Volcanic ash is a heterogeneous mineral dust that is typically composed of a mixture of amorphous (glass) and crystalline (mineral) fragments. It commonly contains an abundance of the crystalline silica (SiO2) polymorph cristobalite. Inhalation of crystalline silica can induce inflammation by stimulating the NLRP3 inflammasome, a cytosolic receptor complex that plays a critical role in driving inflammatory immune responses. Ingested material results in the assembly of NLRP3, ASC, and caspase-1 with subsequent secretion of the interleukin-1 family cytokine IL-1β. Previous toxicology work suggests that cristobalite-bearing volcanic ash is minimally reactive, calling into question the reactivity of volcanically derived crystalline silica, in general. In this study, we target the NLRP3 inflammasome as a crystalline silica responsive element to clarify volcanic cristobalite reactivity. We expose immortalized bone marrow-derived macrophages of genetically engineered mice and primary human peripheral blood mononuclear cells (PBMCs) to ash from the Soufrière Hills volcano as well as representative, pure-phase samples of its primary componentry (volcanic glass, feldspar, cristobalite) and measure NLRP3 inflammasome activation. We demonstrate that respirable Soufrière Hills volcanic ash induces the activation of caspase-1 with subsequent release of mature IL-1β in a NLRP3 inflammasome-dependent manner. Macrophages deficient in NLRP3 inflammasome components are incapable of secreting IL-1β in response to volcanic ash ingestion. Cellular uptake induces lysosomal destabilization involving cysteine proteases. Furthermore, the response involves activation of mitochondrial stress pathways leading to the generation of reactive oxygen species. Considering ash componentry, cristobalite is the most reactive pure-phase with other components inducing only low-level IL-1β secretion. Inflammasome activation mediated by inhaled ash and its potential relevance in chronic pulmonary disease was further evidenced in PBMC using the NLRP3 small-molecule inhibitor CP-456,773 (CRID3, MCC950). Our data indicate the functional activation of the NLRP3 inflammasome by volcanic ash in murine and human macrophages in vitro. Cristobalite is identified as the apparent driver, thereby contesting previous assertions that chemical and structural imperfections may be sufficient to abrogate the reactivity of volcanically derived cristobalite. This is a novel mechanism for the stimulation of a pro-inflammatory response by volcanic particulate and provides new insight regarding chronic exposure to environmentally occurring particles.
","language":"English","publisher":"Frontiers","doi":"10.3389/fimmu.2017.02000","usgsCitation":"Damby, D., Horwell, C.J., Baxter, P.J., Kueppers, U., Schnurr, M., Dingwell, D.B., and Duewell, P., 2018, Volcanic ash activates the NLRP3 inflammasome in murine and human macrophages: Frontiers in Immunology, v. 8, Article 2000; 11 p., https://doi.org/10.3389/fimmu.2017.02000.","productDescription":"Article 2000; 11 p.","ipdsId":"IP-085438","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469016,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fimmu.2017.02000","text":"Publisher Index Page"},{"id":351297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-22","publicationStatus":"PW","scienceBaseUri":"5a7c1e6fe4b00f54eb2292ac","contributors":{"authors":[{"text":"Damby, David 0000-0002-3238-3961 ddamby@usgs.gov","orcid":"https://orcid.org/0000-0002-3238-3961","contributorId":177453,"corporation":false,"usgs":true,"family":"Damby","given":"David","email":"ddamby@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":727071,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horwell, Claire J.","contributorId":177455,"corporation":false,"usgs":false,"family":"Horwell","given":"Claire","email":"","middleInitial":"J.","affiliations":[{"id":16770,"text":"Dept. Earth Sciences, Durham University, UK","active":true,"usgs":false}],"preferred":false,"id":727072,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baxter, Peter J.","contributorId":201839,"corporation":false,"usgs":false,"family":"Baxter","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":727073,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kueppers, Ulrich","contributorId":178534,"corporation":false,"usgs":false,"family":"Kueppers","given":"Ulrich","affiliations":[],"preferred":false,"id":727074,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schnurr, Max","contributorId":201840,"corporation":false,"usgs":false,"family":"Schnurr","given":"Max","email":"","affiliations":[{"id":36272,"text":"Klinikum der Universität München","active":true,"usgs":false}],"preferred":false,"id":727075,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dingwell, Donald B.","contributorId":201841,"corporation":false,"usgs":false,"family":"Dingwell","given":"Donald","email":"","middleInitial":"B.","affiliations":[{"id":36273,"text":"Ludwig-Maximilians-Universität (LMU) München","active":true,"usgs":false}],"preferred":false,"id":727076,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Duewell, Peter","contributorId":201842,"corporation":false,"usgs":false,"family":"Duewell","given":"Peter","email":"","affiliations":[{"id":36272,"text":"Klinikum der Universität München","active":true,"usgs":false}],"preferred":false,"id":727077,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70195108,"text":"70195108 - 2018 - Unraveling the dynamics of magmatic CO2 degassing at Mammoth Mountain, California","interactions":[],"lastModifiedDate":"2018-02-08T09:27:41","indexId":"70195108","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Unraveling the dynamics of magmatic CO2 degassing at Mammoth Mountain, California","title":"Unraveling the dynamics of magmatic CO2 degassing at Mammoth Mountain, California","docAbstract":"The accumulation of magmatic CO2 beneath low-permeability barriers may lead to the formation of CO2-rich gas reservoirs within volcanic systems. Such accumulation is often evidenced by high surface CO2 emissions that fluctuate over time. The temporal variability in surface degassing is believed in part to reflect a complex interplay between deep magmatic degassing and the permeability of degassing pathways. A better understanding of the dynamics of CO2 degassing is required to improve monitoring and hazards mitigation in these systems. Owing to the availability of long-term records of CO2 emissions rates and seismicity, Mammoth Mountain in California constitutes an ideal site towards such predictive understanding. Mammoth Mountain is characterized by intense soil CO2 degassing (up to ∼1000 t d−1) and tree kill areas that resulted from leakage of CO2 from a CO2-rich gas reservoir located in the upper ∼4 km. The release of CO2-rich fluids from deeper basaltic intrusions towards the reservoir induces seismicity and potentially reactivates faults connecting the reservoir to the surface. While this conceptual model is well-accepted, there is still a debate whether temporally variable surface CO2 fluxes directly reflect degassing of intrusions or variations in fault permeability. Here, we report the first large-scale numerical model of fluid and heat transport for Mammoth Mountain. We discuss processes (i) leading to the initial formation of the CO2-rich gas reservoir prior to the occurrence of high surface CO2 degassing rates and (ii) controlling current CO2 degassing at the surface. Although the modeling settings are site-specific, the key mechanisms discussed in this study are likely at play at other volcanic systems hosting CO2-rich gas reservoirs. In particular, our model results illustrate the role of convection in stripping a CO2-rich gas phase from a rising hydrothermal fluid and leading to an accumulation of a large mass of CO2 (∼107–108 t) in a shallow gas reservoir. Moreover, we show that both, short-lived (months to years) and long-lived (hundreds of years) events of magmatic fluid injection can lead to critical pressures within the reservoir and potentially trigger fault reactivation. Our sensitivity analysis suggests that observed temporal fluctuations in surface degassing are only indirectly controlled by variations in magmatic degassing and are mainly the result of temporally variable fault permeability. Finally, we suggest that long-term CO2 emission monitoring, seismic tomography and coupled thermal–hydraulic–mechanical modeling are important for CO2-related hazard mitigation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2017.12.038","usgsCitation":"Pfeiffer, L., Wanner, C., and Lewicki, J.L., 2018, Unraveling the dynamics of magmatic CO2 degassing at Mammoth Mountain, California: Earth and Planetary Science Letters, v. 484, p. 318-328, https://doi.org/10.1016/j.epsl.2017.12.038.","productDescription":"11 p.","startPage":"318","endPage":"328","ipdsId":"IP-089596","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":502607,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://boris.unibe.ch/108615/","text":"External Repository"},{"id":351302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mammoth Mountain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.0456199645996,\n 37.615387232289116\n ],\n [\n -119.01257514953612,\n 37.615387232289116\n ],\n [\n -119.01257514953612,\n 37.6343536596899\n ],\n [\n -119.0456199645996,\n 37.6343536596899\n ],\n [\n -119.0456199645996,\n 37.615387232289116\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"484","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7c1e6fe4b00f54eb2292b9","contributors":{"authors":[{"text":"Pfeiffer, Loic","contributorId":201801,"corporation":false,"usgs":false,"family":"Pfeiffer","given":"Loic","email":"","affiliations":[{"id":36253,"text":"CICESE","active":true,"usgs":false}],"preferred":false,"id":726985,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wanner, Christoph","contributorId":201802,"corporation":false,"usgs":false,"family":"Wanner","given":"Christoph","email":"","affiliations":[{"id":25430,"text":"University of Bern","active":true,"usgs":false}],"preferred":false,"id":726986,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":726984,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70195173,"text":"70195173 - 2018 - Uptake and distribution of organo-iodine in deep-sea corals","interactions":[],"lastModifiedDate":"2018-03-13T10:11:30","indexId":"70195173","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2263,"text":"Journal of Environmental Radioactivity","active":true,"publicationSubtype":{"id":10}},"title":"Uptake and distribution of organo-iodine in deep-sea corals","docAbstract":"Understanding iodine concentration, transport, and bioavailability is essential in evaluating iodine's impact to the environment and its effectiveness as an environmental biogeotracer. While iodine and its radionuclides have proven to be important tracers in geologic and biologic studies, little is known about transport of this element to the deep sea and subsequent uptake in deep-sea coral habitats. Results presented here on deep-sea black coral iodine speciation and iodine isotope variability provides key information on iodine behavior in natural and anthropogenic environments, and its geochemical pathway in the Gulf of Mexico. Organo-iodine is the dominant iodine species in the black corals, demonstrating that binding of iodine to organic matter plays an important role in the transport and transfer of iodine to the deep-sea corals. The identification of growth bands captured in high-resolution scanning electron images (SEM) with synchronous peaks in iodine variability suggest that riverine delivery of terrestrial-derived organo-iodine is the most plausible explanation to account for annual periodicity in the deep-sea coral geochemistry. Whereas previous studies have suggested the presence of annual growth rings in deep-sea corals, this present study provides a mechanism to explain the formation of annual growth bands. Furthermore, deep-sea coral ages based on iodine peak counts agree well with those ages derived from radiocarbon (14C) measurements. These results hold promise for developing chronologies independent of 14C dating, which is an essential component in constraining reservoir ages and using radiocarbon as a tracer of ocean circulation. Furthermore, the presence of enriched 129I/127I ratios during the most recent period of skeleton growth is linked to nuclear weapons testing during the 1960s. The sensitivity of the coral skeleton to record changes in surface water 129I composition provides further evidence that iodine composition and isotope variability captured in proteinaceous deep-sea corals is a promising geochronometer as well as an emerging tracer for continental material flux.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvrad.2018.01.003","usgsCitation":"Prouty, N.G., Roark, E.B., Mohon, L.M., and Chang, C., 2018, Uptake and distribution of organo-iodine in deep-sea corals: Journal of Environmental Radioactivity, v. 187, p. 122-132, https://doi.org/10.1016/j.jenvrad.2018.01.003.","productDescription":"11 p.","startPage":"122","endPage":"132","ipdsId":"IP-090588","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469021,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvrad.2018.01.003","text":"Publisher Index Page"},{"id":351529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.5,\n 28.5\n ],\n [\n -86,\n 28.5\n ],\n [\n -86,\n 29.75\n ],\n [\n -88.5,\n 29.75\n ],\n [\n -88.5,\n 28.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"187","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee731e4b0da30c1bfc1ae","contributors":{"authors":[{"text":"Prouty, Nancy G. 0000-0002-8922-0688 nprouty@usgs.gov","orcid":"https://orcid.org/0000-0002-8922-0688","contributorId":3350,"corporation":false,"usgs":true,"family":"Prouty","given":"Nancy","email":"nprouty@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":727297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roark, E. Brendan","contributorId":195726,"corporation":false,"usgs":false,"family":"Roark","given":"E.","email":"","middleInitial":"Brendan","affiliations":[],"preferred":false,"id":727298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mohon, Leslye M.","contributorId":201970,"corporation":false,"usgs":false,"family":"Mohon","given":"Leslye","email":"","middleInitial":"M.","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":728382,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chang, Ching-Chih","contributorId":178566,"corporation":false,"usgs":false,"family":"Chang","given":"Ching-Chih","email":"","affiliations":[],"preferred":false,"id":728383,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195101,"text":"70195101 - 2018 - Why large cells dominate estuarine phytoplankton","interactions":[],"lastModifiedDate":"2018-03-12T13:09:06","indexId":"70195101","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","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":"Why large cells dominate estuarine phytoplankton","docAbstract":"Surveys across the world oceans have shown that phytoplankton biomass and production are dominated by small cells (picoplankton) where nutrient concentrations are low, but large cells (microplankton) dominate when nutrient-rich deep water is mixed to the surface. I analyzed phytoplankton size structure in samples collected over 25 yr in San Francisco Bay, a nutrient-rich estuary. Biomass was dominated by large cells because their biomass selectively grew during blooms. Large-cell dominance appears to be a characteristic of ecosystems at the land–sea interface, and these places may therefore function as analogs to oceanic upwelling systems. Simulations with a size-structured NPZ model showed that runs of positive net growth rate persisted long enough for biomass of large, but not small, cells to accumulate. Model experiments showed that small cells would dominate in the absence of grazing, at lower nutrient concentrations, and at elevated (+5°C) temperatures. Underlying these results are two fundamental scaling laws: (1) large cells are grazed more slowly than small cells, and (2) grazing rate increases with temperature faster than growth rate. The model experiments suggest testable hypotheses about phytoplankton size structure at the land–sea interface: (1) anthropogenic nutrient enrichment increases cell size; (2) this response varies with temperature and only occurs at mid-high latitudes; (3) large-cell blooms can only develop when temperature is below a critical value, around 15°C; (4) cell size diminishes along temperature gradients from high to low latitudes; and (5) large-cell blooms will diminish or disappear where planetary warming increases temperature beyond their critical threshold.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.10749","usgsCitation":"Cloern, J.E., 2018, Why large cells dominate estuarine phytoplankton: Limnology and Oceanography, v. 63, no. S1, p. S392-S409, https://doi.org/10.1002/lno.10749.","productDescription":"18 p.","startPage":"S392","endPage":"S409","ipdsId":"IP-090756","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":469025,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10749","text":"Publisher Index Page"},{"id":438020,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74F1P6P","text":"USGS data release","linkHelpText":"Phytoplankton Species Composition, Abundance and Cell Size in San Francisco Bay: Microscopic Analyses of USGS Samples Collected 1992-2014"},{"id":351310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"S1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-30","publicationStatus":"PW","scienceBaseUri":"5a7c1e71e4b00f54eb2292ca","contributors":{"authors":[{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":726930,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70195200,"text":"70195200 - 2018 - Molecular testing of adult Pacific salmon and trout (Oncorhynchus spp.) for several RNA viruses demonstrates widespread distribution of piscine orthoreovirus in Alaska and Washington","interactions":[],"lastModifiedDate":"2018-02-07T12:44:31","indexId":"70195200","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2286,"text":"Journal of Fish Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Molecular testing of adult Pacific salmon and trout (Oncorhynchus spp.) for several RNA viruses demonstrates widespread distribution of piscine orthoreovirus in Alaska and Washington","title":"Molecular testing of adult Pacific salmon and trout (Oncorhynchus spp.) for several RNA viruses demonstrates widespread distribution of piscine orthoreovirus in Alaska and Washington","docAbstract":"This research was initiated in conjunction with a systematic, multiagency surveillance effort in the United States (U.S.) in response to reported findings of infectious salmon anaemia virus (ISAV) RNA in British Columbia, Canada. In the systematic surveillance study reported in a companion paper, tissues from various salmonids taken from Washington and Alaska were surveyed for ISAV RNA using the U.S.-approved diagnostic method, and samples were released for use in this present study only after testing negative. Here, we tested a subset of these samples for ISAV RNA with three additional published molecular assays, as well as for RNA from salmonid alphavirus (SAV), piscine myocarditis virus (PMCV) and piscine orthoreovirus (PRV). All samples (n = 2,252; 121 stock cohorts) tested negative for RNA from ISAV, PMCV, and SAV. In contrast, there were 25 stock cohorts from Washington and Alaska that had one or more individuals test positive for PRV RNA; prevalence within stocks varied and ranged from 2% to 73%. The overall prevalence of PRV RNA-positive individuals across the study was 3.4% (77 of 2,252 fish tested). Findings of PRV RNA were most common in coho (Oncorhynchus kisutch Walbaum) and Chinook (O. tshawytscha Walbaum) salmon.
