The term capture, related to the source of water derived from wells, has been used in two distinct yet related contexts by the hydrologic community. The first is a water‐budget context, in which capture refers to decreases in the rates of groundwater outflow and (or) increases in the rates of recharge along head‐dependent boundaries of an aquifer in response to pumping. The second is a transport context, in which capture zone refers to the specific flowpaths that define the three‐dimensional, volumetric portion of a groundwater flow field that discharges to a well. A closely related issue that has become associated with the source of water to wells is streamflow depletion, which refers to the reduction in streamflow caused by pumping, and is a type of capture. Rates of capture and streamflow depletion are calculated by use of water‐budget analyses, most often with groundwater‐flow models. Transport models, particularly particle‐tracking methods, are used to determine capture zones to wells. In general, however, transport methods are not useful for quantifying actual or potential streamflow depletion or other types of capture along aquifer boundaries. To clarify the sometimes subtle differences among these terms, we describe the processes and relations among capture, capture zones, and streamflow depletion, and provide proposed terminology to distinguish among them.
Interactions between fire and nonnative, annual plant species (that is, “the grass/fire cycle”) represent one of the greatest threats to sagebrush (Artemisia spp.) ecosystems and associated wildlife, including the greater sage-grouse (Centrocercus urophasianus). In 2015, U.S. Department of the Interior called for a “science-based strategy to reduce the threat of large-scale rangeland fire to habitat for the greater sage-grouse and the sagebrush-steppe ecosystem.” An associated guidance document, the “Integrated Rangeland Fire Management Strategy Actionable Science Plan,” identified fuel breaks as high priority areas for scientific research. Fuel breaks are intended to reduce fire size and frequency, and potentially they can compartmentalize wildfire spatial distribution in a landscape. Fuel breaks are designed to reduce flame length, fireline intensity, and rates of fire spread in order to enhance firefighter access, improve response times, and provide safe and strategic anchor points for wildland fire-fighting activities. To accomplish these objectives, fuel breaks disrupt fuel continuity, reduce fuel accumulation, and (or) increase plants with high moisture content through the removal or modification of vegetation in strategically placed strips or blocks of land.
Fuel breaks are being newly constructed, enhanced, or proposed across large areas of the Great Basin to reduce wildfire risk and to protect remaining sagebrush ecosystems (including greater sage-grouse habitat). These projects are likely to result in thousands of linear miles of fuel breaks that will have direct ecological effects across hundreds of thousands of acres through habitat loss and conversion. These projects may also affect millions of acres indirectly because of edge effects and habitat fragmentation created by networks of fuel breaks. Hence, land managers are often faced with a potentially paradoxical situation: the need to substantially alter sagebrush habitats with fuel breaks to ultimately reduce a greater threat of their destruction from wildfire. However, there is relatively little published science that directly addresses the ability of fuel breaks to influence fire behavior in dryland landscapes or that addresses the potential ecological effects of the construction and maintenance of fuel breaks on sagebrush ecosystems and associated wildlife species.
This report is intended to provide an initial assessment of both the potential effectiveness of fuel breaks and their ecological costs and benefits. To provide this assessment, we examined prior studies on fuel breaks and other scientific evidence to address three crucial questions: (1) How effective are fuel breaks in reducing or slowing the spread of wildfire in arid and semi-arid shrubland ecosystems? (2) How do fuel breaks affect sagebrush plant communities? (3) What are the effects of fuel breaks on the greater sage-grouse, other sagebrush obligates, and sagebrush-associated wildlife species? We also provide an overview of recent federal policies and management directives aimed at protecting remaining sagebrush and greater sage-grouse habitat; describe the fuel conditions, fire behavior, and fire trends in the Great Basin; and suggest how scientific inquiry and management actions can improve our understanding of fuel breaks and their effects in sagebrush landscapes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181034","collaboration":"Prepared in cooperation with the U.S. Forest Service","usgsCitation":"Shinneman, D.J., Aldridge, C.L., Coates, P.S., Germino, M.J., Pilliod, D.S., and Vaillant, N.M., 2018, A conservation paradox in the Great Basin—Altering sagebrush landscapes with fuel breaks to reduce habitat loss from wildfire: U.S. Geological Survey Open-File Report 2018–1034, 70 p., https://doi.org/10.3133/ofr20181034.","productDescription":"vi, 70 p.","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-092468","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":352531,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1034/coverthb.jpg"},{"id":352532,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1034/ofr20181034.pdf","text":"Report","size":"6.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1034"}],"contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
Effective monitoring and prediction of flood and drought events requires an improved understanding of how and why surface water expansion and contraction in response to climate varies across space. This paper sought to (1) quantify how interannual patterns of surface water expansion and contraction vary spatially across the Prairie Pothole Region (PPR) and adjacent Northern Prairie (NP) in the United States, and (2) explore how landscape characteristics influence the relationship between climate inputs and surface water dynamics. Due to differences in glacial history, the PPR and NP show distinct patterns in regards to drainage development and wetland density, together providing a diversity of conditions to examine surface water dynamics. We used Landsat imagery to characterize variability in surface water extent across 11 Landsat path/rows representing the PPR and NP (images spanned 1985–2015). The PPR not only experienced a 2.6-fold greater surface water extent under median conditions relative to the NP, but also showed a 3.4-fold greater change in surface water extent between drought and deluge conditions. The relationship between surface water extent and accumulated water availability (precipitation minus potential evapotranspiration) was quantified per watershed and statistically related to variables representing hydrology-related landscape characteristics (e.g., infiltration capacity, surface storage capacity, stream density). To investigate the influence stream connectivity has on the rate at which surface water leaves a given location, we modeled stream-connected and stream-disconnected surface water separately. Stream-connected surface water showed a greater expansion with wetter climatic conditions in landscapes with greater total wetland area, but lower total wetland density. Disconnected surface water showed a greater expansion with wetter climatic conditions in landscapes with higher wetland density, lower infiltration and less anthropogenic drainage. From these findings, we can expect that shifts in precipitation and evaporative demand will have uneven effects on surface water quantity. Accurate predictions regarding the effect of climate change on surface water quantity will require consideration of hydrology-related landscape characteristics including wetland storage and arrangement.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-22-1851-2018","usgsCitation":"Vanderhoof, M.K., Lane, C., McManus, M.L., Alexander, L.C., and Christensen, J.R., 2018, Wetlands inform how climate extremes influence surface water expansion and contraction: Hydrology and Earth System Sciences, v. 22, p. 1851-1873, https://doi.org/10.5194/hess-22-1851-2018.","productDescription":"23 p.","startPage":"1851","endPage":"1873","ipdsId":"IP-090618","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468912,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-22-1851-2018","text":"Publisher Index Page"},{"id":352699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Prairie Pothole Regino","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109,\n 39.198205348894795\n ],\n [\n -91.0986328125,\n 39.198205348894795\n ],\n [\n -91.0986328125,\n 48.980216985374994\n ],\n [\n -109,\n 48.980216985374994\n ],\n [\n -109,\n 39.198205348894795\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-15","publicationStatus":"PW","scienceBaseUri":"5afee6fde4b0da30c1bfc026","contributors":{"authors":[{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":731498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lane, Charles R.","contributorId":138991,"corporation":false,"usgs":false,"family":"Lane","given":"Charles R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":731499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McManus, Michael L.","contributorId":189612,"corporation":false,"usgs":false,"family":"McManus","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":731500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alexander, Laurie C.","contributorId":196285,"corporation":false,"usgs":false,"family":"Alexander","given":"Laurie","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":731501,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, Jay R.","contributorId":179361,"corporation":false,"usgs":false,"family":"Christensen","given":"Jay","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":731502,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195496,"text":"sir20185027 - 2018 - Conceptual model to assess water use associated with the life cycle of unconventional oil and gas development","interactions":[],"lastModifiedDate":"2018-09-25T06:18:31","indexId":"sir20185027","displayToPublicDate":"2018-03-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5027","title":"Conceptual model to assess water use associated with the life cycle of unconventional oil and gas development","docAbstract":"As the demand for energy increases in the United States, so does the demand for water used to produce many forms of that energy. Technological advances, limited access to conventional oil and gas accumulations, and the rise of oil and gas prices resulted in increased development of unconventional oil and gas (UOG) accumulations. Unconventional oil and gas is developed using a method that combines directional drilling and hydraulic fracturing techniques, allowing for greater oil and gas production from previously unrecoverable reservoirs. Quantification of the water resources required for UOG development and production is difficult because of disparate data sources, variable reporting requirements across boundaries (local, State, and national), and incomplete or proprietary datasets.
A topical study was started in 2015 under the U.S. Geological Survey’s Water Availability and Use Science Program, as part of the directive in the Secure Water Act for the U.S. Geological Survey to conduct a National Water Census, to better understand the relation between production of UOG resources for energy and the amount of water needed to produce and sustain this type of energy development in the United States. The Water Availability and Use Science Program goal for this topical study is to develop and apply a statistical model to better estimate the water use associated with UOG development, regardless of the location and target geologic formation. As a first step, a conceptual model has been developed to characterize the life cycle of water use in areas of UOG development.
