Aftershocks (earthquakes clustered spatially and chronologically near the occurrence of a causative earthquake) are ongoing in southwestern Puerto Rico after a series of earthquakes, which include a magnitude 6.4 earthquake that occurred near Barrio Indios, Guayanilla, on January 7, 2020, and affected the surrounding area. This report estimates the expected duration of these aftershocks by incorporating observations of aftershocks as of January 17, 2020, into a well-established statistical model of how earthquake sequences behave. Aftershocks will persist for years to decades, although with decreasing frequency, and earthquakes will likely be felt on a daily basis for up to several months. These estimates have significant uncertainty owing to different scenarios of how the earthquake sequence may evolve over time and could also change if a new large aftershock occurs. This report also estimates the amount of time remaining until the annual probability of magnitude 5, 6, and 7 or greater aftershocks—which could cause additional damage—decreases to 50, 25, 10, 5, and 1 percent. As of this writing, the chance of having a magnitude 6 or greater earthquake within a given year, going forward, will not fall below 25 percent for another 3 months to 3 years. The chance of having a magnitude 5 or greater earthquake will not fall below 25 percent for a decade or more. The aftershocks discussed in this report would be located in the same general area as the aftershocks that have already occurred. Our results do not imply a change in the risk of earthquakes in other parts of Puerto Rico.
Las réplicas (terremotos agrupados espacial y cronológicamente cerca de la ocurrencia de un terremoto causante) están en curso en el suroeste de Puerto Rico después de una serie de terremotos, que incluyen un terremoto de magnitud 6.4, ocurrido cerca del Barrio Indios, Guayanilla, el 7 de enero de 2020 y que afectaron las áreas circundantes. Este informe estima la duración esperada de las réplicas incorporando observaciones de réplicas a partir del 17 de enero de 2020 en un modelo estadístico bien establecido de cómo se comportan las secuencias de terremotos. Las réplicas persistirán durante años o décadas, aunque con una frecuencia decreciente, y los terremotos probablemente se sentirán a diario durante varios meses. Estos estimados tienen una incertidumbre significativa debido a diferentes escenarios de cómo la secuencia del terremoto puede evolucionar con el tiempo y también podrían cambiar si ocurre una nueva réplica grande. Este informe también estima la cantidad de tiempo restante hasta que la probabilidad anual de réplicas de magnitud 5, 6 y 7 o más - que podría causar daños adicionales- disminuya a un 50, 25, 10, 5 y 1 por ciento. Al momento de escribir este artículo, la posibilidad de tener un terremoto de magnitud 6 en un año determinado, en el futuro, no caerá por debajo del 25 por ciento durante otros 3 meses a 3 años. La probabilidad de tener un terremoto de magnitud 5 o mayor no será inferior al 25 por ciento durante una década o más. Las réplicas discutidas en este informe se ubicarían en la misma área general que las réplicas que ya han ocurrido. Nuestros resultados no implican un cambio en el riesgo de terremotos en otras partes de Puerto Rico.
","language":"English, Spanish","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201009","usgsCitation":"van der Elst, N.J., Hardebeck, J.L., and Michael, A.J., 2020, Potential duration of aftershocks of the 2020 southwestern Puerto Rico earthquake: U.S. Geological Survey Open-File Report 2020–1009, 5 p., https://doi.org/10.3133/ofr20201009.","productDescription":"v, 5 p.","onlineOnly":"Y","ipdsId":"IP-115560","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":399452,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109627.htm"},{"id":371666,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1009/coverthb.jpg"},{"id":371665,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1009/ofr20201009_spanish.pdf","text":"Report (Español)","linkFileType":{"id":1,"text":"pdf"}},{"id":371664,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1009/ofr20201009.pdf","text":"Report (English)","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.21,\n 17.7683\n ],\n [\n -66.5942,\n 17.7683\n ],\n [\n -66.5942,\n 18.0558\n ],\n [\n -67.21,\n 18.0558\n ],\n [\n -67.21,\n 17.7683\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, California 94025
Historical cross-shore positions of the shoreline and dune base were used as inputs for a Kalman filter algorithm to forecast the positions of these features in the year 2028. The beach width was also computed as the cross-shore distance between the forecasted 2028 shoreline and dune-base positions. While it does not evaluate the suitability of a nesting beach or identify optimal nesting habitat, the beach width can be used as a proxy for habitat availability. An analysis was conducted along the Florida Atlantic coast with an initial goal of demonstrating a method that combines available data for shoreline and dune positions with a Kalman Filter algorithm developed to predict decadal-scale shoreline evolution and then uses these features to define future beach width. This section of the southeastern United States hosts the largest assemblage of nesting loggerhead sea turtles (Caretta caretta) in the world, in addition to other species, and critical habitat is designated as part of the species’ listing package under the Endangered Species Act of 1973 (16 U.S.C. ch. 35 § 1531 et seq) for most of the nesting beaches within the study area. This work introduces an approach to inform ecosystem services assessments using data typically derived for shoreline change and storm vulnerability models.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191150","usgsCitation":"Long, J.W., Henderson, R.E., and Thompson, D.M., 2020, Forecasting future beach width—A case study along the Florida Atlantic coast: U.S. Geological Survey Open-File Report 2019–1150, 13 p., https://doi.org/10.3133/ofr20191150.","productDescription":"vi, 13 p.","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-112427","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":371572,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1150/coverthb.jpg"},{"id":371577,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1150/ofr20191150.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1150"},{"id":399439,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109625.htm"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.771484375,\n 25.16517336866393\n ],\n [\n -80.09033203125,\n 25.264568475331583\n ],\n [\n -79.5849609375,\n 26.62781822639305\n ],\n [\n -80.244140625,\n 28.013801376380712\n ],\n [\n -81.23291015625,\n 30.751277776257812\n ],\n [\n -81.76025390625,\n 30.770159115784214\n ],\n [\n -81.73828125,\n 30.334953881988564\n ],\n [\n -80.947265625,\n 28.401064827220896\n ],\n [\n -80.419921875,\n 27.11781284232125\n ],\n [\n -80.35400390625,\n 26.43122806450644\n ],\n [\n -80.771484375,\n 25.16517336866393\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
