The 2017 Discovering the Deep expedition provided the first glimpse of the deep-sea geology and ecology of the deepwater regions of Swains Island, the Howland and Baker Islands Unit of PRIMNM, Phoenix Islands Protected Areas (PIPA), and the Tokelau Region (Figure 1). Prior to this expedition, virtually no visual reconnaissance had been conducted in any of these areas below scuba diving depths.
ROV dives during this expedition focused on deep-sea corals, sponges, and fish assemblages, with particular interest in locating high-density and high-diversity biological communities. Indeed, nine high-density biological communities were documented out of the 19 dive sites explored. Many of these observations were new records for these regions, and several likely yielded species new to science. Acoustic mapping operations covered more than 47,000 km2 of seafloor. The collected imagery and specimens will improve our understanding of the distribution of deep-sea corals and sponges, the ages of the seafloor features, and overall geological context of these different environments.
","language":"English","publisher":"The Oceanography Society","doi":"10.5670/oceanog.2018.supplement.01","usgsCitation":"Demopoulos, A.W., Auscavitch, S., Sowers, D., Pawlenko, N., and Kennedy, B.R., 2018, Discovering the deep: Exploring remote Pacific marine protected areas: Oceanography, v. 31, no. 1 Supplement, p. 76-77, https://doi.org/10.5670/oceanog.2018.supplement.01.","productDescription":"2 p.","startPage":"76","endPage":"77","ipdsId":"IP-091987","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468945,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5670/oceanog.2018.supplement.01","text":"Publisher Index Page"},{"id":361873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"1 Supplement","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":145681,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":758992,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Auscavitch, Steven","contributorId":168299,"corporation":false,"usgs":false,"family":"Auscavitch","given":"Steven","affiliations":[{"id":12547,"text":"Temple University","active":true,"usgs":false}],"preferred":false,"id":758994,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sowers, Derek","contributorId":214036,"corporation":false,"usgs":false,"family":"Sowers","given":"Derek","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":758995,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pawlenko, Nikolai","contributorId":214037,"corporation":false,"usgs":false,"family":"Pawlenko","given":"Nikolai","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":758996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kennedy, Brian R. C.","contributorId":149603,"corporation":false,"usgs":false,"family":"Kennedy","given":"Brian","email":"","middleInitial":"R. C.","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":758993,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198339,"text":"70198339 - 2018 - Individual species–area relationships in temperate coniferous forests","interactions":[],"lastModifiedDate":"2018-07-31T08:55:23","indexId":"70198339","displayToPublicDate":"2018-03-01T08:55:16","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2490,"text":"Journal of Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Individual species–area relationships in temperate coniferous forests","docAbstract":"Questions
What drives individual species–area relationships in temperate coniferous forests?
Location
Two 25.6‐ha forest plots on the Pacific Slope of North America, one in California, and one in Washington State.
Methods
We mapped all trees ≥1 cm in diameter and examined tree species diversity of their local neighbourhoods by calculating the individual species–area relationship for each species and for each of three diameter classes (saplings, mature trees and large‐diameter trees).
Results
In the California plot, small trees in four of the five major species occurred in neighbourhoods with higher levels of diversity than would be expected at random. In the Washington plot, small trees for four of five abundant species had neighbourhoods with lower than expected diversity at distances ≤5 m for small trees. However, at distances >5 m, all five species showed higher than expected diversity in their neighbourhoods. Larger trees at both plots tended to occur in neighbourhoods with lower than expected diversity, and no large‐diameter focal species had neighbourhoods with higher than expected diversity.
Conclusion
Diversity and co‐existence in temperate conifer‐dominated forests do not appear to be the result of random processes. Competitive interactions appear to dominate for the largest trees of most species, resulting in neighbourhoods with lower diversity. For smaller trees, we suggest that a positive response to environmental heterogeneity is the likely driver of neighbourhoods with higher than expected diversity, although we cannot rule out the possibility that facilitation or conspecific negative density dependence (CNDD) also play a role.
The U.S. Geological Survey tested the utility of imaging spectroscopy (also referred to as hyperspectral remote sensing) as an aid to regional mineral exploration efforts in remote parts of Alaska. Airborne imaging spectrometer data were collected in 2014 over unmined porphyry Cu deposits in the eastern Alaska Range using the HyMap™ sensor. Maps of the distributions of predominant minerals, made by matching reflectance signatures in the remotely sensed data to reference spectra in the shortwave infrared region, do not uniquely discriminate individual rock units. However, they do highlight hydrothermal alteration associated with porphyry deposits and prospects hosted mostly within the Nabesna pluton. In and around porphyry Cu deposits at Orange Hill and Bond Creek, unique spectral signatures are related to variations in chlorite and white mica abundance and their chemical composition. This is best revealed in the longer-wavelength 2,200-nm Al-OH absorption feature positions in pixels spectrally dominated by white mica proximal to porphyry deposits. Similar spectral signatures of chlorite and white mica wavelength positions were also recognized away from the porphyry deposits; follow-up sampling identified these satellite areas to also contain Cu-Mo-Au mineralized rock. Our study confirms that airborne imaging spectroscopy has application for regional mineral exploration in exposed mountainous terrain in Alaska.
We compare the ability of eight machine-learning models (elastic net, gradient boosting, kernel-k-nearest neighbors, two variants of support vector machines, M5-cubist, random forest, and a meta-learning ensemble M5-cubist model) and four baseline models (ordinary kriging, a unit area discharge model, and two variants of censored regression) to generate estimates of the annual minimum 7-day mean streamflow with an annual exceedance probability of 90% (7Q10) at 224 unregulated sites in South Carolina, Georgia, and Alabama, USA. The machine-learning models produced substantially lower cross validation errors compared to the baseline models. The meta-learning M5-cubist model had the lowest root-mean-squared-error of 26.72 cubic feet per second. Partial dependence plots show that 7Q10s are likely moderated by late summer and early fall precipitation and the infiltration capacity of basin soils.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2017.12.021","usgsCitation":"Worland, S.C., Farmer, W.H., and Kiang, J.E., 2018, Improving predictions of hydrological low-flow indices in ungaged basins using machine learning: Environmental Modelling and Software, v. 101, p. 169-182, https://doi.org/10.1016/j.envsoft.2017.12.021.","productDescription":"14 p.","startPage":"169","endPage":"182","ipdsId":"IP-080308","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":468958,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2017.12.021","text":"Publisher Index Page"},{"id":437995,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CR5S4T","text":"USGS data release","linkHelpText":"7Q10 records and basin characteristics for 224 basins in South Carolina, Georgia, and Alabama (2015)"},{"id":355718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Georgia, South 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\"}}]}","volume":"101","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc483e4b0f5d57878ea9e","contributors":{"authors":[{"text":"Worland, Scott C. 0000-0001-6384-2457 scworland@usgs.gov","orcid":"https://orcid.org/0000-0001-6384-2457","contributorId":5802,"corporation":false,"usgs":true,"family":"Worland","given":"Scott","email":"scworland@usgs.gov","middleInitial":"C.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":740154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":740155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":740156,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159602,"text":"sir20155164 - 2018 - Volcanic aquifers of Hawai‘i—Hydrogeology, water budgets, and conceptual models","interactions":[],"lastModifiedDate":"2023-06-08T16:40:09.114831","indexId":"sir20155164","displayToPublicDate":"2018-03-01T00:00:00","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":"2015-5164","displayTitle":"Volcanic Aquifers of Hawai‘i—Hydrogeology, Water budgets, and Conceptual Models","title":"Volcanic aquifers of Hawai‘i—Hydrogeology, water budgets, and conceptual models","docAbstract":"Hawai‘i’s aquifers have limited capacity to store fresh groundwater because each island is small and surrounded by saltwater. Saltwater also underlies much of the fresh groundwater. Fresh groundwater resources are, therefore, particularly vulnerable to human activity, short-term climate cycles, and long-term climate change. Availability of fresh groundwater for human use is constrained by the degree to which the impacts of withdrawal—such as lowering of the water table, saltwater intrusion, and reduction in the natural discharge to springs, streams, wetlands, and submarine seeps—are deemed acceptable. This report describes the hydrogeologic framework, groundwater budgets (inflows and outflows), conceptual models of groundwater occurrence and movement, and the factors limiting groundwater availability for the largest and most populated of the Hawaiian Islands—Kaua‘i, O‘ahu, Maui, and Hawai‘i Island.
The bulk of each of Hawai‘i’s islands is built of many thin lava flows erupted from shield volcanoes; the great piles of lava flows form highly permeable aquifers. In some areas, low-permeability dikes cutting across the lava flows, or low-permeability ash and soil horizons interlayered with the lava flows, can substantially alter groundwater flow. On some islands, sedimentary rocks form thick semiconfining coastal-plain deposits, locally known as caprock, that impede natural groundwater discharge to the ocean. In some regions, thick lava flows that ponded in preexisting depressions form aquifers that are much less permeable than aquifers formed by thin lava flows.
