion and deposition within the reach. Despite caveats and limitations, the analysis provides useful information about geomorphic change under extreme flow and potential implications for river management. Although a 500-year RI is rare, extreme hydrologic events such as this are predicted to increase in frequency.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12678","usgsCitation":"Nustad, R.A., Benthem, A.J., Skalak, K., McDonald, R.R., Schenk, E., and Galloway, J.M., 2021, Streamflow, sediment transport, and geomorphic change during the 2011 flood on the Missouri River near Bismarck-Mandan, ND: JAWRA, v. 54, no. 5, p. 1151-1167, https://doi.org/10.1111/1752-1688.12678.","productDescription":"17 p.","startPage":"1151","endPage":"1167","ipdsId":"IP-075678","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":454576,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12678","text":"Publisher Index Page"},{"id":386466,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","city":"Bismarck","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.0137939453125,\n 45.94351068030587\n ],\n [\n -100.3436279296875,\n 45.94351068030587\n ],\n [\n -100.3436279296875,\n 46.98774725646568\n ],\n [\n -101.0137939453125,\n 46.98774725646568\n ],\n [\n -101.0137939453125,\n 45.94351068030587\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"5","noUsgsAuthors":false,"publicationDate":"2018-08-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Nustad, Rochelle A. 0000-0002-4713-5944 ranustad@usgs.gov","orcid":"https://orcid.org/0000-0002-4713-5944","contributorId":1811,"corporation":false,"usgs":true,"family":"Nustad","given":"Rochelle","email":"ranustad@usgs.gov","middleInitial":"A.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benthem, Adam J. 0000-0003-2372-0281","orcid":"https://orcid.org/0000-0003-2372-0281","contributorId":220000,"corporation":false,"usgs":true,"family":"Benthem","given":"Adam","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","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":817500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":817501,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schenk, Edward R.","contributorId":202017,"corporation":false,"usgs":false,"family":"Schenk","given":"Edward R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":817554,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Galloway, Joel M. 0000-0002-9836-9724 jgallowa@usgs.gov","orcid":"https://orcid.org/0000-0002-9836-9724","contributorId":1562,"corporation":false,"usgs":true,"family":"Galloway","given":"Joel","email":"jgallowa@usgs.gov","middleInitial":"M.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817555,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70254945,"text":"70254945 - 2020 - Statistical implementations of agent-based demographic models","interactions":[],"lastModifiedDate":"2024-06-11T19:15:50.661658","indexId":"70254945","displayToPublicDate":"2024-08-03T13:41:03","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17811,"text":"International Statistical Review","onlineIssn":"1751-5823","printIssn":"0306-7734","active":true,"publicationSubtype":{"id":10}},"title":"Statistical implementations of agent-based demographic models","docAbstract":"A variety of demographic statistical models exist for studying population dynamics when individuals can be tracked over time. In cases where data are missing\ndue to imperfect detection of individuals, the associated measurement error can\nbe accommodated under certain study designs (e.g., those that involve multiple\nsurveys or replication). However, the interaction of the measurement error and\nthe underlying dynamic process can complicate the implementation of statistical\nagent-based models (ABMs) for population demography. In a Bayesian setting,\ntraditional computational algorithms for fitting hierarchical demographic models can be prohibitively cumbersome to construct. Thus, we discuss a variety of\napproaches for fitting statistical ABMs to data and demonstrate how to use multistage recursive Bayesian computing and statistical emulators to fit models in such\na way that alleviates the need to have analytical knowledge of the ABM likelihood.