The Mississippi Barrier Islands in the northern Gulf of Mexico experienced high rates of spatial change over recorded history. Wave-induced sediment transport induced island migration, landward retreat, and inlet evolution. These processes can be measured using repeat bathymetric surveys to analyze elevation change over time. This study analyzes digital elevation models created from three time periods where bathymetric data have been collected: the 1920s, 2009, and 2016. The models are compared to assess volumetric change between surveys and characterize morphologic responses to natural and human-influenced processes. Although all the islands within the study area experienced a loss of area over the period of study, the nearshore and tidal inlets experience both accretion and erosion that vary spatially and temporally. Major morphologic changes include westward island migration, expanding ebb-tidal deltas, and changes in inlet dimensions. This study is a collaboration between the U.S. Geological Survey, the U.S. Army Corps of Engineers, and the National Park Service to establish baseline physical and pre-restoration morphologic conditions preceding a major restoration of the islands as part of the Mississippi Coastal Improvement Project.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191140","usgsCitation":"Flocks, J.G., Buster, N.A., and Brenner, O.T., 2020, Seafloor change around the Mississippi barrier islands, 1920 to 2016—The influence of storm effects on inlet and island morphodynamics: U.S. Geological Survey Open-File Report 2019–1140, 23 p., https://doi.org/10.3133/ofr20191140.","productDescription":"vi, 23 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-106950","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":371197,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1140/coverthb.jpg"},{"id":371199,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1140/ofr20191140.pdf","text":"Report","size":"7.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1140"}],"country":"United States","otherGeospatial":"Mississippi barrier islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.91113281249999,\n 28.76765910569123\n ],\n [\n -87.4951171875,\n 28.76765910569123\n ],\n [\n -87.4951171875,\n 30.977609093348686\n ],\n [\n -93.91113281249999,\n 30.977609093348686\n ],\n [\n -93.91113281249999,\n 28.76765910569123\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
To assess and track changes to the rocky subtidal communities surrounding San Nicolas Island, the U.S. Navy entered into an agreement with the U.S. Geological Survey (USGS) in 2014 to conduct an ecological monitoring program at several sites around the island. Four permanent sites—Nav Fac 100, West End, Dutch Harbor, and Daytona 100—were established. The sites were based on ones that had been monitored since 1980 by USGS and were combined or expanded for better comparability with monitoring programs conducted at the other California Channel Islands. At the sites, scientists from USGS and our cooperator, the University of California, Santa Cruz, measured bottom cover of algae and sessile invertebrate species in quadrats, counted and sized fish on swimming transects, and counted a suite of kelps and invertebrates on benthic band transects. Holdfast diameter and number of stipes of giant kelp (Macrocystis pyrifera) were recorded on these transects, and size data were collected for urchins, sea stars, and shelled mollusks. Bottom temperatures were recorded at hourly intervals by archival data loggers that were deployed at the sites. This report focuses primarily on data collected in fall 2017 and spring 2018 and makes comparisons with data collected in previous years, beginning in fall 2014.
Nav Fac 100 is a site with a relatively low benthic profile, situated on the north side of San Nicolas Island. It was previously urchin dominated but underwent a dramatic decline in purple sea urchins in 2015 and 2016. Since then, macroalgae has become more prevalent as both annual brown algae, such as Dictyota, and perennials (for example, Cystoseira) have become established. The invasive brown alga Sargassum horneri has also become established. West End, on the southwest side of the island, also lacks much bottom relief but has more crevice habitat associated with boulders. It remains dominated by kelps and red algae, but red algae have decreased recently. Dutch Harbor, on the south side, has many high relief rocky reefs and had the greatest fish and non-motile invertebrate densities. It remains the most stable of the sites. Daytona 100, on the southeast side, has moderate relief and has remained a patchwork of kelp and urchin dominated areas with moderate fish density.
