Using a geology-based assessment methodology, the U.S. Geological Survey assessed undiscovered, technically recoverable mean resources of 787 billion cubic feet of conventional gas and 1,630 billion cubic feet of unconventional gas in the Thrace Basin, Turkey.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163001","usgsCitation":"Schenk, C.J., Klett, T.R., Tennyson, M.E., Pitman, J.K., Gaswirth, S.B., Le, P.A., Leathers-Miller, H.M., Mercier, T.J., Marra, K.R., Hawkins, S.J., and Brownfield, M.E., 2016, Assessment of undiscovered gas resources of the Thrace Basin, Turkey, 2015: U.S. Geological Survey Fact Sheet 2016–3001, 2 p., https://dx.doi.org/10.3133/fs20163001.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070442","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":314887,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3001/coverthb.jpg"},{"id":314888,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3001/fs20163001.pdf","text":"Report","size":"1.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3001"}],"country":"Turkey","otherGeospatial":"Thrace Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 26.597900390625,\n 40.49709237269567\n ],\n [\n 26.597900390625,\n 41.95949009892465\n ],\n [\n 29.102783203125,\n 41.95949009892465\n ],\n [\n 29.102783203125,\n 40.49709237269567\n ],\n [\n 26.597900390625,\n 40.49709237269567\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
http://energy.usgs.gov
Lowland boreal forest ecosystems in Alaska are dominated by wetlands comprised of a complex mosaic of fens, collapse-scar bogs, low shrub/scrub, and forests growing on elevated ice-rich permafrost soils. Thermokarst has affected the lowlands of the Tanana Flats in central Alaska for centuries, as thawing permafrost collapses forests that transition to wetlands. Located within the discontinuous permafrost zone, this region has significantly warmed over the past half-century, and much of these carbon-rich permafrost soils are now within ~0.5 °C of thawing. Increased permafrost thaw in lowland boreal forests in response to warming may have consequences for the climate system. This study evaluates the trajectories and potential drivers of 60 years of forest change in a landscape subjected to permafrost thaw in unburned dominant forest types (paper birch and black spruce) associated with location on elevated permafrost plateau and across multiple time periods (1949, 1978, 1986, 1998, and 2009) using historical and contemporary aerial and satellite images for change detection. We developed (i) a deterministic statistical model to evaluate the potential climatic controls on forest change using gradient boosting and regression tree analysis, and (ii) a 30 × 30 m land cover map of the Tanana Flats to estimate the potential landscape-level losses of forest area due to thermokarst from 1949 to 2009. Over the 60-year period, we observed a nonlinear loss of birch forests and a relatively continuous gain of spruce forest associated with thermokarst and forest succession, while gradient boosting/regression tree models identify precipitation and forest fragmentation as the primary factors controlling birch and spruce forest change, respectively. Between 1950 and 2009, landscape-level analysis estimates a transition of ~15 km² or ~7% of birch forests to wetlands, where the greatest change followed warm periods. This work highlights that the vulnerability and resilience of lowland ice-rich permafrost ecosystems to climate changes depend on forest type.
","language":"English","publisher":"Blackwell Science","doi":"10.1111/gcb.13124","usgsCitation":"Lara, M., Genet, H., McGuire, A.D., Euskirchen, E., Zhang, Y., Brown, D.R., Jorgenson, M., Romanovsky, V., Breen, A.L., and Bolton, W., 2016, Thermokarst rates intensify due to climate change and forest fragmentation in an Alaskan boreal forest lowland: Global Change Biology, v. 22, no. 2, p. 816-829, https://doi.org/10.1111/gcb.13124.","productDescription":"14 p.","startPage":"816","endPage":"829","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067107","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487093,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1401401","text":"External Repository"},{"id":319360,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Tanana Flats","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -146.7279052734375,\n 64.29705772139192\n ],\n [\n -146.7718505859375,\n 64.31849111981204\n ],\n [\n -146.85974121093747,\n 64.33039136366138\n ],\n [\n -146.9586181640625,\n 64.39931146138198\n ],\n [\n -147.0135498046875,\n 64.42777961851408\n ],\n [\n -146.964111328125,\n 64.49882087569566\n ],\n [\n -147.0355224609375,\n 64.51773408905306\n ],\n [\n -147.06298828125,\n 64.55316108653571\n ],\n [\n -147.1453857421875,\n 64.60268165499696\n ],\n [\n -147.227783203125,\n 64.62858508010181\n ],\n [\n -147.2882080078125,\n 64.68736477621857\n ],\n [\n -147.403564453125,\n 64.73195224826483\n ],\n [\n -147.535400390625,\n 64.76944266707025\n ],\n [\n -147.7496337890625,\n 64.79518717004242\n ],\n [\n -147.90344238281247,\n 64.78582837449026\n ],\n [\n -148.0023193359375,\n 64.77880714659877\n ],\n [\n -148.1341552734375,\n 64.72491700255974\n ],\n [\n -148.271484375,\n 64.68031793418317\n ],\n [\n -148.38684082031247,\n 64.65681522497661\n ],\n [\n -148.480224609375,\n 64.65211223878967\n ],\n [\n -148.5845947265625,\n 64.64740843756522\n ],\n [\n -148.6724853515625,\n 64.63799838956571\n ],\n [\n -148.656005859375,\n 64.58382729385322\n ],\n [\n -148.60107421875,\n 64.61445899874353\n ],\n [\n -148.5076904296875,\n 64.6168138555028\n ],\n [\n -148.458251953125,\n 64.58146958015028\n ],\n [\n -148.40332031249997,\n 64.543718384468\n ],\n [\n -148.30993652343747,\n 64.51773408905306\n ],\n [\n -148.2110595703125,\n 64.45384948864441\n ],\n [\n -148.1396484375,\n 64.37794095121995\n ],\n [\n -147.98583984375,\n 64.32563188307633\n ],\n [\n -147.7880859375,\n 64.26606893454858\n ],\n [\n -147.601318359375,\n 64.19442343702703\n ],\n [\n -147.5628662109375,\n 64.12019460255497\n ],\n [\n -147.568359375,\n 64.05297838071347\n ],\n [\n -147.469482421875,\n 64.0914075226231\n ],\n [\n -147.41455078125,\n 64.08660677881706\n ],\n [\n -147.2552490234375,\n 64.06499318301724\n ],\n [\n -147.0904541015625,\n 64.0914075226231\n ],\n [\n -146.9476318359375,\n 64.08180520696276\n ],\n [\n -146.7938232421875,\n 64.0890072542193\n ],\n [\n -146.76635742187497,\n 64.16092532332391\n ],\n [\n -146.7388916015625,\n 64.2231039063906\n ],\n [\n -146.7279052734375,\n 64.29705772139192\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-06","publicationStatus":"PW","scienceBaseUri":"56f50fd4e4b0f59b85e1ebe5","chorus":{"doi":"10.1111/gcb.13124","url":"http://dx.doi.org/10.1111/gcb.13124","publisher":"Wiley-Blackwell","authors":"Lara Mark J., Genet Hélène, McGuire Anthony D., Euskirchen Eugénie S., Zhang Yujin, Brown Dana R. N., Jorgenson Mark T., Romanovsky Vladimir, Breen Amy, Bolton William R.","journalName":"Global Change Biology","publicationDate":"1/6/2016","auditedOn":"1/7/2017"},"contributors":{"authors":[{"text":"Lara, M.","contributorId":17167,"corporation":false,"usgs":true,"family":"Lara","given":"M.","email":"","affiliations":[],"preferred":false,"id":623606,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Genet, Helene","contributorId":95370,"corporation":false,"usgs":true,"family":"Genet","given":"Helene","affiliations":[],"preferred":false,"id":623607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGuire, A. 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N.","contributorId":140386,"corporation":false,"usgs":false,"family":"Brown","given":"Dana","email":"","middleInitial":"R. 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We hypothesize that the climatic impact of boreal fires depends on local landscape heterogeneity such as burn severity, prefire vegetation type, and soil properties. To test this hypothesis, spatially explicit emission of greenhouse gases (GHGs) and aerosols and their resulting radiative forcing are required as an important and necessary component towards a full assessment. In this study, we integrated remote sensing (Landsat and MODIS) and models (carbon consumption model, emission factors model, and radiative forcing model) to calculate the carbon consumption, GHGs and aerosol emissions, and their radiative forcing of 2001–2010 fires at 30 m resolution in the Yukon River Basin of Alaska. Total carbon consumption showed significant spatial variation, with a mean of 2,615 g C m−2 and a standard deviation of 2,589 g C m−2. The carbon consumption led to different amounts of GHGs and aerosol emissions, ranging from 593.26 Tg (CO2) to 0.16 Tg (N2O). When converted to equivalent CO2 based on global warming potential metric, the maximum 20 years equivalent CO2 was black carbon (713.77 Tg), and the lowest 20 years equivalent CO2 was organic carbon (−583.13 Tg). The resulting radiative forcing also showed significant spatial variation: CO2, CH4, and N2O can cause a 20-year mean radiative forcing of 7.41 W m−2 with a standard deviation of 2.87 W m−2. This emission forcing heterogeneity indicates that different boreal fires have different climatic impacts. When considering the spatial variation of other forcings, such as surface shortwave forcing, we may conclude that some boreal fires, especially boreal deciduous fires, can warm the climate.
