Ongoing climate change is affecting the concentration, export (flux), and timing of dissolved organic carbon (DOC) exported to the Gulf of Maine (GoM) through changes in hydrologic regime. DOC export was calculated for water years 1950 through 2013 for 20 rivers and for water years 1930 through 2013 for 14 rivers draining to the GoM. DOC export was also estimated for the 21st century based on climate and hydrologic modeling in a previously published study. DOC export was calculated by using the regression model LOADEST to fit seasonally adjusted concentration discharge (C-Q) relations. Our results are an analysis of the sensitivity of DOC export to changes in hydrologic conditions over time since land cover and vegetation were held constant over time. Despite large interannual variability, all rivers had increasing DOC export during winter and these trends were significant (p < 0.05) in 10 out of 20 rivers for 1950 to 2013 and in 13 out of 14 rivers for 1930 to 2013. All rivers also had increasing annual export of DOC although fewer trends were statistically significant than for winter export. Projections for DOC export during the 21st century were variable depending on the climate model and greenhouse gas emission scenario that affected future river discharge through effects on precipitation and evapotranspiration. The most consistent result was a significant increase in DOC export in winter in all model-by-emission scenarios. DOC export was projected to decrease during the summer in all model-by-emission scenarios, with statistically significant decreases in half of the scenarios.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015JG003314","usgsCitation":"Huntington, T.G., Balch, W.M., Aiken, G.R., Sheffield, J., Luo, L., Roesler, C.S., and Camill, P., 2016, Climate change and dissolved organic carbon export to the Gulf of Maine: Journal of Geophysical Research: Biogeosciences, v. 121, no. 10, p. 2700-2716, https://doi.org/10.1002/2015JG003314.","productDescription":"17 p.","startPage":"2700","endPage":"2716","ipdsId":"IP-071250","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":331162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Gulf of 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Justin","contributorId":69462,"corporation":false,"usgs":true,"family":"Sheffield","given":"Justin","affiliations":[],"preferred":false,"id":654170,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luo, Lifeng","contributorId":176993,"corporation":false,"usgs":false,"family":"Luo","given":"Lifeng","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":654171,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roesler, Collin S.","contributorId":152025,"corporation":false,"usgs":false,"family":"Roesler","given":"Collin","email":"","middleInitial":"S.","affiliations":[{"id":18855,"text":"Department of Earth and Oceanographic Science, Bowdoin College, Brunswick, ME","active":true,"usgs":false}],"preferred":false,"id":654172,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Camill, Philip","contributorId":176994,"corporation":false,"usgs":false,"family":"Camill","given":"Philip","email":"","affiliations":[],"preferred":false,"id":654173,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70182773,"text":"70182773 - 2016 - The timing of compositionally-zoned magma reservoirs and mafic 'priming' weeks before the 1912 Novarupta-Katmai rhyolite eruption","interactions":[],"lastModifiedDate":"2017-03-01T14:43:11","indexId":"70182773","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"The timing of compositionally-zoned magma reservoirs and mafic 'priming' weeks before the 1912 Novarupta-Katmai rhyolite eruption","docAbstract":"The June 6, 1912 eruption of more than 13 km3 of dense rock equivalent (DRE) magma at Novarupta vent, Alaska was the largest of the 20th century. It ejected >7 km3 of rhyolite, ~1.3 km3 of andesite and ~4.6 km3 of dacite. Early ideas about the origin of pyroclastic flows and magmatic differentiation (e.g., compositional zonation of reservoirs) were shaped by this eruption. Despite being well studied, the timing of events that led to the chemically and mineralogically zoned magma reservoir remain poorly known. Here we provide new insights using the textures and chemical compositions of plagioclase and orthopyroxene crystals and by reevaluating previous U-Th isotope data. Compositional zoning of the magma reservoir likely developed a few thousand years before the eruption by several additions of mafic magma below an extant silicic reservoir. Melt compositions calculated from Sr contents in plagioclase fill the compositional gap between 68 and 76% SiO2 in whole pumice clasts, consistent with uninterrupted crystal growth from a continuum of liquids. Thus, our findings support a general model in which large volumes of crystal-poor rhyolite are related to intermediate magmas through gradual separation of melt from crystal-rich mush. The rhyolite is incubated by, but not mixed with, episodic recharge pulses of mafic magma that interact thermochemically with the mush and intermediate magmas. Hot, Mg-, Ca-, and Al-rich mafic magma intruded into, and mixed with, deeper parts of the reservoir (andesite and dacite) multiple times. Modeling the relaxation of the Fe-Mg concentrations in orthopyroxene and Mg in plagioclase rims indicates that the final recharge event occurred just weeks prior to the eruption. Rapid addition of mass, volatiles, and heat from the recharge magma, perhaps aided by partial melting of cumulate mush below the andesite and dacite, pressurized the reservoir and likely propelled a ~10 km lateral dike that allowed the overlying rhyolite to reach the surface.","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2016.07.015","usgsCitation":"Singer, B.S., Costa, F., Herrin, J.S., Hildreth, W., and Fierstein, J., 2016, The timing of compositionally-zoned magma reservoirs and mafic 'priming' weeks before the 1912 Novarupta-Katmai rhyolite eruption: Earth and Planetary Science Letters, v. 451, p. 125-137, https://doi.org/10.1016/j.epsl.2016.07.015.","productDescription":"13 p. ","startPage":"125","endPage":"137","ipdsId":"IP-078234","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470525,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2016.07.015","text":"Publisher Index Page"},{"id":336778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"451","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b7eba6e4b01ccd5500bb03","contributors":{"authors":[{"text":"Singer, Brad S.","contributorId":184168,"corporation":false,"usgs":false,"family":"Singer","given":"Brad","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":673703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costa, Fidel","contributorId":184169,"corporation":false,"usgs":false,"family":"Costa","given":"Fidel","email":"","affiliations":[],"preferred":false,"id":673704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herrin, Jason S.","contributorId":184170,"corporation":false,"usgs":false,"family":"Herrin","given":"Jason","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":673705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hildreth, Wes 0000-0002-7925-4251 hildreth@usgs.gov","orcid":"https://orcid.org/0000-0002-7925-4251","contributorId":2221,"corporation":false,"usgs":true,"family":"Hildreth","given":"Wes","email":"hildreth@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":680460,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fierstein, Judith 0000-0001-8024-1426 jfierstn@usgs.gov","orcid":"https://orcid.org/0000-0001-8024-1426","contributorId":147000,"corporation":false,"usgs":true,"family":"Fierstein","given":"Judith","email":"jfierstn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":673707,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70182777,"text":"70182777 - 2016 - Inferring invasive species abundance using removal data from management actions","interactions":[],"lastModifiedDate":"2017-03-01T12:32:34","indexId":"70182777","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Inferring invasive species abundance using removal data from management actions","docAbstract":"Evaluation of the progress of management programs for invasive species is crucial for demonstrating impacts to stakeholders and strategic planning of resource allocation. Estimates of abundance before and after management activities can serve as a useful metric of population management programs. However, many methods of estimating population size are too labor intensive and costly to implement, posing restrictive levels of burden on operational programs. Removal models are a reliable method for estimating abundance before and after management using data from the removal activities exclusively, thus requiring no work in addition to management. We developed a Bayesian hierarchical model to estimate abundance from removal data accounting for varying levels of effort, and used simulations to assess the conditions under which reliable population estimates are obtained. We applied this model to estimate site-specific abundance of an invasive species, feral swine (Sus scrofa), using removal data from aerial gunning in 59 site/time-frame combinations (480–19,600 acres) throughout Oklahoma and Texas, USA. Simulations showed that abundance estimates were generally accurate when effective removal rates (removal rate accounting for total effort) were above 0.40. However, when abundances were small (<50) the effective removal rate needed to accurately estimates abundances was considerably higher (0.70). Based on our post-validation method, 78% of our site/time frame estimates were accurate. To use this modeling framework it is important to have multiple removals (more than three) within a time frame during which demographic changes are minimized (i.e., a closed population; ≤3 months for feral swine). Our results show that the probability of accurately estimating abundance from this model improves with increased sampling effort (8+ flight hours across the 3-month window is best) and increased removal rate. Based on the inverse relationship between inaccurate abundances and inaccurate removal rates, we suggest auxiliary information that could be collected and included in the model as covariates (e.g., habitat effects, differences between pilots) to improve accuracy of removal rates and hence abundance estimates.
","language":"English","publisher":"Wiley","doi":"10.1002/eap.1383","usgsCitation":"Davis, A.J., Hooten, M., Miller, R.S., Farnsworth, M.L., Lewis, J., Moxcey, M., and Pepin, K., 2016, Inferring invasive species abundance using removal data from management actions: Ecological Applications, v. 26, no. 7, p. 2339-2346, https://doi.org/10.1002/eap.1383.","productDescription":"8 p.","startPage":"2339","endPage":"2346","ipdsId":"IP-067270","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":336748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-19","publicationStatus":"PW","scienceBaseUri":"58b7eba6e4b01ccd5500bb01","contributors":{"authors":[{"text":"Davis, Amy J.","contributorId":149854,"corporation":false,"usgs":false,"family":"Davis","given":"Amy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":680416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":673716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Ryan S.","contributorId":49005,"corporation":false,"usgs":false,"family":"Miller","given":"Ryan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":680417,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farnsworth, Matthew L.","contributorId":56473,"corporation":false,"usgs":false,"family":"Farnsworth","given":"Matthew","email":"","middleInitial":"L.","affiliations":[{"id":12434,"text":"USDA, Wildlife Services, National Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":680418,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lewis, Jesse S.","contributorId":147540,"corporation":false,"usgs":false,"family":"Lewis","given":"Jesse S.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":680419,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moxcey, Michael","contributorId":187442,"corporation":false,"usgs":false,"family":"Moxcey","given":"Michael","email":"","affiliations":[],"preferred":false,"id":680420,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pepin, Kim M. 0000-0002-9931-8312","orcid":"https://orcid.org/0000-0002-9931-8312","contributorId":187441,"corporation":false,"usgs":false,"family":"Pepin","given":"Kim M.","affiliations":[],"preferred":false,"id":680421,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70177882,"text":"70177882 - 2016 - Synthesising empirical results to improve predictions of post-wildfire runoff and erosion response","interactions":[],"lastModifiedDate":"2016-10-25T15:51:47","indexId":"70177882","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Synthesising empirical results to improve predictions of post-wildfire runoff and erosion response","docAbstract":"Advances in research into wildfire impacts on runoff and erosion have demonstrated increasing complexity of controlling factors and responses, which, combined with changing fire frequency, present challenges for modellers. We convened a conference attended by experts and practitioners in post-wildfire impacts, meteorology and related research, including modelling, to focus on priority research issues. The aim was to improve our understanding of controls and responses and the predictive capabilities of models. This conference led to the eight selected papers in this special issue. They address aspects of the distinctiveness in the controls and responses among wildfire regions, spatiotemporal rainfall variability, infiltration, runoff connectivity, debris flow formation and modelling applications. Here we summarise key findings from these papers and evaluate their contribution to improving understanding and prediction of post-wildfire runoff and erosion under changes in climate, human intervention and population pressure on wildfire-prone areas.