","language":"English","publisher":"Wiley","doi":"10.1111/jfd.12740","usgsCitation":"Purcell, M.K., Thompson, R.L., Evered, J., Kerwin, J., Meyers, T.R., Stewart, B., and Winton, J., 2018, Molecular testing of adult Pacific salmon and trout (Oncorhynchus spp.) for several RNA viruses demonstrates widespread distribution of piscine orthoreovirus in Alaska and Washington: Journal of Fish Diseases, v. 41, no. 2, p. 347-355, https://doi.org/10.1111/jfd.12740.","productDescription":"13 p.","startPage":"347","endPage":"355","ipdsId":"IP-082523","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":469011,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jfd.12740","text":"Publisher Index Page"},{"id":438019,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VX0F1H","text":"USGS data release","linkHelpText":"Final Dataset: Molecular testing of adult Pacific salmon and trout (Oncorhynchus spp.) for several RNA viruses demonstrates widespread distribution of piscine orthoreovirus (PRV) in Alaska and Washington"},{"id":351241,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Washington","volume":"41","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-21","publicationStatus":"PW","scienceBaseUri":"5a7c1e6be4b00f54eb229282","contributors":{"authors":[{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":727405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Rachel L. 0000-0001-6901-4361 rlthompson@usgs.gov","orcid":"https://orcid.org/0000-0001-6901-4361","contributorId":5707,"corporation":false,"usgs":true,"family":"Thompson","given":"Rachel","email":"rlthompson@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":727406,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evered, Joy","contributorId":127579,"corporation":false,"usgs":false,"family":"Evered","given":"Joy","affiliations":[{"id":7061,"text":"U.S. FWS, DOI","active":true,"usgs":false}],"preferred":false,"id":727407,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kerwin, John","contributorId":127577,"corporation":false,"usgs":false,"family":"Kerwin","given":"John","email":"","affiliations":[{"id":7060,"text":"Washington State Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":727408,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meyers, Ted R.","contributorId":202026,"corporation":false,"usgs":false,"family":"Meyers","given":"Ted","email":"","middleInitial":"R.","affiliations":[{"id":36327,"text":"Alaska Department of Fish and Game, Division of Commercial Fisheries, 1255 W. 8th Street Juneau, AK 99802, USA","active":true,"usgs":false}],"preferred":false,"id":727409,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stewart, Bruce","contributorId":127576,"corporation":false,"usgs":false,"family":"Stewart","given":"Bruce","email":"","affiliations":[{"id":7059,"text":"Northwest Indian Fisheries Commission","active":true,"usgs":false}],"preferred":false,"id":727410,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Winton, James 0000-0002-3505-5509 jwinton@usgs.gov","orcid":"https://orcid.org/0000-0002-3505-5509","contributorId":179330,"corporation":false,"usgs":true,"family":"Winton","given":"James","email":"jwinton@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":727411,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70194701,"text":"sir20175151 - 2018 - Assessment of water resources and the potential effects from oil and gas development in the Bureau of Land Management Tri-County planning area, Sierra, Doña Ana, and Otero Counties, New Mexico","interactions":[],"lastModifiedDate":"2018-02-07T17:11:00","indexId":"sir20175151","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5151","title":"Assessment of water resources and the potential effects from oil and gas development in the Bureau of Land Management Tri-County planning area, Sierra, Doña Ana, and Otero Counties, New Mexico","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the Bureau of Land Management, conducted a study to assess the water resources and potential effects on the water resources from oil and gas development in the Tri-County planning area, Sierra, Doña Ana, and Otero Counties, New Mexico. Publicly available data were used to assess these resources and effects and to identify data gaps in the Tri-County planning area.
The Tri-County planning area includes approximately 9.3 million acres and is within the eastern extent of the Basin and Range Province, which consists of mountain ranges and low elevation basins. Three specific areas of interest within the Tri-County planning area are the Jornada del Muerto, Tularosa Basin, and Otero Mesa, which is adjacent to the Salt Basin. Surface-water resources are limited in the Tri-County planning area, with the Rio Grande as the main perennial river flowing from north to south through Sierra and Doña Ana Counties. The Tularosa Creek is an important surface-water resource in the Tularosa Basin. The Sacramento River, which flows southeast out of the Sacramento Mountains, is an important source of recharge to aquifers in the Salt Basin. Groundwater resources vary in aquifer type, depth to water, and water quality. For example, the Jornada del Muerto, Tularosa Basin, and Salt Basin each have shallow and deep aquifer systems, and water can range from freshwater, with less than 1,000 milligrams per liter (mg/L) of total dissolved solids, to brine, with greater than 35,000 mg/L of total dissolved solids. Water quality in the Tri-County planning area is affected by the dissolution of salt deposits and evaporation which are common in arid regions such as southern New Mexico.
The potential for oil and gas development exists in several areas within the Tri-County area. As many as 81 new conventional wells and 25 coalbed natural gas wells could be developed by 2035. Conventional oil and gas well construction in the Tri-County planning area is expected to require 1.53 acre-feet (acre-ft) (500,000 gallons) of water per well, similar to requirements in the nearby Permian Basin of New Mexico, while construction of unconventional wells is expected to require 7.3 acre-ft of water per well. Produced waters in the Permian Basin have high total dissolved solids, in the brackish to brine range.
Data gaps identified in this study include the limited detailed data on surface-water resources, the lack of groundwater data in areas of interest, and the lack of water chemistry data related to oil and gas development issues. Surface waters in the Tri-County planning area are sparse; some streams are perennial, and most are ephemeral. A more detailed study of the ephemeral channels and their interaction with groundwater could provide a better understanding of the importance of these surface-water resources. Groundwater data used in this study are from the USGS National Water Information System, which does not have continuous water-level depth data at many of the sites in the Tri-County planning area. On Otero Mesa, no recurrent groundwater-level data are available at any one site. The water-quality data compiled in this study provide a good overview of the general chemistry of groundwater in the Tri-County planning area. To fully understand the groundwater resources, it would be helpful to have more wells in specific areas of interest for groundwater-level and water-quality measurements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175151","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Blake, J.M., Miltenberger, Keely, Stewart, Anne, Ritchie, Andre, Montoya, Jennifer, Durr, Corey, McHugh, Amy, and Charles, Emmanuel, 2018, Assessment of water resources and the potential effects from oil and gas development in the Bureau of Land Management Tri-County planning area, Sierra, Doña Ana, and Otero Counties, New Mexico: U.S. Geological Survey Scientific Investigations Report 2017–5151, 87 p., https://doi.org/10.3133/sir20175151. ","productDescription":"Report: x, 87 p.; Data Release","numberOfPages":"102","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085998","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":351050,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5151/coverthb.jpg"},{"id":351051,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5151/sir20175151.pdf","text":"Report","size":"12.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5151"},{"id":351052,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DR2T0M","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geodatabase supporting the assessment of hydrologic resources and the potential effects from oil and gas development in the Bureau of Land Management Tri-County Planning Area, Sierra, Doña Ana, and Otero Counties, New Mexico"}],"country":"United States","state":"New Mexico","county":"Doña Ana County, Otero County, Sierra