Categories of water use and the way water-use data are collected might change over time; therefore, a generic approach was used in developing the conceptual model to allow for greater flexibility in adapting to future changes or newly available data. UOG development can be summarized into four stages: predrilling construction, drilling, hydraulic fracturing, and ongoing production. The water used in UOG production can be categorized further as direct, indirect, or ancillary water use. Direct water use is defined as the water used for drilling and hydraulic fracturing a well and for maintaining the well during ongoing production. Indirect water use is defined as the water used at or near a well pad. The water used for dust abatement also is considered an indirect use but may be applied away from the well pad. Ancillary water use is defined as the additional local or regional water use resulting from a change (for example, population) directly related to UOG development throughout the life cycle that is not used directly in the well or indirectly for any other purpose at the well pad.
The conceptual model presented in this report consists of five elements: (1) input data, (2) processes, (3) decisions, (4) output data, and (5) outcomes. The input data requirements for estimating water use associated with UOG development are somewhat onerous, and obtaining suitable datasets can be challenging because local, State, and Federal agencies do not collect data similarly. The quality of a water-use assessment that uses the conceptual model presented in this report is dependent on the quality and quantity of data that are available for a UOG play. The conceptual model can be used for an assessment with sparse data; however, having sparse data likely will result in greater uncertainty in the water-use estimates.
The conceptual model presented in this report is designed to be robust to characterize and simulate the data processing to estimate water use associated with UOG development. Although the results of an analysis that includes missing data have greater uncertainty, the analysis still can be insightful because it can establish a baseline estimate of UOG water use that may be refined further as more data become available. Analysis of models that include missing data also could aid in identifying the data most needed for future water-use estimates. Characterizing individual model limitations is important because the conceptual model can be used in future water-use studies to facilitate data compiling, data processing, estimating, and assessing UOG activities regardless of location.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185027","collaboration":"U.S. Geological Survey Water Availability and Use Science Program","usgsCitation":"Valder, J.F., McShane, R.R., Barnhart, T.B., Sando, R., Carter, J.M., and Lundgren, R.F., 2018, Conceptual model to assess water use associated with the life cycle of unconventional oil and gas development: U.S. Geological Survey Scientific Investigations Report 2018–5027, 22 p., https://doi.org/10.3133/sir20185027.","productDescription":"v, 22 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-092881","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":352571,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5027/coverthb2.jpg"},{"id":352572,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5027/sir20185027.pdf","text":"Report","size":"3.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5027"},{"id":352573,"rank":3,"type":{"id":18,"text":"Project Site"},"url":"https://water.usgs.gov/wausp/","text":"Water Availability and Use Science Program"}],"contact":"Director, Dakota Water Science Center, South Dakota Office
U.S. Geological Survey
1608 Mountain View Road
Rapid City, SD 57702
Partial-depth guide walls are used to improve passage efficiency and reduce the delay of out-migrating anadromous fish species by guiding fish to a bypass route (i.e. weir, pipe, sluice gate) that circumvents the turbine intakes, where survival is usually lower. Evaluation and monitoring studies, however, indicate a high propensity for some fish to pass underneath, rather than along, the guide walls, compromising their effectiveness. In the present study we evaluated a range of guide wall structures to identify where/if the flow field shifts from sweeping (i.e. flow direction primarily along the wall and towards the bypass) to downward-dominant. Many migratory fish species, particularly juveniles, are known to drift with the flow and/or exhibit rheotactic behaviour during their migration. When these behaviours are present, fish follow the path of the flow field. Hence, maintaining a strong sweeping velocity in relation to the downward velocity along a guide wall is essential to successful fish guidance. Nine experiments were conducted to measure the three-dimensional velocity components upstream of a scale model guide wall set at a wide range of depths and angles to flow. Results demonstrated how each guide wall configuration affected the three-dimensional velocity components, and hence the downward and sweeping velocity, along the full length of the guide wall. In general, the velocities produced in the scale model were sweeping dominant near the water surface and either downward dominant or close to the transitional depth near the bottom of the guide wall. The primary exception to this shift from sweeping do downward flow was for the minimum guide wall angle tested in this study (15°). At 15° the flow pattern was fully sweeping dominant for every cross-section, indicating that a guide wall with a relatively small angle may be more likely to produce conditions favorable to efficient guidance. A critical next step is to evaluate the behaviour of migratory fish as they approach and swim along a guide wall in a controlled laboratory environment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2018.02.006","usgsCitation":"Mulligan, K., Towler, B., Haro, A.J., and Ahlfeld, D.P., 2018, Downstream fish passage guide walls: A hydraulic scale model analysis: Ecological Engineering, v. 115, p. 122-138, https://doi.org/10.1016/j.ecoleng.2018.02.006.","productDescription":"17 p.","startPage":"122","endPage":"138","ipdsId":"IP-080365","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":468911,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2018.02.006","text":"Publisher Index Page"},{"id":352541,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6fde4b0da30c1bfc02c","contributors":{"authors":[{"text":"Mulligan, Kevin 0000-0002-3534-4239 kmulligan@usgs.gov","orcid":"https://orcid.org/0000-0002-3534-4239","contributorId":177024,"corporation":false,"usgs":true,"family":"Mulligan","given":"Kevin","email":"kmulligan@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":731136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Towler, Brett","contributorId":141164,"corporation":false,"usgs":false,"family":"Towler","given":"Brett","email":"","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":731137,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haro, Alexander J. 0000-0002-7188-9172 aharo@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-9172","contributorId":2917,"corporation":false,"usgs":true,"family":"Haro","given":"Alexander","email":"aharo@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":731138,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ahlfeld, David P.","contributorId":196530,"corporation":false,"usgs":false,"family":"Ahlfeld","given":"David","email":"","middleInitial":"P.","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":731139,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196066,"text":"70196066 - 2018 - Stress concentrations at structural discontinuities in active fault zones in the western United States: Implications for permeability and fluid flow in geothermal fields","interactions":[],"lastModifiedDate":"2018-07-03T11:32:17","indexId":"70196066","displayToPublicDate":"2018-03-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Stress concentrations at structural discontinuities in active fault zones in the western United States: Implications for permeability and fluid flow in geothermal fields","docAbstract":"Slip can induce concentration of stresses at discontinuities along fault systems. These structural discontinuities, i.e., fault terminations, fault step-overs, intersections, bends, and other fault interaction areas, are known to host fluid flow in ore deposition systems, oil and gas reservoirs, and geothermal systems. We modeled stress transfer associated with slip on faults with Holocene-to-historic slip histories at the Salt Wells and Bradys geothermal systems in western Nevada, United States. Results show discrete locations of stress perturbation within discontinuities along these fault systems. Well field data, surface geothermal manifestations, and subsurface temperature data, each a proxy for modern fluid circulation in the fields, indicate that geothermal fluid flow is focused in these same areas where stresses are most highly perturbed. These results suggest that submeter- to meter-scale slip on these fault systems generates stress perturbations that are sufficiently large to promote slip on an array of secondary structures spanning the footprint of the modern geothermal activity. Slip on these secondary faults and fractures generates permeability through kinematic deformation and allows for transmission of fluids. Still, mineralization is expected to seal permeability along faults and fractures over time scales that are generally shorter than either earthquake recurrence intervals or the estimated life span of geothermal fields. This suggests that though stress perturbations resulting from fault slip are broadly important for defining the location and spatial extent of enhanced permeability at structural discontinuities, continual generation and maintenance of flow conduits throughout these areas are probably dependent on the deformation mechanism(s) affecting individual structures.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31729.1","usgsCitation":"Siler, D.L., Hinz, N., and Faulds, J., 2018, Stress concentrations at structural discontinuities in active fault zones in the western United States: Implications for permeability and fluid flow in geothermal fields: GSA Bulletin, v. 130, no. 7-8, p. 1273-1288, https://doi.org/10.1130/B31729.1.","productDescription":"16 p.","startPage":"1273","endPage":"1288","ipdsId":"IP-080783","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":352584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"130","issue":"7-8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-05","publicationStatus":"PW","scienceBaseUri":"5afee6fde4b0da30c1bfc028","contributors":{"authors":[{"text":"Siler, Drew L. 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":203341,"corporation":false,"usgs":true,"family":"Siler","given":"Drew","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":731188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hinz, Nicholas H.","contributorId":184260,"corporation":false,"usgs":false,"family":"Hinz","given":"Nicholas H.","affiliations":[],"preferred":false,"id":731189,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Faulds, James E.","contributorId":184258,"corporation":false,"usgs":false,"family":"Faulds","given":"James E.","affiliations":[],"preferred":false,"id":731190,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196057,"text":"70196057 - 2018 - Misleading prioritizations from modelling range shifts under climate change","interactions":[],"lastModifiedDate":"2018-05-29T13:39:20","indexId":"70196057","displayToPublicDate":"2018-03-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Misleading prioritizations from modelling range shifts under climate change","docAbstract":"Aim
Conservation planning requires the prioritization of a subset of taxa and geographical locations to focus monitoring and management efforts. Integration of the threats and opportunities posed by climate change often relies on predictions from species distribution models, particularly for assessments of vulnerability or invasion risk for multiple taxa. We evaluated whether species distribution models could reliably rank changes in species range size under climate and land use change.
Location
Conterminous U.S.A.
Time period
1977–2014.
Major taxa studied
Passerine birds.
