{"pageNumber":"195","pageRowStart":"4850","pageSize":"25","recordCount":40782,"records":[{"id":70226210,"text":"70226210 - 2022 - Risk-based wellhead protection decision support: A repeatable workflow approach","interactions":[],"lastModifiedDate":"2022-01-25T17:15:23.798251","indexId":"70226210","displayToPublicDate":"2021-08-31T07:41:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Risk-based wellhead protection decision support: A repeatable workflow approach","docAbstract":"

Environmental water management often benefits from a risk-based approach where information on the area of interest is characterized, assembled, and incorporated into a decision model considering uncertainty. This includes prior information from literature, field measurements, professional interpretation, and data assimilation resulting in a decision tool with a posterior uncertainty assessment accounting for prior understanding and what is learned through model development and data assimilation. Model construction and data assimilation are time consuming and prone to errors, which motivates a repeatable workflow where revisions resulting from new interpretations or discovery of errors can be addressed and the analyses repeated efficiently and rigorously. In this work, motivated by the real world application of delineating risk-based (probabilistic) sources of water to supply wells in a humid temperate climate, a scripted workflow was generated for groundwater model construction, data assimilation, particle-tracking and post-processing. The workflow leverages existing datasets describing hydrogeology, hydrography, water use, recharge, and lateral boundaries. These specific data are available in the United States but the tools can be applied to similar datasets worldwide. The workflow builds the model, performs ensemble-based history matching, and uses a posterior Monte Carlo approach to provide probabilistic capture zones describing source water to wells in a risk-based framework. The water managers can then select areas of varying levels of protection based on their tolerance for risk of potential wrongness of the underlying models. All the tools in this workflow are open-source and free, which facilitates testing of this repeatable and transparent approach to other environmental problems.

","language":"English","publisher":"National Ground Water Association","doi":"10.1111/gwat.13129","usgsCitation":"Fienen, M., Corson-Dosch, N., White, J., Leaf, A.T., and Hunt, R., 2022, Risk-based wellhead protection decision support: A repeatable workflow approach: Groundwater, v. 60, no. 1, p. 71-86, https://doi.org/10.1111/gwat.13129.","productDescription":"16 p.","startPage":"71","endPage":"86","ipdsId":"IP-127914","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":436057,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HWSOHP","text":"USGS data release","linkHelpText":"Groundwater Model Archive and Workflow for Neversink/Rondout Basin, New York, Source Water Delineation"},{"id":391793,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-09-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corson-Dosch, Nicholas 0000-0002-6776-6241","orcid":"https://orcid.org/0000-0002-6776-6241","contributorId":202630,"corporation":false,"usgs":true,"family":"Corson-Dosch","given":"Nicholas","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, Jeremy T. 0000-0002-4950-1469","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":248830,"corporation":false,"usgs":false,"family":"White","given":"Jeremy T.","affiliations":[{"id":50032,"text":"GNS New Zealand","active":true,"usgs":false}],"preferred":false,"id":826893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826894,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826895,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70230329,"text":"70230329 - 2022 - A big problem for small earthquakes: Benchmarking routine magnitudes and conversion relationships with coda-envelope-derived Mw in southern Kansas and northern Oklahoma","interactions":[],"lastModifiedDate":"2022-04-07T11:58:37.794763","indexId":"70230329","displayToPublicDate":"2021-08-31T06:51:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10539,"text":"Bulletin of the Seismological Society of America (BSSA)","active":true,"publicationSubtype":{"id":10}},"title":"A big problem for small earthquakes: Benchmarking routine magnitudes and conversion relationships with coda-envelope-derived Mw in southern Kansas and northern Oklahoma","docAbstract":"

Earthquake magnitudes are widely relied upon measures of earthquake size. Although moment magnitude (⁠Mw\">MwMw⁠) has become the established standard for moderate and large earthquakes, difficulty in reliably measuring seismic moments for small (generally Mw&lt;4\">Mw<4Mw<4⁠) earthquakes has meant that magnitudes for these events remain plagued by a patchwork of inconsistent measurement scales. Because of this, magnitudes of small earthquakes and statistics derived from them can be biased. Furthermore, because small earthquakes are much more numerous than large ones, many applications, such as seismic hazard modeling, depend critically on analysis of events characterized by magnitudes other than Mw\">MwMw⁠. To assess this problem, we apply coda envelope analysis to reliably determine moment magnitudes for a case study of small earthquakes from northern Oklahoma and southern Kansas. Not surprisingly, we find significant differences among ML\">MLML⁠, mbLg\">mbLgmbLg⁠, and Mw\">MwMw for M ∼2–4 earthquakes examined here. More troublingly, we find that relations designed to convert other magnitudes to Mw\">MwMw⁠, which are relied upon for important applications such as seismic hazard analysis, often increase rather than decrease this bias for our dataset. In our case study, we find that converted magnitudes can result in a systematic bias sometimes exceeding 0.5 magnitude units, a difference that typically corresponds to a factor of ∼3 in seismicity rate. Moreover, we find a correspondingly large bias in Gutenberg–Richter b‐values, controlled primarily by inaccurate magnitude scaling in the conversion relationships. Although this study focuses on a relatively small geographic area, we can expect that similar issues exist with varying severity in other regions. Therefore, magnitudes of small earthquakes and their associated statistics, including seismicity rates and b‐values, should be treated with caution.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120210115","usgsCitation":"Shelly, D.R., Mayeda, K., Barno, J., Whidden, K.M., Moschetti, M.P., Llenos, A.L., Rubinstein, J., Yeck, W.L., Earle, P.S., Gok, R., and Walter, W.R., 2022, A big problem for small earthquakes: Benchmarking routine magnitudes and conversion relationships with coda-envelope-derived Mw in southern Kansas and northern Oklahoma: Bulletin of the Seismological Society of America (BSSA), v. 112, no. 1, p. 210-225, https://doi.org/10.1785/0120210115.","productDescription":"16 p.","startPage":"210","endPage":"225","ipdsId":"IP-130008","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":449735,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1868860","text":"External Repository"},{"id":398302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.8876953125,\n 35.31736632923788\n ],\n [\n -94.7021484375,\n 35.31736632923788\n ],\n [\n -94.7021484375,\n 38.34165619279595\n ],\n [\n -99.8876953125,\n 38.34165619279595\n ],\n [\n -99.8876953125,\n 35.31736632923788\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"112","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-08-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Shelly, David R. dshelly@usgs.gov","contributorId":2978,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":114,"text":"Alaska Science 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M.","contributorId":289898,"corporation":false,"usgs":false,"family":"Whidden","given":"Katherine","email":"","middleInitial":"M.","affiliations":[{"id":62280,"text":"University of Utah Seismograph Stations, University of Utah, USA","active":true,"usgs":false}],"preferred":false,"id":839993,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":839994,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Llenos, Andrea L. 0000-0002-4088-6737 allenos@usgs.gov","orcid":"https://orcid.org/0000-0002-4088-6737","contributorId":4455,"corporation":false,"usgs":true,"family":"Llenos","given":"Andrea","email":"allenos@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":839995,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rubinstein, Justin 0000-0003-1274-6785","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":215341,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":839996,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yeck, William L. 0000-0002-2801-8873 wyeck@usgs.gov","orcid":"https://orcid.org/0000-0002-2801-8873","contributorId":147558,"corporation":false,"usgs":true,"family":"Yeck","given":"William","email":"wyeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":839997,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Earle, Paul S. 0000-0002-3500-017X pearle@usgs.gov","orcid":"https://orcid.org/0000-0002-3500-017X","contributorId":173551,"corporation":false,"usgs":true,"family":"Earle","given":"Paul","email":"pearle@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":839998,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gok, Rengin","contributorId":289899,"corporation":false,"usgs":false,"family":"Gok","given":"Rengin","email":"","affiliations":[{"id":62279,"text":"Lawrence Livermore National Laboratory, Livermore, CA, USA","active":true,"usgs":false}],"preferred":false,"id":839999,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Walter, William R.","contributorId":289900,"corporation":false,"usgs":false,"family":"Walter","given":"William","email":"","middleInitial":"R.","affiliations":[{"id":62279,"text":"Lawrence Livermore National Laboratory, Livermore, CA, USA","active":true,"usgs":false}],"preferred":false,"id":840000,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70229532,"text":"70229532 - 2022 - Factors affecting nest success of colonial nesting waterbirds in southwest Louisiana","interactions":[],"lastModifiedDate":"2022-03-28T16:57:27.539992","indexId":"70229532","displayToPublicDate":"2021-08-27T09:49:21","publicationYear":"2022","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":"Factors affecting nest success of colonial nesting waterbirds in southwest Louisiana","docAbstract":"

Subsidence and accelerated sea level rise impact nesting area availability and flood probabilities of breeding islands for colonial nesting waterbirds. In 2017 and 2018, we monitored 855 nests of four species of colonial nesting waterbirds on Rabbit Island, LA, to determine factors affecting nest and chick success. Based on logistic exposure models of nests, tricolored herons had the greatest likelihood of survival to hatch (mean (95% confidence interval)) (77% (65.9–83.1%)), followed by brown pelicans (70% (59.9–98.5%)), roseate spoonbills (70% (38.9–83.8%)), and Forster’s terns (12% (10.7–12.2%)). Likelihood of survival to fledge was highest for tricolored herons (32% (12.8–40.7%)), followed by brown pelicans (28% (19.5–28.6%)), roseate spoonbills (47% (43.7–53.3%)), and Forster’s terns (0% (0.005–0.01%)). Nesting strategy and nest timing impacted survival rate; however, the effect depended on timing of inundation events as the timing of inundation events varied across years. Flooding was the primary cause of nest failure for most species. In 2003–2012, rapid expansion in brown pelican colony numbers and significant chick production occurred at Rabbit Island, but hydrologic records indicate no island inundation occurred during the breeding season from the beginning of the hydrologic record (2006) through 2011. Thus, our results contrast with those of previous studies conducted under different hydrologic conditions and demonstrate the challenges of short-term studies informing coastal restoration in a system that is influenced by multi-year to multi-decadal climatic cycles.


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\"}}]}","volume":"45","noUsgsAuthors":false,"publicationDate":"2021-08-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Ritenour, K.","contributorId":288348,"corporation":false,"usgs":false,"family":"Ritenour","given":"K.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":837772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":837773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, S. M.","contributorId":273184,"corporation":false,"usgs":false,"family":"Collins","given":"S.","email":"","middleInitial":"M.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":837774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaller, M.D.","contributorId":288351,"corporation":false,"usgs":false,"family":"Kaller","given":"M.D.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":837775,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227377,"text":"70227377 - 2022 - Basin and site effects in the U.S. Pacific Northwest estimated from small‐magnitude earthquakes","interactions":[],"lastModifiedDate":"2022-02-15T16:24:50.654097","indexId":"70227377","displayToPublicDate":"2021-08-24T07:03:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Basin and site effects in the U.S. Pacific Northwest estimated from small‐magnitude earthquakes","docAbstract":"