Fresh groundwater inflow to Hawai‘i’s aquifers comes from recharge. For predevelopment conditions (1870), estimates of groundwater recharge from this study are 871, 675, 1,279, and 5,291 million gallons per day (Mgal/d) for Kaua‘i, O‘ahu, Maui, and Hawai‘i Island, respectively. Estimates of recharge for recent conditions (2010 land cover and 1978–2007 rainfall for Kaua‘i, O‘ahu, and Maui; 2008 land cover and 1916–1983 rainfall for Hawai‘i Island) are 875, 660, 1,308, and 6,595 Mgal/d for Kaua‘i, O‘ahu, Maui, and Hawai‘i Island, respectively. Recent recharge values differ from predevelopment recharge values by only a few percent for all islands except Hawai‘i Island, where changes in forest cover affected recharge. Spatial distribution of recharge mimics the orographic rainfall pattern—recharge is high on windward slopes and mountain peaks below the top of the trade-wind inversion. Human activity such as irrigation also contributes to recharge in some areas.
Outflows from Hawai‘i’s aquifers include withdrawals from wells and natural groundwater discharge to springs, streams, wetlands, and submarine seeps. Under predevelopment conditions, groundwater withdrawal is assumed to be negligible and natural groundwater discharge probably was equal, or close, to recharge. Under recent conditions (2000–2010), groundwater withdrawal averaged 19, 209, 104, and 103 Mgal/d on Kaua‘i, O‘ahu, Maui, and Hawai‘i Island, respectively. If recent withdrawal and recharge rates are maintained until steady state is achieved, natural groundwater discharge will be reduced by an amount equal to the withdrawal rate. Total recent withdrawal for the four islands is only about 5 percent of total recharge, but about half of the withdrawal comes from O‘ahu, whereas O‘ahu receives only 7 percent of the total recharge. Effects of high withdrawals on O‘ahu cannot be mitigated by the lower withdrawals on other islands because no freshwater flows between islands. Even within an island, high withdrawals from one area cannot be completely mitigated by recharge in another area. Water-level, saltwater/freshwater-transition-zone, spring, and stream base-flow data indicate an overall reduction in storage for most areas where groundwater has been developed.
Groundwater occurrence and movement in Hawai‘i’s volcanic aquifers can be described in terms of four conceptual models: (1) fresh groundwater lenses in high-permeability lava-flow aquifers, (2) aquifers with groundwater impounded by dikes, (3) thickly saturated low-permeability aquifers, and (4) perched aquifers. In Hawai‘i, most fresh groundwater withdrawn for human use comes from freshwater lenses in the dike-free high-permeability lava-flow aquifers where the principal limiting factor to groundwater availability is saltwater intrusion, but impacts of reduced natural groundwater discharge may also limit availability. Dike-impounded groundwater is common near the center of Hawaiian shield volcanoes, where water moves and is stored in permeable lava flows between the dikes; groundwater availability in these aquifers is primarily limited by storage depletion and reduction of flow to adjacent aquifers and natural groundwater discharge. Thickly saturated low-permeability aquifers have been identified on Kaua‘i and Maui; groundwater availability is primarily limited by streamflow depletion and water-table decline. Perched groundwater is postulated to exist in some areas of Hawai‘i, but store much less water than other modes ofgroundwater occurrence. Limits on groundwater availability in perched aquifers include the potential of reducing inflow to other groundwater settings and reducing natural discharge and stream seepage. Some groundwater bodies in Hawai‘i are enigmatic; consequences of groundwater development in these bodies and their relation to groundwater availability are not completely understood.
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\"}}]}","edition":"Version 1.0: June 13, 2016; Version 2.0: March 1, 2018","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
This study explores the relationship between municipal water use and an array of climate, economic, behavioral, and policy variables across the contiguous U.S. The relationship is explored using Bayesian‐hierarchical regression models for over 2,500 counties, 18 covariates, and three higher‐level grouping variables. Additionally, a second analysis is included for 83 cities where water price and water conservation policy information is available. A hierarchical model using the nine climate regions (product of National Oceanic and Atmospheric Administration) as the higher‐level groups results in the best out‐of‐sample performance, as estimated by the Widely Available Information Criterion, compared to counties grouped by urban continuum classification or primary economic activity. The regression coefficients indicate that the controls on water use are not uniform across the nation: e.g., counties in the Northeast and Northwest climate regions are more sensitive to social variables, whereas counties in the Southwest and East North Central climate regions are more sensitive to environmental variables. For the national city‐level model, it appears that arid cities with a high cost of living and relatively low water bills sell more water per customer, but as with the county‐level model, the effect of each variable depends heavily on where a city is located.
","language":"English","publisher":"AGU","doi":"10.1002/2017WR021268","usgsCitation":"Worland, S.C., Steinschneider, S., and Hornberger, G.M., 2018, Drivers of variability in public‐supply water use across the contiguous United States: Water Resources Research, v. 54, no. 3, p. 1868-1889, https://doi.org/10.1002/2017WR021268.","productDescription":"22 p.","startPage":"1868","endPage":"1889","ipdsId":"IP-087770","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":488785,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr021268","text":"Publisher Index Page"},{"id":355717,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"54","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-15","publicationStatus":"PW","scienceBaseUri":"5b6fc483e4b0f5d57878ea9c","contributors":{"authors":[{"text":"Worland, Scott C. 0000-0001-6384-2457 scworland@usgs.gov","orcid":"https://orcid.org/0000-0001-6384-2457","contributorId":5802,"corporation":false,"usgs":true,"family":"Worland","given":"Scott","email":"scworland@usgs.gov","middleInitial":"C.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":740159,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steinschneider, Scott 0000-0002-8882-1908","orcid":"https://orcid.org/0000-0002-8882-1908","contributorId":206359,"corporation":false,"usgs":false,"family":"Steinschneider","given":"Scott","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":740160,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hornberger, George M.","contributorId":206360,"corporation":false,"usgs":false,"family":"Hornberger","given":"George","email":"","middleInitial":"M.","affiliations":[{"id":36656,"text":"Vanderbilt University","active":true,"usgs":false}],"preferred":false,"id":740161,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196225,"text":"70196225 - 2018 - Stability and change in kelp forest habitats at San Nicolas Island","interactions":[],"lastModifiedDate":"2020-12-16T16:29:35.001376","indexId":"70196225","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Stability and change in kelp forest habitats at San Nicolas Island","docAbstract":"Kelp forest communities are highly variable over space and time. Despite this complexity it has been suggested that kelp forest communities can be classified into one of 2 states: kelp dominated or sea urchin dominated. It has been further hypothesized that these represent “alternate stable states” because a site can remain in either of these states for decades before some perturbation causes a rapid shift to the other state. Our research group has maintained a subtidal community monitoring program for 38 years at San Nicolas Island consisting of twice-annual scuba-based surveys at 6 sites distributed within 4 regions around the island. Three types of perturbations are thought to be relevant to subtidal community dynamics at San Nicolas: (1) physical disturbances in the form of major storm and El Niño/Southern Oscillation (ENSO) events; (2) invertebrate diseases, which periodically decimate urchin populations; and (3) the reintroduction and subsequent increase of sea otters (Enhydra lutris nereis). These 3 perturbations differ in spatial and temporal specificity; physical disturbances and disease outbreaks occur periodically and could affect all 4 regions, while sea otter predation has been concentrated primarily at the West End sites over the last 15 years. The different types of perturbations and the duration of the time series at the kelp forests at San Nicolas make the data set ideal for testing the “alternate stable state” hypothesis. We use nonmetric multidimensional scaling (NMDS) to examine spatial and temporal patterns of community similarity at the 4 regions. In particular, we evaluate support for the existence of stable states, which are represented on NMDS plots as distinct spatial clusters. Community dynamics at each site approximated a biased random walk in NMDS space, with one or more basins of attraction and occasional jumps between basins. We found evidence for alternative stable states at some sites, and we show that transitions from one stable state to another may be influenced by interactions between multiple perturbations.