County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-106.3733,32.0017],[-106.4575,32.0014],[-106.4743,32.0014],[-106.491,32.0013],[-106.5407,32.0011],[-106.558,32.001],[-106.576,32.001],[-106.6193,32.0012],[-106.619,31.998],[-106.6216,31.996],[-106.6266,31.9951],[-106.6306,31.9937],[-106.633,31.9915],[-106.6362,31.9878],[-106.6364,31.9873],[-106.6384,31.9832],[-106.6389,31.9791],[-106.6367,31.9764],[-106.6329,31.9755],[-106.6291,31.9755],[-106.6248,31.9757],[-106.6209,31.975],[-106.6183,31.9738],[-106.6175,31.9725],[-106.6177,31.9688],[-106.6196,31.966],[-106.622,31.9651],[-106.6247,31.9632],[-106.6268,31.961],[-106.6276,31.9577],[-106.6263,31.9555],[-106.6241,31.9547],[-106.6214,31.9549],[-106.6183,31.9564],[-106.6156,31.9566],[-106.6144,31.9544],[-106.6143,31.9535],[-106.6158,31.9516],[-106.6172,31.9501],[-106.6197,31.9468],[-106.6213,31.9436],[-106.6218,31.94],[-106.6225,31.9356],[-106.6229,31.9333],[-106.6244,31.9319],[-106.6264,31.9304],[-106.6287,31.929],[-106.6304,31.9272],[-106.6298,31.9251],[-106.6282,31.9244],[-106.6249,31.925],[-106.6211,31.9247],[-106.6185,31.9245],[-106.6168,31.9236],[-106.6149,31.9219],[-106.6147,31.9196],[-106.6162,31.9182],[-106.6188,31.9166],[-106.6222,31.9154],[-106.6257,31.9149],[-106.6297,31.9135],[-106.633,31.9121],[-106.6382,31.9091],[-106.6427,31.9047],[-106.6442,31.902],[-106.6458,31.8988],[-106.6452,31.8965],[-106.6431,31.8943],[-106.6393,31.892],[-106.6378,31.8908],[-106.6336,31.8865],[-106.6316,31.8829],[-106.6309,31.8798],[-106.6322,31.8761],[-106.6342,31.8729],[-106.6357,31.8701],[-106.636,31.8694],[-106.6342,31.8673],[-106.6309,31.8633],[-106.6177,31.8509],[-106.6103,31.8452],[-106.6064,31.8451],[-106.6032,31.8453],[-106.6009,31.8441],[-106.6007,31.8409],[-106.6011,31.8384],[-106.6016,31.8343],[-106.6016,31.8302],[-106.6013,31.8285],[-106.5994,31.8254],[-106.5961,31.8247],[-106.5934,31.8253],[-106.5907,31.8244],[-106.589,31.8238],[-106.587,31.8221],[-106.5844,31.8204],[-106.5803,31.816],[-106.5772,31.8116],[-106.5739,31.8109],[-106.5706,31.8102],[-106.5675,31.8107],[-106.5642,31.8115],[-106.5618,31.8119],[-106.5605,31.8121],[-106.5597,31.8122],[-106.5545,31.8122],[-106.5508,31.8118],[-106.544,31.8081],[-106.5416,31.8063],[-106.5394,31.8047],[-106.5363,31.8003],[-106.5334,31.7963],[-106.531,31.7947],[-106.5287,31.793],[-106.5275,31.7918],[-106.5264,31.79],[-106.5264,31.7886],[-106.5274,31.7868],[-106.529,31.7845],[-106.7472,31.7842],[-106.7833,31.7841],[-106.8119,31.7841],[-106.9691,31.784],[-107.001,31.784],[-107.1378,31.7841],[-107.1545,31.7844],[-107.2402,31.7843],[-107.2569,31.7842],[-107.2903,31.7842],[-107.2942,31.8225],[-107.2944,31.838],[-107.2942,31.9247],[-107.2944,31.9393],[-107.2943,31.9958],[-107.2945,32.0113],[-107.2957,32.0528],[-107.2962,32.0829],[-107.2959,32.0975],[-107.2965,32.1709],[-107.2962,32.1859],[-107.297,32.1996],[-107.2967,32.2142],[-107.2964,32.2292],[-107.2969,32.257],[-107.2967,32.2798],[-107.2969,32.2939],[-107.2966,32.3076],[-107.2966,32.345],[-107.2964,32.3605],[-107.296,32.3732],[-107.2959,32.4334],[-107.2956,32.4475],[-107.2965,32.504],[-107.297,32.5336],[-107.2967,32.5486],[-107.2972,32.5764],[-107.2974,32.5901],[-107.2977,32.6074],[-107.314,32.6072],[-107.3314,32.607],[-107.3477,32.6068],[-107.3815,32.6064],[-107.3989,32.6057],[-107.4163,32.606],[-107.4669,32.6067],[-107.4838,32.6065],[-107.5002,32.6067],[-107.5856,32.606],[-107.6052,32.6058],[-107.609,32.6057],[-107.6281,32.6059],[-107.645,32.6061],[-107.6646,32.6067],[-107.6712,32.6103],[-107.6909,32.6168],[-107.7063,32.622],[-107.7096,32.6234],[-107.7113,32.6261],[-107.7141,32.6338],[-107.7199,32.6473],[-107.7266,32.6573],[-107.723,32.6651],[-107.7226,32.671],[-107.7226,32.6742],[-107.7244,32.6796],[-107.7261,32.6841],[-107.7257,32.6896],[-107.7215,32.6961],[-107.7183,32.6984],[-107.7189,32.7011],[-107.7173,32.7048],[-107.7179,32.7084],[-107.7191,32.712],[-107.717,32.7157],[-107.7138,32.7208],[-107.7152,32.7353],[-107.7177,32.7462],[-107.7168,32.7553],[-107.7168,32.7581],[-107.7142,32.7608],[-107.7148,32.7636],[-107.7165,32.7686],[-107.7182,32.7731],[-107.72,32.7794],[-107.7322,32.7861],[-107.7378,32.7965],[-107.7446,32.8046],[-107.7459,32.8145],[-107.7417,32.821],[-107.7429,32.8255],[-107.7473,32.8296],[-107.7509,32.8432],[-107.7587,32.849],[-107.7658,32.8511],[-107.7703,32.8552],[-107.7715,32.8629],[-107.7728,32.8711],[-107.7741,32.8783],[-107.7753,32.8865],[-107.7749,32.8933],[-107.7708,32.9025],[-107.7655,32.9103],[-107.7634,32.9163],[-107.7657,32.9217],[-107.7703,32.9285],[-107.7719,32.9307],[-107.7683,32.9403],[-107.7707,32.9494],[-107.774,32.9512],[-107.7768,32.9511],[-107.7811,32.9497],[-107.7854,32.9474],[-107.7898,32.9487],[-107.7926,32.9509],[-107.7938,32.9527],[-107.7966,32.9563],[-107.7988,32.9581],[-107.8054,32.958],[-107.8086,32.9575],[-107.8136,32.9588],[-107.8152,32.9587],[-107.8175,32.961],[-107.8191,32.9623],[-107.8208,32.9632],[-107.8247,32.9672],[-107.827,32.9704],[-107.8287,32.9726],[-107.8298,32.974],[-107.8315,32.9762],[-107.8327,32.9799],[-107.8333,32.9826],[-107.835,32.9844],[-107.8367,32.9875],[-107.8395,32.9893],[-107.8406,32.9907],[-107.8467,32.9947],[-107.8489,32.9951],[-107.8495,32.9996],[-107.8453,33.0047],[-107.8443,33.0097],[-107.8444,33.0138],[-107.845,33.0179],[-107.8468,33.0242],[-107.8514,33.0319],[-107.852,33.0328],[-107.8537,33.0382],[-107.8489,33.0433],[-107.8496,33.0506],[-107.8459,33.0557],[-107.8422,33.0598],[-107.8374,33.0649],[-107.8342,33.0691],[-107.8326,33.0723],[-107.8322,33.0773],[-107.8345,33.0813],[-107.8389,33.0831],[-107.8434,33.0858],[-107.8429,33.0899],[-107.8408,33.0954],[-107.8414,33.0981],[-107.8426,33.0999],[-107.8442,33.1012],[-107.8454,33.1039],[-107.8455,33.1076],[-107.8462,33.1121],[-107.8473,33.1153],[-107.8474,33.1185],[-107.8485,33.1203],[-107.847,33.1235],[-107.846,33.1281],[-107.8444,33.1322],[-107.8494,33.1348],[-107.8506,33.1366],[-107.8523,33.1425],[-107.8519,33.1475],[-107.8541,33.1493],[-107.8526,33.1543],[-107.8527,33.1584],[-107.8544,33.1602],[-107.855,33.1643],[-107.8508,33.1689],[-107.8421,33.1713],[-107.8378,33.176],[-107.8385,33.1855],[-107.8446,33.1881],[-107.8518,33.1912],[-107.8579,33.1925],[-107.857,33.1993],[-107.8642,33.2038],[-108.0003,33.2042],[-107.9974,33.3289],[-107.9962,33.3927],[-107.9968,33.48],[-107.9181,33.4791],[-107.8113,33.4795],[-107.7304,33.4784],[-107.7116,33.4774],[-107.6748,33.4774],[-107.6401,33.4775],[-107.6236,33.4773],[-107.6038,33.4775],[-107.5036,33.478],[-107.4898,33.4777],[-107.4491,33.4787],[-107.3946,33.4789],[-107.3021,33.4777],[-107.2603,33.4782],[-107.2256,33.4785],[-107.2091,33.4792],[-107.191,33.4794],[-107.1739,33.4791],[-107.1569,33.4793],[-107.1409,33.4794],[-107.1255,33.4796],[-107.1073,33.4788],[-106.9999,33.4757],[-106.8833,33.4771],[-106.831,33.4771],[-106.8145,33.4772],[-106.7974,33.4773],[-106.7809,33.4774],[-106.7617,33.4771],[-106.7441,33.4772],[-106.4684,33.4782],[-106.4684,33.4828],[-106.3693,33.4813],[-106.3683,33.3908],[-106.3403,33.3913],[-106.1028,33.3918],[-106.0935,33.3923],[-106.0676,33.3923],[-106.0594,33.3923],[-106.0495,33.3923],[-106.0418,33.3923],[-106.0313,33.3923],[-106.0143,33.3923],[-105.9978,33.3923],[-105.9879,33.3927],[-105.9285,33.3927],[-105.8774,33.3918],[-105.8411,33.3922],[-105.7218,33.3924],[-105.7221,33.3069],[-105.5179,33.308],[-105.4157,33.3075],[-105.3125,33.3065],[-105.314,33.1323],[-105.3136,33.0485],[-105.3142,33.0044],[-105.3143,32.9629],[-105.3512,32.9628],[-105.3514,32.9276],[-105.3536,32.5218],[-105.3165,32.5221],[-105.2997,32.522],[-105.2828,32.5219],[-105.266,32.5218],[-105.2497,32.5217],[-105.2301,32.5216],[-105.2138,32.5219],[-105.1801,32.5217],[-105.1627,32.5215],[-105.1436,32.5214],[-105.1441,32.5241],[-105.1376,32.5241],[-105.0083,32.5208],[-104.9767,32.5205],[-104.9593,32.5203],[-104.9436,32.5202],[-104.9403,32.5201],[-104.9338,32.5201],[-104.924,32.52],[-104.9164,32.5199],[-104.9071,32.5194],[-104.8658,32.519],[-104.8566,32.5189],[-104.849,32.5188],[-104.8491,32.5124],[-104.8495,32.4427],[-104.8492,32.4286],[-104.8496,32.399],[-104.8493,32.3839],[-104.8495,32.2554],[-104.8457,32.2554],[-104.8461,32.1533],[-104.8463,32.1378],[-104.8462,32.1104],[-104.8464,32.0958],[-104.8466,32.0031],[-104.8612,32.003],[-104.9115,32.0029],[-104.9201,32.0029],[-104.9282,32.0029],[-104.9449,32.0029],[-104.9606,32.003],[-105.0114,32.0026],[-105.0276,32.0028],[-105.0439,32.0029],[-105.0601,32.0027],[-105.0775,32.0028],[-105.1445,32.0025],[-105.1521,32.0025],[-105.1643,32.0024],[-105.1853,32.0022],[-105.2145,32.002],[-105.2486,32.0017],[-105.2534,32.0017],[-105.2619,32.0017],[-105.3015,32.002],[-105.3177,32.0021],[-105.335,32.0023],[-105.3528,32.0019],[-105.3701,32.002],[-105.4204,32.0023],[-105.4372,32.0024],[-105.454,32.0021],[-105.4713,32.0021],[-105.5216,32.0024],[-105.572,32.0022],[-105.6219,32.0022],[-105.6391,32.0022],[-105.6467,32.0018],[-105.6662,32.0019],[-105.7169,32.002],[-105.7337,32.002],[-105.7548,32.0016],[-105.7738,32.0016],[-105.7953,32.0017],[-105.8228,32.0018],[-105.8393,32.0019],[-105.8622,32.0019],[-105.879,32.0019],[-105.9281,32.0019],[-105.9444,32.0019],[-105.9978,32.002],[-106.0439,32.002],[-106.1662,32.0023],[-106.2214,32.0021],[-106.314,32.0018],[-106.3733,32.0017]]]},\"properties\":{\"name\":\"Dona Ana\",\"state\":\"NM\"}}]}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montgomery Blvd., NE Suite 400
Albuquerque, NM 87109–1311
Consideration of ecological scale is fundamental to understanding and managing avian population growth and decline. Empirically driven models for population dynamics and demographic processes across multiple spatial scales can be powerful tools to help guide conservation actions. Integrated population models (IPMs) provide a framework for better parameter estimation by unifying multiple sources of data (e.g., count and demographic data). Hierarchical structure within such models that include random effects allow for varying degrees of data sharing across different spatiotemporal scales. We developed an IPM to investigate Greater Sage-Grouse (Centrocercus urophasianus) on the border of California and Nevada, known as the Bi-State Distinct Population Segment. Our analysis integrated 13 years of lek count data (n > 2,000) and intensive telemetry (VHF and GPS; n > 350 individuals) data across 6 subpopulations. Specifically, we identified the most parsimonious models among varying random effects and density-dependent terms for each population vital rate (e.g., nest survival). Using a joint likelihood process, we integrated the lek count data with the demographic models to estimate apparent abundance and refine vital rate parameter estimates. To investigate effects of climatic conditions, we extended the model to fit a precipitation covariate for instantaneous rate of change (r). At a metapopulation extent (i.e. Bi-State), annual population rate of change λ (er) did not favor an overall increasing or decreasing trend through the time series. However, annual changes in λ were driven by changes in precipitation (one-year lag effect). At subpopulation extents, we identified substantial variation in λ and demographic rates. One subpopulation clearly decoupled from the trend at the metapopulation extent and exhibited relatively high risk of extinction as a result of low egg fertility. These findings can inform localized, targeted management actions for specific areas, and status of the species for the larger Bi-State.