","language":"English","publisher":"Springer","publisherLocation":"New York","doi":"10.1007/s00704-015-1379-0","usgsCitation":"Huang, S., Liu, H., Dahal, D., Jin, S., Li, S., and Liu, S., 2016, Spatial variations in immediate greenhouse gases and aerosol emissions and resulting radiative forcing from wildfires in interior Alaska: Theoretical and Applied Climatology, v. 123, no. 3, p. 581-592, https://doi.org/10.1007/s00704-015-1379-0.","startPage":"581","endPage":"592","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058246","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":326645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"123","issue":"3","noUsgsAuthors":false,"publicationDate":"2015-01-18","publicationStatus":"PW","scienceBaseUri":"57b58b5de4b03bcb0104bc6e","contributors":{"authors":[{"text":"Huang, Shengli shuang@usgs.gov","contributorId":1926,"corporation":false,"usgs":true,"family":"Huang","given":"Shengli","email":"shuang@usgs.gov","affiliations":[],"preferred":true,"id":519096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Heping","contributorId":117909,"corporation":false,"usgs":true,"family":"Liu","given":"Heping","affiliations":[],"preferred":false,"id":519100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dahal, Devendra 0000-0001-9594-1249 ddahal@usgs.gov","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":5622,"corporation":false,"usgs":true,"family":"Dahal","given":"Devendra","email":"ddahal@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":519098,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":519097,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Shuang","contributorId":116219,"corporation":false,"usgs":true,"family":"Li","given":"Shuang","email":"","affiliations":[],"preferred":false,"id":519099,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liu, Shu-Guang sliu@usgs.gov","contributorId":984,"corporation":false,"usgs":true,"family":"Liu","given":"Shu-Guang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":519095,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70164311,"text":"70164311 - 2016 - Dome growth at Mount Cleveland, Aleutian Arc, quantified by time-series TerraSAR-X imagery","interactions":[],"lastModifiedDate":"2016-02-01T11:10:02","indexId":"70164311","displayToPublicDate":"2016-02-01T12:00:00","publicationYear":"2016","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":"Dome growth at Mount Cleveland, Aleutian Arc, quantified by time-series TerraSAR-X imagery","docAbstract":"Synthetic aperture radar imagery is widely used to study surface deformation induced by volcanic activity; however, it is rarely applied to quantify the evolution of lava domes, which is important for understanding hazards and magmatic system characteristics. We studied dome formation associated with eruptive activity at Mount Cleveland, Aleutian Volcanic Arc, in 2011–2012 using TerraSAR-X imagery. Interferometry and offset tracking show no consistent deformation and only motion of the crater rim, suggesting that ascending magma may pass through a preexisting conduit system without causing appreciable surface deformation. Amplitude imagery has proven useful for quantifying rates of vertical and areal growth of the lava dome within the crater from formation to removal by explosive activity to rebirth. We expect that this approach can be applied at other volcanoes that host growing lava domes and where hazards are highly dependent on dome geometry and growth rates.
","language":"English","publisher":"Americal Geophysical Union","doi":"10.1002/2015GL066784","usgsCitation":"Wang, T., Poland, M.P., and Lu, Z., 2016, Dome growth at Mount Cleveland, Aleutian Arc, quantified by time-series TerraSAR-X imagery: Geophysical Research Letters, v. 42, no. 24, p. 10614-10621, https://doi.org/10.1002/2015GL066784.","productDescription":"8 p.","startPage":"10614","endPage":"10621","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070279","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":316381,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Mount Cleveland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -170.01651763916016,\n 52.78220817434916\n ],\n [\n -170.01651763916016,\n 52.86063195166758\n ],\n [\n -169.8651123046875,\n 52.86063195166758\n ],\n [\n -169.8651123046875,\n 52.78220817434916\n ],\n [\n -170.01651763916016,\n 52.78220817434916\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"24","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-23","publicationStatus":"PW","scienceBaseUri":"56b081bae4b010e2af2a1181","contributors":{"authors":[{"text":"Wang, Teng","contributorId":156235,"corporation":false,"usgs":false,"family":"Wang","given":"Teng","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":596942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":596941,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lu, Zhong 0000-0001-9181-1818 lu@usgs.gov","orcid":"https://orcid.org/0000-0001-9181-1818","contributorId":901,"corporation":false,"usgs":true,"family":"Lu","given":"Zhong","email":"lu@usgs.gov","affiliations":[],"preferred":true,"id":596943,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70164312,"text":"70164312 - 2016 - Post-eruptive inflation of Okmok Volcano, Alaska, from InSAR, 2008–2014","interactions":[],"lastModifiedDate":"2016-02-01T11:00:28","indexId":"70164312","displayToPublicDate":"2016-02-01T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Post-eruptive inflation of Okmok Volcano, Alaska, from InSAR, 2008–2014","docAbstract":"Okmok, a ~10-km wide caldera that occupies most of the northeastern end of Umnak Island, is one of the most active volcanoes in the Aleutian arc. The most recent eruption at Okmok during July-August 2008 was by far its largest and most explosive since at least the early 19th century. We investigate post-eruptive magma supply and storage at the volcano during 2008–2014 by analyzing all available synthetic aperture radar (SAR) images of Okmok acquired during that time period using the multi-temporal InSAR technique. Data from the C-band Envisat and X-band TerraSAR-X satellites indicate that Okmok started inflating very soon after the end of 2008 eruption at a time-variable rate of 48-130 mm/y, consistent with GPS measurements. The “model-assisted” phase unwrapping method is applied to improve the phase unwrapping operation for long temporal baseline pairs. The InSAR time-series is used as input for deformation source modeling, which suggests magma accumulating at variable rates in a shallow storage zone at ~3.9 km below sea level beneath the summit caldera, consistent with previous studies. The modeled volume accumulation in the 6 years following the 2008 eruption is ~75% of the 1997 eruption volume and ~25% of the 2008 eruption volume.
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The 2014–2015 Pāhoa lava flow crisis, however, was unique in terms of its societal impact and volcanological characteristics. Despite low effusion rates, a long-lived lava flow whose extent reached 20 km (the longest at Kīlauea Volcano in the past several hundred years) was poised for months to impact thousands of people, although direct impacts were ultimately minor (thus far). Careful observation of the flow reaffirmed and expanded knowledge of the processes associated with pāhoehoe emplacement, including the direct correlation between summit pressurization and flow advance, the influence of existing geologic structures on flow pathways, and the possible relationship between effusion rate and flow length. Communicating uncertainty associated with lava flow hazards was a challenge throughout the crisis, but online distribution of information and direct contact with residents proved to be effective strategies for keeping the public informed and educated about flow progress and how lava flows work (including forecasting limitations). Volcanological and sociological lessons will be important for inevitable future lava flow crises in Hawai‘i and, potentially, elsewhere in the world.
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The increase in mercury deposition to these systems over the past century, coupled with their limited exposure to direct anthropogenic disturbance make them useful indicators for estimating how changes in mercury emissions may propagate to changes in Hg bioaccumulation and ecological risk. We evaluated mercury concentrations in resident fish from 28 high-elevation, sub-alpine lakes in the Pacific Northwest region of the United States. Fish total mercury (THg) concentrations ranged from 4 to 438 ng/g wet weight, with a geometric mean concentration (±standard error) of 43 ± 2 ng/g ww. Fish THg concentrations were negatively correlated with relative condition factor, indicating that faster growing fish that are in better condition have lower THg concentrations. Across the 28 study lakes, mean THg concentrations of resident salmonid fishes varied as much as 18-fold among lakes. We used a hierarchal statistical approach to evaluate the relative importance of physiological, limnological, and catchment drivers of fish Hg concentrations. Our top statistical model explained 87% of the variability in fish THg concentrations among lakes with four key landscape and limnological variables: catchment conifer density (basal area of conifers within a lake's catchment), lake surface area, aqueous dissolved sulfate, and dissolved organic carbon. Conifer density within a lake's catchment was the most important variable explaining fish THg concentrations across lakes, with THg concentrations differing by more than 400 percent across the forest density spectrum. These results illustrate the importance of landscape characteristics in controlling mercury bioaccumulation in fish.
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We examined whether the spatial distribution of the endangered Alasmidonta heterodon in Flat Brook, a tributary of the upper Delaware River, was constrained by water chemistry (i.e., calcium availability), bed mobility, or both. Alasmidonta heterodon populations were bracketed between upstream reaches that were under-saturated with respect to aragonite and downstream reaches that were saturated for aragonite during summer baseflow but had steep channels with high bed mobility. Variability in bed mobility and water chemistry along the length of Flat Brook create a “habitat window” for A. heterodon defined by bed stability (mobility index ≤1) and aragonite saturation (saturation index ≥1). We suggest the species may exist in a narrow biogeochemical window that is seasonally near saturation. Alasmidonta heterodon populations may be susceptible to climate change or anthropogenic disturbances that increase discharge, decrease groundwater inflow or chemistry, and thus affect either bed mobility or aragonite saturation. Identifying the biogeochemical microhabitats and requirements of individual mussel species and incorporating this knowledge into management decisions should enhance the conservation and restoration of endangered mussel species.