Methods
We estimated ensembles of species distribution models based on historical North American Breeding Bird Survey occurrences for 190 songbirds, and generated predictions to recent years given c. 35 years of observed land use and climate change. We evaluated model predictions using standard metrics of discrimination performance and a more detailed assessment of the ability of models to rank species vulnerability to climate change based on predicted range loss, range gain, and overall change in range size.
Results
Species distribution models yielded unreliable and misleading assessments of relative vulnerability to climate and land use change. Models could not accurately predict range expansion or contraction, and therefore failed to anticipate patterns of range change among species. These failures occurred despite excellent overall discrimination ability and transferability to the validation time period, which reflected strong performance at the majority of locations that were either always or never occupied by each species.
Main conclusions
Models failed for the questions and at the locations of greatest interest to conservation and management. This highlights potential pitfalls of multi-taxa impact assessments under global change; in our case, models provided misleading rankings of the most impacted species, and spatial information about range changes was not credible. As modelling methods and frameworks continue to be refined, performance assessments and validation efforts should focus on the measures of risk and vulnerability useful for decision-making.
","language":"English","publisher":"Wiley","doi":"10.1111/geb.12726","usgsCitation":"Sofaer, H., Jarnevich, C.S., and Flather, C.H., 2018, Misleading prioritizations from modelling range shifts under climate change: Global Ecology and Biogeography, v. 27, no. 6, p. 658-666, https://doi.org/10.1111/geb.12726.","productDescription":"9 p.","startPage":"658","endPage":"666","ipdsId":"IP-085159","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468913,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/geb.12726","text":"Publisher Index Page"},{"id":437986,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NS0S4R","text":"USGS data release","linkHelpText":"Breeding Bird Survey songbird occurrences during 1977-1979 and 2012-2014 in conterminous 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\"}}]}\n\n\n","volume":"27","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-09","publicationStatus":"PW","scienceBaseUri":"5afee6fde4b0da30c1bfc02a","contributors":{"authors":[{"text":"Sofaer, Helen 0000-0002-9450-5223 hsofaer@usgs.gov","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":169118,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"hsofaer@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":731163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":731164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flather, Curtis H.","contributorId":177590,"corporation":false,"usgs":false,"family":"Flather","given":"Curtis","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":731165,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70212303,"text":"70212303 - 2018 - Ceres internal structure from geophysical constraints","interactions":[],"lastModifiedDate":"2020-08-14T15:51:27.162961","indexId":"70212303","displayToPublicDate":"2018-03-14T10:49:49","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2715,"text":"Meteoritics and Planetary Science","active":true,"publicationSubtype":{"id":10}},"title":"Ceres internal structure from geophysical constraints","docAbstract":"Thermal evolution modeling has yielded a variety of interior structures for Ceres, ranging from a modestly differentiated interior to more advanced evolution with a dry silicate core, a hydrated silicate mantle, and a volatile‐rich crust. Here we compute the mass and hydrostatic flattening from more than one hundred billion three‐layer density models for Ceres and describe the characteristics of the population of density structures that are consistent with the Dawn observations. We show that the mass and hydrostatic flattening constraints from Ceres indicate the presence of a high‐density core with greater than a 1σ probability, but provide little constraint on the density, allowing for core compositions that range from hydrous and/or anhydrous silicates to a mixture of metal and silicates. The crustal densities are consistent with surface observations of salts, water ice, carbonates, and ammoniated clays, which indicate hydrothermal alteration, partial fractionation, and the possible settling of heavy sulfide and metallic particles, which provide a potential process for increasing mass with depth.
","language":"English","publisher":"Wiley","doi":"10.1111/maps.13063","usgsCitation":"King, S., Castillo-Rogez, J.C., Toplis, M.J., Bland, M.T., Raymond, C.A., and Russell, C.T., 2018, Ceres internal structure from geophysical constraints: Meteoritics and Planetary Science, v. 53, no. 9, p. 1999-2007, https://doi.org/10.1111/maps.13063.","productDescription":"9 p.","startPage":"1999","endPage":"2007","ipdsId":"IP-092685","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":468914,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/maps.13063","text":"External Repository"},{"id":377531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Ceres","volume":"53","issue":"9","noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"King, S.J.","contributorId":197182,"corporation":false,"usgs":false,"family":"King","given":"S.J.","email":"","affiliations":[],"preferred":false,"id":796241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Castillo-Rogez, J. C.","contributorId":177375,"corporation":false,"usgs":false,"family":"Castillo-Rogez","given":"J.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":796242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toplis, M. J.","contributorId":238461,"corporation":false,"usgs":false,"family":"Toplis","given":"M.","email":"","middleInitial":"J.","affiliations":[{"id":47711,"text":"University of Toulouse","active":true,"usgs":false}],"preferred":false,"id":796243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bland, Michael T. 0000-0001-5543-1519 mbland@usgs.gov","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":146287,"corporation":false,"usgs":true,"family":"Bland","given":"Michael","email":"mbland@usgs.gov","middleInitial":"T.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":796244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Raymond, C. A.","contributorId":238463,"corporation":false,"usgs":false,"family":"Raymond","given":"C.","email":"","middleInitial":"A.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":796245,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Russell, C. T.","contributorId":238465,"corporation":false,"usgs":false,"family":"Russell","given":"C.","email":"","middleInitial":"T.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":796246,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196250,"text":"70196250 - 2018 - Restricted access Giant kelp, Macrocystis pyrifera, increases faunal diversity through physical engineering","interactions":[],"lastModifiedDate":"2018-03-28T13:04:41","indexId":"70196250","displayToPublicDate":"2018-03-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3173,"text":"Proceedings of the Royal Society B","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Restricted access Giant kelp, Macrocystis pyrifera, increases faunal diversity through physical engineering","title":"Restricted access Giant kelp, Macrocystis pyrifera, increases faunal diversity through physical engineering","docAbstract":"Foundation species define the ecosystems they live in, but ecologists have often characterized dominant plants as foundational without supporting evidence. Giant kelp has long been considered a marine foundation species due to its complex structure and high productivity; however, there is little quantitative evidence to evaluate this. Here, we apply structural equation modelling to a 15-year time series of reef community data to evaluate how giant kelp affects the reef community. Although species richness was positively associated with giant kelp biomass, most direct paths did not involve giant kelp. Instead, the foundational qualities of giant kelp were driven mostly by indirect effects attributed to its dominant physical structure and associated engineering influence on the ecosystem, rather than by its use as food by invertebrates and fishes. Giant kelp structure has indirect effects because it shades out understorey algae that compete with sessile invertebrates. When released from competition, sessile species in turn increase the diversity of mobile predators. Sea urchin grazing effects could have been misinterpreted as kelp effects, because sea urchins can overgraze giant kelp, understorey algae and sessile invertebrates alike. Our results confirm the high diversity and biomass associated with kelp forests, but highlight how species interactions and habitat attributes can be misconstrued as direct consequences of a foundation species like giant kelp.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rspb.2017.2571","usgsCitation":"Miller, R.J., Lafferty, K.D., Lamy, T., Kui, L., Rassweiler, A., and Reed, D.C., 2018, Restricted access Giant kelp, Macrocystis pyrifera, increases faunal diversity through physical engineering: Proceedings of the Royal Society B, v. 285, no. 1874, Article 20172571, https://doi.org/10.1098/rspb.2017.2571.","productDescription":"Article 20172571","ipdsId":"IP-087899","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468917,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1098/rspb.2017.2571","text":"External Repository"},{"id":352838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"285","issue":"1874","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","scienceBaseUri":"5afee6fee4b0da30c1bfc034","contributors":{"authors":[{"text":"Miller, Robert J.","contributorId":176277,"corporation":false,"usgs":false,"family":"Miller","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":731870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":731869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lamy, Thomas","contributorId":203605,"corporation":false,"usgs":false,"family":"Lamy","given":"Thomas","email":"","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":731871,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kui, Li","contributorId":194515,"corporation":false,"usgs":false,"family":"Kui","given":"Li","email":"","affiliations":[],"preferred":false,"id":731872,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rassweiler, Andrew 0000-0002-8760-3888","orcid":"https://orcid.org/0000-0002-8760-3888","contributorId":203606,"corporation":false,"usgs":false,"family":"Rassweiler","given":"Andrew","email":"","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":731873,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reed, Daniel C.","contributorId":203607,"corporation":false,"usgs":false,"family":"Reed","given":"Daniel","email":"","middleInitial":"C.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":731874,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196042,"text":"70196042 - 2018 - Pleistocene vertical motions of the Costa Rican outer forearc from subducting topography and a migrating fracture zone triple junction","interactions":[],"lastModifiedDate":"2018-03-15T10:59:42","indexId":"70196042","displayToPublicDate":"2018-03-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Pleistocene vertical motions of the Costa Rican outer forearc from subducting topography and a migrating fracture zone triple junction","docAbstract":"Understanding the links between subducting slabs and upper-plate deformation is a longstanding goal in the field of tectonics. New 3D seismic sequence stratigraphy, mapped within the Costa Rica Seismogenesis Project (CRISP) seismic-reflection volume offshore southern Costa Rica, spatiotemporally constrains several Pleistocene outer forearc processes and provides clearer connections to subducting plate dynamics. Three significant shelf and/or slope erosional events at ca. 2.5–2.3 Ma, 1.95–1.78 Ma, and 1.78–1.19 Ma, each with notable differences in spatial extent, volume removed, and subsequent margin response, caused abrupt shifts in sedimentation patterns and rates. These shifts, coupled with observed deformation, suggest three primary mechanisms for Pleistocene shelf and slope vertical motions: (1) regional subaerial erosion and rapid subsidence linked to the southeastward Panama Fracture Zone triple-junction migration, with associated abrupt bathymetric variations and plate kinematic changes; (2) transient, kilometer-scale uplift and subsidence due to inferred subducting plate topography; and (3) progressive outer wedge shortening accommodated by landward- and seaward-dipping thrust faults and fold development due to the impinging Cocos Ridge. Furthermore, we find that the present-day wedge geometry (to within ∼3 km along strike) has been maintained through the Pleistocene, in contrast to modeled landward margin retreat. We also observe that deformation, i.e., extension and shortening, is decoupled from net margin subsidence. Our findings do not require basal erosion, and they suggest that the vertical motions of the Costa Rican outer forearc are not the result of a particular continuous process, but rather are a summation of plate to plate changes (e.g., passage of a fracture zone triple junction) and episodic events (e.g., subducting plate topography).
