{"pageNumber":"374","pageRowStart":"9325","pageSize":"25","recordCount":46619,"records":[{"id":70188350,"text":"70188350 - 2017 - Unusual population attributes of invasive red-eared slider turtles (Trachemys scripta elegans) in Japan: do they have a performance advantage?","interactions":[],"lastModifiedDate":"2017-06-07T10:03:22","indexId":"70188350","displayToPublicDate":"2017-06-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":868,"text":"Aquatic Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Unusual population attributes of invasive red-eared slider turtles (Trachemys scripta elegans) in Japan: do they have a performance advantage?","docAbstract":"

The slider turtle (Trachemys scripta Thunberg in Schoepff, 1792) is native to the USA and Mexico. Due to the popularity of their colorful hatchlings as pets, they have been exported worldwide and are now present on all continents, except Antarctica. Slider turtles are well-established in Japan and occupy aquatic habitats in urban and agricultural areas, to the detriment of native turtles with which they compete. We asked the overall question, do slider turtles in Japan have a performance advantage because they are liberated from the numerous competing turtle species in their native range and released from many of their natural predators? Traits compared included various measures of adult body size (mean, maximum), female size at maturity as measured by size of gravid females, clutch size, population density and biomass, sex ratio, and sexual size dimorphism, the latter two a partial reflection of growth and maturity differences between the sexes. We sampled slider turtle populations in three habitats in Japan and compared population attributes with published data for the species from throughout its native range in the USA. Mean male body sizes were at the lower end of values from the USA suggesting that males in Japan may mature at smaller body sizes. The smallest gravid females in Japan mature at smaller body sizes but have mean clutch sizes larger than some populations in the USA. Compared to most populations in the USA, slider turtles achieve higher densities and biomasses in Japanese wetlands, especially the lotic system we sampled. Sex ratios were female-biased, the opposite of what is reported for many populations in protected areas of the USA. Sexual size dimorphism was enhanced relative to native populations with females as the larger sex. The enhanced dimorphism is likely a result of earlier size of maturity in Japanese males and the large size of mature (gravid) Japanese females. Slider turtles appear to have a performance advantage over native turtles in Japan, possibly as a result of being released from competition with numerous sympatric turtle species in their native range, and the absence of many co-evolved predators and parasites in Japan. This slight competitive edge, coupled with the catholic diet and broad tolerance of varying aquatic habitats of slider turtles, is reflected in their dominance over native and naturalized Japanese turtles in altered aquatic habitats.

","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/ai.2017.12.1.10","usgsCitation":"Taniguchi, M., Lovich, J.E., Mine, K., Ueno, S., and Kamezaki, N., 2017, Unusual population attributes of invasive red-eared slider turtles (Trachemys scripta elegans) in Japan: do they have a performance advantage?: Aquatic Invasions, v. 12, no. 1, p. 97-108, https://doi.org/10.3391/ai.2017.12.1.10.","productDescription":"12 p.","startPage":"97","endPage":"108","ipdsId":"IP-064335","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469768,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/ai.2017.12.1.10","text":"Publisher Index Page"},{"id":438306,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71C1V2B","text":"USGS data release","linkHelpText":"Body size estimates for slider turtles in the United States, 1944-2010Data"},{"id":342190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5937bf2ae4b0f6c2d0d9c738","contributors":{"authors":[{"text":"Taniguchi, Mari","contributorId":192680,"corporation":false,"usgs":false,"family":"Taniguchi","given":"Mari","email":"","affiliations":[],"preferred":false,"id":697354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":697353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mine, Kanako","contributorId":192681,"corporation":false,"usgs":false,"family":"Mine","given":"Kanako","email":"","affiliations":[],"preferred":false,"id":697355,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ueno, Shintaro","contributorId":192682,"corporation":false,"usgs":false,"family":"Ueno","given":"Shintaro","email":"","affiliations":[],"preferred":false,"id":697356,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kamezaki, Naoki","contributorId":192683,"corporation":false,"usgs":false,"family":"Kamezaki","given":"Naoki","email":"","affiliations":[],"preferred":false,"id":697357,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188200,"text":"70188200 - 2017 - Intraspecific variability and reaction norms of forest understory plant species traits","interactions":[],"lastModifiedDate":"2017-11-22T16:55:41","indexId":"70188200","displayToPublicDate":"2017-06-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1711,"text":"Functional Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Intraspecific variability and reaction norms of forest understory plant species traits","docAbstract":"
  1. Trait-based models of ecological communities typically assume intraspecific variation in functional traits is not important, though such variation can change species trait rankings along gradients in resources and environmental conditions, and thus influence community structure and function.
  2. We examined the degree of intraspecific relative to interspecific variation, and reaction norms of 11 functional traits for 57 forest understory plant species, including: intrinsic water-use efficiency (iWUE), Δ15N, 5 leaf traits, 2 stem traits and 2 root traits along gradients in light, nitrogen, moisture and understory cover.
  3. Our results indicate that interspecific trait variation exceeded intraspecific variation by at least 50% for most, but not all traits. Intraspecific variation in Δ15N, iWUE, leaf nitrogen content and root traits was high (47-70%) compared with most leaf traits and stem traits (13-38%).
  4. Δ15N varied primarily along gradients in abiotic conditions, while light and understory cover were relatively less important. iWUE was related primarily to light transmission, reflecting increases in photosynthesis relative to stomatal conductance. Leaf traits varied mainly as a function of light availability, with some reaction norms depending on understory cover. Plant height increased with understory cover, while stem specific density was related primarily to light. Resources, environmental conditions and understory cover did not contribute strongly to the observed variation in root traits.
  5. Gradients in resources, environmental conditions and competition all appear to control intraspecific variability in most traits to some extent. However, our results suggest that species cross-over (i.e., trait rank reversals) along the gradients measured here are generally not a concern.
  6. Intraspecific variability in understory plant species traits can be considerable. However, trait data collected under a narrow range of environmental conditions appears sufficient to establish species rankings and scale between community and ecosystem levels using trait-based models. Investigators may therefore focus on obtaining a sufficient sample size within a single set of conditions rather than characterizing trait variation across entire gradients in order to optimize sampling efforts.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2435.12898","usgsCitation":"Burton, J.I., Perakis, S.S., McKenzie, S.C., Lawrence, C.E., and Puettmann, K.J., 2017, Intraspecific variability and reaction norms of forest understory plant species traits: Functional Ecology, v. 31, no. 10, p. 1881-1893, https://doi.org/10.1111/1365-2435.12898.","productDescription":"13 p.","startPage":"1881","endPage":"1893","ipdsId":"IP-080541","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469770,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2435.12898","text":"Publisher Index Page"},{"id":342063,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Oregon Cascades, Oregon Coast Range","volume":"31","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-12","publicationStatus":"PW","scienceBaseUri":"59366da8e4b0f6c2d0d7d61e","contributors":{"authors":[{"text":"Burton, Julia I. 0000-0002-3205-8819","orcid":"https://orcid.org/0000-0002-3205-8819","contributorId":192599,"corporation":false,"usgs":false,"family":"Burton","given":"Julia","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":697019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":696973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKenzie, Sean C.","contributorId":192600,"corporation":false,"usgs":false,"family":"McKenzie","given":"Sean","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":697020,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawrence, Caitlin E.","contributorId":192601,"corporation":false,"usgs":false,"family":"Lawrence","given":"Caitlin","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":697021,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Puettmann, Klaus J.","contributorId":36828,"corporation":false,"usgs":true,"family":"Puettmann","given":"Klaus","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":696977,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188293,"text":"70188293 - 2017 - Spatio-temporal mapping of plate boundary faults in California using geodetic imaging","interactions":[],"lastModifiedDate":"2017-11-13T15:05:50","indexId":"70188293","displayToPublicDate":"2017-06-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1816,"text":"Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"Spatio-temporal mapping of plate boundary faults in California using geodetic imaging","docAbstract":"

The Pacific–North American plate boundary in California is composed of a 400-km-wide network of faults and zones of distributed deformation. Earthquakes, even large ones, can occur along individual or combinations of faults within the larger plate boundary system. While research often focuses on the primary and secondary faults, holistic study of the plate boundary is required to answer several fundamental questions. How do plate boundary motions partition across California faults? How do faults within the plate boundary interact during earthquakes? What fraction of strain accumulation is relieved aseismically and does this provide limits on fault rupture propagation? Geodetic imaging, broadly defined as measurement of crustal deformation and topography of the Earth’s surface, enables assessment of topographic characteristics and the spatio-temporal behavior of the Earth’s crust. We focus here on crustal deformation observed with continuous Global Positioning System (GPS) data and Interferometric Synthetic Aperture Radar (InSAR) from NASA’s airborne UAVSAR platform, and on high-resolution topography acquired from lidar and Structure from Motion (SfM) methods. Combined, these measurements are used to identify active structures, past ruptures, transient motions, and distribution of deformation. The observations inform estimates of the mechanical and geometric properties of faults. We discuss five areas in California as examples of different fault behavior, fault maturity and times within the earthquake cycle: the M6.0 2014 South Napa earthquake rupture, the San Jacinto fault, the creeping and locked Carrizo sections of the San Andreas fault, the Landers rupture in the Eastern California Shear Zone, and the convergence of the Eastern California Shear Zone and San Andreas fault in southern California. These examples indicate that distribution of crustal deformation can be measured using interferometric synthetic aperture radar (InSAR), Global Navigation Satellite System (GNSS), and high-resolution topography and can improve our understanding of tectonic deformation and rupture characteristics within the broad plate boundary zone.

","language":"English","publisher":"Multidisciplinary Digital Publishing Institute","doi":"10.3390/geosciences7010015","usgsCitation":"Donnellan, A., Arrowsmith, R., and DeLong, S.B., 2017, Spatio-temporal mapping of plate boundary faults in California using geodetic imaging: Geosciences, v. 7, no. 1, p. 1-26, https://doi.org/10.3390/geosciences7010015.","productDescription":"Article 15; 26 p.","startPage":"1","endPage":"26","ipdsId":"IP-082746","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469772,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/geosciences7010015","text":"Publisher Index Page"},{"id":342133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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watersheds","docAbstract":"

Hydrologic units provide a convenient but problematic nationwide set of geographic polygons based on subjectively determined subdivisions of land surface areas at several hierarchical levels. The problem is that it is impossible to map watersheds, basins, or catchments of relatively equal size and cover the whole country. The hydrologic unit framework is in fact composed mostly of watersheds and pieces of watersheds. The pieces include units that drain to segments of streams, remnant areas, noncontributing areas, and coastal or frontal units that can include multiple watersheds draining to an ocean or large lake. Hence, half or more of the hydrologic units are not watersheds as the name of the framework “Watershed Boundary Dataset” implies. Nonetheless, hydrologic units and watersheds are commonly treated as synonymous, and this misapplication and misunderstanding can have some serious scientific and management consequences. We discuss some of the strengths and limitations of watersheds and hydrologic units as spatial frameworks. Using examples from the Northwest and Southeast United States, we explain how the misapplication of the hydrologic unit framework has altered the meaning of watersheds and can impair understanding associations between spatial geographic characteristics and surface water conditions.

