To address a paucity of Common Era data in the Gulf of Mexico, we reconstructed ~ 1.1 m of relative sea-level (RSL) rise over the past ~ 2000 years at Little Manatee River (Gulf Coast of Florida, USA). We applied a regional-scale foraminiferal transfer function to fossil assemblages preserved in a core of salt-marsh peat and organic silt that was dated using radiocarbon and recognition of pollution, 137Cs and pollen chronohorizons. Our proxy reconstruction was combined with tide-gauge data from four nearby sites spanning 1913–2014 CE. Application of an Errors-in-Variables Integrated Gaussian Process (EIV-IGP) model to the combined proxy and instrumental dataset demonstrates that RSL fell from ~ 350 to 100 BCE, before rising continuously to present. This initial RSL fall was likely the result of local-scale processes (e.g., silting up of a tidal flat or shallow sub-tidal shoal) as salt-marsh development at the site began. Since ~ 0 CE, we consider the reconstruction to be representative of regional-scale RSL trends. We removed a linear rate of 0.3 mm/yr from the RSL record using the EIV-IGP model to estimate climate-driven sea-level trends and to facilitate comparison among sites. This analysis demonstrates that since ~ 0 CE sea level did not deviate significantly from zero until accelerating continuously from ~ 1500 CE to present. Sea level was rising at 1.33 mm/yr in 1900 CE and accelerated until 2014 CE when a rate of 2.02 mm/yr was attained, which is the fastest, century-scale trend in the ~ 2000-year record. Comparison to existing reconstructions from the Gulf coast of Louisiana and the Atlantic coast of northern Florida reveal similar sea-level histories at all three sites. We explored the influence of compaction and fluvial processes on our reconstruction and concluded that compaction was likely insignificant. Fluvial processes were also likely insignificant, but further proxy evidence is needed to fully test this hypothesis. Our results indicate that no significant Common Era sea-level changes took place on the Gulf and southeastern Atlantic U.S. coasts until the onset of modern sea-level rise in the late 19th century.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2017.07.001","usgsCitation":"Gerlach, M.J., Engelhart, S.E., Kemp, A.C., Moyer, R.P., Smoak, J.M., Bernhardt, C.E., and Cahill, N., 2017, Reconstructing Common Era relative sea-level change on the Gulf Coast of Florida: Marine Geology, v. 390, p. 254-269, https://doi.org/10.1016/j.margeo.2017.07.001.","productDescription":"16 p.","startPage":"254","endPage":"269","ipdsId":"IP-082795","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":461432,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.margeo.2017.07.001","text":"Publisher Index Page"},{"id":348617,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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C.","contributorId":192892,"corporation":false,"usgs":false,"family":"Kemp","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":717816,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moyer, Ryan P.","contributorId":198993,"corporation":false,"usgs":false,"family":"Moyer","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":13560,"text":"Florida Fish and Wildlife Conservation Commission, Eustis, FL","active":true,"usgs":false}],"preferred":false,"id":717817,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smoak, Joseph M.","contributorId":195503,"corporation":false,"usgs":false,"family":"Smoak","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":17733,"text":"University of South Florida, St. Petersburg, FL","active":true,"usgs":false}],"preferred":false,"id":717818,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bernhardt, Christopher E. 0000-0003-0082-4731 cbernhardt@usgs.gov","orcid":"https://orcid.org/0000-0003-0082-4731","contributorId":2131,"corporation":false,"usgs":true,"family":"Bernhardt","given":"Christopher","email":"cbernhardt@usgs.gov","middleInitial":"E.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":717813,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cahill, Niamh","contributorId":150754,"corporation":false,"usgs":false,"family":"Cahill","given":"Niamh","email":"","affiliations":[{"id":18091,"text":"University College Dublin","active":true,"usgs":false},{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":717819,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70189286,"text":"ofr20171089 - 2017 - Hierarchical population monitoring of greater sage-grouse (Centrocercus urophasianus) in Nevada and California—Identifying populations for management at the appropriate spatial scale","interactions":[],"lastModifiedDate":"2017-12-27T14:59:13","indexId":"ofr20171089","displayToPublicDate":"2017-08-10T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1089","title":"Hierarchical population monitoring of greater sage-grouse (Centrocercus urophasianus) in Nevada and California—Identifying populations for management at the appropriate spatial scale","docAbstract":"Population ecologists have long recognized the importance of ecological scale in understanding processes that guide observed demographic patterns for wildlife species. However, directly incorporating spatial and temporal scale into monitoring strategies that detect whether trajectories are driven by local or regional factors is challenging and rarely implemented. Identifying the appropriate scale is critical to the development of management actions that can attenuate or reverse population declines. We describe a novel example of a monitoring framework for estimating annual rates of population change for greater sage-grouse (Centrocercus urophasianus) within a hierarchical and spatially nested structure. Specifically, we conducted Bayesian analyses on a 17-year dataset (2000–2016) of lek counts in Nevada and northeastern California to estimate annual rates of population change, and compared trends across nested spatial scales. We identified leks and larger scale populations in immediate need of management, based on the occurrence of two criteria: (1) crossing of a destabilizing threshold designed to identify significant rates of population decline at a particular nested scale; and (2) crossing of decoupling thresholds designed to identify rates of population decline at smaller scales that decouple from rates of population change at a larger spatial scale. This approach establishes how declines affected by local disturbances can be separated from those operating at larger scales (for example, broad-scale wildfire and region-wide drought). Given the threshold output from our analysis, this adaptive management framework can be implemented readily and annually to facilitate responsive and effective actions for sage-grouse populations in the Great Basin. The rules of the framework can also be modified to identify populations responding positively to management action or demonstrating strong resilience to disturbance. Similar hierarchical approaches might be beneficial for other species occupying landscapes with heterogeneous disturbance and climatic regimes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171089","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Coates, P.S., Prochazka, B.G., Ricca, M.A., Wann, G.T., Aldridge, C.L., Hanser, S.E., Doherty, K.E., O’Donnell, M.S., Edmunds, D.R., and, Espinosa, S.P., 2017, Hierarchical population monitoring of greater sage-grouse (Centrocercus urophasianus) in Nevada and California—Identifying populations for management at the appropriate spatial scale: U.S. Geological Survey Open-File Report 2017-1089, 49 p., https://doi.org/10.3133/ofr20171089.","productDescription":"viii, 49 p.","onlineOnly":"Y","ipdsId":"IP-087898","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":344634,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1089/ofr20171089.pdf","text":"Report","size":"15.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1089"},{"id":344633,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1089/coverthb.jpg"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.9,\n 34\n ],\n [\n -113,\n 34\n ],\n [\n -113,\n 42.25\n ],\n [\n -121.9,\n 42.25\n ],\n [\n -121.9,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The stochastic empirical loading and dilution model (SELDM) was used to demonstrate methods for estimating risks for water-quality exceedances of event-mean concentrations (EMCs) of total-copper. Monte Carlo methods were used to simulate stormflow, total-hardness, suspended-sediment, and total-copper EMCs as stochastic variables. These simulations were done for the Charles River Basin upstream of Interstate 495 in Bellingham, Massachusetts. The hydrology and water quality of this site were simulated with SELDM by using data from nearby, hydrologically similar sites. Three simulations were done to assess the potential effects of the highway on receiving-water quality with and without highway-runoff treatment by a structural best-management practice (BMP). In the low-development scenario, total copper in the receiving stream was simulated by using a sediment transport curve, sediment chemistry, and sediment-water partition coefficients. In this scenario, neither the highway runoff nor the BMP effluent caused concentration exceedances in the receiving stream that exceed the once in three-year threshold (about 0.54 percent). In the second scenario, without the highway, runoff from the large urban areas in the basin caused exceedances in the receiving stream in 2.24 percent of runoff events. In the third scenario, which included the effects of the urban runoff, neither the highway runoff nor the BMP effluent increased the percentage of exceedances in the receiving stream. Comparison of the simulated geometric mean EMCs with data collected at a downstream monitoring site indicates that these simulated values are within the 95-percent confidence interval of the geometric mean of the measured EMCs.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"World environmental and water resources congress 2017: Watershed management, irrigation and drainage, and water resources planning and management","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"World Environmental and Water Resources Congress 2017","conferenceDate":"May 21-25, 2017","conferenceLocation":"Sacremento, CA","language":"English","publisher":"American Society of Civil Engineers","publisherLocation":"Reston, VA","doi":"10.1061/9780784480601.028","isbn":"978-0-7844-8060-1","usgsCitation":"Granato, G.E., and Jones, S.C., 2017, Estimating risks for water-quality exceedances of total-copper from highway and urban runoff under predevelopment and current conditions with the Stochastic Empirical Loading and Dilution Model (SELDM), in World environmental and water resources congress 2017: Watershed management, irrigation and drainage, and water resources planning and management, Sacremento, CA, May 21-25, 2017, p. 313-327, https://doi.org/10.1061/9780784480601.028.","productDescription":"15 p.","startPage":"313","endPage":"327","ipdsId":"IP-074316","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":344706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-18","publicationStatus":"PW","scienceBaseUri":"598c1f3ee4b09fa1cb0ffef3","contributors":{"editors":[{"text":"Dunn, Christopher N.","contributorId":195552,"corporation":false,"usgs":false,"family":"Dunn","given":"Christopher","email":"","middleInitial":"N.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":707424,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Van Weele, Brian","contributorId":176821,"corporation":false,"usgs":false,"family":"Van Weele","given":"Brian","email":"","affiliations":[],"preferred":false,"id":707425,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":147346,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory","email":"ggranato@usgs.gov","middleInitial":"E.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":707417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Susan C. 0000-0002-5891-5209","orcid":"https://orcid.org/0000-0002-5891-5209","contributorId":64716,"corporation":false,"usgs":false,"family":"Jones","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":34302,"text":"Federal Highway Administration (United States)","active":true,"usgs":false}],"preferred":false,"id":707418,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190051,"text":"70190051 - 2017 - Hierarchical, quantitative biogeographic provinces for all North American turtles and their contribution to the biogeography of turtles and the continent","interactions":[],"lastModifiedDate":"2017-08-07T16:53:26","indexId":"70190051","displayToPublicDate":"2017-08-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1896,"text":"Herpetological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical, quantitative biogeographic provinces for all North American turtles and their contribution to the biogeography of turtles and the continent","docAbstract":"Our study represents the first attempt to describe biogeographic provinces for North American (México, United States, and Canada) turtles. We analyzed three nested data sets separately: (1) all turtles, (2) freshwater turtles, and (3) aquatic turtles. We georeferenced North American turtle distributions, then we created presence–absence matrices for each of the three data sets. We used watershed unit as biogeographic units. We conducted an unweighted pair-group method with arithmetic mean clustering analysis on each Jaccard index distance matrix from our watershed species matrices to delineate biogeographic provinces. Provinces were then tested for significant differences in species compositions in a global model with the use of a one-way analysis of similarity. We conducted a best subset of environmental variables with maximum (rank) correlation with community dissimilarities that determined the best model of abiotic variables explaining province delineation (i.e., climate, topography, and stream channel). To identify which species contributed the most to province delineations, we conducted an indicator species analysis and a similarity-percentage analysis. There were 16 all-turtle provinces, 15 freshwater provinces, and 13 aquatic provinces. Species compositions delineating the provinces were explained by abiotic variables, including mean annual precipitation, mean precipitation seasonality, and diversity of streams. Province delineations correspond closely with geographical boundaries, many of which have Pleistocene origins. For example, rivers with a history of carrying glacial runoff (e.g., Arkansas, Mississippi) sometimes dissect upland provinces, especially for aquatic and semiaquatic turtles. Compared with freshwater fishes, turtles show greater sensitivity to decreased temperature with restriction of most taxa south of the last permafrost maximum. Turtles also exhibit higher sensitivity to climatic, geomorphic, and tectonic instability, with richness and endemism concentrated along the more stable Gulf of México and Atlantic (south of the last permafrost maximum) coasts. Although distribution data indicate two aquatic turtles are most cold tolerant (i.e., Chrysemys picta, Chelydra serpentina), aquatic turtles overall show the most restriction to warmer, wetter climates. Sequential addition of semiaquatic and terrestrial turtles into analyses shows, as expected, that these taxa flesh out turtle faunas in climatically harsh (e.g., grasslands) or remote (e.g., California, Sonoran Desert) regions. The turtle assemblages of southwestern versus southeastern North America are distinct. But there is a transition zone across the semiarid plains of the Texas Gulf Coast, High Plains, and Chihuahuan Desert, including a strong boundary congruent with the Cochise Filter-Barrier. This is not a simple subdivision of Neotropical versus Nearctic taxa, as some lineages from both realms span the transition zone.