","language":"English","publisher":"Western North American Naturalist Publications","doi":"10.3398/064.078.0407","usgsCitation":"Kenner, M.C., and Tinker, M.T., 2018, Stability and change in kelp forest habitats at San Nicolas Island: Western North American Naturalist, v. 78, no. 4, p. 633-643, https://doi.org/10.3398/064.078.0407.","productDescription":"11 p.","startPage":"633","endPage":"643","ipdsId":"IP-086463","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488846,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarsarchive.byu.edu/wnan/vol78/iss4/14","text":"External Repository"},{"id":352844,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.58824157714842,\n 33.20881849225547\n ],\n [\n -119.42893981933592,\n 33.20881849225547\n ],\n [\n -119.42893981933592,\n 33.289785856885224\n ],\n [\n -119.58824157714842,\n 33.289785856885224\n ],\n [\n -119.58824157714842,\n 33.20881849225547\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee710e4b0da30c1bfc0b6","contributors":{"authors":[{"text":"Kenner, Michael C. 0000-0003-4659-461X","orcid":"https://orcid.org/0000-0003-4659-461X","contributorId":203543,"corporation":false,"usgs":false,"family":"Kenner","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":731747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":731746,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70196258,"text":"70196258 - 2018 - Movers and stayers: Novel assemblages in changing environments","interactions":[],"lastModifiedDate":"2018-03-28T13:39:51","indexId":"70196258","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3653,"text":"Trends in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Movers and stayers: Novel assemblages in changing environments","docAbstract":"How species will respond to ongoing climate and other change is of increasing concern.
Most attention is given to how species move or are moved, but many species stay.
Understanding the dynamics of new species combinations is essential for successful conservation in a changing climate.
Increased attention to species movement in response to environmental change highlights the need to consider changes in species distributions and altered biological assemblages. Such changes are well known from paleoecological studies, but have accelerated with ongoing pervasive human influence. In addition to species that move, some species will stay put, leading to an array of novel interactions. Species show a variety of responses that can allow movement or persistence. Conservation and restoration actions have traditionally focused on maintaining or returning species in particular places, but increasingly also include interventions that facilitate movement. Approaches are required that incorporate the fluidity of biotic assemblages into the goals set and interventions deployed.
This report describes options for monitoring the status and population trends of the golden eagle (Aquila chrysaetos) within the Desert Renewable Energy Conservation Plan (DRECP) area of Southern California in maintaining stable or increasing population in the planning area. The report profiles the ecology of golden eagles in the region and provides a range of potential sampling options to address monitoring needs and objectives. This approach also focused on links between changes in human land-use, golden eagle nesting and foraging habitat conditions, and population dynamics. The report outlines how monitoring data from demographic, prey, and habitat studies were used to develop a predictive demographic model for golden eagles in the DRECP area. Results from the model simulations suggest increases in renewable energy development could have negative consequences for population trajectories. Results also suggest site-specific conservation actions could reduce the magnitude of negative impacts to the local population of eagles.
A monitoring framework is proposed including: (1) annual assessments of site-occupancy and reproduction by territorial pairs of golden eagles (including rates at which sites become colonized or vacated over time); (2) estimates of survival, movements, and intensity of use of landscapes by breeding and non-breeding golden eagles; (3) periodic (conducted every two to four years) assessments of nesting and foraging habitats, prey populations, and associations with land-use and management activities; and (4) updating the predictive demographic model with new information obtained on eagles and associated population stressors.
The results of this research were published in the Journal of Rapture Research, Wiens, David,Inman, Rich D., Esque, Todd C., Longshore, Kathleen M. and Nussear, Kenneth (2017). Spatial Demographic Models to Inform Conservation Planning of Golden Eagles in Renewable Energy Landscapes. 51(3):234-257.
","language":"English","publisher":"California Energy Commission","usgsCitation":"Wiens, D., Kolar, P., and Katzner, T., 2018, Golden Eagle Monitoring Plan for the Desert Renewable Energy Conservation Plan, 99 p.","productDescription":"99 p.","ipdsId":"IP-086130","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":353243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":353224,"type":{"id":11,"text":"Document"},"url":"https://www.energy.ca.gov/2018publications/CEC-500-2018-008/CEC-500-2018-008.pdf"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee70fe4b0da30c1bfc0aa","contributors":{"authors":[{"text":"Wiens, David 0000-0002-2020-038X jwiens@usgs.gov","orcid":"https://orcid.org/0000-0002-2020-038X","contributorId":167538,"corporation":false,"usgs":true,"family":"Wiens","given":"David","email":"jwiens@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":732901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolar, Patrick 0000-0002-0076-7565 pkolar@usgs.gov","orcid":"https://orcid.org/0000-0002-0076-7565","contributorId":189512,"corporation":false,"usgs":true,"family":"Kolar","given":"Patrick","email":"pkolar@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":732902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":732903,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196210,"text":"70196210 - 2018 - Local extinction of the Asian tiger mosquito (Aedes albopictus) following rat eradication on Palmyra Atol","interactions":[],"lastModifiedDate":"2018-03-26T16:27:48","indexId":"70196210","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1028,"text":"Biology Letters","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Local extinction of the Asian tiger mosquito (Aedes albopictus) following rat eradication on Palmyra Atol","title":"Local extinction of the Asian tiger mosquito (Aedes albopictus) following rat eradication on Palmyra Atol","docAbstract":"The Asian tiger mosquito, Aedes albopictus, appears to have been extirpated from Palmyra Atoll following rat eradication. Anecdotal biting reports, collection records, and regular captures in black-light traps showed the species was present before rat eradication. Since then, there have been no biting reports and no captures over 2 years of extensive trapping (black-light and scent traps). By contrast, the southern house mosquito, Culex quinquefasciatus, was abundant before and after rat eradication. We hypothesize that mammals were a substantial and preferred blood meal for Aedes, whereas Culex feeds mostly on seabirds. Therefore, after rat eradication, humans and seabirds alone could not support positive population growth or maintenance of Aedes. This seems to be the first documented accidental secondary extinction of a mosquito. Furthermore, it suggests that preferred host abundance can limit mosquito populations, opening new directions for controlling important disease vectors that depend on introduced species like rats.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rsbl.2017.0743","usgsCitation":"Lafferty, K.D., McLaughlin, J.P., Gruner, D.S., Bogar, T.A., Bui, A., Childress, J.N., Espinoza, M., Forbes, E.S., Johnston, C.A., Klope, M., Kuile, A.M., Lee, M., Plummer, K.A., Weber, D., Young, R.T., and Young, H.S., 2018, Local extinction of the Asian tiger mosquito (Aedes albopictus) following rat eradication on Palmyra Atol: Biology Letters, v. 14, no. 2, Article 20170743; 4 p., https://doi.org/10.1098/rsbl.2017.0743.","productDescription":"Article 20170743; 4 p.","ipdsId":"IP-093187","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":461007,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsbl.2017.0743","text":"Publisher Index Page"},{"id":352773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Palmyra Atoll","volume":"14","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee710e4b0da30c1bfc0ba","contributors":{"authors":[{"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":731687,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLaughlin, John P. 0000-0002-8756-2123","orcid":"https://orcid.org/0000-0002-8756-2123","contributorId":203516,"corporation":false,"usgs":false,"family":"McLaughlin","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":731688,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gruner, Daniel S.","contributorId":195507,"corporation":false,"usgs":false,"family":"Gruner","given":"Daniel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":731689,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bogar, Taylor A.","contributorId":203517,"corporation":false,"usgs":false,"family":"Bogar","given":"Taylor","email":"","middleInitial":"A.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":731690,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bui, An","contributorId":203518,"corporation":false,"usgs":false,"family":"Bui","given":"An","email":"","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":731691,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Childress, Jasmine N. 0000-0003-0423-4069","orcid":"https://orcid.org/0000-0003-0423-4069","contributorId":203519,"corporation":false,"usgs":false,"family":"Childress","given":"Jasmine","email":"","middleInitial":"N.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":731692,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Espinoza, Magaly","contributorId":203520,"corporation":false,"usgs":false,"family":"Espinoza","given":"Magaly","email":"","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":731693,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Forbes, Elizabeth S.","contributorId":203521,"corporation":false,"usgs":false,"family":"Forbes","given":"Elizabeth","email":"","middleInitial":"S.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":731694,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Johnston, Cora A.","contributorId":203522,"corporation":false,"usgs":false,"family":"Johnston","given":"Cora","email":"","middleInitial":"A.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":731695,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Klope, Maggie","contributorId":203523,"corporation":false,"usgs":false,"family":"Klope","given":"Maggie","email":"","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":731696,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kuile, Ana Miller-ter","contributorId":203524,"corporation":false,"usgs":false,"family":"Kuile","given":"Ana","email":"","middleInitial":"Miller-ter","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":731697,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lee, Michelle","contributorId":203525,"corporation":false,"usgs":false,"family":"Lee","given":"Michelle","email":"","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":731698,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Plummer, Katherine A.","contributorId":203526,"corporation":false,"usgs":false,"family":"Plummer","given":"Katherine","email":"","middleInitial":"A.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":731699,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Weber, David A.","contributorId":203527,"corporation":false,"usgs":false,"family":"Weber","given":"David A.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":731700,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Young, Ronald T.","contributorId":203528,"corporation":false,"usgs":false,"family":"Young","given":"Ronald","email":"","middleInitial":"T.