The main change at the sites during the last 4 years was the decline in urchin numbers at Nav Fac 100. There was storm-related mortality and subsequent recruitment in the M. pyrifera population at several of the sites in both 2016 and 2017. The winter of 2018, however, was relatively mild, with less destructive storm-related disturbance. The invasive brown alga S. horneri, first seen at San Nicolas Island at Nav Fac 100 in fall 2015, has become firmly established there during the last 2 sampling years. Finally, moderate increases were observed in purple urchin densities at all sites this spring. Long-term data are presented to illustrate trends and changes over the past three decades. Results indicate continued monitoring to evaluate ecosystem effects from perturbations owing to natural processes and anthropomorphic factors, including recovery of the sea otter population, changes in fisheries, invasive species and changing environmental conditions, could be valuable to inform managers’ decision-making.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191147","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Kenner, M.C., and Tomoleoni, J., 2020, Kelp forest monitoring at Naval Base Ventura County, San Nicolas Island, California: Fall 2017 and Spring 2018, Fourth Annual Report: U.S. Geological Survey Open-File Report 2019–1147, 76 p., https://doi.org/10.3133/ofr20191147.","productDescription":"vi, 76 p.","numberOfPages":"76","onlineOnly":"Y","ipdsId":"IP-111796","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":399434,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109596.htm"},{"id":371253,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1147/coverthb.jpg"},{"id":371254,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1147/ofr20191147.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2019-1147"}],"country":"United States","state":"California","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.64111328125,\n 33.18353672893615\n ],\n [\n -119.37744140625,\n 33.18353672893615\n ],\n [\n -119.37744140625,\n 33.32134852669881\n ],\n [\n -119.64111328125,\n 33.32134852669881\n ],\n [\n -119.64111328125,\n 33.18353672893615\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 primary objective of the project was to locate previously unknown stands of mast-producing hardwood forest trees in the Upper Mississippi River floodplain using existing information. We located and mapped 399 previously unknown hardwood forest stands within the Mississippi River floodplain area of navigation pools 9, 10, and 11. Using color infrared images in combination with true-color imagery was useful for identifying hardwood forest stands. We recommend our result be refined by visiting the forest stands we identified to evaluate our classification rate and determine which stands are regenerating. In combination with regeneration information, our results can help better inform flood inundation modeling, which will help improve the efficacy of restoration design. Although we had some success using the best available information, to obtain more relevant observations, we recommend acquiring color infrared aerial imagery during the late fall season if providing detailed mapping of forest stands is a management priority. Imagery of this type collected in the fall, when trees may be distinguished by their differing senescence, has the potential to uniquely identify individual species or perhaps even individual trees. Gaining a better understanding of forest diversity and developing conservation strategies to preserve that diversity is timely because remaining aging trees, established before lock-and-dam installation on the Mississippi River, are nearing the end of their life expectancy.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191089","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Hanson, J.L., King, R., Hoy, E.E., 2019, Remnant hardwood forest mapping within the Upper Mississippi River floodplain: U.S. Geological Survey Open-File Report 2019–1089, 10 p., https://doi.org/10.3133/ofr20191089.","productDescription":"Report: vi, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-102264","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":399413,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109582.htm"},{"id":370698,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1089/ofr20191089.pdf","text":"Report","size":"4.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1089"},{"id":370697,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1089/coverthb.jpg"},{"id":370699,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TD9WNW","text":"USGS data release","description":"USGS Data Release","linkHelpText":"FWS McGregor District Mast Hardwood Floodplain Forest Community"}],"country":"United States","state":"Iowa, Minnesota, Wisconsin","otherGeospatial":"Upper Mississippi floodplain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.42822265625,\n 43.67581809328341\n ],\n [\n -91.5380859375,\n 43.6599240747891\n ],\n [\n -91.49414062499999,\n 43.48481212891603\n ],\n [\n -91.60400390625,\n 43.100982876188546\n ],\n [\n -91.2744140625,\n 42.65012181368022\n ],\n [\n -90.81298828125,\n 42.52069952914966\n ],\n [\n -90.37353515625,\n 42.52069952914966\n ],\n [\n -90.68115234375,\n 42.97250158602597\n ],\n [\n -90.72509765625,\n 43.30919109985686\n ],\n [\n -91.01074218749999,\n 43.61221676817573\n ],\n [\n -91.42822265625,\n 43.67581809328341\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54602
Federal agencies need credible scientific information to determine the production and value of ecosystem services in an efficient and timely manner. The U.S. Geological Survey addresses this scientific information need through the Sustaining Environmental Capital Initiative project. The project has relied on U.S. Geological Survey expertise related to water, fisheries, advanced modeling, and economics and other social sciences to conduct eight case studies across a range of environment types, including water-based environments, deserts, sagebrush ecosystems, floodplains, and forests. The Sustaining Environmental Capital Initiative also supported the development and expansion of four tools with the intent of adding content and usability for partners’ decision-making needs. The tools are the Natural Value Resource Center, Benefit Transfer Toolkit, Riverine Environmental Flow Decision Support System, and Artificial Intelligence for Ecosystem Services modeling platform.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191117","usgsCitation":"Huber, C., Meldrum, J.R., Schuster, R.M., Ancona, Z.H., Bagstad, K.J., Beck, S.M., Carlisle, D.M., Claggett, P.R., Franco, F., Galbraith, H.S., Haefele, M., Hoelting, K.R., Hogan, D.M., Hopkins, K.G., Kern, T., Lawrence, C.B., Lischka, S., Loomis, J.B., Mueller, J.M., Noe, G.B., Pindilli, E.J., Quay, B., Semmens, D.J., Sinclair, W., Spooner, D.E., Voigt, B., and St. John White, B., 2020, Sustaining Environmental Capital Initiative summary report: U.S. Geological Survey Open-File Report 2019–1117, 23 p., https://doi.org/10.3133/ofr20191117.","productDescription":"v, 23 p.","onlineOnly":"Y","ipdsId":"IP-099772","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":370958,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1117/ofr20191117.pdf","text":"Report","size":"348 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1117"},{"id":370957,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1117/coverthb.jpg"}],"contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