","language":"English","publisher":"International Association of Wildland Fire","doi":"10.1071/WF16021","usgsCitation":"Shakesby, R.A., Moody, J.A., Martin, D.A., and Robichaud, P.R., 2016, Synthesising empirical results to improve predictions of post-wildfire runoff and erosion response: International Journal of Wildland Fire, v. 25, no. 3, p. 257-261, https://doi.org/10.1071/WF16021.","productDescription":"5 p.","startPage":"257","endPage":"261","ipdsId":"IP-073495","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":462069,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wf16021","text":"Publisher Index Page"},{"id":330382,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58106f98e4b0f497e7961113","contributors":{"authors":[{"text":"Shakesby, Richard A.","contributorId":176258,"corporation":false,"usgs":false,"family":"Shakesby","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":652007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moody, John A. 0000-0003-2609-364X jamoody@usgs.gov","orcid":"https://orcid.org/0000-0003-2609-364X","contributorId":771,"corporation":false,"usgs":true,"family":"Moody","given":"John","email":"jamoody@usgs.gov","middleInitial":"A.","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}],"preferred":true,"id":652006,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Deborah A. 0000-0001-8237-0838 damartin@usgs.gov","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":1900,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah","email":"damartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":652008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robichaud, Peter R.","contributorId":176259,"corporation":false,"usgs":false,"family":"Robichaud","given":"Peter","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":652009,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178381,"text":"70178381 - 2016 - Geologic history of Martian regolith breccia Northwest Africa 7034: Evidence for hydrothermal activity and lithologic diversity in the Martian crust","interactions":[],"lastModifiedDate":"2016-11-15T17:02:35","indexId":"70178381","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"Geologic history of Martian regolith breccia Northwest Africa 7034: Evidence for hydrothermal activity and lithologic diversity in the Martian crust","docAbstract":"The timing and mode of deposition for Martian regolith breccia Northwest Africa (NWA) 7034 were determined by combining petrography, shape analysis, and thermochronology. NWA 7034 is composed of igneous, impact, and brecciated clasts within a thermally annealed submicron matrix of pulverized crustal rocks and devitrified impact/volcanic glass. The brecciated clasts are likely lithified portions of Martian regolith with some evidence of past hydrothermal activity. Represented lithologies are primarily ancient crustal materials with crystallization ages as old as 4.4 Ga. One ancient zircon was hosted by an alkali-rich basalt clast, confirming that alkalic volcanism occurred on Mars very early. NWA 7034 is composed of fragmented particles that do not exhibit evidence of having undergone bed load transport by wind or water. The clast size distribution is similar to terrestrial pyroclastic deposits. We infer that the clasts were deposited by atmospheric rainout subsequent to a pyroclastic eruption(s) and/or impact event(s), although the ancient ages of igneous components favor mobilization by impact(s). Despite ancient components, the breccia has undergone a single pervasive thermal event at 500–800°C, evident by groundmass texture and concordance of ~1.5 Ga dates for bulk rock K-Ar, U-Pb in apatite, and U-Pb in metamict zircons. The 1.5 Ga age is likely a thermal event that coincides with rainout/breccia lithification. We infer that the episodic process of regolith lithification dominated sedimentary processes during the Amazonian Epoch. The absence of pre-Amazonian high-temperature metamorphic events recorded in ancient zircons indicates source domains of static southern highland crust punctuated by episodic impact modification.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016JE005143","usgsCitation":"McCubbin, F.M., Boyce, J.W., Novak-Szabo, T., Santos, A., Tartese, R., Muttik, N., Domokos, G., Vazquez, J.A., Keller, L.P., Moser, D.E., Jerolmack, D.J., Shearer, C.K., Steele, A., Elardo, S.M., Rahman, Z., Anand, M., Delhaye, T., and Agee, C.B., 2016, Geologic history of Martian regolith breccia Northwest Africa 7034: Evidence for hydrothermal activity and lithologic diversity in the Martian crust: Journal of Geophysical Research E: Planets, v. 121, no. 10, p. 2120-2149, https://doi.org/10.1002/2016JE005143.","productDescription":"30 p.","startPage":"2120","endPage":"2149","ipdsId":"IP-072126","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470534,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2016je005143","text":"External 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P.","contributorId":176886,"corporation":false,"usgs":false,"family":"Keller","given":"Lindsay","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":653889,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Moser, Desmond E.","contributorId":176887,"corporation":false,"usgs":false,"family":"Moser","given":"Desmond","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":653890,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jerolmack, Douglas J.","contributorId":78622,"corporation":false,"usgs":true,"family":"Jerolmack","given":"Douglas","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":653891,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Shearer, Charles K.","contributorId":111575,"corporation":false,"usgs":true,"family":"Shearer","given":"Charles","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":653892,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Steele, Andrew","contributorId":23830,"corporation":false,"usgs":true,"family":"Steele","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":653893,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Elardo, Stephen M.","contributorId":176891,"corporation":false,"usgs":false,"family":"Elardo","given":"Stephen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":653894,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Rahman, Zia","contributorId":176892,"corporation":false,"usgs":false,"family":"Rahman","given":"Zia","email":"","affiliations":[],"preferred":false,"id":653895,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Anand, 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now","interactions":[],"lastModifiedDate":"2018-09-13T15:42:44","indexId":"70178591","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Primary production in the Delta: Then and now","docAbstract":"To evaluate the role of restoration in the recovery of the Delta ecosystem, we need to have clear targets and performance measures that directly assess ecosystem function. Primary production is a crucial ecosystem process, which directly limits the quality and quantity of food available for secondary consumers such as invertebrates and fish. The Delta has a low rate of primary production, but it is unclear whether this was always the case. Recent analyses from the Historical Ecology Team and Delta Landscapes Project provide quantitative comparisons of the areal extent of 14 habitat types in the modern Delta versus the historical Delta (pre-1850). Here we describe an approach for using these metrics of land use change to: (1) produce the first quantitative estimates of how Delta primary production and the relative contributions from five different producer groups have been altered by large-scale drainage and conversion to agriculture; (2) convert these production estimates into a common currency so the contributions of each producer group reflect their food quality and efficiency of transfer to consumers; and (3) use simple models to discover how tidal exchange between marshes and open water influences primary production and its consumption. Application of this approach could inform Delta management in two ways. First, it would provide a quantitative estimate of how large-scale conversion to agriculture has altered the Delta's capacity to produce food for native biota. Second, it would provide restoration practitioners with a new approach—based on ecosystem function—to evaluate the success of restoration projects and gauge the trajectory of ecological recovery in the Delta region.
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J.","contributorId":51147,"corporation":false,"usgs":true,"family":"Naiman","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":654578,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Pinckney, James L.","contributorId":177090,"corporation":false,"usgs":false,"family":"Pinckney","given":"James","email":"","middleInitial":"L.","affiliations":[{"id":27670,"text":"Marine Science Program, University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":654579,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Safran, Samuel M.","contributorId":177091,"corporation":false,"usgs":false,"family":"Safran","given":"Samuel","email":"","middleInitial":"M.","affiliations":[{"id":27771,"text":"San Francisco Estuary Institute – Aquatic Science Center, Richmond, CA 94804","active":true,"usgs":false}],"preferred":false,"id":654580,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654581,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Simenstad, Charles A.","contributorId":88477,"corporation":false,"usgs":false,"family":"Simenstad","given":"Charles","email":"","middleInitial":"A.