\nUsing two examples, a demographic model for survival and a compartment model\nfor COVID-19, we illustrate statistical procedures for implementing ABMs. The\napproaches we describe are intuitive and accessible for practitioners and can be\nparallelized easily for additional computational eciency.","language":"English","publisher":"Wiley","doi":"10.1111/insr.12399","usgsCitation":"Hooten, M., Wikle, C., and Schwob, M., 2020, Statistical implementations of agent-based demographic models: International Statistical Review, v. 88, no. 2, p. 441-461, https://doi.org/10.1111/insr.12399.","productDescription":"21 p,","startPage":"441","endPage":"461","ipdsId":"IP-120052","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":454581,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/insr.12399","text":"Publisher Index Page"},{"id":429907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-08-03","publicationStatus":"PW","contributors":{"authors":[{"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":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":902944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wikle, Christopher K.","contributorId":338088,"corporation":false,"usgs":false,"family":"Wikle","given":"Christopher K.","affiliations":[{"id":81080,"text":"umo","active":true,"usgs":false}],"preferred":false,"id":902945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwob, Michael R.","contributorId":338089,"corporation":false,"usgs":false,"family":"Schwob","given":"Michael R.","affiliations":[{"id":81083,"text":"un","active":true,"usgs":false}],"preferred":false,"id":902946,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228586,"text":"70228586 - 2020 - A new approach to the study of relationship quality in dolphins: framework and preliminary results","interactions":[],"lastModifiedDate":"2022-02-14T15:18:48.742945","indexId":"70228586","displayToPublicDate":"2022-12-30T09:03:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":987,"text":"Behavioural Processes","active":true,"publicationSubtype":{"id":10}},"title":"A new approach to the study of relationship quality in dolphins: framework and preliminary results","docAbstract":"Proximity and synchronous behaviours from surface observations have been used to measure association patterns within and between dolphin dyads. To facilitate an investigation of relationship quality in dolphins, we applied a method used for chimpanzees and ravens that examined three main components to describe relationships: value, security, and compatibility. Using pilot data from a long-term study of two study populations for this preliminary assessment, these three components were extracted from PCA analysis of eight behavioural variables with more than 80% variance accounted for in both study groups. Only pair swim position differed between groups. Although value, security, and compatibility are abstract terms, each is based on behaviours identified as important in dolphin social life, at least for these two populations. Examining relationship quality in dolphins with a method used to illustrate dyadic differences for chimpanzees and ravens allows for a quantitative, comparative assessment of sociality across disparate taxa. Although these three species are diverse in their anatomies and in their social habitats (e.g., aquatic, terrestrial, aerial), they may well share the basic societal building blocks in the factors affecting how relationships are formed. We discuss how an examination of these behavioural variables facilitates understanding relationship quality in dolphins, as well as how dolphin relationships fit into the context of social animals’ society.","language":"English","publisher":"Elsevier","doi":"10.1016/j.beproc.2020.104260","usgsCitation":"Themelin, M., Ribic, C., Melillo-Sweeting, K., Bolton, T., and Dudzinski, K., 2020, A new approach to the study of relationship quality in dolphins: framework and preliminary results: Behavioural Processes, v. 181, 104260, 10 p., https://doi.org/10.1016/j.beproc.2020.104260.","productDescription":"104260, 10 p.","ipdsId":"IP-118323","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Bahamas, Honduras","otherGeospatial":"Bimini Islands, Great Bahama Bank, Roatan Island","volume":"181","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Themelin, Manon","contributorId":276248,"corporation":false,"usgs":false,"family":"Themelin","given":"Manon","email":"","affiliations":[{"id":56353,"text":"Dolphin Communication Project","active":true,"usgs":false}],"preferred":false,"id":834687,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Melillo-Sweeting, Kel","contributorId":276249,"corporation":false,"usgs":false,"family":"Melillo-Sweeting","given":"Kel","affiliations":[{"id":56353,"text":"Dolphin Communication Project","active":true,"usgs":false}],"preferred":false,"id":834688,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bolton, Teri","contributorId":276251,"corporation":false,"usgs":false,"family":"Bolton","given":"Teri","email":"","affiliations":[{"id":56942,"text":"The Roatan Institute for Marine Sciences","active":true,"usgs":false}],"preferred":false,"id":834689,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dudzinski, Kathleen M.","contributorId":276253,"corporation":false,"usgs":false,"family":"Dudzinski","given":"Kathleen M.","affiliations":[{"id":56353,"text":"Dolphin Communication Project","active":true,"usgs":false}],"preferred":false,"id":834690,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}