This report estimates the economic impacts on the Wyoming economy from investments made by the Wyoming Landscape Conservation Initiative (WLCI) on conservation and restoration projects. The WLCI has been working in southwestern Wyoming since 2007 to coordinate science and management decisions among government and private entities that invest in conservation projects aimed at restoring and enhancing wildlife habitat. These investments support jobs and generate business activities within the Wyoming economy. WLCI conservation and restoration projects occur on both publicly managed and privately owned lands and are supported by leveraging funds from Federal bureaus, Wyoming State and local government agencies, and private contributions. During 2007–2018, the WLCI invested a total of more than $69,100,000 (in 2018 dollars) on conservation projects within the State of Wyoming. These pooled funds have been used to purchase conservation easements and hire business contractors to complete restoration projects, with 98 percent of project funds awarded to Wyoming-based businesses. Including both direct and secondary effects, the U.S. Geological Survey estimates that local spending on these conservation and restoration projects during 2007–2018 supported an estimated 1,055 job-years (the number of annualized full- and part-time jobs generated or supported), more than $30,500,000 in labor income, almost $40,900,000 in value added, and almost $68,200,000 in economic output within the Wyoming economy. These results demonstrate how investments in WLCI conservation projects support jobs, livelihoods, small businesses, and rural economies in Wyoming.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191135","isbn":"978-1-4113-4342-9","usgsCitation":"Huber, C., Flyr, M., and Cullinane Thomas, C., 2020, Economic impacts of Wyoming Landscape Conservation Initiative conservation projects in Wyoming: U.S. Geological Survey Open-File Report 2019–1135, 11 p., https://doi.org/10.3133/ofr20191135","productDescription":"iv, 11 p.","onlineOnly":"N","ipdsId":"IP-111077","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":370967,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1135/coverthb.jpg"},{"id":370968,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1135/ofr20191135.pdf","text":"Report","size":"384 kB ","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1135"}],"country":"United States","state":"Wyoming","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-110.048476,40.997555],[-110.121639,40.997101],[-110.125709,40.99655],[-110.237848,40.995427],[-110.250709,40.996089],[-110.375714,40.994947],[-110.500718,40.994746],[-110.539819,40.996346],[-110.715026,40.996347],[-110.750727,40.996847],[-111.046723,40.997959],[-111.046551,41.251716],[-111.0466,41.360692],[-111.046264,41.377731],[-111.045789,41.565571],[-111.045818,41.579845],[-111.046689,42.001567],[-111.047109,42.142497],[-111.047107,42.148971],[-111.047058,42.182672],[-111.047097,42.194773],[-111.047074,42.280787],[-111.04708,42.34942],[-111.046801,42.504946],[-111.046719,42.513118],[-111.046017,42.582723],[-111.043564,42.722624],[-111.044135,42.874924],[-111.043959,42.96445],[-111.043957,42.969482],[-111.043924,42.975063],[-111.044129,43.018702],[-111.044156,43.020052],[-111.044206,43.022614],[-111.044034,43.024581],[-111.044034,43.024844],[-111.044033,43.026411],[-111.044094,43.02927],[-111.043997,43.041415],[-111.044058,43.04464],[-111.044063,43.046302],[-111.044086,43.054819],[-111.044117,43.060309],[-111.04415,43.066172],[-111.044162,43.068222],[-111.044143,43.072364],[-111.044235,43.177121],[-111.044266,43.177236],[-111.044232,43.18444],[-111.044168,43.189244],[-111.044229,43.195579],[-111.044617,43.31572],[-111.045205,43.501136],[-111.045706,43.659112],[-111.04588,43.681033],[-111.046118,43.684902],[-111.046051,43.685812],[-111.04611,43.687848],[-111.046421,43.722059],[-111.046435,43.726545],[-111.04634,43.726957],[-111.046715,43.815832],[-111.046515,43.908376],[-111.046917,43.974978],[-111.047064,43.983467],[-111.047349,43.999921],[-111.049077,44.020072],[-111.048751,44.060403],[-111.048751,44.060838],[-111.048633,44.062903],[-111.048452,44.114831],[-111.049119,44.124923],[-111.049695,44.353626],[-111.049148,44.374925],[-111.049216,44.435811],[-111.049194,44.438058],[-111.048974,44.474072],[-111.055208,44.624927],[-111.055333,44.666263],[-111.055511,44.725343],[-111.056416,44.749928],[-111.056888,44.866658],[-111.055629,44.933578],[-111.056207,44.935901],[-111.055199,45.001321],[-111.044275,45.001345],[-110.785008,45.002952],[-110.761554,44.999934],[-110.750767,44.997948],[-110.705272,44.992324],[-110.552433,44.992237],[-110.547165,44.992459],[-110.48807,44.992361],[-110.402927,44.99381],[-110.362698,45.000593],[-110.342131,44.999053],[-110.324441,44.999156],[-110.28677,44.99685],[-110.199503,44.996188],[-110.110103,45.003905],[-110.026347,45.003665],[-110.025544,45.003602],[-109.99505,45.003174],[-109.875735,45.003275],[-109.798687,45.002188],[-109.75073,45.001605],[-109.663673,45.002536],[-109.574321,45.002631],[-109.386432,45.004887],[-109.375713,45.00461],[-109.269294,45.005283],[-109.263431,45.005345],[-109.103445,45.005904],[-109.08301,44.99961],[-109.062262,44.999623],[-108.621313,45.000408],[-108.578484,45.000484],[-108.565921,45.000578],[-108.500679,44.999691],[-108.271201,45.000251],[-108.249345,44.999458],[-108.238139,45.000206],[-108.218479,45.000541],[-108.14939,45.001062],[-108.000663,45.001223],[-107.997353,45.001565],[-107.911743,45.001292],[-107.750654,45.000778],[-107.608854,45.00086],[-107.607824,45.000929],[-107.49205,45.00148],[-107.351441,45.001407],[-107.13418,45.000109],[-107.125633,44.999388],[-107.105685,44.998734],[-107.084939,44.996599],[-107.074996,44.997004],[-107.050801,44.996424],[-106.892875,44.995947],[-106.888773,44.995885],[-106.263586,44.993788],[-106.024814,44.993688],[-105.928184,44.993647],[-105.914258,44.999986],[-105.913382,45.000941],[-105.848065,45.000396],[-