","language":"English","publisher":"The Herpetologists’ League","doi":"10.1655/HERPMONOGRAPHS-D-16-00013","usgsCitation":"Ennen, J.R., Matamoros, W.A., Agha, M., Lovich, J.E., Sweat, S.C., and Hoagstrom, C.W., 2017, Hierarchical, quantitative biogeographic provinces for all North American turtles and their contribution to the biogeography of turtles and the continent: Herpetological Monographs, v. 31, no. 1, p. 114-140, https://doi.org/10.1655/HERPMONOGRAPHS-D-16-00013.","productDescription":"27 p.","startPage":"114","endPage":"140","ipdsId":"IP-080651","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":344620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","volume":"31","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59897c0ee4b09fa1cb0c2bf1","contributors":{"authors":[{"text":"Ennen, Joshua R.","contributorId":83858,"corporation":false,"usgs":true,"family":"Ennen","given":"Joshua","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":707330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matamoros, Wilfredo A.","contributorId":172518,"corporation":false,"usgs":false,"family":"Matamoros","given":"Wilfredo","email":"","middleInitial":"A.","affiliations":[{"id":27060,"text":"Facultad de Ciencias Biologicas, Universidad de Cencias y Artes de Chiapas, Museo de Zoologia, Tuxtla Gutiérrez, Chiapas, México Apartado Postal 29000, México","active":true,"usgs":false}],"preferred":false,"id":707332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Agha, Mickey","contributorId":22235,"corporation":false,"usgs":false,"family":"Agha","given":"Mickey","email":"","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false},{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":707333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":707329,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sweat, Sarah C.","contributorId":195519,"corporation":false,"usgs":false,"family":"Sweat","given":"Sarah","email":"","middleInitial":"C.","affiliations":[{"id":13216,"text":"Tennessee Aquarium Conservation Institute","active":true,"usgs":false}],"preferred":false,"id":707331,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hoagstrom, Christopher W.","contributorId":195520,"corporation":false,"usgs":false,"family":"Hoagstrom","given":"Christopher","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":707334,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70190048,"text":"70190048 - 2017 - Investigation of late Pleistocene and Holocene activity in the San Gregorio fault zone on the continental slope north of Monterey Canyon, offshore central California","interactions":[],"lastModifiedDate":"2017-08-07T17:04:12","indexId":"70190048","displayToPublicDate":"2017-08-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Investigation of late Pleistocene and Holocene activity in the San Gregorio fault zone on the continental slope north of Monterey Canyon, offshore central California","docAbstract":"We provide an extensive high‐resolution geophysical, sediment core, and radiocarbon dataset to address late Pleistocene and Holocene fault activity of the San Gregorio fault zone (SGFZ), offshore central California. The SGFZ occurs primarily offshore in the San Andreas fault system and has been accommodating dextral strike‐slip motion between the Pacific and North American plates since the mid‐Miocene. Our study focuses on the SGFZ where it has been mapped through the continental slope north of Monterey Canyon. From 2009 to 2015, the Monterey Bay Aquarium Research Institute collected high‐resolution multibeam bathymetry and chirp sub‐bottom profiles using an autonomous underwater vehicle (AUV). Targeted samples were collected using a remotely operated vehicle (ROV) to provide radiocarbon age constraints. We integrate the high‐resolution geophysical data with radiocarbon dates to reveal Pleistocene seismic horizons vertically offset less than 5 m on nearly vertical faults. These faults are buried by continuous reflections deposited after ∼17.5 ka and likely following erosion during the last sea‐level lowstand ∼21 ka, bracketing the age of faulting to ∼32–21 ka. Clearly faulted horizons are only detected in a small area where mass wasting exhumed older strata to within ∼25 m of the seafloor. The lack of clearly faulted Holocene deposits and possible highly distributed faulting in the study area are consistent with previous interpretations that late Pleistocene and Holocene activity along the SGFZ may decrease to the south. This study illustrates the complexity of the SGFZ, offshore central California, and demonstrates the utility of very high‐resolution data from combined AUV (geophysical)–ROV (seabed sampling) surveys in offshore studies of fault activity.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160261","usgsCitation":"Maier, K., Paull, C.K., Brothers, D.S., Caress, D.W., McGann, M., Lundsten, E.M., Anderson, K., and Gwiazda, R., 2017, Investigation of late Pleistocene and Holocene activity in the San Gregorio fault zone on the continental slope north of Monterey Canyon, offshore central California: Bulletin of the Seismological Society of America, v. 107, no. 3, p. 1094-1106, https://doi.org/10.1785/0120160261.","productDescription":"13 p.","startPage":"1094","endPage":"1106","ipdsId":"IP-066081","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":344622,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-11","publicationStatus":"PW","scienceBaseUri":"59897c12e4b09fa1cb0c2bf6","contributors":{"authors":[{"text":"Maier, Katherine L.","contributorId":91411,"corporation":false,"usgs":true,"family":"Maier","given":"Katherine L.","affiliations":[],"preferred":false,"id":707315,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paull, Charles K. 0000-0001-5940-3443","orcid":"https://orcid.org/0000-0001-5940-3443","contributorId":55825,"corporation":false,"usgs":false,"family":"Paull","given":"Charles","email":"","middleInitial":"K.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":true,"id":707316,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":707317,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caress, David W.","contributorId":147392,"corporation":false,"usgs":false,"family":"Caress","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":16837,"text":"MBARI","active":true,"usgs":false}],"preferred":false,"id":707318,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGann, Mary 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":169540,"corporation":false,"usgs":true,"family":"McGann","given":"Mary","email":"mmcgann@usgs.gov","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":707319,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lundsten, Eve M.","contributorId":147191,"corporation":false,"usgs":false,"family":"Lundsten","given":"Eve","email":"","middleInitial":"M.","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":707320,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Anderson, Krystle","contributorId":147192,"corporation":false,"usgs":false,"family":"Anderson","given":"Krystle","email":"","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":707321,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gwiazda, Roberto","contributorId":147193,"corporation":false,"usgs":false,"family":"Gwiazda","given":"Roberto","email":"","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":707322,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70190020,"text":"70190020 - 2017 - Effects of extreme floods on macroinvertebrate assemblages in tributaries to the Mohawk River, New York, USA","interactions":[],"lastModifiedDate":"2017-09-05T12:31:59","indexId":"70190020","displayToPublicDate":"2017-08-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Effects of extreme floods on macroinvertebrate assemblages in tributaries to the Mohawk River, New York, USA","docAbstract":"Climate change is forecast to bring more frequent and intense precipitation to New York which has motivated research into the effects of floods on stream ecosystems. Macroinvertebrate assemblages were sampled at 13 sites in the Mohawk River basin during August 2011, and again in October 2011, following historic floods caused by remnants of Hurricane Irene and Tropical Storm Lee. The annual exceedance probabilities of floods at regional flow-monitoring sites ranged from 0.5 to 0.001. Data from the first 2 surveys, and from additional surveys done during July and October 2014, were assessed to characterize the severity of flood impacts, effect of seasonality, and recovery. Indices of total taxa richness; Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness; Hilsenhoff's biotic index; per cent model affinity; and nutrient biotic index-phosphorus were combined to calculate New York State Biological Assessment Profile scores. Analysis of variance tests were used to determine if the Biological Assessment Profile, its component metrics, relative abundance, and diversity differed significantly (p ≤ .05) among the four surveys. Only total taxa richness and Shannon–Wiener diversity increased significantly, and abundance decreased significantly, following the floods. No metrics differed significantly between the July and August 2014 surveys which indicates that the differences denoted between the August and October 2011 surveys were caused by the floods. Changes in taxa richness, EPT richness, and diversity were significantly correlated with flood annual exceedance probabilities. This study increased our understanding of the resistance and resilience of benthic macroinvertebrate communities by showing that their assemblages were relatively impervious to extreme floods across the region.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3158","usgsCitation":"Calderon, M.R., Baldigo, B.P., Smith, A., and Endreny, T.A., 2017, Effects of extreme floods on macroinvertebrate assemblages in tributaries to the Mohawk River, New York, USA: River Research and Applications, v. 33, no. 7, p. 1060-1070, https://doi.org/10.1002/rra.3158.","productDescription":"11 p.","startPage":"1060","endPage":"1070","ipdsId":"IP-082245","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":469620,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/rra.3158","text":"External Repository"},{"id":344584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Mohawk River","volume":"33","issue":"7","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-12","publicationStatus":"PW","scienceBaseUri":"59858808e4b05ba66e9ea29c","contributors":{"authors":[{"text":"Calderon, Mirian R.","contributorId":195488,"corporation":false,"usgs":false,"family":"Calderon","given":"Mirian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":707211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":707210,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Alexander J.","contributorId":140345,"corporation":false,"usgs":false,"family":"Smith","given":"Alexander J.","affiliations":[{"id":13464,"text":"Environmental Analyst, NY State Dept of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":707212,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Endreny, Theodore A.","contributorId":195489,"corporation":false,"usgs":false,"family":"Endreny","given":"Theodore","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":707213,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190024,"text":"70190024 - 2017 - Using multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software","interactions":[],"lastModifiedDate":"2017-08-04T10:07:58","indexId":"70190024","displayToPublicDate":"2017-08-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2027,"text":"International Journal of Applied Earth Observation and Geoinformation","active":true,"publicationSubtype":{"id":10}},"title":"Using multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software","docAbstract":"Among the most pressing concerns of land managers in post-wildfire landscapes are the establishment and spread of invasive species. Land managers need accurate maps of invasive species cover for targeted management post-disturbance that are easily transferable across space and time. In this study, we sought to develop an iterative, replicable methodology based on limited invasive species occurrence data, freely available remotely sensed data, and open source software to predict the distribution of Bromus tectorum (cheatgrass) in a post-wildfire landscape. We developed four species distribution models using eight spectral indices derived from five months of Landsat 8 Operational Land Imager (OLI) data in 2014. These