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":731701,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Young, Hillary S.","contributorId":53711,"corporation":false,"usgs":false,"family":"Young","given":"Hillary","email":"","middleInitial":"S.","affiliations":[{"id":13007,"text":"Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":731702,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70196176,"text":"70196176 - 2018 - Fire and climate suitability for woody vegetation communities in the south central United States","interactions":[],"lastModifiedDate":"2019-10-28T09:26:31","indexId":"70196176","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Fire and climate suitability for woody vegetation communities in the south central United States","docAbstract":"Climate and fire are primary drivers of plant species distributions. Long-term management of south central United States woody vegetation communities can benefit from information on potential changes in climate and fire frequencies, and how these changes might affect plant communities. We used historical (1900 to 1929) and future (2040 to 2069 and 2070 to 2099) projected climate data for the conterminous US to estimate reference and future fire probabilities\nusing a physical chemistry fire frequency model. We then used the fire probability data with additional climate parameters to construct maximum entropy environmental suitability models for three south central US vegetation communities. The modeled communities included an oak type (dominated by post oak, Quercus stellata Wangenh., and blackjack oak, Q. marilandica Münchh.), a mesquite type (dominated by honey mesquite, Prosopis glandulosa Torr., and velvet mesquite, P. velutina Wooton), and a pinyon−juniper type (dominated by pinyon pine, Pinus edulis Engelm., and Utah juniper, Juniperus osteosperma [Torr.] Little). We mapped baseline and future mean fire-climate suitability using data from three global climate models for 2040 to 2069 and 2070 to 2099; we also mapped future locations of threshold conditions for which all three models agreed on suitability for each community. Future projections included northward, southward, and eastward shifts in suitable conditions for the oaks along a broad path of fire-climate stability; an overall reduction in suitable area for historic mesquite communities coupled with potential expansion to new areas; and constriction and isolation of suitable conditions for pinyon−juniper communities. The inclusion of fire probability adds an important driver of vegetation distribution to climate envelope modeling. The simple models showed good fit, but future projections failed to account for future management activities or land use changes. Results provided information on potential future de-coupling and spatial re-arrangement of environmental conditions under which these communities have historically persisted and been managed. In particular, consensus threshold maps can inform long-term planning for maintenance or restoration of these communities, and they can be used as a potential tool for other communities in fire-prone environments within the study area and beyond its borders.","language":"English","publisher":"Springer","doi":"10.4996/fireecology.140110612","usgsCitation":"Stroh, E., Struckhoff, M., Stambaugh, M.C., and Guyette, R.P., 2018, Fire and climate suitability for woody vegetation communities in the south central United States: Fire Ecology, v. 14, no. 1, p. 106-124, https://doi.org/10.4996/fireecology.140110612.","productDescription":"19 p.","startPage":"106","endPage":"124","ipdsId":"IP-088298","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":468948,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4996/fireecology.140110612","text":"Publisher Index Page"},{"id":352785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-01","publicationStatus":"PW","scienceBaseUri":"5afee711e4b0da30c1bfc0bc","contributors":{"authors":[{"text":"Stroh, Esther 0000-0003-4291-4647","orcid":"https://orcid.org/0000-0003-4291-4647","contributorId":202825,"corporation":false,"usgs":true,"family":"Stroh","given":"Esther","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":731537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Struckhoff, Matthew 0000-0002-4911-9956","orcid":"https://orcid.org/0000-0002-4911-9956","contributorId":201512,"corporation":false,"usgs":true,"family":"Struckhoff","given":"Matthew","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":731538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stambaugh, Michael C.","contributorId":202826,"corporation":false,"usgs":false,"family":"Stambaugh","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":13706,"text":"University of Missouri-Columbia","active":true,"usgs":false}],"preferred":false,"id":731539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guyette, Richard P.","contributorId":176595,"corporation":false,"usgs":false,"family":"Guyette","given":"Richard","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":731540,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196133,"text":"70196133 - 2018 - National Gas Hydrate Program Expedition 01 offshore India; gas hydrate systems as revealed by hydrocarbon gas geochemistry","interactions":[],"lastModifiedDate":"2018-05-04T15:12:28","indexId":"70196133","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"National Gas Hydrate Program Expedition 01 offshore India; gas hydrate systems as revealed by hydrocarbon gas geochemistry","docAbstract":"The National Gas Hydrate Program Expedition 01 (NGHP-01) targeted gas hydrate accumulations offshore of the Indian Peninsula and along the Andaman convergent margin. The primary objectives of coring were to understand the geologic and geochemical controls on the accumulation of methane hydrate and their linkages to underlying petroleum systems. Four areas were investigated: 1) the Kerala-Konkan Basin in the eastern Arabian Sea, 2) the Mahanadi and 3) Krishna-Godavari Basins in the western Bay of Bengal, and 4) the Andaman forearc Basin in the Andaman Sea.
Upward flux of methane at three of the four of the sites cored during NGHP-01 is apparent from the presence of seafloor mounds, seismic evidence for upward gas migration, shallow sub-seafloor geochemical evidence of methane oxidation, and near-seafloor gas composition that resembles gas from depth.
The Kerala-Konkan Basin well contained only CO2 with no detectable hydrocarbons suggesting there is no gas hydrate system here. Gas and gas hydrate from the Krishna-Godavari Basin is mainly microbial methane with δ13C values ranging from −58.9 to −78.9‰, with small contributions from microbial ethane (−52.1‰) and CO2. Gas from the Mahanadi Basin was mainly methane with lower concentrations of C2-C5 hydrocarbons (C1/C2 ratios typically >1000) and CO2. Carbon isotopic compositions that ranged from −70.7 to −86.6‰ for methane and −62.9 to −63.7‰ for ethane are consistent with a microbial gas source; however deeper cores contained higher molecular weight hydrocarbon gases suggesting a small contribution from a thermogenic gas source. Gas composition in the Andaman Basin was mainly methane with lower concentrations of ethane to isopentane and CO2, C1/C2 ratios were mainly >1000 although deeper samples were <1000. Carbon isotopic compositions range from −65.2 to −80.7‰ for methane, −53.1 to −55.2‰ for ethane is consistent with mainly microbial gas sources, although one value recorded of −35.4‰ for propane suggests a thermogenic source. Gas hydrate accumulations in the Krishna-Godavari and Mahanadi Basins are the result of a microbially sourced gas hydrate system. The system is enhanced by the migration of microbial gas from surrounding areas through pathways including high-porosity delta sands, shale diapirism, faulting and folding of sediment due to the local processes associated with rapid sediment deposition, sediment overpressure, and the recycling of methane from a rapidly upward moving gas hydrate stability zone. The gas hydrate system in the Andaman Basin is less well constrained due to lack of exploration and occurs in a forearc basin. Each of these hydrate-bearing systems overlies and is likely supported by the presence and possible migration of gas from deeper gas-prone petroleum systems currently generating thermogenic hydrocarbons at much greater depths.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2017.11.011","usgsCitation":"Lorenson, T., and Collett, T.S., 2018, National Gas Hydrate Program Expedition 01 offshore India; gas hydrate systems as revealed by hydrocarbon gas geochemistry: Marine and Petroleum Geology, v. 92, p. 477-492, https://doi.org/10.1016/j.marpetgeo.2017.11.011.","productDescription":"16 p.","startPage":"477","endPage":"492","ipdsId":"IP-077202","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468959,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marpetgeo.2017.11.011","text":"Publisher Index Page"},{"id":353004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","volume":"92","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee711e4b0da30c1bfc0c0","contributors":{"authors":[{"text":"Lorenson, Thomas 0000-0001-7669-2873 tlorenson@usgs.gov","orcid":"https://orcid.org/0000-0001-7669-2873","contributorId":174599,"corporation":false,"usgs":true,"family":"Lorenson","given":"Thomas","email":"tlorenson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":731492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":731493,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70196173,"text":"70196173 - 2018 - Adaptive influence of extrinsic and intrinsic factors on variation of incubation periods among tropical and temperate passerines","interactions":[],"lastModifiedDate":"2018-03-22T09:59:54","indexId":"70196173","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3544,"text":"The Auk","onlineIssn":"1938-4254","printIssn":"0004-8038","active":true,"publicationSubtype":{"id":10}},"title":"Adaptive influence of extrinsic and intrinsic factors on variation of incubation periods among tropical and temperate passerines","docAbstract":"Understanding intrinsic (physiological) and extrinsic (e.g., temperature) causes of variation in embryonic development time (incubation period) is important because they can have different impacts on individual quality. Robert Ricklefs and colleagues have argued that longer incubation periods result primarily from intrinsic physiological programs that increase individual quality and adult survival. They claim that incubation periods are largely invariant and that extrinsic factors like temperature have little impact. We have argued that adult survival may be a cause rather than a consequence of much of the variation in embryonic development time. A reduction in extrinsic sources of annual adult mortality (e.g., migration, predation, nonbreeding-season mortality) favors reduced parental effort during incubation to minimize costs to future reproduction and survival. Reduced parental effort, in turn, manifests as cooler average egg temperatures that yield longer incubation periods. Ricklefs and colleagues mischaracterized our hypothesis and deconstructed their own incorrect version, while also making some incorrect statements. We show that reevaluation of previous evidence provided by this group actually supports a role of egg temperature for the variation in incubation periods. We also summarize other observational and experimental evidence that incubation periods are not invariant and that egg temperature has a strong causal influence on variation within and among species. In fact, egg temperature explains ∼60% of the difference in incubation periods among species. The remaining ∼40% reflects intrinsic physiological programs and other factors, potentially providing intrinsic benefits. Ultimately, annual adult mortality explains substantial variation in parental effort and egg temperature, and the latter strongly explains variation in incubation periods. Both intrinsic programs and extrinsic temperature effects need to be considered in attempts to understand incubation strategies.