105.076607,45.000347],[-105.038405,45.000345],[-105.025266,45.00029],[-105.019284,45.000329],[-105.01824,45.000437],[-104.765063,44.999183],[-104.759855,44.999066],[-104.72637,44.999518],[-104.665171,44.998618],[-104.663882,44.998869],[-104.470422,44.998453],[-104.470117,44.998453],[-104.250145,44.99822],[-104.057698,44.997431],[-104.055914,44.874986],[-104.056496,44.867034],[-104.055963,44.768236],[-104.055963,44.767962],[-104.055934,44.72372],[-104.05587,44.723422],[-104.055777,44.700466],[-104.055938,44.693881],[-104.05581,44.691343],[-104.055877,44.571016],[-104.055892,44.543341],[-104.055927,44.51773],[-104.055389,44.249983],[-104.054487,44.180381],[-104.054562,44.141081],[-104.05495,43.93809],[-104.055077,43.936535],[-104.055488,43.853477],[-104.055488,43.853476],[-104.055138,43.750421],[-104.055133,43.747105],[-104.054902,43.583852],[-104.054885,43.583512],[-104.05484,43.579368],[-104.055032,43.558603],[-104.054787,43.503328],[-104.054786,43.503072],[-104.054779,43.477815],[-104.054766,43.428914],[-104.054614,43.390949],[-104.054403,43.325914],[-104.054218,43.30437],[-104.053884,43.297047],[-104.053876,43.289801],[-104.053127,43.000585],[-104.052863,42.754569],[-104.052809,42.749966],[-104.052583,42.650062],[-104.052741,42.633982],[-104.052586,42.630917],[-104.052773,42.611766],[-104.052775,42.61159],[-104.052775,42.610813],[-104.053107,42.499964],[-104.052776,42.25822],[-104.052793,42.249962],[-104.053125,42.249962],[-104.052761,42.170278],[-104.052547,42.166801],[-104.053001,42.137254],[-104.052738,42.133769],[-104.0526,42.124963],[-104.052954,42.089077],[-104.052967,42.075004],[-104.05288,42.021761],[-104.052729,42.016318],[-104.052704,42.001718],[-104.052699,41.998673],[-104.052761,41.994967],[-104.05283,41.9946],[-104.052856,41.975958],[-104.052734,41.973007],[-104.052991,41.914973],[-104.052931,41.906143],[-104.053026,41.885464],[-104.052774,41.733401],[-104.05283,41.697954],[-104.052913,41.64519],[-104.052945,41.638167],[-104.052975,41.622931],[-104.052735,41.613676],[-104.052859,41.592254],[-104.05254,41.564274],[-104.052531,41.552723],[-104.052584,41.55265],[-104.052692,41.541154],[-104.052686,41.539111],[-104.052476,41.522343],[-104.052478,41.515754],[-104.05234,41.417865],[-104.05216,41.407662],[-104.052287,41.393307],[-104.052288,41.393214],[-104.052687,41.330569],[-104.052324,41.321144],[-104.052476,41.320961],[-104.052568,41.316202],[-104.052453,41.278202],[-104.052574,41.278019],[-104.052666,41.275251],[-104.053514,41.157257],[-104.053142,41.114457],[-104.053083,41.104985],[-104.053025,41.090274],[-104.053177,41.089725],[-104.053097,41.018045],[-104.053158,41.016809],[-104.053249,41.001406],[-104.066961,41.001504],[-104.086068,41.001563],[-104.10459,41.001543],[-104.123586,41.001626],[-104.211473,41.001591],[-104.214191,41.001568],[-104.214692,41.001657],[-104.467672,41.001473],[-104.497058,41.001805],[-104.497149,41.001828],[-104.675999,41.000957],[-104.829504,40.99927],[-104.855273,40.998048],[-104.943371,40.998084],[-105.254779,40.99821],[-105.256527,40.998191],[-105.27686,40.998173],[-105.277138,40.998173],[-105.724804,40.99691],[-105.730421,40.996886],[-106.061181,40.996999],[-106.190554,40.997607],[-106.217573,40.997734],[-106.321165,40.999123],[-106.386356,41.001144],[-106.391852,41.001176],[-106.43095,41.001752],[-106.437419,41.001795],[-106.439563,41.001978],[-106.453859,41.002057],[-106.857773,41.002663],[-107.000606,41.003444],[-107.241194,41.002804],[-107.317794,41.002967],[-107.367443,41.003073],[-107.625624,41.002124],[-107.918421,41.002036],[-108.046539,41.002064],[-108.181227,41.000455],[-108.250649,41.000114],[-108.500659,41.000112],[-108.526667,40.999608],[-108.631108,41.000156],[-108.884138,41.000094],[-109.050076,41.000659],[-109.173682,41.000859],[-109.231985,41.002059],[-109.250735,41.001009],[-109.500694,40.999127],[-109.534926,40.998143],[-109.676421,40.998395],[-109.713877,40.998266],[-109.715409,40.998191],[-109.854302,40.997661],[-109.855299,40.997614],[-109.97553,40.997912],[-109.999838,40.99733],[-110.000708,40.997352],[-110.006495,40.997815],[-110.048476,40.997555]]]},\"properties\":{\"name\":\"Wyoming\",\"nation\":\"USA \"}}]}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
Rare earth elements (REEs) are critical mineral commodities for the United States. In response to a need for information on potential domestic sources of REEs in mineral deposits, the U.S. Geological Survey (USGS) identified broad focus areas throughout the conterminous United States and Alaska as a guide for selecting new geoscience research areas. This study was done to support the USGS Earth Mapping Resources Initiative (Earth MRI).
Focus areas are identified in four regions of the United States (Alaska, West, Central, and East) by mineral deposit type. The areas are described in a companion USGS data release that consists of a map in a geographic information system and accompanying tables that document the rationale for each focus area (C.L. Dicken and others, 2019, https://doi.org/10.5066/P95CHIL0). This open-file report describes the methodology that was used to identify focus areas and determine new data acquisition needs. Deposit types that are likely to be of interest for future exploration and development of domestic nonfuel REE resources include deposits associated with carbonatites and peralkaline rocks, iron oxide-apatite deposits, monazite-bearing placers, and REE-enriched phosphorites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191023A","usgsCitation":"Hammarstrom, J.H., and Dicken, C.L., 2019, Focus areas for data acquisition for potential domestic sources of critical minerals—Rare earth elements (ver. 1.1, July 2022), chap. A of U.S. Geological Survey, Focus areas for data acquisition for potential domestic sources of critical minerals: U.S. Geological Survey Open-File Report 2019–1023, 11 p, https://doi.org/10.3133/ofr20191023A.","productDescription":"Report: vi, 11 p.; Data Release","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-104700","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":501521,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_108444.htm","linkFileType":{"id":5,"text":"html"}},{"id":403730,"rank":9,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/ofr20191023E","text":"Open-File Report 2019-1023-E","linkHelpText":"- Alaska Focus Area Definition