","language":"English","publisher":"Springer","doi":"10.1007/s00267-017-0854-z","usgsCitation":"Omernik, J.M., Griffith, G.E., Hughes, R.M., Glover, J.B., and Weber, M.H., 2017, How misapplication of the hydrologic unit framework diminishes the meaning of watersheds: Environmental Management, v. 60, no. 1, p. 1-11, https://doi.org/10.1007/s00267-017-0854-z.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-067027","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469773,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6145848","text":"External Repository"},{"id":342118,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-04","publicationStatus":"PW","scienceBaseUri":"59366da7e4b0f6c2d0d7d603","contributors":{"authors":[{"text":"Omernik, James M.","contributorId":169740,"corporation":false,"usgs":false,"family":"Omernik","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":25578,"text":"USGS -Volunteer","active":true,"usgs":false}],"preferred":false,"id":697136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffith, Glenn E. 0000-0001-7966-4720 ggriffith@usgs.gov","orcid":"https://orcid.org/0000-0001-7966-4720","contributorId":4053,"corporation":false,"usgs":true,"family":"Griffith","given":"Glenn","email":"ggriffith@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":697135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hughes, Robert M.","contributorId":113579,"corporation":false,"usgs":true,"family":"Hughes","given":"Robert","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":697137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glover, James B.","contributorId":192631,"corporation":false,"usgs":false,"family":"Glover","given":"James","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":697139,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weber, Marc H.","contributorId":169742,"corporation":false,"usgs":false,"family":"Weber","given":"Marc","email":"","middleInitial":"H.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":697138,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188600,"text":"70188600 - 2017 - Demographic consequences of nest box use for Red-footed Falcons Falco vespertinus in Central Asia","interactions":[],"lastModifiedDate":"2017-11-22T16:54:39","indexId":"70188600","displayToPublicDate":"2017-06-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Demographic consequences of nest box use for Red-footed Falcons Falco vespertinus in Central Asia","title":"Demographic consequences of nest box use for Red-footed Falcons Falco vespertinus in Central Asia","docAbstract":"

Nest box programs are frequently implemented for the conservation of cavity-nesting birds, but their effectiveness is rarely evaluated in comparison to birds not using nest boxes. In the European Palearctic, Red-footed Falcon Falco vespertinus populations are both of high conservation concern and are strongly associated with nest box programs in heavily managed landscapes. We used a 21-year monitoring dataset collected on 753 nesting attempts by Red-footed Falcons in unmanaged natural or semi-natural habitats to provide basic information on this poorly known species; to evaluate long-term demographic trends; and to evaluate response of demographic parameters of Red-footed Falcons to environmental factors including use of nest boxes. We observed significant differences among years in laying date, offspring loss, and numbers of fledglings produced, but not in egg production. Of these four parameters, offspring loss and, to a lesser extent, number of fledglings exhibited directional trends over time. Variation in laying date and in numbers of eggs were not well explained by any one model, but instead by combinations of models, each with informative terms for nest type. Nevertheless, laying in nest boxes occurred 2.10 ± 0.70 days earlier than in natural nests. In contrast, variation in both offspring loss and numbers of fledglings produced were fairly well explained by a single model including terms for nest type, nest location, and an interaction between the two parameters (65% and 81% model weights respectively), with highest offspring loss in nest boxes on forest edges. Because, for other species, earlier laying dates are associated with more fit individuals, this interaction highlighted a possible ecological trap, whereby birds using nest boxes on forest edges lay eggs earlier but suffer greater offspring loss and produce lower numbers of fledglings than do those in other nesting settings. If nest boxes increase offspring loss for Red-footed Falcons in heavily managed landscapes where populations are at greater risk, or for the many other species of rare or endangered birds supported by nest box programs, these processes could have important demographic and conservation consequences.

","language":"English","publisher":"Wiley","doi":"10.1111/ibi.12503","usgsCitation":"Bragin, E.A., Bragin, A.E., and Katzner, T., 2017, Demographic consequences of nest box use for Red-footed Falcons Falco vespertinus in Central Asia: Ibis, v. 159, no. 4, p. 841-853, https://doi.org/10.1111/ibi.12503.","productDescription":"13 p.","startPage":"841","endPage":"853","ipdsId":"IP-081874","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":342604,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Kazakhstan","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[70.96231,42.26615],[70.38896,42.08131],[69.07003,41.38424],[68.63248,40.66868],[68.2599,40.66232],[67.98586,41.13599],[66.71405,41.16844],[66.51065,41.98764],[66.02339,41.99465],[66.09801,42.99766],[64.90082,43.72808],[63.18579,43.65007],[62.0133,43.50448],[61.05832,44.40582],[60.23997,44.78404],[58.68999,45.50001],[58.50313,45.5868],[55.92892,44.99586],[55.96819,41.30864],[55.45525,41.25986],[54.75535,42.04397],[54.07942,42.32411],[52.94429,42.11603],[52.50246,41.78332],[52.44634,42.02715],[52.69211,42.4439],[52.50143,42.7923],[51.34243,43.13297],[50.89129,44.03103],[50.33913,44.28402],[50.30564,44.60984],[51.2785,44.51485],[51.3169,45.246],[52.16739,45.40839],[53.04088,45.25905],[53.22087,46.23465],[53.04274,46.85301],[52.04202,46.80464],[51.19195,47.0487],[50.03408,46.60899],[49.10116,46.39933],[48.59324,46.56103],[48.69473,47.07563],[48.05725,47.74375],[47.31523,47.71585],[46.46645,48.39415],[47.04367,49.15204],[46.7516,49.35601],[47.54948,50.4547],[48.57784,49.87476],[48.70238,50.60513],[50.76665,51.69276],[52.32872,51.71865],[54.53288,51.02624],[55.71694,50.62172],[56.77796,51.04355],[58.36329,51.06365],[59.64228,50.54544],[59.93281,50.84219],[61.33742,50.79907],[61.588,51.27266],[59.96753,51.96042],[60.92727,52.44755],[60.73999,52.71999],[61.69999,52.98],[60.97807,53.66499],[61.43659,54.00626],[65.17853,54.35423],[65.66688,54.60127],[68.1691,54.97039],[69.06817,55.38525],[70.86527,55.16973],[71.18013,54.13329],[72.22415,54.37666],[73.50852,54.03562],[73.42568,53.48981],[74.38485,53.54686],[76.8911,54.49052],[76.52518,54.177],[77.80092,53.40441],[80.03556,50.86475],[80.56845,51.38834],[81.94599,50.8122],[83.383,51.06918],[83.93511,50.88925],[84.41638,50.3114],[85.11556,50.1173],[85.54127,49.69286],[86.82936,49.82667],[87.35997,49.21498],[86.59878,48.54918],[85.76823,48.45575],[85.72048,47.45297],[85.16429,47.00096],[83.18048,47.33003],[82.45893,45.53965],[81.94707,45.31703],[79.96611,44.91752],[80.86621,43.18036],[80.18015,42.92007],[80.25999,42.35],[79.64365,42.49668],[79.14218,42.85609],[77.65839,42.96069],[76.00035,42.98802],[75.63696,42.8779],[74.21287,43.29834],[73.6453,43.09127],[73.48976,42.50089],[71.84464,42.8454],[71.18628,42.70429],[70.96231,42.26615]]]},\"properties\":{\"name\":\"Kazakhstan\"}}]}","volume":"159","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-23","publicationStatus":"PW","scienceBaseUri":"5944ee13e4b062508e3335e9","contributors":{"authors":[{"text":"Bragin, Evgeny A.","contributorId":194894,"corporation":false,"usgs":false,"family":"Bragin","given":"Evgeny","email":"","middleInitial":"A.","affiliations":[{"id":35656,"text":"Science Department, Naurzum National Nature Reserve, Kostanay Oblast, Naurzumski Raijon, Karamendy, Kazakhstan","active":true,"usgs":false}],"preferred":false,"id":698515,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bragin, Alexander E.","contributorId":193027,"corporation":false,"usgs":false,"family":"Bragin","given":"Alexander","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":698516,"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":698514,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187570,"text":"fs20173035 - 2017 - Magnetic monitoring in Saguaro National Park","interactions":[],"lastModifiedDate":"2020-07-13T14:38:50.422625","indexId":"fs20173035","displayToPublicDate":"2017-06-02T18:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3035","title":"Magnetic monitoring in Saguaro National Park","docAbstract":"

On a sandy, arid plain, near the Rincon Moun­tain Visitor Center of Saguaro National Park, tucked in among brittlebush, creosote, and other hardy desert plants, is an unusual type of observatory—a small unmanned station that is used for monitor­ing the Earth’s variable magnetic field. Named for the nearby city of Tucson, Arizona, the observatory is 1 of 14 that the Geomagnetism Program of the U.S. Geological Survey operates at various locations across the United States and Ter­ritories.

Data from USGS magnetic observatories, including the Tucson observatory, as well as observatories operated by institutions in other countries, record a variety of signals related to a wide diversity of physical phenomena in the Earth’s interior and its surrounding outer-space environment. The data are used for geomagnetic mapping and surveying, for fundamental scientific research, and for assessment of magnetic storms, which can be hazardous for the activities and infra­structure of our modern, technologically based society. The U.S. Geological Survey observatory service is an integral part of a U.S. national project for monitoring and assessing space weather hazards.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173035","usgsCitation":"Love, J.J., Finn, C.A., Gamez Valdez, Y.C., Swann, Don, 2017, Magnetic monitoring in Saguaro National Park: U.S. Geological Survey Fact Sheet 2017–3035, 2 p., https://doi.org/10.3133/fs20173035.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-084937","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":342004,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3035/fs20173035.pdf","text":"Report","size":"14.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3035"},{"id":342003,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3035/coverthb3.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Saguaro National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.16567611694336,\n 32.24779674710343\n ],\n [\n -111.16567611694336,\n 32.24924855874583\n ],\n [\n -111.10559463500975,\n 32.24924855874583\n ],\n [\n -111.10559463500975,\n 32.265071800242445\n ],\n [\n -111.11383438110352,\n 32.265071800242445\n ],\n [\n -111.11417770385742,\n 32.27218410189552\n ],\n [\n -111.12258911132812,\n 32.272474388080994\n ],\n [\n -111.12224578857422,\n 32.29380787959086\n ],\n [\n -111.10490798950194,\n 32.29453342030047\n ],\n [\n -111.10559463500975,\n 32.30164341194408\n ],\n [\n -111.11434936523438,\n 32.30178850800702\n ],\n [\n -111.11417770385742,\n 32.30483547166609\n ],\n [\n -111.10198974609374,\n 32.30570601389429\n ],\n [\n -111.10370635986328,\n 32.30889793050953\n ],\n [\n -111.10010147094727,\n 32.30904301495666\n ],\n [\n -111.10027313232422,\n 32.31092909162695\n ],\n [\n -111.09563827514648,\n 32.31179957530851\n ],\n [\n -111.09186172485352,\n 32.313540517578666\n ],\n [\n -111.08945846557616,\n 32.31629694107953\n ],\n [\n -111.08963012695312,\n 32.32326016365093\n ],\n [\n -111.10559463500975,\n 32.32311510197487\n ],\n [\n -111.10559463500975,\n 32.319923686309146\n ],\n [\n -111.10937118530273,\n 32.32006875309753\n ],\n [\n -111.10971450805664,\n 32.323405225094625\n ],\n [\n -111.11434936523438,\n 32.32326016365093\n ],\n [\n -111.11400604248047,\n 32.31615186824962\n ],\n [\n -111.12190246582031,\n 32.31658708604226\n ],\n [\n -111.12258911132812,\n 32.33471930167625\n ],\n [\n -111.126708984375,\n 32.33471930167625\n ],\n [\n -111.12653732299805,\n 32.3377651576181\n ],\n [\n -111.13151550292969,\n 32.33791019582042\n ],\n [\n -111.13134384155273,\n 32.35212281198644\n ],\n [\n -111.1402702331543,\n 32.352557856852634\n ],\n [\n -111.14009857177733,\n 32.35560311232581\n ],\n [\n -111.14919662475586,\n 32.355458102485485\n ],\n [\n -111.14953994750977,\n 32.352267827174344\n ],\n [\n -111.18267059326172,\n 32.352267827174344\n ],\n [\n -111.18267059326172,\n 32.33529947261555\n ],\n [\n -111.16722106933594,\n 32.335444514769286\n ],\n [\n -111.16704940795897,\n 32.306431459362386\n ],\n [\n -111.18387222290038,\n 32.306431459362386\n ],\n [\n -111.18370056152344,\n 32.31368559459092\n ],\n [\n -111.23588562011719,\n 32.31368559459092\n ],\n [\n -111.23588562011719,\n 32.306431459362386\n ],\n [\n -111.21820449829102,\n 32.30599619277848\n ],\n [\n -111.21820449829102,\n 32.29148611029876\n ],\n [\n -111.23554229736328,\n 32.29163122262151\n ],\n [\n -111.23537063598633,\n 32.27755424598\n ],\n [\n -111.24395370483398,\n 32.277699380597454\n ],\n [\n -111.24429702758789,\n 32.27029721905168\n ],\n [\n -111.23537063598633,\n 32.26986177897686\n ],\n [\n -111.23537063598633,\n 32.26260413677006\n ],\n [\n -111.21837615966795,\n 32.26274929530214\n ],\n [\n -111.21820449829102,\n 32.24837747454558\n ],\n [\n -111.16567611694336,\n 32.24779674710343\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS-966
Denver, CO 80225-0046