Earthquake hazards in the U.S. Pacific Northwest (PNW) are increased by the presence of deep sedimentary basins that amplify and prolong ground shaking. To better understand basin and site effects on ground motions, we compile a database of recordings from crustal and intraslab earthquakes. We process 8028 records with magnitudes from 3.5 to 6.8 and hypocentral depths up to 62 km to compute Fourier amplitude spectra of ground acceleration for frequencies of 0–20 Hz. We compute residuals relative to the Bayless and Abrahamson (2019; hereafter, BA18) ground‐motion model and perform a series of linear, crossed, mixed‐effects regressions. In addition to estimating the bias, event, and site terms, we incorporate groupings for broad regionalized site response in three different regions (Seattle basin, Puget Lowland, non‐Puget Lowland), for effects from seismotectonic regime (crustal and intraslab sources), and for interactions between the regions and seismotectonic regimes. We find that the scaling of site response with respect to VS30 (time‐averaged shear‐wave velocity from the surface to a depth of 30 m) and to basin depth indicators Z1.0 and Z2.5 (depths to the 1.0 and 2.5 km/s shear‐wave velocity horizons) is generally consistent with BA18; however, the region terms display strong spatial amplification patterns. For frequencies less than 5 Hz, the Seattle basin amplifies ground motions up to a factor of four, relative to the non‐Puget Lowland, with a maximum amplification around near 0.5 Hz. Sites in the Puget Lowland amplify low frequencies up to a factor of 2.5. At higher frequencies (⁠f>5  Hz⁠), the Puget Lowland and Seattle basin show regional deamplification of ground motions, with the smallest average amplification factor of 0.65 occurring at 10.0 Hz. Although we observe slight differences in the seismotectonic regime terms, we find that the region terms are significantly more important for modeling earthquake hazard in the PNW.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120210029","usgsCitation":"Rekoske, J., Moschetti, M.P., and Thompson, E.M., 2022, Basin and site effects in the U.S. Pacific Northwest estimated from small‐magnitude earthquakes: Bulletin of the Seismological Society of America, v. 112, no. 1, p. 438-456, https://doi.org/10.1785/0120210029.","productDescription":"19 p.","startPage":"438","endPage":"456","ipdsId":"IP-129686","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":436058,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BUCRF7","text":"USGS data release","linkHelpText":"Database of horizontal component Fourier amplitude spectra of acceleration ground motions from Pacific Northwest earthquakes"},{"id":394240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, 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\"}}]}","volume":"112","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Rekoske, John 0000-0003-0539-2069","orcid":"https://orcid.org/0000-0003-0539-2069","contributorId":220108,"corporation":false,"usgs":true,"family":"Rekoske","given":"John","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":830664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":830665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Eric M. 0000-0002-6943-4806 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Emerging evidence suggests that zooplankton production is affected by physiological and nutritional constraints due to climate change and eutrophication, which in turn could have broad implications for food-web dynamics and fisheries production. In this study, we developed a resource-based zooplankton production dynamics model that causally links freshwater cladoceran and copepod daily production-to-biomass (P/B) ratios with water temperature, phytoplankton biomass and community composition, and zooplankton feeding selectivity. This model was used to evaluate constraints on zooplankton growth under four hypothetical scenarios: involving natural plankton community seasonal succession; lake fertilization to enhance fisheries production; eutrophication; and climatic warming. Our novel modeling approach predicts zooplankton production is strongly dependent on seasonal variation in resource availability and quality, which results in more complex zooplankton dynamics than predicted by simpler temperature dependent models. For mesotrophic and hypereutrophic lakes, our study suggests that the ultimate control over zooplankton P/B ratios shifts from physiological control during colder periods to strong resource control during warmer periods. Our resource-based model provided important insights into the nature of biophysical control of zooplankton under a changing climate that has crucial implications for food web energy transfer and fisheries production.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2021-0071","usgsCitation":"Zhang, C., Brett, M.T., Nielsen, J.M., Arhonditsis, G.B., Ballantyne, A.P., Carter, J.L., Kann, J., Muller-Navarra, D.C., Schindler, D., Stockwell, J.D., Winder, M., and Beauchamp, D., 2022, Physiological and nutritional constraints on zooplankton productivity due to eutrophication and climate change predicted using a resource-based modeling approach: Canadian Journal of Fisheries and Aquatic Sciences, v. 79, no. 3, p. 472-486, https://doi.org/10.1139/cjfas-2021-0071.","productDescription":"15 p.","startPage":"472","endPage":"486","ipdsId":"IP-107589","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":449738,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2021-0071","text":"External 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Jens M","contributorId":265169,"corporation":false,"usgs":false,"family":"Nielsen","given":"Jens","email":"","middleInitial":"M","affiliations":[{"id":54619,"text":"Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98195, USA","active":true,"usgs":false}],"preferred":false,"id":822399,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arhonditsis, George B","contributorId":265170,"corporation":false,"usgs":false,"family":"Arhonditsis","given":"George","email":"","middleInitial":"B","affiliations":[{"id":54621,"text":"Ecological Modeling Laboratory, Department of Physical & Environmental Sciences, University of Toronto, Toronto, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":822400,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ballantyne, Ashley P","contributorId":166784,"corporation":false,"usgs":false,"family":"Ballantyne","given":"Ashley","email":"","middleInitial":"P","affiliations":[{"id":24513,"text":"Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":822401,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carter, Jackie L","contributorId":265171,"corporation":false,"usgs":false,"family":"Carter","given":"Jackie","email":"","middleInitial":"L","affiliations":[{"id":54623,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington 98195, USA","active":true,"usgs":false}],"preferred":false,"id":822402,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kann, Jacob","contributorId":265172,"corporation":false,"usgs":false,"family":"Kann","given":"Jacob","email":"","affiliations":[{"id":54624,"text":"Aquatic Ecosystem Sciences, LLC, 295 East Main St., Suite 7, Ashland, OR 97520, USA","active":true,"usgs":false}],"preferred":false,"id":822403,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Muller-Navarra, Dorthe C","contributorId":265173,"corporation":false,"usgs":false,"family":"Muller-Navarra","given":"Dorthe","email":"","middleInitial":"C","affiliations":[{"id":54625,"text":"University of Hamburg, Aquatic Ecology, Hamburg, Germany","active":true,"usgs":false}],"preferred":false,"id":822404,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schindler, Daniel E.","contributorId":223885,"corporation":false,"usgs":false,"family":"Schindler","given":"Daniel E.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":822405,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stockwell, Jason D. 0000-0003-3393-6799","orcid":"https://orcid.org/0000-0003-3393-6799","contributorId":61004,"corporation":false,"usgs":false,"family":"Stockwell","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":822406,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Winder, Monika","contributorId":196556,"corporation":false,"usgs":false,"family":"Winder","given":"Monika","email":"","affiliations":[],"preferred":false,"id":822407,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":822408,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70229452,"text":"70229452 - 2022 - Connecting regional-scale tree distribution models with seed dispersal kernels","interactions":[],"lastModifiedDate":"2022-03-09T15:55:47.176117","indexId":"70229452","displayToPublicDate":"2021-08-22T09:50:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10270,"text":"Applied Mathematics and Computation","active":true,"publicationSubtype":{"id":10}},"title":"Connecting regional-scale tree distribution models with seed dispersal kernels","docAbstract":"

Regional scale forest distribution models are important tools for biogeography and understanding the structure of forest communities in space. These models take climate and geographic variables as input and are therefore helpful for long-term decision support and climate adaptation planning. Generally, local processes of tree germination and seedling survival are resolved probabilistically with explanatory variables such as elevation, latitude, exposure, soil type, moisture availability, climate and weather inputs and `trained’ using landscape and regional presence-absence data and machine learning techniques. How seeds are distributed in these models, that is, determining the dispersal kernel, is far more problematic. The challenge is that variables conditioning vertebrate seed dispersal (motility and probability of utilization or caching in response to cover type) are not represented in large scale distribution models, and in fact vary on scales (10-100 meters) that are much smaller than the smallest pixel size for the distribution model (1-10 kilometers). We present a homogenized seed digestion kernel (HSDK) which incorporates this scale separation. Homogenization naturally links highly variable small-scale processes (like seed foraging and caching by birds and rodents) with large scale effects (like dispersal of seeds over tens of kilometers). We develop a homogenization strategy to predict seed dispersal on landscape scales, analytically linking small-scale variables (landscape fraction cover by tree type, gut residence times and cover type utilization by frugivorous birds) with large scale behaviors. Closed form approximations are developed in two dimensions for two limiting cases of seed handling behavior, and the approach is illustrated using landscape data and piñon-pine dispersal in a 630,000 square kilometer region in the southwestern US.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.amc.2021.126591","usgsCitation":"Neupane, R.C., Powell, J., and Edwards, T., 2022, Connecting regional-scale tree distribution models with seed dispersal kernels: Applied Mathematics and Computation, v. 412, 126591, 17 p., https://doi.org/10.1016/j.amc.2021.126591.","productDescription":"126591, 17 p.","ipdsId":"IP-124972","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449740,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.amc.2021.126591","text":"Publisher Index Page"},{"id":396921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"412","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Neupane, Ram C.","contributorId":288149,"corporation":false,"usgs":false,"family":"Neupane","given":"Ram","email":"","middleInitial":"C.","affiliations":[{"id":61709,"text":"ta&m","active":true,"usgs":false}],"preferred":false,"id":837519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powell, James A.","contributorId":288150,"corporation":false,"usgs":false,"family":"Powell","given":"James A.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":837520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, Thomas C. Jr. 0000-0002-0773-0909 tce@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-0909","contributorId":191916,"corporation":false,"usgs":true,"family":"Edwards","given":"Thomas C.","suffix":"Jr.","email":"tce@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":837518,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224338,"text":"70224338 - 2022 - Solutions in microbiome engineering: Prioritizing barriers to organism establishment","interactions":[],"lastModifiedDate":"2022-01-25T16:50:53.459975","indexId":"70224338","displayToPublicDate":"2021-08-21T07:11:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9357,"text":"The ISME Journal: Multidisciplinary Journal of Microbial Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Solutions in microbiome engineering: Prioritizing barriers to organism establishment","docAbstract":"

Microbiome engineering is increasingly being employed as a solution to challenges in health, agriculture, and climate. Often manipulation involves inoculation of new microbes designed to improve function into a preexisting microbial community. Despite, increased efforts in microbiome engineering inoculants frequently fail to establish and/or confer long-lasting modifications on ecosystem function. We posit that one underlying cause of these shortfalls is the failure to consider barriers to organism establishment. This is a key challenge and focus of macroecology research, specifically invasion biology and restoration ecology. We adopt a framework from invasion biology that summarizes establishment barriers in three categories: (1) propagule pressure, (2) environmental filtering, and (3) biotic interactions factors. We suggest that biotic interactions is the most neglected factor in microbiome engineering research, and we recommend a number of actions to accelerate engineering solutions.