","language":"English","publisher":"The Geological Society of America","doi":"10.1130/GES01577.1","usgsCitation":"Edwards, J.H., Kluesner, J.W., Silver, E.A., and Bangs, N.L., 2018, Pleistocene vertical motions of the Costa Rican outer forearc from subducting topography and a migrating fracture zone triple junction: Geosphere, v. 14, no. 2, p. 1-25, https://doi.org/10.1130/GES01577.1.","productDescription":"25 p.","startPage":"1","endPage":"25","ipdsId":"IP-087901","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468915,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01577.1","text":"Publisher Index Page"},{"id":352533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Costa Rica","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86,\n 6.5\n ],\n [\n -82.5,\n 6.5\n ],\n [\n -82.5,\n 10\n ],\n [\n -86,\n 10\n ],\n [\n -86,\n 6.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-16","publicationStatus":"PW","scienceBaseUri":"5afee6fee4b0da30c1bfc038","contributors":{"authors":[{"text":"Edwards, Joel H.","contributorId":202599,"corporation":false,"usgs":false,"family":"Edwards","given":"Joel","email":"","middleInitial":"H.","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":731103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kluesner, Jared W. 0000-0003-1701-8832 jkluesner@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":167088,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared","email":"jkluesner@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":731102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silver, Eli A.","contributorId":83505,"corporation":false,"usgs":true,"family":"Silver","given":"Eli","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":731104,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bangs, Nathan L.","contributorId":202602,"corporation":false,"usgs":false,"family":"Bangs","given":"Nathan","email":"","middleInitial":"L.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":731105,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195979,"text":"70195979 - 2018 - Spatial capture–recapture with partial identity: An application to camera traps","interactions":[],"lastModifiedDate":"2018-03-12T11:06:43","indexId":"70195979","displayToPublicDate":"2018-03-12T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":787,"text":"Annals of Applied Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Spatial capture–recapture with partial identity: An application to camera traps","docAbstract":"Camera trapping surveys frequently capture individuals whose identity is only known from a single flank. The most widely used methods for incorporating these partial identity individuals into density analyses discard some of the partial identity capture histories, reducing precision, and, while not previously recognized, introducing bias. Here, we present the spatial partial identity model (SPIM), which uses the spatial location where partial identity samples are captured to probabilistically resolve their complete identities, allowing all partial identity samples to be used in the analysis. We show that the SPIM outperforms other analytical alternatives. We then apply the SPIM to an ocelot data set collected on a trapping array with double-camera stations and a bobcat data set collected on a trapping array with single-camera stations. The SPIM improves inference in both cases and, in the ocelot example, individual sex is determined from photographs used to further resolve partial identities—one of which is resolved to near certainty. The SPIM opens the door for the investigation of trapping designs that deviate from the standard two camera design, the combination of other data types between which identities cannot be deterministically linked, and can be extended to the problem of partial genotypes.
","language":"English","publisher":"IMS","doi":"10.1214/17-AOAS1091","usgsCitation":"Augustine, B.C., Royle, J., Kelly, M.J., Satter, C.B., Alonso, R.S., Boydston, E.E., and Crooks, K.R., 2018, Spatial capture–recapture with partial identity: An application to camera traps: Annals of Applied Statistics, v. 12, no. 1, p. 67-95, https://doi.org/10.1214/17-AOAS1091.","productDescription":"29 p.","startPage":"67","endPage":"95","ipdsId":"IP-088130","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468923,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1214/17-aoas1091","text":"Publisher Index Page"},{"id":352404,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6ffe4b0da30c1bfc048","contributors":{"authors":[{"text":"Augustine, Ben C.","contributorId":203257,"corporation":false,"usgs":false,"family":"Augustine","given":"Ben","email":"","middleInitial":"C.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":730769,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":138865,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":730768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelly, Marcella J.","contributorId":179348,"corporation":false,"usgs":false,"family":"Kelly","given":"Marcella","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":730770,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Satter, Christopher B.","contributorId":203259,"corporation":false,"usgs":false,"family":"Satter","given":"Christopher","email":"","middleInitial":"B.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":730771,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alonso, Robert S.","contributorId":93739,"corporation":false,"usgs":false,"family":"Alonso","given":"Robert","email":"","middleInitial":"S.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":730772,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boydston, Erin E. 0000-0002-8452-835X eboydston@usgs.gov","orcid":"https://orcid.org/0000-0002-8452-835X","contributorId":1705,"corporation":false,"usgs":true,"family":"Boydston","given":"Erin","email":"eboydston@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":730773,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Crooks, Kevin R.","contributorId":51137,"corporation":false,"usgs":false,"family":"Crooks","given":"Kevin","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":730774,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70195620,"text":"ofr20181026 - 2018 - Preliminary stage and streamflow data at selected U.S. Geological Survey streamgages in Maine and New Hampshire for the flood of October 30–31, 2017","interactions":[],"lastModifiedDate":"2018-03-08T12:26:26","indexId":"ofr20181026","displayToPublicDate":"2018-03-08T11:15:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1026","title":"Preliminary stage and streamflow data at selected U.S. Geological Survey streamgages in Maine and New Hampshire for the flood of October 30–31, 2017","docAbstract":"Rainfall from a storm on October 24–27, 2017, and Tropical Storm Philippe on October 29–30, created conditions that led to flooding across portions of New Hampshire and western Maine. On the basis of streamflow data collected at 30 selected U.S. Geological Survey (USGS) streamgages in the Androscoggin River, Connecticut River, Merrimack River, and Saco River Basins, the storms caused minor to moderate flooding in those basins on October 30–31, 2017. During the storms, the USGS deployed hydrographers to take discrete measurements of streamflow. The measurements were used to confirm the stage-to-streamflow relation (rating curve) at the selected USGS streamgages. Following the storms, hydrographers documented high-water marks in support of indirect measurements of streamflow. Seven streamgages with greater than 50 years of streamflow data recorded preliminary streamflow peaks within the top five for the periods of record. Twelve streamgages recorded preliminary peak streamflows greater than an estimate of the 100-year streamflow based on drainage area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181026","usgsCitation":"Kiah, R.G, and Stasulis, N.W., 2018, Preliminary stage and streamflow data at selected U.S. Geological Survey streamgages in Maine and New Hampshire for the flood of October 30–31, 2017: U.S. Geological Survey Open-File Report 2018–1026, 12 p., https://doi.org/10.3133/ofr20181026.","productDescription":"iv, 12 p.","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092894","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":352270,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1026/ofr20181026.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1026"},{"id":352269,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1026/coverthb.jpg"}],"country":"United States","state":"Maine, New Hampshire","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72,\n 42.75\n ],\n [\n -69,\n 42.75\n ],\n [\n -69,\n 46\n ],\n [\n -72,\n 46\n ],\n [\n -72,\n 42.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
We analyze the response of Kenyan maize yields to near-term climate change and explore potential mitigation options. We model county level yields as a function of rainfall and temperature during a period of increased regional warming and drying (1989–2008). We then do a counter factual analysis by comparing existing maize yields from 2000 to 2008 to what yields might have been if observed warming and drying trends had not occurred. We also examine maize yields based on projected 2026–2040 climate trends. Without the observed warming and drying trends, Eastern Kenya would have had an 8% increase in maize yields, which in turn would have led to a net production increase of 500,000 metric tons. In Western Kenya, the magnitude of change is higher but the relative changes in predicted values are smaller. If warming and drying trends continue, we expect future maize yields to decline by 11% in Eastern Kenya (vs. 7% in Western Kenya). We also examine whether these future losses might be offset through agricultural development. For that analysis, we use a household panel dataset (2000, 2005) with measurements of individual farm plot yields, inputs, and outputs. We find that under a scenario of aggressive adoption of hybrid seeds and fertilizer usage coupled with warming and drying trends, yields in Western Kenya might increase by 6% while those in Eastern Kenya could increase by 14%. This increase in yields might be larger if there is a corresponding increase in usage of drought-tolerant hybrids. However, wide prediction intervals across models highlight the uncertainty in these outcomes and scenarios.