","language":"English","publisher":"American Ornithological Society","doi":"10.1642/AUK-17-137.1","usgsCitation":"Coates, P.S., Prochazka, B., Ricca, M.A., Halstead, B., Casazza, M.L., Blomberg, E.J., Brussee, B.E., Wiechman, L., Tebbenkamp, J., Gardner, S.C., and Reese, K.P., 2018, The relative importance of intrinsic and extrinsic drivers to population growth vary among local populations of Greater Sage-Grouse: An integrated population modeling approach: The Auk, v. 135, no. 2, p. 240-261, https://doi.org/10.1642/AUK-17-137.1.","productDescription":"22 p.","startPage":"240","endPage":"261","ipdsId":"IP-090891","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":469019,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.1642/AUK-17-137.1","text":"External Repository"},{"id":353689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"135","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee731e4b0da30c1bfc1ac","contributors":{"authors":[{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":733981,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prochazka, Brian G. bprochazka@usgs.gov","contributorId":147020,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian G.","email":"bprochazka@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":733982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ricca, Mark A. mark_ricca@usgs.gov","contributorId":2400,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":733983,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":733984,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":733985,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blomberg, Erik J.","contributorId":17543,"corporation":false,"usgs":false,"family":"Blomberg","given":"Erik","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":733986,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brussee, Brianne E. 0000-0002-2452-7101 bbrussee@usgs.gov","orcid":"https://orcid.org/0000-0002-2452-7101","contributorId":4249,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","email":"bbrussee@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":733987,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wiechman, Lief","contributorId":108039,"corporation":false,"usgs":true,"family":"Wiechman","given":"Lief","affiliations":[],"preferred":false,"id":733988,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tebbenkamp, Joel","contributorId":25089,"corporation":false,"usgs":true,"family":"Tebbenkamp","given":"Joel","email":"","affiliations":[],"preferred":false,"id":733989,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gardner, Scott C.","contributorId":192081,"corporation":false,"usgs":false,"family":"Gardner","given":"Scott","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":733990,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Reese, Kerry P.","contributorId":70254,"corporation":false,"usgs":true,"family":"Reese","given":"Kerry","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":733991,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70195156,"text":"70195156 - 2018 - Time series sightability modeling of animal populations","interactions":[],"lastModifiedDate":"2018-02-07T13:33:48","indexId":"70195156","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Time series sightability modeling of animal populations","docAbstract":"Logistic regression models—or “sightability models”—fit to detection/non-detection data from marked individuals are often used to adjust for visibility bias in later detection-only surveys, with population abundance estimated using a modified Horvitz-Thompson (mHT) estimator. More recently, a model-based alternative for analyzing combined detection/non-detection and detection-only data was developed. This approach seemed promising, since it resulted in similar estimates as the mHT when applied to data from moose (Alces alces) surveys in Minnesota. More importantly, it provided a framework for developing flexible models for analyzing multiyear detection-only survey data in combination with detection/non-detection data. During initial attempts to extend the model-based approach to multiple years of detection-only data, we found that estimates of detection probabilities and population abundance were sensitive to the amount of detection-only data included in the combined (detection/non-detection and detection-only) analysis. Subsequently, we developed a robust hierarchical modeling approach where sightability model parameters are informed only by the detection/non-detection data, and we used this approach to fit a fixed-effects model (FE model) with year-specific parameters and a temporally-smoothed model (TS model) that shares information across years via random effects and a temporal spline. The abundance estimates from the TS model were more precise, with decreased interannual variability relative to the FE model and mHT abundance estimates, illustrating the potential benefits from model-based approaches that allow information to be shared across years.
","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0190706","usgsCitation":"ArchMiller, A.A., Dorazio, R., St. Clair, K., and Fieberg, J.R., 2018, Time series sightability modeling of animal populations: PLoS ONE, v. 13, no. 1, p. 1-16, https://doi.org/10.1371/journal.pone.0190706.","productDescription":"e0190706; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-085670","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469014,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0190706","text":"Publisher Index Page"},{"id":351270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-12","publicationStatus":"PW","scienceBaseUri":"5a7c1e6ee4b00f54eb2292a6","contributors":{"authors":[{"text":"ArchMiller, Althea A.","contributorId":194336,"corporation":false,"usgs":false,"family":"ArchMiller","given":"Althea","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":727232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dorazio, Robert 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":172151,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":727231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"St. Clair, Katherine","contributorId":201938,"corporation":false,"usgs":false,"family":"St. Clair","given":"Katherine","email":"","affiliations":[{"id":36306,"text":"Dept. of Mathematics and Statistics, Carleton College","active":true,"usgs":false}],"preferred":false,"id":727233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fieberg, John R. 0000-0002-3180-7021","orcid":"https://orcid.org/0000-0002-3180-7021","contributorId":194333,"corporation":false,"usgs":false,"family":"Fieberg","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":727234,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195285,"text":"70195285 - 2018 - Juvenile coho salmon growth and health in streams across an urbanization gradient","interactions":[],"lastModifiedDate":"2018-02-07T12:12:02","indexId":"70195285","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Juvenile coho salmon growth and health in streams across an urbanization gradient","docAbstract":"Expanding human population and urbanization alters freshwater systems through structural changes to habitat, temperature effects from increased runoff and reduced canopy cover, altered flows, and increased toxicants. Current stream assessments stop short of measuring health or condition of species utilizing these freshwater habitats and fail to link specific stressors mechanistically to the health of organisms in the stream. Juvenile fish growth integrates both external and internal conditions providing a useful indicator of habitat quality and ecosystem health. Thus, there is a need to account for ecological and environmental influences on fish growth accurately. Bioenergetics models can simulate changes in growth and consumption in response to environmental conditions and food availability to account for interactions between an organism's environmental experience and utilization of available resources. The bioenergetics approach accounts for how thermal regime, food supply, and food quality affect fish growth. This study used a bioenergetics modeling approach to evaluate the environmental factors influencing juvenile coho salmon growth among ten Pacific Northwest streams spanning an urban gradient. Urban streams tended to be warmer, have earlier emergence dates and stronger early season growth. However, fish in urban streams experienced increased stress through lower growth efficiencies, especially later in the summer as temperatures warmed, with as much as a 16.6% reduction when compared to fish from other streams. Bioenergetics modeling successfully characterized salmonid growth in small perennial streams as part of a more extensive monitoring program and provides a powerful assessment tool for characterizing mixed life-stage specific responses in urban streams.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.12.327","usgsCitation":"Spanjer, A., Moran, P.W., Larsen, K., Wetzel, L., Hansen, A.G., and Beauchamp, D.A., 2018, Juvenile coho salmon growth and health in streams across an urbanization gradient: Science of the Total Environment, v. 625, p. 1003-1012, https://doi.org/10.1016/j.scitotenv.2017.12.327.","productDescription":"10 p.","startPage":"1003","endPage":"1012","ipdsId":"IP-091284","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":469018,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2017.12.327","text":"Publisher Index Page"},{"id":438023,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7W094WD","text":"USGS data release","linkHelpText":"Influence of urbanization on the health of juvenile salmonids in Pacific Northwest perennial streams"},{"id":351235,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"625","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7c1e68e4b00f54eb229268","contributors":{"authors":[{"text":"Spanjer, Andrew R.","contributorId":202171,"corporation":false,"usgs":false,"family":"Spanjer","given":"Andrew R.","affiliations":[{"id":17855,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":727732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moran, Patrick W. 0000-0002-2002-3539 pwmoran@usgs.gov","orcid":"https://orcid.org/0000-0002-2002-3539","contributorId":489,"corporation":false,"usgs":true,"family":"Moran","given":"Patrick","email":"pwmoran@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":727733,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larsen, Kimberly 0000-0001-7978-2452","orcid":"https://orcid.org/0000-0001-7978-2452","contributorId":202172,"corporation":false,"usgs":true,"family":"Larsen","given":"Kimberly","email":"","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":727734,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wetzel, Lisa 0000-0003-3178-9940","orcid":"https://orcid.org/0000-0003-3178-9940","contributorId":202173,"corporation":false,"usgs":true,"family":"Wetzel","given":"Lisa","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":727735,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, Adam G.","contributorId":197415,"corporation":false,"usgs":false,"family":"Hansen","given":"Adam","email":"","middleInitial":"G.","affiliations":[{"id":34919,"text":"Colorado Parks and Wildlife, 317 West Prospect Road, Fort Collins, Colorado 80526, USA","active":true,"usgs":false}],"preferred":false,"id":727736,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beauchamp, David A. 0000-0002-3592-8381 fadave@usgs.gov","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":4205,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","email":"fadave@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":727731,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70195289,"text":"70195289 - 2018 - Quarterly wildlife mortality report January 2018","interactions":[],"lastModifiedDate":"2023-10-13T14:05:18.459016","indexId":"70195289","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3769,"text":"Wildlife Disease Association Newsletter","active":true,"publicationSubtype":{"id":10}},"title":"Quarterly wildlife mortality report January 2018","docAbstract":"No abstract available.
","language":"English","publisher":"Wildlife Disease Association","usgsCitation":"Richards, B.J., Grear, D.A., Ballmann, A., Dusek, R.J., Kaler, R., and Kuletz, K., 2018, Quarterly wildlife mortality report January 2018: Wildlife Disease Association Newsletter, HTML document.","productDescription":"HTML document","ipdsId":"IP-093337","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":351285,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.wildlifedisease.org/PersonifyEbusiness/Resources/Publications/Newsletter/Archive"},{"id":351298,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7c1e68e4b00f54eb229264","contributors":{"authors":[{"text":"Richards, Bryan J. 0000-0001-9955-2523 brichards@usgs.gov","orcid":"https://orcid.org/0000-0001-9955-2523","contributorId":3533,"corporation":false,"usgs":true,"family":"Richards","given":"Bryan","email":"brichards@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":727755,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":727756,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ballmann, Anne 0000-0002-0380-056X aballmann@usgs.gov","orcid":"https://orcid.org/0000-0002-0380-056X","contributorId":140319,"corporation":false,"usgs":true,"family":"Ballmann","given":"Anne","email":"aballmann@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":727757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":174374,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert","email":"rdusek@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":727758,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaler, Robert","contributorId":199324,"corporation":false,"usgs":false,"family":"Kaler","given":"Robert","email":"","affiliations":[],"preferred":false,"id":727759,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kuletz, Kathy","contributorId":202179,"corporation":false,"usgs":false,"family":"Kuletz","given":"Kathy","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":727760,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70195284,"text":"70195284 - 2018 - Relationships between indicators of acid-base chemistry and fish assemblages in streams of the Great Smoky Mountains National Park","interactions":[],"lastModifiedDate":"2018-02-07T12:08:06","indexId":"70195284","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Relationships between indicators of acid-base chemistry and fish assemblages in streams of the Great Smoky Mountains National Park","docAbstract":"The acidity of many streams in the Great Smoky Mountains National Park (GRSM) has increased significantly since pre-industrial (∼1850) times due to the effects of highly acidic atmospheric deposition in poorly buffered watersheds. Extensive stream-monitoring programs since 1993 have shown that fish and macroinvertebrate assemblages have been adversely affected in many streams across the GRSM. Matching chemistry and fishery information collected from 389 surveys performed at 52 stream sites over a 22-year period were assessed using logistic regression analysis to help inform the U.S. Environmental Protection Agency’s assessment of the environmental impacts of emissions of oxides of nitrogen (NOx) and sulfur (SOx). Numerous logistic equations and associated curves were derived that defined the relations between acid neutralizing capacity (ANC) or pH and different levels of community richness, density, and biomass; and density and biomass of brook trout, rainbow trout, and small prey (minnow) populations in streams of the GRSM. The equations and curves describe the status of fish assemblages in the GRSM under contemporary emission levels and deposition loads of nitrogen (N) and sulfur (S) and provide a means to estimate how newly proposed (and various alternative) target deposition loads, which strongly influence stream ANC, might affect key ecological indicators. Several examples using ANC, community richness, and brook trout density are presented to illustrate the steps needed to predict how future changes in stream chemistry (resulting from different target deposition loads of N and S) will affect the probabilities of observing specific levels of selected biological indicators in GRSM streams. The implications of this study to the regulation of NOx and SOx emissions, water quality, and fisheries management in streams of the GRSM are discussed, but also qualified by the fact that specific examples provided need to be further explored before recommendations concerning their use as ecological indicators could be proposed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2018.01.021","usgsCitation":"Baldigo, B.P., Kulp, M.A., and Schwartz, J.S., 2018, Relationships between indicators of acid-base chemistry and fish assemblages in streams of the Great Smoky Mountains National Park: Ecological Indicators, v. 88, p. 465-484, https://doi.org/10.1016/j.ecolind.2018.01.021.","productDescription":"20 p.","startPage":"465","endPage":"484","ipdsId":"IP-083415","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":351234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Tennessee","otherGeospatial":"Great Smoky Mountains National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.16900634765625,\n 35.34201475584807\n ],\n [\n -82.72979736328125,\n 35.34201475584807\n ],\n [\n -82.72979736328125,\n 35.92909271208457\n ],\n [\n -84.16900634765625,\n 35.92909271208457\n ],\n [\n -84.16900634765625,\n 35.34201475584807\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"88","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7c1e69e4b00f54eb22926b","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":727728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kulp, Matt A.","contributorId":196801,"corporation":false,"usgs":false,"family":"Kulp","given":"Matt","email":"","middleInitial":"A.","affiliations":[{"id":35484,"text":"National Park Service, Great Smoky Mountains National Park","active":true,"usgs":false}],"preferred":false,"id":727729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwartz, John S.","contributorId":196802,"corporation":false,"usgs":false,"family":"Schwartz","given":"John","email":"","middleInitial":"S.","affiliations":[{"id":36358,"text":" University of Tennessee, Knoxville, TN","active":true,"usgs":false}],"preferred":false,"id":727730,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70195166,"text":"70195166 - 2018 - Mapping elemental contamination on Palmyra Atoll National Wildlife Refuge","interactions":[],"lastModifiedDate":"2019-06-03T13:20:00","indexId":"70195166","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Mapping elemental contamination on Palmyra Atoll National Wildlife Refuge","docAbstract":"Palmyra Atoll, once a WWII U.S. Navy air station, is now a U.S. National Wildlife Refuge with nearly 50 km2 of coral reef and 275 ha of emergent lands with forests of Pisonia grandistrees and colonies of several bird species. Due to the known elemental and organic contamination from chemicals associated with aviation, power generation and transmission, waste management, and other air station activities, a screening survey to map elemental concentrations was conducted. A map of 1944 Navy facilities was georeferenced and identifiable features were digitized. These data informed a targeted survey of 25 elements in soils and sediment at locations known or suspected to be contaminated, using a hand-held X-ray fluorescence spectrometer. At dozens of locations, concentrations of elements exceeded established soil and marine sediment thresholds for adverse ecological effects. Results were compiled into a publicly available geospatial dataset to inform potential remediation and habitat restoration activities.