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Efforts to recover the California Ridgway’s Rail (Rallus obsoletus obsoletus; hereafter, California rail), a federally and state-listed species, and restoration of tidal marsh ecosystems in the San Francisco Bay estuary provide a prime example of habitat restoration that has conflicted with species conservation. On the brink of extinction from habitat loss and degradation, and non-native predators in the 1990s, California rail populations responded positively to introduction of a non-native plant, Atlantic cordgrass (Spartina alterniflora). California rail populations were in substantial decline when the non-native Spartina was initially introduced as part of efforts to recover tidal marshes. Subsequent hybridization with the native Pacific cordgrass (Spartina foliosa) boosted California rail populations by providing greater cover and increased habitat area. The hybrid cordgrass (S. alterniflora × S. foliosa) readily invaded tidal mudflats and channels, and both crowded out native tidal marsh plants and increased sediment accretion in the marsh plain. This resulted in modification of tidal marsh geomorphology, hydrology, productivity, and species composition. Our results show that denser California rail populations occur in invasive Spartina than in native Spartina in San Francisco Bay. Herbicide treatment between 2005 and 2012 removed invasive Spartina from open intertidal mud and preserved foraging habitat for shorebirds. However, removal of invasive Spartina caused substantial decreases in California rail populations. Unknown facets of California rail ecology, undesirable interim stages of tidal marsh restoration, and competing management objectives among stakeholders resulted in management planning for endangered species or ecosystem restoration that favored one goal over the other. We have examined this perceived conflict and propose strategies for moderating harmful effects of restoration while meeting the needs of both endangered species and the imperiled native marsh ecosystem.
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Shannon 0000-0003-1229-8580 sskalos@usgs.gov","orcid":"https://orcid.org/0000-0003-1229-8580","contributorId":167191,"corporation":false,"usgs":true,"family":"Skalos","given":"Shannon","email":"sskalos@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":621354,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":621355,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70164449,"text":"70164449 - 2016 - Reflectance spectroscopy (0.35–8 μm) of ammonium-bearing minerals and qualitative comparison to Ceres-like asteroids","interactions":[],"lastModifiedDate":"2016-02-05T09:15:58","indexId":"70164449","displayToPublicDate":"2016-02-01T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Reflectance spectroscopy (0.35–8 μm) of ammonium-bearing minerals and qualitative comparison to Ceres-like asteroids","docAbstract":"Ammonium-bearing minerals have been suggested to be present on Mars, Ceres, and various asteroids and comets. We undertook a systematic study of the spectral reflectance properties of ammonium-bearing minerals and compounds that have possible planetary relevance (i.e., ammonium carbonates, chlorides, nitrates, oxalates, phosphates, silicates, and sulfates). Various synthetic and natural NH4+-bearing minerals were analyzed using reflectance spectroscopy in the long-wave ultraviolet, visible, near-infrared, and mid-infrared regions (0.35–8 μm) in order to identify spectral features characteristic of the NH4+ molecule, and to evaluate if and how these features vary among different species. Mineral phases were confirmed through structural and compositional analyses using X-ray diffraction, X-ray fluorescence, and elemental combustion analysis. Characteristic absorption features associated with NH4 can be seen in the reflectance spectra at wavelengths as short as ∼1 μm. In the near-infrared region, the most prominent absorption bands are located near 1.6, 2.0, and 2.2 μm. Absorption features characteristic of NH4+ occurred at slightly longer wavelengths in the mineral-bound NH4+ spectra than for free NH4+ for most of the samples. Differences in wavelength position are attributable to various factors, including differences in the type and polarizability of the anion(s) attached to the NH4+, degree and type of hydrogen bonding, molecule symmetry, and cation substitutions. Multiple absorption features, usually three absorption bands, in the mid-infrared region between ∼2.8 and 3.8 μm were seen in all but the most NH4-poor sample spectra, and are attributed to fundamentals, combinations, and overtones of stretching and bending vibrations of the NH4+ molecule. These features appear even in reflectance spectra of water-rich samples which exhibit a strong 3 μm region water absorption feature. While many of the samples examined in this study have NH4 absorption bands at unique wavelength positions, in order to discriminate between different NH4+-bearing phases, absorption features corresponding to molecules other than NH4+ should be included in spectral analysis. A qualitative comparison of the laboratory results to telescopic spectra of Asteroids 1 Ceres, 10 Hygiea, and 324 Bamberga for the 3 μm region demonstrates that a number of NH4-bearing phases are consistent with the observational data in terms of exhibiting an absorption band in the 3.07 μm region.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Icarus","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.icarus.2015.10.028","usgsCitation":"Berg, B.L., Cloutis, E.A., Beck, P., Vernazza, P., Bishop, J., Takir, D., Reddy, V., Applin, D., and Mann, P., 2016, Reflectance spectroscopy (0.35–8 μm) of ammonium-bearing minerals and qualitative comparison to Ceres-like asteroids: Icarus, v. 265, p. 218-237, https://doi.org/10.1016/j.icarus.2015.10.028.","productDescription":"10 p.","startPage":"218","endPage":"237","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066433","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":316593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"265","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56b5d658e4b0cc799981738d","contributors":{"authors":[{"text":"Berg, Breanne L.","contributorId":156312,"corporation":false,"usgs":false,"family":"Berg","given":"Breanne","email":"","middleInitial":"L.","affiliations":[{"id":20308,"text":"Department of Geography, University of Winnipeg, Winnipeg, MB, Canada R3B 2E9","active":true,"usgs":false}],"preferred":false,"id":597404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cloutis, Edward A.","contributorId":156313,"corporation":false,"usgs":false,"family":"Cloutis","given":"Edward","email":"","middleInitial":"A.","affiliations":[{"id":20308,"text":"Department of Geography, University of Winnipeg, Winnipeg, MB, Canada R3B 2E9","active":true,"usgs":false}],"preferred":false,"id":597405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beck, P.","contributorId":43700,"corporation":false,"usgs":true,"family":"Beck","given":"P.","affiliations":[],"preferred":false,"id":597406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vernazza, P.","contributorId":156314,"corporation":false,"usgs":false,"family":"Vernazza","given":"P.","email":"","affiliations":[{"id":20309,"text":"Aix Marseille Université, CNRS, LAM (Laboratoire d’Astrophysique de Marseille) UMR 7326, 13388 Marseille, France","active":true,"usgs":false}],"preferred":false,"id":597407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bishop, Janice L","contributorId":156315,"corporation":false,"usgs":false,"family":"Bishop","given":"Janice L","affiliations":[{"id":20310,"text":"SETI Institute, 89 Bernardo Ave, Suite 100, Mountain View, CA, USA 94043","active":true,"usgs":false}],"preferred":false,"id":597408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Takir, Driss dtakir@usgs.gov","contributorId":152190,"corporation":false,"usgs":true,"family":"Takir","given":"Driss","email":"dtakir@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":597403,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reddy, V.","contributorId":156316,"corporation":false,"usgs":false,"family":"Reddy","given":"V.","email":"","affiliations":[{"id":20311,"text":"Planetary Science Institute, 1700 East Fort Lowell, Suite 106, Tucson, AZ, USA 85719-2395","active":true,"usgs":false}],"preferred":false,"id":597409,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Applin, D.","contributorId":156317,"corporation":false,"usgs":false,"family":"Applin","given":"D.","email":"","affiliations":[{"id":20308,"text":"Department of Geography, University of Winnipeg, Winnipeg, MB, Canada R3B 2E9","active":true,"usgs":false}],"preferred":false,"id":597410,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mann, Paul","contributorId":57729,"corporation":false,"usgs":true,"family":"Mann","given":"Paul","email":"","affiliations":[],"preferred":false,"id":597411,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70169024,"text":"70169024 - 2016 - Does biodiversity protect humans against infectious disease? Reply","interactions":[],"lastModifiedDate":"2020-12-17T20:24:50.855583","indexId":"70169024","displayToPublicDate":"2016-02-01T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Does biodiversity protect humans against infectious disease? Reply","docAbstract":"The dilution effect is the sort of idea that everyone wants to be true. If nature protects humans against infectious disease, imagine the implications: nature's value could be tallied in terms of human suffering avoided. This makes a potent argument for conservation, convincing even to those who would otherwise be disinclined to support conservation initiatives. The appeal of the dilution effect has been recognized by others: “the desire to make the case for conservation has led to broad claims regarding the benefits of nature conservation for human health” (Bauch et al. 2015). Randolph and Dobson (2012) were among the first to critique these claims, making the case that promotion of conservation to reduce Lyme disease risk, although well intentioned, was flawed. Along with Randolph and Dobson's critique, there have been several calls for a more nuanced scientific assessment of the relationship between biodiversity and disease transmission (Dunn 2010, Salkeld et al. 2013, Wood and Lafferty 2013, Young et al. 2013). In response, supporters of the dilution effect have instead increased the scope of their generalizations with review papers, press releases, and, like Levi et al. (2015), letters. These responses have been successful; it is not uncommon to read papers that repeat the assertion that biodiversity generally interferes with disease transmission and that conservation will therefore generally benefit human health. Here, we explain how Levi et al. (2015) and other, similar commentaries use selective interpretation and shifting definitions to argue for the generality of the dilution effect hypothesis.