","language":"English","publisher":"Nature","doi":"10.1038/s41396-021-01088-5","usgsCitation":"Albright, M., Louca, S., Winkler, D.E., Feeser, K.L., Haig, S., Whiteson, K.L., Emerson, J.B., and Dunbar, J.M., 2022, Solutions in microbiome engineering: Prioritizing barriers to organism establishment: The ISME Journal: Multidisciplinary Journal of Microbial Ecology, v. 16, p. 331-338, https://doi.org/10.1038/s41396-021-01088-5.","productDescription":"8 p.","startPage":"331","endPage":"338","ipdsId":"IP-127565","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":449741,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41396-021-01088-5","text":"Publisher Index Page"},{"id":389634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","noUsgsAuthors":false,"publicationDate":"2021-08-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Albright, Michaeline B.N.","contributorId":265940,"corporation":false,"usgs":false,"family":"Albright","given":"Michaeline B.N.","affiliations":[{"id":54832,"text":"Bioscience Division, Los Alamos National Laboratory, NM","active":true,"usgs":false}],"preferred":false,"id":823814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Louca, Stilianos","contributorId":195708,"corporation":false,"usgs":false,"family":"Louca","given":"Stilianos","email":"","affiliations":[],"preferred":false,"id":823815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":823816,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feeser, Kelli L.","contributorId":265941,"corporation":false,"usgs":false,"family":"Feeser","given":"Kelli","email":"","middleInitial":"L.","affiliations":[{"id":54832,"text":"Bioscience Division, Los Alamos National Laboratory, NM","active":true,"usgs":false}],"preferred":false,"id":823817,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haig, Sarah-Jane","contributorId":265942,"corporation":false,"usgs":false,"family":"Haig","given":"Sarah-Jane","email":"","affiliations":[{"id":54833,"text":"Department of Civil and Environmental Engineering, University of Pittsburg, PA","active":true,"usgs":false}],"preferred":false,"id":823818,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whiteson, Katrine L.","contributorId":265943,"corporation":false,"usgs":false,"family":"Whiteson","given":"Katrine","email":"","middleInitial":"L.","affiliations":[{"id":54834,"text":"Department of Molecular Biology and Biochemistry, University of California, Irvine, CA","active":true,"usgs":false}],"preferred":false,"id":823819,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Emerson, Joanne B.","contributorId":265944,"corporation":false,"usgs":false,"family":"Emerson","given":"Joanne","email":"","middleInitial":"B.","affiliations":[{"id":54835,"text":"Department of Plant Pathology, University of California, Davis, CA","active":true,"usgs":false}],"preferred":false,"id":823820,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dunbar, John M.","contributorId":105778,"corporation":false,"usgs":false,"family":"Dunbar","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":823821,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70223849,"text":"70223849 - 2022 - Incorporating antenna detections into abundance estimates of fish","interactions":[],"lastModifiedDate":"2022-03-15T16:01:40.457204","indexId":"70223849","displayToPublicDate":"2021-08-18T06:57:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating antenna detections into abundance estimates of fish","docAbstract":"
Autonomous passive integrated transponder (PIT) tag antennas are commonly used to detect fish marked with PIT tags but cannot detect unmarked fish, creating challenges for abundance estimation. Here we describe an approach to estimate abundance from paired physical capture and antenna detection data in closed and open mark-recapture models. Additionally, for open models, we develop an approach that incorporates uncertainty in fish size, because fish size changes through time (as fish grow bigger) but is unknown if fish are not physically captured (e.g., only detected on antennas). Incorporation of size uncertainty allows for estimation of size-specific abundances and demonstrates a generally useful method for obtaining state-specific abundances estimates under state uncertainty. Simulation studies comparing models with and without antenna detections illustrate that the benefit of our approach increases as a larger proportion of the population is marked. When applied to two field data sets, our approach to incorporating antenna detections reduced uncertainty in abundance substantially. We conclude that PIT antennas hold great potential for improving abundance estimation, despite the challenges they present.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2021-0003","usgsCitation":"Dzul, M.C., Yackulic, C., Kendall, W.L., Winkelman, D.L., Conner, M.M., and Yard, M.D., 2022, Incorporating antenna detections into abundance estimates of fish: Canadian Journal of Fisheries and Aquatic Sciences, v. 79, no. 3, p. 436-447, https://doi.org/10.1139/cjfas-2021-0003.","productDescription":"12 p.","startPage":"436","endPage":"447","ipdsId":"IP-125707","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":449745,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1807/109444","text":"External Repository"},{"id":436059,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZCNR6X","text":"USGS data release","linkHelpText":"Humpback chub (Gila cypha) capture history data (2009-2020), Grand Canyon, Arizona"},{"id":389049,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"79","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dzul, Maria C. 0000-0002-4798-5930 mdzul@usgs.gov","orcid":"https://orcid.org/0000-0002-4798-5930","contributorId":5469,"corporation":false,"usgs":true,"family":"Dzul","given":"Maria","email":"mdzul@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":822926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":822927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":822928,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":822929,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Conner, Mary M","contributorId":222152,"corporation":false,"usgs":false,"family":"Conner","given":"Mary","email":"","middleInitial":"M","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":822930,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yard, Michael D. 0000-0002-6580-6027 myard@usgs.gov","orcid":"https://orcid.org/0000-0002-6580-6027","contributorId":169281,"corporation":false,"usgs":true,"family":"Yard","given":"Michael","email":"myard@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":822931,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70230385,"text":"70230385 - 2022 - The US Geological Survey ground failure product: Near-real-time estimates of earthquake-triggered landslides and liquefaction","interactions":[],"lastModifiedDate":"2022-04-11T14:20:51.924412","indexId":"70230385","displayToPublicDate":"2021-08-14T06:46:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"The US Geological Survey ground failure product: Near-real-time estimates of earthquake-triggered landslides and liquefaction","docAbstract":"

Since late 2018, the US Geological Survey (USGS) ground failure (GF) earthquake product has provided publicly available spatial estimates of earthquake-triggered landslide and liquefaction hazards, along with the qualitative hazard and population exposure-based alerts for M > 6 earthquakes worldwide and in near real time (within ∼30 min). Earthquake losses are oftentimes greatly aggravated by the impacts due to ground failure, yet those particular events with dramatic additional losses have not, heretofore, been rapidly identifiable. The GF product now provides situational awareness about the potential extent and severity of ground failure in the crucial time period before direct observations are available. We describe our implementation of the GF product and the lessons learned from the earthquakes that have occurred since the GF product was released. We describe the product design process, the underlying GF models, the methods we have developed for modeling uncertainty, and the development of the alert levels. The GF product has been produced in near real time for 320 events over the 2-year period since its public implementation in late 2018 through early 2021. The majority of these events yielded the lowest level (green) alerts for all ground-failure types, with 25 resulting in elevated hazard or exposure to landslides and 47 for liquefaction. In a qualitative comparison between the GF product alerts and GF occurrence information, we found that the product succeeds at assigning appropriate alert levels in the majority of cases. Based on our experience with the product, we have identified the following priorities for future improvements: (1) refinements of the underlying probabilistic models to incorporate severity and explicitly model the type of landslide/liquefaction; (2) development of models for fatalities and economic losses due to ground failure; and (3) estimation of the impacts of ground failure on infrastructure.

","language":"English","publisher":"SAGE","doi":"10.1177/87552930211032685","usgsCitation":"Allstadt, K.E., Thompson, E.M., Jibson, R., Wald, D.J., Hearne, M., Hunter, E.J., Fee, J., Schovanec, H., Slosky, D., and Haynie, K.L., 2022, The US Geological Survey ground failure product: Near-real-time estimates of earthquake-triggered landslides and liquefaction: Earthquake Spectra, v. 38, no. 1, p. 5-36, https://doi.org/10.1177/87552930211032685.","productDescription":"32 p.","startPage":"5","endPage":"36","ipdsId":"IP-127952","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":449748,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/87552930211032685","text":"Publisher Index Page"},{"id":436060,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91G4NS4","text":"USGS data release","linkHelpText":"groundfailure"},{"id":398467,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840145,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840146,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jibson, Randall W.","contributorId":247850,"corporation":false,"usgs":false,"family":"Jibson","given":"Randall W.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":840147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840148,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hearne, Mike 0000-0002-8225-2396 mhearne@usgs.gov","orcid":"https://orcid.org/0000-0002-8225-2396","contributorId":4659,"corporation":false,"usgs":true,"family":"Hearne","given":"Mike","email":"mhearne@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840149,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hunter, Edward J. 0000-0003-0708-1459","orcid":"https://orcid.org/0000-0003-0708-1459","contributorId":290020,"corporation":false,"usgs":true,"family":"Hunter","given":"Edward","email":"","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840150,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fee, Jeremy 0000-0002-6851-2796 jmfee@usgs.gov","orcid":"https://orcid.org/0000-0002-6851-2796","contributorId":194758,"corporation":false,"usgs":true,"family":"Fee","given":"Jeremy","email":"jmfee@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840151,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schovanec, Heather","contributorId":290119,"corporation":false,"usgs":false,"family":"Schovanec","given":"Heather","email":"","affiliations":[],"preferred":false,"id":840308,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Slosky, Daniel 0000-0001-7407-3606 dslosky@usgs.gov","orcid":"https://orcid.org/0000-0001-7407-3606","contributorId":194954,"corporation":false,"usgs":true,"family":"Slosky","given":"Daniel","email":"dslosky@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840152,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Haynie, Kirstie Lafon 0000-0001-9930-6736","orcid":"https://orcid.org/0000-0001-9930-6736","contributorId":289894,"corporation":false,"usgs":true,"family":"Haynie","given":"Kirstie","email":"","middleInitial":"Lafon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840309,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70228362,"text":"70228362 - 2022 - NGA-subduction global ground motion models with regional adjustment factors","interactions":[],"lastModifiedDate":"2022-02-10T12:03:19.524677","indexId":"70228362","displayToPublicDate":"2021-08-13T10:07:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"NGA-subduction global ground motion models with regional adjustment factors","docAbstract":"

We develop semi-empirical ground motion models (GMMs) for peak ground acceleration, peak ground velocity, and 5%-damped pseudo-spectral accelerations for periods from 0.01 to 10 s, for the median orientation-independent horizontal component of subduction earthquake ground motion. The GMMs are applicable to interface and intraslab subduction earthquakes in Japan, Taiwan, Mexico, Central America, South America, Alaska, the Aleutian Islands, and Cascadia. The GMMs are developed using a combination of data inspection, data regression with respect to physics-informed functions, ground-motion simulations, and geometrical constraints for certain model components. The GMMs capture observed differences in source and path effects for interface and intraslab events, conditioned on moment magnitude, rupture distance, and hypocentral depth. Site effect and aleatory variability models are shared between event types. Regionalized GMM components include the model constant (that controls ground motion amplitude), anelastic attenuation, magnitude-scaling break point, linear site response, and sediment depth terms. We develop models for the aleatory between-event variability (&#x3C4;)\">(τ), within-event variability (&#x3D5;)\">(ϕ), single-station within-event variability (&#x3D5;SS)\">(ϕSS), and site-to-site variability (&#x3D5;S2S)\">(ϕS2S). Ergodic analyses should use the median GMM and aleatory variability computed using the between-event and within-event variability models. An analysis incorporating non-ergodic site response should use the median GMM at the reference shear-wave velocity condition, a site-specific site response model, and aleatory variability computed using the between-event and single-station within-event variability models. Epistemic uncertainty in the median model is represented by standard deviations on the regional model constants, which facilitates scaled-backbone representations of model uncertainty in hazard analyses.