","tableOfContents":"","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2017-06-02","noUsgsAuthors":false,"publicationDate":"2017-06-02","publicationStatus":"PW","scienceBaseUri":"5932791ee4b0e9bd0eab54de","contributors":{"authors":[{"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":694606,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finn, Carol 0000-0003-3144-1645","orcid":"https://orcid.org/0000-0003-3144-1645","contributorId":13201,"corporation":false,"usgs":true,"family":"Finn","given":"Carol","affiliations":[],"preferred":false,"id":694607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gamez Valdez, Yesenia C.","contributorId":192605,"corporation":false,"usgs":false,"family":"Gamez Valdez","given":"Yesenia","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":694608,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swann, Don","contributorId":191890,"corporation":false,"usgs":false,"family":"Swann","given":"Don","affiliations":[],"preferred":false,"id":694609,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186602,"text":"sir20175025 - 2017 - Evaluation of long-term trends in hydrologic and water-quality conditions, and estimation of water budgets through 2013, Chester County, Pennsylvania","interactions":[],"lastModifiedDate":"2017-07-10T14:14:42","indexId":"sir20175025","displayToPublicDate":"2017-06-02T11:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5025","title":"Evaluation of long-term trends in hydrologic and water-quality conditions, and estimation of water budgets through 2013, Chester County, Pennsylvania","docAbstract":"

An evaluation of trends in hydrologic and water quality conditions and estimation of water budgets through 2013 was done by the U.S. Geological Survey in cooperation with the Chester County Water Resources Authority. Long-term hydrologic, meteorologic, and biologic data collected in Chester County, Pennsylvania, which included streamflow, groundwater levels, surface-water quality, biotic integrity, precipitation, and air temperature were analyzed to determine possible trends or changes in hydrologic conditions. Statistically significant trends were determined by applying the Kendall rank correlation test; the magnitudes of the trends were determined using the Sen slope estimator. Water budgets for eight selected watersheds were updated and a new water budget was developed for the Marsh Creek watershed. An average water budget for Chester County was developed using the eight selected watersheds and the new Marsh Creek water budget.

Annual and monthly mean streamflow, base flow, and runoff were analyzed for trends at 10 streamgages. The periods of record at the 10 streamgages ranged from 1961‒2013 to 1988‒2013. The only statistically significant trend for annual mean streamflow was for West Branch Brandywine Creek near Honey Brook, Pa. (01480300) where annual mean streamflow increased 1.6 cubic feet per second (ft3/s) per decade. The greatest increase in monthly mean streamflow was for Brandywine Creek at Chadds Ford, Pa. (01481000) for December; the increase was 47 ft3/s per decade. No statistically significant trends in annual mean base flow or runoff were determined for the 10 streamgages. The greatest increase in monthly mean base flow was for Brandywine Creek at Chadds Ford, Pa. (01481000) for December; the increase was 26 ft3/s per decade.

The magnitude of peaks greater than a base streamflow was analyzed for trends for 12 streamgages. The period of record at the 12 stream gages ranged from 1912‒2012 to 2004–11. Fifty percent of the streamgages showed a small statistically significant increase in peaks greater than the base streamflow. The greatest increase was for Brandywine Creek at Chadds Ford, Pa. (01481000) during 1962‒2012; the increase was 1.8 ft3/s per decade. There were no statistically significant trends in the number of floods equal to or greater than the 2-year recurrence interval flood flow.

Twenty‒one monitoring wells were evaluated for statistically significant trends in annual mean water level, minimum annual water level, maximum annual water level, and annual range in water-level fluctuations. For four wells, a small statistically significant increase in annual mean water level was determined that ranged from 0.16 to 0.7 feet per decade. There was poor or no correlation between annual mean groundwater levels and annual mean streamflow and base flow. No correlation was determined between annual mean groundwater level and annual precipitation. Despite rapid population growth and land-use change since 1950, there appears to have been little or no detrimental effects on groundwater levels in 21 monitoring wells.

Long-term precipitation and temperature data were available from the West Chester (1893‒2013) and Phoenixville, Pa. (1915‒2013) National Oceanic and Atmospheric Administration (NOAA) weather stations. No statistically significant trends in annual mean precipitation or annual mean temperature were determined for either station. Both weather stations had a significant decrease in the number of days per year with precipitation greater than or equal to 0.1 inch. Annual mean minimum and maximum temperatures from the NOAA Southeastern Piedmont Climate Division increased 0.2 degrees Fahrenheit (F) per decade between 1896 and 2014. The number of days with a maximum temperature equal to or greater than 90 degrees F increased at West Chester and decreased at Phoenixville. No statistically significant trend was determined for annual snowfall amounts.

Data from 1974 to 2013 for three stream water-quality monitors in the Brandywine Creek watershed were evaluated. The monitors are on the West Branch Brandywine Creek at Modena, Pa. (01480617), East Branch Brandywine Creek below Downingtown, Pa. (01480870), and Brandywine Creek at Chadds Ford, Pa. (01481000). Statistically significant upward trends were determined for annual mean specific conductance at all three stations, indicating the total dissolved solids load has been increasing. If the current trend continues, the annual mean specific conductance could almost double from 1974 to 2050. The increase in specific conductance likely is due to increases in chloride concentrations, which have been increasing steadily over time at all three stations. No correlation was found between monthly mean specific conductance and monthly mean streamflow or base flow. Statistically significant upward trends in pH were determined for all three stations. Statistically significant upward trends in stream temperature were determined for East Branch Brandywine Creek below Downingtown, Pa. (01480870) and Brandywine Creek at Chadds Ford, Pa. (01481000). The stream water-quality data indicate substantial increases in the minimum daily dissolved oxygen concentrations in the Brandywine Creek over time.

The Chester County Index of Biotic Integrity (CC-IBI) determined for 1998‒2013 was evaluated for the five biological sampling sites collocated with streamgages. CC-IBI scores are based on a 0‒100 scale with higher scores indicating better stream quality. Statistically significant upward trends in the CC-IBI were determined for West Branch Brandywine Creek at Modena, Pa. (01480617) and East Branch Brandywine Creek below Downingtown, Pa. (01480870). No correlation was found between the CC-IBI and streamflow, precipitation, or stream specific conductance, pH, temperature, or dissolved oxygen concentration.

A Chester County average water budget was developed using the nine estimated watershed water budgets. Average precipitation was 48.4 inches, and average streamflow was 21.4 inches. Average runoff and base flow were 8.3 and 13.1 inches, respectively, and average evapotranspiration and estimation of errors was 27.2 inches.\"

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175025","collaboration":"Prepared in cooperation with the Chester County Water Resources Authority","usgsCitation":"Sloto, R.A., and Reif, A.G., 2017, Evaluation of long-term trends in hydrologic and water-quality conditions, and estimation of water budgets through 2013, Chester County, Pennsylvania (ver.1.1, July 2017): U.S. Geological Survey Scientific Investigations Report 2017–5025, 59 p., https://doi.org/10.3133/sir20175025.","productDescription":"vii, 59 p.","numberOfPages":"71","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064731","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":341981,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5025/sir20175025.pdf","text":"Report","size":"8.49 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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1.0: Originally posted June 2,2017; Version 1.1: July 10, 2017","contact":"

Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070

","tableOfContents":"","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2017-06-02","revisedDate":"2017-07-10","noUsgsAuthors":false,"publicationDate":"2017-06-02","publicationStatus":"PW","scienceBaseUri":"59327920e4b0e9bd0eab54e8","contributors":{"authors":[{"text":"Sloto, Ronald A. rasloto@usgs.gov","contributorId":424,"corporation":false,"usgs":true,"family":"Sloto","given":"Ronald","email":"rasloto@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":689716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reif, Andrew G. 0000-0002-5054-5207 agreif@usgs.gov","orcid":"https://orcid.org/0000-0002-5054-5207","contributorId":2632,"corporation":false,"usgs":true,"family":"Reif","given":"Andrew","email":"agreif@usgs.gov","middleInitial":"G.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":689717,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70188147,"text":"ofr20171061 - 2017 - Incorporating genetic sampling in long-term monitoring and adaptive management in the San Diego County Management Strategic Plan Area, Southern California","interactions":[],"lastModifiedDate":"2017-06-05T08:30:40","indexId":"ofr20171061","displayToPublicDate":"2017-06-02T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1061","title":"Incorporating genetic sampling in long-term monitoring and adaptive management in the San Diego County Management Strategic Plan Area, Southern California","docAbstract":"

Habitat and species conservation plans usually rely on monitoring to assess progress towards conservation goals. Southern California, USA, is a hotspot of biodiversity and home to many federally endangered and threatened species. Here, several regional multi-species conservation plans have been implemented to balance development and conservation goals, including in San Diego County. In the San Diego County Management Strategic Plan Area (MSPA), a monitoring framework for the preserve system has been developed with a focus on species monitoring, vegetation monitoring, threats monitoring and abiotic monitoring. Genetic sampling over time (genetic monitoring) has proven useful in gathering species presence and abundance data and detecting population trends, particularly related to species and threats monitoring objectives. This report reviews genetic concepts and techniques of genetics that relate to monitoring goals and outlines components of a genetic monitoring scheme that could be applied in San Diego or in other monitoring frameworks throughout the Nation.

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Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2017-06-02","noUsgsAuthors":false,"publicationDate":"2017-06-02","publicationStatus":"PW","scienceBaseUri":"59327924e4b0e9bd0eab54fe","contributors":{"authors":[{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":97617,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":696889,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70198379,"text":"70198379 - 2017 - Seasonal and spatial variabilities in northern Gulf of Alaska surface water iron concentrations driven by shelf sediment resuspension, glacial meltwater, a Yakutat eddy, and dust","interactions":[],"lastModifiedDate":"2018-08-02T11:57:27","indexId":"70198379","displayToPublicDate":"2017-06-01T11:57:20","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal and spatial variabilities in northern Gulf of Alaska surface water iron concentrations driven by shelf sediment resuspension, glacial meltwater, a Yakutat eddy, and dust","docAbstract":"

Phytoplankton growth in the Gulf of Alaska (GoA) is limited by iron (Fe), yet Fe sources are poorly constrained. We examine the temporal and spatial distributions of Fe, and its sources in the GoA, based on data from three cruises carried out in 2010 from the Copper River (AK) mouth to beyond the shelf break. April data are the first to describe late winter Fe behavior before surface water nitrate depletion began. Sediment resuspension during winter and spring storms generated high “total dissolvable Fe” (TDFe) concentrations of ~1000 nmol kg−1 along the entire continental shelf, which decreased beyond the shelf break. In July, high TDFe concentrations were similar on the shelf, but more spatially variable, and driven by low‐salinity glacial meltwater. Conversely, dissolved Fe (DFe) concentrations in surface waters were far lower and more seasonally consistent, ranging from ~4 nmol kg−1 in nearshore waters to ~0.6–1.5 nmol kg−1seaward of the shelf break during April and July, despite dramatic depletion of nitrate over that period. The reasonably constant DFe concentrations are likely maintained during the year across the shelf by complexation by strong organic ligands, coupled with ample supply of labile particulate Fe. The April DFe data can be simulated using a simple numerical model that assumes a DFe flux from shelf sediments, horizontal transport by eddy diffusion, and removal by scavenging. Given how global change is altering many processes impacting the Fe cycle, additional studies are needed to examine controls on DFe in the Gulf of Alaska.