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Brooklyn, NY","doi":"10.1890/15-1503.1","usgsCitation":"Wood, C., Lafferty, K.D., DeLeo, G., Young, H.S., Hudson, P., and Kuris, A.M., 2016, Does biodiversity protect humans against infectious disease? Reply: Ecology, v. 97, no. 2, p. 543-546, https://doi.org/10.1890/15-1503.1.","productDescription":"4 p.","startPage":"543","endPage":"546","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069419","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471273,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2027.42/117557","text":"External Repository"},{"id":318810,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-07","publicationStatus":"PW","scienceBaseUri":"56e3fa41e4b0f59b85d4940a","contributors":{"authors":[{"text":"Wood, Chelsea L.","contributorId":36866,"corporation":false,"usgs":true,"family":"Wood","given":"Chelsea L.","affiliations":[],"preferred":false,"id":622562,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":622561,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeLeo, Giulio","contributorId":147447,"corporation":false,"usgs":false,"family":"DeLeo","given":"Giulio","email":"","affiliations":[{"id":16854,"text":"Standford University","active":true,"usgs":false}],"preferred":false,"id":622563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, Hillary S.","contributorId":53711,"corporation":false,"usgs":false,"family":"Young","given":"Hillary","email":"","middleInitial":"S.","affiliations":[{"id":13007,"text":"Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":622564,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hudson, Peter J.","contributorId":85056,"corporation":false,"usgs":true,"family":"Hudson","given":"Peter J.","affiliations":[],"preferred":false,"id":622565,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kuris, Armand M.","contributorId":54332,"corporation":false,"usgs":true,"family":"Kuris","given":"Armand","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":622566,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70175167,"text":"70175167 - 2016 - Continental Shelf Morphology and Stratigraphy Offshore San Onofre, CA: The Interplay Between Rates of Eustatic Change and Sediment Supply","interactions":[],"lastModifiedDate":"2016-08-02T11:25:26","indexId":"70175167","displayToPublicDate":"2016-02-01T06:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Continental Shelf Morphology and Stratigraphy Offshore San Onofre, CA: The Interplay Between Rates of Eustatic Change and Sediment Supply","docAbstract":"New high-resolution CHIRP seismic data acquired offshore San Onofre, southern California reveal that shelf sediment distribution and thickness are primarily controlled by eustatic sea level rise and sediment supply. Throughout the majority of the study region, a prominent abrasion platform and associated shoreline cutoff are observed in the subsurface from ~ 72 to 53 m below present sea level. These erosional features appear to have formed between Melt Water Pulse 1A and Melt Water Pulse 1B, when the rate of sea-level rise was lower. There are three distinct sedimentary units mapped above a regional angular unconformity interpreted to be the Holocene transgressive surface in the seismic data. Unit I, the deepest unit, is interpreted as a lag deposit that infills a topographic low associated with an abrasion platform. Unit I thins seaward by downlap and pinches out landward against the shoreline cutoff. Unit II is a mid-shelf lag deposit formed from shallower eroded material and thins seaward by downlap and landward by onlap. The youngest, Unit III, is interpreted to represent modern sediment deposition. Faults in the study area do not appear to offset the transgressive surface. The Newport Inglewood/Rose Canyon fault system is active in other regions to the south (e.g., La Jolla) where it offsets the transgressive surface and creates seafloor relief. Several shoals observed along the transgressive surface could record minor deformation due to fault activity in the study area. Nevertheless, our preferred interpretation is that the shoals are regions more resistant to erosion during marine transgression. The Cristianitos fault zone also causes a shoaling of the transgressive surface. This may be from resistant antecedent topography due to an early phase of compression on the fault. The Cristianitos fault zone was previously defined as a down-to-the-north normal fault, but the folding and faulting architecture imaged in the CHIRP data are more consistent with a strike-slip fault with a down-to-the-northwest dip-slip component. A third area of shoaling is observed off of San Mateo and San Onofre creeks. This shoaling has a constructional component and could be a relict delta or beach structure. (C) 2015 Elsevier B.V. All rights reserved.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.margeo.2015.08.003","usgsCitation":"Klotsko, S., Driscoll, N.W., Kent, G., and Brothers, D.S., 2016, Continental Shelf Morphology and Stratigraphy Offshore San Onofre, CA: The Interplay Between Rates of Eustatic Change and Sediment Supply: Marine Geology, v. 369, p. 116-126, https://doi.org/10.1016/j.margeo.2015.08.003.","productDescription":"11 p.","startPage":"116","endPage":"126","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064476","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":325909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Onofre State Beach, Southern California, between Los Angeles and San Diego","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.5665855407715,\n 33.37913595905522\n ],\n [\n -117.5430679321289,\n 33.36444180060303\n ],\n [\n -117.52504348754881,\n 33.351680957199115\n ],\n [\n -117.50916481018065,\n 33.340495758384954\n ],\n [\n -117.50144004821779,\n 33.3333250034563\n ],\n [\n -117.50555992126465,\n 33.33038482330389\n ],\n [\n -117.57113456726073,\n 33.37583894926043\n ],\n [\n -117.5665855407715,\n 33.37913595905522\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"369","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a1c42ee4b006cb45552c00","contributors":{"authors":[{"text":"Klotsko, Shannon","contributorId":173303,"corporation":false,"usgs":false,"family":"Klotsko","given":"Shannon","email":"","affiliations":[{"id":27208,"text":"UC San Diego","active":true,"usgs":false}],"preferred":false,"id":644187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driscoll, Neal W.","contributorId":140186,"corporation":false,"usgs":false,"family":"Driscoll","given":"Neal","email":"","middleInitial":"W.","affiliations":[{"id":12888,"text":"Scripps Institution of Oceanography, Univ of California","active":true,"usgs":false}],"preferred":false,"id":644188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kent, Graham","contributorId":7608,"corporation":false,"usgs":true,"family":"Kent","given":"Graham","affiliations":[],"preferred":false,"id":644189,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brothers, Daniel S. 0000-0001-7702-157X dbrothers@usgs.gov","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":167089,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel","email":"dbrothers@usgs.gov","middleInitial":"S.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":644186,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171476,"text":"70171476 - 2016 - Integrated risk and recovery monitoring of ecosystem restorations on contaminated sites","interactions":[],"lastModifiedDate":"2018-08-07T12:46:43","indexId":"70171476","displayToPublicDate":"2016-02-01T01:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Integrated risk and recovery monitoring of ecosystem restorations on contaminated sites","docAbstract":"Ecological restorations of contaminated sites balance the human and ecological risks of residual contamination with the benefits of ecological recovery and the return of lost ecological function and ecosystem services. Risk and recovery are interrelated dynamic conditions, changing as remediation and restoration activities progress through implementation into long-term management and ecosystem maturation. Monitoring restoration progress provides data critical to minimizing residual contaminant risk and uncertainty, while measuring ecological advancement toward recovery goals. Effective monitoring plans are designed concurrently with restoration plan development and implementation and are focused on assessing the effectiveness of activities performed in support of restoration goals for the site. Physical, chemical, and biotic measures characterize progress toward desired structural and functional ecosystem components of the goals. Structural metrics, linked to ecosystem functions and services, inform restoration practitioners of work plan modifications or more substantial adaptive management actions necessary to maintain desired recovery. Monitoring frequency, duration, and scale depend on specific attributes and goals of the restoration project. Often tied to restoration milestones, critical assessment of monitoring metrics ensures attainment of risk minimization and ecosystem recovery. Finally, interpretation and communication of monitoring findings inform and engage regulators, other stakeholders, the scientific community, and the public. Because restoration activities will likely cease before full ecosystem recovery, monitoring endpoints should demonstrate risk reduction and a successional trajectory toward the condition established in the restoration goals. A detailed assessment of the completed project's achievements, as well as unrealized objectives, attained through project monitoring, will determine if contaminant risk has been minimized, if injured resources have recovered, and if ecosystem services have been returned. Such retrospective analysis will allow better planning for future restoration goals and strengthen the evidence base for quantifying injuries and damages at other sites in the future.