A mass balance is formulated to evaluate the mobilization of chlorinated ethene compounds (CE) from the rock matrix of a fractured mudstone aquifer under pre- and postbioremediation conditions. The analysis relies on a sparse number of monitoring locations and is constrained by a detailed description of the groundwater flow regime. Groundwater flow modeling developed under the site characterization identified groundwater fluxes to formulate the CE mass balance in the rock volume exposed to the injected remediation amendments. Differences in the CE fluxes into and out of the rock volume identify the total CE mobilized from diffusion, desorption, and nonaqueous phase liquid dissolution under pre- and postinjection conditions. The initial CE mass in the rock matrix prior to remediation is estimated using analyses of CE in rock core. The CE mass mobilized per year under preinjection conditions is small relative to the total CE mass in the rock, indicating that current pump-and-treat and natural attenuation conditions are likely to require hundreds of years to achieve groundwater concentrations that meet regulatory guidelines. The postinjection CE mobilization rate increased by approximately an order of magnitude over the 5 years of monitoring after the amendment injection. This rate is likely to decrease and additional remediation applications over several decades would still be needed to reduce CE mass in the rock matrix to levels where groundwater concentrations in fractures achieve regulatory standards.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12586","usgsCitation":"Shapiro, A.M., Tiedeman, C.R., Imbrigiotta, T.E., Goode, D.J., Hsieh, P.A., Lacombe, P., DeFlaun, M.F., Drew, S.R., and Curtis, G.P., 2018, Bioremediation in fractured rock: 2. Mobilization of chloroethene compounds from the rock matrix: Groundwater, v. 56, no. 2, p. 317-336, https://doi.org/10.1111/gwat.12586.","productDescription":"20 p.","startPage":"317","endPage":"336","ipdsId":"IP-088890","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":352329,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","city":"West Trenton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.81480240821838,\n 40.26764815781309\n ],\n [\n -74.8107898235321,\n 40.26764815781309\n ],\n [\n -74.8107898235321,\n 40.27047242769165\n ],\n [\n -74.81480240821838,\n 40.27047242769165\n ],\n [\n -74.81480240821838,\n 40.26764815781309\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-05","publicationStatus":"PW","scienceBaseUri":"5afee701e4b0da30c1bfc05a","contributors":{"authors":[{"text":"Shapiro, Allen M. 0000-0002-6425-9607 ashapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":2164,"corporation":false,"usgs":true,"family":"Shapiro","given":"Allen","email":"ashapiro@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - 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Office of Quality Assurance","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":730562,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lacombe, Pierre 0000-0002-9596-7622 placombe@usgs.gov","orcid":"https://orcid.org/0000-0002-9596-7622","contributorId":152113,"corporation":false,"usgs":true,"family":"Lacombe","given":"Pierre","email":"placombe@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730563,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DeFlaun, Mary F.","contributorId":203177,"corporation":false,"usgs":false,"family":"DeFlaun","given":"Mary","email":"","middleInitial":"F.","affiliations":[{"id":36571,"text":"Geosyntec Consultants","active":true,"usgs":false}],"preferred":false,"id":730564,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Drew, Scott R.","contributorId":203178,"corporation":false,"usgs":false,"family":"Drew","given":"Scott","email":"","middleInitial":"R.","affiliations":[{"id":36571,"text":"Geosyntec Consultants","active":true,"usgs":false}],"preferred":false,"id":730565,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Curtis, Gary P. 0000-0003-3975-8882 gpcurtis@usgs.gov","orcid":"https://orcid.org/0000-0003-3975-8882","contributorId":2346,"corporation":false,"usgs":true,"family":"Curtis","given":"Gary","email":"gpcurtis@usgs.gov","middleInitial":"P.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":730566,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70195940,"text":"70195940 - 2018 - Context-dependent interactions and the regulation of species richness in freshwater fish","interactions":[],"lastModifiedDate":"2018-03-08T10:54:23","indexId":"70195940","displayToPublicDate":"2018-03-08T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Context-dependent interactions and the regulation of species richness in freshwater fish","docAbstract":"Species richness is regulated by a complex network of scale-dependent processes. This complexity can obscure the influence of limiting species interactions, making it difficult to determine if abiotic or biotic drivers are more predominant regulators of richness. Using integrative modeling of freshwater fish richness from 721 lakes along an 11olatitudinal gradient, we find negative interactions to be a relatively minor independent predictor of species richness in lakes despite the widespread presence of predators. Instead, interaction effects, when detectable among major functional groups and 231 species pairs, were strong, often positive, but contextually dependent on environment. These results are consistent with the idea that negative interactions internally structure lake communities but do not consistently ‘scale-up’ to regulate richness independently of the environment. The importance of environment for interaction outcomes and its role in the regulation of species richness highlights the potential sensitivity of fish communities to the environmental changes affecting lakes globally.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-018-03419-1","usgsCitation":"MacDougall, A.S., Harvey, E., McCune, J.L., Nilsson, K.A., Bennett, J., Firn, J., Bartley, T., Grace, J.B., Kelly, J., Tunney, T.D., McMeans, B.C., Matsuzaki, S.S., Kadoya, T., Esch, E., Cazelles, K., Lester, N., and McCann, K.S., 2018, Context-dependent interactions and the regulation of species richness in freshwater fish: Nature Communications, v. 9, p. 1-9, https://doi.org/10.1038/s41467-018-03419-1.","productDescription":"Article number 973; 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-086293","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":460987,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-018-03419-1","text":"Publisher Index Page"},{"id":352333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-06","publicationStatus":"PW","scienceBaseUri":"5afee701e4b0da30c1bfc058","contributors":{"authors":[{"text":"MacDougall, Andrew S.","contributorId":39509,"corporation":false,"usgs":true,"family":"MacDougall","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":730574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harvey, Eric","contributorId":203184,"corporation":false,"usgs":false,"family":"Harvey","given":"Eric","email":"","affiliations":[{"id":36573,"text":"Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":730575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCune, Jenny 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Ontario","active":true,"usgs":false}],"preferred":false,"id":730578,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Firn, Jennifer","contributorId":66405,"corporation":false,"usgs":false,"family":"Firn","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":730579,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bartley, Timothy","contributorId":203189,"corporation":false,"usgs":false,"family":"Bartley","given":"Timothy","email":"","affiliations":[{"id":36573,"text":"Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":730580,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":455,"text":"National 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dissolved nitrate carried in groundwater discharge to streams. To estimate the concentrations, loads, and yields of nitrate from groundwater to streams for the Chesapeake Bay watershed, a regression model was developed based on measured nitrate concentrations from 156 small streams with watersheds less than 500 square miles (mi2 ) at baseflow. The regression model has three predictive variables: geologic unit, percent developed land, and percent agricultural land. Comparisons of estimated and actual values within geologic units were closely matched. The coefficient of determination (R2 ) for the model was 0.6906. The model was used to calculate baseflow nitrate concentrations at over 83,000 National Hydrography Dataset Plus Version 2 catchments and aggregated to 1,966 total 12-digit hydrologic units in the Chesapeake Bay watershed. The modeled output geospatial data layers provided estimated annual loads and yields of nitrate from groundwater into streams. The spatial distribution of annual nitrate yields from groundwater estimated by this method was compared to the total watershed yields of all sources estimated from a Chesapeake Bay SPAtially Referenced Regressions On Watershed attributes (SPARROW) water-quality model. The comparison showed similar spatial patterns. The regression model for groundwater contribution had similar but lower yields, suggesting that groundwater is an important source of nitrogen for streams in the Chesapeake Bay watershed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175160","usgsCitation":"Terziotti, Silvia, Capel, P.D., Tesoriero, A.J., Hopple, J.A., and Kronholm, S.C., 2017, Estimates of nitrate loads and yields from groundwater to streams in the Chesapeake Bay watershed based on land use and geology: U.S. Geological Survey Scientific Investigations Report 2017–5160, 20 p., https://doi.org/10.3133/sir20175160.","productDescription":"Report: iv, 20 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-086227","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":352267,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79G5KP4","text":"USGS data release","description":"USGS data release","linkHelpText":"Datasets and metadata for estimates of nitrate loads and yields from groundwater to streams in the 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U.S. Geological Survey
3916 Sunset Ridge Road
Raleigh, NC 27607