months corresponded to both cheatgrass growing period and time of field data collection in the study area. The four models were improved using an iterative approach in which a threshold for cover was established, and all models had high sensitivity values when tested on an independent dataset. We also quantified the area at highest risk for invasion in future seasons given 2014 distribution, topographic covariates, and seed dispersal limitations. These models demonstrate the effectiveness of using derived multi-date spectral indices as proxies for species occurrence on the landscape, the importance of selecting thresholds for invasive species cover to evaluate ecological risk in species distribution models, and the applicability of Landsat 8 OLI and the Software for Assisted Habitat Modeling for targeted invasive species management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jag.2017.03.009","usgsCitation":"West, A.M., Evangelista, P.H., Jarnevich, C.S., Kumar, S., Swallow, A., Luizza, M., and Chignell, S., 2017, Using multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software: International Journal of Applied Earth Observation and Geoinformation, v. 59, p. 135-146, https://doi.org/10.1016/j.jag.2017.03.009.","productDescription":"12 p.","startPage":"135","endPage":"146","ipdsId":"IP-062677","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469621,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jag.2017.03.009","text":"Publisher Index Page"},{"id":438249,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7J67F5X","text":"USGS data release","linkHelpText":"Cheatgrass mapping in Squirrel Creek Wildfire, WY in 2014"},{"id":344581,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59858804e4b05ba66e9ea291","contributors":{"authors":[{"text":"West, Amanda M.","contributorId":176705,"corporation":false,"usgs":false,"family":"West","given":"Amanda","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":707232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evangelista, Paul H.","contributorId":14747,"corporation":false,"usgs":true,"family":"Evangelista","given":"Paul","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":707233,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":707231,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kumar, Sunil","contributorId":195493,"corporation":false,"usgs":false,"family":"Kumar","given":"Sunil","affiliations":[],"preferred":false,"id":707234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swallow, Aaron","contributorId":195494,"corporation":false,"usgs":false,"family":"Swallow","given":"Aaron","email":"","affiliations":[],"preferred":false,"id":707235,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luizza, Matthew","contributorId":169629,"corporation":false,"usgs":false,"family":"Luizza","given":"Matthew","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":707236,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chignell, Steve","contributorId":195495,"corporation":false,"usgs":false,"family":"Chignell","given":"Steve","email":"","affiliations":[],"preferred":false,"id":707237,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70189168,"text":"ofr20171083 - 2017 - Barrier island habitat map and vegetation survey—Dauphin Island, Alabama, 2015","interactions":[],"lastModifiedDate":"2017-08-04T15:01:34","indexId":"ofr20171083","displayToPublicDate":"2017-08-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1083","title":"Barrier island habitat map and vegetation survey—Dauphin Island, Alabama, 2015","docAbstract":"Barrier islands are dynamic environments due to their position at the land-sea interface. Storms, waves, tides, currents, and relative sea-level rise are powerful forces that shape barrier island geomorphology and habitats (for example, beach, dune, marsh, and forest). Hurricane Katrina in 2005 and the Deep Water Horizon oil spill in 2010 are two major events that have affected habitats and natural resources on Dauphin Island, Alabama. The latter event prompted a collaborative effort between the U.S. Geological Survey, the U.S. Army Corps of Engineers, and the State of Alabama funded by the National Fish and Wildlife Foundation to investigate viable, sustainable restoration options that protect and restore the natural resources of Dauphin Island, Alabama.
In order to understand the feasibility and sustainability of various restoration scenarios, it is important to understand current conditions on Dauphin Island. To further this understanding, a detailed 19-class habitat map for Dauphin Island was produced from 1-foot aerial infrared photography collected on December 4, 2015, and lidar data collected in January 2015. We also conducted a ground survey of habitat types, vegetation community structure, and elevations in November and December 2015. These products provide baseline data regarding the ecological and general geomorphological attributes of the area, which can be compared with observations from other dates for tracking changes over time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171083","collaboration":"Prepared in collaboration with the U.S. Army Corps of Engineers","usgsCitation":"Enwright, N.M., Borchert, S.M., Day, R.H., Feher, L.C., Osland, M.J., Wang, Lei, and Wang, Hongqing, 2017, Barrier island habitat map and vegetation survey—Dauphin Island, Alabama, 2015: U.S. Geological Survey Open-File Report 2017–1083, 17 p., https://doi.org/10.3133/ofr20171083.","productDescription":"Report: vi, 17 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-087262","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":344579,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7513WPC","text":"USGS - Data Release","description":"USGS Data Release","linkHelpText":"Barrier island habitat map and vegetation survey, Dauphin Island, AL, 2015"},{"id":344578,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1083/ofr20171083.pdf","size":"2.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1083"},{"id":344577,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1083/coverthb.jpg"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.37127685546875,\n 30.20626765511821\n ],\n [\n -88.05541992187499,\n 30.20626765511821\n ],\n [\n -88.05541992187499,\n 30.288717426233095\n ],\n [\n -88.37127685546875,\n 30.288717426233095\n ],\n [\n -88.37127685546875,\n 30.20626765511821\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
The U.S. Army Garrison Fort Carson (AGFC) and the Piñon Canyon Maneuver Site (PCMS) are facilities operated by the U.S. Department of the Army in southern Colorado. The U.S. Geological Survey, in cooperation with the U.S. Department of the Army, established a hydrologic and water-quality data-collection network at the AGFC in June 1978 and at the PCMS in October 1982. The data-collection networks are designed to assess the quantity and quality of water resources and monitor the effects of military training activities on streamflow and water quality. Two preexisting U.S. Geological Survey streamgages at the PCMS were incorporated into the data-collection network at the time it was established, providing periods of record that begin as early as 1966. This report presents and summarizes precipitation, streamflow, suspended-sediment, and water-quality data from 34 U.S. Geological Survey sites on or near the AGFC and the PCMS for the period of record at each site. (Streamflow data are presented as discharge in cubic feet per second.)
At AGFC, daily sum precipitation ranged from 0 to 11.85 inches, daily mean discharge ranged from 0 to 836 cubic feet per second, and daily mean suspended-sediment discharge ranged from 0 to 39,900 tons per day. With the exception of total (unfiltered) mercury and filtered sulfate at two sites and filtered manganese at three sites, 95th percentile trace element concentrations and median total (unfiltered) metal concentrations were less than regulatory numeric standards for all samples. However, individual water-quality results occasionally exceeded respective regulatory numeric standards.
At the PCMS, daily sum precipitation ranged from 0 to 4.59 inches, daily mean discharge ranged from 0 to 4,190 cubic feet per second, and daily mean suspended-sediment discharge ranged from 0 to 21,100 tons per day. Water-quality results, 95th percentile trace element concentrations, and median total (unfiltered) metal concentrations were less than regulatory numeric standards for most properties and constituents except for filtered chloride at one site, filtered sulfate at six sites, filtered phosphorus at one site, filtered manganese at three sites, and total (unfiltered) iron at three sites. Individual water-quality values also occasionally exceeded respective regulatory numeric standards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171072","collaboration":"Prepared in cooperation with the U.S. Department of the Army","usgsCitation":"Arnold, L.R., 2017, Precipitation, streamflow, suspended-sediment, and water-quality data for the U.S. Army Garrison Fort Carson and Piñon Canyon Maneuver Site, Colorado, 1966–2015: U.S. Geological Survey Open-File Report 2017–1072, 130 p., https://doi.org/10.3133/ofr20171072.","productDescription":"v, 129 p.","onlineOnly":"Y","ipdsId":"IP-086258","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":344560,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1072/ofr20171072.pdf","text":"Report","size":"4.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1072"},{"id":344559,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1072/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Piñon Canyon Maneuver Site, U.S. Army Garrison Fort Carson","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.05,\n 38.77\n ],\n [\n -104.59,\n 38.77\n ],\n [\n -104.59,\n 38.4\n ],\n [\n -105.05,\n 38.4\n ],\n [\n -105.05,\n 38.77\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225
Undiscovered potash resources in the Pripyat Basin, Belarus, and Dnieper-Donets Basin, Ukraine, were assessed as part of a global mineral resource assessment led by the U.S. Geological Survey (USGS). The Pripyat Basin (in Belarus) and the Dnieper-Donets Basin (in Ukraine and southern Belarus) host stratabound and halokinetic Upper Devonian (Frasnian and Famennian) and Permian (Cisuralian) potash-bearing salt. The evaporite basins formed in the Donbass-Pripyat Rift, a Neoproterozoic continental rift structure that was reactivated during the Late Devonian and was flooded by seawater. Though the rift was divided, in part by volcanic deposits, into the separate Pripyat and Dnieper-Donets Basins, both basins contain similar potash‑bearing evaporite sequences. An Early Permian (Cisuralian) sag basin formed over the rift structure and was also inundated by seawater resulting in another sequence of evaporite deposition. Halokinetic activity initiated by basement faulting during the Devonian continued at least into the Permian and influenced potash salt deposition and structural evolution of potash-bearing salt in both basins.
Within these basins, four areas (permissive tracts) that permit the presence of undiscovered potash deposits were defined by using geological criteria. Three tracts are permissive for stratabound potash-bearing deposits and include Famennian (Upper Devonian) salt in the Pripyat Basin, and Famennian and Cisuralian (lower Permian) salt in the Dnieper-Donets Basin. In addition, a tract was delineated for halokinetic potash-bearing Famennian salt in the Dnieper-Donets Basin.
The Pripyat Basin is the third largest source of potash in the world, producing 6.4 million metric tons of potassium chloride (KCl) (the equivalent of about 4.0 million metric tons of potassium oxide or K2O) in 2012. Potash production began in 1963 in the Starobin #1 mine, near the town of Starobin, Belarus, in the northwestern corner of the basin. Potash is currently produced from six potash mines in the Starobin area. Published reserves in the Pripyat Basin area are about 7.3 billion metric tons of potash ore (about 1.3 billion metric tons of K2O) mostly from potash-bearing salt horizons in the Starobin and Petrikov mine areas. The 15,160-square-kilometer area of the Pripyat Basin underlain by Famennian potash-bearing salt contains as many as 60 known potash-bearing salt horizons. Rough estimates of the total mineral endowment associated with stratabound Famennian salt horizons in the Pripyat Basin range from 80 to 200 billion metric tons of potash-bearing salt that could contain 15 to 30 billion metric tons of K2O.