","language":"English","publisher":"SAGE Publishing","doi":"10.1177/87552930211034889","usgsCitation":"Parker, G.A., Stewart, J.P., Boore, D., Atkinson, G.M., and Hassani, B., 2022, NGA-subduction global ground motion models with regional adjustment factors: Earthquake Spectra, v. 38, no. 1, p. 456-493, https://doi.org/10.1177/87552930211034889.","productDescription":"38 p.","startPage":"456","endPage":"493","ipdsId":"IP-122810","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":395672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-08-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Parker, Grace Alexandra 0000-0002-9445-2571","orcid":"https://orcid.org/0000-0002-9445-2571","contributorId":237091,"corporation":false,"usgs":true,"family":"Parker","given":"Grace","email":"","middleInitial":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":833952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stewart, Jonathan P.","contributorId":100110,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":833953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boore, David 0000-0002-8605-9673 boore@usgs.gov","orcid":"https://orcid.org/0000-0002-8605-9673","contributorId":140502,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":833954,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Atkinson, Gail M.","contributorId":60515,"corporation":false,"usgs":false,"family":"Atkinson","given":"Gail","email":"","middleInitial":"M.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":833955,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hassani, Behzad","contributorId":275298,"corporation":false,"usgs":false,"family":"Hassani","given":"Behzad","email":"","affiliations":[{"id":37568,"text":"BC Hydro","active":true,"usgs":false}],"preferred":false,"id":833956,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223304,"text":"70223304 - 2022 - From drought to deluge: Spatiotemporal variation in migration routing, survival, travel time and floodplain use of an endangered migratory fish","interactions":[],"lastModifiedDate":"2022-03-15T15:58:31.592817","indexId":"70223304","displayToPublicDate":"2021-08-11T08:01:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"From drought to deluge: Spatiotemporal variation in migration routing, survival, travel time and floodplain use of an endangered migratory fish","docAbstract":"
We developed a novel statistical model to relate the daily survival and migration dynamics of an endangered anadromous fish to river flow and water temperature during both extreme drought and severe flooding in an intensively managed river system. Our Bayesian temporally stratified multistate mark recapture model integrates over unobserved travel times and route transitions to efficiently estimate covariate relationships and includes an adjustment for telemetry tag battery failure. We applied the model to acoustic-tagged juvenile Sacramento river winter-run Chinook salmon (Oncorhynchus tshawytscha) and found that survival decreased with decreasing river flows and increased water temperatures. We found that fish were likely to enter at a large floodplain during flood conditions and that survival in floodplain was comparable to the mainstem Sacramento river. Our study demonstrates the response of an endangered anadromous fish population to extreme spatial and temporal variability in habitat accessibility and quality. The general model framework we introduce here can be applied to telemetry of migratory fish through systems with multiple routes to efficiently estimate spatiotemporal variation in survival, travel time, and routing.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2021-0042","usgsCitation":"Hance, D., Perry, R., Pope, A., Ammann, A.J., Hassrick, J.L., and Hansen, G.S., 2022, From drought to deluge: Spatiotemporal variation in migration routing, survival, travel time and floodplain use of an endangered migratory fish: Canadian Journal of Fisheries and Aquatic Sciences, v. 79, no. 3, p. 410-428, https://doi.org/10.1139/cjfas-2021-0042.","productDescription":"19 p.","startPage":"410","endPage":"428","ipdsId":"IP-127321","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":449755,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/50483","text":"External Repository"},{"id":388223,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.73925781250001,\n 37.78808138412046\n ],\n [\n -121.343994140625,\n 37.78808138412046\n ],\n [\n -121.343994140625,\n 39.2\n ],\n [\n -122.73925781250001,\n 39.2\n ],\n [\n -122.73925781250001,\n 37.78808138412046\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"79","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hance, Dalton 0000-0002-4475-706X","orcid":"https://orcid.org/0000-0002-4475-706X","contributorId":220179,"corporation":false,"usgs":true,"family":"Hance","given":"Dalton","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":821665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":217814,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":821666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pope, Adam C. 0000-0002-7253-2247","orcid":"https://orcid.org/0000-0002-7253-2247","contributorId":223237,"corporation":false,"usgs":true,"family":"Pope","given":"Adam","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":821667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ammann, Arnold J.","contributorId":207095,"corporation":false,"usgs":false,"family":"Ammann","given":"Arnold","email":"","middleInitial":"J.","affiliations":[{"id":37452,"text":"National Marine Fisheries Service, Southwest Fisheries Science Center, 110 Shaffer Rd., Santa Cruz, CA 95060","active":true,"usgs":false}],"preferred":false,"id":821668,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hassrick, Jason L.","contributorId":264556,"corporation":false,"usgs":false,"family":"Hassrick","given":"Jason","email":"","middleInitial":"L.","affiliations":[{"id":54497,"text":"ICF, 201 Mission Street, Suite 1500, San Francisco, CA 94105 USA","active":true,"usgs":false}],"preferred":false,"id":821669,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hansen, Gabriel S. 0000-0001-6272-3632 ghansen@usgs.gov","orcid":"https://orcid.org/0000-0001-6272-3632","contributorId":3422,"corporation":false,"usgs":true,"family":"Hansen","given":"Gabriel","email":"ghansen@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":821670,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229703,"text":"70229703 - 2022 - Understanding the effects of climate change via disturbance on pristine arctic lakes — Multitrophic level response and recovery to a 12-yr, low-level fertilization experiment","interactions":[],"lastModifiedDate":"2022-04-12T13:46:22.68099","indexId":"70229703","displayToPublicDate":"2021-08-02T09:51:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the effects of climate change via disturbance on pristine arctic lakes — Multitrophic level response and recovery to a 12-yr, low-level fertilization experiment","docAbstract":"

Effects of climate change-driven disturbance on lake ecosystems can be subtle; indirect effects include increased nutrient loading that could impact ecosystem function. We designed a low-level fertilization experiment to mimic persistent, climate change-driven disturbances (deeper thaw, greater weathering, or thermokarst failure) delivering nutrients to arctic lakes. We measured responses of pelagic trophic levels over 12 yr in a fertilized deep lake with fish and a shallow fishless lake, compared to paired reference lakes, and monitored recovery for 6 yr. Relative to prefertilization in the deep lake, we observed a maximum pelagic response in chl a (+201%), dissolved oxygen (DO, −43%), and zooplankton biomass (+88%) during the fertilization period (2001–2012). Other responses to fertilization, such as water transparency and fish relative abundance, were delayed, but both ultimately declined. Phyto- and zooplankton biomass and community composition shifted with fertilization. The effects of fertilization were less pronounced in the paired shallow lakes, because of a natural thermokarst failure likely impacting the reference lake. In the deep lake there was (a) moderate resistance to change in ecosystem functions at all trophic levels, (b) eventual responses were often nonlinear, and (c) postfertilization recovery (return) times were most rapid at the base of the food web (2–4 yr) while higher trophic levels failed to recover after 6 yr. The timing and magnitude of responses to fertilization in these arctic lakes were similar to responses in other lakes, suggesting indirect effects of climate change that modify nutrient inputs may affect many lakes in the future.

","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.11893","usgsCitation":"Budy, P., Pennock, C., Giblin, A.E., Luecke, C., White, D.L., and Kling, G., 2022, Understanding the effects of climate change via disturbance on pristine arctic lakes — Multitrophic level response and recovery to a 12-yr, low-level fertilization experiment: Limnology and Oceanography, v. 67, no. S1, p. S224-S241, https://doi.org/10.1002/lno.11893.","productDescription":"18 p.","startPage":"S224","endPage":"S241","ipdsId":"IP-129828","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449764,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.11893","text":"Publisher Index Page"},{"id":397154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Toolik Field Station","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.8642578125,\n 68.24089575900885\n ],\n [\n -148.73291015625,\n 68.24089575900885\n ],\n [\n -148.73291015625,\n 68.87143872335129\n ],\n [\n -150.8642578125,\n 68.87143872335129\n ],\n [\n -150.8642578125,\n 68.24089575900885\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"67","issue":"S1","noUsgsAuthors":false,"publicationDate":"2021-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":838019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pennock, Casey A.","contributorId":287044,"corporation":false,"usgs":false,"family":"Pennock","given":"Casey A.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":838020,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giblin, Anne E.","contributorId":103966,"corporation":false,"usgs":true,"family":"Giblin","given":"Anne","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":838021,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Luecke, Chris","contributorId":239659,"corporation":false,"usgs":false,"family":"Luecke","given":"Chris","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":838022,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, D. L.","contributorId":288498,"corporation":false,"usgs":false,"family":"White","given":"D.","email":"","middleInitial":"L.","affiliations":[{"id":61777,"text":"wh","active":true,"usgs":false}],"preferred":false,"id":838023,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kling, George","contributorId":120446,"corporation":false,"usgs":true,"family":"Kling","given":"George","email":"","affiliations":[],"preferred":false,"id":838024,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70226472,"text":"70226472 - 2022 - Trachyandesite of Kennedy Table, its vent complex, and post−9.3 Ma uplift of the central Sierra Nevada","interactions":[],"lastModifiedDate":"2022-05-13T14:33:49.961069","indexId":"70226472","displayToPublicDate":"2021-08-02T07:40:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Trachyandesite of Kennedy Table, its vent complex, and post−9.3 Ma uplift of the central Sierra Nevada","docAbstract":"

Tectonic interpretation of the central Sierra Nevada—whether the crest of the Sierra Nevada (California, USA) was uplifted in the late Cenozoic or whether the range has undergone continuous down-wearing since the Late Cretaceous—is controversial, since there is no obvious tectonic explanation for renewed uplift. The strongest direct evidence for late Cenozoic uplift of the central Sierra Nevada comes from study of the Trachyandesite of Kennedy Table, which followed the course of the Miocene San Joaquin River but has a steeper gradient than the modern river. Early workers attributed this steeper gradient to tilting of the Sierra Nevada block since the late Miocene, resulting in 2 km of range-crest uplift. However, this interpretation has been contested on grounds that the Miocene river gradient had to be assumed and that the Sierran Batholith could have warped during tilting, thus failing to uplift the range crest. The objective of this study was to obtain quantitative data that test these criticisms.

The Trachyandesite of Kennedy Table is a chain of 33 remnants of a single lava flow as thick as 65 m, preserved for 21 km from Squaw Leap to Little Dry Creek, close to the modern San Joaquin River in the foothills of the Sierra Nevada. Several remnants lie on fluvial gravel of the late Miocene San Joaquin River. Early workers speculated that the lava concealed its own (unrecognized) vent, but in 2011, we identified the vent on the Middle Fork of the San Joaquin River, 13.5 km south of Deadman Pass and 70 km northeast of Kennedy Table. The vent complex intrudes Cretaceous granite, has 285 m relief, and is an intricately jointed intrusion that grades up into a glassy lava flow. Composition (58% SiO2) and 40Ar/39Ar age (9.3 Ma) are identical at the vent and downstream. Basal elevations of remnants were recorded, and the present-day basal gradients of several were adjusted for apparent dip and projected along a vertical plane at 220° (the estimated tilt azimuth). The basal gradients are far steeper than that of the modern river, but they differ slightly from reach to reach and are thus inconsistent measures of the post-Miocene tilt. Likewise, relief eroded atop most remnants renders modeling of upper surfaces suspect. At Little Dry Creek, however, a chain of nine remnants rests on fluvial floodplain sand and gravel; this chain trends 230°, and its smooth basal contact now dips 1.36° (adjusted at 220°). Projection of this dip 89 km from the 207 m base of the most distal remnant at Little Dry Creek to the vent intrusion falls far below the 2760 m intrusion-to-lava-flow transition near the Sierran crest, showing that the Sierran block has not undergone pronounced convex warping. Using elevation data on paleoriver meanders preserved by the lava flow, we show that the paleogradient has a cosine dependence on meander-section azimuth, indicating tilting. Subtraction of 1.07° of dip restores the data to an azimuth-independent configuration, indicating total tilting since 9.3 Ma of 1.07° and an original large-scale gradient of 0.46°, similar to the published value of 0.33° at Squaw Leap, but larger than the previously obtained value of 0.057° at Little Dry Creek. Subtraction of those Miocene estimates from the observable 1.643° tilt along the section from Little Dry Creek to the vent yields vent uplift of 2464 m (for 0.057°), 1835 m (for 0.46°), and 2040 m (for 0.33°). Confirmation of earlier assumptions regarding Miocene river gradient and block rigidity greatly strengthens the case for ∼2 km of late Cenozoic uplift of the central Sierra Nevada crest.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/B36125.1","usgsCitation":"Hildreth, E., Fierstein, J., Phillips, F., and Calvert, A.T., 2022, Trachyandesite of Kennedy Table, its vent complex, and post−9.3 Ma uplift of the central Sierra Nevada: GSA Bulletin, v. 134, no. 5-6, p. 1143-1159, https://doi.org/10.1130/B36125.1.","productDescription":"17 p.","startPage":"1143","endPage":"1159","ipdsId":"IP-130343","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":449767,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/b36125.1","text":"Publisher Index Page"},{"id":391916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sierra Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120,\n 37\n ],\n [\n -119,\n 37\n ],\n [\n -119,\n 37.75\n ],\n [\n -120,\n 37.75\n ],\n [\n -120,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"134","issue":"5-6","noUsgsAuthors":false,"publicationDate":"2021-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Hildreth, Edward 0000-0002-7925-4251 hildreth@usgs.gov","orcid":"https://orcid.org/0000-0002-7925-4251","contributorId":146999,"corporation":false,"usgs":true,"family":"Hildreth","given":"Edward","email":"hildreth@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":827032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fierstein, Judith 0000-0001-8024-1426 jfierstn@usgs.gov","orcid":"https://orcid.org/0000-0001-8024-1426","contributorId":147000,"corporation":false,"usgs":true,"family":"Fierstein","given":"Judith","email":"jfierstn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":827033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, Fred M.","contributorId":269402,"corporation":false,"usgs":false,"family":"Phillips","given":"Fred M.","affiliations":[{"id":34868,"text":"New Mexico Institute of Mining and Technology","active":true,"usgs":false}],"preferred":false,"id":827034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":827035,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70240891,"text":"70240891 - 2022 - Potential role for microbial ureolysis in the rapid formation of carbonate tufa mounds","interactions":[],"lastModifiedDate":"2023-02-28T12:41:34.192522","indexId":"70240891","displayToPublicDate":"2021-08-02T06:38:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1751,"text":"Geobiology","active":true,"publicationSubtype":{"id":10}},"title":"Potential role for microbial ureolysis in the rapid formation of carbonate tufa mounds","docAbstract":"