Mismatches between invasive species management policies and ecological knowledge can lead to profound societal consequences. For this reason, natural resource agencies have adopted the scientifically-based density-impact invasive species curve to guide invasive species management. We use the density-impact model to evaluate how well management policies for a native invader (Juniperus virginiana) match scientific guidelines. Juniperus virginiana invasion is causing a sub-continental regime shift from grasslands to woodlands in central North America, and its impacts span collapses in endemic diversity, heightened wildfire risk, and crashes in grazing land profitability. We (1) use land cover data to identify the stage of Juniperus virginiana invasion for three ecoregions within Nebraska, USA, (2) determine the range of invasion stages at individual land parcel extents within each ecoregion based on the density-impact model, and (3) determine policy alignment and mismatches relative to the density-impact model in order to assess their potential to meet sustainability targets and avoid societal impacts as Juniperus virginiana abundance increases. We found that nearly all policies evidenced doublethink and policy-ecology mismatches, for instance, promoting spread of Juniperus virginiana regardless of invasion stage while simultaneously managing it as a native invader in the same ecoregion. Like other invasive species, theory and literature for this native invader indicate that the consequences of invasion are unlikely to be prevented if policies fail to prioritize management at incipient invasion stages. Theory suggests a more realistic approach would be to align policy with the stage of invasion at local and ecoregion management scales. There is a need for scientists, policy makers, and ecosystem managers to move past ideologies governing native versus non-native invader classification and toward a framework that accounts for the uniqueness of native species invasions, their anthropogenic drivers, and their impacts on ecosystem services.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0189733","usgsCitation":"Roberts, C.P., Uden, D.R., Allen, C.R., and Twidwell, D., 2018, Doublethink and scale mismatch polarize policies for an invasive tree: PLoS ONE, v. 13, no. 3, p. 1-20, https://doi.org/10.1371/journal.pone.0189733.","productDescription":"e0189733; 20 p.","startPage":"1","endPage":"20","ipdsId":"IP-092986","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468930,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0189733","text":"Publisher Index Page"},{"id":354145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","volume":"13","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-07","publicationStatus":"PW","scienceBaseUri":"5afee70ce4b0da30c1bfc06b","contributors":{"authors":[{"text":"Roberts, Caleb P. 0000-0002-8716-0423","orcid":"https://orcid.org/0000-0002-8716-0423","contributorId":197604,"corporation":false,"usgs":true,"family":"Roberts","given":"Caleb","middleInitial":"P.","affiliations":[],"preferred":false,"id":735230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Uden, Daniel R.","contributorId":74258,"corporation":false,"usgs":true,"family":"Uden","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":735231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":734907,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Twidwell, Dirac","contributorId":187431,"corporation":false,"usgs":false,"family":"Twidwell","given":"Dirac","email":"","affiliations":[],"preferred":false,"id":735232,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195854,"text":"70195854 - 2018 - West Nile virus infection in American singer canaries: An experimental model in a highly susceptible avian species","interactions":[],"lastModifiedDate":"2023-06-21T15:17:03.091282","indexId":"70195854","displayToPublicDate":"2018-03-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3687,"text":"Veterinary Pathology","active":true,"publicationSubtype":{"id":10}},"title":"West Nile virus infection in American singer canaries: An experimental model in a highly susceptible avian species","docAbstract":"This study investigated the susceptibility of American singer canaries (Serinus canaria) to West Nile virus (WNV) infection. Adult canaries were inoculated with 105, 102, and 101plaque forming units (PFU) of WNV. All birds became infected and mortality occurred by 5 days postinoculation. The load of viral RNA as determined by RT-qPCR was dose dependent, and was higher at all doses than the level of viral RNA detected in American crows (Corvus brachyrhynchos) challenged with 105 PFU of WNV. In a subset of birds, viremia was detected by virus isolation; canaries inoculated with 101 PFU of WNV developed viremia exceeding 1010 PFU/mL serum, a log higher than American crows inoculated with 105 PFU of virus. In canaries euthanized at 3 days postinoculation, WNV was isolated at >107 PFU of virus/100 mg of lung, liver, heart, spleen, and kidney tissues. Pallor of the liver and splenomegaly were the most common macroscopic observations and histologic lesions were most severe in liver, spleen, and kidney, particularly in canaries challenged with 102 and 101 PFU. Immunoreactivity to WNV was pronounced in the liver and spleen. IgG antibodies to WNV were detected in serum by enzyme immunoassay in 11 of 21 (52%) challenged canaries and, in 4 of 5 (20%) of these sera, neutralization antibodies were detected at a titer ≥ 1:20. American singer canaries provide a useful model as this bird species is highly susceptible to WNV infection.
","language":"English","publisher":"American College of Veterinary Pathologists","doi":"10.1177/0300985818760377","usgsCitation":"Hofmeister, E.K., Lund, M., and Shearn-Bochsler, V.I., 2018, West Nile virus infection in American singer canaries: An experimental model in a highly susceptible avian species: Veterinary Pathology, v. 55, no. 4, p. 531-538, https://doi.org/10.1177/0300985818760377.","productDescription":"8 p.; Data Release","startPage":"531","endPage":"538","ipdsId":"IP-085734","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":460991,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/0300985818760377","text":"Publisher Index Page"},{"id":352250,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418295,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7XG9QD9","linkFileType":{"id":5,"text":"html"}}],"volume":"55","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-05","publicationStatus":"PW","scienceBaseUri":"5afee70de4b0da30c1bfc078","contributors":{"authors":[{"text":"Hofmeister, Erik K. 0000-0002-6360-3912 ehofmeister@usgs.gov","orcid":"https://orcid.org/0000-0002-6360-3912","contributorId":3230,"corporation":false,"usgs":true,"family":"Hofmeister","given":"Erik","email":"ehofmeister@usgs.gov","middleInitial":"K.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":730315,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lund, Melissa 0000-0003-4577-2015 mlund@usgs.gov","orcid":"https://orcid.org/0000-0003-4577-2015","contributorId":177923,"corporation":false,"usgs":true,"family":"Lund","given":"Melissa","email":"mlund@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":730317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shearn-Bochsler, Valerie I. 0000-0002-5590-6518 vbochsler@usgs.gov","orcid":"https://orcid.org/0000-0002-5590-6518","contributorId":3234,"corporation":false,"usgs":true,"family":"Shearn-Bochsler","given":"Valerie","email":"vbochsler@usgs.gov","middleInitial":"I.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":730316,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70195858,"text":"70195858 - 2018 - Metamodeling and mapping of nitrate flux in the unsaturated zone and groundwater, Wisconsin, USA","interactions":[],"lastModifiedDate":"2018-03-06T11:24:17","indexId":"70195858","displayToPublicDate":"2018-03-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Metamodeling and mapping of nitrate flux in the unsaturated zone and groundwater, Wisconsin, USA","docAbstract":"Nitrate contamination of groundwater in agricultural areas poses a major challenge to the sustainability of water resources. Aquifer vulnerability models are useful tools that can help resource managers identify areas of concern, but quantifying nitrogen (N) inputs in such models is challenging, especially at large spatial scales. We sought to improve regional nitrate (NO3−) input functions by characterizing unsaturated zone NO3− transport to groundwater through use of surrogate, machine-learning metamodels of a process-based N flux model. The metamodels used boosted regression trees (BRTs) to relate mappable landscape variables to parameters and outputs of a previous “vertical flux method” (VFM) applied at sampled wells in the Fox, Wolf, and Peshtigo (FWP) river basins in northeastern Wisconsin. In this context, the metamodels upscaled the VFM results throughout the region, and the VFM parameters and outputs are the metamodel response variables. The study area encompassed the domain of a detailed numerical model that provided additional predictor variables, including groundwater recharge, to the metamodels. We used a statistical learning framework to test a range of model complexities to identify suitable hyperparameters of the six BRT metamodels corresponding to each response variable of interest: NO3− source concentration factor (which determines the local NO3− input concentration); unsaturated zone travel time; NO3− concentration at the water table in 1980, 2000, and 2020 (three separate metamodels); and NO3− “extinction depth”, the eventual steady state depth of the NO3−front. The final metamodels were trained to 129 wells within the active numerical flow model area, and considered 58 mappable predictor variables compiled in a geographic information system (GIS). These metamodels had training and cross-validation testing R2 values of 0.52 – 0.86 and 0.22 – 0.38, respectively, and predictions were compiled as maps of the above response variables. Testing performance was reasonable, considering that we limited the metamodel predictor variables to mappable factors as opposed to using all available VFM input variables. Relationships between metamodel predictor variables and mapped outputs were generally consistent with expectations, e.g. with greater source concentrations and NO3− at the groundwater table in areas of intensive crop use and well drained soils. Shorter unsaturated zone travel times in poorly drained areas likely indicated preferential flow through clay soils, and a tendency for fine grained deposits to collocate with areas of shallower water table. Numerical estimates of groundwater recharge were important in the metamodels and may have been a proxy for N input and redox conditions in the northern FWP, which had shallow predicted NO3− extinction depth. The metamodel results provide proof-of-concept for regional characterization of unsaturated zone NO3− transport processes in a statistical framework based on readily mappable GIS input variables.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2018.02.029","usgsCitation":"Nolan, B.T., Green, C.T., Juckem, P.F., Liao, L., and Reddy, J.E., 2018, Metamodeling and mapping of nitrate flux in the unsaturated zone and groundwater, Wisconsin, USA: Journal of Hydrology, v. 559, p. 428-441, https://doi.org/10.1016/j.jhydrol.2018.02.029.","productDescription":"14 p.","startPage":"428","endPage":"441","ipdsId":"IP-088948","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":468931,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2018.02.029","text":"Publisher Index Page"},{"id":437988,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZC81VR","text":"USGS data release","linkHelpText":"Data Release for Metamodeling and Mapping of Nitrate Flux in the Unsaturated Zone and Groundwater, Wisconsin, USA"},{"id":352259,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90,\n 43.5\n ],\n [\n -87.38525390624999,\n 43.5\n ],\n [\n -87.38525390624999,\n 46\n ],\n [\n -90,\n 46\n ],\n [\n -90,\n 43.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"559","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee70ce4b0da30c1bfc074","contributors":{"authors":[{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":730332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Green, Christopher T. 0000-0002-6480-8194 ctgreen@usgs.gov","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":1343,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"ctgreen@usgs.gov","middleInitial":"T.