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":654582,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70182807,"text":"70182807 - 2016 - Determining the flux of methane into Hudson Canyon at the edge of methane clathrate hydrate stability","interactions":[],"lastModifiedDate":"2017-03-01T11:03:39","indexId":"70182807","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Determining the flux of methane into Hudson Canyon at the edge of methane clathrate hydrate stability","docAbstract":"Methane seeps were investigated in Hudson Canyon, the largest shelf-break canyon on the northern US Atlantic Margin. The seeps investigated are located at or updip of the nominal limit of methane clathrate hydrate stability. The acoustic identification of bubble streams was used to guide water column sampling in a 32 km2 region within the canyon's thalweg. By incorporating measurements of dissolved methane concentration with methane oxidation rates and current velocity into a steady-state box model, the total emission of methane to the water column in this region was estimated to be 12 kmol methane per day (range: 6 – 24 kmol methane per day). These analyses suggest this methane is largely retained inside the canyon walls below 300 m water depth, and that it is aerobically oxidized to near completion within the larger extent of Hudson Canyon. Based on estimated methane emissions and measured oxidation rates, the oxidation of this methane to dissolved CO2 is expected to have minimal influences on seawater pH. This article is protected by copyright. All rights reserved.","language":"English","publisher":"Wiley ","doi":"10.1002/2016GC006421","usgsCitation":"Weinsten, A., Navarrete, L., Ruppel, C., Weber, T., Leonte, M., Kellermann, M., Arrington, E., Valentine, D., Scranton, M., and Kessler, J.D., 2016, Determining the flux of methane into Hudson Canyon at the edge of methane clathrate hydrate stability: Geochemistry, Geophysics, Geosystems, v. 17, no. 10, p. 3882-3892, https://doi.org/10.1002/2016GC006421.","productDescription":"11 p. ","startPage":"3882","endPage":"3892","ipdsId":"IP-076064","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470542,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2016gc006421","text":"External Repository"},{"id":336729,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":336360,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1002/2016GC006421/full"}],"volume":"17","issue":"10","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-13","publicationStatus":"PW","scienceBaseUri":"58b7eba6e4b01ccd5500baff","contributors":{"authors":[{"text":"Weinsten, A.","contributorId":184233,"corporation":false,"usgs":false,"family":"Weinsten","given":"A.","email":"","affiliations":[],"preferred":false,"id":673828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Navarrete, L","contributorId":184234,"corporation":false,"usgs":false,"family":"Navarrete","given":"L","email":"","affiliations":[],"preferred":false,"id":673829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruppel, Carolyn D. 0000-0003-2284-6632 cruppel@usgs.gov","orcid":"https://orcid.org/0000-0003-2284-6632","contributorId":145770,"corporation":false,"usgs":true,"family":"Ruppel","given":"Carolyn D.","email":"cruppel@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":673827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weber, T.C.","contributorId":184235,"corporation":false,"usgs":false,"family":"Weber","given":"T.C.","email":"","affiliations":[],"preferred":false,"id":673830,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leonte, M.","contributorId":184236,"corporation":false,"usgs":false,"family":"Leonte","given":"M.","affiliations":[],"preferred":false,"id":673831,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kellermann, M.","contributorId":184237,"corporation":false,"usgs":false,"family":"Kellermann","given":"M.","email":"","affiliations":[],"preferred":false,"id":673832,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arrington, E.","contributorId":184238,"corporation":false,"usgs":false,"family":"Arrington","given":"E.","email":"","affiliations":[],"preferred":false,"id":673833,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Valentine, D.L.","contributorId":184239,"corporation":false,"usgs":false,"family":"Valentine","given":"D.L.","email":"","affiliations":[],"preferred":false,"id":673834,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scranton, M.L","contributorId":184240,"corporation":false,"usgs":false,"family":"Scranton","given":"M.L","email":"","affiliations":[],"preferred":false,"id":673835,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kessler, John D. 0000-0003-1097-6800","orcid":"https://orcid.org/0000-0003-1097-6800","contributorId":184241,"corporation":false,"usgs":false,"family":"Kessler","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":673836,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70184970,"text":"70184970 - 2016 - Influence of glacier runoff on ecosystem structure in Gulf of Alaska fjords","interactions":[],"lastModifiedDate":"2017-03-15T12:05:48","indexId":"70184970","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Influence of glacier runoff on ecosystem structure in Gulf of Alaska fjords","docAbstract":"To better understand the influence of glacier runoff on fjord ecosystems, we sampled oceanographic conditions, nutrients, zooplankton, forage fish and seabirds within 4 fjords in coastal areas of the Gulf Alaska. We used generalized additive models and geostatistics to identify the range of glacier runoff influence into coastal waters within fjords of varying estuarine influence and topographic complexity. We also modeled the response of depth-integrated chlorophyll a concentration, copepod biomass, fish and seabird abundance to physical, nutrient and biotic predictor variables. The effects of glacial runoff were traced at least 10 km into coastal fjords by cold, turbid, stratified and generally nutrient-rich near-surface conditions. Glacially modified physical gradients, nutrient availability and among-fjord differences explained 67% of the variation in phytoplankton abundance, which is a driver of ecosystem structure at higher trophic levels. Copepod, euphausiid, fish and seabird distribution and abundance were related to environmental gradients that could be traced to glacial freshwater input, particularly turbidity and temperature. Seabird density was predicted by prey availability and silicate concentrations, which may be a proxy for upwelling areas where this nutrient is in excess. Similarities in ecosystem structure among fjords were attributable to an influx of cold, fresh and sediment-laden water, whereas differences were likely related to fjord topography and local differences in estuarine vs. ocean influence. We anticipate that continued changes in the timing and volume of glacial runoff will ultimately alter coastal ecosystems in the future.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps11888","usgsCitation":"Arimitsu, M.L., Piatt, J.F., and Mueter, F.J., 2016, Influence of glacier runoff on ecosystem structure in Gulf of Alaska fjords: Marine Ecology Progress Series, v. 560, p. 19-40, https://doi.org/10.3354/meps11888.","productDescription":"22 p.","startPage":"19","endPage":"40","ipdsId":"IP-066857","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":470531,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps11888","text":"Publisher Index Page"},{"id":438542,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PZ57P7","text":"USGS data release","linkHelpText":"Kuskokwim Bay chum salmon (Oncorhynchus keta) energy density, distribution, and stomach data, 2004"},{"id":438541,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K072DR","text":"USGS data release","linkHelpText":"Influence of Glacier Runoff on Ecosystem Structure in Gulf of Alaska Fjords 2004-2011"},{"id":337612,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.326171875,\n 57.314657355733274\n ],\n [\n -134.6484375,\n 57.314657355733274\n ],\n [\n -134.6484375,\n 61.52269494598361\n ],\n [\n -149.326171875,\n 61.52269494598361\n ],\n [\n -149.326171875,\n 57.314657355733274\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"560","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ca52cee4b0849ce97c86ac","contributors":{"authors":[{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":683772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":684475,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueter, Franz J.","contributorId":131144,"corporation":false,"usgs":false,"family":"Mueter","given":"Franz","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":684476,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70177878,"text":"70177878 - 2016 - Dynamic distributions and population declines of Golden-winged Warblers","interactions":[],"lastModifiedDate":"2020-08-25T17:09:33.774891","indexId":"70177878","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesTitle":{"id":5103,"text":"Studies in Avian Biology","printIssn":"0197-9922","active":true,"publicationSubtype":{"id":24}},"chapter":"1","title":"Dynamic distributions and population declines of Golden-winged Warblers","docAbstract":"With an estimated breeding population in 2010 of 383,000 pairs, the Golden-winged Warbler (Vermivora chrysoptera) is among the most vulnerable and steeply declining of North American passerines. This species also has exhibited among the most dynamic breeding distributions, with populations expanding and then contracting over the past 150 years in response to regional habitat changes, interactions with closely related Blue-winged Warblers (V. cyanoptera), and possibly climate change. Since 1966, the rangewide population has declined by >70% (-2.3% per year; latest North American Breeding Bird Survey data), with much steeper declines in the Appalachian Mountains bird conservation region (-8.3% per year, 98% overall decline). Despite apparently stable or increasing populations in the northwestern part of the range (Minnesota, Manitoba), population estimates for Golden-winged Warbler have continued to decline by 18% from the decade of the 1990s to the 2000s. Population modeling predicts a further decline to roughly 37,000 individuals by 2100, with the species likely to persist only in Manitoba, Minnesota, and possibly Ontario. To delineate the present-day distribution and to identify population concentrations that could serve as conservation focus areas, we compiled rangewide survey data collected in 2000-2006 in 21 states and 3 Canadian provinces, as part of the Golden-winged Warbler Atlas Project (GOWAP), supplemented by state and provincial Breeding Bird Atlas data and more recent observations in eBird. Based on >8,000 GOWAP surveys for Golden-winged and Blue-winged warblers and their hybrids, we mapped occurrence of phenotypically pure and mixed populations in a roughly 0.5-degree grid across the species’ ranges. Hybrids and mixed Golden-winged-Blue-winged populations occurred in a relatively narrow zone across Minnesota, Wisconsin, Michigan, southern Ontario, and northern New York. Phenotypically pure Golden-winged Warbler populations occurred north of this hybrid zone, but the future of northern populations in the Great Lakes states and Canada (where >80% of the species occurs at present) is highly uncertain because of continued northward expansion of Blue-winged Warblers and hybridization. A second, now-disjunct band of Golden-winged Warbler populations exists in the Appalachian Mountains from southeastern New York to northern Georgia, surrounded at lower elevations by Blue-winged Warblers. Important concentrations of Golden-winged Warblers persist in the Allegheny Mountains region of West Virginia, the Cumberland Mountains in Tennessee, Blue Ridge Mountains of western North Carolina, Allegheny Plateau and Pocono Mountains in Pennsylvania, and in the Hudson Highlands of southern New York. These high-elevation Appalachian populations have escaped contact with Blue-winged Warblers until very recently and represent important refugia for conservation and management; other Appalachian populations are rapidly declining. In addition, based on historical records and standardized surveys across the wintering grounds, we identified three regions of concentration: highlands and Caribbean slopes from Guatemala and Belize to northwestern Nicaragua; middle elevations (both slopes) in Costa Rica and western Panama; and in an arc of the northern Andes from central Colombia to northern Venezuela. It is possible that the winter range has been shifting towards the northwest in recent decades, paralleling shifts in the breeding distribution. Future conservation efforts for Golden-winged Warbler need to include close monitoring of the dynamic phenotypic and genetic distributional shifts, and may need to consider the “winged warbler” complex together as a highly adaptable evolutionary unit.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Golden-winged Warbler ecology, conservation, and habitat management (Studies in Avian Biology, volume 49)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CRC Press","publisherLocation":"Boca Raton, FL","isbn":"978-1-4822-4068-9","usgsCitation":"Rosenberg, K.V., Will, T., Buehler, D.A., Barker Swarthout, S., Thogmartin, W.E., Bennett, R.E., and Chandler, R., 2016, Dynamic distributions and population declines of Golden-winged Warblers, chap. 1 of Golden-winged Warbler ecology, conservation, and habitat management (Studies in Avian Biology, volume 49): Studies in Avian Biology, v. 49, p. 3-28.","productDescription":"26 p.","startPage":"3","endPage":"28","ipdsId":"IP-059605","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":330436,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":330361,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/11299/189700"}],"volume":"49","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5811c0f2e4b0f497e79a5a6b","contributors":{"authors":[{"text":"Rosenberg, Kenneth V.","contributorId":171463,"corporation":false,"usgs":false,"family":"Rosenberg","given":"Kenneth","email":"","middleInitial":"V.","affiliations":[{"id":27615,"text":"Cornell Lab of Ornithology, Conservation Science Program","active":true,"usgs":false}],"preferred":false,"id":651970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Will, Tom","contributorId":149777,"corporation":false,"usgs":false,"family":"Will","given":"Tom","email":"","affiliations":[{"id":17821,"text":"U.S. Fish and Wildlife Service, Division of Migratory Birds","active":true,"usgs":false}],"preferred":false,"id":651971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buehler, David A.","contributorId":169746,"corporation":false,"usgs":false,"family":"Buehler","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":651972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barker Swarthout, Sara","contributorId":176239,"corporation":false,"usgs":false,"family":"Barker Swarthout","given":"Sara","email":"","affiliations":[{"id":34544,"text":"Cornell Lab of Ornithology, Cornell University","active":true,"usgs":false}],"preferred":false,"id":651973,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":651969,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bennett, Ruth E.","contributorId":94622,"corporation":false,"usgs":false,"family":"Bennett","given":"Ruth","email":"","middleInitial":"E.