Modern carbonate tufa towers in the alkaline (~pH 9.5) Big Soda Lake (BSL), Nevada, exhibit rapid precipitation rates (exceeding 3 cm/year) and host diverse microbial communities. Geochemical indicators reveal that carbonate precipitation is, in part, promoted by the mixing of calcium-rich groundwater and carbonate-rich lake water, such that a microbial role for carbonate precipitation is unknown. Here, we characterize the BSL microbial communities and evaluate their potential effects on carbonate precipitation that may influence fast carbonate precipitation rates of the active tufa mounds of BSL. Small subunit rRNA gene surveys indicate a diverse microbial community living endolithically, in interior voids, and on tufa surfaces. Metagenomic DNA sequencing shows that genes associated with metabolisms that are capable of increasing carbonate saturation (e.g., photosynthesis, ureolysis, and bicarbonate transport) are abundant. Enzyme activity assays revealed that urease and carbonic anhydrase, two microbial enzymes that promote carbonate precipitation, are active in situ in BSL tufa biofilms, and urease also increased calcium carbonate precipitation rates in laboratory incubation analyses. We propose that, although BSL tufas form partially as a result of water mixing, tufa-inhabiting microbiota promote rapid carbonate authigenesis via ureolysis, and potentially via bicarbonate dehydration and CO2 outgassing by carbonic anhydrase. Microbially induced calcium carbonate precipitation in BSL tufas may generate signatures preserved in the carbonate microfabric, such as stromatolitic layers, which could serve as models for developing potential biosignatures on Earth and elsewhere.

","language":"English","publisher":"Wiley","doi":"10.1111/gbi.12467","usgsCitation":"Medina Ferrer, F., Rosen, M., Russell, V.V., Feyhl-Buska, J., Sonderholm, F., Loyd, S., Shapiro, R., Stamps, B.W., Petryshyn, V., Demirel-Floyd, C., Bailey, J.V., Johnson, H.A., Spear, J.R., and Corsetti, F., 2022, Potential role for microbial ureolysis in the rapid formation of carbonate tufa mounds: Geobiology, v. 20, no. 1, p. 79-97, https://doi.org/10.1111/gbi.12467.","productDescription":"19 p.","startPage":"79","endPage":"97","ipdsId":"IP-114311","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":413465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Medina Ferrer, Fernando 0000-0001-9864-7627","orcid":"https://orcid.org/0000-0001-9864-7627","contributorId":238171,"corporation":false,"usgs":false,"family":"Medina Ferrer","given":"Fernando","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":865200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosen, Michael R. 0000-0003-3991-0522","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":224435,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Russell, Virginia V.","contributorId":302713,"corporation":false,"usgs":false,"family":"Russell","given":"Virginia","email":"","middleInitial":"V.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":865202,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feyhl-Buska, Jayme","contributorId":302714,"corporation":false,"usgs":false,"family":"Feyhl-Buska","given":"Jayme","email":"","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":865203,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sonderholm, Fredrik","contributorId":302715,"corporation":false,"usgs":false,"family":"Sonderholm","given":"Fredrik","email":"","affiliations":[{"id":12672,"text":"University of Copenhagen","active":true,"usgs":false}],"preferred":false,"id":865204,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loyd, Sean","contributorId":302716,"corporation":false,"usgs":false,"family":"Loyd","given":"Sean","email":"","affiliations":[{"id":13544,"text":"California State University, Fullerton","active":true,"usgs":false}],"preferred":false,"id":865205,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shapiro, Russell","contributorId":302717,"corporation":false,"usgs":false,"family":"Shapiro","given":"Russell","email":"","affiliations":[{"id":40943,"text":"California State University, Chico","active":true,"usgs":false}],"preferred":false,"id":865206,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stamps, Blake W.","contributorId":176485,"corporation":false,"usgs":false,"family":"Stamps","given":"Blake","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":865207,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Petryshyn, Victoria","contributorId":293634,"corporation":false,"usgs":false,"family":"Petryshyn","given":"Victoria","email":"","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":865208,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Demirel-Floyd, Cansu","contributorId":292063,"corporation":false,"usgs":false,"family":"Demirel-Floyd","given":"Cansu","email":"","affiliations":[{"id":62818,"text":"School of Geosciences, University of Oklahoma, Norman, OK, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":865209,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bailey, Jake V. 0000-0002-7655-5200","orcid":"https://orcid.org/0000-0002-7655-5200","contributorId":238173,"corporation":false,"usgs":false,"family":"Bailey","given":"Jake","email":"","middleInitial":"V.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":865210,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Johnson, Hope A","contributorId":293637,"corporation":false,"usgs":false,"family":"Johnson","given":"Hope","email":"","middleInitial":"A","affiliations":[{"id":63349,"text":"California State University Fullerton","active":true,"usgs":false}],"preferred":false,"id":865211,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Spear, John R.","contributorId":176847,"corporation":false,"usgs":false,"family":"Spear","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":865212,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Corsetti, Frank A","contributorId":293642,"corporation":false,"usgs":false,"family":"Corsetti","given":"Frank A","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":865213,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70222547,"text":"70222547 - 2022 - Modeling morphodynamics of coastal response to extreme events: What shape are we in?","interactions":[],"lastModifiedDate":"2022-01-25T16:45:04.659973","indexId":"70222547","displayToPublicDate":"2021-07-27T07:03:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":811,"text":"Annual Review of Marine Science","active":true,"publicationSubtype":{"id":10}},"title":"Modeling morphodynamics of coastal response to extreme events: What shape are we in?","docAbstract":"

This review focuses on recent advances in process-based numerical models of the impact of extreme storms on sandy coasts. Driven by larger-scale models of meteorology and hydrodynamics, these models simulate morphodynamics across the Sallenger storm-impact scale, including swash, collision, overwash, and inundation. Models are becoming both wider (as more processes are added) and deeper (as detailed physics replaces earlier parameterizations). Algorithms for wave-induced flows and sediment transport under shoaling waves are among the recent developments. Community and open-source models have become the norm. Observations of initial conditions (topography, land cover, and sediment characteristics) have become more detailed, and improvements in tropical cyclone and wave models provide forcing (winds, waves, surge, and upland flow) that is better resolved and more accurate, yielding commensurate improvements in model skill. We foresee that future storm-impact models will increasingly resolve individual waves, apply data assimilation, and be used in ensemble modeling modes to predict uncertainties.

","language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev-marine-032221-090215","usgsCitation":"Sherwood, C.R., van Dongeren, A., Doyle, J., Hegermiller, C., Hsu, T.J., Kalra, T., Olabarrieta, M., Penko, A., Rafati, Y., Roelvink, D., van der Lugt, M., Veeramony, J., and Warner, J.C., 2022, Modeling morphodynamics of coastal response to extreme events: What shape are we in?: Annual Review of Marine Science, v. 14, p. 457-492, https://doi.org/10.1146/annurev-marine-032221-090215.","productDescription":"36 p.","startPage":"457","endPage":"492","ipdsId":"IP-126726","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":449771,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/29021","text":"External Repository"},{"id":387676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":820520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Dongeren, Ap","contributorId":149002,"corporation":false,"usgs":false,"family":"van Dongeren","given":"Ap","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":820521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doyle, James","contributorId":261741,"corporation":false,"usgs":false,"family":"Doyle","given":"James","affiliations":[{"id":52981,"text":"U.S. Naval Research Laboratory, Monterey, C","active":true,"usgs":false}],"preferred":false,"id":820522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hegermiller, Christie 0000-0002-6383-7508 chegermiller@usgs.gov","orcid":"https://orcid.org/0000-0002-6383-7508","contributorId":149010,"corporation":false,"usgs":true,"family":"Hegermiller","given":"Christie","email":"chegermiller@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":820523,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hsu, T. J.","contributorId":261742,"corporation":false,"usgs":false,"family":"Hsu","given":"T.","email":"","middleInitial":"J.","affiliations":[{"id":52981,"text":"U.S. Naval Research Laboratory, Monterey, C","active":true,"usgs":false}],"preferred":false,"id":820524,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":820544,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":211373,"corporation":false,"usgs":false,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":820526,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Penko, Allison","contributorId":191932,"corporation":false,"usgs":false,"family":"Penko","given":"Allison","affiliations":[],"preferred":false,"id":820527,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rafati, Yashar","contributorId":223049,"corporation":false,"usgs":false,"family":"Rafati","given":"Yashar","email":"","affiliations":[],"preferred":false,"id":820528,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Roelvink, Dano","contributorId":139950,"corporation":false,"usgs":false,"family":"Roelvink","given":"Dano","email":"","affiliations":[{"id":13328,"text":"UNESCO-IHE","active":true,"usgs":false}],"preferred":false,"id":820529,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"van der Lugt, Marlies","contributorId":221148,"corporation":false,"usgs":false,"family":"van der Lugt","given":"Marlies","email":"","affiliations":[{"id":40335,"text":"Detlares","active":true,"usgs":false}],"preferred":false,"id":820530,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Veeramony, Jay","contributorId":261743,"corporation":false,"usgs":false,"family":"Veeramony","given":"Jay","email":"","affiliations":[{"id":52984,"text":"U.S. Naval Research Laboratory, Stennis Space Center, MS","active":true,"usgs":false}],"preferred":false,"id":820531,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":258015,"corporation":false,"usgs":true,"family":"Warner","given":"John","email":"jcwarner@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":820532,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70222416,"text":"70222416 - 2022 - Taxonomic, temporal, and spatial variations in zooplankton fatty acid composition in Puget Sound, WA, USA","interactions":[],"lastModifiedDate":"2022-01-25T16:42:32.553137","indexId":"70222416","displayToPublicDate":"2021-07-26T07:16:15","publicationYear":"2022","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":"Taxonomic, temporal, and spatial variations in zooplankton fatty acid composition in Puget Sound, WA, USA","docAbstract":"

Fatty acid (FA) content and composition of zooplankton in Puget Sound, Washington (USA) was studied to investigate the nutritional quality of diverse zooplankton prey for juvenile salmon (Oncorhynchus spp.) in terms of their essential fatty acid (EFA) content. The study focus was on eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and arachidonic acid (ARA) as these are key FA needed to maintain growth and development of juvenile fish. The different zooplankton taxa varied in their FA composition. Much of the variation in FA composition was driven by 18:1ω9 (a biomarker of carnivory), ARA, DHA, and FA characteristic of diatoms, which are linked to zooplankton diet sources. Gammarid and hyperiid amphipods contained the highest amount of EFA, particularly the gammarid amphipod Cyphocaris challengeri, while shrimp and copepods had much lower EFA content. Crab larvae, which are important prey for juvenile salmon in Puget Sound, had intermediate EPA + DHA content and the lowest DHA/EPA ratio, and were rich in diatom biomarkers. Temporal and spatial trends in zooplankton lipids were less apparent than the taxonomic differences, although the EFA content increased from spring to summer in Cancridae zoeae and the amphipod C. challengeri. These results on taxon-specific EFA content provide baseline information on the nutritional quality of zooplankton that can be applied in food web models. Combining zooplankton fatty acid data (quality) with taxon-specific zooplankton biomass data (quantity) enables development of new, sensitive indicators of juvenile fish production to help assess recent declines in salmon production in the Pacific Northwest and predict future adult returns.