for Data Acquisition for Potential Domestic Sources of Critical Minerals in Alaska for Antimony, Barite, Beryllium, Chromium, Fluorspar, Hafnium, Magnesium, Manganese, Uranium, Vanadium, and Zirconium"},{"id":403727,"rank":6,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/ofr20191023B","text":"Open-File Report 2019-1023-B","linkHelpText":"- Focus Areas for Data Acquisition for Potential Domestic Resources of 11 Critical Minerals in the Conterminous United States, Hawaii, and Puerto Rico—Aluminum, Cobalt, Graphite, Lithium, Niobium, Platinum-Group Elements, Rare Earth Elements, Tantalum, Tin, Titanium, and Tungsten"},{"id":403468,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2019/1023/a/versionHist.txt","size":"2.97 KB","linkFileType":{"id":2,"text":"txt"}},{"id":361988,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95CHIL0","text":"USGS data release","description":"USGS data release"},{"id":361987,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20193007","text":"Fact Sheet 2019–3007","linkHelpText":"- The Earth Mapping Resources Initiative (Earth MRI): Mapping the Nation’s Critical Mineral Resources"},{"id":361986,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1023/a/ofr20191023a.pdf","text":"Report","size":"1.65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1023"},{"id":420419,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1023/a/coverthb2.jpg"},{"id":403729,"rank":8,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/ofr20191023D","text":"Open-File Report 2019-1023-D","linkHelpText":"- Focus Areas for Data Acquisition for Potential Domestic Resources of 13 Critical Minerals in the Conterminous United States and Puerto Rico—Antimony, Barite, Beryllium, Chromium, Fluorspar, Hafnium, Helium, Magnesium, Manganese, Potash, Uranium, Vanadium, and Zirconium"},{"id":403728,"rank":7,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/ofr20191023C","text":"Open-File Report 2019-1023-C","linkHelpText":"- Focus Areas for Data Acquisition for Potential Domestic Resources of 11 Critical Minerals in Alaska—Aluminum, Cobalt, Graphite, Lithium, Niobium, Platinum Group Elements, Rare Earth Elements, Tantalum, Tin, Titanium, and Tungsten"}],"country":"United States","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-66.28243,18.51476],[-65.7713,18.42668],[-65.591,18.22803],[-65.84716,17.97591],[-66.59993,17.98182],[-67.18416,17.94655],[-67.24243,18.37446],[-67.10068,18.5206],[-66.28243,18.51476]]],[[[-155.54211,19.08348],[-155.68817,18.91619],[-155.93665,19.05939],[-155.90806,19.33888],[-156.07347,19.70294],[-156.02368,19.81422],[-155.85008,19.97729],[-155.91907,20.17395],[-155.86108,20.26721],[-155.78505,20.2487],[-155.40214,20.07975],[-155.22452,19.99302],[-155.06226,19.8591],[-154.80741,19.50871],[-154.83147,19.45328],[-155.22217,19.23972],[-155.54211,19.08348]]],[[[-156.07926,20.64397],[-156.41445,20.57241],[-156.58673,20.783],[-156.70167,20.8643],[-156.71055,20.92676],[-156.61258,21.01249],[-156.25711,20.91745],[-155.99566,20.76404],[-156.07926,20.64397]]],[[[-156.75824,21.17684],[-156.78933,21.06873],[-157.32521,21.09777],[-157.25027,21.21958],[-156.75824,21.17684]]],[[[-157.65283,21.32217],[-157.70703,21.26442],[-157.7786,21.27729],[-158.12667,21.31244],[-158.2538,21.53919],[-158.29265,21.57912],[-158.0252,21.71696],[-157.94161,21.65272],[-157.65283,21.32217]]],[[[-159.34512,21.982],[-159.46372,21.88299],[-159.80051,22.06533],[-159.74877,22.1382],[-159.5962,22.23618],[-159.36569,22.21494],[-159.34512,21.982]]],[[[-94.81758,49.38905],[-94.64,48.84],[-94.32914,48.67074],[-93.63087,48.60926],[-92.61,48.45],[-91.64,48.14],[-90.83,48.27],[-89.6,48.01],[-89.27292,48.01981],[-88.37811,48.30292],[-87.43979,47.94],[-86.46199,47.55334],[-85.65236,47.22022],[-84.87608,46.90008],[-84.77924,46.6371],[-84.54375,46.53868],[-84.6049,46.4396],[-84.3367,46.40877],[-84.14212,46.51223],[-84.09185,46.27542],[-83.89077,46.11693],[-83.61613,46.11693],[-83.46955,45.99469],[-83.59285,45.81689],[-82.55092,45.34752],[-82.33776,44.44],[-82.13764,43.57109],[-82.43,42.98],[-82.9,42.43],[-83.12,42.08],[-83.142,41.97568],[-83.02981,41.8328],[-82.69009,41.67511],[-82.43928,41.67511],[-81.27775,42.20903],[-80.24745,42.3662],[-78.93936,42.86361],[-78.92,42.965],[-79.01,43.27],[-79.17167,43.46634],[-78.72028,43.62509],[-77.73789,43.62906],[-76.82003,43.62878],[-76.5,44.01846],[-76.375,44.09631],[-75.31821,44.81645],[-74.867,45.00048],[-73.34783,45.00738],[-71.50506,45.0082],[-71.405,45.255],[-71.08482,45.30524],[-70.66,45.46],[-70.305,45.915],[-69.99997,46.69307],[-69.23722,47.44778],[-68.905,47.185],[-68.23444,47.35486],[-67.79046,47.06636],[-67.79134,45.70281],[-67.13741,45.13753],[-66.96466,44.8097],[-68.03252,44.3252],[-69.06,43.98],[-70.11617,43.68405],[-70.64548,43.09024],[-70.81489,42.8653],[-70.825,42.335],[-70.495,41.805],[-70.08,41.78],[-70.185,42.145],[-69.88497,41.92283],[-69.96503,41.63717],[-70.64,41.475],[-71.12039,41.49445],[-71.86,41.32],[-72.295,41.27],[-72.87643,41.22065],[-73.71,40.9311],[-72.24126,41.11948],[-71.945,40.93],[-73.345,40.63],[-73.982,40.628],[-73.95232,40.75075],[-74.25671,40.47351],[-73.96244,40.42763],[-74.17838,39.70926],[-74.90604,38.93954],[-74.98041,39.1964],[-75.20002,39.24845],[-75.52805,39.4985],[-75.32,38.96],[-75.07183,38.78203],[-75.05673,38.40412],[-75.37747,38.01551],[-75.94023,37.21689],[-76.03127,37.2566],[-75.72205,37.93705],[-76.23287,38.31921],[-76.35,39.15],[-76.54272,38.71762],[-76.32933,38.08326],[-76.99,38.23999],[-76.30162,37.91794],[-76.25874,36.9664],[-75.9718,36.89726],[-75.86804,36.55125],[-75.72749,35.55074],[-76.36318,34.80854],[-77.39763,34.51201],[-78.05496,33.92547],[-78.55435,33.86133],[-79.06067,33.49395],[-79.20357,33.15839],[-80.30132,32.50935],[-80.86498,32.0333],[-81.33629,31.44049],[-81.49042,30.72999],[-81.31371,30.03552],[-80.98,29.18],[-80.53558,28.47213],[-80.53,28.04],[-80.05654,26.88],[-80.08801,26.20576],[-80.13156,25.81677],[-80.38103,25.20616],[-80.68,25.08],[-81.17213,25.20126],[-81.33,25.64],[-81.71,25.87],[-82.24,26.73],[-82.70515,27.49504],[-82.85526,27.88624],[-82.65,28.55],[-82.93,29.1],[-83.70959,29.93656],[-84.1,30.09],[-85.10882,29.63615],[-85.28784,29.68612],[-85.7731,30.15261],[-86.4,30.4],[-87.53036,30.27433],[-88.41782,30.3849],[-89.18049,30.31598],[-89.59383,30.15999],[-89.41373,29.89419],[-89.43,29.48864],[-89.21767,29.29108],[-89