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2017.12.065","usgsCitation":"Struckhoff, M.A., Orazio, C.E., Tillitt, D.E., Shaver, D.K., and Papoulias, D.M., 2018, Mapping elemental contamination on Palmyra Atoll National Wildlife Refuge: Marine Pollution Bulletin, v. 128, p. 97-105, https://doi.org/10.1016/j.marpolbul.2017.12.065.","productDescription":"9 p.","startPage":"97","endPage":"105","ipdsId":"IP-087627","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":469012,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marpolbul.2017.12.065","text":"Publisher Index Page"},{"id":351287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Palmyra Atoll National Wildlife Refuge","volume":"128","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7c1e6de4b00f54eb229296","contributors":{"authors":[{"text":"Struckhoff, Matthew A. 0000-0002-4911-9956 mstruckhoff@usgs.gov","orcid":"https://orcid.org/0000-0002-4911-9956","contributorId":2095,"corporation":false,"usgs":true,"family":"Struckhoff","given":"Matthew","email":"mstruckhoff@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":727272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orazio, Carl E. 0000-0002-2532-9668 corazio@usgs.gov","orcid":"https://orcid.org/0000-0002-2532-9668","contributorId":1366,"corporation":false,"usgs":true,"family":"Orazio","given":"Carl","email":"corazio@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":727273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tillitt, Donald E. 0000-0002-8278-3955 dtillitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8278-3955","contributorId":1875,"corporation":false,"usgs":true,"family":"Tillitt","given":"Donald","email":"dtillitt@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":727274,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shaver, David K. dshaver@usgs.gov","contributorId":1611,"corporation":false,"usgs":true,"family":"Shaver","given":"David","email":"dshaver@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":727275,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Papoulias, Diana M. 0000-0002-5106-2469 dpapoulias@usgs.gov","orcid":"https://orcid.org/0000-0002-5106-2469","contributorId":2726,"corporation":false,"usgs":true,"family":"Papoulias","given":"Diana","email":"dpapoulias@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":727276,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195157,"text":"70195157 - 2018 - Shrubland carbon sink depends upon winter water availability in the warm deserts of North America","interactions":[],"lastModifiedDate":"2018-02-08T09:24:14","indexId":"70195157","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":681,"text":"Agricultural and Forest Meteorology","active":true,"publicationSubtype":{"id":10}},"title":"Shrubland carbon sink depends upon winter water availability in the warm deserts of North America","docAbstract":"Global-scale studies suggest that dryland ecosystems dominate an increasing trend in the magnitude and interannual variability of the land CO2 sink. However, such model-based analyses are poorly constrained by measured CO2 exchange in open shrublands, which is the most common global land cover type, covering ∼14% of Earth’s surface. Here we evaluate how the amount and seasonal timing of water availability regulate CO2 exchange between shrublands and the atmosphere. We use eddy covariance data from six US sites across the three warm deserts of North America with observed ranges in annual precipitation of ∼100–400mm, annual temperatures of 13–18°C, and records of 2–8 years (33 site-years in total). The Chihuahuan, Sonoran and Mojave Deserts present gradients in both mean annual precipitation and its seasonal distribution between the wet-winter Mojave Desert and the wet-summer Chihuahuan Desert. We found that due to hydrologic losses during the wettest summers in the Sonoran and Chihuahuan Deserts, evapotranspiration (ET) was a better metric than precipitation of water available to drive dryland CO2 exchange. In contrast with recent synthesis studies across diverse dryland biomes, we found that NEP could not be directly predicted from ET due to wintertime decoupling of the relationship between ecosystem respiration (Reco) and gross ecosystem productivity (GEP). Ecosystem water use efficiency (WUE=GEP/ET) did not differ between winter and summer. Carbon use efficiency (CUE=NEP/GEP), however, was greater in winter because Reco returned a smaller fraction of carbon to the atmosphere (23% of GEP) than in summer (77%). Combining the water-carbon relations found here with historical precipitation since 1980, we estimate that lower average winter precipitation during the 21st century reduced the net carbon sink of the three deserts by an average of 6.8TgC yr1. Our results highlight that winter precipitation is critical to the annual carbon balance of these warm desert shrublands.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2017.11.005","usgsCitation":"Biederman, J.A., Scott, R.L., Arnone, J.A., Jasoni, R.L., Litvak, M.E., Moreo, M.T., Papuga, S.A., Ponce-Campos, G.E., Schreiner-McGraw, A.P., and Vivoni, E.R., 2018, Shrubland carbon sink depends upon winter water availability in the warm deserts of North America: Agricultural and Forest Meteorology, v. 249, p. 407-419, https://doi.org/10.1016/j.agrformet.2017.11.005.","productDescription":"13 p.","startPage":"407","endPage":"419","ipdsId":"IP-088519","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":469024,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1549057","text":"Publisher Index Page"},{"id":351309,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"249","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7c1e6ee4b00f54eb2292a1","contributors":{"authors":[{"text":"Biederman, Joel A.","contributorId":201939,"corporation":false,"usgs":false,"family":"Biederman","given":"Joel","email":"","middleInitial":"A.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":727236,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, Russell L.","contributorId":39875,"corporation":false,"usgs":false,"family":"Scott","given":"Russell","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":727237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arnone, John A.","contributorId":201941,"corporation":false,"usgs":false,"family":"Arnone","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":727238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jasoni, Richard L.","contributorId":201942,"corporation":false,"usgs":false,"family":"Jasoni","given":"Richard","email":"","middleInitial":"L.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":727239,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Litvak, Marcy E.","contributorId":73932,"corporation":false,"usgs":true,"family":"Litvak","given":"Marcy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":727240,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moreo, Michael T. 0000-0002-9122-6958 mtmoreo@usgs.gov","orcid":"https://orcid.org/0000-0002-9122-6958","contributorId":2363,"corporation":false,"usgs":true,"family":"Moreo","given":"Michael","email":"mtmoreo@usgs.gov","middleInitial":"T.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":727235,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Papuga, Shirley A.","contributorId":197727,"corporation":false,"usgs":false,"family":"Papuga","given":"Shirley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":727241,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ponce-Campos, Guillermo E.","contributorId":201945,"corporation":false,"usgs":false,"family":"Ponce-Campos","given":"Guillermo","email":"","middleInitial":"E.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":727242,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schreiner-McGraw, Adam P.","contributorId":201946,"corporation":false,"usgs":false,"family":"Schreiner-McGraw","given":"Adam","email":"","middleInitial":"P.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":727243,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Vivoni, Enrique R.","contributorId":139052,"corporation":false,"usgs":false,"family":"Vivoni","given":"Enrique","email":"","middleInitial":"R.","affiliations":[{"id":12634,"text":"School of Earth and Space Exploration and School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ","active":true,"usgs":false}],"preferred":false,"id":727244,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70195168,"text":"70195168 - 2018 - Accurate ocean bottom seismometer positioning method inspired by multilateration technique","interactions":[],"lastModifiedDate":"2018-07-03T11:38:27","indexId":"70195168","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","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":"Accurate ocean bottom seismometer positioning method inspired by multilateration technique","docAbstract":"The positioning of ocean bottom seismometers (OBS) is a key step in the processing flow of OBS data, especially in the case of self popup types of OBS instruments. The use of first arrivals from airgun shots, rather than relying on the acoustic transponders mounted in the OBS, is becoming a trend and generally leads to more accurate positioning due to the statistics from a large number of shots. In this paper, a linearization of the OBS positioning problem via the multilateration technique is discussed. The discussed linear solution solves jointly for the average water layer velocity and the OBS position using only shot locations and first arrival times as input data.
","language":"English","publisher":"Springer","doi":"10.1007/s11004-017-9719-5","usgsCitation":"Benazzouz, O., Pinheiro, L.M., Matias, L.M., Afilhado, A., Herold, D., and Haines, S.S., 2018, Accurate ocean bottom seismometer positioning method inspired by multilateration technique: Mathematical Geosciences, v. 50, no. 5, p. 569-584, https://doi.org/10.1007/s11004-017-9719-5.","productDescription":"16 p.","startPage":"569","endPage":"584","ipdsId":"IP-075056","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":469020,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10400.21/9110","text":"External Repository"},{"id":351283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-08","publicationStatus":"PW","scienceBaseUri":"5a7c1e6ce4b00f54eb229293","contributors":{"authors":[{"text":"Benazzouz, Omar","contributorId":201961,"corporation":false,"usgs":false,"family":"Benazzouz","given":"Omar","email":"","affiliations":[{"id":36309,"text":"University of Aveiro, Portugal","active":true,"usgs":false}],"preferred":false,"id":727281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pinheiro, Luis M.","contributorId":201962,"corporation":false,"usgs":false,"family":"Pinheiro","given":"Luis","email":"","middleInitial":"M.","affiliations":[{"id":36309,"text":"University of Aveiro, Portugal","active":true,"usgs":false}],"preferred":false,"id":727282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matias, Luis M. A.","contributorId":201963,"corporation":false,"usgs":false,"family":"Matias","given":"Luis","email":"","middleInitial":"M. A.","affiliations":[{"id":36310,"text":"Dom Luiz Institute, Portugal","active":true,"usgs":false}],"preferred":false,"id":727283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Afilhado, Alexandra","contributorId":201964,"corporation":false,"usgs":false,"family":"Afilhado","given":"Alexandra","email":"","affiliations":[{"id":36311,"text":"Superior Institute of Engineering of Lisbon, Portugal","active":true,"usgs":false}],"preferred":false,"id":727284,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herold, Daniel","contributorId":201965,"corporation":false,"usgs":false,"family":"Herold","given":"Daniel","email":"","affiliations":[{"id":36312,"text":"Parallel Geoscience Corporation","active":true,"usgs":false}],"preferred":false,"id":727285,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haines, Seth S. 0000-0003-2611-8165 shaines@usgs.gov","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":1344,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","email":"shaines@usgs.gov","middleInitial":"S.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":727280,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70195195,"text":"70195195 - 2018 - Floodplain trapping and cycling compared to streambank erosion of sediment and nutrients in an agricultural watershed","interactions":[],"lastModifiedDate":"2018-04-02T13:51:41","indexId":"70195195","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Floodplain trapping and cycling compared to streambank erosion of sediment and nutrients in an agricultural watershed","docAbstract":"Floodplains and streambanks can positively and negatively influence downstream water quality through interacting geomorphic and biogeochemical processes. Few studies have measured those processes in agricultural watersheds. We measured inputs (floodplain sedimentation and dissolved inorganic loading), cycling (floodplain soil nitrogen [N] and phosphorus [P] mineralization), and losses (bank erosion) of sediment, N, and P longitudinally in stream reaches of Smith Creek, an agricultural watershed in the Valley and Ridge physiographic province. All study reaches were net depositional (floodplain deposition > bank erosion), had high N and P sedimentation and loading rates to the floodplain, high soil concentrations of N and P, and high rates of floodplain soil N and P mineralization. High sediment, N, and P inputs to floodplains are attributed to agricultural activity in the region. Rates of P mineralization were much greater than those measured in other studies of nontidal floodplains that used the same method. Floodplain connectivity and sediment deposition decreased longitudinally, contrary to patterns in most watersheds. The net trapping function of Smith Creek floodplains indicates a benefit to water quality. Further research is needed to determine if future decreases in floodplain deposition, continued bank erosion, and the potential for nitrate leaching from nutrient-enriched floodplain soils could pose a long-term source of sediment and nutrients to downstream rivers.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12624","usgsCitation":"Gillespie, J., Noe, G.E., Hupp, C.R., Gellis, A.C., and Schenk, E., 2018, Floodplain trapping and cycling compared to streambank erosion of sediment and nutrients in an agricultural watershed: Journal of the American Water Resources Association, v. 54, no. 2, p. 565-582, https://doi.org/10.1111/1752-1688.12624.","productDescription":"18 p.","startPage":"565","endPage":"582","ipdsId":"IP-081496","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":438021,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z036BD","text":"USGS data release","linkHelpText":"Floodplain sedimentation, bank erosion, and biogeochemical cycling of sediment and nutrients in Smith Creek (Virginia) 2012-2015"},{"id":351245,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.8667,\n 38.4167\n ],\n [\n -78.55,\n 38.4167\n ],\n [\n -78.55,\n 38.7333\n ],\n [\n -78.8667,\n 38.7333\n ],\n [\n -78.8667,\n 38.4167\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-22","publicationStatus":"PW","scienceBaseUri":"5a7c1e6ce4b00f54eb229289","contributors":{"authors":[{"text":"Gillespie, Jaimie 0000-0002-6483-0359","orcid":"https://orcid.org/0000-0002-6483-0359","contributorId":202016,"corporation":false,"usgs":true,"family":"Gillespie","given":"Jaimie","email":"","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":727380,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":727381,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":727382,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":727383,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schenk, Edward R.","contributorId":202017,"corporation":false,"usgs":false,"family":"Schenk","given":"Edward R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":727384,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195124,"text":"70195124 - 2018 - Making ecological models adequate","interactions":[],"lastModifiedDate":"2018-02-08T09:25:55","indexId":"70195124","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Making ecological models adequate","docAbstract":"Critical evaluation of the adequacy of ecological models is urgently needed to enhance their utility in developing theory and enabling environmental managers and policymakers to make informed decisions. Poorly supported management can have detrimental, costly or irreversible impacts on the environment and society. Here, we examine common issues in ecological modelling and suggest criteria for improving modelling frameworks. An appropriate level of process description is crucial to constructing the best possible model, given the available data and understanding of ecological structures. Model details unsupported by data typically lead to over parameterisation and poor model performance. Conversely, a lack of mechanistic details may limit a model's ability to predict ecological systems’ responses to management. Ecological studies that employ models should follow a set of model adequacy assessment protocols that include: asking a series of critical questions regarding state and control variable selection, the determinacy of data, and the sensitivity and validity of analyses. We also need to improve model elaboration, refinement and coarse graining procedures to better understand the relevancy and adequacy of our models and the role they play in advancing theory, improving hind and forecasting, and enabling problem solving and management.