","language":"English","publisher":"Springer","doi":"10.1007/s12237-021-00973-8","usgsCitation":"Hiltunen, M., Strandberg, U., Brett, M.T., Winans, A.K., Beauchamp, D., Kotila, M., and Keister, J.E., 2022, Taxonomic, temporal, and spatial variations in zooplankton fatty acid composition in Puget Sound, WA, USA: Estuaries and Coasts, v. 45, p. 567-581, https://doi.org/10.1007/s12237-021-00973-8.","productDescription":"15 p.","startPage":"567","endPage":"581","ipdsId":"IP-112526","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":449772,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-021-00973-8","text":"Publisher Index Page"},{"id":387504,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.76074218749999,\n 46.89023157359399\n ],\n [\n -121.59667968749999,\n 46.89023157359399\n ],\n [\n -121.59667968749999,\n 48.8936153614802\n ],\n [\n -124.76074218749999,\n 48.8936153614802\n ],\n [\n -124.76074218749999,\n 46.89023157359399\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","noUsgsAuthors":false,"publicationDate":"2021-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Hiltunen, Minna","contributorId":261400,"corporation":false,"usgs":false,"family":"Hiltunen","given":"Minna","email":"","affiliations":[{"id":52842,"text":"Department of Environmental and Biological Sciences, University of Eastern Finland, Joensuu, Finland","active":true,"usgs":false}],"preferred":false,"id":819974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Strandberg, Ursula","contributorId":261401,"corporation":false,"usgs":false,"family":"Strandberg","given":"Ursula","email":"","affiliations":[{"id":52842,"text":"Department of Environmental and Biological Sciences, University of Eastern Finland, Joensuu, Finland","active":true,"usgs":false}],"preferred":false,"id":819975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brett, Michael T.","contributorId":261402,"corporation":false,"usgs":false,"family":"Brett","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":52844,"text":"Civil and Environmental Engineering, University of Washington, Seattle, USA","active":true,"usgs":false}],"preferred":false,"id":819976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winans, Amanda K.","contributorId":261403,"corporation":false,"usgs":false,"family":"Winans","given":"Amanda","email":"","middleInitial":"K.","affiliations":[{"id":52845,"text":"School of Oceanography, University of Washington, Seattle, USA","active":true,"usgs":false}],"preferred":false,"id":819977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819978,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kotila, Miika","contributorId":261404,"corporation":false,"usgs":false,"family":"Kotila","given":"Miika","email":"","affiliations":[{"id":52842,"text":"Department of Environmental and Biological Sciences, University of Eastern Finland, Joensuu, Finland","active":true,"usgs":false}],"preferred":false,"id":819979,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keister, Julie E.","contributorId":261405,"corporation":false,"usgs":false,"family":"Keister","given":"Julie","email":"","middleInitial":"E.","affiliations":[{"id":52845,"text":"School of Oceanography, University of Washington, Seattle, USA","active":true,"usgs":false}],"preferred":false,"id":819980,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224977,"text":"70224977 - 2022 - Quantifying the response of nitrogen speciation to hydrology in the Chesapeake Bay Watershed using a multilevel modeling approach","interactions":[],"lastModifiedDate":"2023-01-18T15:37:05.805872","indexId":"70224977","displayToPublicDate":"2021-07-26T07:16:06","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6465,"text":"Journal of American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the response of nitrogen speciation to hydrology in the Chesapeake Bay Watershed using a multilevel modeling approach","docAbstract":"

Excessive nitrogen (N) inputs to coastal waters can lead to severe eutrophication and different chemical forms of N exhibit varying levels of effectiveness in fueling primary production. Efforts to mitigate N fluxes from coastal watersheds are often guided by models that predict changes in N loads as a function of changes in land use, management practices, and climate. However, relatively little is known on the impacts of such changes on the relative fractions of different N forms. We leveraged a long-term dataset of N loads from over 100 river stations to investigate how the \"urn:x-wiley:1093474X:media:jawr12951:jawr12951-math-0001\" fraction, that is, the ratio of \"urn:x-wiley:1093474X:media:jawr12951:jawr12951-math-0002\" to total N (\"urn:x-wiley:1093474X:media:jawr12951:jawr12951-math-0003\"/TN), changes as a function of spatio-temporal changes in TN loads in the Chesapeake Bay watershed. We built a hierarchical model that separates the response of \"urn:x-wiley:1093474X:media:jawr12951:jawr12951-math-0004\" to changes in TN load occurring at different scales: Across river stations, where differences in TN loads are largely driven by spatial differences in anthropogenic inputs, and within stations, where inter-annual variability in hydrology is a key driver of changes in TN loads. Results suggest that while increases in TN loads resulting from changes in anthropogenic inputs lead to an increase in the \"urn:x-wiley:1093474X:media:jawr12951:jawr12951-math-0005\" fraction, a decrease in the \"urn:x-wiley:1093474X:media:jawr12951:jawr12951-math-0006\" fraction may occur when increases in TN loads are driven by increased streamflow. These results are especially relevant in watersheds that may experience changes in N loads due to both management decisions and climate-driven changes in hydrology.

","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12951","usgsCitation":"Bertani, I., Bhatt, G., Shenk, G.W., and Linker, L.C., 2022, Quantifying the response of nitrogen speciation to hydrology in the Chesapeake Bay Watershed using a multilevel modeling approach: Journal of American Water Resources Association, v. 58, no. 6, p. 792-804, https://doi.org/10.1111/1752-1688.12951.","productDescription":"13 p.","startPage":"792","endPage":"804","ipdsId":"IP-128081","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":390377,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.1904296875,\n 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0000-0001-6451-2513","orcid":"https://orcid.org/0000-0001-6451-2513","contributorId":225440,"corporation":false,"usgs":true,"family":"Shenk","given":"Gary","email":"","middleInitial":"W.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Linker, Lewis C. 0000-0002-3456-3659","orcid":"https://orcid.org/0000-0002-3456-3659","contributorId":252964,"corporation":false,"usgs":false,"family":"Linker","given":"Lewis","email":"","middleInitial":"C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":824994,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227801,"text":"70227801 - 2022 - High-resolution remote sensing and multistate occupancy estimation identify drivers of spawning site selection in fall chum salmon (Oncorhynchus keta) across a sub-Arctic riverscape","interactions":[],"lastModifiedDate":"2022-03-15T16:56:30.794133","indexId":"70227801","displayToPublicDate":"2021-07-23T15:54:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"High-resolution remote sensing and multistate occupancy estimation identify drivers of spawning site selection in fall chum salmon (Oncorhynchus keta) across a sub-Arctic riverscape","title":"High-resolution remote sensing and multistate occupancy estimation identify drivers of spawning site selection in fall chum salmon (Oncorhynchus keta) across a sub-Arctic riverscape","docAbstract":"

Groundwater upwellings provide warmer, stable overwinter temperatures for developing salmon embryos, which may be particularly important in cold, braided, gravel-bed sub-Arctic rivers. We used a three-year time series of aerial counts and remote sensing to estimate the distribution of low and high aggregations of spawning fall chum salmon (Oncorhynchus keta), classify approximately 0.5 km long river segments by geomorphic channel type, and map thermal variability along a 25.4 km stretch of the Teedriinjik River, Alaska. We used a dynamic multistate occupancy model to estimate detectability, occupancy, and the dynamics of spawning aggregations among river segments. Detectability was higher for large (>150) relative to smaller aggregations. Unoccupied segments were likely to remain so from year to year; low abundance spawning segments were dynamic and rarely remained in that state for multiple years, while ∼20%–35% of high abundance segments remained stable, indicating the presence of high-quality spawning habitat. Spawning habitat use was associated with warmer water temperatures likely caused by groundwater upwellings. We identified spawning habitat characteristics and trends in usage by fall chum salmon, which will inform land management decisions and assist in evaluating impacts of shifting climate conditions and resource management on Arctic salmon populations.

","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2021-0013","usgsCitation":"Clawson, C.M., Falke, J.A., Bailey, L.L., Rose, J., Prakash, A., and Martin, A.E., 2022, High-resolution remote sensing and multistate occupancy estimation identify drivers of spawning site selection in fall chum salmon (Oncorhynchus keta) across a sub-Arctic riverscape: Canadian Journal of Fisheries and Aquatic Sciences, v. 79, no. 3, p. 380-394, https://doi.org/10.1139/cjfas-2021-0013.","productDescription":"15 p.","startPage":"380","endPage":"394","ipdsId":"IP-092932","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395245,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Teedriinjik River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -147.28271484375,\n 66.98810916256633\n ],\n [\n -146.37908935546875,\n 66.98810916256633\n ],\n [\n -146.37908935546875,\n 67.11714654279567\n ],\n [\n -147.28271484375,\n 67.11714654279567\n ],\n [\n -147.28271484375,\n 66.98810916256633\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"79","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Clawson, Chelsea M.","contributorId":272841,"corporation":false,"usgs":false,"family":"Clawson","given":"Chelsea","email":"","middleInitial":"M.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":832330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832329,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bailey, Larissa L. 0000-0002-5959-2018","orcid":"https://orcid.org/0000-0002-5959-2018","contributorId":189578,"corporation":false,"usgs":false,"family":"Bailey","given":"Larissa","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":832331,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rose, Joshua","contributorId":273053,"corporation":false,"usgs":false,"family":"Rose","given":"Joshua","affiliations":[{"id":13228,"text":"U.S. Fish and Wildlife Service, Arctic National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":832535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Prakash, Anupma","contributorId":41101,"corporation":false,"usgs":true,"family":"Prakash","given":"Anupma","affiliations":[],"preferred":false,"id":832332,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Martin, Aaron E.","contributorId":200419,"corporation":false,"usgs":false,"family":"Martin","given":"Aaron","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":832333,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70226450,"text":"70226450 - 2022 - Late Quaternary deglaciation of Prince William Sound, Alaska","interactions":[],"lastModifiedDate":"2023-11-06T16:08:22.943696","indexId":"70226450","displayToPublicDate":"2021-07-23T06:31:17","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Late Quaternary deglaciation of Prince William Sound, Alaska","docAbstract":"

To understand the timing of deglaciation of the northernmost marine-terminating glaciers of the Cordilleran Ice Sheet (CIS), we obtained 26 10Be surface-exposure ages from glacially scoured bedrock surfaces in Prince William Sound (PWS), Alaska. We sampled six elevation transects between sea level and 620 m and spanning a distance of 14 to 70 km along ice flow paths. Most transect age–elevation patterns could not be explained by a simple model of thinning ice; the patterns provide evidence for lingering ice cover and possible inheritance. A reliable set of 20 ages ranges between 17.4 ± 2.0 and 11.6 ± 2.8 ka and indicates ice receded from northwestern PWS around 14.3 ± 1.6 ka, thinned at a rate of ~120–160 m/ka, and retreated from sea-level sites at 12.9 ± 1.1 ka at a rate of 20 m/yr. The retreat rate likely slowed as glaciers retreated into northern PWS. These results are consistent with the growing body of reported deglacial constraints on collapse of ice sheets along the Alaska margin indicating collapse of the CIS soon after 17 ka. These data are consistent with paleotemperature data indicating that a warming North Pacific Ocean caused catastrophic collapse of this part of the CIS.