Parameters (including the number of economic potash horizons, grades, and depths) for these estimates are not published so the estimates are not easily confirmed. Historically, reserves have been estimated above a depth of 1,200 meters (m) (approximately the depths of conventional underground mining). Additional undiscovered K2O resources could be significantly greater in the remainder of the Fammenian salt depending on the extents and grades of the 60 identified potash horizons above the USGS assessment depth of 3,000 m in the remainder of the tract. Increasing ambient temperatures with increasing depths in the eastern parts of the Pripyat Basin may require a solution mining process which is aided by higher temperatures.
No resource or reserve data have been published and little is known about stratabound Famennian and Frasnian salt in the Dnieper-Donets Basin. These Upper Devonian salt units dip to the southeast and extend to depths of 15–19 kilometers (km) or greater. The tract of stratabound Famennian salt that lies above a depth of 3 km, the depth above which potash is technically recoverable by solution mining, underlies an area of about 15,600 square kilometers (km2). If Upper Devonian salt units in the Dnieper-Donets Basin contain potash-bearing strata similar to salt of the same age in the Pripyat Basin, then the stratabound Famennian tract in the Dnieper-Donets Basin could contain significant undiscovered potash resources.
The Cisuralian evaporite sequence in the Dnieper-Donets Basin consists of 10 evaporite cycles with the upper 3 cycles containing potash-bearing salt (mainly as sylvite and carnallite) in several subbasins and polyhalite in the sulfate bearing parts of the identified tract. The area of the Cisuralian tract is 62,700 km2. Potash-bearing cycles are as much as 40 m thick. One subbasin is reported to contain 794 million metric tons of “raw or crude” potash-bearing salt which could contain 50 to 150 million metric tons of K2O, depending on the grade. Undiscovered potash resources in the remainder of this permissive tract may be significantly greater. Depths to the Permian salt range from less than 100 to about 1,500 m.
Undiscovered resources of halokinetic potash-bearing salt in the Dnieper-Donets Basin were assessed quantitatively for this study by using the standard USGS three-part form of mineral resource assessment (Singer, 2007a; Singer and Menzie, 2010). Delineation of the permissive tract was based on distributions of mapped halokinetic salt structures. This tract contains at least 248 diapiric salt structures with a total area of 7,840 km2 that occupies approximately 8 percent of the basin area. The vertical extent of these salt structures is hundreds of meters to several kilometers. This assessment estimated that a total mean of 11 undiscovered deposits contain an arithmetic mean estimate of about 840 million metric tons of K2O in the halokinetic salt structures of the Dnieper-Donets Basin for which the probabilistic estimate was made.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090BB","usgsCitation":"Cocker, M.D., Orris, G.J., and Dunlap, Pamela, with contributions from Lipin, B.R., Ludington, Steve, Ryan, R.J., Słowakiewicz, Mirosław, Spanski, G.T., Wynn, Jeff, and Yang, Chao, 2017, Geology and undiscovered resource assessment of the potash-bearing Pripyat and Dnieper-Donets Basins, Belarus and Ukraine: U.S. Geological Survey Scientific Investigations Report 2010–5090–BB, 116 p., and spatial data, https://doi.org/10.3133/sir20105090BB.","productDescription":"Report: x, 116 p.; GIS Data","numberOfPages":"116","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053911","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":344467,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2010/5090/bb/sir20105090bb_gis.zip","text":"GIS Data","size":"2.75 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2010-5090-BB"},{"id":344465,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2010/5090/bb/coverthb.jpg"},{"id":344466,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/bb/sir20105090bb.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090-BB"}],"country":"Belarus, Ukraine","otherGeospatial":"Dnieper-Donets Basin, Pripyat Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 25.9716796875,\n 44.74673324024678\n ],\n [\n 46.8896484375,\n 44.74673324024678\n ],\n [\n 46.8896484375,\n 54.23955053156177\n ],\n [\n 25.9716796875,\n 54.23955053156177\n ],\n [\n 25.9716796875,\n 44.74673324024678\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Mineral Resources Program
U.S. Geological Survey
12201 Sunrise Valley Drive
913 National Center
Reston, VA 20192
Altitudinal movement by tropical birds to track seasonally variable resources can move them from protected areas to areas of increased vulnerability. In Hawaiʻi, historical reports suggest that many Hawaiian honeycreepers such as the ‘I‘iwi (Drepanis coccinea) once undertook seasonal migrations, but the existence of such movements today is unclear. Because Hawaiian honeycreepers are highly susceptible to avian malaria, currently minimal in high-elevation forests, understanding the degree to which honeycreepers visit lower elevation forests may be critical to predict the current impact of malaria on population dynamics and how susceptible bird populations may respond to climate change and mitigation scenarios. Using radio telemetry data, we demonstrate for the first time that a large fraction of breeding adult and juvenile ‘I‘iwi originating from an upper-elevation (1,920 m) population at Hakalau Forest National Wildlife Refuge exhibit post-breeding movements well below the upper elevational limit for mosquitoes. Bloom data suggest seasonal variation in floral resources is the primary driver of seasonal movement for ‘I‘iwi. To understand the demographic implications of such movement, we developed a spatial individual-based model calibrated using previously published and original data. ʻI‘iwi dynamics were simulated backward in time, to estimate population levels in the absence of avian malaria, and forward in time, to assess the impact of climate warming as well as two potential mitigation actions. Even in disease-free ‘refuge’ populations, we found that breeding densities failed to reach the estimated carrying capacity, suggesting the existence of a seasonal “migration load” as a result of travel to disease-prevalent areas. We predict that ‘I‘iwi may be on the verge of extinction in 2100, with the total number of pairs reaching only ~ 0.2–12.3% of the estimated pre-malaria density, based on an optimistic climate change scenario. The probability of extinction of ‘I‘iwi populations, as measured by population estimates for 2100, is strongly related to their estimated migration propensity. Long-term conservation strategies likely will require a multi-pronged response including a reduction of malaria threats, habitat restoration and continued landscape-level access to seasonally variable nectar resources.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecm.1253","usgsCitation":"Guillaumet, A., Kuntz, W.A., Samuel, M.D., and Paxton, E., 2017, Altitudinal migration and the future of an iconic Hawaiian honeycreeper in response to climate change and management: Ecological Monographs, v. 87, no. 3, p. 410-428, https://doi.org/10.1002/ecm.1253.","productDescription":"19 p.","startPage":"410","endPage":"428","ipdsId":"IP-071642","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":344549,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"87","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-03","publicationStatus":"PW","scienceBaseUri":"59843646e4b0e2f5d466538b","contributors":{"authors":[{"text":"Guillaumet, Alban","contributorId":150397,"corporation":false,"usgs":false,"family":"Guillaumet","given":"Alban","email":"","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":707061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kuntz, Wendy A.","contributorId":195426,"corporation":false,"usgs":false,"family":"Kuntz","given":"Wendy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":707062,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Samuel, Michael D. msamuel@usgs.gov","contributorId":1419,"corporation":false,"usgs":true,"family":"Samuel","given":"Michael","email":"msamuel@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":707063,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paxton, Eben H. 0000-0001-5578-7689 epaxton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":438,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben H.","email":"epaxton@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":707060,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189994,"text":"70189994 - 2017 - Recent stability of resident and migratory landbird populations in National Parks of the Pacific Northwest","interactions":[],"lastModifiedDate":"2017-11-22T16:46:34","indexId":"70189994","displayToPublicDate":"2017-08-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Recent stability of resident and migratory landbird populations in National Parks of the Pacific Northwest","docAbstract":"Monitoring species in National Parks facilitates inference regarding effects of climate change on population dynamics because parks are relatively unaffected by other forms of anthropogenic disturbance. Even at early points in a monitoring program, identifying climate covariates of population density can suggest vulnerabilities to future change. Monitoring landbird populations in parks during the breeding season brings the added benefit of allowing a comparative approach to inference across a large suite of species with diverse requirements. For example, comparing resident and migratory species that vary in exposure to non-park habitats can reveal the relative importance of park effects, such as those related to local climate. We monitored landbirds using breeding-season point-count data collected during 2005–2014 in three wilderness areas of the Pacific Northwest (Mount Rainier, North Cascades, and Olympic National Parks). For 39 species, we estimated recent trends in population density while accounting for individual detection probability using Bayesian hierarchical N-mixture models. Our analyses integrated several recent developments in N-mixture modeling, incorporating interval and distance sampling to estimate distinct components of detection probability while also accommodating count intervals of varying duration, annual variation in the length and number of point-count transects, spatial autocorrelation, random effects, and covariates of detection and density. As covariates of density, we considered metrics of precipitation and temperature hypothesized to affect breeding success. We also considered effects of park and elevational stratum on trend. Regardless of model structure, we estimated stable or increasing densities during 2005–2014 for most populations. Mean trends across species were positive for migrants in every park and for residents in one park. A recent snowfall deficit in this region might have contributed to the positive trend, because population density varied inversely with precipitation-as-snow for both migrants and residents. Densities varied directly but much more weakly with mean spring temperature. Our approach exemplifies an analytical framework for estimating trends from point-count data, and for assessing the role of climatic and other spatiotemporal variables in driving those trends. Understanding population trends and the factors that drive them is critical for adaptive management and resource stewardship in the context of climate change.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1902","usgsCitation":"Ray, C., Saracco, J., Holmgren, M., Wilkerson, R., Siegel, R., Jenkins, K.J., Ransom, J.I., Happe, P.J., Boetsch, J., and Huff, M., 2017, Recent stability of resident and migratory landbird populations in National Parks of the Pacific Northwest: Ecosphere, v. 8, no. 7, e01902: 24 p., https://doi.org/10.1002/ecs2.1902.","productDescription":"e01902: 24 p.","ipdsId":"IP-081909","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469623,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1902","text":"Publisher Index Page"},{"id":344551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"8","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-31","publicationStatus":"PW","scienceBaseUri":"59843648e4b0e2f5d466539d","contributors":{"authors":[{"text":"Ray, Chris","contributorId":150148,"corporation":false,"usgs":false,"family":"Ray","given":"Chris","email":"","affiliations":[{"id":17921,"text":"Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado","active":true,"usgs":false}],"preferred":false,"id":707036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saracco, James","contributorId":195412,"corporation":false,"usgs":false,"family":"Saracco","given":"James","affiliations":[],"preferred":false,"id":707037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holmgren, Mandy","contributorId":195413,"corporation":false,"usgs":false,"family":"Holmgren","given":"Mandy","email":"","affiliations":[],"preferred":false,"id":707038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilkerson, Robert","contributorId":195414,"corporation":false,"usgs":false,"family":"Wilkerson","given":"Robert","affiliations":[],"preferred":false,"id":707039,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Siegel, Rodney","contributorId":195415,"corporation":false,"usgs":false,"family":"Siegel","given":"Rodney","affiliations":[],"preferred":false,"id":707040,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jenkins, Kurt J. 0000-0003-1415-6607 kurt_jenkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1415-6607","contributorId":3415,"corporation":false,"usgs":true,"family":"Jenkins","given":"Kurt","email":"kurt_jenkins@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":707035,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ransom, Jason I.","contributorId":139841,"corporation":false,"usgs":false,"family":"Ransom","given":"Jason","email":"","middleInitial":"I.