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":709867,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chandler, Richard rchandler@usgs.gov","contributorId":2511,"corporation":false,"usgs":true,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","affiliations":[{"id":13266,"text":"Warnell School of Forestry and Natural Resources, The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":709868,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70178440,"text":"70178440 - 2016 - Testing fault growth models with low-temperature thermochronology in the northwest Basin and Range, USA","interactions":[],"lastModifiedDate":"2016-11-21T14:36:13","indexId":"70178440","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Testing fault growth models with low-temperature thermochronology in the northwest Basin and Range, USA","docAbstract":"Common fault growth models diverge in predicting how faults accumulate displacement and lengthen through time. A paucity of field-based data documenting the lateral component of fault growth hinders our ability to test these models and fully understand how natural fault systems evolve. Here we outline a framework for using apatite (U-Th)/He thermochronology (AHe) to quantify the along-strike growth of faults. To test our framework, we first use a transect in the normal fault-bounded Jackson Mountains in the Nevada Basin and Range Province, then apply the new framework to the adjacent Pine Forest Range. We combine new and existing cross sections with 18 new and 16 existing AHe cooling ages to determine the spatiotemporal variability in footwall exhumation and evaluate models for fault growth. Three age-elevation transects in the Pine Forest Range show that rapid exhumation began along the range-front fault between approximately 15 and 11 Ma at rates of 0.2–0.4 km/Myr, ultimately exhuming approximately 1.5–5 km. The ages of rapid exhumation identified at each transect lie within data uncertainty, indicating concomitant onset of faulting along strike. We show that even in the case of growth by fault-segment linkage, the fault would achieve its modern length within 3–4 Myr of onset. Comparison with the Jackson Mountains highlights the inadequacies of spatially limited sampling. A constant fault-length growth model is the best explanation for our thermochronology results. We advocate that low-temperature thermochronology can be further utilized to better understand and quantify fault growth with broader implications for seismic hazard assessments and the coevolution of faulting and topography.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016TC004211","usgsCitation":"Curry, M.A., Barnes, J., and Colgan, J.P., 2016, Testing fault growth models with low-temperature thermochronology in the northwest Basin and Range, USA: Tectonics, v. 35, no. 10, p. 2467-2492, https://doi.org/10.1002/2016TC004211.","productDescription":"26 p.","startPage":"2467","endPage":"2492","ipdsId":"IP-064596","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":331170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-29","publicationStatus":"PW","scienceBaseUri":"583415b3e4b0070c0abed824","contributors":{"authors":[{"text":"Curry, Magdalena A. E.","contributorId":176959,"corporation":false,"usgs":false,"family":"Curry","given":"Magdalena","email":"","middleInitial":"A. E.","affiliations":[],"preferred":false,"id":654183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnes, Jason B.","contributorId":8877,"corporation":false,"usgs":true,"family":"Barnes","given":"Jason B.","affiliations":[],"preferred":false,"id":654184,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colgan, Joseph P. 0000-0001-6671-1436 jcolgan@usgs.gov","orcid":"https://orcid.org/0000-0001-6671-1436","contributorId":1649,"corporation":false,"usgs":true,"family":"Colgan","given":"Joseph","email":"jcolgan@usgs.gov","middleInitial":"P.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":654185,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70179072,"text":"70179072 - 2016 - A case study on evaluating impacts of potential climate change on groundwater resources: Groundwater recharge in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2016-12-20T11:43:51","indexId":"70179072","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"A case study on evaluating impacts of potential climate change on groundwater resources: Groundwater recharge in the Upper Colorado River Basin","docAbstract":"An investigation of the change in groundwater recharge in response to potential climate change\nwas performed for the UCRB using the SWB groundwater recharge model and downscaled\nclimate data from the CMIP5 multi-model dataset. Climate projections from 97 downscaled\nCMIP5 datasets were assumed to be equally likely and recharge simulation results were\ncombined. Results for the UCRB suggest that projected increases in actual ET from higher\ntemperatures may be offset by increases in precipitation, resulting in increased groundwater\nrecharge for many areas in the basin in future time periods.","language":"English","publisher":"Bureau of Reclamation","collaboration":"Bureau of Reclamation","usgsCitation":"Tillman, F.D., Gangopadhyay, S., and Pruitt, T., 2016, A case study on evaluating impacts of potential climate change on groundwater resources: Groundwater recharge in the Upper Colorado River Basin, ii., 20 p.","productDescription":"ii., 20 p.","ipdsId":"IP-066612","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":332339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":332146,"type":{"id":15,"text":"Index Page"},"url":"https://www.usbr.gov/watersmart/wcra/docs/techmemoclimatechangeongroundwaterresources.pdf"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.2802734375,\n 37.142803443716836\n ],\n [\n -110.3466796875,\n 39.50404070558415\n ],\n [\n -107.81982421874999,\n 40.111688665595956\n ],\n [\n -105.556640625,\n 39.8928799002948\n ],\n [\n -106.01806640624999,\n 37.03763967977139\n ],\n [\n -108.25927734375,\n 36.50963615733049\n ],\n [\n -112.30224609374999,\n 36.70365959719456\n ],\n [\n -112.2802734375,\n 37.142803443716836\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"585a51bee4b01224f329b5e7","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":655926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":655927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pruitt, Tom 0000-0002-3543-1324","orcid":"https://orcid.org/0000-0002-3543-1324","contributorId":173440,"corporation":false,"usgs":false,"family":"Pruitt","given":"Tom","email":"","affiliations":[{"id":27228,"text":"Reclamation","active":true,"usgs":false}],"preferred":false,"id":655928,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70177855,"text":"70177855 - 2016 - Seismic imaging beneath an InSAR anomaly in eastern Washington State: Shallow faulting associated with an earthquake swarm in a low-hazard area","interactions":[],"lastModifiedDate":"2016-10-25T10:05:35","indexId":"70177855","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Seismic imaging beneath an InSAR anomaly in eastern Washington State: Shallow faulting associated with an earthquake swarm in a low-hazard area","docAbstract":"In 2001, a rare swarm of small, shallow earthquakes beneath the city of Spokane, Washington, caused ground shaking as well as audible booms over a five‐month period. Subsequent Interferometric Synthetic Aperture Radar (InSAR) data analysis revealed an area of surface uplift in the vicinity of the earthquake swarm. To investigate the potential faults that may have caused both the earthquakes and the topographic uplift, we collected ∼3 km of high‐resolution seismic‐reflection profiles to image the upper‐source region of the swarm. The two profiles reveal a complex deformational pattern within Quaternary alluvial, fluvial, and flood deposits, underlain by Tertiary basalts and basin sediments. At least 100 m of arching on a basalt surface in the upper 500 m is interpreted from both the seismic profiles and magnetic modeling. Two west‐dipping faults deform Quaternary sediments and project to the surface near the location of the Spokane fault defined from modeling of the InSAR data.
","language":"English","publisher":" Seismological Society of America","doi":"10.1785/0120150295","usgsCitation":"Stephenson, W.J., Odum, J., Wicks, C.W., Pratt, T.L., and Blakely, R.J., 2016, Seismic imaging beneath an InSAR anomaly in eastern Washington State: Shallow faulting associated with an earthquake swarm in a low-hazard area: Bulletin of the Seismological Society of America, v. 106, no. 4, p. 1461-1469, https://doi.org/10.1785/0120150295.","productDescription":"9 p.","startPage":"1461","endPage":"1469","ipdsId":"IP-074071","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":330355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","volume":"106","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-21","publicationStatus":"PW","scienceBaseUri":"58106f98e4b0f497e7961115","contributors":{"authors":[{"text":"Stephenson, William J. 0000-0001-8699-0786 wstephens@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-0786","contributorId":695,"corporation":false,"usgs":true,"family":"Stephenson","given":"William","email":"wstephens@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":651942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Odum, Jackson K. 0000-0003-4697-2430 odum@usgs.gov","orcid":"https://orcid.org/0000-0003-4697-2430","contributorId":1365,"corporation":false,"usgs":true,"family":"Odum","given":"Jackson K.","email":"odum@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":651943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wicks, Charles W. Jr. 0000-0002-0809-1328 cwicks@usgs.gov","orcid":"https://orcid.org/0000-0002-0809-1328","contributorId":127701,"corporation":false,"usgs":true,"family":"Wicks","given":"Charles","suffix":"Jr.","email":"cwicks@usgs.gov","middleInitial":"W.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":651944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pratt, Thomas L. 0000-0003-3131-3141 tpratt@usgs.gov","orcid":"https://orcid.org/0000-0003-3131-3141","contributorId":3279,"corporation":false,"usgs":true,"family":"Pratt","given":"Thomas","email":"tpratt@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":651945,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blakely, Richard J. 0000-0003-1701-5236 blakely@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":1540,"corporation":false,"usgs":true,"family":"Blakely","given":"Richard","email":"blakely@usgs.gov","middleInitial":"J.","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":651946,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70185037,"text":"70185037 - 2016 - Integrating seasonal information on nutrients and benthic algal biomass into stream water quality monitoring","interactions":[],"lastModifiedDate":"2017-03-13T16:40:31","indexId":"70185037","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","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":"Integrating seasonal information on nutrients and benthic algal biomass into stream water quality monitoring","docAbstract":"Benthic chlorophyll a (BChl a) and environmental factors that influence algal biomass were measured monthly from February through October in 22 streams from three agricultural regions of the United States. At-site maximum BChl a ranged from 14 to 406 mg/m2 and generally varied with dissolved inorganic nitrogen (DIN): 8 out of 9 sites with at-site median DIN >0.5 mg/L had maximum BChl a >100 mg/m2. BChl aaccrued and persisted at levels within 50% of at-site maximum for only one to three months. No dominant seasonal pattern for algal biomass accrual was observed in any region. A linear model with DIN, water surface gradient, and velocity accounted for most of the cross-site variation in maximum chlorophyll a(adjusted R2 = 0.7), but was no better than a single value of DIN = 0.5 mg/L for distinguishing between low and high-biomass sites. Studies of nutrient enrichment require multiple samples to estimate algal biomass with sufficient precision given the magnitude of temporal variability of algal biomass. An effective strategy for regional stream assessment of nutrient enrichment could be based on a relation between maximum BChl a and DIN based on repeat sampling at sites selected to represent a gradient in nutrients and application of the relation to a larger number of sites with synoptic nutrient information.