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":730331,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Juckem, Paul F. 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":1905,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","middleInitial":"F.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liao, Lixia 0000-0003-2513-0680 lliao@usgs.gov","orcid":"https://orcid.org/0000-0003-2513-0680","contributorId":5311,"corporation":false,"usgs":true,"family":"Liao","given":"Lixia","email":"lliao@usgs.gov","affiliations":[],"preferred":true,"id":730335,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reddy, James E. 0000-0002-6998-7267 jreddy@usgs.gov","orcid":"https://orcid.org/0000-0002-6998-7267","contributorId":1080,"corporation":false,"usgs":true,"family":"Reddy","given":"James","email":"jreddy@usgs.gov","middleInitial":"E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730334,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194669,"text":"fs20173089 - 2018 - Rare earth element and rare metal inventory of central Asia","interactions":[],"lastModifiedDate":"2018-03-06T16:14:14","indexId":"fs20173089","displayToPublicDate":"2018-03-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3089","title":"Rare earth element and rare metal inventory of central Asia","docAbstract":"Rare earth elements (REE), with their unique physical and chemical properties, are an essential part of modern living. REE have enabled development and manufacture of high-performance materials, processes, and electronic technologies commonly used today in computing and communications, clean energy and transportation, medical treatment and health care, glass and ceramics, aerospace and defense, and metallurgy and chemical refining. Central Asia is an emerging REE and rare metals (RM) producing region. A newly compiled inventory of REE-RM-bearing mineral occurrences and delineation of areas-of-interest indicate this region may have considerable undiscovered resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173089","usgsCitation":"Mihalasky, M.J., Tucker, R.D., Renaud, K., and Verstraeten, I.M., 2018, Rare earth element and rare metal inventory of central Asia: U.S. Geological Survey Fact Sheet 2017–3089, 4 p., https://doi.org/10.3133/fs20173089.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-089992","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":352223,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3089/coverthb.jpg"},{"id":352224,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3089/fs20173089.pdf","text":"Report","size":"7.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2017-3089"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 45,\n 35\n ],\n [\n 90,\n 35\n ],\n [\n 90,\n 56\n ],\n [\n 45,\n 56\n ],\n [\n 45,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"The interannual variability of tidal marsh plant phenology is largely unknown and may have important ecological consequences. Marsh plants are critical to the biogeomorphic feedback processes that build estuarine soils, maintain marsh elevation relative to sea level, and sequester carbon. We calculated Tasseled Cap Greenness, a metric of plant biomass, using remotely sensed data available in the Landsat archive to assess how recent climate variation has affected biomass production and plant phenology across three maritime tidal marshes in the Pacific Northwest of the United States. First, we used clipped vegetation plots at one of our sites to confirm that tasseled cap greenness provided a useful measure of aboveground biomass (r2 = 0.72). We then used multiple measures of biomass each growing season over 20–25 years per study site and developed models to test how peak biomass and the date of peak biomass varied with 94 climate and sea-level metrics using generalized linear models and Akaike Information Criterion (AIC) model selection. Peak biomass was positively related to total annual precipitation, while the best predictor for date of peak biomass was average growing season temperature, with the peak 7.2 days earlier per degree C. Our study provides insight into how plants in maritime tidal marshes respond to interannual climate variation and demonstrates the utility of time-series remote sensing data to assess ecological responses to climate stressors.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2018.01.006","usgsCitation":"Buffington, K., Dugger, B.D., and Thorne, K., 2018, Climate-related variation in plant peak biomass and growth phenology across Pacific Northwest tidal marshes: Estuarine, Coastal and Shelf Science, v. 202, p. 212-221, https://doi.org/10.1016/j.ecss.2018.01.006.","productDescription":"10 p.","startPage":"212","endPage":"221","ipdsId":"IP-093014","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":437990,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7F18XZR","text":"USGS data release","linkHelpText":"Data for climate-related variation in plant peak biomass and growth phenology across Pacific Northwest tidal marshes"},{"id":353900,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.8486328125,\n 43.068887774169625\n ],\n [\n -122.51953124999999,\n 43.068887774169625\n ],\n [\n -122.51953124999999,\n 47.18971246448421\n ],\n [\n -124.8486328125,\n 47.18971246448421\n ],\n [\n -124.8486328125,\n 43.068887774169625\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"202","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee70de4b0da30c1bfc084","contributors":{"authors":[{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":734453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dugger, Bruce D.","contributorId":176167,"corporation":false,"usgs":false,"family":"Dugger","given":"Bruce","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":734454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":734452,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265020,"text":"70265020 - 2018 - Performance metrics for the assessment of satellite data products: An ocean color case study","interactions":[],"lastModifiedDate":"2025-03-28T14:10:39.577867","indexId":"70265020","displayToPublicDate":"2018-03-04T09:08:22","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5953,"text":"Optics Express","active":true,"publicationSubtype":{"id":10}},"title":"Performance metrics for the assessment of satellite data products: An ocean color case study","docAbstract":"Performance assessment of ocean color satellite data has generally relied on statistical metrics chosen for their common usage and the rationale for selecting certain metrics is infrequently explained. Commonly reported statistics based on mean squared errors, such as the coefficient of determination (r2), root mean square error, and regression slopes, are most appropriate for Gaussian distributions without outliers and, therefore, are often not ideal for ocean color algorithm performance assessment, which is often limited by sample availability. In contrast, metrics based on simple deviations, such as bias and mean absolute error, as well as pair-wise comparisons, often provide more robust and straightforward quantities for evaluating ocean color algorithms with non-Gaussian distributions and outliers. This study uses a SeaWiFS chlorophyll-a validation data set to demonstrate a framework for satellite data product assessment and recommends a multi-metric and user-dependent approach that can be applied within science, modeling, and resource management communities.
","language":"English","publisher":"Optica Publishing Group","doi":"10.1364/OE.26.007404","usgsCitation":"Seegers, B.N., Stumpf, R., Schaeffer, B., Loftin, K.A., and Werdell, P., 2018, Performance metrics for the assessment of satellite data products: An ocean color case study: Optics Express, v. 26, no. 6, p. 7404-7422, https://doi.org/10.1364/OE.26.007404.","productDescription":"19 p.","startPage":"7404","endPage":"7422","ipdsId":"IP-093210","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":488729,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1364/oe.26.007404","text":"Publisher Index Page"},{"id":483985,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Seegers, Bridget N.","contributorId":334288,"corporation":false,"usgs":false,"family":"Seegers","given":"Bridget","email":"","middleInitial":"N.","affiliations":[{"id":80107,"text":"Morgan State University, National Aeronautics and Space Administration","active":true,"usgs":false}],"preferred":false,"id":932328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stumpf, Richard P.","contributorId":193799,"corporation":false,"usgs":false,"family":"Stumpf","given":"Richard P.","affiliations":[],"preferred":false,"id":932329,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaeffer, Blake A.","contributorId":334287,"corporation":false,"usgs":false,"family":"Schaeffer","given":"Blake A.","affiliations":[{"id":35215,"text":"Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":932330,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loftin, Keith A. 0000-0001-5291-876X","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":221964,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":932331,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Werdell, P. Jeremy","contributorId":269868,"corporation":false,"usgs":false,"family":"Werdell","given":"P. Jeremy","affiliations":[{"id":37453,"text":"National Aeronautics and Space Administration","active":true,"usgs":false}],"preferred":false,"id":932332,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195813,"text":"70195813 - 2018 - Modeling intrinsic potential for beaver (Castor canadensis) habitat to inform restoration and climate change adaptation","interactions":[],"lastModifiedDate":"2018-03-02T16:06:47","indexId":"70195813","displayToPublicDate":"2018-03-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Modeling intrinsic potential for beaver (Castor canadensis) habitat to inform restoration and climate change adaptation","title":"Modeling intrinsic potential for beaver (Castor canadensis) habitat to inform restoration and climate change adaptation","docAbstract":"Through their dam-building activities and subsequent water storage, beaver have the potential to restore riparian ecosystems and offset some of the predicted effects of climate change by modulating streamflow. Thus, it is not surprising that reintroducing beaver to watersheds from which they have been extirpated is an often-used restoration and climate-adaptation strategy. Identifying sites for reintroduction, however, requires detailed information about habitat factors—information that is not often available at broad spatial scales. Here we explore the potential for beaver relocation throughout the Snohomish River Basin in Washington, USA with a model that identifies some of the basic building blocks of beaver habitat suitability and does so by relying solely on remotely sensed data. More specifically, we developed a generalized intrinsic potential model that draws on remotely sensed measures of stream gradient, stream width, and valley width to identify where beaver could become established if suitable vegetation were to be present. Thus, the model serves as a preliminary screening tool that can be applied over relatively large extents. We applied the model to 5,019 stream km and assessed the ability of the model to correctly predict beaver habitat by surveying for beavers in 352 stream reaches. To further assess the potential for relocation, we assessed land ownership, use, and land cover in the landscape surrounding stream reaches with varying levels of intrinsic potential. Model results showed that 33% of streams had moderate or high intrinsic potential for beaver habitat. We found that no site that was classified as having low intrinsic potential had any sign of beavers and that beaver were absent from nearly three quarters of potentially suitable sites, indicating that there are factors preventing the local population from occupying these areas. Of the riparian areas around streams with high intrinsic potential for beaver, 38% are on public lands and 17% are on large tracts of privately-owned timber land. Thus, although there are a large number of areas that could be suitable for relocation and restoration using beavers, current land use patterns may substantially limit feasibility in these areas.