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":707041,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Happe, Patricia J.","contributorId":177053,"corporation":false,"usgs":false,"family":"Happe","given":"Patricia","email":"","middleInitial":"J.","affiliations":[{"id":20307,"text":"US National Park Service","active":true,"usgs":false}],"preferred":false,"id":707042,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Boetsch, John","contributorId":195416,"corporation":false,"usgs":false,"family":"Boetsch","given":"John","affiliations":[],"preferred":false,"id":707043,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Huff, Mark","contributorId":195417,"corporation":false,"usgs":false,"family":"Huff","given":"Mark","affiliations":[],"preferred":false,"id":707044,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70186194,"text":"sir20175019 - 2017 - Estimation of low-flow statistics at ungaged sites on streams in the Lower Hudson River Basin, New York, from data in geographic information systems","interactions":[],"lastModifiedDate":"2017-10-06T14:28:10","indexId":"sir20175019","displayToPublicDate":"2017-08-02T09:45:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5019","title":"Estimation of low-flow statistics at ungaged sites on streams in the Lower Hudson River Basin, New York, from data in geographic information systems","docAbstract":"A variety of watershed properties available in 2015 from geographic information systems were tested in regression equations to estimate two commonly used statistical indices of the low flow of streams, namely the lowest flows averaged over 7 consecutive days that have a 1 in 10 and a 1 in 2 chance of not being exceeded in any given year (7-day, 10-year and 7-day, 2-year low flows). The equations were based on streamflow measurements in 51 watersheds in the Lower Hudson River Basin of New York during the years 1958–1978, when the number of streamflow measurement sites on unregulated streams was substantially greater than in subsequent years. These low-flow indices are chiefly a function of the area of surficial sand and gravel in the watershed; more precisely, 7-day, 10-year and 7-day, 2-year low flows both increase in proportion to the area of sand and gravel deposited by glacial meltwater, whereas 7-day, 2-year low flows also increase in proportion to the area of postglacial alluvium. Both low-flow statistics are also functions of mean annual runoff (a measure of net water input to the watershed from precipitation) and area of swamps and poorly drained soils in or adjacent to surficial sand and gravel (where groundwater recharge is unlikely and riparian water loss to evapotranspiration is substantial). Small but significant refinements in estimation accuracy resulted from the inclusion of two indices of stream geometry, channel slope and length, in the regression equations. Most of the regression analysis was undertaken with the ordinary least squares method, but four equations were replicated by using weighted least squares to provide a more realistic appraisal of the precision of low-flow estimates. The most accurate estimation equations tested in this study explain nearly 84 and 87 percent of the variation in 7-day, 10-year and 7-day, 2-year low flows, respectively, with standard errors of 0.032 and 0.050 cubic feet per second per square mile. The equations use natural values of streamflow and watershed properties; logarithmic transformations yielded less accurate equations inconsistent with some conceptualized relationships.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175019","usgsCitation":"Randall, A.D., and Freehafer, D.A., 2017, Estimation of low-flow statistics at ungaged sites on streams in the Lower Hudson River Basin, New York, from data in geographic information systems: U.S. Geological Survey Scientific Investigations Report 2017–5019, 42 p., https://doi.org/10.3133/sir20175019.","productDescription":"v, 42 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073104","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":344430,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5019/sir20175019.pdf","text":"Report","size":"3.89 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5019"},{"id":344429,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5019/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Lower Hudson River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.6,\n 41\n ],\n [\n -73.2,\n 41\n ],\n [\n -73.2,\n 42.9\n ],\n [\n -74.6,\n 42.9\n ],\n [\n -74.6,\n 41\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180
This specification documents the requirements and standards used to produce the seamless elevation layers for The National Map of the United States. Seamless elevation data are available for the conterminous United States, Hawaii, Alaska, and the U.S. territories, in three different resolutions—1/3-arc-second, 1-arc-second, and 2-arc-second. These specifications include requirements and standards information about source data requirements, spatial reference system, distribution tiling schemes, horizontal resolution, vertical accuracy, digital elevation model surface treatment, georeferencing, data source and tile dates, distribution and supporting file formats, void areas, metadata, spatial metadata, and quality assurance and control.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section B: U.S. Geological Survey Standards in Book 11: Collection and Delineation of Spatial Data","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm11B9","usgsCitation":"Archuleta, C.M., Constance, E.W., Arundel, S.T., Lowe, A.J., Mantey, K.S., and Phillips, L.A., 2017, The National Map seamless digital elevation model specifications: U.S. Geological Survey Techniques and Methods, book 11, chap. B9, 39 p., https://doi.org/10.3133/tm11B9.","productDescription":"v, 39 p.","onlineOnly":"Y","ipdsId":"IP-083616","costCenters":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"links":[{"id":344505,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/11b9/tm11B9.pdf","text":"Report","size":"3.88 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 11–B–9"},{"id":344504,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/11b9/coverthb.jpg"}],"publicComments":"This report is Chapter 9 of Section B: U.S. Geological Survey Standards in Book 11: Collection and Delineation of Spatial Data","contact":"Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
On March 22, 2014, the State Route 530 Landslide near Oso, Washington mobilized 8 million cubic meters of unconsolidated Pleistocene material, creating a valley‑spanning deposit that fully impounded the North Fork Stillaguamish River. The river overtopped the 8-meter high debris impoundment within 25 hours and began steadily incising a new channel through the center of the deposit. Repeat topographic surveys, sediment transport measurements, bedload transport models, and observations of downstream channel change were used to document the establishment of that new channel through the landslide and assess the potential for downstream aggradation or channel change that might increase downstream flood hazards.
Efficient erosion of the landslide deposit, associated with the steep knickzone formed by the downstream edge of the deposit, resulted in the re-establishment of a 20–40 meters wide, deeply inset channel through the entire deposit by May 2014, 2 months after the landslide. The mean water-surface elevation of the channel through the landslide decreased 7 meters during that 2-month period, and was about 1 meter above the pre-landslide profile in July 2014. The 2014–15 flood season, which included flows near the 0.5 annual exceedance probability discharge (2-year flood), widened the channel tens of meters, and further lowered the water-surface profile 0.5 meter. The planform position evolved slowly as a result of 5–20-meter high banks predominantly composed of clay-rich, cohesive lacustrine material. Erosion of the landslide deposit delivered a total of 820 thousand metric tons of sediment to the North Fork Stillaguamish River over the 18 months following the landslide. The sediment delivery from the deposit was predominantly fine grained: 77 percent (by mass) of the eroded material was silt or clay (less than 0.063 millimeter [mm]), 19 percent sand (0.063–2 mm), and 4 percent pebbles and cobbles (greater than 2 mm).
Over the 18 months following the landslide, the bedload at a site 5 kilometers downstream of the landslide was estimated to be 310±65 thousand metric tons, and the suspended load at that same site was estimated to be 990±110 thousand metric tons. These loads represent the combined input from the landslide and ambient upstream sources; over the study interval, landslide sediment made up about 20–40 percent of the bedload, and 65–85 percent of the suspended-sediment load at this site. At a site 70 kilometers downstream of the landslide, near the mouth of the main‑stem Stillaguamish River, suspended sediment loads were estimated to be about 1,440 thousand metric tons, of which about 600 thousand metric tons, or 30 percent, likely was derived from the landslide. The mass of landslide sediment in suspension at the mouth of the river, and the timing of arrival of that sediment, indicates that about 70 percent of the landslide sediment eroded during the study period was quickly transported through the entire basin, exiting into Puget Sound within weeks of initial entrainment.
Empirical bedload transport equations, in conjunction with surficial grain-size data and output from a one‑dimensional hydraulic model, were used to estimate spatial trends in bedload transport capacity, highlighting areas where reach-scale conditions would be most likely to promote deposition of coarse landslide sediment. Transport capacities decreased sharply over a reach about 5 kilometers downstream of the landslide and remained relatively low over the next 10 kilometers downstream. However, the magnitude of calculated transport capacities are large relative to the coarse sediment input from the landslide, suggesting that substantial deposition of landslide sediment was not likely to occur. These assessments were corroborated by observations of channel change, which indicated that the downstream channel response to the landslide was modest and short-lived. The most pronounced downstream effects included a wedge of aggradation just downstream of the landslide, about 1 meter high and extending a kilometer downstream, and a 0.3-meter pulse of aggradation observed 5 kilometers downstream of the landslide. In both locations, peak aggradation and channel response occurred within about a month of the landslide, and both sites had largely recovered to pre-landslide conditions by July 2014. No substantial channel change clearly linked to the landslide was observed after July 2014 except for a modest fining of surficial gravel size distributions and continued recovery and incision of the reach just downstream of the landslide.
The muted downstream response of the North Fork Stillaguamish River to the State Route 530 Landslide primarily can be attributed to the cohesive, silt- and clay-rich material that bounded most of the new channel. Although the river efficiently incised a new channel through the deposit, subsequent rates of lateral erosion were slowed by the tall, cohesive banks, limiting the total volume of sediment delivery. Once entrained, however, most landslide material was rapidly transported downstream in suspension with little geomorphic effect. Landslide material coarse enough to travel as bedload was predominantly sand and fine gravel, and sediment transport models and observations of downstream change indicated that the rate of coarse sediment delivery from the landslide did not exceed the rivers ability to transport that material. The generally muted downstream response to sediment delivery from the State Route 530 Landslide, as well as the mechanics of that delivery and response, were generally consistent with observations made following the intentional removal of constructed dams.