","language":"English","publisher":"SETAC","publisherLocation":"Pensacola, FL","doi":"10.1002/ieam.1731","usgsCitation":"Hooper, M.J., Glomb, S.J., Harper, D., Hoelzle, T.B., McIntosh, L.M., and Mulligan, D.R., 2016, Integrated risk and recovery monitoring of ecosystem restorations on contaminated sites: Integrated Environmental Assessment and Management, v. 12, no. 2, p. 284-295, https://doi.org/10.1002/ieam.1731.","productDescription":"12 p.","startPage":"284","endPage":"295","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062929","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":471274,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ieam.1731","text":"Publisher Index Page"},{"id":322008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-01","publicationStatus":"PW","scienceBaseUri":"57500767e4b0ee97d51bb663","contributors":{"authors":[{"text":"Hooper, Michael J. 0000-0002-4161-8961 mhooper@usgs.gov","orcid":"https://orcid.org/0000-0002-4161-8961","contributorId":3251,"corporation":false,"usgs":true,"family":"Hooper","given":"Michael","email":"mhooper@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":631238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glomb, Stephen J.","contributorId":169847,"corporation":false,"usgs":false,"family":"Glomb","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":25606,"text":"Office of Restoration and Damage Assessment, U.S. Department of the Interior, 1849 C Street NW, Washington, DC","active":true,"usgs":false}],"preferred":false,"id":631239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harper, David 0000-0001-7061-8461 david_harper@usgs.gov","orcid":"https://orcid.org/0000-0001-7061-8461","contributorId":169848,"corporation":false,"usgs":true,"family":"Harper","given":"David","email":"david_harper@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":631240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoelzle, Timothy B.","contributorId":169849,"corporation":false,"usgs":false,"family":"Hoelzle","given":"Timothy","email":"","middleInitial":"B.","affiliations":[{"id":25607,"text":"Great Ecology, 3459 Ringsby Court, Suite 421, Denver, CO","active":true,"usgs":false}],"preferred":false,"id":631241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McIntosh, Lisa M.","contributorId":169850,"corporation":false,"usgs":false,"family":"McIntosh","given":"Lisa","email":"","middleInitial":"M.","affiliations":[{"id":25608,"text":"Woodard & Curran, 980 Washington Street, Suite 325N, Dedham, MA","active":true,"usgs":false}],"preferred":false,"id":631242,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mulligan, David R.","contributorId":169851,"corporation":false,"usgs":false,"family":"Mulligan","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":25609,"text":"Centre for Mined Land Rehabilitation, Sustainable Minerals Institute, The University of Queensland, Brisbane, QLD 4072 Australia","active":true,"usgs":false}],"preferred":false,"id":631243,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192535,"text":"70192535 - 2016 - Ungulate reproductive parameters track satellite observations of plant phenology across latitude and climatological regimes","interactions":[],"lastModifiedDate":"2017-10-26T13:15:55","indexId":"70192535","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","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":"Ungulate reproductive parameters track satellite observations of plant phenology across latitude and climatological regimes","docAbstract":"The effect of climatically-driven plant phenology on mammalian reproduction is one key to predicting species-specific demographic responses to climate change. Large ungulates face their greatest energetic demands from the later stages of pregnancy through weaning, and so in seasonal environments parturition dates should match periods of high primary productivity. Interannual variation in weather influences the quality and timing of forage availability, which can influence neonatal survival. Here, we evaluated macro-scale patterns in reproductive performance of a widely distributed ungulate (mule deer, Odocoileus hemionus) across contrasting climatological regimes using satellite-derived indices of primary productivity and plant phenology over eight degrees of latitude (890 km) in the American Southwest. The dataset comprised > 180,000 animal observations taken from 54 populations over eight years (2004–2011). Regionally, both the start and peak of growing season (“Start” and “Peak”, respectively) are negatively and significantly correlated with latitude, an unusual pattern stemming from a change in the dominance of spring snowmelt in the north to the influence of the North American Monsoon in the south. Corresponding to the timing and variation in both the Start and Peak, mule deer reproduction was latest, lowest, and most variable at lower latitudes where plant phenology is timed to the onset of monsoonal moisture. Parturition dates closely tracked the growing season across space, lagging behind the Start and preceding the Peak by 27 and 23 days, respectively. Mean juvenile production increased, and variation decreased, with increasing latitude. Temporally, juvenile production was best predicted by primary productivity during summer, which encompassed late pregnancy, parturition, and early lactation. Our findings offer a parsimonious explanation of two key reproductive parameters in ungulate demography, timing of parturition and mean annual production, across latitude and changing climatological regimes. Practically, this demonstrates the potential for broad-scale modeling of couplings between climate, plant phenology, and animal populations using space-borne observations.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0148780","usgsCitation":"Stoner, D., Sexton, J.O., Nagol, J., Bernales, H.H., and Edwards, T., 2016, Ungulate reproductive parameters track satellite observations of plant phenology across latitude and climatological regimes: PLoS ONE, v. 11, no. 2, p. 1-19, https://doi.org/10.1371/journal.pone.0148780.","productDescription":"e0148780; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-061623","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471281,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0148780","text":"Publisher Index Page"},{"id":347470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, Utah","otherGeospatial":"Chihuahuan Desert, Colorado Plateau, Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.06005859375,\n 33.63291573870479\n ],\n [\n -108.61083984375,\n 33.63291573870479\n ],\n [\n -108.61083984375,\n 42.65012181368022\n ],\n [\n -114.06005859375,\n 42.65012181368022\n ],\n [\n -114.06005859375,\n 33.63291573870479\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-05","publicationStatus":"PW","scienceBaseUri":"5a07ea6ce4b09af898c8cc86","contributors":{"authors":[{"text":"Stoner, David","contributorId":191912,"corporation":false,"usgs":false,"family":"Stoner","given":"David","affiliations":[],"preferred":false,"id":716338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sexton, Joseph O.","contributorId":191918,"corporation":false,"usgs":false,"family":"Sexton","given":"Joseph","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":716339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nagol, Jyoteshwar","contributorId":198512,"corporation":false,"usgs":false,"family":"Nagol","given":"Jyoteshwar","affiliations":[],"preferred":false,"id":716340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bernales, Heather H.","contributorId":198513,"corporation":false,"usgs":false,"family":"Bernales","given":"Heather","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":716341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edwards, Thomas C. Jr. 0000-0002-0773-0909 tce@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-0909","contributorId":191916,"corporation":false,"usgs":true,"family":"Edwards","given":"Thomas C.","suffix":"Jr.","email":"tce@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716135,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70160077,"text":"70160077 - 2016 - Differences in impacts of Hurricane Sandy on freshwater swamps on the Delmarva Peninsula, Mid−Atlantic Coast, USA","interactions":[],"lastModifiedDate":"2016-07-17T23:22:49","indexId":"70160077","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Differences in impacts of Hurricane Sandy on freshwater swamps on the Delmarva Peninsula, Mid−Atlantic Coast, USA","docAbstract":"Hurricane wind and surge may have different influences on the subsequent composition of forests. During Hurricane Sandy, while damaging winds were highest near landfall in New Jersey, inundation occurred along the entire eastern seaboard from Georgia to Maine. In this study, a comparison of damage from salinity intrusion vs. wind/surge was recorded in swamps of the Delmarva Peninsula along the Pocomoke (MD) and Nanticoke (DE) Rivers, south of the most intense wind damage. Hickory Point Cypress Swamp (Hickory) was closest to the Chesapeake Bay and may have been subjected to a salinity surge as evidenced by elevated salinity levels at a gage upstream of this swamp (storm salinity = 13.1 ppt at Nassawango Creek, Snow Hill, Maryland). After Hurricane Sandy, 8% of the standing trees died at Hickory including Acer rubrum, Amelanchier laevis, Ilex spp., and Taxodium distichum. In Plot 2 of Hickory, 25% of the standing trees were dead, and soil salinity levels were the highest recorded in the study. The most important variables related to structural tree damage were soil salinity and proximity to the Atlantic coast as based on Stepwise Regression and NMDS procedures. Wind damage was mostly restricted to broken branches although tipped−up trees were found at Hickory, Whiton and Porter (species: Liquidamabar styraciflua, Pinus taeda, Populus deltoides, Quercus pagoda and Ilex spp.). These trees fell mostly in an east or east−southeast direction (88o−107o) in keeping with the wind direction of Hurricane Sandy on the Delmarva Peninsula. Coastal restoration and management can be informed by the specific differences in hurricane damage to vegetation by salt versus wind.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2015.11.035","usgsCitation":"Middleton, B.A., 2016, Differences in impacts of Hurricane Sandy on freshwater swamps on the Delmarva Peninsula, Mid−Atlantic Coast, USA: Ecological Engineering, v. 87, p. 62-70, https://doi.org/10.1016/j.ecoleng.2015.11.035.","productDescription":"9 p.","startPage":"62","endPage":"70","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059151","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471288,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2015.11.035","text":"Publisher Index Page"},{"id":312209,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Delmarva peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.6024169921875,\n 38.466492845389446\n ],\n [\n -75.7122802734375,\n 38.12591462924157\n ],\n [\n -75.19866943359375,\n 38.34165619279593\n ],\n [\n -75.58868408203125,\n 38.47294404791815\n ],\n [\n -75.6024169921875,\n 38.466492845389446\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"87","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56af3029e4b036ee44b83a49","contributors":{"authors":[{"text":"Middleton, Beth A. 0000-0002-1220-2326 middletonb@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":2029,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","email":"middletonb@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":581773,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70169964,"text":"70169964 - 2016 - Migratory corridors of adult female Kemp’s ridley turtles in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2016-07-17T23:39:52","indexId":"70169964","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Migratory corridors of adult female Kemp’s ridley turtles in the Gulf of Mexico","docAbstract":"For many marine species, locations of migratory pathways are not well defined. We used satellite telemetry and switching state-space modeling (SSM) to define the migratory corridor used by Kemp's ridley turtles (Lepidochelys kempii) in the Gulf of Mexico. The turtles were tagged after nesting at Padre Island National Seashore, Texas, USA from 1997 to 2014 (PAIS; n = 80); Rancho Nuevo, Tamaulipas, Mexico from 2010 to 2011 (RN; n = 14); Tecolutla, Veracruz, Mexico from 2012 to 2013 (VC; n = 13); and Gulf Shores, Alabama, USA during 2012 (GS; n = 1). The migratory corridor lies in nearshore Gulf of Mexico waters in the USA and Mexico with mean water depth of 26 m and a mean distance of 20 km from the nearest mainland coast. Migration from the nesting beach is a short phenomenon that occurs from late-May through August, with a peak in June. There was spatial similarity of post-nesting migratory pathways for different turtles over a 16 year period. Thus, our results indicate that these nearshore Gulf waters represent a critical migratory habitat for this species. However, there is a gap in our understanding of the migratory pathways used by this and other species to return from foraging grounds to nesting beaches. Therefore, our results highlight the need for tracking reproductive individuals from foraging grounds to nesting beaches. Continued tracking of adult females from PAIS, RN, and VC nesting beaches will allow further study of environmental and bathymetric components of migratory habitat and threats occurring within our defined corridor. Furthermore, the existence of this migratory corridor in nearshore waters of both the USA and Mexico demonstrates that international cooperation is necessary to protect essential migratory habitat for this imperiled species.