","language":"English","publisher":"Wiley","doi":"10.1111/ele.12893","usgsCitation":"Getz, W.M., Marshall, C.R., Carlson, C.J., Giuggioli, L., Ryan, S.J., Romanach, S.S., Boettiger, C., Chamberlain, S.D., Larsen, L., D'Odorico, P., and O’Sullivan, D., 2018, Making ecological models adequate: Ecology Letters, v. 21, no. 2, p. 153-166, https://doi.org/10.1111/ele.12893.","productDescription":"14 p.","startPage":"153","endPage":"166","ipdsId":"IP-088087","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469017,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research-information.bris.ac.uk/en/publications/8d5d214b-4b79-4eaf-80fb-edd67296962f","text":"External Repository"},{"id":351271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-27","publicationStatus":"PW","scienceBaseUri":"5a7c1e6fe4b00f54eb2292b3","contributors":{"authors":[{"text":"Getz, Wayne M.","contributorId":201830,"corporation":false,"usgs":false,"family":"Getz","given":"Wayne","email":"","middleInitial":"M.","affiliations":[{"id":36267,"text":"Dept of Environmental Science, University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":727050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Charles R.","contributorId":197649,"corporation":false,"usgs":false,"family":"Marshall","given":"Charles","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":727052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlson, Colin J.","contributorId":201831,"corporation":false,"usgs":false,"family":"Carlson","given":"Colin","email":"","middleInitial":"J.","affiliations":[{"id":36267,"text":"Dept of Environmental Science, University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":727053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giuggioli, Luca","contributorId":201832,"corporation":false,"usgs":false,"family":"Giuggioli","given":"Luca","email":"","affiliations":[{"id":36268,"text":"Bristol Centre for Complexity Sciences, University of Bristol, UK","active":true,"usgs":false}],"preferred":false,"id":727054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ryan, Sadie J.","contributorId":139037,"corporation":false,"usgs":false,"family":"Ryan","given":"Sadie","email":"","middleInitial":"J.","affiliations":[{"id":12623,"text":"State University of New York College of Environmental Science and Forestry","active":true,"usgs":false}],"preferred":false,"id":727055,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Romanach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":140419,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","email":"sromanach@usgs.gov","middleInitial":"S.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":727051,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boettiger, Carl","contributorId":201833,"corporation":false,"usgs":false,"family":"Boettiger","given":"Carl","affiliations":[{"id":36267,"text":"Dept of Environmental Science, University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":727056,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chamberlain, Samuel D.","contributorId":201834,"corporation":false,"usgs":false,"family":"Chamberlain","given":"Samuel","email":"","middleInitial":"D.","affiliations":[{"id":36267,"text":"Dept of Environmental Science, University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":727057,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Larsen, Laurel","contributorId":190106,"corporation":false,"usgs":false,"family":"Larsen","given":"Laurel","affiliations":[],"preferred":false,"id":727058,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"D'Odorico, Paolo","contributorId":201835,"corporation":false,"usgs":false,"family":"D'Odorico","given":"Paolo","affiliations":[{"id":36267,"text":"Dept of Environmental Science, University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":727059,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"O’Sullivan, David","contributorId":201836,"corporation":false,"usgs":false,"family":"O’Sullivan","given":"David","email":"","affiliations":[{"id":36269,"text":"Dept of Geography, University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":727060,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70195214,"text":"70195214 - 2018 - Demographic modelling reveals a history of divergence with gene flow for a glacially tied stonefly in a changing post-Pleistocene landscape","interactions":[],"lastModifiedDate":"2018-02-08T09:08:53","indexId":"70195214","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Demographic modelling reveals a history of divergence with gene flow for a glacially tied stonefly in a changing post-Pleistocene landscape","docAbstract":"Aim
Climate warming is causing extensive loss of glaciers in mountainous regions, yet our understanding of how glacial recession influences evolutionary processes and genetic diversity is limited. Linking genetic structure with the influences shaping it can improve understanding of how species respond to environmental change. Here, we used genome-scale data and demographic modelling to resolve the evolutionary history of Lednia tumana, a rare, aquatic insect endemic to alpine streams. We also employed a range of widely used data filtering approaches to quantify how they influenced population structure results.
Location
Alpine streams in the Rocky Mountains of Glacier National Park, Montana, USA.
Taxon
Lednia tumana, a stonefly (Order Plecoptera) in the family Nemouridae.
Methods
We generated single nucleotide polymorphism data through restriction-site associated DNA sequencing to assess contemporary patterns of genetic structure for 11 L. tumana populations. Using identified clusters, we assessed demographic history through model selection and parameter estimation in a coalescent framework. During population structure analyses, we filtered our data to assess the influence of singletons, missing data and total number of markers on results.
Results
Contemporary patterns of population structure indicate that L. tumana exhibits a pattern of isolation-by-distance among populations within three genetic clusters that align with geography. Mean pairwise genetic differentiation (FST) among populations was 0.033. Coalescent-based demographic modelling supported divergence with gene flow among genetic clusters since the end of the Pleistocene (~13-17 kya), likely reflecting the south-to-north recession of ice sheets that accumulated during the Wisconsin glaciation.
Main conclusions
We identified a link between glacial retreat, evolutionary history and patterns of genetic diversity for a range-restricted stonefly imperiled by climate change. This finding included a history of divergence with gene flow, an unexpected conclusion for a mountaintop species. Beyond L. tumana, this study demonstrates the complexity of assessing genetic structure for weakly differentiated species, shows the degree to which rare alleles and missing data may influence results, and highlights the usefulness of genome-scale data to extend population genetic inquiry in non-model species.
","language":"English","publisher":"Wiley","doi":"10.1111/jbi.13125","usgsCitation":"Hotaling, S., Muhlfeld, C.C., Giersch, J.J., Ali, O., Jordan, S., Miller, M.R., Luikart, G., and Weisrock, D.W., 2018, Demographic modelling reveals a history of divergence with gene flow for a glacially tied stonefly in a changing post-Pleistocene landscape: Journal of Biogeography, v. 45, no. 2, p. 304-317, https://doi.org/10.1111/jbi.13125.","productDescription":"14 p.","startPage":"304","endPage":"317","ipdsId":"IP-090859","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":351237,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.47479248046875,\n 49.001843917978526\n ],\n [\n -114.41986083984375,\n 48.95407191575548\n ],\n [\n -114.41162109375,\n 48.94775898298233\n ],\n [\n -114.39376831054688,\n 48.926108577622024\n ],\n [\n -114.38415527343749,\n 48.91527985344383\n ],\n [\n -114.37728881835938,\n 48.9089620134408\n ],\n [\n -114.38415527343749,\n 48.89903236496008\n ],\n [\n -114.3731689453125,\n 48.894518236158234\n ],\n [\n -114.36492919921875,\n 48.888197770982316\n ],\n [\n -114.37454223632812,\n 48.88187650678903\n ],\n [\n -114.37042236328125,\n 48.87555444355432\n ],\n [\n -114.36080932617186,\n 48.86923158125418\n ],\n [\n -114.37179565429688,\n 48.857487002645485\n ],\n [\n -114.35256958007811,\n 48.854776323867306\n ],\n [\n -114.34707641601562,\n 48.83579746243093\n ],\n [\n -114.33609008789062,\n 48.83579746243093\n ],\n [\n -114.33197021484375,\n 48.81952414194507\n ],\n [\n -114.31961059570312,\n 48.8032455364465\n ],\n [\n -114.2962646484375,\n 48.79239019646406\n ],\n [\n -114.28253173828124,\n 48.77972266402536\n ],\n [\n -114.27841186523438,\n 48.75799945448164\n ],\n [\n -114.26193237304688,\n 48.75256718365392\n ],\n [\n -114.2633056640625,\n 48.73083222613515\n ],\n [\n -114.23583984374999,\n 48.71452483966837\n ],\n [\n -114.21661376953125,\n 48.71271258145237\n ],\n [\n -114.2083740234375,\n 48.705462895790546\n ],\n [\n -114.21112060546875,\n 48.69549287252203\n ],\n [\n -114.18914794921874,\n 48.68824070611107\n ],\n [\n -114.19601440429686,\n 48.68098749511622\n ],\n [\n -114.158935546875,\n 48.64198358792223\n ],\n [\n -114.14932250976561,\n 48.63200099590253\n ],\n [\n -114.13970947265625,\n 48.62020084032983\n ],\n [\n -114.14932250976561,\n 48.62020084032983\n ],\n [\n -114.16168212890625,\n 48.61112192003074\n ],\n [\n -114.17129516601562,\n 48.608397925562606\n ],\n [\n -114.16305541992188,\n 48.60294949578345\n ],\n [\n -114.16717529296875,\n 48.59568400838304\n ],\n [\n -114.14520263671875,\n 48.592050872804194\n ],\n [\n -114.158935546875,\n 48.57660713188407\n ],\n [\n -114.14108276367188,\n 48.57933284084407\n ],\n [\n -114.12872314453125,\n 48.570246572767076\n ],\n [\n -114.12185668945312,\n 48.558431982894355\n ],\n [\n -114.12185668945312,\n 48.54388716039111\n ],\n [\n -114.11636352539062,\n 48.53661318127798\n ],\n [\n -114.1204833984375,\n 48.525700252688765\n ],\n [\n -114.14657592773438,\n 48.507506811647325\n ],\n [\n -114.12460327148438,\n 48.50295743049266\n ],\n [\n -114.12460327148438,\n 48.49203724954177\n ],\n [\n -114.11361694335938,\n 48.493857443054395\n ],\n [\n -114.093017578125,\n 48.48111471624846\n ],\n [\n -114.08340454101562,\n 48.47110032750183\n ],\n [\n -114.07379150390625,\n 48.468368787493915\n ],\n [\n -114.02572631835936,\n 48.485666057669334\n ],\n [\n -114.01336669921875,\n 48.48748647988415\n ],\n [\n -114.00787353515625,\n 48.49567757122466\n ],\n [\n -114.00924682617186,\n 48.50932644976633\n ],\n [\n -113.99002075195312,\n 48.49749763405313\n ],\n [\n -113.97766113281249,\n 48.499317631540286\n ],\n [\n -113.94058227539062,\n 48.49840764096433\n ],\n [\n -113.88839721679688,\n 48.49294735446591\n ],\n [\n -113.84170532226562,\n 48.48475582205773\n ],\n [\n -113.82659912109375,\n 48.473831720475225\n ],\n [\n -113.80050659179688,\n 48.45106561953216\n ],\n [\n -113.80050659179688,\n 48.44286732344491\n ],\n [\n -113.79501342773438,\n 48.43193420325806\n ],\n [\n -113.76754760742186,\n 48.428289306991815\n ],\n [\n -113.71810913085938,\n 48.4164415885222\n ],\n [\n -113.70437622070312,\n 48.39729713260604\n ],\n [\n -113.69476318359375,\n 48.390002110874136\n ],\n [\n -113.67965698242188,\n 48.375408929573624\n ],\n [\n -113.66455078125,\n 48.37449671682332\n ],\n [\n -113.64532470703125,\n 48.3617240221937\n ],\n [\n -113.63983154296875,\n 48.3434717583591\n ],\n [\n -113.63296508789062,\n 48.32977826971931\n ],\n [\n -113.63296508789062,\n 48.31973404047173\n ],\n [\n -113.63296508789062,\n 48.31060120649363\n ],\n [\n -113.61373901367188,\n 48.29324431799557\n ],\n [\n -113.6151123046875,\n 48.278623413079096\n ],\n [\n -113.60687255859375,\n 48.26765498757743\n ],\n [\n -113.59451293945312,\n 48.26216989188534\n ],\n [\n -113.57254028320311,\n 48.25119793455411\n ],\n [\n -113.55056762695312,\n 48.232906106325146\n ],\n [\n -113.477783203125,\n 48.24936904607428\n ],\n [\n -113.4503173828125,\n 48.274967532852976\n ],\n [\n -113.44757080078124,\n 48.284106742914524\n ],\n [\n -113.42971801757812,\n 48.278623413079096\n ],\n [\n -113.41461181640625,\n 48.29507163681939\n ],\n [\n -113.38851928710938,\n 48.29415798558204\n ],\n [\n -113.38165283203125,\n 48.30329376225394\n ],\n [\n -113.367919921875,\n 48.30146673770983\n ],\n [\n -113.35968017578125,\n 48.30877444352327\n ],\n [\n -113.3514404296875,\n 48.31790760445764\n ],\n [\n -113.27865600585938,\n 48.372672242291294\n ],\n [\n -113.27728271484374,\n 48.37723330604312\n ],\n [\n -113.28689575195312,\n 48.38544219115483\n ],\n [\n -113.27041625976562,\n 48.39091404578955\n ],\n [\n -113.25668334960938,\n 48.39456162202509\n ],\n [\n -113.25531005859375,\n 48.40094425125627\n ],\n [\n -113.258056640625,\n 48.40914931221878\n ],\n [\n -113.24295043945312,\n 48.41097247934197\n ],\n [\n -113.42147827148438,\n 48.691866919887374\n ],\n [\n -113.41873168945312,\n 48.73536111738081\n ],\n [\n -113.48739624023436,\n 48.78243740444988\n ],\n [\n -113.61236572265624,\n 48.93783704616433\n ],\n [\n -113.609619140625,\n 48.99824008113872\n ],\n [\n -114.47479248046875,\n 49.001843917978526\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-13","publicationStatus":"PW","scienceBaseUri":"5a7c1e6ae4b00f54eb229271","contributors":{"authors":[{"text":"Hotaling, Scott","contributorId":202050,"corporation":false,"usgs":false,"family":"Hotaling","given":"Scott","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":727482,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":727481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giersch, J. Joseph 