","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2021.33","usgsCitation":"Haeussler, P., Matmon, A., Arnold, M., Aumaitre, G., Bourles, D., and Keddadouche, K., 2022, Late Quaternary deglaciation of Prince William Sound, Alaska: Quaternary Research, v. 105, p. 115-134, https://doi.org/10.1017/qua.2021.33.","productDescription":"20 p.","startPage":"115","endPage":"134","ipdsId":"IP-125952","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":449776,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/qua.2021.33","text":"Publisher Index Page"},{"id":391851,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149,\n 60\n ],\n [\n -147,\n 60\n ],\n [\n -147,\n 61.25\n ],\n [\n -149,\n 61.25\n ],\n [\n -149,\n 60\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","noUsgsAuthors":false,"publicationDate":"2021-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":826944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matmon, Ari","contributorId":196405,"corporation":false,"usgs":false,"family":"Matmon","given":"Ari","email":"","affiliations":[],"preferred":false,"id":826945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arnold, Maurice","contributorId":269392,"corporation":false,"usgs":false,"family":"Arnold","given":"Maurice","email":"","affiliations":[],"preferred":false,"id":827000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aumaitre, Georges","contributorId":269393,"corporation":false,"usgs":false,"family":"Aumaitre","given":"Georges","email":"","affiliations":[],"preferred":false,"id":827001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bourles, Didier","contributorId":269394,"corporation":false,"usgs":false,"family":"Bourles","given":"Didier","email":"","affiliations":[],"preferred":false,"id":827002,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keddadouche, Karim","contributorId":269395,"corporation":false,"usgs":false,"family":"Keddadouche","given":"Karim","email":"","affiliations":[],"preferred":false,"id":827003,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222585,"text":"70222585 - 2022 - Temporal and petrogenetic links between Mesoproterozoic alkaline and carbonatite magmas at Mountain Pass, California","interactions":[],"lastModifiedDate":"2021-11-26T17:49:19.982303","indexId":"70222585","displayToPublicDate":"2021-07-22T06:31:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Temporal and petrogenetic links between Mesoproterozoic alkaline and carbonatite magmas at Mountain Pass, California","docAbstract":"

Mountain Pass is the site of the most economically important rare earth element (REE) deposit in the United States. Mesoproterozoic alkaline intrusions are spatiotemporally associated with a composite carbonatite stock that hosts REE ore. Understanding the genesis of the alkaline and carbonatite magmas is an essential scientific goal for a society in which critical minerals are in high demand and will continue to be so for the foreseeable future. We present an ion microprobe study of zircon crystals in shonkinite and syenite intrusions to establish geochronological and geochemical constraints on the igneous underpinnings of the Mountain Pass REE deposit. Silicate whole-rock compositions occupy a broad spectrum (50–72 wt % SiO2), are ultrapotassic (6–9 wt % K2O; K2O/Na2O = 2–9), and have highly elevated concentrations of REEs (La 500–1,100× chondritic). Zircon concordia 206Pb/238U-207Pb/235U ages determined for shonkinite and syenite units are 1409 ± 8, 1409 ± 12, 1410 ± 8, and 1415 ± 6 Ma (2σ). Most shonkinite dikes are dominated by inherited Paleoproterozoic xenocrysts, but there are sparse primary zircons with 207Pb/206Pb ages of 1390–1380 ± 15 Ma for the youngest grains. Our new zircon U-Pb ages for shonkinite and syenite units overlap published monazite Th-Pb ages for the carbonatite orebody and a smaller carbonatite dike. Inherited zircons in shonkinite and syenite units are ubiquitous and have a multimodal distribution of 207Pb/206Pb ages that cluster in the range of 1785–1600 ± 10–30 Ma. Primary zircons have generally lower Hf (<11,000 ppm) and higher Eu/Eu* (>0.6), Th (>300 ppm), Th/U (>1), and Ti-in-zircon temperatures (>800°C) than inherited zircons. Oxygen isotope data reveals a large range in δ18O values for primary zircons, from mantle (5–5.5‰) to crustal and supracrustal (7–9‰). A couple of low-δ18O outliers (2‰) point to a component of shallow crust altered by meteoric water. The δ18O range of inherited zircons (5–10‰) overlaps that of the primary zircons. Our study supports a model in which alkaline and carbonatite magmatism occurred over tens of millions of years, repeatedly tapping a metasomatized mantle source, which endowed magmas with elevated REEs and other diagnostic components (e.g., F, Ba). Though this metasomatized mantle region existed for the duration of Mountain Pass magmatism, it probably did not predate magmatism by substantial geologic time (>100 m.y.), based on the similarity of 1500 Ma zircons with the dominantly 1800–1600 Ma inherited zircons, as opposed to the 1450–1350 Ma primary zircons. Mountain Pass magmas had diverse crustal inputs from assimilation of Paleoproterozoic and Mesoproterozoic igneous, metaigneous, and metasedimentary rocks. Crustal assimilation is only apparent from high spatial resolution zircon analyses and underscores the need for mineral-scale approaches in understanding the genesis of the Mountain Pass system.

","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.4848","usgsCitation":"Watts, K., Haxel, G.B., and Miller, D., 2022, Temporal and petrogenetic links between Mesoproterozoic alkaline and carbonatite magmas at Mountain Pass, California: Economic Geology, v. 117, no. 1, p. 1-23, https://doi.org/10.5382/econgeo.4848.","productDescription":"23 p.","startPage":"1","endPage":"23","ipdsId":"IP-123131","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":449779,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5382/econgeo.4848","text":"Publisher Index Page"},{"id":436062,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UE4HFE","text":"USGS data release","linkHelpText":"Geochemistry, geochronology, and isotope geochemistry data for rocks and zircons from Mountain Pass, California"},{"id":387730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"southeast California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.71874999999999,\n 34.813803317113155\n ],\n [\n -115.400390625,\n 34.813803317113155\n ],\n [\n -115.400390625,\n 36.527294814546245\n ],\n [\n -116.71874999999999,\n 36.527294814546245\n ],\n [\n -116.71874999999999,\n 34.813803317113155\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"117","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Watts, Kathryn E. 0000-0002-6110-7499","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":204344,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":820649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haxel, Gordon B. 0000-0002-6722-7803 gbhaxel@usgs.gov","orcid":"https://orcid.org/0000-0002-6722-7803","contributorId":261783,"corporation":false,"usgs":true,"family":"Haxel","given":"Gordon","email":"gbhaxel@usgs.gov","middleInitial":"B.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":820650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":140769,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":820651,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228671,"text":"70228671 - 2022 - Species-specific demographic and behavioral responses to food availability during migratory stopover","interactions":[],"lastModifiedDate":"2022-02-16T16:03:41.730784","indexId":"70228671","displayToPublicDate":"2021-07-18T09:55:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3103,"text":"Population Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Species-specific demographic and behavioral responses to food availability during migratory stopover","docAbstract":"

Understanding the effects of migratory stopover site conditions on both demographic rates and migratory behaviors is critical for interpreting changes in passage population sizes at stopover sites and predicting responses to future changes and conservation actions. We used a Bayesian formulation of the open robust design model to analyze mark-resight observations of three migratory shorebird species using Delaware Bay, USA during spring stopover from 2005 to 2018. We tested for an effect of stopover food availability and weather conditions on survival probability and the probability of returning to this site in the next year and found species differences in these relationships. After years with greater food availability, red knot Calidris canutus rufa had higher survival probability but ruddy turnstone Arenaria interpres were more likely to return to the site. Estimates of within-year probabilities of arrival and persistence at the stopover site showed relatively consistent migration schedules for ruddy turnstone, but more interannual variation for red knot and sanderling Calidris alba. Shorebird use of this site typically peaked during May 26–28, but the estimated proportion of the population present during this period varied dramatically among years for red knot (range: 0.07–0.59) but less so for ruddy turnstone and sanderling. This demonstrates that both the proportion of the flyway population using this stopover site and the proportion present during a given sampling period vary among years, and both should be considered in analyzing and interpreting monitoring data. Stopover conditions can influence both migratory behavior and demographics, underscoring the importance of flyway-wide monitoring.

","language":"English","publisher":"Ecological Society of Japan","doi":"10.1002/1438-390X.12094","usgsCitation":"Tucker, A.M., McGowan, C., Lyons, J.E., Derose-Wilson, A., and Clark, N., 2022, Species-specific demographic and behavioral responses to food availability during migratory stopover: Population Ecology, v. 64, no. 1, p. 19-34, https://doi.org/10.1002/1438-390X.12094.","productDescription":"16 p.","startPage":"19","endPage":"34","ipdsId":"IP-113655","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":396019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey","otherGeospatial":"Delaware Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.08331298828125,\n 38.700515838688716\n ],\n [\n -74.94049072265625,\n 38.9380483825641\n ],\n [\n -74.87457275390625,\n 39.193948213963665\n ],\n [\n -75.00091552734375,\n 39.234380580544276\n ],\n [\n -75.15472412109375,\n 39.20671884491848\n ],\n [\n -75.3826904296875,\n 39.39587712612034\n ],\n [\n -75.50079345703125,\n 39.48920467334085\n ],\n [\n -75.52276611328125,\n 39.607804249995105\n ],\n [\n -75.53924560546875,\n 39.69239407904182\n ],\n [\n -75.63812255859375,\n 39.620499321968104\n ],\n [\n -75.58319091796875,\n 39.552765371831015\n ],\n [\n -75.60791015625,\n 39.46588451142044\n ],\n [\n -75.42938232421875,\n 39.25990481501755\n ],\n [\n -75.43212890625,\n 39.08530414503412\n ],\n [\n -75.333251953125,\n 38.9914373369788\n ],\n [\n -75.31677246093749,\n 38.91240739487225\n ],\n [\n -75.16845703124999,\n 38.773357720269075\n ],\n [\n -75.08880615234375,\n 38.78406349514289\n ],\n [\n -75.08331298828125,\n 38.700515838688716\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"64","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Tucker, A. M.","contributorId":276002,"corporation":false,"usgs":false,"family":"Tucker","given":"A.","email":"","middleInitial":"M.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":834971,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":3381,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":834972,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":834973,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Derose-Wilson, A.","contributorId":243204,"corporation":false,"usgs":false,"family":"Derose-Wilson","given":"A.","email":"","affiliations":[{"id":36379,"text":"Delaware Division of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":834974,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, N.A.","contributorId":279481,"corporation":false,"usgs":false,"family":"Clark","given":"N.A.","affiliations":[{"id":38864,"text":"British Trust for Ornithology","active":true,"usgs":false}],"preferred":false,"id":834975,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254791,"text":"70254791 - 2022 - An integrated path for spatial capture–recapture and animal movement modeling","interactions":[],"lastModifiedDate":"2024-06-10T15:51:14.737168","indexId":"70254791","displayToPublicDate":"2021-07-16T10:45:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"An integrated path for spatial capture–recapture and animal movement modeling","docAbstract":"