The rate and efficiency of erosion from the landslide decreased over the period of analysis, as the new channel approached a quasi-equilibrium form. In the absence of additional hillslope activity, rates of erosion from the landslide are likely to be small compared to those over the first 18 months after the landslide. The modest channel response to the highest rates of sediment delivery, and rapid recovery thereafter, indicate that the river should be able to convey the continued supply of landslide-derived sediment effectively with little effect on the downstream morphology and flood risks.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175055","collaboration":"Prepared in cooperation with the Federal Emergency Management Administration and Snohomish County, Washington","usgsCitation":"Anderson, S.W., Keith, M.K., Magirl, C.S., Wallick, J.R., Mastin, M.C., and Foreman, J.R., 2017, Geomorphic response of the North Fork Stillaguamish River to the State Route 530 landslide near Oso, Washington: U.S. Geological Survey Scientific Investigations Report 2017–5055, 85 p., https://doi.org/10.3133/sir20175055.","productDescription":"Report: ix, 85 p.; 2 Data Releases","numberOfPages":"85","onlineOnly":"Y","ipdsId":"IP-070334","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":344575,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VH5M2S","text":"USGS Data Release","linkHelpText":"Surficial sediment data on the North Fork Stillaguamish River and State Route 530 Landslide near Oso, Washington"},{"id":344574,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7T72FPK","text":"USGS Data Release","linkHelpText":"Digital elevation models of the State Route 530 Landslide near Oso, Washington, July 2014 to July 2015"},{"id":344572,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5055/coverthb.jpg"},{"id":344573,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5055/sir20175055.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5055"}],"country":"United States","state":"Washington","city":"Oso","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.4,\n 47.95\n ],\n [\n -121.35,\n 47.95\n ],\n [\n -121.35,\n 48.5\n ],\n [\n -122.4,\n 48.5\n ],\n [\n -122.4,\n 47.95\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
To assess the change in the size of the eastern North American monarch butterfly summer population, studies have used long-term data sets of counts of adult butterflies or eggs per milkweed stem. Despite the observed decline in the monarch population as measured at overwintering sites in Mexico, these studies found no decline in summer counts in the Midwest, the core of the summer breeding range, leading to a suggestion that the cause of the monarch population decline is not the loss of Midwest agricultural milkweeds but increased mortality during the fall migration. Using these counts to estimate population size, however, does not account for the shift of monarch activity from agricultural fields to non-agricultural sites over the past 20 years, as a result of the loss of agricultural milkweeds due to the near-ubiquitous use of glyphosate herbicides. We present the counter-hypotheses that the proportion of the monarch population present in non-agricultural habitats, where counts are made, has increased and that counts reflect both population size and the proportion of the population observed. We use data on the historical change in the proportion of milkweeds, and thus monarch activity, in agricultural fields and non-agricultural habitats to show why using counts can produce misleading conclusions about population size. We then separate out the shifting proportion effect from the counts to estimate the population size and show that these corrected summer monarch counts show a decline over time and are correlated with the size of the overwintering population. In addition, we present evidence against the hypothesis of increased mortality during migration. The milkweed limitation hypothesis for monarch decline remains supported and conservation efforts focusing on adding milkweeds to the landscape in the summer breeding region have a sound scientific basis.
","language":"English","publisher":"Wiley","doi":"10.1371/journal.pone.0181245","usgsCitation":"Pleasants, J., Zalucki, M.P., Oberhauser, K.S., Brower, L.P., Taylor, O.R., and Thogmartin, W.E., 2017, Interpreting surveys to estimate the size of the monarch butterfly population: Pitfalls and prospects: PLoS ONE, v. 12, no. 7, Article e0181245; 16 p., https://doi.org/10.1371/journal.pone.0181245.","productDescription":"Article e0181245; 16 p.","ipdsId":"IP-076480","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":469627,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0181245","text":"Publisher Index Page"},{"id":344542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"7","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-14","publicationStatus":"PW","scienceBaseUri":"5982e4aae4b0e2f5d464b711","contributors":{"authors":[{"text":"Pleasants, John M.","contributorId":168616,"corporation":false,"usgs":false,"family":"Pleasants","given":"John M.","affiliations":[{"id":25341,"text":"Department of Ecology, Evolution, and Organismal Biology, Iowa State University","active":true,"usgs":false}],"preferred":false,"id":707165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zalucki, Myron P.","contributorId":195450,"corporation":false,"usgs":false,"family":"Zalucki","given":"Myron","email":"","middleInitial":"P.","affiliations":[{"id":7031,"text":"School of Biological Sciences, University of Queensland","active":true,"usgs":false}],"preferred":false,"id":707166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oberhauser, Karen S.","contributorId":195451,"corporation":false,"usgs":false,"family":"Oberhauser","given":"Karen","email":"","middleInitial":"S.","affiliations":[{"id":24577,"text":"University of Minnesota, St. Paul, MN","active":true,"usgs":false}],"preferred":false,"id":707167,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brower, Lincoln P.","contributorId":195452,"corporation":false,"usgs":false,"family":"Brower","given":"Lincoln","email":"","middleInitial":"P.","affiliations":[{"id":34276,"text":"Sweet Briar College, Sweet Briar, VA","active":true,"usgs":false}],"preferred":false,"id":707168,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Orley R.","contributorId":191432,"corporation":false,"usgs":false,"family":"Taylor","given":"Orley","email":"","middleInitial":"R.","affiliations":[{"id":28093,"text":"Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS 66045, USA","active":true,"usgs":false}],"preferred":false,"id":707169,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":707170,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198400,"text":"70198400 - 2017 - New constraints on coseismic slip during southern Cascadia subduction zone earthquakes over the past 4600 years implied by tsunami deposits and marine turbidites","interactions":[],"lastModifiedDate":"2018-08-03T10:54:06","indexId":"70198400","displayToPublicDate":"2017-08-01T10:53:57","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"New constraints on coseismic slip during southern Cascadia subduction zone earthquakes over the past 4600 years implied by tsunami deposits and marine turbidites","docAbstract":"Forecasting earthquake and tsunami hazards along the southern Cascadia subduction zone is complicated by uncertainties in the amount of megathrust fault slip during past ruptures. Here, we estimate slip on hypothetical ruptures of the southern part of the megathrust through comparisons of late Holocene Cascadia earthquake histories derived from tsunami deposits on land and marine turbidites offshore. Bradley Lake in southern Oregon lies ~600 m landward of the shoreline and contains deposits from 12 tsunamis in the past 4600 years. Tsunami simulations that overtop the 6-m-high lake outlet, generated by ruptures with most slip south of Cape Blanco, require release of at least as much strain on the megathrust as would accumulate in 430–640 years (>15–22 m). Such high slip is inconsistent with global seismic data for a rupture ~300-km long and slip deficits over the past ~4700 years on the southern Cascadia subduction zone. Assuming slip deficits accumulated during the time intervals between marine turbidites, up to 8 of 12 tsunami inundations at the lake are predicted from a marine core site 170 km north of the lake (at Hydrate Ridge) compared to 4 of 12 when using a core site ~80 km south (at Rogue Apron). Longer time intervals between turbidites at Hydrate Ridge imply larger slip deficits compared to Rogue Apron. The different inundations predicted by the two records suggest that Hydrate Ridge records subduction ruptures that extend past both Rogue Apron and Bradley Lake. We also show how turbidite-based estimates of CSZ rupture length relate to tsunami source scenarios for probabilistic tsunami hazard assessments consistent with lake inundations over the last ~4600 years.
","language":"English","publisher":"Springer","doi":"10.1007/s11069-017-2864-9","usgsCitation":"Priest, G.R., Witter, R., Zhang, Y.J., Goldfinger, C., Wang, K., and Allan, J.C., 2017, New constraints on coseismic slip during southern Cascadia subduction zone earthquakes over the past 4600 years implied by tsunami deposits and marine turbidites: Natural Hazards, v. 88, no. 1, p. 285-313, https://doi.org/10.1007/s11069-017-2864-9.","productDescription":"29 p.","startPage":"285","endPage":"313","ipdsId":"IP-086547","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":488399,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarworks.wm.edu/vimsarticles/734","text":"External Repository"},{"id":356129,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.5,\n 42\n ],\n [\n -123.75,\n 42\n ],\n [\n -123.75,\n 45\n ],\n [\n -125.5,\n 45\n ],\n [\n -125.5,\n 42\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"88","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-29","publicationStatus":"PW","scienceBaseUri":"5b6fc609e4b0f5d57878eb5d","contributors":{"authors":[{"text":"Priest, George R.","contributorId":206646,"corporation":false,"usgs":false,"family":"Priest","given":"George","email":"","middleInitial":"R.","affiliations":[{"id":37367,"text":"Oregon Dept. of Geology and Mineral Industries","active":true,"usgs":false}],"preferred":false,"id":741351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":741350,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Yinglong J.","contributorId":206647,"corporation":false,"usgs":false,"family":"Zhang","given":"Yinglong","email":"","middleInitial":"J.","affiliations":[{"id":37368,"text":"Center for Coastal Resources Management, VA Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":741352,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldfinger, Chris","contributorId":195634,"corporation":false,"usgs":false,"family":"Goldfinger","given":"Chris","email":"","affiliations":[],"preferred":false,"id":741353,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Kelin","contributorId":194791,"corporation":false,"usgs":false,"family":"Wang","given":"Kelin","email":"","affiliations":[],"preferred":false,"id":741354,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allan, Jonathan C.","contributorId":118007,"corporation":false,"usgs":false,"family":"Allan","given":"Jonathan","email":"","middleInitial":"C.","affiliations":[{"id":7198,"text":"Oregon Department Geology and Mineral Industries","active":true,"usgs":false}],"preferred":false,"id":741355,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70194201,"text":"70194201 - 2017 - Paltry past-precipitation: Predisposing prairie dogs to plague?","interactions":[],"lastModifiedDate":"2017-11-17T15:14:11","indexId":"70194201","displayToPublicDate":"2017-08-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Paltry past-precipitation: Predisposing prairie dogs to plague?","docAbstract":"The plague bacterium Yersinia pestis was introduced to California in 1900 and spread rapidly as a sylvatic disease of mammalian hosts and flea vectors, invading the Great Plains in the United States by the 1930s to 1940s. In grassland ecosystems, plague causes periodic, devastating epizootics in colonies of black-tailed prairie dogs (Cynomys ludovicianus), sciurid rodents that create and maintain subterranean burrows. In doing so, plague inhibits prairie dogs from functioning as keystone species of grassland communities. The rate at which fleas transmit Y. pestis is thought to increase when fleas are abundant. Flea densities can increase during droughts when vegetative production is reduced and herbivorous prairie dogs are malnourished and have weakened defenses against fleas. Epizootics of plague have erupted frequently in prairie dogs during years in which precipitation was plentiful, and the accompanying cool temperatures might have facilitated the rate at which fleas transmitted Y. pestis. Together these observations evoke the hypothesis that transitions from dry-to-wet years provide conditions for plague epizootics in prairie dogs. Using generalized linear models, we analyzed a 24-year dataset on the occurrence of plague epizootics in 42 colonies of prairie dogs from Colorado, USA, 1982–2005. Of the 33 epizootics observed, 52% erupted during years with increased precipitation in summer. For the years with increased summer precipitation, if precipitation in the prior growing season declined from the maximum of 502 mm to the minimum of 200 mm, the prevalence of plague epizootics was predicted to increase 3-fold. Thus, reduced precipitation may have predisposed prairie dogs to plague epizootics when moisture returned. Biologists sometimes assume dry conditions are detrimental for plague. However, 48% of epizootics occurred during years in which precipitation was scarce in summer. In some cases, an increased abundance of fleas during dry years might compensate for other conditions that become less favorable for plague transmission. Global warming is forecasted to amplify the hydrological cycle in the Great Plains, causing an increased occurrence of prolonged droughts interceded by brief periods of intense precipitation. Results herein suggest these changes might affect plague cycles in prairie dogs. Both negative and positive consequences of dry conditions should be considered when managing plague.