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2015.12.014","usgsCitation":"Shaver, D.J., Hart, K.M., Fujisaki, I., Rubio, C., Sartain-Iverson, A.R., Pena, J., Gamez, D.G., Gonzales Diaz Miron, R.D., Burchfield, P.M., Martinez, H.J., and Ortiz, J., 2016, Migratory corridors of adult female Kemp’s ridley turtles in the Gulf of Mexico: Biological Conservation, v. 194, p. 158-167, https://doi.org/10.1016/j.biocon.2015.12.014.","productDescription":"10 p.","startPage":"158","endPage":"167","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067268","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471279,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2015.12.014","text":"Publisher Index Page"},{"id":319676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United 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Jaime","contributorId":168392,"corporation":false,"usgs":false,"family":"Pena","given":"Jaime","email":"","affiliations":[],"preferred":false,"id":625780,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gamez, Daniel Gomez","contributorId":32065,"corporation":false,"usgs":true,"family":"Gamez","given":"Daniel","email":"","middleInitial":"Gomez","affiliations":[],"preferred":false,"id":625781,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gonzales Diaz Miron, Raul de Jesus","contributorId":168393,"corporation":false,"usgs":false,"family":"Gonzales Diaz Miron","given":"Raul","email":"","middleInitial":"de Jesus","affiliations":[],"preferred":false,"id":625782,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Burchfield, Patrick M.","contributorId":47676,"corporation":false,"usgs":true,"family":"Burchfield","given":"Patrick","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":625783,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Martinez, Hector J.","contributorId":168394,"corporation":false,"usgs":false,"family":"Martinez","given":"Hector","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":625784,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ortiz, Jaime","contributorId":77447,"corporation":false,"usgs":true,"family":"Ortiz","given":"Jaime","email":"","affiliations":[],"preferred":false,"id":625785,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70187348,"text":"70187348 - 2016 - The road to Yucca Mountain—Evolution of nuclear waste disposal in the United States","interactions":[],"lastModifiedDate":"2017-05-01T13:21:15","indexId":"70187348","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1574,"text":"Environmental & Engineering Geoscience","printIssn":"1078-7275","active":true,"publicationSubtype":{"id":10}},"title":"The road to Yucca Mountain—Evolution of nuclear waste disposal in the United States","docAbstract":"The generation of electricity by nuclear power and the manufacturing of atomic weapons have created a large amount of spent nuclear fuel and high-level radioactive waste. There is a world-wide consensus that the best way to protect mankind and the environment is to dispose of this waste in a deep geologic repository. Initial efforts focused on salt as the best medium for disposal, but the heat generated by the radioactive waste led many earth scientists to examine other rock types. In 1976, the director of the U.S. Geological Survey (USGS) wrote to the U.S. Energy Research and Development Administration (ERDA), predecessor agency of the U.S. Department of Energy (DOE), suggesting that there were several favorable environments at the Nevada Test Site (NTS), and that the USGS already had extensive background information on the NTS. Later, in a series of communications and one publication, the USGS espoused the favorability of the thick unsaturated zone. After the passage of the Nuclear Waste Policy Act (1982), the DOE compiled a list of nine favorable sites and settled on three to be characterized. In 1987, as the costs of characterizing three sites ballooned, Congress amended the Nuclear Waste Policy Act directing the DOE to focus only on Yucca Mountain in Nevada, with the proviso that if anything unfavorable was discovered, work would stop immediately. The U.S. DOE, the U.S. DOE national laboratories, and the USGS developed more than 100 detailed plans to study various earth-science aspects of Yucca Mountain and the surrounding area, as well as materials studies and engineering projects needed for a mined geologic repository. The work, which cost more than 10 billion dollars and required hundreds of man-years of work, culminated in a license application submitted to the U.S. Nuclear Regulatory Commission (NRC) in 2008.
","language":"English","publisher":"Association of Environmental & Engineering Geologists","doi":"10.2113/gseegeosci.22.1.1","usgsCitation":"Stuckless, J.S., and Levich, R.A., 2016, The road to Yucca Mountain—Evolution of nuclear waste disposal in the United States: Environmental & Engineering Geoscience, v. 22, no. 1, p. 1-25, https://doi.org/10.2113/gseegeosci.22.1.1.","productDescription":"25 p.","startPage":"1","endPage":"25","ipdsId":"IP-058280","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":340682,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-03","publicationStatus":"PW","scienceBaseUri":"59084927e4b0fc4e448ffd50","contributors":{"authors":[{"text":"Stuckless, John S. 0000-0002-7536-0444 jstuckless@usgs.gov","orcid":"https://orcid.org/0000-0002-7536-0444","contributorId":4974,"corporation":false,"usgs":true,"family":"Stuckless","given":"John","email":"jstuckless@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":693574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Levich, Robert A.","contributorId":93374,"corporation":false,"usgs":true,"family":"Levich","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693775,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156877,"text":"70156877 - 2016 - Mapping extent and change in surface mines within the United States for 2001 to 2006","interactions":[],"lastModifiedDate":"2017-04-06T17:07:18","indexId":"70156877","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2597,"text":"Land Degradation and Development","active":true,"publicationSubtype":{"id":10}},"title":"Mapping extent and change in surface mines within the United States for 2001 to 2006","docAbstract":"A complete, spatially explicit dataset illustrating the 21st century mining footprint for the conterminous United States does not exist. To address this need, we developed a semi-automated procedure to map the country's mining footprint (30-m pixel) and establish a baseline to monitor changes in mine extent over time. The process uses mine seed points derived from the U.S. Energy Information Administration (EIA), U.S. Geological Survey (USGS) Mineral Resources Data System (MRDS), and USGS National Land Cover Dataset (NLCD) and recodes patches of barren land that meet a “distance to seed” requirement and a patch area requirement before mapping a pixel as mining. Seed points derived from EIA coal points, an edited MRDS point file, and 1992 NLCD mine points were used in three separate efforts using different distance and patch area parameters for each. The three products were then merged to create a 2001 map of moderate-to-large mines in the United States, which was subsequently manually edited to reduce omission and commission errors. This process was replicated using NLCD 2006 barren pixels as a base layer to create a 2006 mine map and a 2001–2006 mine change map focusing on areas with surface mine expansion. In 2001, 8,324 km2 of surface mines were mapped. The footprint increased to 9,181 km2 in 2006, representing a 10·3% increase over 5 years. These methods exhibit merit as a timely approach to generate wall-to-wall, spatially explicit maps representing the recent extent of a wide range of surface mining activities across the country.
","language":"English","publisher":"John Wiley and Sons","doi":"10.1002/ldr.2412","usgsCitation":"Soulard, C.E., Acevedo, W., Stehman, S.V., and Parker, O.P., 2016, Mapping extent and change in surface mines within the United States for 2001 to 2006: Land Degradation and Development, v. 27, no. 2, p. 248-257, https://doi.org/10.1002/ldr.2412.","productDescription":"10 p.","startPage":"248","endPage":"257","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054963","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":324655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-14","publicationStatus":"PW","scienceBaseUri":"5774f27ce4b07dd077c6a55d","contributors":{"authors":[{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":570924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Acevedo, William wacevedo@usgs.gov","contributorId":2689,"corporation":false,"usgs":true,"family":"Acevedo","given":"William","email":"wacevedo@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":570925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stehman, Stephen V.","contributorId":77283,"corporation":false,"usgs":true,"family":"Stehman","given":"Stephen","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":641373,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parker, Owen P.","contributorId":147263,"corporation":false,"usgs":false,"family":"Parker","given":"Owen","email":"","middleInitial":"P.","affiliations":[{"id":6785,"text":"USGS Contractor, Minerals & Environmental Resources Sci Ctr","active":true,"usgs":false}],"preferred":false,"id":570926,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191079,"text":"70191079 - 2016 - Mountain pine beetle host selection between lodgepole and ponderosa pines in the southern Rocky Mountains","interactions":[],"lastModifiedDate":"2017-09-25T11:36:23","indexId":"70191079","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1536,"text":"Environmental Entomology","active":true,"publicationSubtype":{"id":10}},"title":"Mountain pine beetle host selection between lodgepole and ponderosa pines in the southern Rocky Mountains","docAbstract":"Recent evidence of range expansion and host transition by mountain pine beetle ( Dendroctonus ponderosae Hopkins; MPB) has suggested that MPB may not primarily breed in their natal host, but will switch hosts to an alternate tree species. As MPB populations expanded in lodgepole pine forests in the southern Rocky Mountains, we investigated the potential for movement into adjacent ponderosa pine forests. We conducted field and laboratory experiments to evaluate four aspects of MPB population dynamics and host selection behavior in the two hosts: emergence timing, sex ratios, host choice, and reproductive success. We found that peak MPB emergence from both hosts occurred simultaneously between late July and early August, and the sex ratio of emerging beetles did not differ between hosts. In two direct tests of MPB host selection, we identified a strong preference by MPB for ponderosa versus lodgepole pine. At field sites, we captured naturally emerging beetles from both natal hosts in choice arenas containing logs of both species. In the laboratory, we offered sections of bark and phloem from both species to individual insects in bioassays. In both tests, insects infested ponderosa over lodgepole pine at a ratio of almost 2:1, regardless of natal host species. Reproductive success (offspring/female) was similar in colonized logs of both hosts. Overall, our findings suggest that MPB may exhibit equally high rates of infestation and fecundity in an alternate host under favorable conditions.