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12451","usgsCitation":"Konrad, C.P., and Munn, M.D., 2016, Integrating seasonal information on nutrients and benthic algal biomass into stream water quality monitoring: Journal of the American Water Resources Association, v. 52, no. 5, p. 1223-1237, https://doi.org/10.1111/1752-1688.12451.","productDescription":"15 p.","startPage":"1223","endPage":"1237","ipdsId":"IP-072819","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":470532,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12451","text":"Publisher Index Page"},{"id":337474,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-22","publicationStatus":"PW","scienceBaseUri":"58c7afa0e4b0849ce9795e9a","contributors":{"authors":[{"text":"Konrad, Christopher P. 0000-0002-7354-547X cpkonrad@usgs.gov","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":1716,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","email":"cpkonrad@usgs.gov","middleInitial":"P.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":684031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munn, Mark D. 0000-0002-7154-7252 mdmunn@usgs.gov","orcid":"https://orcid.org/0000-0002-7154-7252","contributorId":976,"corporation":false,"usgs":true,"family":"Munn","given":"Mark","email":"mdmunn@usgs.gov","middleInitial":"D.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":684032,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70177821,"text":"70177821 - 2016 - Ontogenetic development of otoliths in Alligator Gar","interactions":[],"lastModifiedDate":"2016-10-24T09:34:25","indexId":"70177821","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Ontogenetic development of otoliths in Alligator Gar","docAbstract":"The Alligator Gar Atractosteus spatula is a species of conservation concern throughout its range, and better definition of otoliths during early development would aid understanding its life history and ecology. We conducted X-ray computed tomography scans, scanning electron microscopy, and light microscopy to examine the three pairs of otoliths and how they developed over time in relation to fish size and age. The sagittae are the largest, possessing distinct dorsal and ventral lobes covered with small otoconia concentrated in the sulcul region. The sagittae exhibited allometric growth, increasing more rapidly in the ventral lobe than in the dorsal. The asterisci were smaller and also exhibited small otoconia on their surface, but much less than the sagittae. The lapilli were oriented laterally, in contrast to the sagittae and asterisci, which were oriented vertically, with a hump on the dorsum and very large otoconia on the lateral surface that appeared to fuse into the main otolith as the fish grew. Based on size measurements and ring counts in all three pairs of otoliths from 101 known-age Alligator Gar sampled weekly through 91 d after hatch, we developed regression models to examine otolith growth and predict age. All relationships were significant and highly explanatory, but the strongest relationships were between otolith and fish size (for measurements from sagittae) and for age predictions from the lapillus. Age prediction models all resulted in a slope near unity, indicating that ring deposition occurred approximately daily. The first ring in sagittae and lapilli corresponded to swim-up, whereas the first ring formed in asterisci approximately 8 d after swim-up. These results fill a gap in knowledge and can aid understanding of evolutionary processes as well as provide useful information for management and conservation.
","language":"English","publisher":"Taylor & Frances","doi":"10.1080/00028487.2015.1135189","usgsCitation":"Long, J.M., and Snow, R.A., 2016, Ontogenetic development of otoliths in Alligator Gar: Transactions of the American Fisheries Society, v. 145, no. 3, p. 537-544, https://doi.org/10.1080/00028487.2015.1135189.","productDescription":"8 p.","startPage":"537","endPage":"544","ipdsId":"IP-058724","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":330339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"145","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-19","publicationStatus":"PW","scienceBaseUri":"580f1db9e4b0f497e794e4cf","contributors":{"authors":[{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":651896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snow, Richard A.","contributorId":176213,"corporation":false,"usgs":false,"family":"Snow","given":"Richard","email":"","middleInitial":"A.","affiliations":[{"id":27443,"text":"Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":651909,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70160312,"text":"70160312 - 2016 - Expert elicitation of population-level effects of disturbance","interactions":[],"lastModifiedDate":"2016-10-13T14:14:04","indexId":"70160312","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Expert elicitation of population-level effects of disturbance","docAbstract":"Expert elicitation is a rigorous method for synthesizing expert knowledge to inform decision making and is reliable and practical when field data are limited. We evaluated the feasibility of applying expert elicitation to estimate population-level effects of disturbance on marine mammals. Diverse experts estimated parameters related to mortality and sublethal injury of North Atlantic right whales (Eubalaena glacialis). We are now eliciting expert knowledge on the movement of right whales among geographic regions to parameterize a spatial model of health. Expert elicitation complements methods such as simulation models or extrapolations from other species, sometimes with greater accuracy and less uncertainty.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The effects of noise on aquatic life II","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-1-4939-2981-8_35","usgsCitation":"Fleishman, E., Burgman, M., Runge, M.C., Schick, R.S., and Krauss, S., 2016, Expert elicitation of population-level effects of disturbance, chap. of The effects of noise on aquatic life II, v. 875, p. 295-302, https://doi.org/10.1007/978-1-4939-2981-8_35.","productDescription":"8 p.","startPage":"295","endPage":"302","ipdsId":"IP-071243","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":329543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"875","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57ffdefee4b0824b2d179cf2","contributors":{"editors":[{"text":"Popper, Arthur N.","contributorId":175351,"corporation":false,"usgs":false,"family":"Popper","given":"Arthur","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":650845,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Hawkins, Anthony","contributorId":175352,"corporation":false,"usgs":false,"family":"Hawkins","given":"Anthony","email":"","affiliations":[],"preferred":false,"id":650846,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Fleishman, Erica","contributorId":11863,"corporation":false,"usgs":true,"family":"Fleishman","given":"Erica","affiliations":[],"preferred":false,"id":582502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burgman, Mark","contributorId":150633,"corporation":false,"usgs":false,"family":"Burgman","given":"Mark","email":"","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":582503,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":582501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schick, Robert S","contributorId":149294,"corporation":false,"usgs":false,"family":"Schick","given":"Robert","email":"","middleInitial":"S","affiliations":[{"id":12470,"text":"University of St. Andrews","active":true,"usgs":false}],"preferred":false,"id":582504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krauss, Scott","contributorId":43250,"corporation":false,"usgs":true,"family":"Krauss","given":"Scott","affiliations":[],"preferred":false,"id":582505,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188067,"text":"70188067 - 2016 - Forecasting climate change impacts on plant populations over large spatial extents","interactions":[],"lastModifiedDate":"2018-03-08T12:59:33","indexId":"70188067","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting climate change impacts on plant populations over large spatial extents","docAbstract":"Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. We overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1525","usgsCitation":"Tredennick, A.T., Hooten, M., Aldridge, C.L., Homer, C.G., Kleinhesselink, A.R., and Adler, P.B., 2016, Forecasting climate change impacts on plant populations over large spatial extents: Ecosphere, v. 7, no. 10, e01525; 16 p., https://doi.org/10.1002/ecs2.1525.","productDescription":"e01525; 16 p.","ipdsId":"IP-071731","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":470538,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1525","text":"Publisher Index Page"},{"id":341852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","volume":"7","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-24","publicationStatus":"PW","scienceBaseUri":"592e84b9e4b092b266f10d30","contributors":{"authors":[{"text":"Tredennick, Andrew T.","contributorId":152688,"corporation":false,"usgs":false,"family":"Tredennick","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":18962,"text":"Dept. of Wildland Resources and the Ecology Center, Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":696411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":696382,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":696412,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696413,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kleinhesselink, Andrew R.","contributorId":192387,"corporation":false,"usgs":false,"family":"Kleinhesselink","given":"Andrew","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":696414,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adler, Peter B.","contributorId":64789,"corporation":false,"usgs":false,"family":"Adler","given":"Peter","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":696415,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191981,"text":"70191981 - 2016 - Efficacy of GPS cluster analysis for predicting carnivory sites of a wide-ranging omnivore: the American black bear","interactions":[],"lastModifiedDate":"2017-10-19T10:50:38","indexId":"70191981","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Efficacy of GPS cluster analysis for predicting carnivory sites of a wide-ranging omnivore: the American black bear","docAbstract":"The capacity to describe and quantify predation by large carnivores expanded considerably with the advent of GPS technology. Analyzing clusters of GPS locations formed by carnivores facilitates the detection of predation events by identifying characteristics which distinguish predation sites. We present a performance assessment of GPS cluster analysis as applied to the predation and scavenging of an omnivore, the American black bear (Ursus americanus), on ungulate prey and carrion. Through field investigations of 6854 GPS locations from 24 individual bears, we identified 54 sites where black bears formed a cluster of locations while predating or scavenging elk (Cervus elaphus), mule deer (Odocoileus hemionus), or cattle (Bos spp.). We developed models for three data sets to predict whether a GPS cluster was formed at a carnivory site vs. a non-carnivory site (e.g., bed sites or non-ungulate foraging sites). Two full-season data sets contained GPS locations logged at either 3-h or 30-min intervals from April to November, and a third data set contained 30-min interval data from April through July corresponding to the calving period for elk. Longer fix intervals resulted in the detection of fewer carnivory sites. Clusters were more likely to be carnivory sites if they occurred in open or edge habitats, if they occurred in the early season, if the mean distance between all pairs of GPS locations within the cluster was less, and if the cluster endured for a longer period of time. Clusters were less likely to be carnivory sites if they were initiated in the morning or night compared to the day. The top models for each data set performed well and successfully predicted 71–96% of field-verified carnivory events, 55–75% of non–carnivory events, and 58–76% of clusters overall. Refinement of this method will benefit from further application across species and ecological systems.