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21281","usgsCitation":"Eads, D., and Biggins, D.E., 2017, Paltry past-precipitation: Predisposing prairie dogs to plague?: Journal of Wildlife Management, v. 81, no. 6, p. 990-998, https://doi.org/10.1002/jwmg.21281.","productDescription":"9 p.","startPage":"990","endPage":"998","ipdsId":"IP-086521","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":438257,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71G0K17","text":"USGS data release","linkHelpText":"Occurrence of plague epizootics in colonies of black-tailed prairie dogs, Pawnee National Grassland, Colorado, 1982-2005"},{"id":349075,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"81","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-04","publicationStatus":"PW","scienceBaseUri":"5a60fb74e4b06e28e9c230b6","contributors":{"authors":[{"text":"Eads, David deads@usgs.gov","contributorId":200549,"corporation":false,"usgs":true,"family":"Eads","given":"David","email":"deads@usgs.gov","affiliations":[],"preferred":true,"id":722638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biggins, Dean E. 0000-0003-2078-671X bigginsd@usgs.gov","orcid":"https://orcid.org/0000-0003-2078-671X","contributorId":2522,"corporation":false,"usgs":true,"family":"Biggins","given":"Dean","email":"bigginsd@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":722639,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193640,"text":"70193640 - 2017 - Distribution and migration chronology of Eastern population sandhill cranes","interactions":[],"lastModifiedDate":"2018-03-29T14:26:33","indexId":"70193640","displayToPublicDate":"2017-08-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Distribution and migration chronology of Eastern population sandhill cranes","docAbstract":"The Eastern Population (EP) of greater sandhill cranes (Antigone canadensis tabida; cranes) is expanding in size and geographic range. Little information exists regarding the geographic extent of breeding, migration, and wintering ranges, migration chronology, or use of staging areas for cranes in the EP. To obtain these data, we attached solar global positioning system (GPS) platform transmitting terminals (PTTs) to 42 sandhill cranes and monitored daily locations from December 2009 through August 2014. On average, tagged cranes settled in summer areas during late‐March in Minnesota (7%), Wisconsin (29%), Michigan, USA (21%), and Ontario, Canada (38%) and arrived at their winter terminus beginning mid‐December in Indiana (15%), Kentucky (3%), Tennessee (45%), Georgia (5%), and Florida (32%). Cranes initiated spring migration beginning mid‐February to their respective summer areas on routes similar to those used during fall migration. Twenty‐five marked cranes returned to the same summer area after a second spring migration, of which 19 (76%) settled <3 km from the estimated mean center of the summer area of the previous year. During the 2010–2012 United States Fish and Wildlife Service (USFWS) Cooperative Fall Abundance Survey for cranes in the EP, we estimated that approximately 29–31% of cranes that summered in both Wisconsin and the Lower Peninsula of Michigan were not in areas included in the survey. The information we collected on crane movements provides insight into distribution and migration chronology that will aid in assessment of the current USFWS fall survey. In addition, information on specific use sites can assist state and federal managers to identify and protect key staging and winter areas particularly during current and future recreational harvest seasons.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21272","usgsCitation":"Fronczak, D.L., Andersen, D.E., Hanna, E.E., and Cooper, T.R., 2017, Distribution and migration chronology of Eastern population sandhill cranes: Journal of Wildlife Management, v. 81, no. 6, p. 1021-1032, https://doi.org/10.1002/jwmg.21272.","productDescription":"12 p.","startPage":"1021","endPage":"1032","ipdsId":"IP-070501","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":461443,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21272","text":"Publisher Index Page"},{"id":352953,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"81","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-18","publicationStatus":"PW","scienceBaseUri":"5afee823e4b0da30c1bfc3f7","contributors":{"authors":[{"text":"Fronczak, David L.","contributorId":191560,"corporation":false,"usgs":false,"family":"Fronczak","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":732039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":199408,"corporation":false,"usgs":true,"family":"Andersen","given":"David","email":"dea@usgs.gov","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719727,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanna, Everett E.","contributorId":191561,"corporation":false,"usgs":false,"family":"Hanna","given":"Everett","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":732040,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cooper, Thomas R.","contributorId":191468,"corporation":false,"usgs":false,"family":"Cooper","given":"Thomas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":732041,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192610,"text":"70192610 - 2017 - Empirical estimation of recreational exploitation of burbot, Lota lota, in the Wind River drainage of Wyoming using a multistate capture–recapture model","interactions":[],"lastModifiedDate":"2017-11-10T11:32:56","indexId":"70192610","displayToPublicDate":"2017-08-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Empirical estimation of recreational exploitation of burbot, Lota lota, in the Wind River drainage of Wyoming using a multistate capture–recapture model","title":"Empirical estimation of recreational exploitation of burbot, Lota lota, in the Wind River drainage of Wyoming using a multistate capture–recapture model","docAbstract":"Burbot, Lota lota (Linnaeus), is a regionally popular sportfish in the Wind River drainage of Wyoming, USA, at the southern boundary of the range of the species. Recent declines in burbot abundances were hypothesised to be caused by overexploitation, entrainment in irrigation canals and habitat loss. This study addressed the overexploitation hypothesis using tagging data to generate reliable exploitation, abundance and density estimates from a multistate capture–recapture model that accounted for incomplete angler reporting and tag loss. Exploitation rate μ was variable among the study lakes and inversely correlated with density. Exploitation thresholds μ40 associated with population densities remaining above 40% of carrying capacity were generated to characterise risk of overharvest using exploitation and density estimates from tagging data and a logistic surplus-production model parameterised with data from other burbot populations. Bull Lake (μ = 0.06, 95% CI: 0.03–0.11; μ40 = 0.18) and Torrey Lake (μ = 0.02, 95% CI: 0.00–0.11; μ40 = 0.18) had a low risk of overfishing, Upper Dinwoody Lake had intermediate risk (μ = 0.08, 95% CI: 0.02–0.32; μ40 = 0.18) and Lower Dinwoody Lake had high risk (μ = 0.32, 95% CI: 0.10–0.67; μ40 = 0.08). These exploitation and density estimates can be used to guide sustainable management of the Wind River drainage recreational burbot fishery and inform management of other burbot fisheries elsewhere.
","language":"English","publisher":"Wiley","doi":"10.1111/fme.12226","usgsCitation":"Lewandoski, S., Guy, C.S., Zale, A.V., Gerrity, P.C., Deromedi, J.W., Johnson, K.M., and Skates, D.L., 2017, Empirical estimation of recreational exploitation of burbot, Lota lota, in the Wind River drainage of Wyoming using a multistate capture–recapture model: Fisheries Management and Ecology, v. 24, no. 4, p. 298-307, https://doi.org/10.1111/fme.12226.","productDescription":"10 p.","startPage":"298","endPage":"307","ipdsId":"IP-076704","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348576,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","volume":"24","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-03","publicationStatus":"PW","scienceBaseUri":"5a06c8cae4b09af898c86108","contributors":{"authors":[{"text":"Lewandoski, S. A.","contributorId":200246,"corporation":false,"usgs":false,"family":"Lewandoski","given":"S. A.","affiliations":[],"preferred":false,"id":721592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zale, Alexander V. 0000-0003-1703-885X zale@usgs.gov","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":3010,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"zale@usgs.gov","middleInitial":"V.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716545,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerrity, Paul C.","contributorId":104198,"corporation":false,"usgs":true,"family":"Gerrity","given":"Paul","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":721593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Deromedi, J. W.","contributorId":200247,"corporation":false,"usgs":false,"family":"Deromedi","given":"J.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":721594,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, K. M.","contributorId":23513,"corporation":false,"usgs":true,"family":"Johnson","given":"K.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721595,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Skates, D. L.","contributorId":200248,"corporation":false,"usgs":false,"family":"Skates","given":"D.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":721596,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70193043,"text":"70193043 - 2017 - Automated quantification of surface water inundation in wetlands using optical satellite imagery","interactions":[],"lastModifiedDate":"2017-11-12T11:13:09","indexId":"70193043","displayToPublicDate":"2017-08-01T00:00:00","publicationYear":"2017","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":"Automated quantification of surface water inundation in wetlands using optical satellite imagery","docAbstract":"We present a fully automated and scalable algorithm for quantifying surface water inundation in wetlands. Requiring no external training data, our algorithm estimates sub-pixel water fraction (SWF) over large areas and long time periods using Landsat data. We tested our SWF algorithm over three wetland sites across North America, including the Prairie Pothole Region, the Delmarva Peninsula and the Everglades, representing a gradient of inundation and vegetation conditions. We estimated SWF at 30-m resolution with accuracies ranging from a normalized root-mean-square-error of 0.11 to 0.19 when compared with various high-resolution ground and airborne datasets. SWF estimates were more sensitive to subtle inundated features compared to previously published surface water datasets, accurately depicting water bodies, large heterogeneously inundated surfaces, narrow water courses and canopy-covered water features. Despite this enhanced sensitivity, several sources of errors affected SWF estimates, including emergent or floating vegetation and forest canopies, shadows from topographic features, urban structures and unmasked clouds. The automated algorithm described in this article allows for the production of high temporal resolution wetland inundation data products to support a broad range of applications.
","language":"English","publisher":"MDPI","doi":"10.3390/rs9080807","usgsCitation":"DeVries, B., Huang, C., Lang, M.W., Jones, J., Huang, W., Creed, I., and Carroll, M.L., 2017, Automated quantification of surface water inundation in wetlands using optical satellite imagery: Remote Sensing, v. 9, no. 8, Article 807; 22 p., https://doi.org/10.3390/rs9080807.","productDescription":"Article 807; 22 p.","ipdsId":"IP-087428","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469631,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs9080807","text":"Publisher Index Page"},{"id":348619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"8","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-07","publicationStatus":"PW","scienceBaseUri":"5a096bb1e4b09af898c94143","contributors":{"authors":[{"text":"DeVries, Ben 0000-0003-2136-3401","orcid":"https://orcid.org/0000-0003-2136-3401","contributorId":198971,"corporation":false,"usgs":false,"family":"DeVries","given":"Ben","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":717737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huang, Chengquan 0000-0003-0055-9798","orcid":"https://orcid.org/0000-0003-0055-9798","contributorId":198972,"corporation":false,"usgs":false,"family":"Huang","given":"Chengquan","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":717738,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lang, Megan W.","contributorId":196284,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":717739,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, John 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":717736,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huang, Wenli 0000-0001-9608-1690","orcid":"https://orcid.org/0000-0001-9608-1690","contributorId":198973,"corporation":false,"usgs":false,"family":"Huang","given":"Wenli","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":717740,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Creed, Irena F.","contributorId":81209,"corporation":false,"usgs":false,"family":"Creed","given":"Irena F.","affiliations":[{"id":27655,"text":"Department of Biology, University of Western Ontario, London, ON Canada","active":true,"usgs":false}],"preferred":false,"id":717741,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carroll, Mark L.","contributorId":145826,"corporation":false,"usgs":false,"family":"Carroll","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":16246,"text":"Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false},{"id":16247,"text":"Sigma Space Corp, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false},{"id":7239,"text":"Science Systems and Applications, Inc.","active":true,"usgs":false}],"preferred":false,"id":721689,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70189990,"text":"70189990 - 2017 - How well do route survey areas represent landscapes at larger spatial extents? An analysis of land cover composition along Breeding Bird Survey routes","interactions":[],"lastModifiedDate":"2018-03-29T14:24:11","indexId":"70189990","displayToPublicDate":"2017-08-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"How well do route survey areas represent landscapes at larger spatial extents? An analysis of land cover composition along Breeding Bird Survey routes","docAbstract":"The occurrence of birds in a survey unit is partly determined by the habitat present. Moreover, some bird species preferentially avoid some land cover types and are attracted to others. As such, land cover composition within the 400 m survey areas along a Breeding Bird Survey (BBS) route clearly influences the species available to be detected. Ideally, to extend survey results to the larger landscape, land cover composition within the survey area should be similar to that at larger spatial extents defining the landscape. Such representativeness helps minimize possible roadside effects (bias), here defined as differences in bird species composition and abundance along a roadside as compared to a larger surrounding landscape. We used land cover data from the 2011 National Land Cover Database to examine representativeness of land cover composition along routes. Using ArcGIS, the percentages of each of 15 land cover types within 400 m buffers along 2,696 U.S. BBS routes were calculated and compared to percentages in 2 km, 5 km, and 10 km buffers surrounding each route. This assessment revealed that aquatic cover types and highly urbanized land tend to be slightly underrepresented in the survey areas. Two anthropogenic cover types (pasture/hay and cropland) may be slightly overrepresented in the survey areas. Over all cover types, 92% of the 2,696 routes exhibited “good” representativeness, with <5 percentage points per cover type difference in proportional cover between the 400 m and 10 km buffers. This assessment further supports previous research indicating that any land-cover-based roadside bias in the bird data of the BBS is likely minimal.