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/ee/nvv167","usgsCitation":"West, D.R., Briggs, J.S., Jacobi, W.R., and Negron, J.F., 2016, Mountain pine beetle host selection between lodgepole and ponderosa pines in the southern Rocky Mountains: Environmental Entomology, v. 45, no. 1, p. 127-141, https://doi.org/10.1093/ee/nvv167.","productDescription":"15 p.","startPage":"127","endPage":"141","ipdsId":"IP-057981","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":346043,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Rocky Mountains","volume":"45","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-06","publicationStatus":"PW","scienceBaseUri":"59ca15b1e4b017cf314041d6","contributors":{"authors":[{"text":"West, Daniel R.","contributorId":196678,"corporation":false,"usgs":false,"family":"West","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":711093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Jenny S. 0000-0001-7454-6928 jsbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-7454-6928","contributorId":3087,"corporation":false,"usgs":true,"family":"Briggs","given":"Jenny","email":"jsbriggs@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":711092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacobi, William R.","contributorId":196679,"corporation":false,"usgs":false,"family":"Jacobi","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":711094,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Negron, Jose F.","contributorId":195663,"corporation":false,"usgs":false,"family":"Negron","given":"Jose","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":711095,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171090,"text":"70171090 - 2016 - Elevated Rocky Mountain elk numbers prevent positive effects of fire on quaking aspen (Populus tremuloides) recruitment","interactions":[],"lastModifiedDate":"2016-05-19T09:51:09","indexId":"70171090","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Elevated Rocky Mountain elk numbers prevent positive effects of fire on quaking aspen (Populus tremuloides) recruitment","docAbstract":"Quaking aspen (Populus tremuloides) is the most widespread tree species in North America and has supported a unique ecosystem for tens of thousands of years, yet is currently threatened by dramatic loss and possible local extinctions. While multiple factors such as climate change and fire suppression are thought to contribute to aspen’s decline, increased browsing by elk (Cervus elaphus), which have experienced dramatic population increases in the last ∼80 years, may severely inhibit aspen growth and regeneration. Fires are known to favor aspen recovery, but in the last several decades the spatial scale and intensity of wildfires has greatly increased, with poorly understood ramifications for aspen growth. Here, focusing on the 2000 Cerro Grande fire in central New Mexico – one of the earliest fires described as a “mega-fire” - we use three methods to examine the impact of elk browsing on aspen regeneration after a mega-fire. First, we use an exclosure experiment to show that aspen growing in the absence of elk were 3× taller than trees growing in the presence of elk. Further, aspen that were both protected from elk and experienced burning were 8.5× taller than unburned trees growing in the presence of elk, suggesting that the combination of release from herbivores and stimulation from fire creates the largest aspen growth rates. Second, using surveys at the landscape level, we found a correlation between elk browsing intensity and aspen height, such that where elk browsing was highest, aspen were shortest. This relationship between elk browsing intensity and aspen height was stronger in burned (r = −0.53) compared to unburned (r = −0.24) areas. Third, in conjunction with the landscape-level surveys, we identified possible natural refugia, microsites containing downed logs, shrubs etc. that may inhibit elk browsing by physically blocking aspen from elk or by impeding elk’s ability to move through the forest patch. We did not find any consistent patterns between refuge elements and aspen size or canopy cover suggesting that natural refugia are not aiding in aspen recruitment and that all young aspen were susceptible to browsing. In much of their normal range, aspen are not growing to large size classes, which threatens the future of this iconic species and calls into question the ability of ecosystems to recover from mega-fires. Our results highlight the importance of considering multiple interacting factors (i.e. fire and increased elk browsing) when considering aspen management and regeneration.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2015.11.020","usgsCitation":"Smith, D.S., Fettig, S.M., and Bowker, M.A., 2016, Elevated Rocky Mountain elk numbers prevent positive effects of fire on quaking aspen (Populus tremuloides) recruitment: Forest Ecology and Management, v. 362, p. 46-54, https://doi.org/10.1016/j.foreco.2015.11.020.","productDescription":"9 p.","startPage":"46","endPage":"54","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067527","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Cerro Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.42507553100586,\n 35.858309181565716\n ],\n [\n -106.42507553100586,\n 35.881122573005875\n ],\n [\n -106.38971328735352,\n 35.881122573005875\n ],\n [\n -106.38971328735352,\n 35.858309181565716\n ],\n [\n -106.42507553100586,\n 35.858309181565716\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"362","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"573ee3afe4b04a3a6a24acf8","contributors":{"authors":[{"text":"Smith, David Solance","contributorId":169498,"corporation":false,"usgs":false,"family":"Smith","given":"David","email":"","middleInitial":"Solance","affiliations":[{"id":25534,"text":"Dept. of Biological Sciences, Northern Arizona Univ, PO Box 15018, Flagstaff AZ 86011; current address: Denison Univ, Dept of Biology, PO Box 810, Granville, OH 43023. Email: smithd@denison.edu","active":true,"usgs":false}],"preferred":false,"id":629814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fettig, Stephen M.","contributorId":169499,"corporation":false,"usgs":false,"family":"Fettig","given":"Stephen","email":"","middleInitial":"M.","affiliations":[{"id":25535,"text":"U.S. National Park Service, Bandelier National Monument, 15 Entrance Rd., Los Alamos, NM 87544","active":true,"usgs":false}],"preferred":false,"id":629815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowker, Matthew A. mbowker@usgs.gov","contributorId":2875,"corporation":false,"usgs":true,"family":"Bowker","given":"Matthew","email":"mbowker@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":629813,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176956,"text":"70176956 - 2016 - A typology of time-scale mismatches and behavioral interventions to diagnose and solve conservation problems","interactions":[],"lastModifiedDate":"2017-04-27T10:23:50","indexId":"70176956","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"A typology of time-scale mismatches and behavioral interventions to diagnose and solve conservation problems","docAbstract":"Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers’ actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed.
","language":"English","publisher":"Wiley","doi":"10.1111/cobi.12632","usgsCitation":"Wilson, R.S., Hardisty, D.J., Epanchin-Niell, R.S., Runge, M.C., Cottingham, K.L., Urban, D., Maguire, L., Hastings, A., Mumby, P.J., and Peters, D., 2016, A typology of time-scale mismatches and behavioral interventions to diagnose and solve conservation problems: Conservation Biology, v. 30, no. 1, p. 42-49, https://doi.org/10.1111/cobi.12632.","productDescription":"8 p.","startPage":"42","endPage":"49","ipdsId":"IP-064693","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471289,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2429/58321","text":"External Repository"},{"id":329546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"1","noUsgsAuthors":false,"publicationDate":"2015-12-18","publicationStatus":"PW","scienceBaseUri":"58009d55e4b0824b2d183b8e","contributors":{"authors":[{"text":"Wilson, Robyn S.","contributorId":175362,"corporation":false,"usgs":false,"family":"Wilson","given":"Robyn","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":650868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hardisty, David J.","contributorId":175363,"corporation":false,"usgs":false,"family":"Hardisty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":650869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Epanchin-Niell, Rebecca S.","contributorId":175364,"corporation":false,"usgs":false,"family":"Epanchin-Niell","given":"Rebecca","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":650870,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":650871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cottingham, Kathryn L.","contributorId":26425,"corporation":false,"usgs":true,"family":"Cottingham","given":"Kathryn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":650872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Urban, Dean L.","contributorId":10674,"corporation":false,"usgs":true,"family":"Urban","given":"Dean L.","affiliations":[],"preferred":false,"id":650873,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maguire, Lynn A.","contributorId":46861,"corporation":false,"usgs":true,"family":"Maguire","given":"Lynn A.","affiliations":[],"preferred":false,"id":650874,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hastings, Alan","contributorId":175365,"corporation":false,"usgs":false,"family":"Hastings","given":"Alan","email":"","affiliations":[],"preferred":false,"id":650875,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mumby, Peter J.","contributorId":175366,"corporation":false,"usgs":false,"family":"Mumby","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":650876,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Peters, Debra P. C.","contributorId":36903,"corporation":false,"usgs":false,"family":"Peters","given":"Debra P. C.","affiliations":[{"id":25579,"text":"USDA-ARS Jornada Experimental Range, Las Cruces, NM 88003","active":true,"usgs":false}],"preferred":false,"id":650877,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70193142,"text":"70193142 - 2016 - A decision support tool for adaptive management of native prairie ecosystems","interactions":[],"lastModifiedDate":"2017-11-21T13:38:30","indexId":"70193142","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2013,"text":"Interfaces","active":true,"publicationSubtype":{"id":10}},"title":"A decision support tool for adaptive management of native prairie ecosystems","docAbstract":"The Native Prairie Adaptive Management initiative is a decision support framework that provides cooperators with management-action recommendations to help them conserve native species and suppress invasive species on prairie lands. We developed a Web-based decision support tool (DST) for the U.S. Fish and Wildlife Service and the U.S. Geological Survey initiative. The DST facilitates cross-organizational data sharing, performs analyses to improve conservation delivery, and requires no technical expertise to operate. Each year since 2012, the DST has used monitoring data to update ecological knowledge that it translates into situation-specific management-action recommendations (e.g., controlled burn or prescribed graze). The DST provides annual recommendations for more than 10,000 acres on 20 refuge complexes in four U.S. states. We describe how the DST promotes the long-term implementation of the program for which it was designed and may facilitate decision support and improve ecological outcomes of other conservation efforts.