","language":"English","publisher":"Ameican Geophysical Union","doi":"10.1002/2016GB005493","usgsCitation":"Crusius, J., Schroth, A.W., Resing, J.A., Cullen, J., and Campbell, R.W., 2017, Seasonal and spatial variabilities in northern Gulf of Alaska surface water iron concentrations driven by shelf sediment resuspension, glacial meltwater, a Yakutat eddy, and dust: Global Biogeochemical Cycles, v. 31, no. 6, p. 942-960, https://doi.org/10.1002/2016GB005493.","productDescription":"19 p.","startPage":"942","endPage":"960","ipdsId":"IP-078971","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":469779,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gb005493","text":"Publisher Index Page"},{"id":438308,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7222S06","text":"USGS data release","linkHelpText":"Gulf of Alaska Shelf and Slope Iron and Nitrate data, Copper River Region, 2010"},{"id":356112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -147.5,\n 58\n ],\n [\n -143,\n 58\n ],\n [\n -143,\n 60.359564131824236\n ],\n [\n -147.5,\n 60.359564131824236\n ],\n [\n -147.5,\n 58\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-03","publicationStatus":"PW","scienceBaseUri":"5b6fc67ce4b0f5d57878eb84","contributors":{"authors":[{"text":"Crusius, John 0000-0003-2554-0831 jcrusius@usgs.gov","orcid":"https://orcid.org/0000-0003-2554-0831","contributorId":2155,"corporation":false,"usgs":true,"family":"Crusius","given":"John","email":"jcrusius@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":741299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schroth, Andrew W.","contributorId":192042,"corporation":false,"usgs":false,"family":"Schroth","given":"Andrew","email":"","middleInitial":"W.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":741300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Resing, Joseph A.","contributorId":206619,"corporation":false,"usgs":false,"family":"Resing","given":"Joseph","email":"","middleInitial":"A.","affiliations":[{"id":37351,"text":"University of Washington; Joint Institute for the Study of the Atmosphere and the Ocean","active":true,"usgs":false}],"preferred":false,"id":741301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cullen, Jay","contributorId":206620,"corporation":false,"usgs":false,"family":"Cullen","given":"Jay","email":"","affiliations":[{"id":37352,"text":"University of Victoria; School of Earth and Ocean Sciences Victoria, B.C.","active":true,"usgs":false}],"preferred":false,"id":741302,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell, Robert W.","contributorId":206621,"corporation":false,"usgs":false,"family":"Campbell","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":37353,"text":"Prince William Sound Science Center, Cordova, AK","active":true,"usgs":false}],"preferred":false,"id":741303,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192964,"text":"70192964 - 2017 - Temporal genetic population structure and interannual variation in migration behavior of Pacific Lamprey Entosphenus tridentatus","interactions":[],"lastModifiedDate":"2017-11-07T12:32:37","indexId":"70192964","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Temporal genetic population structure and interannual variation in migration behavior of Pacific Lamprey Entosphenus tridentatus","title":"Temporal genetic population structure and interannual variation in migration behavior of Pacific Lamprey Entosphenus tridentatus","docAbstract":"

Studies using neutral loci suggest that Pacific lamprey, Entosphenus tridentatus, lack strong spatial genetic population structure. However, it is unknown whether temporal genetic population structure exists. We tested whether adult Pacific lamprey: (1) show temporal genetic population structure; and (2) migrate different distances between years. We non-lethally sampled lamprey for DNA in 2009 and 2010 and used eight microsatellite loci to test for genetic population structure. We used telemetry to record the migration behaviors of these fish. Lamprey were assignable to three moderately differentiated genetic clusters (FST = 0.16–0.24 for all pairwise comparisons): one cluster was composed of individuals from 2009, and the other two contained individuals from 2010. The FST value between years was 0.13 and between genetic clusters within 2010 was 0.20. A total of 372 (72.5%) fish were detected multiple times during their migrations. Most fish (69.9%) remained in the mainstem Willamette River; the remaining 30.1% migrated into tributaries. Eighty-two lamprey exhibited multiple back-and-forth movements among tributaries and the mainstem, which may indicate searching behaviors. All migration distances were significantly greater in 2010, when the amplitude of river discharge was greater. Our data suggest genetic structuring between and within years that may reflect different cohorts.

","language":"English","publisher":"Springer","doi":"10.1007/s10750-017-3096-4","usgsCitation":"Clemens, B.J., Wyss, L.A., McCoun, R., Courter, I., Schwabe, L., Peery, C., Schreck, C.B., Spice, E.K., and Docker, M.F., 2017, Temporal genetic population structure and interannual variation in migration behavior of Pacific Lamprey Entosphenus tridentatus: Hydrobiologia, v. 794, no. 1, p. 223-240, https://doi.org/10.1007/s10750-017-3096-4.","productDescription":"18 p.","startPage":"223","endPage":"240","ipdsId":"IP-085011","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.4918212890625,\n 43.64800079902171\n ],\n [\n -121.78344726562499,\n 43.64800079902171\n ],\n [\n -121.78344726562499,\n 45.706179285330855\n ],\n [\n -123.4918212890625,\n 45.706179285330855\n ],\n [\n -123.4918212890625,\n 43.64800079902171\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"794","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-27","publicationStatus":"PW","scienceBaseUri":"5a07e8dee4b09af898c8cbc5","contributors":{"authors":[{"text":"Clemens, Benjamin J.","contributorId":195098,"corporation":false,"usgs":false,"family":"Clemens","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":720919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wyss, Lance A.","contributorId":195114,"corporation":false,"usgs":false,"family":"Wyss","given":"Lance","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":720920,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCoun, Rebecca","contributorId":200082,"corporation":false,"usgs":false,"family":"McCoun","given":"Rebecca","email":"","affiliations":[],"preferred":false,"id":720921,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Courter, Ian","contributorId":173188,"corporation":false,"usgs":false,"family":"Courter","given":"Ian","affiliations":[{"id":27180,"text":"Mount Hood Environmental","active":true,"usgs":false}],"preferred":false,"id":720922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schwabe, Lawrence","contributorId":200083,"corporation":false,"usgs":false,"family":"Schwabe","given":"Lawrence","email":"","affiliations":[],"preferred":false,"id":720923,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peery, Christopher","contributorId":200084,"corporation":false,"usgs":false,"family":"Peery","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":720924,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schreck, Carl B. 0000-0001-8347-1139 carl.schreck@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-1139","contributorId":878,"corporation":false,"usgs":true,"family":"Schreck","given":"Carl","email":"carl.schreck@usgs.gov","middleInitial":"B.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":717453,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Spice, Erin K.","contributorId":200085,"corporation":false,"usgs":false,"family":"Spice","given":"Erin","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":720925,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Docker, Margaret F.","contributorId":195099,"corporation":false,"usgs":false,"family":"Docker","given":"Margaret","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":720926,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70192064,"text":"70192064 - 2017 - Amphibians, pesticides, and the amphibian chytrid fungus in restored wetlands in agricultural landscapes","interactions":[],"lastModifiedDate":"2017-10-25T11:05:19","indexId":"70192064","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1894,"text":"Herpetological Conservation and Biology","onlineIssn":"2151-0733","printIssn":"1931-7603","active":true,"publicationSubtype":{"id":10}},"title":"Amphibians, pesticides, and the amphibian chytrid fungus in restored wetlands in agricultural landscapes","docAbstract":"Information on interactions between pesticide exposure and disease prevalence in amphibian populations is limited, especially from field data. Exposure to certain herbicides and insecticides has the potential to decrease the immune response in frogs, which can potentially lead to increased abundance of Batrachochytrium dendrobatidis (Bd) zoospores on individuals and in the wetlands. In contrast, exposure to certain fungicides can decrease Bd abundance on frog skin. We examined the relationships between the abundance of Bd on the skin of individual Boreal Chorus Frogs (Pseudacris maculata) and the concentrations of pesticides in the water and in frog tissue at six agriculturally dominated wetlands in Iowa, USA. We collected frogs from each wetland, swabbed them for Bd, and analyzed their tissues for a suite of fungicides, herbicides, and insecticides. We collected surface water from the wetlands and we analyzed it for the same suite of pesticides. We observed no relationship between Bd zoospores on the skin of individual frogs and the concentrations of total pesticides, total herbicides/insecticides and total fungicides in frog tissue. Similarly, we observed no relationship between Bd zoospore abundance in water and the concentration of total pesticides or total herbicides in water. However, we observed a negative relationship between Bd zoospore abundance in water and neonicotinoid concentrations in surface water. Negative results are seldom reported but can be important contributors to a more complete understanding of the complex and potentially synergistic relationships between disease and pesticides. Data from field studies on these relationships are particularly scarce. As our laboratory understanding of these relationships expands, the need for field based, or applied, studies grow.","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"Reeves, R.A., Pierce, C., Vandever, M.W., Muths, E.L., and Smalling, K.L., 2017, Amphibians, pesticides, and the amphibian chytrid fungus in restored wetlands in agricultural landscapes: Herpetological Conservation and Biology, v. 12, p. 68-77.","productDescription":"10 p.","startPage":"68","endPage":"77","ipdsId":"IP-078902","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":347332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347331,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/contents_vol12_issue1.html"}],"country":"United States","state":"Iowa","volume":"12","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f1a2a5e4b0220bbd9d9f53","contributors":{"authors":[{"text":"Reeves, Rebecca A.","contributorId":150493,"corporation":false,"usgs":false,"family":"Reeves","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":714051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pierce, Clay 0000-0001-5088-5431 cpierce@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-5431","contributorId":150492,"corporation":false,"usgs":true,"family":"Pierce","given":"Clay","email":"cpierce@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":714052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vandever, Mark W. 0000-0003-0247-2629 vandeverm@usgs.gov","orcid":"https://orcid.org/0000-0003-0247-2629","contributorId":197674,"corporation":false,"usgs":true,"family":"Vandever","given":"Mark","email":"vandeverm@usgs.gov","middleInitial":"W.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":714053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":714054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smalling, Kelly L. 0000-0002-1214-4920 ksmall@usgs.gov","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":190789,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","email":"ksmall@usgs.gov","middleInitial":"L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714050,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70191603,"text":"70191603 - 2017 - Songbirds are resilient to hurricane disturbed habitats during spring migration","interactions":[],"lastModifiedDate":"2022-11-02T13:51:52.509997","indexId":"70191603","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Songbirds are resilient to hurricane disturbed habitats during spring migration","docAbstract":"

The Gulf of Mexico is a conspicuous feature of the Neotropical–Nearctic bird migration system. Traveling long distances across ecological barriers comes with considerable risks, and mortality associated with intercontinental migration may be substantial, including that caused by storms or other adverse weather events. However, little, if anything, is known about how migratory birds respond to disturbance-induced changes in stopover habitat. Isolated, forested cheniere habitat along the northern coast of the Gulf of Mexico often concentrate migrants, during weather conditions unfavorable for northward movement or when birds are energetically stressed. We expected hurricane induced degradation of this habitat to negatively affect the abundance, propensity to stopover, and fueling trends of songbirds that stopover in coastal habitat. We used spring banding data collected in coastal Louisiana to compare migrant abundance and fueling trends before (1993–1996 and 1998–2005) and after hurricanes Rita (2006) and Ike (2009). We also characterized changes in vegetative structure before (1995) and after (2010) the hurricanes. The hurricanes caused dramatic changes to the vegetative structure, which likely decreased resources. Surprisingly, abundance, propensity to stopover, and fueling trends of most migrant species were not influenced by hurricane disturbance. Our results suggest that: 1) the function of chenieres as a refuge for migrants after completing a trans-Gulf flight may not have changed despite significant changes to habitat and decreases in resource availability, and 2) that most migrants may be able to cope with habitat disturbance during stopover. The fact that migrants use disturbed habitat points to their conservation value along the northern coast of the Gulf of Mexico.