","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-17-15.1","usgsCitation":"Veech, J.A., Pardieck, K.L., and Ziolkowski, D., 2017, How well do route survey areas represent landscapes at larger spatial extents? An analysis of land cover composition along Breeding Bird Survey routes: Condor, v. 119, no. 3, p. 607-615, https://doi.org/10.1650/CONDOR-17-15.1.","productDescription":"9 p.","startPage":"607","endPage":"615","ipdsId":"IP-080236","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":469723,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-17-15.1","text":"Publisher Index Page"},{"id":352952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee839e4b0da30c1bfc403","contributors":{"authors":[{"text":"Veech, Joseph A.","contributorId":195410,"corporation":false,"usgs":false,"family":"Veech","given":"Joseph","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":707017,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pardieck, Keith L. 0000-0003-2779-4392 kpardieck@usgs.gov","orcid":"https://orcid.org/0000-0003-2779-4392","contributorId":4104,"corporation":false,"usgs":true,"family":"Pardieck","given":"Keith","email":"kpardieck@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":707015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ziolkowski, David 0000-0002-2500-4417 dziolkowski@usgs.gov","orcid":"https://orcid.org/0000-0002-2500-4417","contributorId":195409,"corporation":false,"usgs":true,"family":"Ziolkowski","given":"David","email":"dziolkowski@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":707016,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70190996,"text":"70190996 - 2017 - Climate change and tree-line ecosystems in the Sierra Nevada: Habitat suitability modelling to inform high-elevation forest dynamics monitoring","interactions":[],"lastModifiedDate":"2017-10-16T14:58:51","indexId":"70190996","displayToPublicDate":"2017-08-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/SIEN/NRR—2017/1476","title":"Climate change and tree-line ecosystems in the Sierra Nevada: Habitat suitability modelling to inform high-elevation forest dynamics monitoring","docAbstract":"Whitebark pine and foxtail pine serve foundational roles in the subalpine zone of the Sierra Nevada. They provide the dominant structure in tree-line forests and regulate key ecosystem processes and community dynamics. Climate change models suggest that there will be changes in temperature regimes and in the timing and magnitude of precipitation within the current distribution of these species, and these changes may alter the species’ distributional limits. Other stressors include the non-native pathogen white pine blister rust and mountain pine beetle, which have played a role in the decline of whitebark pine throughout much of its range. The National Park Service is monitoring status and trends of these species. This report provides complementary information in the form of habitat suitability models to predict climate change impacts on the future distribution of these species within Sierra Nevada national parks.
We used maximum entropy modeling to build habitat suitability models by relating species occurrence to environmental variables. Species occurrence was available from 328 locations for whitebark pine and 244 for foxtail pine across the species’ distributions within the parks. We constructed current climate surfaces for modeling by interpolating data from weather stations. Climate surfaces included mean, minimum, and maximum temperature and total precipitation for January, April, July, and October. We downscaled five general circulation models for the 2050s and the 2090s from ~125 km2 to 1 km2 under both an optimistic and an extreme climate scenario to bracket potential climatic change and its influence on projected suitable habitat.
To describe anticipated changes in the distribution of suitable habitat, we compared, for each species, climate scenario, and time period, the current models with future models in terms of proportional change in habitat size, elevation distribution, model center points, and where habitat is predicted to expand or contract.
Overall, models indicated that suitable habitats for whitebark and foxtail pine are more likely to shift geographically within the parks by 2100 rather than decline precipitously. This implies park managers might focus conservation efforts on stressors other than climate change, working toward species resilience in the face of threats from introduced disease and elevated native insect damage. More specifically, further understanding of the incidence and severity of white pine blister rust and other stressors in high elevation white pines would help assess vulnerability from threats other than climate change.
A geochemical study was conducted on 37 springs discharging from the Toroweap Formation, Coconino Sandstone, Hermit Formation, Supai Group, and Redwall Limestone north of the Grand Canyon near areas of breccia-pipe uranium mining. Baseline concentrations were established for the elements As, B, Li, Se, SiO2, Sr, Tl, U, and V. Three springs exceeded U.S. Environmental Protection Agency drinking water standards: Fence Spring for arsenic, Pigeon Spring for selenium and uranium, and Willow (Hack) Spring for selenium. The majority of the spring sites had uranium values of less than 10 micrograms per liter (μg/L), but six springs discharging from all of the geologic units studied that are located stratigraphically above the Redwall Limestone had uranium values greater than 10 μg/L (Cottonwood [Tuckup], Grama, Pigeon, Rock, and Willow [Hack and Snake Gulch] Springs). The geochemical characteristics of these six springs with elevated uranium include Ca-Mg-SO4 water type, circumneutral pH, high specific conductance, correlation and multivariate associations between U, Mo, Sr, Se, Li, and Zn, low 87Sr/86Sr, low 234U/238U activity ratios (1.34–2.31), detectable tritium, and carbon isotopic interpretation indicating they may be a mixture of modern and pre-modern waters. Similar geochemical compositions of spring waters having elevated uranium concentrations are observed at sites located both near and away from sites of uranium-mining activities in the present study. Therefore, mining does not appear to explain the presence of elevated uranium concentrations in groundwater at the six springs noted above. The elevated uranium at the six previously mentioned springs may be influenced by iron mineralization associated with mineralized breccia pipe deposits. Six springs discharging from the Coconino Sandstone (Upper Jumpup, Little, Horse, and Slide Springs) and Redwall Limestone (Kanab and Side Canyon Springs) contained water with corrected radiocarbon ages as much as 9,300 years old. Of the springs discharging water with radiocarbon age, Kanab and Side Canyon Springs contain tritium of more than 1.3 picocuries per liter (pCi/L), indicating they may contain a component of modern water recharged after 1952. Springs containing high values of tritium (greater than 5.1 pCi/L), which may suggest a significant component of modern water, include Willow (Hack), Saddle Horse, Cottonwood (Tuckup), Hotel, Bitter, Unknown, Hole in the Wall, and Hanging Springs. Fence and Rider Springs, located on the eastern end of the study area near the Colorado River, have distinctly different geochemical compositions compared to the other springs of the study. Additionally, water from Fence Spring has the highest 87Sr/86Sr for samples analyzed from this study with a value greater than those known in sedimentary rocks from the region. Strontium isotope data likely indicate that water discharging at Fence Spring has interacted with Precambrian basement rocks. Rider Spring had the most depleted values of stable O and H isotopes indicating that recharge, if recent, occurred at higher elevations or was recharged during earlier, cooler-climate conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175068","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Beisner, K.R., Tillman, F.D., Anderson, J.R., Antweiler, R.C., and Bills, D.J., 2017, Geochemical characterization of groundwater discharging from springs north of the Grand Canyon, Arizona, 2009–2016: U.S. Geological Survey Scientific Investigations Report 2017–5068, 58 p., https://doi.org/10.3133/sir20175068.","productDescription":"Report: vi, 58 p.; 6 Appendixes","onlineOnly":"Y","ipdsId":"IP-084230","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":344518,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5068/sir20175068_appendixes.xlsx","text":"Appendixes 1–6","size":"85 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5068"},{"id":344517,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5068/sir20175068_.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5068"},{"id":344516,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5068/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.4,\n 35.6\n ],\n [\n -111.6,\n 35.6\n ],\n [\n -111.6,\n 37\n ],\n [\n -113.4,\n 37\n ],\n [\n -113.4,\n 35.6\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
(520) 670-6671
Landscape capability (LC) models are a spatial tool with potential applications in conservation planning. We used survey data to validate LC models as predictors of occurrence and abundance at broad and fine scales for American woodcock (Scolopax minor) and ruffed grouse (Bonasa umbellus). Landscape capability models were reliable predictors of occurrence but were less indicative of relative abundance at route (11.5–14.6 km) and point scales (0.5–1 km). As predictors of occurrence, LC models had high sensitivity (0.71–0.93) and were accurate (0.71–0.88) and precise (0.88 and 0.92 for woodcock and grouse, respectively). Models did not predict point-scale abundance independent of the ability to predict occurrence of either species. The LC models are useful predictors of patterns of occurrences in the northeastern United States, but they have limited utility as predictors of fine-scale or route-specific abundances.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21265","usgsCitation":"Loman, Z., Blomberg, E.J., DeLuca, W., Harrison, D.J., Loftin, C., and Wood, P.B., 2017, Landscape capability predicts upland game bird abundance and occurrence: Journal of Wildlife Management, v. 81, no. 6, p. 1110-1116, https://doi.org/10.1002/jwmg.21265.","productDescription":"7 p.","startPage":"1110","endPage":"1116","ipdsId":"IP-076384","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348595,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"81","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-27","publicationStatus":"PW","scienceBaseUri":"5a06c8cae4b09af898c86104","contributors":{"authors":[{"text":"Loman, Zachary G.","contributorId":145932,"corporation":false,"usgs":false,"family":"Loman","given":"Zachary G.","affiliations":[],"preferred":false,"id":721640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blomberg, Erik J.","contributorId":17543,"corporation":false,"usgs":false,"family":"Blomberg","given":"Erik","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":721641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeLuca, William","contributorId":192836,"corporation":false,"usgs":false,"family":"DeLuca","given":"William","affiliations":[],"preferred":false,"id":721642,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harrison, Daniel J.","contributorId":200256,"corporation":false,"usgs":false,"family":"Harrison","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":721643,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719130,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":721644,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}