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0192538","usgsCitation":"Dittbrenner, B.J., Pollack, M.M., Schilling, J.W., Olden, J., Lawler, J.J., and Torgersen, C.E., 2018, Modeling intrinsic potential for beaver (Castor canadensis) habitat to inform restoration and climate change adaptation: PLoS ONE, v. 13, no. 2, e0192538; 15 p., https://doi.org/10.1371/journal.pone.0192538.","productDescription":"e0192538; 15 p.","ipdsId":"IP-093284","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":468936,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0192538","text":"Publisher Index Page"},{"id":352193,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Snohomish River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.37945556640624,\n 47.372314620566925\n ],\n [\n -120.9979248046875,\n 47.372314620566925\n ],\n [\n -120.9979248046875,\n 48.08908799881762\n ],\n [\n -122.37945556640624,\n 48.08908799881762\n ],\n [\n -122.37945556640624,\n 47.372314620566925\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee70ee4b0da30c1bfc088","contributors":{"authors":[{"text":"Dittbrenner, Benjamin J.","contributorId":202890,"corporation":false,"usgs":false,"family":"Dittbrenner","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":730022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pollack, Michael M.","contributorId":202891,"corporation":false,"usgs":false,"family":"Pollack","given":"Michael","email":"","middleInitial":"M.","affiliations":[{"id":36546,"text":"National Oceanic and Atmospheric Administration – Northwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":730023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schilling, Jason W.","contributorId":202892,"corporation":false,"usgs":false,"family":"Schilling","given":"Jason","email":"","middleInitial":"W.","affiliations":[{"id":36547,"text":"Tulalip Tribes Natural Resources","active":true,"usgs":false}],"preferred":false,"id":730024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olden, Julian D.","contributorId":202893,"corporation":false,"usgs":false,"family":"Olden","given":"Julian D.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":730025,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lawler, Joshua J.","contributorId":73327,"corporation":false,"usgs":false,"family":"Lawler","given":"Joshua","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":730026,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":730021,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70201617,"text":"70201617 - 2018 - Carbon budget of tidal wetlands, estuaries, and shelf waters of eastern North America","interactions":[],"lastModifiedDate":"2018-12-18T15:53:14","indexId":"70201617","displayToPublicDate":"2018-03-01T15:53:23","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Carbon budget of tidal wetlands, estuaries, and shelf waters of eastern North America","docAbstract":"Carbon cycling in the coastal zone affects global carbon budgets and is critical for understanding the urgent issues of hypoxia, acidification, and tidal wetland loss. However, there are no regional carbon budgets spanning the three main ecosystems in coastal waters: tidal wetlands, estuaries, and shelf waters. Here we construct such a budget for eastern North America using historical data, empirical models, remote sensing algorithms, and process‐based models. Considering the net fluxes of total carbon at the domain boundaries, 59 ± 12% (± 2 standard errors) of the carbon entering is from rivers and 41 ± 12% is from the atmosphere, while 80 ± 9% of the carbon leaving is exported to the open ocean and 20 ± 9% is buried. Net lateral carbon transfers between the three main ecosystem types are comparable to fluxes at the domain boundaries. Each ecosystem type contributes substantially to exchange with the atmosphere, with CO2uptake split evenly between tidal wetlands and shelf waters, and estuarine CO2outgassing offsetting half of the uptake. Similarly, burial is about equal in tidal wetlands and shelf waters, while estuaries play a smaller but still substantial role. The importance of tidal wetlands and estuaries in the overall budget is remarkable given that they, respectively, make up only 2.4 and 8.9% of the study domain area. This study shows that coastal carbon budgets should explicitly include tidal wetlands, estuaries, shelf waters, and the linkages between them; ignoring any of them may produce a biased picture of coastal carbon cycling.
","language":"English","publisher":"AGU","doi":"10.1002/2017GB005790","usgsCitation":"Najjar, R., Herrmann, M., Alexander, R.B., Boyer, E., Burdige, D., Butman, D., Cai, W., Canuel, E., Chen, R., Friedrichs, M.A., Feagin, R., Griffith, P.C., Hinson, A., Holmquist, J., Hu, X., Kemp, W., Kroeger, K.D., Mannino, A., McCallister, S., McGillis, W., Mulholland, M., Pilskaln, C.H., Salisbury, J., Signorini, S., St. Laurent, P., Tian, H., Tzortziou, M., Vlahos, P., Wan, Z., and Zimmerman, R.C., 2018, Carbon budget of tidal wetlands, estuaries, and shelf waters of eastern North America: Global Biogeochemical Cycles, v. 32, no. 3, p. 389-416, https://doi.org/10.1002/2017GB005790.","productDescription":"28 p.","startPage":"389","endPage":"416","ipdsId":"IP-092980","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468939,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2017gb005790","text":"External Repository"},{"id":360518,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"32","issue":"3","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-11","publicationStatus":"PW","scienceBaseUri":"5c1a1534e4b0708288c23542","contributors":{"authors":[{"text":"Najjar, R.G.","contributorId":211647,"corporation":false,"usgs":false,"family":"Najjar","given":"R.G.","affiliations":[{"id":38295,"text":"Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, Pennsylvania, USA.","active":true,"usgs":false}],"preferred":false,"id":754585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herrmann, M.","contributorId":211648,"corporation":false,"usgs":false,"family":"Herrmann","given":"M.","email":"","affiliations":[{"id":38295,"text":"Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, Pennsylvania, USA.","active":true,"usgs":false}],"preferred":false,"id":754586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alexander, Richard B. 0000-0001-9166-0626 ralex@usgs.gov","orcid":"https://orcid.org/0000-0001-9166-0626","contributorId":541,"corporation":false,"usgs":true,"family":"Alexander","given":"Richard","email":"ralex@usgs.gov","middleInitial":"B.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":754587,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyer, E.W.","contributorId":56358,"corporation":false,"usgs":false,"family":"Boyer","given":"E.W.","email":"","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":754588,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burdige, D. 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A. M.","contributorId":211654,"corporation":false,"usgs":false,"family":"Friedrichs","given":"M.","email":"","middleInitial":"A. M.","affiliations":[{"id":38299,"text":"Virginia Institute of Marine Science, College of William & Mary, Gloucester Point, Virginia, USA","active":true,"usgs":false}],"preferred":false,"id":754594,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Feagin, R.A.","contributorId":211655,"corporation":false,"usgs":false,"family":"Feagin","given":"R.A.","email":"","affiliations":[{"id":38301,"text":"Department of Ecosystem Science and Management, Texas A&M University, College Station, Texas, USA","active":true,"usgs":false}],"preferred":false,"id":754595,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Griffith, P. 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Salmon have two major isoforms of the catalytic alpha subunit of Na+/K+-ATPase (NKA), with NKAα1a being the major freshwater (FW) isoform and NKAα1b the major seawater (SW) isoform. Here we evaluate physiological markers of SW preparedness and NKAα1a and NKAα1b isoforms after short-term exposure to acidified water and acidified water with added Al (acid–Al). Atlantic salmon smolts were exposed to low ion FW (Control), low ion acidic water (pH 5.2; acid), and low ion acidic water (pH 5.2) with moderate levels of added inorganic Al (35 μg·L−1; acid–Al) for 4 days. Acid exposure resulted in loss of salinity tolerance (higher plasma chloride (Cl) after SW exposure) and significantly decreased the levels of gill NKAα1b but not NKAα1a protein abundance. Acid–Al exposure resulted in loss of plasma Cl in FW and higher plasma Cl in SW and decreased NKAα1a and NKAα1b abundance. The loss of salinity tolerance in smolts can be explained by the differential sensitivity of NKA isoforms to acid.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2017-0198","usgsCitation":"Regish, A.M., Kelly, J.T., O'Dea, M., and McCormick, S.D., 2018, Sensitivity of Na+/K+-ATPase isoforms to acid and aluminum explains differential effects on Atlantic salmon osmoregulation in fresh water and seawater: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 8, p. 1319-1328, https://doi.org/10.1139/cjfas-2017-0198.","productDescription":"20 p.","startPage":"1319","endPage":"1328","ipdsId":"IP-085421","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":361033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Regish, Amy M. 0000-0003-4747-4265 aregish@usgs.gov","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":5415,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"aregish@usgs.gov","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":756692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelly, John T.","contributorId":212827,"corporation":false,"usgs":false,"family":"Kelly","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":38688,"text":"Department of Biology & Environmental Science, University of New Haven","active":true,"usgs":false}],"preferred":false,"id":756693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Dea, Michael F.","contributorId":212828,"corporation":false,"usgs":false,"family":"O'Dea","given":"Michael F.","affiliations":[],"preferred":false,"id":756694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":756695,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}