","language":"English","publisher":"Wiley","doi":"10.1111/jav.01215","usgsCitation":"Lain, E., Zenzal, T.J., Moore, F.R., Barrow, W., and Diehl, R.H., 2017, Songbirds are resilient to hurricane disturbed habitats during spring migration: Journal of Avian Biology, v. 48, no. 6, p. 815-826, https://doi.org/10.1111/jav.01215.","productDescription":"12 p.","startPage":"815","endPage":"826","ipdsId":"IP-079284","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":347255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.65792584983939,\n 29.761961814735386\n ],\n [\n -93.65792584983939,\n 29.748602525985405\n ],\n [\n -93.59138240270923,\n 29.748602525985405\n ],\n [\n -93.59138240270923,\n 29.761961814735386\n ],\n [\n -93.65792584983939,\n 29.761961814735386\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"48","issue":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-15","publicationStatus":"PW","scienceBaseUri":"59f05122e4b0220bbd9a1d98","contributors":{"authors":[{"text":"Lain, Emily","contributorId":197195,"corporation":false,"usgs":false,"family":"Lain","given":"Emily","affiliations":[],"preferred":false,"id":712845,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zenzal, Theodore J. Jr. 0000-0001-7342-1373","orcid":"https://orcid.org/0000-0001-7342-1373","contributorId":140179,"corporation":false,"usgs":false,"family":"Zenzal","given":"Theodore","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[{"id":13403,"text":"University of Southern Mississippi, Department of Biological Sciences, Hattiesburg, Mississippi, USA","active":true,"usgs":false}],"preferred":false,"id":712846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Frank R.","contributorId":54582,"corporation":false,"usgs":false,"family":"Moore","given":"Frank","email":"","middleInitial":"R.","affiliations":[{"id":12981,"text":"Department of Biological Sciences, University of Southern Mississippi","active":true,"usgs":false}],"preferred":false,"id":712847,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barrow, Wylie C. Jr. 0000-0003-4671-2823 barroww@usgs.gov","orcid":"https://orcid.org/0000-0003-4671-2823","contributorId":168953,"corporation":false,"usgs":true,"family":"Barrow","given":"Wylie C.","suffix":"Jr.","email":"barroww@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":712843,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diehl, Robert H. 0000-0001-9141-1734 rhdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9141-1734","contributorId":3396,"corporation":false,"usgs":true,"family":"Diehl","given":"Robert","email":"rhdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":712844,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70190739,"text":"70190739 - 2017 - Erosion characteristics and horizontal variability for small erosion depths in the Sacramento-San Joaquin River Delta, California, USA","interactions":[],"lastModifiedDate":"2017-09-13T15:42:25","indexId":"70190739","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2923,"text":"Ocean Dynamics","active":true,"publicationSubtype":{"id":10}},"title":"Erosion characteristics and horizontal variability for small erosion depths in the Sacramento-San Joaquin River Delta, California, USA","docAbstract":"

Erodibility of cohesive sediment in the Sacramento-San Joaquin River Delta (Delta) was investigated with an erosion microcosm. Erosion depths in the Delta and in the microcosm were estimated to be about one floc diameter over a range of shear stresses and times comparable to half of a typical tidal cycle. Using the conventional assumption of horizontally homogeneous bed sediment, data from 27 of 34 microcosm experiments indicate that the erosion rate coefficient increased as eroded mass increased, contrary to theory. We believe that small erosion depths, erosion rate coefficient deviation from theory, and visual observation of horizontally varying biota and texture at the sediment surface indicate that erosion cannot solely be a function of depth but must also vary horizontally. We test this hypothesis by developing a simple numerical model that includes horizontal heterogeneity, use it to develop an artificial time series of suspended-sediment concentration (SSC) in an erosion microcosm, then analyze that time series assuming horizontal homogeneity. A shear vane was used to estimate that the horizontal standard deviation of critical shear stress was about 30% of the mean value at a site in the Delta. The numerical model of the erosion microcosm included a normal distribution of initial critical shear stress, a linear increase in critical shear stress with eroded mass, an exponential decrease of erosion rate coefficient with eroded mass, and a stepped increase in applied shear stress. The maximum SSC for each step increased gradually, thus confounding identification of a single well-defined critical shear stress as encountered with the empirical data. Analysis of the artificial SSC time series with the assumption of a homogeneous bed reproduced the original profile of critical shear stress, but the erosion rate coefficient increased with eroded mass, similar to the empirical data. Thus, the numerical experiment confirms the small-depth erosion hypothesis. A linear model of critical shear stress and eroded mass is proposed to simulate small-depth erosion, assuming that the applied and critical shear stresses quickly reach equilibrium.

","language":"English","publisher":"Springer","doi":"10.1007/s10236-017-1047-2","usgsCitation":"Schoellhamer, D., Manning, A.J., and Work, P.A., 2017, Erosion characteristics and horizontal variability for small erosion depths in the Sacramento-San Joaquin River Delta, California, USA: Ocean Dynamics, v. 67, no. 6, p. 799-811, https://doi.org/10.1007/s10236-017-1047-2.","productDescription":"13 p.","startPage":"799","endPage":"811","ipdsId":"IP-053622","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":461533,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10236-017-1047-2","text":"Publisher Index Page"},{"id":345708,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.08007812499999,\n 37.79676317682161\n ],\n [\n -121.27670288085938,\n 37.79676317682161\n ],\n [\n -121.27670288085938,\n 38.36211833953394\n ],\n [\n -122.08007812499999,\n 38.36211833953394\n ],\n [\n -122.08007812499999,\n 37.79676317682161\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"67","issue":"6","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-24","publicationStatus":"PW","scienceBaseUri":"59ba43b9e4b091459a5629ba","contributors":{"authors":[{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manning, Andrew J.","contributorId":175079,"corporation":false,"usgs":false,"family":"Manning","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":710290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Work, Paul A. 0000-0002-2815-8040 pwork@usgs.gov","orcid":"https://orcid.org/0000-0002-2815-8040","contributorId":168561,"corporation":false,"usgs":true,"family":"Work","given":"Paul","email":"pwork@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710291,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189872,"text":"70189872 - 2017 - Aerodynamic roughness length estimation with lidar and imaging spectroscopy in a shrub-dominated dryland","interactions":[],"lastModifiedDate":"2017-11-22T16:53:38","indexId":"70189872","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3052,"text":"Photogrammetric Engineering and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Aerodynamic roughness length estimation with lidar and imaging spectroscopy in a shrub-dominated dryland","docAbstract":"

The aerodynamic roughness length (Z0 m) serves an important role in the flux exchange between the land surface and atmosphere. In this study, airborne lidar (ALS), terrestrial lidar (TLS), and imaging spectroscopy data were integrated to develop and test two approaches to estimate Z0 m over a shrub dominated dryland study area in south-central Idaho, USA. Sensitivity of the two parameterization methods to estimate Z0 m was analyzed. The comparison of eddy covariance-derived Z0 m and remote sensing-derived Z0 m showed that the accuracy of the estimated Z0 m heavily depends on the estimation model and the representation of shrub (e.g., Artemisia tridentata subsp. wyomingensis) height in the models. The geometrical method (RA1994) led to 9 percent (~0.5 cm) and 25% (~1.1 cm) errors at site 1 and site 2, respectively, which performed better than the height variability-based method (MR1994) with bias error of 20 percent and 48 percent at site 1 and site 2, respectively. The RA1994 model resulted in a larger range of Z0 m than the MR1994 method. We also found that the mean, median and 75th percentiles of heights (H75) from ALS provides the best Z0 m estimates in the MR1994 model, while the mean, median, and MLD (Median Absolute Deviation from Median Height), as well as AAD (Mean Absolute Deviation from Mean Height) heights from ALS provides the best Z0 m estimates in the RA1994 model. In addition, the fractional cover of shrub and grass, distinguished with ALS and imaging spectroscopy data, provided the opportunity to estimate the frontal area index at the pixel-level to assess the influence of grass and shrub on Z0m estimates in the RA1994 method. Results indicate that grass had little effect on Z0 m in the RA1994 method. The Z0 m estimations were tightly coupled with vegetation height and its local variance for the shrubs. Overall, the results demonstrate that the use of height and fractional cover from remote sensing data are promising for estimating Z0 m, and thus refining land surface models at regional scales in semiarid shrublands.

","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","doi":"10.14358/PERS.83.6.415","usgsCitation":"Li, A., Zhao, W., Mitchell, J., Glenn, N.F., Germino, M., Sankey, J.B., and Allen, R.M., 2017, Aerodynamic roughness length estimation with lidar and imaging spectroscopy in a shrub-dominated dryland: Photogrammetric Engineering and Remote Sensing, v. 83, no. 6, p. 415-427, https://doi.org/10.14358/PERS.83.6.415.","productDescription":"13 p.","startPage":"415","endPage":"427","ipdsId":"IP-080636","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":488694,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.83.6.415","text":"Publisher Index Page"},{"id":344452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.90576171874999,\n 42.09822241118974\n ],\n [\n -112.1044921875,\n 42.09822241118974\n ],\n [\n -112.1044921875,\n 44.315987905196906\n ],\n [\n -115.90576171874999,\n 44.315987905196906\n ],\n [\n -115.90576171874999,\n 42.09822241118974\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"83","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59804199e4b0a38ca2789336","contributors":{"authors":[{"text":"Li, Aihua","contributorId":169445,"corporation":false,"usgs":false,"family":"Li","given":"Aihua","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":706603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhao, Wenguang","contributorId":195243,"corporation":false,"usgs":false,"family":"Zhao","given":"Wenguang","email":"","affiliations":[],"preferred":false,"id":706607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mitchell, Jessica J","contributorId":195242,"corporation":false,"usgs":false,"family":"Mitchell","given":"Jessica J","affiliations":[],"preferred":false,"id":706605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glenn, Nancy F.","contributorId":195241,"corporation":false,"usgs":false,"family":"Glenn","given":"Nancy","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":706604,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Germino, Matthew J. 0000-0001-6326-7579 mgermino@usgs.gov","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":152582,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","email":"mgermino@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":706602,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":706606,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Allen, Richard M.","contributorId":195244,"corporation":false,"usgs":false,"family":"Allen","given":"Richard","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":706608,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70192187,"text":"70192187 - 2017 - Analyzing cloud base at local and regional scales to understand tropical montane cloud forest vulnerability to climate change","interactions":[],"lastModifiedDate":"2017-10-23T13:41:14","indexId":"70192187","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":922,"text":"Atmospheric Chemistry and Physics","active":true,"publicationSubtype":{"id":10}},"title":"Analyzing cloud base at local and regional scales to understand tropical montane cloud forest vulnerability to climate change","docAbstract":"

The degree to which cloud immersion provides water in addition to rainfall, suppresses transpiration, and sustains tropical montane cloud forests (TMCFs) during rainless periods is not well understood. Climate and land use changes represent a threat to these forests if cloud base altitude rises as a result of regional warming or deforestation. To establish a baseline for quantifying future changes in cloud base, we installed a ceilometer at 100 m altitude in the forest upwind of the TMCF that occupies an altitude range from ∼ 600 m to the peaks at 1100 m in the Luquillo Mountains of eastern Puerto Rico. Airport Automated Surface Observing System (ASOS) ceilometer data, radiosonde data, and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite data were obtained to investigate seasonal cloud base dynamics, altitude of the trade-wind inversion (TWI), and typical cloud thickness for the surrounding Caribbean region. Cloud base is rarely quantified near mountains, so these results represent a first look at seasonal and diurnal cloud base dynamics for the TMCF. From May 2013 to August 2016, cloud base was lowest during the midsummer dry season, and cloud bases were lower than the mountaintops as often in the winter dry season as in the wet seasons. The lowest cloud bases most frequently occurred at higher elevation than 600 m, from 740 to 964 m. The Luquillo forest low cloud base altitudes were higher than six other sites in the Caribbean by ∼ 200–600 m, highlighting the importance of site selection to measure topographic influence on cloud height. Proximity to the oceanic cloud system where shallow cumulus clouds are seasonally invariant in altitude and cover, along with local trade-wind orographic lifting and cloud formation, may explain the dry season low clouds. The results indicate that climate change threats to low-elevation TMCFs are not limited to the dry season; changes in synoptic-scale weather patterns that increase frequency of drought periods during the wet seasons (periods of higher cloud base) may also impact ecosystem health.