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1513","usgsCitation":"Kindschuh, S.R., Cain, J.W., Daniel, D., and Peyton, M.A., 2016, Efficacy of GPS cluster analysis for predicting carnivory sites of a wide-ranging omnivore: the American black bear: Ecosphere, v. 7, no. 10, p. 1-17, https://doi.org/10.1002/ecs2.1513.","productDescription":"e01513; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-074517","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470521,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1513","text":"Publisher Index Page"},{"id":346948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Jemez Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.93954467773438,\n 35.53781387714839\n ],\n [\n -106.39434814453125,\n 35.53781387714839\n ],\n [\n -106.39434814453125,\n 35.99578538642032\n ],\n [\n -106.93954467773438,\n 35.99578538642032\n ],\n [\n -106.93954467773438,\n 35.53781387714839\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-19","publicationStatus":"PW","scienceBaseUri":"59e9b997e4b05fe04cd65ccb","contributors":{"authors":[{"text":"Kindschuh, Sarah R.","contributorId":197601,"corporation":false,"usgs":false,"family":"Kindschuh","given":"Sarah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":713887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":713808,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daniel, David","contributorId":197602,"corporation":false,"usgs":false,"family":"Daniel","given":"David","email":"","affiliations":[],"preferred":false,"id":713888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peyton, Mark A.","contributorId":197603,"corporation":false,"usgs":false,"family":"Peyton","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":713889,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189515,"text":"70189515 - 2016 - A synthesis of terrestrial mercury in the western United States: Spatial distribution defined by land cover and plant productivity","interactions":[],"lastModifiedDate":"2020-09-01T14:28:24.754124","indexId":"70189515","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","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":"A synthesis of terrestrial mercury in the western United States: Spatial distribution defined by land cover and plant productivity","docAbstract":"A synthesis of published vegetation mercury (Hg) data across 11 contiguous states in the western United States showed that aboveground biomass concentrations followed the order: leaves (26 μg kg− 1) ~ branches (26 μg kg− 1) > bark (16 μg kg− 1) > bole wood (1 μg kg− 1). No spatial trends of Hg in aboveground biomass distribution were detected, which likely is due to very sparse data coverage and different sampling protocols. Vegetation data are largely lacking for important functional vegetation types such as shrubs, herbaceous species, and grasses.
Soil concentrations collected from the published literature were high in the western United States, with 12% of observations exceeding 100 μg kg− 1, reflecting a bias toward investigations in Hg-enriched sites. In contrast, soil Hg concentrations from a randomly distributed data set (1911 sampling points; Smith et al., 2013a) averaged 24 μg kg− 1 (A-horizon) and 22 μg kg− 1 (C-horizon), and only 2.6% of data exceeded 100 μg kg− 1. Soil Hg concentrations significantly differed among land covers, following the order: forested upland > planted/cultivated > herbaceous upland/shrubland > barren soils. Concentrations in forests were on average 2.5 times higher than in barren locations. Principal component analyses showed that soil Hg concentrations were not or weakly related to modeled dry and wet Hg deposition and proximity to mining, geothermal areas, and coal-fired power plants. Soil Hg distribution also was not closely related to other trace metals, but strongly associated with organic carbon, precipitation, canopy greenness, and foliar Hg pools of overlying vegetation. These patterns indicate that soil Hg concentrations are related to atmospheric deposition and reflect an overwhelming influence of plant productivity — driven by water availability — with productive landscapes showing high soil Hg accumulation and unproductive barren soils and shrublands showing low soil Hg values. Large expanses of low-productivity, arid ecosystems across the western U.S. result in some of the lowest soil Hg concentrations observed worldwide.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2015.11.104","usgsCitation":"Obrist, D., Pearson, C., Webster, J., Kane, T., Lin, C., Aiken, G.R., and Alpers, C.N., 2016, A synthesis of terrestrial mercury in the western United States: Spatial distribution defined by land cover and plant productivity: Science of the Total Environment, v. 568, p. 522-535, https://doi.org/10.1016/j.scitotenv.2015.11.104.","productDescription":"14 p.","startPage":"522","endPage":"535","ipdsId":"IP-070736","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":470615,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2015.11.104","text":"Publisher Index Page"},{"id":343856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"568","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5969d82ae4b0d1f9f060a184","contributors":{"authors":[{"text":"Obrist, Daniel","contributorId":172155,"corporation":false,"usgs":false,"family":"Obrist","given":"Daniel","email":"","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":704988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearson, Christopher","contributorId":49278,"corporation":false,"usgs":true,"family":"Pearson","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":704989,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webster, Jackson","contributorId":172157,"corporation":false,"usgs":false,"family":"Webster","given":"Jackson","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":704990,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kane, Tyler J. 0000-0003-2511-7312","orcid":"https://orcid.org/0000-0003-2511-7312","contributorId":194675,"corporation":false,"usgs":false,"family":"Kane","given":"Tyler J.","affiliations":[],"preferred":false,"id":704991,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lin, Che-Jen","contributorId":167257,"corporation":false,"usgs":false,"family":"Lin","given":"Che-Jen","email":"","affiliations":[{"id":24666,"text":"Lamar University","active":true,"usgs":false}],"preferred":false,"id":704992,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704993,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704994,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70192639,"text":"70192639 - 2016 - The extra mile: Ungulate migration distance alters the use of seasonal range and exposure to anthropogenic risk","interactions":[],"lastModifiedDate":"2017-11-08T15:55:53","indexId":"70192639","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"The extra mile: Ungulate migration distance alters the use of seasonal range and exposure to anthropogenic risk","docAbstract":"Partial migration occurs across a variety of taxa and has important ecological and evolutionary consequences. Among ungulates, studies of partially migratory populations have allowed researchers to compare and contrast performance metrics of migrants versus residents and examine how environmental factors influence the relative abundance of each. Such studies tend to characterize animals discretely as either migratory or resident, but we suggest that variable migration distances within migratory herds are an important and overlooked form of population structure, with potential consequences for animal fitness. We examined whether the variation in individual migration distances (20–264 km) within a single wintering population of mule deer (Odocoileus hemionus) was associated with several critical behavioral attributes of migration, including timing of migration, time allocation to seasonal ranges, and exposure to anthropogenic mortality risks. Both the timing of migration and the amount of time animals allocated to seasonal ranges varied with migration distance. Animals migrating long distances (150–250 km) initiated spring migration more than three weeks before than those migrating moderate (50–150 km) or short distances (<50 km). Across an entire year, long-distance migrants spent approximately 100 more days migrating compared to moderate- and short-distance migrants. Relatedly, winter residency of long-distance migrants was 71 d fewer than for animals migrating shorter distances. Exposure to anthropogenic mortality factors, including highways and fences, was high for long-distance migrants, whereas vulnerability to harvest was high for short- and moderate-distance migrants. By reducing the amount of time that animals spend on winter range, long-distance migration may alleviate intraspecific competition for limited forage and effectively increase carrying capacity. Clear differences in winter residency, migration duration, and risk of anthropogenic mortality among short-, moderate-, and long-distance migrants suggest fitness trade-offs may exist among migratory segments of the population. Future studies of partial migration may benefit from expanding comparisons of residents and migrants, to consider how variable migration distances of migrants may influence the costs and benefits of migration.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1534","usgsCitation":"Sawyer, H., Middleton, A., Hayes, M.M., Kauffman, M., and Monteith, K.L., 2016, The extra mile: Ungulate migration distance alters the use of seasonal range and exposure to anthropogenic risk: Ecosphere, v. 7, no. 10, p. 1-11, https://doi.org/10.1002/ecs2.1534.","productDescription":"e01534; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-073382","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470541,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1534","text":"Publisher Index Page"},{"id":348515,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.841064453125,\n 41.5579215778042\n ],\n [\n -108.63830566406249,\n 41.5579215778042\n ],\n [\n -108.63830566406249,\n 43.46886761482925\n ],\n [\n -110.841064453125,\n 43.46886761482925\n ],\n [\n -110.841064453125,\n 41.5579215778042\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-24","publicationStatus":"PW","scienceBaseUri":"5a0425bfe4b0dc0b45b453f0","contributors":{"authors":[{"text":"Sawyer, Hall","contributorId":39930,"corporation":false,"usgs":false,"family":"Sawyer","given":"Hall","affiliations":[],"preferred":false,"id":716619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Middleton, Arthur D.","contributorId":99440,"corporation":false,"usgs":true,"family":"Middleton","given":"Arthur D.","affiliations":[],"preferred":false,"id":716620,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Matthew M.","contributorId":172344,"corporation":false,"usgs":false,"family":"Hayes","given":"Matthew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":716621,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900 mkauffman@usgs.gov","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":189179,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew J.","email":"mkauffman@usgs.gov","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716618,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Monteith, Kevin L.","contributorId":198656,"corporation":false,"usgs":false,"family":"Monteith","given":"Kevin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":716622,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193723,"text":"70193723 - 2016 - Magma decompression rates during explosive eruptions of Kīlauea volcano, Hawaii, recorded by melt embayments","interactions":[],"lastModifiedDate":"2017-11-03T18:01:31","indexId":"70193723","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Magma decompression rates during explosive eruptions of Kīlauea volcano, Hawaii, recorded by melt embayments","docAbstract":"The decompression rate of magma as it ascends during volcanic eruptions is an important but poorly constrained parameter that controls many of the processes that influence eruptive behavior. In this study, we quantify decompression rates for basaltic magmas using volatile diffusion in olivine-hosted melt tubes (embayments) for three contrasting eruptions of Kīlauea volcano, Hawaii. Incomplete exsolution of H2O, CO2, and S from the embayment melts during eruptive ascent creates diffusion profiles that can be measured using microanalytical techniques, and then modeled to infer the average decompression rate. We obtain average rates of ~0.05–0.45 MPa s−1 for eruptions ranging from Hawaiian style fountains to basaltic subplinian, with the more intense eruptions having higher rates. The ascent timescales for these magmas vary from around ~5 to ~36 min from depths of ~2 to ~4 km, respectively. Decompression-exsolution models based on the embayment data also allow for an estimate of the mass fraction of pre-existing exsolved volatiles within the magma body. In the eruptions studied, this varies from 0.1 to 3.2 wt% but does not appear to be the key control on eruptive intensity. Our results do not support a direct link between the concentration of pre-eruptive volatiles and eruptive intensity; rather, they suggest that for these eruptions, decompression rates are proportional to independent estimates of mass discharge rate. Although the intensity of eruptions is defined by the discharge rate, based on the currently available dataset of embayment analyses, it does not appear to scale linearly with average decompression rate. This study demonstrates the utility of the embayment method for providing quantitative constraints on magma ascent during explosive basaltic eruptions.