Ecologists and conservation biologists increasingly rely on spatial capture–recapture (SCR) and movement modeling to study animal populations. Historically, SCR has focused on population-level processes (e.g., vital rates, abundance, density, and distribution), whereas animal movement modeling has focused on the behavior of individuals (e.g., activity budgets, resource selection, migration). Even though animal movement is clearly a driver of population-level patterns and dynamics, technical and conceptual developments to date have not forged a firm link between the two fields. Instead, movement modeling has typically focused on the individual level without providing a coherent scaling from individual- to population-level processes, whereas SCR has typically focused on the population level while greatly simplifying the movement processes that give rise to the observations underlying these models. In our view, the integration of SCR and animal movement modeling has tremendous potential for allowing ecologists to scale up from individuals to populations and advancing the types of inferences that can be made at the intersection of population, movement, and landscape ecology. Properly accounting for complex animal movement processes can also potentially reduce bias in estimators of population-level parameters, thereby improving inferences that are critical for species conservation and management. This introductory article to the Special Feature reviews recent advances in SCR and animal movement modeling, establishes a common notation, highlights potential advantages of linking individual-level (Lagrangian) movements to population-level (Eulerian) processes, and outlines a general conceptual framework for the integration of movement and SCR models. We then identify important avenues for future research, including key challenges and potential pitfalls in the developments and applications that lie ahead.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3473","usgsCitation":"McClintock, B., Abrahms, B., Chandler, R., Conn, P., Converse, S.J., Emmet, R., Gardner, B., Hostetter, N., and Johnson, D., 2022, An integrated path for spatial capture–recapture and animal movement modeling: Ecology, e03473, 21 p., https://doi.org/10.1002/ecy.3473.","productDescription":"e03473, 21 p.","ipdsId":"IP-124731","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449786,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.3473","text":"Publisher Index Page"},{"id":429768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"McClintock, Brett T.","contributorId":337619,"corporation":false,"usgs":false,"family":"McClintock","given":"Brett T.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":902580,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abrahms, Briana","contributorId":337620,"corporation":false,"usgs":false,"family":"Abrahms","given":"Briana","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":902581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chandler, Richard","contributorId":337621,"corporation":false,"usgs":false,"family":"Chandler","given":"Richard","affiliations":[{"id":24699,"text":"UGA","active":true,"usgs":false}],"preferred":false,"id":902582,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conn, Paul B.","contributorId":337622,"corporation":false,"usgs":false,"family":"Conn","given":"Paul B.","affiliations":[{"id":24699,"text":"UGA","active":true,"usgs":false}],"preferred":false,"id":902583,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":902579,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Emmet, Robbie","contributorId":337623,"corporation":false,"usgs":false,"family":"Emmet","given":"Robbie","email":"","affiliations":[{"id":40853,"text":"UE","active":true,"usgs":false}],"preferred":false,"id":902584,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gardner, Beth","contributorId":337624,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":902585,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hostetter, Nathan J.","contributorId":337625,"corporation":false,"usgs":false,"family":"Hostetter","given":"Nathan J.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":902586,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Johnson, Devin S.","contributorId":337626,"corporation":false,"usgs":false,"family":"Johnson","given":"Devin S.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":902587,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70221845,"text":"70221845 - 2022 - A Bayesian nonparametric approach to unmixing detrital geochronologic data","interactions":[],"lastModifiedDate":"2022-02-15T15:29:53.440463","indexId":"70221845","displayToPublicDate":"2021-07-08T06:58:11","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2701,"text":"Mathematical Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"A Bayesian nonparametric approach to unmixing detrital geochronologic data","docAbstract":"

Sedimentary deposits constitute the primary record of changing environmental conditions that have acted on Earth’s surface over geologic time. Clastic material is eroded from source locations (parents) in sediment routing systems and deposited at sink locations (children). Both parents and children have characteristics that vary across many different dimensions, including grain size, chemical composition, and the geochronologic age of constituent detrital minerals. During transport, sediment from different parents is mixed together to form a child, which in turn may serve as the parent for other sediment farther down-system or later in time when buried sediment is exhumed. The distribution of detrital mineral ages observed in parent and child sediments allows for investigation of the proportion of each parent in the child sediment, which reflects the properties of the sediment routing system. To model the proportion of dates in a child sample that comes from each of the parent distributions, we use a Bayesian mixture of Dirichlet processes. This model enables us to estimate the mixing proportions with associated uncertainty while making minimal assumptions. We also present an extension to the model whereby we reconstruct unobserved parent distributions from multiple observed child distributions using mixtures of Dirichlet processes. The model accounts for uncertainty in both the number of mineral formation events that constitute each parent distribution and the mixing proportions of each parent distribution that constitutes a child distribution. To demonstrate the model, we perform analyses using simulated data where the true age distribution is known as well as using a real-world case study from the coast of central California, USA.

","language":"English","publisher":"Springer","doi":"10.1007/s11004-021-09961-x","usgsCitation":"Tipton, J.R., Sharman, G.R., and Johnstone, S., 2022, A Bayesian nonparametric approach to unmixing detrital geochronologic data: Mathematical Geosciences, v. 54, p. 151-176, https://doi.org/10.1007/s11004-021-09961-x.","productDescription":"16 p.","startPage":"151","endPage":"176","ipdsId":"IP-117381","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":387071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","noUsgsAuthors":false,"publicationDate":"2021-07-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Tipton, John R. 0000-0002-6135-8191","orcid":"https://orcid.org/0000-0002-6135-8191","contributorId":260843,"corporation":false,"usgs":false,"family":"Tipton","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":818949,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sharman, Glenn R.","contributorId":196537,"corporation":false,"usgs":false,"family":"Sharman","given":"Glenn","email":"","middleInitial":"R.","affiliations":[{"id":34621,"text":"Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA","active":true,"usgs":false}],"preferred":false,"id":818950,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnstone, Samuel 0000-0002-3945-2499","orcid":"https://orcid.org/0000-0002-3945-2499","contributorId":207545,"corporation":false,"usgs":true,"family":"Johnstone","given":"Samuel","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":818951,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228759,"text":"70228759 - 2022 - Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non-forest ecosystems","interactions":[],"lastModifiedDate":"2022-02-18T15:07:23.972221","indexId":"70228759","displayToPublicDate":"2021-07-07T08:10:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5347,"text":"Remote Sensing in Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non-forest ecosystems","docAbstract":"

Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales. Here we developed and deployed a new protocol for photogrammetric height using unoccupied aerial vehicle (UAV) images to test its capability for delivering standardized measurements of biomass across a globally distributed field experiment. We assessed whether canopy height inferred from UAV photogrammetry allows the prediction of aboveground biomass (AGB) across low-stature plant species by conducting 38 photogrammetric surveys over 741 harvested plots to sample 50 species. We found mean canopy height was strongly predictive of AGB across species, with a median adjusted R2 of 0.87 (ranging from 0.46 to 0.99) and median prediction error from leave-one-out cross-validation of 3.9%. Biomass per-unit-of-height was similar within but different among, plant functional types. We found that photogrammetric reconstructions of canopy height were sensitive to wind speed but not sun elevation during surveys. We demonstrated that our photogrammetric approach produced generalizable measurements across growth forms and environmental settings and yielded accuracies as good as those obtained from in situ approaches. We demonstrate that using a standardized approach for UAV photogrammetry can deliver accurate AGB estimates across a wide range of dynamic and heterogeneous ecosystems. Many academic and land management institutions have the technical capacity to deploy these approaches over extents of 1–10 ha−1. Photogrammetric approaches could provide much-needed information required to calibrate and validate the vegetation models and satellite-derived biomass products that are essential to understand vulnerable and understudied non-forested ecosystems around the globe.

","language":"English","publisher":"Wiley","doi":"10.1002/rse2.228","usgsCitation":"Cunliffe, A., Anderson, K., Boschetti, F., Brazier, R.E., Graham, H.A., Myers-Smith, I.H., Astor, T., Boer, M.M., Calvo, L.G., Clark, P., Cramer, M.D., Encinas-Lara, M.S., Escarzaga, S.M., Fisher, A., Fernandez-Guisuraga, J.M., Gdulova, K., Gillespie, B.M., Griebel, A., Hanan, N.P., Hanggito, M.S., Haselberger, S., Havrilla, C.A., Heilman, P., Ji, W., Karl, J., Kraushaar, S., Mauritz, M., Lyons, M., Marzolff, I., McIntire, C.D., Metzen, D., Mendez-Barroso, L.A., Power, S.C., Prosek, J., Sanz-Ablanedo, E., Sauer, K.J., Schulze-Bruninghoff, D., Simova, P., Sitch, S., Smit, J.L., Steele, C.M., Suarez-Seoane, S., Vargas, S.A., Visser, F., Villarreal, M.L., Wachendorf, M., Wirnsberger, H., and Wojcikiewicz, R., 2022, Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non-forest ecosystems: Remote Sensing in Ecology and Conservation, v. 8, no. 1, p. 57-71, https://doi.org/10.1002/rse2.228.","productDescription":"15 p.","startPage":"57","endPage":"71","ipdsId":"IP-116952","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":449792,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.228","text":"Publisher Index Page"},{"id":396172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Cunliffe, Andrew 0000-0002-8346-4278","orcid":"https://orcid.org/0000-0002-8346-4278","contributorId":279669,"corporation":false,"usgs":false,"family":"Cunliffe","given":"Andrew","email":"","affiliations":[{"id":57332,"text":"Department of Geography, College of Life and Environmental Sciences, University of Exeter, Exeter","active":true,"usgs":false}],"preferred":false,"id":835335,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Karen","contributorId":279724,"corporation":false,"usgs":false,"family":"Anderson","given":"Karen","email":"","affiliations":[],"preferred":false,"id":835406,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boschetti, Fabio","contributorId":279725,"corporation":false,"usgs":false,"family":"Boschetti","given":"Fabio","email":"","affiliations":[],"preferred":false,"id":835407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brazier, Richard E.","contributorId":279726,"corporation":false,"usgs":false,"family":"Brazier","given":"Richard","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":835408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graham, Hugh 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2022 - Shrub influence on soil carbon and nitrogen in a semi-arid grassland is mediated by precipitation and largely insensitive to livestock grazing","interactions":[],"lastModifiedDate":"2022-02-15T15:33:21.112862","indexId":"70222374","displayToPublicDate":"2021-06-22T07:35:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":904,"text":"Arid Land Research and Management","active":true,"publicationSubtype":{"id":10}},"title":"Shrub influence on soil carbon and nitrogen in a semi-arid grassland is mediated by precipitation and largely insensitive to livestock grazing","docAbstract":"

Dryland (arid and semi-arid) ecosystems globally provide more than half of livestock production and store roughly one-third of soil organic carbon (SOC). Biogeochemical pools are changing due to shrub encroachment, livestock grazing, and climate change. We assessed how vegetation microsite, grazing, and precipitation interacted to affect SOC and total nitrogen (TN) at a site with long-term grazing manipulations and well-described patterns of shrub encroachment across elevation and mean annual precipitation (MAP) gradients. We analyzed SOC and TN in the context of vegetation cover at ungrazed locations within livestock exclosures, high-intensity grazing locations near water sources, and moderate-intensity grazing locations away from water. SOC was enhanced by MAP (p < 0.0001), but grazing intensity had little effect regardless of MAP (p = 0.12). Shrubs enhanced SOC (300–1279 g C m−2) and TN (27–122 g N m−2), except at high MAP where the contribution or stabilization of shrub inputs relative to grassland inputs was likely diminished. Cover of perennial herbaceous plants and litter were significant predictors of SOC (r2 = 0.63 and 0.34, respectively) and TN (r2 = 0.64 and 0.30, respectively). Our results suggest that continued shrub encroachment in drylands can increase SOC storage when grass production remains high, although this response may saturate with higher MAP. In contrast, grazing – at least at the intensities of our sites – has a lesser effect. These effects underscore the need to understand how future climate and grazing may interact to influence dryland biogeochemical cycling.

","language":"English","publisher":"Taylor and Francis","doi":"10.1080/15324982.2021.1952660","usgsCitation":"Throop, H.L., Munson, S.M., Hornslein, N., and McClaran, M., 2022, Shrub influence on soil carbon and nitrogen in a semi-arid grassland is mediated by precipitation and largely insensitive to livestock grazing: Arid Land Research and Management, v. 36, no. 1, p. 27-46, https://doi.org/10.1080/15324982.2021.1952660.","productDescription":"20 p.","startPage":"27","endPage":"46","ipdsId":"IP-126222","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":502623,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":387410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Throop, Heather L. 0000-0002-7963-4342","orcid":"https://orcid.org/0000-0002-7963-4342","contributorId":139051,"corporation":false,"usgs":false,"family":"Throop","given":"Heather","email":"","middleInitial":"L.","affiliations":[{"id":12633,"text":"Biology Department, New Mexico State University, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":819848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":819849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hornslein, Nicole","contributorId":261340,"corporation":false,"usgs":false,"family":"Hornslein","given":"Nicole","email":"","affiliations":[{"id":52828,"text":"School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, USA","active":true,"usgs":false}],"preferred":false,"id":819850,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McClaran, Mitchel P","contributorId":261341,"corporation":false,"usgs":false,"family":"McClaran","given":"Mitchel P","affiliations":[{"id":52829,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ 85721-0043, USA","active":true,"usgs":false}],"preferred":false,"id":819851,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}