","language":"English","publisher":"European Geophysical Union","doi":"10.5194/acp-17-7245-2017","usgsCitation":"Van Beusekom, A.E., Gonzalez, G., and Scholl, M.A., 2017, Analyzing cloud base at local and regional scales to understand tropical montane cloud forest vulnerability to climate change: Atmospheric Chemistry and Physics, v. 17, no. 11, p. 7245-7259, https://doi.org/10.5194/acp-17-7245-2017.","productDescription":"15 p.","startPage":"7245","endPage":"7259","ipdsId":"IP-084476","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469802,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/acp-17-7245-2017","text":"Publisher Index Page"},{"id":347125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Luquillo Mountains, Puerto Rico","volume":"17","issue":"11","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-16","publicationStatus":"PW","scienceBaseUri":"59eeffa8e4b0220bbd988f9c","contributors":{"authors":[{"text":"Van Beusekom, Ashley E.","contributorId":197950,"corporation":false,"usgs":false,"family":"Van Beusekom","given":"Ashley","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":714640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gonzalez, Grizelle","contributorId":191117,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Grizelle","email":"","affiliations":[],"preferred":false,"id":714641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scholl, Martha A. 0000-0001-6994-4614 mascholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6994-4614","contributorId":1920,"corporation":false,"usgs":true,"family":"Scholl","given":"Martha","email":"mascholl@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":714639,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192992,"text":"70192992 - 2017 - A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011","interactions":[],"lastModifiedDate":"2018-03-08T13:03:59","indexId":"70192992","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011","docAbstract":"

Monitoring and mapping land cover changes are important ways to support evaluation of the status and transition of ecosystems. The Alaska National Land Cover Database (NLCD) 2001 was the first 30-m resolution baseline land cover product of the entire state derived from circa 2001 Landsat imagery and geospatial ancillary data. We developed a comprehensive approach named AKUP11 to update Alaska NLCD from 2001 to 2011 and provide a 10-year cyclical update of the state's land cover and land cover changes. Our method is designed to characterize the main land cover changes associated with different drivers, including the conversion of forests to shrub and grassland primarily as a result of wildland fire and forest harvest, the vegetation successional processes after disturbance, and changes of surface water extent and glacier ice/snow associated with weather and climate changes. For natural vegetated areas, a component named AKUP11-VEG was developed for updating the land cover that involves four major steps: 1) identify the disturbed and successional areas using Landsat images and ancillary datasets; 2) update the land cover status for these areas using a SKILL model (System of Knowledge-based Integrated-trajectory Land cover Labeling); 3) perform decision tree classification; and 4) develop a final land cover and land cover change product through the postprocessing modeling. For water and ice/snow areas, another component named AKUP11-WIS was developed for initial land cover change detection, removal of the terrain shadow effects, and exclusion of ephemeral snow changes using a 3-year MODIS snow extent dataset from 2010 to 2012. The overall approach was tested in three pilot study areas in Alaska, with each area consisting of four Landsat image footprints. The results from the pilot study show that the overall accuracy in detecting change and no-change is 90% and the overall accuracy of the updated land cover label for 2011 is 86%. The method provided a robust, consistent, and efficient means for capturing major disturbance events and updating land cover for Alaska. The method has subsequently been applied to generate the land cover and land cover change products for the entire state of Alaska.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2017.04.021","usgsCitation":"Jin, S., Yang, L., Zhu, Z., and Homer, C.G., 2017, A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011: Remote Sensing of Environment, v. 195, p. 44-55, https://doi.org/10.1016/j.rse.2017.04.021.","productDescription":"12 p.","startPage":"44","endPage":"55","ipdsId":"IP-082390","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":347728,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"195","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f83a36e4b063d5d30980dc","contributors":{"authors":[{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Limin 0000-0002-2843-6944 lyang@usgs.gov","orcid":"https://orcid.org/0000-0002-2843-6944","contributorId":4305,"corporation":false,"usgs":true,"family":"Yang","given":"Limin","email":"lyang@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhu, Zhe 0000-0001-8283-6407 zhezhu@usgs.gov","orcid":"https://orcid.org/0000-0001-8283-6407","contributorId":168792,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhe","email":"zhezhu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717550,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717549,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188126,"text":"sir20175040 - 2017 - Water-level and recoverable water in storage changes, High Plains aquifer, predevelopment to 2015 and 2013–15","interactions":[],"lastModifiedDate":"2017-06-01T16:33:02","indexId":"sir20175040","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5040","title":"Water-level and recoverable water in storage changes, High Plains aquifer, predevelopment to 2015 and 2013–15","docAbstract":"

The High Plains aquifer underlies 111.8 million acres (about 175,000 square miles) in parts of eight States—Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. Water-level declines began in parts of the High Plains aquifer soon after the beginning of substantial irrigation with groundwater in the aquifer area (about 1950). This report presents water-level changes and change in recoverable water in storage in the High Plains aquifer from predevelopment (about 1950) to 2015 and from 2013 to 2015.

The methods to calculate area-weighted, average water-level changes; change in recoverable water in storage; and total recoverable water in storage used geospatial data layers organized as rasters with a cell size of 500 meters by 500 meters, which is an area of about 62 acres. Raster datasets of water-level changes are provided for other uses.

Water-level changes from predevelopment to 2015, by well, ranged from a rise of 84 feet to a decline of 234 feet. Water-level changes from 2013 to 2015, by well, ranged from a rise of 24 feet to a decline of 33 feet. The area-weighted, average water-level changes in the aquifer were an overall decline of 15.8 feet from predevelopment to 2015 and a decline of 0.6 feet from 2013 to 2015. Total recoverable water in storage in the aquifer in 2015 was about 2.91 billion acre-feet, which was a decline of about 273.2 million acre-feet since predevelopment and a decline of 10.7 million acre-feet from 2013 to 2015.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175040","collaboration":"Groundwater and Streamflow Information Program","usgsCitation":"McGuire, V.L., 2017, Water-level and recoverable water in storage changes, High Plains aquifer, predevelopment to 2015 and 2013–15: U.S. Geological Survey Scientific Investigations Report 2017–5040, 14 p., https://doi.org/10.3133/sir20175040.","productDescription":"Report: vi, 14 p.; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079654","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":341985,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7SB43WM","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data used to map water-level changes in the High Plains aquifer, predevelopment (about 1950) to 2015 and 2013 to 2015"},{"id":341997,"rank":4,"type":{"id":18,"text":"Project Site"},"url":"https://www.usgs.gov/science/mission-areas/water/groundwater-and-streamflow-information?qt-programs_l2_landing_page=0#qt-programs_l2_landing_page","text":"Groundwater and Streamflow Information Program"},{"id":341983,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5040/coverthb.jpg"},{"id":341984,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5040/sir20175040.pdf","text":"Report","size":"2.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5040"}],"country":"United States","state":"Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, Wyoming","otherGeospatial":"High Plains Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106,\n 32\n ],\n [\n -96,\n 32\n ],\n [\n -96,\n 44\n ],\n [\n -106,\n 44\n ],\n [\n -106,\n 32\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2017-06-01","noUsgsAuthors":false,"publicationDate":"2017-06-01","publicationStatus":"PW","scienceBaseUri":"593127afe4b0e9bd0ea9ef0a","contributors":{"authors":[{"text":"McGuire, Virginia L. 0000-0002-3962-4158 vlmcguir@usgs.gov","orcid":"https://orcid.org/0000-0002-3962-4158","contributorId":404,"corporation":false,"usgs":true,"family":"McGuire","given":"Virginia","email":"vlmcguir@usgs.gov","middleInitial":"L.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":696845,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70188879,"text":"70188879 - 2017 - Assessing changes in the physico-chemical properties and fluoride adsorption capacity of activated alumina under varied conditions","interactions":[],"lastModifiedDate":"2017-06-27T09:49:15","indexId":"70188879","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Assessing changes in the physico-chemical properties and fluoride adsorption capacity of activated alumina under varied conditions","docAbstract":"

Adsorption using activated alumina is a simple method for removing fluoride from drinking water, but to be cost effective the adsorption capacity must be high and effective long-term. The intent of this study was to assess changes in its adsorption capacity under varied conditions. This was determined by evaluating the physico-chemical properties, surface charge, and fluoride (F−) adsorption capacity and rate of activated alumina under conditions such as hydration period, particle size, and slow vs. fast titrations. X-ray diffraction and scanning electron microscopy analyses show that the mineralogy of activated alumina transformed to boehmite, then bayerite with hydration period and a corresponding reduction in adsorption capacity was expected; while surface area analyses show no notable changes with hydration period or particle size. The pH dependent surface charge was three times higher using slow potentiometric titrations as compared to fast titrations (due largely to diffusion into pore space), with the surface acidity generally unaffected by hydration period. Results from batch adsorption experiments similarly show no change in fluoride adsorption capacity with hydration period. There was also no notable difference in fluoride adsorption capacity between the particle size ranges of 0.5–1.0 mm and 0.125–0.250 mm, or with hydration period. However, adsorption rate increased dramatically with the finer particle sizes: at an initial F− concentration of 0.53 mmol L−1 (10 mg L−1), 90% was adsorbed in the 0.125–0.250 mm range after 1 h, while the 0.5–1.0 mm range required 24 h to achieve 90% adsorption. Also, the pseudo-second-order adsorption rate constants for the finer vs. larger particle sizes were 3.7 and 0.5 g per mmol F− per min respectively (24 h); and the initial intraparticle diffusion rate of the former was 2.6 times faster than the latter. The results show that adsorption capacity of activated alumina remains consistent and high under the conditions evaluated in this study, but in order to increase adsorption rate, a relatively fine particle size is recommended.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2016.11.011","usgsCitation":"Craig, L., Stillings, L.L., and Decker, D.L., 2017, Assessing changes in the physico-chemical properties and fluoride adsorption capacity of activated alumina under varied conditions: Applied Geochemistry, v. 76, p. 112-123, https://doi.org/10.1016/j.apgeochem.2016.11.011.","productDescription":"12 p.","startPage":"112","endPage":"123","ipdsId":"IP-066799","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":342936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59536ea7e4b062508e3c7a6b","contributors":{"authors":[{"text":"Craig, Laura","contributorId":173675,"corporation":false,"usgs":false,"family":"Craig","given":"Laura","affiliations":[{"id":27270,"text":"American Rivers","active":true,"usgs":false}],"preferred":false,"id":700796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stillings, Lisa L. 0000-0002-9011-8891 stilling@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-8891","contributorId":193548,"corporation":false,"usgs":true,"family":"Stillings","given":"Lisa","email":"stilling@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":700795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Decker, David L.","contributorId":193549,"corporation":false,"usgs":false,"family":"Decker","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":700797,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191606,"text":"70191606 - 2017 - Finite‐fault Bayesian inversion of teleseismic body waves","interactions":[],"lastModifiedDate":"2017-10-17T15:00:45","indexId":"70191606","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Finite‐fault Bayesian inversion of teleseismic body waves","docAbstract":"