","language":"English","publisher":"American Ornithological Society","doi":"10.1642/AUK-17-124.1","usgsCitation":"Martin, T.E., Ton, R., and Oteyza, J.C., 2018, Adaptive influence of extrinsic and intrinsic factors on variation of incubation periods among tropical and temperate passerines: The Auk, v. 135, no. 1, p. 101-113, https://doi.org/10.1642/AUK-17-124.1.","productDescription":"13 p.","startPage":"101","endPage":"113","ipdsId":"IP-088493","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468965,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1642/auk-17-124.1","text":"Publisher Index Page"},{"id":352727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"135","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee711e4b0da30c1bfc0be","contributors":{"authors":[{"text":"Martin, Thomas E. 0000-0002-4028-4867 tmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-4028-4867","contributorId":1208,"corporation":false,"usgs":true,"family":"Martin","given":"Thomas","email":"tmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":731534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ton, Riccardo","contributorId":95334,"corporation":false,"usgs":true,"family":"Ton","given":"Riccardo","affiliations":[],"preferred":false,"id":731547,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oteyza, Juan C.","contributorId":166761,"corporation":false,"usgs":false,"family":"Oteyza","given":"Juan","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":731548,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196265,"text":"70196265 - 2018 - Technical note: False low turbidity readings from optical probes during high suspended-sediment concentrations","interactions":[],"lastModifiedDate":"2018-03-29T10:32:21","indexId":"70196265","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Technical note: False low turbidity readings from optical probes during high suspended-sediment concentrations","docAbstract":"Turbidity, a measure of water clarity, is monitored for a variety of purposes including (1) to help determine whether water is safe to drink, (2) to establish background conditions of lakes and rivers and detect pollution caused by construction projects and stormwater discharge, (3) to study sediment transport in rivers and erosion in catchments, (4) to manage siltation of water reservoirs, and (5) to establish connections with aquatic biological properties, such as primary production and predator–prey interactions. Turbidity is typically measured with an optical probe that detects light scattered from particles in the water. Probes have defined upper limits of the range of turbidity that they can measure. The general assumption is that when turbidity exceeds this upper limit, the values of turbidity will be constant, i.e., the probe is pegged
; however, this assumption is not necessarily valid. In rivers with limited variation in the physical properties of the suspended sediment, at lower suspended-sediment concentrations, an increase in suspended-sediment concentration will cause a linear increase in turbidity. When the suspended-sediment concentration in these rivers is high, turbidity levels can exceed the upper measurement limit of an optical probe and record a constant pegged
value. However, at extremely high suspended-sediment concentrations, optical turbidity probes do not necessarily stay pegged
at a constant value. Data from the Colorado River in Grand Canyon, Arizona, USA, and a laboratory experiment both demonstrate that when turbidity exceeds instrument-pegged conditions, increasing suspended-sediment concentration (and thus increasing turbidity) may cause optical probes to record decreasing false
turbidity values that appear to be within the valid measurement range of the probe. Therefore, under high-turbidity conditions, other surrogate measurements of turbidity (e.g., acoustic-attenuation measurements or suspended-sediment samples) are necessary to correct these low false turbidity measurements and accurately measure turbidity.
Small-eared shrews of the genus Cryptotis (Mammalia: Eulipotyphla: Soricidae) are widespread in the northern Neotropics. Systematic studies of these shrews over the past two decades have revealed previously undocumented morphological and species diversity, resulting in a quadrupling of the number of recognized species. Unfortunately, a small proportion of the species in the genus have been included in molecular phylogenetic studies, and evolutionary relationships within the genus are incompletely known. Traditionally, species have been assigned to four or five morphologically defined ‘species groups’, but tests of the monophyly of some of these groups show weak support and relationships amongst species groups remain somewhat speculative. The largest species group is the C. mexicanus group inhabiting Mexico and northern Central America. We studied sequences from mitochondrial cytochrome-b and 16S genes, as well as nuclear ApoB and BRCA1 genes from 22 species of Cryptotis, including 15 species in the C. mexicanus group. Our combined analysis shows that the C. goldmani subgroup is very weakly supported as monophyletic; however, the C. mexicanus group as a whole is not monophyletic. Our molecular phylogenetic analyses confirm the distinctiveness of two newly described species (C. celaque and C. mccarthyi) from isolated highlands of western Honduras and illustrate their relationship with other species formerly considered part of a widespread C. goodwini.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/14772000.2017.1333539","usgsCitation":"Baird, A.B., McCarthy, T.J., Trujillo, R.G., Kang, Y.Y., Esmaeiliyan, M., Valdez, J., Woodman, N., and Bickham, J.W., 2018, Molecular systematics and biodiversity of the Cryptotis mexicanus group (Eulipotyphla: Soricidae): two new species from Honduras supported: Systematics and Biodiversity, v. 16, no. 2, p. 108-117, https://doi.org/10.1080/14772000.2017.1333539.","productDescription":"10 p.","startPage":"108","endPage":"117","ipdsId":"IP-087329","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":352806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-19","publicationStatus":"PW","scienceBaseUri":"5afee710e4b0da30c1bfc0b4","contributors":{"authors":[{"text":"Baird, Amy B.","contributorId":203555,"corporation":false,"usgs":false,"family":"Baird","given":"Amy","email":"","middleInitial":"B.","affiliations":[{"id":36652,"text":"Department of Natural Sciences, University of Houston – Downtown, 1 Main St., Houston, TX 77002","active":true,"usgs":false}],"preferred":false,"id":731775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarthy, Timothy J.","contributorId":203556,"corporation":false,"usgs":false,"family":"McCarthy","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":36653,"text":"Section of Mammals, Carnegie Museum of Natural History, 5800 Baum Boulevard, Pittsburgh, Pennsylvania 15206-3783","active":true,"usgs":false}],"preferred":false,"id":731776,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Trujillo, Robert G.","contributorId":203557,"corporation":false,"usgs":false,"family":"Trujillo","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":36654,"text":"United States Forest Service, 1720 Peachtree Rd NW, Atlanta, GA 30309","active":true,"usgs":false}],"preferred":false,"id":731777,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kang, Yuan Yuan","contributorId":203558,"corporation":false,"usgs":false,"family":"Kang","given":"Yuan","email":"","middleInitial":"Yuan","affiliations":[{"id":36652,"text":"Department of Natural Sciences, University of Houston – Downtown, 1 Main St., Houston, TX 77002","active":true,"usgs":false}],"preferred":false,"id":731778,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esmaeiliyan, Mehdi","contributorId":203559,"corporation":false,"usgs":false,"family":"Esmaeiliyan","given":"Mehdi","email":"","affiliations":[{"id":36652,"text":"Department of Natural Sciences, University of Houston – Downtown, 1 Main St., Houston, TX 77002","active":true,"usgs":false}],"preferred":false,"id":731779,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Valdez, Joselyn","contributorId":203560,"corporation":false,"usgs":false,"family":"Valdez","given":"Joselyn","email":"","affiliations":[{"id":36652,"text":"Department of Natural Sciences, University of Houston – Downtown, 1 Main St., Houston, TX 77002","active":true,"usgs":false}],"preferred":false,"id":731780,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":731774,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bickham, John W.","contributorId":203561,"corporation":false,"usgs":false,"family":"Bickham","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":36655,"text":"Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station, TX 77843","active":true,"usgs":false}],"preferred":false,"id":731781,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70197461,"text":"70197461 - 2018 - Species‐ and habitat‐specific otolith chemistry patterns inform riverine fisheries management","interactions":[],"lastModifiedDate":"2018-06-06T11:28:19","indexId":"70197461","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Species‐ and habitat‐specific otolith chemistry patterns inform riverine fisheries management","docAbstract":"Geology and hydrology are drivers of water chemistry and thus important considerations for fish otolith chemistry research. However, other factors such as species and habitat identity may have predictive ability, enabling selection of appropriate elemental signatures prior to costly, perhaps unnecessary water/age‐0 fish sampling. The goal of this study was to develop a predictive methodology for using species and habitat identity to design efficient otolith chemistry studies. Duplicate water samples and age‐0 fish were collected from 61 sites in 4 Missouri River reservoirs for walleye Sander vitreus and one impoundment (Lake Sharpe, South Dakota) for other fishes (bluegill Lepomis macrochirus, black crappie Pomoxis nigromaculatus, gizzard shad Dorosoma cepedianum, largemouth bass Micropterus salmoides, smallmouth bass M. dolomieu, white bass Morone chrysops, white crappie P. annularis, and yellow perch Perca flavescens). Water chemistry (barium:calcium [Ba:Ca], strontium:calcium [Sr:Ca]) was temporally stable, spatially variable, and highly correlated with otolith chemistry for all species except yellow perch. Classification accuracies based on bivariate Ba:Ca and Sr:Ca signatures were high (84% across species) yet varied between floodplain and main‐channel habitats in a species‐specific manner. Thus, to maximize the reliability of otolith chemistry, researchers can use species classifications presented herein to inform habitat selection (e.g., study reservoir‐oriented species such as white bass in main‐channel environments) and habitat‐based classifications to inform species selection (e.g., focus floodplain studies on littoral species such as largemouth bass). Overall, species and habitat identity are important considerations for efficient, effective otolith chemistry studies that inform and advance fisheries and aquatic resource management.