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-016-1064-x","usgsCitation":"Ferguson, D.J., Gonnermann, H.M., Ruprecht, P., Plank, T., Hauri, E.H., Houghton, B.F., and Swanson, D., 2016, Magma decompression rates during explosive eruptions of Kīlauea volcano, Hawaii, recorded by melt embayments: Bulletin of Volcanology, v. 78, no. 10, Article 71, https://doi.org/10.1007/s00445-016-1064-x.","productDescription":"Article 71","ipdsId":"IP-058137","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470599,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://eprints.whiterose.ac.uk/104505/1/Ferguson%20et%20al%202016.pdf","text":"External Repository"},{"id":348176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano","volume":"78","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-22","publicationStatus":"PW","scienceBaseUri":"59fd8029e4b0531197b50144","contributors":{"authors":[{"text":"Ferguson, David J.","contributorId":199795,"corporation":false,"usgs":false,"family":"Ferguson","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":7135,"text":"Lamont Doherty Earth Observatory, Columbia University, Palisades, NY","active":true,"usgs":false},{"id":35453,"text":"University of Leeds, UK","active":true,"usgs":false},{"id":13619,"text":"Department of Earth & Planetary Sciences, Harvard University, Cambridge, MA","active":true,"usgs":false}],"preferred":false,"id":720065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gonnermann, Helge M.","contributorId":48465,"corporation":false,"usgs":false,"family":"Gonnermann","given":"Helge","email":"","middleInitial":"M.","affiliations":[{"id":35613,"text":"Department of Earth Science, Rice University, Houston, TX 77005","active":true,"usgs":false}],"preferred":false,"id":720139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruprecht, Philipp","contributorId":199796,"corporation":false,"usgs":false,"family":"Ruprecht","given":"Philipp","email":"","affiliations":[{"id":35453,"text":"University of Leeds, UK","active":true,"usgs":false},{"id":7135,"text":"Lamont Doherty Earth Observatory, Columbia University, Palisades, NY","active":true,"usgs":false}],"preferred":false,"id":720140,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plank, Terry","contributorId":16743,"corporation":false,"usgs":false,"family":"Plank","given":"Terry","affiliations":[{"id":7135,"text":"Lamont Doherty Earth Observatory, Columbia University, Palisades, NY","active":true,"usgs":false}],"preferred":false,"id":720141,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hauri, Erik H.","contributorId":199798,"corporation":false,"usgs":false,"family":"Hauri","given":"Erik","email":"","middleInitial":"H.","affiliations":[{"id":35612,"text":"Department of Terrestrial Magnetism, Carnegie Institution of Washington, Washington DC 20015","active":true,"usgs":false}],"preferred":false,"id":720142,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Houghton, Bruce F. 0000-0002-7532-9770","orcid":"https://orcid.org/0000-0002-7532-9770","contributorId":140077,"corporation":false,"usgs":false,"family":"Houghton","given":"Bruce","email":"","middleInitial":"F.","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false},{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":720143,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swanson, Donald A. donswan@usgs.gov","contributorId":149804,"corporation":false,"usgs":true,"family":"Swanson","given":"Donald A.","email":"donswan@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":720144,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70188153,"text":"70188153 - 2016 - Lateral and subsurface flows impact arctic coastal plain lake water budgets","interactions":[],"lastModifiedDate":"2018-10-25T16:43:24","indexId":"70188153","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Lateral and subsurface flows impact arctic coastal plain lake water budgets","docAbstract":"Arctic thaw lakes are an important source of water for aquatic ecosystems, wildlife, and humans. Many recent studies have observed changes in Arctic surface waters related to climate warming and permafrost thaw; however, explaining the trends and predicting future responses to warming is difficult without a stronger fundamental understanding of Arctic lake water budgets. By measuring and simulating surface and subsurface hydrologic fluxes, this work quantified the water budgets of three lakes with varying levels of seasonal drainage, and tested the hypothesis that lateral and subsurface flows are a major component of the post-snowmelt water budgets. A water budget focused only on post-snowmelt surface water fluxes (stream discharge, precipitation, and evaporation) could not close the budget for two of three lakes, even when uncertainty in input parameters was rigorously considered using a Monte Carlo approach. The water budgets indicated large, positive residuals, consistent with up to 70% of mid-summer inflows entering lakes from lateral fluxes. Lateral inflows and outflows were simulated based on three processes; supra-permafrost subsurface inflows from basin-edge polygonal ground, and exchange between seasonally drained lakes and their drained margins through runoff and evapotranspiration. Measurements and simulations indicate that rapid subsurface flow through highly conductive flowpaths in the polygonal ground can explain the majority of the inflow. Drained lakes were hydrologically connected to marshy areas on the lake margins, receiving water from runoff following precipitation and losing up to 38% of lake efflux to drained margin evapotranspiration. Lateral fluxes can be a major part of Arctic thaw lake water budgets and a major control on summertime lake water levels. Incorporating these dynamics into models will improve our ability to predict lake volume changes, solute fluxes, and habitat availability in the changing Arctic.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10917","usgsCitation":"Koch, J.C., 2016, Lateral and subsurface flows impact arctic coastal plain lake water budgets: Hydrological Processes, v. 30, no. 21, p. 3918-3931, https://doi.org/10.1002/hyp.10917.","productDescription":"14 p.","startPage":"3918","endPage":"3931","ipdsId":"IP-064008","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":342033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"30","issue":"21","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-21","publicationStatus":"PW","scienceBaseUri":"59327926e4b0e9bd0eab5513","contributors":{"authors":[{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":696929,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70189513,"text":"70189513 - 2016 - Estimating mercury emissions resulting from wildfire in forests of the Western United States","interactions":[],"lastModifiedDate":"2018-08-07T12:28:27","indexId":"70189513","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5331,"text":"Science of Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Estimating mercury emissions resulting from wildfire in forests of the Western United States","docAbstract":"Understanding the emissions of mercury (Hg) from wildfires is important for quantifying the global atmospheric Hg sources. Emissions of Hg from soils resulting from wildfires in the Western United States was estimated for the 2000 to 2013 period, and the potential emission of Hg from forest soils was assessed as a function of forest type and soil-heating. Wildfire released an annual average of 3100 ± 1900 kg-Hg y− 1 for the years spanning 2000–2013 in the 11 states within the study area. This estimate is nearly 5-fold lower than previous estimates for the study region. Lower emission estimates are attributed to an inclusion of fire severity within burn perimeters. Within reported wildfire perimeters, the average distribution of low, moderate, and high severity burns was 52, 29, and 19% of the total area, respectively. Review of literature data suggests that that low severity burning does not result in soil heating, moderate severity fire results in shallow soil heating, and high severity fire results in relatively deep soil heating (< 5 cm). Using this approach, emission factors for high severity burns ranged from 58 to 640 μg-Hg kg-fuel− 1. In contrast, low severity burns have emission factors that are estimated to be only 18–34 μg-Hg kg-fuel− 1. In this estimate, wildfire is predicted to release 1–30 g Hg ha− 1 from Western United States forest soils while above ground fuels are projected to contribute an additional 0.9 to 7.8 g Hg ha− 1. Land cover types with low biomass (desert scrub) are projected to release less than 1 g Hg ha− 1. Following soil sources, fuel source contributions to total Hg emissions generally followed the order of duff > wood > foliage > litter > branches.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.01.166","usgsCitation":"Webster, J., Kane, T., Obrist, D., Ryan, J.N., and Aiken, G.R., 2016, Estimating mercury emissions resulting from wildfire in forests of the Western United States: Science of Total Environment, v. 568, p. 578-586, https://doi.org/10.1016/j.scitotenv.2016.01.166.","productDescription":"9 p.","startPage":"578","endPage":"586","ipdsId":"IP-071233","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":470596,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.01.166","text":"Publisher Index Page"},{"id":343855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"568","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5969d82be4b0d1f9f060a188","contributors":{"authors":[{"text":"Webster, Jackson","contributorId":172157,"corporation":false,"usgs":false,"family":"Webster","given":"Jackson","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":704982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kane, Tyler J. 0000-0003-2511-7312","orcid":"https://orcid.org/0000-0003-2511-7312","contributorId":194675,"corporation":false,"usgs":false,"family":"Kane","given":"Tyler J.","affiliations":[],"preferred":false,"id":704983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Obrist, Daniel","contributorId":172155,"corporation":false,"usgs":false,"family":"Obrist","given":"Daniel","email":"","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":704984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ryan, Joseph N.","contributorId":54290,"corporation":false,"usgs":false,"family":"Ryan","given":"Joseph","email":"","middleInitial":"N.","affiliations":[{"id":604,"text":"University of Colorado- Boulder","active":false,"usgs":true}],"preferred":false,"id":704985,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":704986,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188434,"text":"70188434 - 2016 - Seismic evidence of glacial-age river incision into the Tahaa barrier reef, French Polynesia","interactions":[],"lastModifiedDate":"2017-06-09T14:29:21","indexId":"70188434","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Seismic evidence of glacial-age river incision into the Tahaa barrier reef, French Polynesia","docAbstract":"Rivers have long been recognized for their ability to shape reef-bound volcanic islands. On the time-scale of glacial–interglacial sea-level cycles, fluvial incision of exposed barrier reef lagoons may compete with constructional coral growth to shape the coastal geomorphology of ocean islands. However, overprinting of Pleistocene landscapes by Holocene erosion or sedimentation has largely obscured the role lowstand river incision may have played in developing the deep lagoons typical of modern barrier reefs. Here we use high-resolution seismic imagery and core stratigraphy to examine how erosion and/or deposition by upland drainage networks has shaped coastal morphology on Tahaa, a barrier reef-bound island located along the Society Islands hotspot chain in French Polynesia. At Tahaa, we find that many channels, incised into the lagoon floor during Pleistocene sea-level lowstands, are located near the mouths of upstream terrestrial drainages. Steeper antecedent topography appears to have enhanced lowstand fluvial erosion along Tahaa's southwestern coast and maintained a deep pass. During highstands, upland drainages appear to contribute little sediment to refilling accommodation space in the lagoon. Rather, the flushing of fine carbonate sediment out of incised fluvial channels by storms and currents appears to have limited lagoonal infilling and further reinforced development of deep barrier reef lagoons during periods of highstand submersion.