Inverting geophysical data has provided fundamental information about the behavior of earthquake rupture. However, inferring kinematic source model parameters for finite‐fault ruptures is an intrinsically underdetermined problem (the problem of nonuniqueness), because we are restricted to finite noisy observations. Although many studies use least‐squares techniques to make the finite‐fault problem tractable, these methods generally lack the ability to apply non‐Gaussian error analysis and the imposition of nonlinear constraints. However, the Bayesian approach can be employed to find a Gaussian or non‐Gaussian distribution of all probable model parameters, while utilizing nonlinear constraints. We present case studies to quantify the resolving power and associated uncertainties using only teleseismic body waves in a Bayesian framework to infer the slip history for a synthetic case and two earthquakes: the 2011 Mw 7.1 Van, east Turkey, earthquake and the 2010 Mw 7.2 El Mayor–Cucapah, Baja California, earthquake. In implementing the Bayesian method, we further present two distinct solutions to investigate the uncertainties by performing the inversion with and without velocity structure perturbations. We find that the posterior ensemble becomes broader when including velocity structure variability and introduces a spatial smearing of slip. Using the Bayesian framework solely on teleseismic body waves, we find rake is poorly constrained by the observations and rise time is poorly resolved when slip amplitude is low.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160268","usgsCitation":"Clayton, B., Hartzell, S.H., Moschetti, M.P., and Minson, S.E., 2017, Finite‐fault Bayesian inversion of teleseismic body waves: Bulletin of the Seismological Society of America, v. 107, no. 3, p. 1526-1544, https://doi.org/10.1785/0120160268.","productDescription":"19 p.","startPage":"1526","endPage":"1544","ipdsId":"IP-083374","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":346721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-28","publicationStatus":"PW","scienceBaseUri":"59e71691e4b05fe04cd331a5","contributors":{"authors":[{"text":"Clayton, Brandon 0000-0003-0502-7184 bclayton@usgs.gov","orcid":"https://orcid.org/0000-0003-0502-7184","contributorId":197196,"corporation":false,"usgs":true,"family":"Clayton","given":"Brandon","email":"bclayton@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":712859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":712860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":712861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":712862,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192680,"text":"70192680 - 2017 - Enclosed nests may provide greater thermal than nest predation benefits compared with open nests across latitudes","interactions":[],"lastModifiedDate":"2017-12-01T13:25:21","indexId":"70192680","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1711,"text":"Functional Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Enclosed nests may provide greater thermal than nest predation benefits compared with open nests across latitudes","docAbstract":"
  1. Nest structure is thought to provide benefits that have fitness consequences for several taxa. Traditionally, reduced nest predation has been considered the primary benefit underlying evolution of nest structure, whereas thermal benefits have been considered a secondary or even non-existent factor. Yet, the relative roles of these factors on nest structures remain largely unexplored.
  2. Enclosed nests have a constructed or natural roof connected to sides that allow a restricted opening or tube entrance that provides cover in all directions except the entrance, whereas open nests are cups or platforms that are open above. We show that construction of enclosed nests is more common among songbirds (Passeriformes) in tropical and southern hemisphere regions than in north temperate regions. This geographic pattern may reflect selection from predation risk, under long-standing assumptions that nest predation rates are higher in southern regions and that enclosed nests reduce predation risk compared with open cup nests. We therefore compared nest predation rates between enclosed vs. open nests in 114 songbird species that do not nest in tree holes among five communities of coexisting birds, and for 205 non-hole-nesting species from the literature, across northern temperate, tropical, and southern hemisphere regions.
  3. Among coexisting species, enclosed nests had lower nest predation rates than open nests in two south temperate sites, but not in either of two tropical sites or a north temperate site. Nest predation did not differ between nest types at any latitude based on literature data. Among 319 species from both our field studies and the literature, enclosed nests did not show consistent benefits of reduced predation and, in fact, predation was not consistently higher in the tropics, contrary to long-standing perspectives.
  4. Thermal benefits of enclosed nests were indicated based on three indirect results. First, species that built enclosed nests were smaller than species using open nests both among coexisting species and among species from the literature. Smaller species lose heat fastest and thereby may gain important thermal benefits from reduced convective cooling. Second, eggs were warmed by parents for less time in species with enclosed nests, as can be expected if egg cooling rates are slower. Finally, species using enclosed nests exhibited enhanced growth of mass and wings compared with species using open nests, suggesting reduced thermoregulatory costs allowed increased energy for growth.
  5. Enclosed nests may therefore provide more consistent thermal than nest predation benefits, counter to long-standing perspectives.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2435.12819","usgsCitation":"Martin, T.E., Boyce, A.J., Fierro-Calderon, K., Mitchell, A.E., Armstad, C.E., Mouton, J.C., and Bin Soudi, E.E., 2017, Enclosed nests may provide greater thermal than nest predation benefits compared with open nests across latitudes: Functional Ecology, v. 31, no. 6, p. 1231-1240, https://doi.org/10.1111/1365-2435.12819.","productDescription":"10 p.","startPage":"1231","endPage":"1240","ipdsId":"IP-066309","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469793,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2435.12819","text":"Publisher Index Page"},{"id":349636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-25","publicationStatus":"PW","scienceBaseUri":"5a60fbbee4b06e28e9c23546","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":716709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyce, Andy J.","contributorId":200182,"corporation":false,"usgs":false,"family":"Boyce","given":"Andy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":724298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fierro-Calderon, Karolina","contributorId":13500,"corporation":false,"usgs":true,"family":"Fierro-Calderon","given":"Karolina","email":"","affiliations":[],"preferred":false,"id":724299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mitchell, Adam E.","contributorId":166758,"corporation":false,"usgs":false,"family":"Mitchell","given":"Adam","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":724300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Armstad, Connor E.","contributorId":201088,"corporation":false,"usgs":false,"family":"Armstad","given":"Connor","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":724301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mouton, James C.","contributorId":198675,"corporation":false,"usgs":false,"family":"Mouton","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":724302,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bin Soudi, Evertius E.","contributorId":201089,"corporation":false,"usgs":false,"family":"Bin Soudi","given":"Evertius","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":724303,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70193948,"text":"70193948 - 2017 - Understanding ecosystem services adoption by natural resource managers and research ecologists","interactions":[],"lastModifiedDate":"2017-11-17T15:23:34","indexId":"70193948","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Understanding ecosystem services adoption by natural resource managers and research ecologists","docAbstract":"

The ecosystem services (ES) paradigm has gained much traction as a natural resource management approach due to its comprehensive nature and ability to provide quantitative tools to improve decision-making. However, it is still uncertain whether and how practitioners have adopted the ES paradigm into their work and how this aligns with resource management information needs. To address this, we surveyed natural resource managers within the Great Lakes region about their use of ES information in decision-making. We complemented our manager survey with in-depth interviews of a related population—research ecologists at the U.S. Geological Survey Great Lakes Science Center. In this study, managers and ecologists almost unanimously agreed that ES were appropriate to consider in resource management. We also found high congruence between managers and ecologists in the ES considered most relevant to their work, with provision of habitat, recreation and tourism, biological control, and primary production being the ES ranked highly by both groups. However, a disconnect arose when research ecologists deemed the information they provide regarding ES as adequate for management needs, but managers disagreed. Furthermore, managers reported that they would use economic information about ES if they had access to that information. We believe this data deficiency could represent a gap in scientific coverage by ecologists, but it may also simply reflect an underrepresentation of ecological economists who can translate ecological knowledge of ES providers into economic information that many managers desired.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2017.01.005","usgsCitation":"Engel, D., Evans, M.A., Low, B.S., and Schaeffer, J., 2017, Understanding ecosystem services adoption by natural resource managers and research ecologists: Journal of Great Lakes Research, v. 43, no. 3, p. 169-179, https://doi.org/10.1016/j.jglr.2017.01.005.","productDescription":"11 p.","startPage":"169","endPage":"179","ipdsId":"IP-074560","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":461529,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2017.01.005","text":"Publisher Index Page"},{"id":349078,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fbbce4b06e28e9c23527","contributors":{"authors":[{"text":"Engel, Daniel dengel@usgs.gov","contributorId":189288,"corporation":false,"usgs":true,"family":"Engel","given":"Daniel","email":"dengel@usgs.gov","affiliations":[],"preferred":true,"id":721703,"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":149358,"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":true,"id":721704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Low, Bobbi S.","contributorId":189289,"corporation":false,"usgs":false,"family":"Low","given":"Bobbi","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":721705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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 Center","active":true,"usgs":true}],"preferred":true,"id":721702,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194492,"text":"70194492 - 2017 - Constraining the thermal history of the North American Midcontinent Rift System using carbonate clumped isotopes and organic thermal maturity indices","interactions":[],"lastModifiedDate":"2017-11-30T11:34:28","indexId":"70194492","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3112,"text":"Precambrian Research","active":true,"publicationSubtype":{"id":10}},"title":"Constraining the thermal history of the North American Midcontinent Rift System using carbonate clumped isotopes and organic thermal maturity indices","docAbstract":"

The Midcontinent Rift System (MRS) is a Late Mesoproterozoic (∼1.1 Ga) sequence of volcanic and sedimentary rocks exposed in the Lake Superior Region of North America. The MRS continues to be the focus of much research due to its economic mineral deposits as well as its archive of Precambrian life and tectonic processes. In order to constrain the post-depositional thermal history of the MRS, samples were analyzed for carbonate clumped isotope composition and organic thermal maturity. Clumped isotope values from sedimentary/early-diagenetic samples were partially reset during burial to temperatures between 68 and 75 °C. Solid-state reordering models indicate that maximum burial temperatures of 125–155 °C would reset the clumped isotope values to the observed temperature range prior to the onset of regional cooling and uplift. Clumped isotope results from late-stage veins in the White Pine Mine encompass a greater temperature range (49–116 °C), indicative of spatially variable hydrothermal activity and vein emplacement after burial temperatures fell below 100 °C during regional cooling and uplift. Clumped isotope and organic thermal maturity data do not indicate significant spatial differences in thermal history along the MRS. Observed variability in bulk organic matter composition and biomarker indices are therefore more likely a result of shifts in primary productivity or early-degradation processes. These results demonstrate that the MRS experienced a spatially consistent, relatively mild thermal history (125–155 °C) and is therefore a valuable archive for understanding the Late Mesoproterozoic environment.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.precamres.2017.03.022","usgsCitation":"Gallagher, T.M., Sheldon, N.D., Mauk, J.L., Petersen, S.V., Gueneli, N., and Brocks, J.J., 2017, Constraining the thermal history of the North American Midcontinent Rift System using carbonate clumped isotopes and organic thermal maturity indices: Precambrian Research, v. 294, p. 53-66, https://doi.org/10.1016/j.precamres.2017.03.022.","productDescription":"14 p.","startPage":"53","endPage":"66","ipdsId":"IP-080782","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":469803,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.precamres.2017.03.022","text":"Publisher Index Page"},{"id":349586,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.4224853515625,\n 46.33175800051563\n ],\n [\n -87.462158203125,\n 46.33175800051563\n ],\n [\n -87.462158203125,\n 48.23565029755308\n ],\n [\n -92.4224853515625,\n 48.23565029755308\n ],\n [\n -92.4224853515625,\n 46.33175800051563\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"294","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fbbce4b06e28e9c23520","contributors":{"authors":[{"text":"Gallagher, Timothy M.","contributorId":201012,"corporation":false,"usgs":false,"family":"Gallagher","given":"Timothy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":724101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheldon, Nathan D.","contributorId":201013,"corporation":false,"usgs":false,"family":"Sheldon","given":"Nathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":724102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mauk, Jeffrey L. 0000-0002-6244-2774 jmauk@usgs.gov","orcid":"https://orcid.org/0000-0002-6244-2774","contributorId":4101,"corporation":false,"usgs":true,"family":"Mauk","given":"Jeffrey","email":"jmauk@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724100,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Petersen, Sierra V.","contributorId":201014,"corporation":false,"usgs":false,"family":"Petersen","given":"Sierra","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":724103,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gueneli, Nur","contributorId":201015,"corporation":false,"usgs":false,"family":"Gueneli","given":"Nur","email":"","affiliations":[],"preferred":false,"id":724104,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brocks, Jochen J.","contributorId":201016,"corporation":false,"usgs":false,"family":"Brocks","given":"Jochen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":724105,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192846,"text":"70192846 - 2017 - The recent warming trend in North Greenland","interactions":[],"lastModifiedDate":"2017-11-17T10:49:13","indexId":"70192846","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"The recent warming trend in North Greenland","docAbstract":"