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3248","usgsCitation":"Radigan, W., Carlson, A.K., Kientz, J., Chipps, S.R., Fincel, M.J., and Graeb, B.D., 2018, Species‐ and habitat‐specific otolith chemistry patterns inform riverine fisheries management: River Research and Applications, v. 34, no. 3, p. 279-287, https://doi.org/10.1002/rra.3248.","productDescription":"9 p.","startPage":"279","endPage":"287","ipdsId":"IP-092404","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":354760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota, South Dakota","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.27,\n 42.49\n ],\n [\n -96.45,\n 42.49\n ],\n [\n -96.45,\n 47.39\n ],\n [\n -103.27,\n 47.39\n ],\n [\n -103.27,\n 42.49\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-30","publicationStatus":"PW","scienceBaseUri":"5b46e5ade4b060350a15d200","contributors":{"authors":[{"text":"Radigan, William","contributorId":205424,"corporation":false,"usgs":false,"family":"Radigan","given":"William","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":737249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Andrew K.","contributorId":172103,"corporation":false,"usgs":false,"family":"Carlson","given":"Andrew","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":737250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kientz, Jeremy","contributorId":205425,"corporation":false,"usgs":false,"family":"Kientz","given":"Jeremy","email":"","affiliations":[{"id":37104,"text":"South Dakota Department of Game, Fish and Parks","active":true,"usgs":false}],"preferred":false,"id":737251,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":737248,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fincel, Mark J.","contributorId":171853,"corporation":false,"usgs":false,"family":"Fincel","given":"Mark","email":"","middleInitial":"J.","affiliations":[{"id":26957,"text":"South Dakota Game, Fish and Parks, Ft. Pierre, SD","active":true,"usgs":false}],"preferred":false,"id":737252,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graeb, Brian D. S.","contributorId":171851,"corporation":false,"usgs":false,"family":"Graeb","given":"Brian","email":"","middleInitial":"D. S.","affiliations":[{"id":26956,"text":"Departement of Natural Resource Management, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":737253,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197450,"text":"70197450 - 2018 - Distinguishing values from science in decision making: Setting harvest quotas for mountain lions in Montana","interactions":[],"lastModifiedDate":"2018-06-05T10:33:23","indexId":"70197450","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Distinguishing values from science in decision making: Setting harvest quotas for mountain lions in Montana","docAbstract":"The relative roles of science and human values can be difficult to distinguish when informal processes are used to make complex and contentious decisions in wildlife management. Structured Decision Making (SDM) offers a formal process for making such decisions, where scientific results and concepts can be disentangled from the values of differing stakeholders. We used SDM to formally integrate science and human values for a citizen working group of ungulate hunting advocates, lion hunting advocates, and outfitters convened to address the contentious allocation of harvest quotas for mountain lions (Puma concolor) in west‐central Montana, USA, during 2014. A science team consisting of mountain lion biologists and population ecologists convened to support the working group. The science team used integrated population models that incorporated 4 estimates of mountain lion density to estimate population trajectories for 5 alternative harvest quotas developed by the working group. Results of the modeling predicted that effects of each harvest quota were consistent across the 4 density estimates; harvest quotas affected predicted population trajectories for 5 years after implementation but differences were not strong. Based on these results, the focus of the working group changed to differences in values among stakeholders that were the true impediment to allocating harvest quotas. By distinguishing roles of science and human values in this process, the working group was able to collaboratively recommend a compromise solution. This solution differed little from the status quo that had been the focus of debate, but the SDM process produced understanding and buy‐in among stakeholders involved, reducing disagreements, misunderstanding, and unproductive arguments founded on informal application of scientific data and concepts. Whereas investments involved in conducting SDM may be unnecessary for many decisions in wildlife management, the investment may be beneficial for complex, contentious, and multiobjective decisions that integrate science and human values.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.861","usgsCitation":"Mitchell, M.S., Cooley, H., Gude, J., Kolbe, J., Nowak, J.J., Proffitt, K.M., Sells, S.N., and Thompson, M., 2018, Distinguishing values from science in decision making: Setting harvest quotas for mountain lions in Montana: Wildlife Society Bulletin, v. 42, no. 1, p. 13-21, https://doi.org/10.1002/wsb.861.","productDescription":"9 p.","startPage":"13","endPage":"21","ipdsId":"IP-089989","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":499990,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/821cf25d1bd94a54a95a168864e646fc","text":"External Repository"},{"id":354717,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.740966796875,\n 45.433153642271385\n ],\n [\n -112.093505859375,\n 45.433153642271385\n ],\n [\n -112.093505859375,\n 47.45037978769006\n ],\n [\n -115.740966796875,\n 47.45037978769006\n ],\n [\n -115.740966796875,\n 45.433153642271385\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","scienceBaseUri":"5b46e5ade4b060350a15d202","contributors":{"authors":[{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":737199,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cooley, Hilary","contributorId":205414,"corporation":false,"usgs":false,"family":"Cooley","given":"Hilary","affiliations":[],"preferred":false,"id":737227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gude, Justin A.","contributorId":95780,"corporation":false,"usgs":true,"family":"Gude","given":"Justin A.","affiliations":[],"preferred":false,"id":737228,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolbe, Jay","contributorId":205415,"corporation":false,"usgs":false,"family":"Kolbe","given":"Jay","email":"","affiliations":[],"preferred":false,"id":737229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nowak, J. Joshua","contributorId":171707,"corporation":false,"usgs":false,"family":"Nowak","given":"J.","email":"","middleInitial":"Joshua","affiliations":[],"preferred":false,"id":737230,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Proffitt, Kelly M.","contributorId":106783,"corporation":false,"usgs":true,"family":"Proffitt","given":"Kelly","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":737231,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sells, Sarah N.","contributorId":171706,"corporation":false,"usgs":false,"family":"Sells","given":"Sarah","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":737232,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thompson, Mike","contributorId":205416,"corporation":false,"usgs":false,"family":"Thompson","given":"Mike","email":"","affiliations":[],"preferred":false,"id":737233,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196334,"text":"70196334 - 2018 - Integrate urban‐scale seismic hazard analyses with the U.S. National Seismic Hazard Model","interactions":[],"lastModifiedDate":"2019-08-30T06:57:40","indexId":"70196334","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Integrate urban‐scale seismic hazard analyses with the U.S. National Seismic Hazard Model","docAbstract":"For more than 20 yrs, damage patterns and instrumental recordings have highlighted the influence of the local 3D geologic structure on earthquake ground motions (e.g.,
We recommend that future U.S. national seismic hazard assessment make use of all available regional information, including that in urban models. In this column, we describe the roles of and differences between the urban and national models, and discuss the obstacles to and benefits of integrating the urban models with the national model. Future progress on this issue will require further coordination and implementation efforts between the USGS and external partners.
The summer meeting of the U.S. Geological Survey (USGS)-NASA Landsat Science Team (LST) was held June 11-13, 2017, at the USGS’s Earth Resources Observation and Science (EROS) Center near Sioux Falls, SD. This was the final meeting of the Second (2012-2017) LST.1 Frank Kelly [EROS—Center Director] welcomed the attendees and expressed his thanks to the LST members for their contributions. He then introduced video-recorded messages from South Dakota’s U.S. senators, John Thune and Mike Rounds, in which they acknowledged the efforts of the team in advancing the societal impacts of the Landsat Program.