0000-0001-7818-3941 jgiersch@usgs.gov","orcid":"https://orcid.org/0000-0001-7818-3941","contributorId":198074,"corporation":false,"usgs":true,"family":"Giersch","given":"J.","email":"jgiersch@usgs.gov","middleInitial":"Joseph","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":727483,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ali, Omar","contributorId":202051,"corporation":false,"usgs":false,"family":"Ali","given":"Omar","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":727484,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jordan, Steve","contributorId":168297,"corporation":false,"usgs":false,"family":"Jordan","given":"Steve","email":"","affiliations":[{"id":25242,"text":"Department of Biology, Bucknell University, Lewisburg, Pennsylvania 17837, USA","active":true,"usgs":false}],"preferred":false,"id":727485,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Michael R.","contributorId":45796,"corporation":false,"usgs":false,"family":"Miller","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":12709,"text":"Department of Animal Science, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA","active":true,"usgs":false}],"preferred":false,"id":727486,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Luikart, Gordon","contributorId":97409,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":727487,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Weisrock, David W.","contributorId":198313,"corporation":false,"usgs":false,"family":"Weisrock","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":727488,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70195104,"text":"70195104 - 2018 - Quaternary sea-level history and the origin of the northernmost coastal aeolianites in the Americas: Channel Islands National Park, California, USA","interactions":[],"lastModifiedDate":"2018-03-23T12:23:46","indexId":"70195104","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"Quaternary sea-level history and the origin of the northernmost coastal aeolianites in the Americas: Channel Islands National Park, California, USA","docAbstract":"Along most of the Pacific Coast of North America, sand dunes are dominantly silicate-rich. On the California Channel Islands, however, dunes are carbonate-rich, due to high productivity offshore and a lack of dilution by silicate minerals. Older sands on the Channel Islands contain enough carbonate to be cemented into aeolianite. Several generations of carbonate aeolianites are present on the California Channel Islands and represent the northernmost Quaternary coastal aeolianites on the Pacific Coast of North America. The oldest aeolianites on the islands may date to the early Pleistocene and thus far have only been found on Santa Cruz Island. Aeolianites with well-developed soils are found on both San Miguel Island and Santa Rosa Island and likely date to the middle Pleistocene. The youngest and best-dated aeolianites are located on San Miguel Island and Santa Rosa Island. These sediments were deposited during the late Pleistocene following the emergence of marine terraces that date to the last interglacial complex (~ 120,000 yr to ~ 80,000 yr). Based on radiocarbon and luminescence dating, the ages of these units correspond in time with marine isotope stages [MIS] 4, 3, and 2. Sea level was significantly lower than present during all three time periods. Reconstruction of insular paleogeography indicates that large areas to the north and northwest of the islands would have been exposed at these times, providing a ready source of carbonate-rich skeletal sands. These findings differ from a previously held concept that carbonate aeolianites are dominantly an interglacial phenomenon forming during high stands of sea. In contrast, our results are consistent with the findings of other investigators of the past decade who have reported evidence of glacial-age and interstadial-age aeolianites on coastlines of Australia and South Africa. They are also consistent with observations made by Darwin regarding the origin of aeolianites on the island of St. Helena, in the South Atlantic Ocean, more than a century and a half ago.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.palaeo.2017.11.042","usgsCitation":"Muhs, D., Pigati, J.S., Schumann, R.R., Skipp, G.L., Porat, N., and DeVogel, S.B., 2018, Quaternary sea-level history and the origin of the northernmost coastal aeolianites in the Americas: Channel Islands National Park, California, USA: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 491, p. 38-76, https://doi.org/10.1016/j.palaeo.2017.11.042.","productDescription":"39 p.","startPage":"38","endPage":"76","ipdsId":"IP-083839","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":469023,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.palaeo.2017.11.042","text":"Publisher Index Page"},{"id":351311,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Channel Islands National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.728759765625,\n 33.76088200086917\n ],\n [\n -119.28955078124999,\n 33.76088200086917\n ],\n [\n -119.28955078124999,\n 34.19135773925218\n ],\n [\n -120.728759765625,\n 34.19135773925218\n ],\n [\n -120.728759765625,\n 33.76088200086917\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"491","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7c1e70e4b00f54eb2292c5","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":168575,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel R.","email":"dmuhs@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":726945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pigati, Jeffrey S. 0000-0001-5843-6219 jpigati@usgs.gov","orcid":"https://orcid.org/0000-0001-5843-6219","contributorId":201167,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffrey","email":"jpigati@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":726946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schumann, R. Randall 0000-0001-8158-6960 rschumann@usgs.gov","orcid":"https://orcid.org/0000-0001-8158-6960","contributorId":1569,"corporation":false,"usgs":true,"family":"Schumann","given":"R.","email":"rschumann@usgs.gov","middleInitial":"Randall","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":726947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skipp, Gary L. 0000-0002-9404-0980","orcid":"https://orcid.org/0000-0002-9404-0980","contributorId":201777,"corporation":false,"usgs":true,"family":"Skipp","given":"Gary","email":"","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":726948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Porat, Naomi","contributorId":201778,"corporation":false,"usgs":false,"family":"Porat","given":"Naomi","email":"","affiliations":[{"id":13093,"text":"Geological Survey of Israel ","active":true,"usgs":false}],"preferred":false,"id":726949,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeVogel, Stephen B.","contributorId":150196,"corporation":false,"usgs":false,"family":"DeVogel","given":"Stephen","email":"","middleInitial":"B.","affiliations":[{"id":6709,"text":"University of Colorado, Denver","active":true,"usgs":false}],"preferred":false,"id":726950,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70195240,"text":"70195240 - 2018 - Removing rural roads from the National Land Cover Database to create improved urban maps for the United States, 1992-2011","interactions":[],"lastModifiedDate":"2025-01-29T15:55:10.456084","indexId":"70195240","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3052,"text":"Photogrammetric Engineering and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Removing rural roads from the National Land Cover Database to create improved urban maps for the United States, 1992-2011","docAbstract":"Quantifying change in urban land provides important information to create empirical models examining the effects of human land use. Maps of developed land from the National Land Cover Database (NLCD) of the conterminous United States include rural roads in the developed land class and therefore overestimate the amount of urban land. To better map the urban class and understand how urban lands change over time, we removed rural roads and small patches of rural development from the NLCD developed class and created four wall-to-wall maps (1992, 2001, 2006, and 2011) of urban land. Removing rural roads from the NLCD developed class involved a multi-step filtering process, data fusion using geospatial road and developed land data, and manual editing. Reference data classified as urban or not urban from a stratified random sample was used to assess the accuracy of the 2001 and 2006 urban and NLCD maps. The newly created urban maps had higher overall accuracy (98.7 percent) than the NLCD maps (96.2 percent). More importantly, the urban maps resulted in lower commission error of the urban class (23 percent versus 57 percent for the NLCD in 2006) with the trade-off of slightly inflated omission error (20 percent for the urban map, 16 percent for NLCD in 2006). The removal of approximately 230,000 km2 of rural roads from the NLCD developed class resulted in maps that better characterize the urban footprint. These urban maps are more suited to modeling applications and policy decisions that rely on quantitative and spatially explicit information regarding urban lands.
","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","doi":"10.14358/PERS.84.2.101","usgsCitation":"Soulard, C.E., Acevedo, W., and Stehman, S.V., 2018, Removing rural roads from the National Land Cover Database to create improved urban maps for the United States, 1992-2011: Photogrammetric Engineering and Remote Sensing, v. 84, no. 2, p. 101-109, https://doi.org/10.14358/PERS.84.2.101.","productDescription":"9 p.","startPage":"101","endPage":"109","ipdsId":"IP-082476","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":489910,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.84.2.101","text":"Publisher Index Page"},{"id":351268,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":361096,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/ja/70195240/70195240.pdf","text":"USGS open-access version of article","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","volume":"84","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7c1e69e4b00f54eb22926e","contributors":{"authors":[{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":727583,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Acevedo, William wacevedo@usgs.gov","contributorId":2689,"corporation":false,"usgs":true,"family":"Acevedo","given":"William","email":"wacevedo@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":727584,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stehman, Stephen V.","contributorId":77283,"corporation":false,"usgs":true,"family":"Stehman","given":"Stephen","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":727585,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70195107,"text":"70195107 - 2018 - Macroecological patterns of sexual size dimorphism in turtles of the world","interactions":[],"lastModifiedDate":"2018-03-12T13:09:58","indexId":"70195107","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2273,"text":"Journal of Evolutionary Biology","active":true,"publicationSubtype":{"id":10}},"title":"Macroecological patterns of sexual size dimorphism in turtles of the world","docAbstract":"Sexual size dimorphism (SSD) is a well-documented phenomenon in both plants and animals; however, the ecological and evolutionary mechanisms that drive and maintain SSD patterns across geographic space at regional and global scales are understudied, especially for reptiles. Our goal was to examine geographic variation of turtle SSD and to explore ecological and environmental correlates using phylogenetic comparative methods. We use published body size data on 135 species from nine turtle families to examine how geographic patterns and the evolution of SSD are influenced by habitat specialization, climate (annual mean temperature and annual precipitation) and climate variability, latitude, or a combination of these predictor variables. We found that geographic variation, magnitude and direction of turtle SSD are best explained by habitat association, annual temperature variance and annual precipitation. Use of semi-aquatic and terrestrial habitats was associated with male-biased SSD, whereas use of aquatic habitat was associated with female-biased SSD. Our results also suggest that greater temperature variability is associated with female-biased SSD. In contrast, wetter climates are associated with male-biased SSD compared with arid climates that are associated with female-biased SSD. We also show support for a global latitudinal trend in SSD, with females being larger than males towards the poles, especially in the families Emydidae and Geoemydidae. Estimates of phylogenetic signal for both SSD and habitat type indicate that closely related species occupy similar habitats and exhibit similar direction and magnitude of SSD. These global patterns of SSD may arise from sex-specific reproductive behaviour, fecundity and sex-specific responses to environmental factors that differ among habitats and vary systematically across latitude. Thus, this study adds to our current understanding that while SSD can vary dramatically across and within turtle species under phylogenetic constraints, it may be driven, maintained and exaggerated by habitat type, climate and geographic location.