The Arctic is among the fastest warming regions on Earth, but it is also one with limited spatial coverage of multidecadal instrumental surface air temperature measurements. Consequently, atmospheric reanalyses are relatively unconstrained in this region, resulting in a large spread of estimated 30 year recent warming trends, which limits their use to investigate the mechanisms responsible for this trend. Here we present a surface temperature reconstruction over 1982–2011 at NEEM (North Greenland Eemian Ice Drilling Project, 51°W, 77°N), in North Greenland, based on the inversion of borehole temperature and inert gas isotope data. We find that NEEM has warmed by 2.7 ± 0.33°C over the past 30 years, from the long-term 1900–1970 average of −28.55 ± 0.29°C. The warming trend is principally caused by an increase in downward longwave heat flux. Atmospheric reanalyses underestimate this trend by 17%, underlining the need for more in situ observations to validate reanalyses.

","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016GL072212","usgsCitation":"Orsi, A.J., Kawamura, K., Masson-Delmotte, V., Fettweis, X., Box, J.E., Dahl-Jensen, D., Clow, G.D., Landais, A., and Severinghaus, J.P., 2017, The recent warming trend in North Greenland: Geophysical Research Letters, v. 44, no. 12, p. 6235-6243, https://doi.org/10.1002/2016GL072212.","productDescription":"9 p.","startPage":"6235","endPage":"6243","ipdsId":"IP-065150","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":469784,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl072212","text":"Publisher Index Page"},{"id":349054,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-28","publicationStatus":"PW","scienceBaseUri":"5a60fbbde4b06e28e9c23538","contributors":{"authors":[{"text":"Orsi, Anais J.","contributorId":140705,"corporation":false,"usgs":false,"family":"Orsi","given":"Anais","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":717177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kawamura, Kenji","contributorId":195041,"corporation":false,"usgs":false,"family":"Kawamura","given":"Kenji","email":"","affiliations":[],"preferred":false,"id":717178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Masson-Delmotte, Valerie","contributorId":198808,"corporation":false,"usgs":false,"family":"Masson-Delmotte","given":"Valerie","email":"","affiliations":[],"preferred":false,"id":717179,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fettweis, Xavier","contributorId":198810,"corporation":false,"usgs":false,"family":"Fettweis","given":"Xavier","email":"","affiliations":[],"preferred":false,"id":717181,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Box, Jason E.","contributorId":198809,"corporation":false,"usgs":false,"family":"Box","given":"Jason","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":717180,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dahl-Jensen, Dorthe","contributorId":198811,"corporation":false,"usgs":false,"family":"Dahl-Jensen","given":"Dorthe","email":"","affiliations":[],"preferred":false,"id":717182,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Clow, Gary D. 0000-0002-2262-3853 clow@usgs.gov","orcid":"https://orcid.org/0000-0002-2262-3853","contributorId":2066,"corporation":false,"usgs":true,"family":"Clow","given":"Gary","email":"clow@usgs.gov","middleInitial":"D.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":717176,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Landais, Amaelle","contributorId":198812,"corporation":false,"usgs":false,"family":"Landais","given":"Amaelle","email":"","affiliations":[],"preferred":false,"id":717183,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Severinghaus, Jeffrey P.","contributorId":140715,"corporation":false,"usgs":false,"family":"Severinghaus","given":"Jeffrey","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":717184,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70193276,"text":"70193276 - 2017 - Dynamic oceanography determines fine scale foraging behavior of Masked Boobies in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2017-11-11T15:17:58","indexId":"70193276","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic oceanography determines fine scale foraging behavior of Masked Boobies in the Gulf of Mexico","docAbstract":"

During breeding, foraging marine birds are under biological, geographic, and temporal constraints. These contraints require foraging birds to efficiently process environmental cues derived from physical habitat features that occur at nested spatial scales. Mesoscale oceanography in particular may change rapidly within and between breeding seasons, and findings from well-studied systems that relate oceanography to seabird foraging may transfer poorly to regions with substantially different oceanographic conditions. Our objective was to examine foraging behavior of a pan-tropical seabird, the Masked Booby (Sula dactylatra), in the understudied Caribbean province, a moderately productive region driven by highly dynamic currents and fronts. We tracked 135 individuals with GPS units during May 2013, November 2013, and December 2014 at a regionally important breeding colony in the southern Gulf of Mexico. We measured foraging behavior using characteristics of foraging trips and used area restricted search as a proxy for foraging events. Among individual attributes, nest stage contributed to differences in foraging behavior whereas sex did not. Birds searched for prey at nested hierarchical scales ranging from 200 m—35 km. Large-scale coastal and shelf-slope fronts shifted position between sampling periods and overlapped geographically with overall foraging locations. At small scales (at the prey patch level), the specific relationship between environmental variables and foraging behavior was highly variable among individuals but general patterns emerged. Sea surface height anomaly and velocity of water were the strongest predictors of area restricted search behavior in random forest models, a finding that is consistent with the characterization of the Gulf of Mexico as an energetic system strongly influenced by currents and eddies. Our data may be combined with tracking efforts in the Caribbean province and across tropical regions to advance understanding of seabird sensing of the environment and serve as a baseline for anthropogenic based threats such as development, pollution, and commercial fisheries.

","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0178318","usgsCitation":"Poli, C.L., Harrison, A., Vallarino, A., Gerard, P.D., and Jodice, P.G., 2017, Dynamic oceanography determines fine scale foraging behavior of Masked Boobies in the Gulf of Mexico: PLoS ONE, v. 12, no. 6, Article e0178318; 24 p., https://doi.org/10.1371/journal.pone.0178318.","productDescription":"Article e0178318; 24 p.","ipdsId":"IP-079143","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469859,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0178318","text":"Publisher Index Page"},{"id":348611,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","otherGeospatial":"Gulf of Mexico, Isla Muertos","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.83932495117188,\n 22.328481987166487\n ],\n [\n -89.57290649414062,\n 22.328481987166487\n ],\n [\n -89.57290649414062,\n 22.590556292249634\n ],\n [\n -89.83932495117188,\n 22.590556292249634\n ],\n [\n -89.83932495117188,\n 22.328481987166487\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-02","publicationStatus":"PW","scienceBaseUri":"5a07e8d2e4b09af898c8cbb9","contributors":{"authors":[{"text":"Poli, Caroline L.","contributorId":199252,"corporation":false,"usgs":false,"family":"Poli","given":"Caroline","email":"","middleInitial":"L.","affiliations":[{"id":33234,"text":"Clemson University, Clemson, SC","active":true,"usgs":false},{"id":12558,"text":"University of Florida, Gainesville","active":true,"usgs":false}],"preferred":false,"id":718501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrison, Autumn-Lynn","contributorId":199253,"corporation":false,"usgs":false,"family":"Harrison","given":"Autumn-Lynn","email":"","affiliations":[{"id":17600,"text":"Migratory Bird Center, Smithsonian Conservation Biology Institute, National Zoological Park, Washington, DC","active":true,"usgs":false}],"preferred":false,"id":718502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vallarino, Adriana","contributorId":199254,"corporation":false,"usgs":false,"family":"Vallarino","given":"Adriana","email":"","affiliations":[{"id":35488,"text":"Centro de Investigacion y de Estudios Unidad Merida","active":true,"usgs":false}],"preferred":false,"id":718503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerard, Patrick D.","contributorId":199255,"corporation":false,"usgs":false,"family":"Gerard","given":"Patrick","email":"","middleInitial":"D.","affiliations":[{"id":33234,"text":"Clemson University, Clemson, SC","active":true,"usgs":false}],"preferred":false,"id":718504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":1119,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":718500,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192080,"text":"70192080 - 2017 - Habitat models to predict wetland bird occupancy influenced by scale, anthropogenic disturbance, and imperfect detection","interactions":[],"lastModifiedDate":"2017-10-19T15:33:13","indexId":"70192080","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Habitat models to predict wetland bird occupancy influenced by scale, anthropogenic disturbance, and imperfect detection","docAbstract":"

Understanding species–habitat relationships for endangered species is critical for their conservation. However, many studies have limited value for conservation because they fail to account for habitat associations at multiple spatial scales, anthropogenic variables, and imperfect detection. We addressed these three limitations by developing models for an endangered wetland bird, Yuma Ridgway's rail (Rallus obsoletus yumanensis), that examined how the spatial scale of environmental variables, inclusion of anthropogenic disturbance variables, and accounting for imperfect detection in validation data influenced model performance. These models identified associations between environmental variables and occupancy. We used bird survey and spatial environmental data at 2473 locations throughout the species' U.S. range to create and validate occupancy models and produce predictive maps of occupancy. We compared habitat-based models at three spatial scales (100, 224, and 500 m radii buffers) with and without anthropogenic disturbance variables using validation data adjusted for imperfect detection and an unadjusted validation dataset that ignored imperfect detection. The inclusion of anthropogenic disturbance variables improved the performance of habitat models at all three spatial scales, and the 224-m-scale model performed best. All models exhibited greater predictive ability when imperfect detection was incorporated into validation data. Yuma Ridgway's rail occupancy was negatively associated with ephemeral and slow-moving riverine features and high-intensity anthropogenic development, and positively associated with emergent vegetation, agriculture, and low-intensity development. Our modeling approach accounts for common limitations in modeling species–habitat relationships and creating predictive maps of occupancy probability and, therefore, provides a useful framework for other species.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1837","usgsCitation":"Glisson, W.J., Conway, C.J., Nadeau, C.P., and Borgmann, K.L., 2017, Habitat models to predict wetland bird occupancy influenced by scale, anthropogenic disturbance, and imperfect detection: Ecosphere, v. 8, no. 6, p. 1-20, https://doi.org/10.1002/ecs2.1837.","productDescription":"e01837; 20 p.","startPage":"1","endPage":"20","ipdsId":"IP-082202","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469792,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1837","text":"Publisher Index Page"},{"id":347000,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.52099609375,\n 32.57459172113418\n ],\n [\n -112.43408203124999,\n 32.57459172113418\n ],\n [\n -112.43408203124999,\n 36.86204269508728\n ],\n [\n -116.52099609375,\n 36.86204269508728\n ],\n [\n -116.52099609375,\n 32.57459172113418\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-02","publicationStatus":"PW","scienceBaseUri":"59e9b994e4b05fe04cd65c8b","contributors":{"authors":[{"text":"Glisson, Wesley J.","contributorId":171646,"corporation":false,"usgs":false,"family":"Glisson","given":"Wesley","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":714095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":714094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nadeau, Christopher P.","contributorId":105956,"corporation":false,"usgs":true,"family":"Nadeau","given":"Christopher","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":714096,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borgmann, Kathi L.","contributorId":171647,"corporation":false,"usgs":false,"family":"Borgmann","given":"Kathi","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":714097,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}