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2016.04.008","usgsCitation":"Toomey, M., Woodruff, J.D., Ashton, A.D., and Perron, J.T., 2016, Seismic evidence of glacial-age river incision into the Tahaa barrier reef, French Polynesia: Marine Geology, v. 380, p. 284-289, https://doi.org/10.1016/j.margeo.2016.04.008.","productDescription":"6 p.","startPage":"284","endPage":"289","ipdsId":"IP-070030","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":470539,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.margeo.2016.04.008","text":"External Repository"},{"id":342343,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"French Polynesia","otherGeospatial":"Tahaa barrier reef","volume":"380","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593bb39fe4b0764e6c60e7b0","contributors":{"authors":[{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":697719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodruff, Jonathan D.","contributorId":192777,"corporation":false,"usgs":false,"family":"Woodruff","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":697720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ashton, Andrew D.","contributorId":96970,"corporation":false,"usgs":true,"family":"Ashton","given":"Andrew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":697721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perron, J. Taylor","contributorId":184100,"corporation":false,"usgs":false,"family":"Perron","given":"J.","email":"","middleInitial":"Taylor","affiliations":[],"preferred":false,"id":697722,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189238,"text":"70189238 - 2016 - Inter-comparison of three-dimensional models of volcanic plumes","interactions":[],"lastModifiedDate":"2017-07-06T13:11:53","indexId":"70189238","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Inter-comparison of three-dimensional models of volcanic plumes","docAbstract":"We performed an inter-comparison study of three-dimensional models of volcanic plumes. A set of common volcanological input parameters and meteorological conditions were provided for two kinds of eruptions, representing a weak and a strong eruption column. From the different models, we compared the maximum plume height, neutral buoyancy level (where plume density equals that of the atmosphere), and level of maximum radial spreading of the umbrella cloud. We also compared the vertical profiles of eruption column properties, integrated across cross-sections of the plume (integral variables). Although the models use different numerical procedures and treatments of subgrid turbulence and particle dynamics, the inter-comparison shows qualitatively consistent results. In the weak plume case (mass eruption rate 1.5 × 106 kg s− 1), the vertical profiles of plume properties (e.g., vertical velocity, temperature) are similar among models, especially in the buoyant plume region. Variability among the simulated maximum heights is ~ 20%, whereas neutral buoyancy level and level of maximum radial spreading vary by ~ 10%. Time-averaging of the three-dimensional (3D) flow fields indicates an effective entrainment coefficient around 0.1 in the buoyant plume region, with much lower values in the jet region, which is consistent with findings of small-scale laboratory experiments. On the other hand, the strong plume case (mass eruption rate 1.5 × 109 kg s− 1) shows greater variability in the vertical plume profiles predicted by the different models. Our analysis suggests that the unstable flow dynamics in the strong plume enhances differences in the formulation and numerical solution of the models. This is especially evident in the overshooting top of the plume, which extends a significant portion (~ 1/8) of the maximum plume height. Nonetheless, overall variability in the spreading level and neutral buoyancy level is ~ 20%, whereas that of maximum height is ~ 10%. This inter-comparison study has highlighted the different capabilities of 3D volcanic plume models, and identified key features of weak and strong plumes, including the roles of jet stability, entrainment efficiency, and particle non-equilibrium, which deserve future investigation in field, laboratory, and numerical studies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2016.06.011","usgsCitation":"Suzuki, Y., Costa, A., Cerminara, M., Esposti Ongaro, T., Herzog, M., Van Eaton, A.R., and Denby, L., 2016, Inter-comparison of three-dimensional models of volcanic plumes: Journal of Volcanology and Geothermal Research, v. 326, p. 26-42, https://doi.org/10.1016/j.jvolgeores.2016.06.011.","productDescription":"17 p.","startPage":"26","endPage":"42","ipdsId":"IP-071593","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470540,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.17863/cam.1638","text":"External Repository"},{"id":343414,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"326","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595f4c3ee4b0d1f9f057e345","contributors":{"authors":[{"text":"Suzuki, Yujiro","contributorId":194289,"corporation":false,"usgs":false,"family":"Suzuki","given":"Yujiro","email":"","affiliations":[],"preferred":false,"id":703662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costa, Antonio","contributorId":194290,"corporation":false,"usgs":false,"family":"Costa","given":"Antonio","email":"","affiliations":[{"id":27088,"text":"Istituto Nazionale di Geofisica e Vulcanologia (INGV)","active":true,"usgs":false}],"preferred":false,"id":703663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cerminara, Matteo","contributorId":194291,"corporation":false,"usgs":false,"family":"Cerminara","given":"Matteo","email":"","affiliations":[],"preferred":false,"id":703664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esposti Ongaro, Tomaso","contributorId":194292,"corporation":false,"usgs":false,"family":"Esposti Ongaro","given":"Tomaso","email":"","affiliations":[],"preferred":false,"id":703665,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herzog, Michael","contributorId":194293,"corporation":false,"usgs":false,"family":"Herzog","given":"Michael","email":"","affiliations":[],"preferred":false,"id":703666,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":703661,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Denby, Leif","contributorId":194294,"corporation":false,"usgs":false,"family":"Denby","given":"Leif","email":"","affiliations":[],"preferred":false,"id":703667,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70192667,"text":"70192667 - 2016 - Use of Atlantic Forest protected areas by free-ranging dogs: estimating abundance and persistence of use","interactions":[],"lastModifiedDate":"2017-11-08T15:24:54","indexId":"70192667","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Use of Atlantic Forest protected areas by free-ranging dogs: estimating abundance and persistence of use","docAbstract":"Worldwide, domestic dogs (Canis familiaris) are one of the most common carnivoran species in natural areas and their populations are still increasing. Dogs have been shown to impact wildlife populations negatively, and their occurrence can alter the abundance, behavior, and activity patterns of native species. However, little is known about abundance and density of the free-ranging dogs that use protected areas. Here, we used camera trap data with an open-robust design mark–recapture model to estimate the number of dogs that used protected areas in Brazilian Atlantic Forest. We estimated the time period these dogs used the protected areas, and explored factors that influenced the probability of continued use (e.g., season, mammal richness, proportion of forest), while accounting for variation in detection probability. Dogs in the studied system were categorized as rural free-ranging, and their abundance varied widely across protected areas (0–73 individuals). Dogs used protected areas near human houses for longer periods (e.g., >50% of sampling occasions) compared to more distant areas. We found no evidence that their probability of continued use varied with season or mammal richness. Dog detection probability decreased linearly among occasions, possibly due to the owners confining their dogs after becoming aware of our presence. Comparing our estimates to those for native carnivoran, we found that dogs were three to 85 times more abundant than ocelots (Leopardus pardalis), two to 25 times more abundant than puma (Puma concolor), and approximately five times more abundant than the crab-eating fox (Cerdocyon thous). Combining camera trapping data with modern mark–recapture methods provides important demographic information on free-ranging dogs that can guide management strategies to directly control dogs' abundance and ranging behavior.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1480","usgsCitation":"Paschoal, A.M., Massara, R., Bailey, L.L., Kendall, W., Doherty, P.F., Hirsch, A., Chiarello, A., and Paglia, A., 2016, Use of Atlantic Forest protected areas by free-ranging dogs: estimating abundance and persistence of use: Ecosphere, v. 7, no. 10, p. 1-15, https://doi.org/10.1002/ecs2.1480.","productDescription":"e01480; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-071412","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470518,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1480","text":"Publisher Index Page"},{"id":348493,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -43,\n -21\n ],\n [\n -41,\n -21\n ],\n [\n -41,\n -19\n ],\n [\n -43,\n -19\n ],\n [\n -43,\n -21\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-21","publicationStatus":"PW","scienceBaseUri":"5a0425bfe4b0dc0b45b453ed","contributors":{"authors":[{"text":"Paschoal, Ana Maria","contributorId":198658,"corporation":false,"usgs":false,"family":"Paschoal","given":"Ana","email":"","middleInitial":"Maria","affiliations":[],"preferred":false,"id":716680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Massara, Rodrigo","contributorId":198659,"corporation":false,"usgs":false,"family":"Massara","given":"Rodrigo","email":"","affiliations":[],"preferred":false,"id":716681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bailey, Larissa L. 0000-0002-5959-2018","orcid":"https://orcid.org/0000-0002-5959-2018","contributorId":189578,"corporation":false,"usgs":false,"family":"Bailey","given":"Larissa","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":716682,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kendall, William L. 0000-0003-0084-9891 wkendall@usgs.gov","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":166709,"corporation":false,"usgs":true,"family":"Kendall","given":"William L.","email":"wkendall@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716679,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doherty, Paul F. Jr.","contributorId":37636,"corporation":false,"usgs":false,"family":"Doherty","given":"Paul","suffix":"Jr.","email":"","middleInitial":"F.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":716683,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hirsch, Andre","contributorId":198661,"corporation":false,"usgs":false,"family":"Hirsch","given":"Andre","email":"","affiliations":[],"preferred":false,"id":716684,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chiarello, Adriano","contributorId":198662,"corporation":false,"usgs":false,"family":"Chiarello","given":"Adriano","email":"","affiliations":[],"preferred":false,"id":716685,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Paglia, Adriano","contributorId":198663,"corporation":false,"usgs":false,"family":"Paglia","given":"Adriano","email":"","affiliations":[],"preferred":false,"id":716686,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}