","language":"English","publisher":"NASA","usgsCitation":"Crawford, C.J., Loveland, T.R., Wulder, M.A., and Irons, J.R., 2018, 2017 Landsat Science Team Summer Meeting Summary: The Earth Observer, v. 30, no. 1, p. 21-25.","productDescription":"5 p.","startPage":"21","endPage":"25","ipdsId":"IP-092816","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":352880,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":351675,"type":{"id":15,"text":"Index Page"},"url":"https://eospso.nasa.gov/sites/default/files/eo_pdfs/Jan_Feb_2018_color508_0.pdf#page=21"}],"volume":"30","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee712e4b0da30c1bfc0d4","contributors":{"authors":[{"text":"Crawford, Christopher J. 0000-0002-7145-0709 cjcrawford@usgs.gov","orcid":"https://orcid.org/0000-0002-7145-0709","contributorId":202517,"corporation":false,"usgs":true,"family":"Crawford","given":"Christopher","email":"cjcrawford@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":728669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loveland, Thomas R. 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140256,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","middleInitial":"R.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":728670,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wulder, Michael A.","contributorId":189990,"corporation":false,"usgs":false,"family":"Wulder","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":731967,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irons, James R.","contributorId":59284,"corporation":false,"usgs":false,"family":"Irons","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":731968,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196947,"text":"70196947 - 2018 - Monitoring Least Bitterns (Ixobrychis exilis) in Vermont: Detection probability and occupancy modeling","interactions":[],"lastModifiedDate":"2018-05-17T15:21:08","indexId":"70196947","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Monitoring Least Bitterns (Ixobrychis exilis) in Vermont: Detection probability and occupancy modeling","title":"Monitoring Least Bitterns (Ixobrychis exilis) in Vermont: Detection probability and occupancy modeling","docAbstract":"Ixobrychus exillis (Least Bittern) is listed as a species of high concern in the North American Waterbird Conservation Plan and is a US Fish and Wildlife Service migratory bird species of conservation concern in the Northeast. Little is known about the population of Least Bitterns in the Northeast because of their low population density, tendency to nest in dense wetland vegetation, and secretive behavior. Urban and agricultural development is expected to encroach on and degrade suitable wetland habitat; however, we cannot predict the effects on Least Bittern populations without more accurate information on their abundance and distribution. We conducted surveys of wetlands in Vermont to assess the efficacy of a monitoring protocol and to establish baseline Least Bittern abundance and distribution data at a sample of 29 wetland sites. Surveys yielded detections of 31 individuals at 15 of 29 sites across 3 biophysical regions and at 5 sites where occupancy had not been previously reported. Probability of occupancy was positively related to wetland size and number of patches, though the relationships were not strong enough to conclude if these were true determinants of occupancy. Call—response broadcast surveys yielded 30 detections, while passive surveys yielded 13. Call—response broadcasts (P = 0.897) increased the rate of detection by 55% compared to passive surveys (P = 0.577). Our results suggest that call—response broadcast surveys are an effective means of assessing Least Bittern occupancy and may reduce bias in long-term monitoring programs.
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\"}}]}","volume":"25","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee70ee4b0da30c1bfc096","contributors":{"authors":[{"text":"Cherukuri, Aswini","contributorId":205003,"corporation":false,"usgs":false,"family":"Cherukuri","given":"Aswini","email":"","affiliations":[],"preferred":false,"id":735719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Strong, Allan","contributorId":205004,"corporation":false,"usgs":false,"family":"Strong","given":"Allan","email":"","affiliations":[],"preferred":false,"id":735720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":735110,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193856,"text":"70193856 - 2018 - Nest survival modelling using a multi-species approach in forests managed for timber and biofuel feedstock","interactions":[],"lastModifiedDate":"2018-03-29T15:13:48","indexId":"70193856","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Nest survival modelling using a multi-species approach in forests managed for timber and biofuel feedstock","docAbstract":"Switchgrass (Panicum virgatum) intercropping is a novel forest management practice for biomass production intended to generate cellulosic feedstocks within intensively managed loblolly pine‐dominated landscapes. These pine plantations are important for early‐successional bird species, as short rotation times continually maintain early‐successional habitat. We tested the efficacy of using community models compared to individual surrogate species models in understanding influences on nest survival. We analysed nest data to test for differences in habitat use for 14 bird species in plots managed for switchgrass intercropping and controls within loblolly pine (Pinus taeda) plantations in Mississippi, USA.
We adapted hierarchical models using hyper‐parameters to incorporate information from both common and rare species to understand community‐level nest survival. This approach incorporates rare species that are often discarded due to low sample sizes, but can inform community‐level demographic parameter estimates. We illustrate use of this approach in generating both species‐level and community‐wide estimates of daily survival rates for songbird nests. We were able to include rare species with low sample size (minimum n = 5) to inform a hyper‐prior, allowing us to estimate effects of covariates on daily survival at the community level, then compare this with a single‐species approach using surrogate species. Using single‐species models, we were unable to generate estimates below a sample size of 21 nests per species.
Community model species‐level survival and parameter estimates were similar to those generated by five single‐species models, with improved precision in community model parameters.
Covariates of nest placement indicated that switchgrass at the nest site (<4 m) reduced daily nest survival, although intercropping at the forest stand level increased daily nest survival.
Synthesis and applications. Community models represent a viable method for estimating community nest survival rates and effects of covariates while incorporating limited data for rarely detected species. Intercropping switchgrass in loblolly pine plantations slightly increased daily nest survival at the research plot scale (0.1 km2), although at a local scale (50 m2) switchgrass negatively influenced nest survival. A likely explanation is intercropping shifted community composition, favouring species with greater disturbance tolerance.
Large lakes provide a variety of ecological services to surrounding cities and communities. Many of these services are supported by ecological processes that are threatened by the increasing prevalence of cyanobacterial blooms which occur as aquatic ecosystems experience cultural eutrophication. Over the past 10 yr, Lake Erie experienced cyanobacterial blooms of increasing severity and frequency, which have resulted in impaired drinking water for the surrounding communities. Cyanobacterial blooms may impact ecological processes that support other services, but many of these impacts have not been documented. Secondary production (production of primary consumers) is an important process that supports economically important higher trophic levels. Cyanobacterial blooms may influence secondary production because cyanobacteria are a poor‐quality food resource and cyanotoxins may be harmful to consumers. Over 3 yr at 34 sites across the western basin of Lake Erie, we measured three indices of secondary production that focus on the dominant bivalve taxa: (1) growth of a native unionid mussel, (2) the size of young‐of‐year dreissenid mussels, and (3) the mass of colonizing animals on a Hester‐Dendy sampler. Associations between these indices and cyanobacterial data were estimated to assess whether cyanobacteria are associated with variation in secondary production in the western basin of Lake Erie. The results suggest cyanobacterial abundance alone is only weakly associated with secondary production, but that cyanotoxins have a larger effect on secondary production. Given recurring late‐summer cyanobacterial blooms, this impact on secondary production has the potential to undermine Lake Erie's ability to sustain important ecosystem services.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography (ASLO)","doi":"10.1002/lno.10733","usgsCitation":"Larson, J.H., Evans, M.A., Kennedy, R.J., Bailey, S., Loftin, K.A., Laughrey, Z.R., Femmer, R., Schaeffer, J., Richardson, W.B., Wynne, T., Nelson, J., and Duris, J.W., 2018, Associations between cyanobacteria and indices of secondary production in the western basin of Lake Erie: Limnology and Oceanography, v. 63, no. S1, p. S232-S243, https://doi.org/10.1002/lno.10733.","productDescription":"12 p.","startPage":"S232","endPage":"S243","ipdsId":"IP-085475","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468950,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10733","text":"Publisher Index Page"},{"id":437994,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QSRU0E","text":"USGS data release","linkHelpText":"Temperature and invertebrate community composition at nearshore Great Lakes sites, 2013-2016"},{"id":353756,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.51669311523438,\n 41.51063406062076\n ],\n [\n -82.77923583984375,\n 41.51063406062076\n ],\n [\n -82.77923583984375,\n 42.04011410708205\n ],\n [\n -83.51669311523438,\n 42.04011410708205\n ],\n [\n -83.51669311523438,\n 41.51063406062076\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"63","issue":"S1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-23","publicationStatus":"PW","scienceBaseUri":"5afee70fe4b0da30c1bfc0a4","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":4883,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":734119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Robert J. 0000-0003-2135-5022 rkennedy@usgs.gov","orcid":"https://orcid.org/0000-0003-2135-5022","contributorId":3652,"corporation":false,"usgs":true,"family":"Kennedy","given":"Robert","email":"rkennedy@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bailey, Sean 0000-0003-0361-7914 sbailey@usgs.gov","orcid":"https://orcid.org/0000-0003-0361-7914","contributorId":198515,"corporation":false,"usgs":true,"family":"Bailey","given":"Sean","email":"sbailey@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734121,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":734122,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Laughrey, Zachary R. 0000-0002-7630-2078 zlaughrey@usgs.gov","orcid":"https://orcid.org/0000-0002-7630-2078","contributorId":198516,"corporation":false,"usgs":true,"family":"Laughrey","given":"Zachary","email":"zlaughrey@usgs.gov","middleInitial":"R.