","language":"English","publisher":"Informs","doi":"10.1287/inte.2015.0822","usgsCitation":"Hunt, V.M., Jacobi, S., Gannon, J., Zorn, J.E., Moore, C.T., and Lonsdorf, E.V., 2016, A decision support tool for adaptive management of native prairie ecosystems: Interfaces, v. 46, no. 4, p. 334-344, https://doi.org/10.1287/inte.2015.0822.","productDescription":"11 p.","startPage":"334","endPage":"344","ipdsId":"IP-053560","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":349210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fd7ae4b06e28e9c24ef8","contributors":{"authors":[{"text":"Hunt, Victoria M.","contributorId":200688,"corporation":false,"usgs":false,"family":"Hunt","given":"Victoria","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":723059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobi, Sarah","contributorId":149496,"corporation":false,"usgs":false,"family":"Jacobi","given":"Sarah","email":"","affiliations":[{"id":17752,"text":"Chicago Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":723060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gannon, Jill J.","contributorId":12722,"corporation":false,"usgs":true,"family":"Gannon","given":"Jill J.","affiliations":[],"preferred":false,"id":723061,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zorn, Jennifer E.","contributorId":200689,"corporation":false,"usgs":false,"family":"Zorn","given":"Jennifer","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":723062,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":718090,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lonsdorf, Eric V.","contributorId":149495,"corporation":false,"usgs":false,"family":"Lonsdorf","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":17752,"text":"Chicago Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":723063,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70177901,"text":"70177901 - 2016 - An assessment of the cultivated cropland class of NLCD 2006 using a multi-source and multi-criteria approach","interactions":[],"lastModifiedDate":"2018-03-09T09:30:18","indexId":"70177901","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"An assessment of the cultivated cropland class of NLCD 2006 using a multi-source and multi-criteria approach","docAbstract":"We developed a method that analyzes the quality of the cultivated cropland class mapped in the USA National Land Cover Database (NLCD) 2006. The method integrates multiple geospatial datasets and a Multi Index Integrated Change Analysis (MIICA) change detection method that captures spectral changes to identify the spatial distribution and magnitude of potential commission and omission errors for the cultivated cropland class in NLCD 2006. The majority of the commission and omission errors in NLCD 2006 are in areas where cultivated cropland is not the most dominant land cover type. The errors are primarily attributed to the less accurate training dataset derived from the National Agricultural Statistics Service Cropland Data Layer dataset. In contrast, error rates are low in areas where cultivated cropland is the dominant land cover. Agreement between model-identified commission errors and independently interpreted reference data was high (79%). Agreement was low (40%) for omission error comparison. The majority of the commission errors in the NLCD 2006 cultivated crops were confused with low-intensity developed classes, while the majority of omission errors were from herbaceous and shrub classes. Some errors were caused by inaccurate land cover change from misclassification in NLCD 2001 and the subsequent land cover post-classification process.
","language":"English","publisher":"MDPI","doi":"10.3390/rs8020101","usgsCitation":"Danielson, P., Yang, L., Jin, S., Homer, C.G., and Napton, D., 2016, An assessment of the cultivated cropland class of NLCD 2006 using a multi-source and multi-criteria approach: Remote Sensing, v. 8, no. 2, Article 101; 16 p., https://doi.org/10.3390/rs8020101.","productDescription":"Article 101; 16 p.","ipdsId":"IP-072277","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":471276,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs8020101","text":"Publisher Index Page"},{"id":330407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-28","publicationStatus":"PW","scienceBaseUri":"5811c0f3e4b0f497e79a5a81","contributors":{"authors":[{"text":"Danielson, Patrick 0000-0002-2990-2783 pdanielson@usgs.gov","orcid":"https://orcid.org/0000-0002-2990-2783","contributorId":3551,"corporation":false,"usgs":true,"family":"Danielson","given":"Patrick","email":"pdanielson@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":652087,"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":652088,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":652089,"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":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":652090,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Napton, Darrell","contributorId":176288,"corporation":false,"usgs":false,"family":"Napton","given":"Darrell","affiliations":[],"preferred":false,"id":652091,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70178113,"text":"70178113 - 2016 - Effective stress, friction and deep crustal faulting","interactions":[],"lastModifiedDate":"2019-07-17T16:23:27","indexId":"70178113","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Effective stress, friction and deep crustal faulting","docAbstract":"Studies of crustal faulting and rock friction invariably assume the effective normal stress that determines fault shear resistance during frictional sliding is the applied normal stress minus the pore pressure. Here we propose an expression for the effective stress coefficient αf at temperatures and stresses near the brittle-ductile transition (BDT) that depends on the percentage of solid-solid contact area across the fault. αf varies with depth and is only near 1 when the yield strength of asperity contacts greatly exceeds the applied normal stress. For a vertical strike-slip quartz fault zone at hydrostatic pore pressure and assuming 1 mm and 1 km shear zone widths for friction and ductile shear, respectively, the BDT is at ~13 km. αf near 1 is restricted to depths where the shear zone is narrow. Below the BDT αf = 0 is due to a dramatically decreased strain rate. Under these circumstances friction cannot be reactivated below the BDT by increasing the pore pressure alone and requires localization. If pore pressure increases and the fault localizes back to 1 mm, then brittle behavior can occur to a depth of around 35 km. The interdependencies among effective stress, contact-scale strain rate, and pore pressure allow estimates of the conditions necessary for deep low-frequency seismicity seen on the San Andreas near Parkfield and in some subduction zones. Among the implications are that shear in the region separating shallow earthquakes and deep low-frequency seismicity is distributed and that the deeper zone involves both elevated pore fluid pressure and localization.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB012115","usgsCitation":"Beeler, N., Hirth, G., Thomas, A.M., and Burgmann, R., 2016, Effective stress, friction and deep crustal faulting: Journal of Geophysical Research B: Solid Earth, v. 121, no. 2, p. 1040-1059, https://doi.org/10.1002/2015JB012115.","productDescription":"20 p.","startPage":"1040","endPage":"1059","ipdsId":"IP-060703","costCenters":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471286,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012115","text":"Publisher Index Page"},{"id":330688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-04","publicationStatus":"PW","scienceBaseUri":"581c4cc4e4b09688d6e90fc9","contributors":{"authors":[{"text":"Beeler, N.M. 0000-0002-3397-8481","orcid":"https://orcid.org/0000-0002-3397-8481","contributorId":68894,"corporation":false,"usgs":true,"family":"Beeler","given":"N.M.","affiliations":[],"preferred":false,"id":652886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hirth, Greg","contributorId":176585,"corporation":false,"usgs":false,"family":"Hirth","given":"Greg","email":"","affiliations":[],"preferred":false,"id":652887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Amanda M.","contributorId":36448,"corporation":false,"usgs":true,"family":"Thomas","given":"Amanda","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":652888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burgmann, Roland","contributorId":95128,"corporation":false,"usgs":true,"family":"Burgmann","given":"Roland","affiliations":[],"preferred":false,"id":652889,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70177144,"text":"70177144 - 2016 - Estimating golden-cheeked warbler immigration: Implications for the spatial scale of conservation","interactions":[],"lastModifiedDate":"2018-03-28T11:05:23","indexId":"70177144","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":774,"text":"Animal Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Estimating golden-cheeked warbler immigration: Implications for the spatial scale of conservation","docAbstract":"Understanding the factors that drive population dynamics is fundamental to species conservation and management. Since the golden-cheeked warbler Setophaga chrysoparia was first listed as endangered, much effort has taken place to monitor warbler abundance, occupancy, reproduction and survival. Yet, despite being directly related to local population dynamics, movement rates have not been estimated for the species. We used an integrated population model to investigate the relationship between immigration rate, fledging rate, survival probabilities and population growth rate for warblers in central Texas, USA. Furthermore, using a deterministic projection model, we examined the response required by vital rates to maintain a viable population across varying levels of immigration. Warbler abundance fluctuated with an overall positive trend across years. In the absence of immigration, the abundance would have decreased. However, the population could remain viable without immigration if both adult and juvenile survival increased by almost half or if juvenile survival more than doubled. We also investigated the response required by fledging rates across a range of immigration in order to maintain a viable population. Overall, we found that immigration was required to maintain warbler target populations, indicating that warbler conservation and management programs need to be implemented at larger spatial scales than current efforts to be effective. This study also demonstrates that by using limited data within integrated population models, biologists are able to monitor multiple key demographic parameters simultaneously to gauge the efficacy of strategies designed to maximize warbler viability in a changing landscape.
","language":"English","publisher":"Wiley","doi":"10.1111/acv.12217","usgsCitation":"Duarte, A., Weckerly, F., Schaub, M., and Hatfield, J., 2016, Estimating golden-cheeked warbler immigration: Implications for the spatial scale of conservation: Animal Conservation, v. 19, no. 1, p. 65-74, https://doi.org/10.1111/acv.12217.","productDescription":"10 p.","startPage":"65","endPage":"74","ipdsId":"IP-064743","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":329754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"1","noUsgsAuthors":false,"publicationDate":"2015-06-17","publicationStatus":"PW","scienceBaseUri":"58088688e4b0f497e78e24d1","contributors":{"authors":[{"text":"Duarte, A.","contributorId":46405,"corporation":false,"usgs":true,"family":"Duarte","given":"A.","email":"","affiliations":[],"preferred":false,"id":651413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weckerly, F.W.","contributorId":77877,"corporation":false,"usgs":true,"family":"Weckerly","given":"F.W.","email":"","affiliations":[],"preferred":false,"id":651414,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaub, M.","contributorId":70897,"corporation":false,"usgs":true,"family":"Schaub","given":"M.","email":"","affiliations":[],"preferred":false,"id":651415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatfield, Jeffrey S. jhatfield@usgs.gov","contributorId":151,"corporation":false,"usgs":true,"family":"Hatfield","given":"Jeffrey S.","email":"jhatfield@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":651416,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}