.40823,29.15961],[-89.77928,29.30714],[-90.15463,29.11743],[-90.88022,29.14854],[-91.62678,29.677],[-92.49906,29.5523],[-93.22637,29.78375],[-93.84842,29.71363],[-94.69,29.48],[-95.60026,28.73863],[-96.59404,28.30748],[-97.14,27.83],[-97.37,27.38],[-97.38,26.69],[-97.33,26.21],[-97.14,25.87],[-97.53,25.84],[-98.24,26.06],[-99.02,26.37],[-99.3,26.84],[-99.52,27.54],[-100.11,28.11],[-100.45584,28.69612],[-100.9576,29.38071],[-101.6624,29.7793],[-102.48,29.76],[-103.11,28.97],[-103.94,29.27],[-104.45697,29.57196],[-104.70575,30.12173],[-105.03737,30.64402],[-105.63159,31.08383],[-106.1429,31.39995],[-106.50759,31.75452],[-108.24,31.75485],[-108.24194,31.34222],[-109.035,31.34194],[-111.02361,31.33472],[-113.30498,32.03914],[-114.815,32.52528],[-114.72139,32.72083],[-115.99135,32.61239],[-117.12776,32.53534],[-117.29594,33.04622],[-117.944,33.62124],[-118.4106,33.74091],[-118.51989,34.02778],[-119.081,34.078],[-119.43884,34.34848],[-120.36778,34.44711],[-120.62286,34.60855],[-120.74433,35.15686],[-121.71457,36.16153],[-122.54747,37.55176],[-122.51201,37.78339],[-122.95319,38.11371],[-123.7272,38.95166],[-123.86517,39.76699],[-124.39807,40.3132],[-124.17886,41.14202],[-124.2137,41.99964],[-124.53284,42.76599],[-124.14214,43.70838],[-124.02053,44.6159],[-123.89893,45.52341],[-124.07963,46.86475],[-124.39567,47.72017],[-124.68721,48.18443],[-124.5661,48.37971],[-123.12,48.04],[-122.58736,47.096],[-122.34,47.36],[-122.5,48.18],[-122.84,49],[-120,49],[-117.03121,49],[-116.04818,49],[-113,49],[-110.05,49],[-107.05,49],[-104.04826,48.99986],[-100.65,49],[-97.22872,49.0007],[-95.15907,49],[-95.15609,49.38425],[-94.81758,49.38905]]],[[[-153.00631,57.11584],[-154.00509,56.73468],[-154.5164,56.99275],[-154.67099,57.4612],[-153.76278,57.81657],[-153.22873,57.96897],[-152.56479,57.90143],[-152.14115,57.59106],[-153.00631,57.11584]]],[[[-165.57916,59.90999],[-166.19277,59.75444],[-166.84834,59.94141],[-167.45528,60.21307],[-166.46779,60.38417],[-165.67443,60.29361],[-165.57916,59.90999]]],[[[-171.73166,63.78252],[-171.11443,63.59219],[-170.49111,63.69498],[-169.68251,63.43112],[-168.68944,63.29751],[-168.77194,63.1886],[-169.52944,62.97693],[-170.29056,63.19444],[-170.67139,63.37582],[-171.55306,63.31779],[-171.79111,63.40585],[-171.73166,63.78252]]],[[[-155.06779,71.14778],[-154.34417,70.69641],[-153.90001,70.88999],[-152.21001,70.82999],[-152.27,70.60001],[-150.73999,70.43002],[-149.72,70.53001],[-147.61336,70.21403],[-145.68999,70.12001],[-144.92001,69.98999],[-143.58945,70.15251],[-142.07251,69.85194],[-140.98599,69.712],[-140.9925,66.00003],[-140.99777,60.3064],[-140.013,60.27684],[-139.039,60.00001],[-138.34089,59.56211],[-137.4525,58.905],[-136.47972,59.46389],[-135.47583,59.78778],[-134.945,59.27056],[-134.27111,58.86111],[-133.35555,58.41029],[-132.73042,57.69289],[-131.70781,56.55212],[-130.00778,55.91583],[-129.97999,55.285],[-130.53611,54.80275],[-131.08582,55.17891],[-131.96721,55.49778],[-132.25001,56.37],[-133.53918,57.17889],[-134.07806,58.12307],[-135.03821,58.18771],[-136.62806,58.21221],[-137.80001,58.5],[-139.86779,59.53776],[-140.82527,59.72752],[-142.57444,60.08445],[-143.95888,59.99918],[-145.92556,60.45861],[-147.11437,60.88466],[-148.22431,60.67299],[-148.01807,59.97833],[-148.57082,59.91417],[-149.72786,59.70566],[-150.60824,59.36821],[-151.71639,59.15582],[-151.85943,59.74498],[-151.40972,60.7258],[-150.34694,61.03359],[-150.62111,61.28442],[-151.89584,60.7272],[-152.57833,60.06166],[-154.01917,59.35028],[-153.28751,58.86473],[-154.23249,58.14637],[-155.30749,57.72779],[-156.30833,57.42277],[-156.5561,56.97998],[-158.11722,56.46361],[-158.43332,55.99415],[-159.60333,55.56669],[-160.28972,55.64358],[-161.22305,55.36473],[-162.23777,55.02419],[-163.06945,54.68974],[-164.78557,54.40417],[-164.94223,54.57222],[-163.84834,55.03943],[-162.87,55.34804],[-161.80417,55.89499],[-160.5636,56.00805],[-160.07056,56.41806],[-158.68444,57.01668],[-158.4611,57.21692],[-157.72277,57.57],[-157.55027,58.32833],[-157.04167,58.91888],[-158.19473,58.6158],[-158.51722,58.78778],[-159.05861,58.42419],[-159.71167,58.93139],[-159.98129,58.57255],[-160.35527,59.07112],[-161.355,58.67084],[-161.96889,58.67166],[-162.05499,59.26693],[-161.87417,59.63362],[-162.51806,59.98972],[-163.81834,59.79806],[-164.66222,60.26748],[-165.34639,60.5075],[-165.35083,61.0739],[-166.12138,61.50002],[-165.73445,62.075],[-164.91918,62.63308],[-164.56251,63.14638],[-163.75333,63.21945],[-163.06722,63.05946],[-162.26056,63.54194],[-161.53445,63.45582],[-160.77251,63.76611],[-160.95834,64.2228],[-161.51807,64.40279],[-160.77778,64.7886],[-161.39193,64.77724],[-162.45305,64.55944],[-162.75779,64.33861],[-163.54639,64.55916],[-164.96083,64.44695],[-166.42529,64.68667],[-166.845,65.0889],[-168.11056,65.67],[-166.70527,66.08832],[-164.47471,66.57666],[-163.65251,66.57666],[-163.7886,66.07721],[-161.67777,66.11612],[-162.48971,66.73557],[-163.71972,67.11639],[-164.43099,67.61634],[-165.39029,68.04277],[-166.76444,68.35888],[-166.20471,68.88303],[-164.43081,68.91554],[-163.16861,69.37111],[-162.93057,69.85806],[-161.9089,70.33333],[-160.9348,70.44769],[-159.03918,70.89164],[-158.11972,70.82472],[-156.58082,71.35776],[-155.06779,71.14778]]]]},\"properties\":{\"name\":\"United States\"}}]}","edition":"Version 1.0: March 2019; Version 1.1: July 2022","contact":"Mineral Resources Program
U.S. Geological Survey
913 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Email: Minerals@usgs.gov