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":734123,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Femmer, Robin 0000-0003-4896-918X rfemmer@usgs.gov","orcid":"https://orcid.org/0000-0003-4896-918X","contributorId":198517,"corporation":false,"usgs":true,"family":"Femmer","given":"Robin","email":"rfemmer@usgs.gov","affiliations":[],"preferred":true,"id":734124,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schaeffer, Jeff 0000-0003-3430-0872 jschaeffer@usgs.gov","orcid":"https://orcid.org/0000-0003-3430-0872","contributorId":2041,"corporation":false,"usgs":true,"family":"Schaeffer","given":"Jeff","email":"jschaeffer@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science 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C. 0000-0002-7105-0107 jcnelson@usgs.gov","orcid":"https://orcid.org/0000-0002-7105-0107","contributorId":459,"corporation":false,"usgs":true,"family":"Nelson","given":"J. C.","email":"jcnelson@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":734128,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Duris, Joseph W. 0000-0002-8669-8109 jwduris@usgs.gov","orcid":"https://orcid.org/0000-0002-8669-8109","contributorId":172426,"corporation":false,"usgs":true,"family":"Duris","given":"Joseph","email":"jwduris@usgs.gov","middleInitial":"W.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":734129,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70196538,"text":"70196538 - 2018 - Ecological drought: Accounting for the non-human impacts of water shortage in the Upper Missouri Headwaters Basin, Montana, USA","interactions":[],"lastModifiedDate":"2018-04-16T16:42:24","indexId":"70196538","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5507,"text":"Resources","printIssn":"2079-9276","active":true,"publicationSubtype":{"id":10}},"title":"Ecological drought: Accounting for the non-human impacts of water shortage in the Upper Missouri Headwaters Basin, Montana, USA","docAbstract":"Water laws and drought plans are used to prioritize and allocate scarce water resources. Both have historically been human-centric, failing to account for non-human water needs. In this paper, we examine the development of instream flow legislation and the evolution of drought planning to highlight the growing concern for the non-human impacts of water scarcity. Utilizing a new framework for ecological drought, we analyzed five watershed-scale drought plans in southwestern Montana, USA to understand if, and how, the ecological impacts of drought are currently being assessed. We found that while these plans do account for some ecological impacts, it is primarily through the narrow lens of impacts to fish as measured by water temperature and streamflow. The latter is typically based on the same ecological principles used to determine instream flow requirements. We also found that other resource plans in the same watersheds (e.g., Watershed Restoration Plans, Bureau of Land Management (BLM) Watershed Assessments or United States Forest Service (USFS) Forest Plans) identify a broader range of ecological drought risks. Given limited resources and the potential for mutual benefits and synergies, we suggest greater integration between various planning processes could result in a more holistic consideration of water needs and uses across the landscape.
","language":"English","publisher":"MDPI","doi":"10.3390/resources7010014","usgsCitation":"McEvoy, J., Bathke, D.J., Burkardt, N., Cravens, A.E., Haigh, T., Hall, K.R., Hayes, M., Jedd, T., Podebradska, M., and Wickham, E., 2018, Ecological drought: Accounting for the non-human impacts of water shortage in the Upper Missouri Headwaters Basin, Montana, USA: Resources, v. 7, no. 1, p. 1-16, https://doi.org/10.3390/resources7010014.","productDescription":"Article 14; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-092941","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468960,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/resources7010014","text":"Publisher Index Page"},{"id":353468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Upper Missouri Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.05957031249999,\n 44.4808302785626\n ],\n [\n -110.67626953125,\n 44.4808302785626\n ],\n [\n -110.67626953125,\n 48.99463598353405\n ],\n [\n -116.05957031249999,\n 48.99463598353405\n ],\n [\n -116.05957031249999,\n 44.4808302785626\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-20","publicationStatus":"PW","scienceBaseUri":"5afee70fe4b0da30c1bfc0a8","contributors":{"authors":[{"text":"McEvoy, Jamie","contributorId":197223,"corporation":false,"usgs":false,"family":"McEvoy","given":"Jamie","affiliations":[],"preferred":false,"id":733491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bathke, Deborah J.","contributorId":197224,"corporation":false,"usgs":false,"family":"Bathke","given":"Deborah","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":733492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burkardt, Nina 0000-0002-9392-9251 burkardtn@usgs.gov","orcid":"https://orcid.org/0000-0002-9392-9251","contributorId":2781,"corporation":false,"usgs":true,"family":"Burkardt","given":"Nina","email":"burkardtn@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":733499,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cravens, Amanda E. 0000-0002-0271-7967 aecravens@usgs.gov","orcid":"https://orcid.org/0000-0002-0271-7967","contributorId":196752,"corporation":false,"usgs":true,"family":"Cravens","given":"Amanda","email":"aecravens@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":733490,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haigh, Tonya","contributorId":204248,"corporation":false,"usgs":false,"family":"Haigh","given":"Tonya","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":733493,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hall, Kimberly R.","contributorId":197221,"corporation":false,"usgs":false,"family":"Hall","given":"Kimberly","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":733494,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hayes, Michael J.","contributorId":197222,"corporation":false,"usgs":false,"family":"Hayes","given":"Michael J.","affiliations":[{"id":34856,"text":"National Drought Mitigation Center, Unversity of Nebraska","active":true,"usgs":false}],"preferred":false,"id":733495,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jedd, Theresa","contributorId":204249,"corporation":false,"usgs":false,"family":"Jedd","given":"Theresa","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":733496,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Podebradska, Marketa","contributorId":204250,"corporation":false,"usgs":false,"family":"Podebradska","given":"Marketa","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":733497,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wickham, Elliot","contributorId":204251,"corporation":false,"usgs":false,"family":"Wickham","given":"Elliot","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":733498,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70196690,"text":"70196690 - 2018 - Geoelectric hazard assessment: the differences of geoelectric responses during magnetic storms within common physiographic zones","interactions":[],"lastModifiedDate":"2018-04-24T16:59:59","indexId":"70196690","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1430,"text":"Earth, Planets and Space","active":true,"publicationSubtype":{"id":10}},"title":"Geoelectric hazard assessment: the differences of geoelectric responses during magnetic storms within common physiographic zones","docAbstract":"Geomagnetic field data obtained through the INTERMAGNET program are convolved with with magnetotelluric surface impedance from four EarthScope USArray sites to estimate the geoelectric variations throughout the duration of a magnetic storm. A duration of time from June 22, 2016, to June 25, 2016, is considered which encompasses a magnetic storm of moderate size recorded at the Brandon, Manitoba and Fredericksburg, Virginia magnetic observatories over 3 days. Two impedance sites were chosen in each case which represent different responses while being within close geographic proximity and within the same physiographic zone. This study produces estimated time series of the geoelectric field throughout the duration of a magnetic storm, providing an understanding of how the geoelectric field differs across small geographic distances within the same physiographic zone. This study shows that the geoelectric response of two sites within 200 km of one another can differ by up to two orders of magnitude (4484 mV/km at one site and 41 mV/km at another site 125 km away). This study demonstrates that the application of uniform 1-dimensional conductivity models of the subsurface to wide geographic regions is insufficient to predict the geoelectric hazard at a given site. This necessitates that an evaluation of the 3-dimensional conductivity distribution at a given location is necessary to produce a reliable estimation of how the geoelectric field evolves over the course of a magnetic storm.
","language":"English","publisher":"Springer","doi":"10.1186/s40623-018-0807-7","usgsCitation":"Cuttler, S.W., Love, J.J., and Swidinsky, A., 2018, Geoelectric hazard assessment: the differences of geoelectric responses during magnetic storms within common physiographic zones: Earth, Planets and Space, v. 70, Article 35; 9 p., https://doi.org/10.1186/s40623-018-0807-7.","productDescription":"Article 35; 9 p.","ipdsId":"IP-092919","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468963,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40623-018-0807-7","text":"Publisher Index Page"},{"id":353688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"70","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-08","publicationStatus":"PW","scienceBaseUri":"5afee70fe4b0da30c1bfc0a6","contributors":{"authors":[{"text":"Cuttler, Stephen W.","contributorId":204450,"corporation":false,"usgs":false,"family":"Cuttler","given":"Stephen","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":733978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":733979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swidinsky, Andrei","contributorId":146924,"corporation":false,"usgs":false,"family":"Swidinsky","given":"Andrei","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":733980,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}