","language":"English","publisher":"Wiley","doi":"10.1111/jeb.13223","usgsCitation":"Agha, M., Ennen, J., Nowakowski, A.J., Lovich, J.E., Sweat, S.C., and Todd, B., 2018, Macroecological patterns of sexual size dimorphism in turtles of the world: Journal of Evolutionary Biology, v. 31, no. 3, p. 336-345, https://doi.org/10.1111/jeb.13223.","productDescription":"10 p.","startPage":"336","endPage":"345","ipdsId":"IP-089878","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469013,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jeb.13223","text":"Publisher Index Page"},{"id":351316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-04","publicationStatus":"PW","scienceBaseUri":"5a7c1e70e4b00f54eb2292bf","contributors":{"authors":[{"text":"Agha, Mickey","contributorId":22235,"corporation":false,"usgs":false,"family":"Agha","given":"Mickey","email":"","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false},{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":726979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ennen, Joshua R.","contributorId":60368,"corporation":false,"usgs":false,"family":"Ennen","given":"Joshua R.","affiliations":[{"id":13216,"text":"Tennessee Aquarium Conservation Institute","active":true,"usgs":false}],"preferred":false,"id":726980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nowakowski, A. Justin","contributorId":201799,"corporation":false,"usgs":false,"family":"Nowakowski","given":"A.","email":"","middleInitial":"Justin","affiliations":[{"id":36252,"text":"Department of Wildlife, Fish, and Conservation Biology, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA","active":true,"usgs":false}],"preferred":false,"id":726981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":726978,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sweat, Sarah C.","contributorId":195519,"corporation":false,"usgs":false,"family":"Sweat","given":"Sarah","email":"","middleInitial":"C.","affiliations":[{"id":13216,"text":"Tennessee Aquarium Conservation Institute","active":true,"usgs":false}],"preferred":false,"id":726983,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Todd, Brian D.","contributorId":196261,"corporation":false,"usgs":false,"family":"Todd","given":"Brian D.","affiliations":[{"id":6961,"text":"Department of Wildlife, Fish & Conservation Biology, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":726982,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70195211,"text":"70195211 - 2018 - Hypocenter relocation along the Sunda arc in Indonesia, using a 3D seismic velocity model","interactions":[],"lastModifiedDate":"2018-02-28T10:04:58","indexId":"70195211","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Hypocenter relocation along the Sunda arc in Indonesia, using a 3D seismic velocity model","docAbstract":"The tectonics of the Sunda arc region is characterized by the junction of the Eurasian and Indo‐Australian tectonic plates, causing complex dynamics to take place. High‐seismicity rates in the Indonesian region occur due to the interaction between these tectonic plates. The availability of a denser network of seismometers after the earthquakes of
Despite the importance of the Missouri River for navigation, recreation, habitat, hydroelectric power, and agriculture, relatively little is known about the basic hydroclimatology of the Missouri River basin (MRB). This is of particular concern given the droughts and floods that have occurred over the past several decades and the potential future exacerbation of these extremes by climate change. Here, observed and modeled hydroclimatic data and estimated natural flow records in the MRB are used to 1) assess the major source regions of MRB flow, 2) describe the climatic controls on streamflow in the upper and lower basins , and 3) investigate trends over the instrumental period. Analyses indicate that 72% of MRB runoff is generated by the headwaters in the upper basin and by the lowest portion of the basin near the mouth. Spring precipitation and temperature and winter precipitation impacted by changes in zonal versus meridional flow from the Pacific Ocean play key roles in surface water supply variability in the upper basin. Lower basin flow is significantly correlated with precipitation in late spring and early summer, indicative of Atlantic-influenced circulation variability affecting the flow of moisture from the Gulf of Mexico. Although increases in precipitation in the lower basin are currently overriding the effects of warming temperatures on total MRB flow, the upper basin’s long-term trend toward decreasing flows, reduction in snow versus rain fraction, and warming spring temperatures suggest that the upper basin may less often provide important flow supplements to the lower basin in the future.
","language":"English","publisher":"American Meteorology Society","doi":"10.1175/JHM-D-17-0155.1","usgsCitation":"Wise, E.K., Woodhouse, C.A., McCabe, G.J., Pederson, G.T., and St. Jacques, J., 2018, Hydroclimatology of the Missouri River basin: Journal of Hydrometeorology, v. 19, no. 1, p. 161-182, https://doi.org/10.1175/JHM-D-17-0155.1.","productDescription":"22 p.","startPage":"161","endPage":"182","ipdsId":"IP-089104","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":469027,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.17615/er6r-bm17","text":"Publisher Index Page"},{"id":351220,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Missouri River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.2197265625,\n 38.42777351132902\n ],\n [\n -91.97753906249999,\n 41.178653972331674\n ],\n [\n -94.921875,\n 43.54854811091286\n ],\n [\n -104.0185546875,\n 49.095452162534826\n ],\n [\n -111.26953125,\n 49.52520834197442\n ],\n [\n -114.43359375,\n 46.5739667965278\n ],\n [\n -104.94140625,\n 38.58252615935333\n ],\n [\n -90.2197265625,\n 38.42777351132902\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-22","publicationStatus":"PW","scienceBaseUri":"5a7acd1ae4b00f54eb20c581","contributors":{"authors":[{"text":"Wise, Erika K.","contributorId":202071,"corporation":false,"usgs":false,"family":"Wise","given":"Erika","email":"","middleInitial":"K.","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":727526,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":727527,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":727528,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":727525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"St. Jacques, Jeannine-Marie","contributorId":195063,"corporation":false,"usgs":false,"family":"St. Jacques","given":"Jeannine-Marie","affiliations":[],"preferred":false,"id":727529,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195250,"text":"70195250 - 2018 - Occupancy modeling of autonomously recorded vocalizations to predict distribution of rallids in tidal wetlands","interactions":[],"lastModifiedDate":"2018-07-13T13:03:41","indexId":"70195250","displayToPublicDate":"2018-02-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Occupancy modeling of autonomously recorded vocalizations to predict distribution of rallids in tidal wetlands","docAbstract":"Conservation and management for a species requires reliable information on its status, distribution, and habitat use. We identified occupancy and distributions of king (Rallus elegans) and clapper (R. crepitans) rail populations in marsh complexes along the Pamunkey and Mattaponi Rivers in Virginia, USA by modeling data on vocalizations recorded from autonomous recording units (ARUs). Occupancy probability for both species combined was 0.64 (95% CI: 0.53, 0.75) in marshes along the Pamunkey and 0.59 (0.45, 0.72) in marshes along the Mattaponi. Occupancy probability along the Pamunkey was strongly influenced by salinity, increasing logistically by a factor of 1.62 (0.6, 2.65) per parts per thousand of salinity. In contrast, there was not a strong salinity gradient on the Mattaponi and therefore vegetative community structure determined occupancy probability on that river. Estimated detection probability across both marshes was 0.63 (0.62, 0.65), but detection rates decreased as the season progressed. Monitoring wildlife within wetlands presents unique challenges for conservation managers. Our findings provide insight not only into how rails responded to environmental variation but also into the general utility of ARUs for occupancy modeling of the distribution and habitat associations of rails within tidal marsh systems.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-018-1003-z","usgsCitation":"Stiffler, L.L., Anderson, J.T., and Katzner, T., 2018, Occupancy modeling of autonomously recorded vocalizations to predict distribution of rallids in tidal wetlands: Wetlands, v. 38, no. 3, p. 605-612, https://doi.org/10.1007/s13157-018-1003-z.","productDescription":"8 p.","startPage":"605","endPage":"612","ipdsId":"IP-088312","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":351216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Mattaponi River, Pamunkey River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.96678161621094,\n 37.51190453731693\n ],\n [\n -76.75804138183594,\n 37.51190453731693\n ],\n [\n -76.75804138183594,\n 37.6359849542696\n ],\n [\n -76.96678161621094,\n 37.6359849542696\n ],\n [\n -76.96678161621094,\n 37.51190453731693\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-22","publicationStatus":"PW","scienceBaseUri":"5a7acd15e4b00f54eb20c576","contributors":{"authors":[{"text":"Stiffler, Lydia L.","contributorId":198904,"corporation":false,"usgs":false,"family":"Stiffler","given":"Lydia","email":"","middleInitial":"L.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false},{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":727616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, James T.","contributorId":28071,"corporation":false,"usgs":false,"family":"Anderson","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":727617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":727615,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70195228,"text":"70195228 - 2018 - Investigating runoff efficiency in upper Colorado River streamflow over past centuries","interactions":[],"lastModifiedDate":"2018-02-22T12:50:21","indexId":"70195228","displayToPublicDate":"2018-02-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Investigating runoff efficiency in upper Colorado River streamflow over past centuries","docAbstract":"With increasing concerns about the impact of warming temperatures on water resources, more attention is being paid to the relationship between runoff and precipitation, or runoff efficiency. Temperature is a key influence on Colorado River runoff efficiency, and warming temperatures are projected to reduce runoff efficiency. Here, we investigate the nature of runoff efficiency in the upper Colorado River (UCRB) basin over the past 400 years, with a specific focus on major droughts and pluvials, and to contextualize the instrumental period. We first verify the feasibility of reconstructing runoff efficiency from tree-ring data. The reconstruction is then used to evaluate variability in runoff efficiency over periods of high and low flow, and its correspondence to a reconstruction of late runoff season UCRB temperature variability. Results indicate that runoff efficiency has played a consistent role in modulating the relationship between precipitation and streamflow over past centuries, and that temperature has likely been the key control. While negative runoff efficiency is most common during dry periods, and positive runoff efficiency during wet years, there are some instances of positive runoff efficiency moderating the impact of precipitation deficits on streamflow. Compared to past centuries, the 20th century has experienced twice as many high flow years with negative runoff efficiency, likely due to warm temperatures. These results suggest warming temperatures will continue to reduce runoff efficiency in wet or dry years, and that future flows will be less than anticipated from precipitation due to warming temperatures.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017WR021663","usgsCitation":"Woodhouse, C.A., and Pederson, G.T., 2018, Investigating runoff efficiency in upper Colorado River streamflow over past centuries: Water Resources Research, v. 54, no. 1, p. 286-300, https://doi.org/10.1002/2017WR021663.","productDescription":"15 p.","startPage":"286","endPage":"300","ipdsId":"IP-082478","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":469029,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/627610","text":"External Repository"},{"id":351219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado River","volume":"54","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-23","publicationStatus":"PW","scienceBaseUri":"5a7acd18e4b00f54eb20c57e","contributors":{"authors":[{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":727535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":727534,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195239,"text":"70195239 - 2018 - Alternate wetting and drying decreases methylmercury in flooded rice (Oryza sativa) systems","interactions":[],"lastModifiedDate":"2018-09-26T15:45:04","indexId":"70195239","displayToPublicDate":"2018-02-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3420,"text":"Soil Science Society of America Journal","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Alternate wetting and drying decreases methylmercury in flooded rice (Oryza sativa) systems","title":"Alternate wetting and drying decreases methylmercury in flooded rice (Oryza sativa) systems","docAbstract":"In flooded soils, including those found in rice (Oryza sativa L.) fields, microbes convert inorganic Hg to more toxic methylmercury (MeHg). Methylmercury is accumulated in rice grain, potentially affecting health. Methylmercury in rice field surface water can bioaccumulate in wildlife. We evaluated how introducing aerobic periods into an otherwise continuously flooded rice growing season affects MeHg dynamics. Conventional continuously flooded (CF) rice field water management was compared with alternate wetting and drying, where irrigation was stopped twice during the growing season, allowing soil to dry to 35% volumetric moisture content, at which point plots were reflooded (AWD-35). Methylmercury studies began at harvest in Year 3 and throughout Year 4 of a 4-yr replicated field experiment. Bulk soil, water, and plant samples were analyzed for MeHg and total Hg (THg), and iron (Fe) speciation was measured in soil samples. Rice grain yield over 4 yr did not differ between treatments. Soil chemistry responded quickly to AWD-35 dry-downs, showing significant oxidation of Fe(II) accompanied by a significant reduction of MeHg concentration (76% reduction at harvest) compared with CF. Surface water MeHg decreased by 68 and 39% in the growing and fallow seasons, respectively, suggesting that the effects of AWD-35 management can last through to the fallow season. The AWD-35 treatment reduced rice grain MeHg and THg by 60 and 32%, respectively. These results suggest that the more aerobic conditions caused by AWD-35 limited the activity of Hg(II)-methylating microbes and may be an effective way to reduce MeHg concentrations in rice ecosystems.
","language":"English","publisher":"Soil Science Society of America","doi":"10.2136/sssaj2017.05.0158","usgsCitation":"Tanner, K.C., Windham-Myers, L., Marvin-DiPasquale, M.C., Fleck, J., and Linquist, B.A., 2018, Alternate wetting and drying decreases methylmercury in flooded rice (Oryza sativa) systems: Soil Science Society of America Journal, v. 82, p. 115-125, https://doi.org/10.2136/sssaj2017.05.0158.","productDescription":"11 p.","startPage":"115","endPage":"125","ipdsId":"IP-090343","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":469030,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2136/sssaj2017.05.0158","text":"Publisher Index Page"},{"id":351218,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"82","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-04","publicationStatus":"PW","scienceBaseUri":"5a7acd17e4b00f54eb20c57b","contributors":{"authors":[{"text":"Tanner, K. Christy","contributorId":179307,"corporation":false,"usgs":false,"family":"Tanner","given":"K.","email":"","middleInitial":"Christy","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":727579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":727580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":727578,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fleck, Jacob 0000-0002-3217-3972 jafleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-3972","contributorId":168694,"corporation":false,"usgs":true,"family":"Fleck","given":"Jacob","email":"jafleck@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":727581,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Linquist, Bruce A.","contributorId":179310,"corporation":false,"usgs":false,"family":"Linquist","given":"Bruce","email":"","middleInitial":"A.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":727582,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}