Wildland fire characteristics, such as area burned, number of large fires, burn intensity, and fire season duration, have increased steadily over the past 30 years, resulting in substantial increases in the costs of suppressing fires and managing damages from wildland fire events (National Academies of Sciences, Engineering, and Medicine, 2017). Wildland fire management could benefit from sound decision making based on reliable scientific information. Fire scientists produce data, tools, and information to support fire and land management decision making. With ever-changing land use scenarios, environmental conditions, and emerging technological capabilities, new assessments and studies are continually needed. Established by Congress in 1879, the U.S. Geological Survey (USGS) is the primary science branch of the Department of the Interior (DOI), which manages more than 400 million acres of public lands in the United States. The USGS has more than 100 scientists across seven Mission Areas that help address the wildland fire science needs of DOI bureaus and their stakeholders. The diverse expertise of these scientists allows them to address complex interdisciplinary challenges. In this report, we identify and characterize scientific literature produced by USGS scientists during 2006–17 that addresses topics associated with wildland fire science. Our goals were to (1) make the most complete list possible of product citations readily available in an organized format, and (2) use bibliometric analysis approaches to highlight the productivity of USGS scientists and the impact of contributions that the Bureau has provided to the scientific, land management, and fire management communities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191002","usgsCitation":"Steblein, P.F., and Miller, M.P., 2018, Characterizing 12 years of wildland fire science at the U.S. Geological Survey—Wildland fire science publications, 2006–17: U.S. Geological Survey Open-File Report 2019–1002, 67 p., https://doi.org/10.3133/ofr20191002.","productDescription":"Report: iii, 67 p.; 2 Companion Files","numberOfPages":"75","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-097383","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":364144,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/fs20193025","text":"Fact Sheet 2019–3025","linkHelpText":"- Wildland Fire Science—Supporting Wildland Fire and Land Management"},{"id":379947,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/cir1471","text":"Circular 1471","linkHelpText":"- U.S. Geological Survey Wildland Fire Science Strategic Plan, 2021–26 (English and Spanish versions)"},{"id":364145,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/gip190","text":"General Information Product 190","linkHelpText":"- Wildland Fire Science at the U.S. Geological Survey—Supporting Wildland Fire and Land Management Across the United States"},{"id":361934,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1002/coverthb.jpg"},{"id":361935,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1002/ofr20191002.pdf","text":"Report","size":"824 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1002"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","contact":"Associate Director
Ecosystems Mission Area
U.S. Geological Survey
Mail Stop 300
12201 Sunrise Valley Drive
Reston, VA 20192
Bottomhole temperature (BHT) measurements offer a useful way to characterize the subsurface thermal regime as long as they are corrected to represent in situ reservoir temperatures. BHT correction methods calibrated for the domestic onshore Gulf of Mexico basin were established in this study. These corrections are empirically derived and based on newly compiled databases of BHT wireline measurements and, to a lesser extent, drill stem test data. A unified BHT correction for the onshore Gulf Coast region, as well as 12 distinct BHT correction equations for each of the 12 physiographic provinces within the onshore Gulf Coast region, are provided. This study also characterizes the geothermal gradient across the onshore Gulf of Mexico basin, which ranges from 1.89 degrees Fahrenheit per 100 feet in the Sabine Uplift area to 1.39 degrees Fahrenheit per 100 feet in the Southern Louisiana Salt Basin. This report disseminates the slides presented at the 68th annual convention of the Gulf Coast Association of Geological Societies and the Gulf Coast Section of the Society of Economic Paleontologists and Mineralogists that was held September 30–October 2, 2018, in Shreveport, Louisiana.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20191143","usgsCitation":"Burke, L.A., Pearson, O.N., and Kinney, S.A., 2020, New method for correcting bottomhole temperatures acquired from wireline logging measurements and calibrated for the onshore Gulf of Mexico basin, U.S.A.: U.S. Geological Survey Open-File Report 2019–1143, 12 p., https://doi.org/10.3133/ofr20191143.","productDescription":"iii, 12 p.","onlineOnly":"Y","ipdsId":"IP-102769","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":399430,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109663.htm"},{"id":371939,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1143/ofr20191143.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1143"},{"id":371937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1143/coverthb.jpg"}],"country":"United States","state":"Alabama, Arkansas, Louisiana, Mississippi, Texas","otherGeospatial":"Gulf of Mexico basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.06640625,\n 30.675715404167743\n ],\n [\n -87.978515625,\n 31.50362930577303\n ],\n [\n -87.8466796875,\n 32.194208672875384\n ],\n [\n -91.23046875,\n 33.394759218577995\n ],\n [\n -95.64697265625,\n 33.52307880890422\n ],\n [\n -97.470703125,\n 33.30298618122413\n ],\n [\n -98.3056640625,\n 30.694611546632277\n ],\n [\n -98.10791015625,\n 29.611670115197377\n ],\n [\n -100.4150390625,\n 28.786918085420226\n ],\n [\n -99.6240234375,\n 27.566721430409707\n ],\n [\n -99.404296875,\n 27.15692045688088\n ],\n [\n -99.11865234374999,\n 26.43122806450644\n ],\n [\n -98.63525390624999,\n 26.27371402440643\n ],\n [\n -98.15185546874999,\n 26.05678288577881\n ],\n [\n -97.36083984375,\n 25.918526162075153\n ],\n [\n -97.0751953125,\n 25.918526162075153\n ],\n [\n -96.87744140625,\n 27.449790329784214\n ],\n [\n -95.03173828125,\n 28.76765910569123\n ],\n [\n -93.3837890625,\n 29.477861195816843\n ],\n [\n -91.99951171875,\n 29.19053283229458\n ],\n [\n -90.703125,\n 28.9600886880068\n ],\n [\n -89.62646484375,\n 28.459033019728043\n ],\n [\n -87.7587890625,\n 29.132970130878636\n ],\n [\n -88.06640625,\n 30.675715404167743\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Bedrock geologic mapping of the Lahore, Va., 7.5-minute quadrangle was completed as part of a broader project, undertaken jointly between the U.S. Geological Survey, the Virginia Division of Geology and Mineral Resources, and other Federal and State agencies to better understand the causative mechanisms of the magnitude-5.8 (M5.8) earthquake that occurred near Mineral, Va., on August 23, 2011. This project involved detailed mapping of eight quadrangles in the epicentral region of the Mineral, Va., earthquake in order to improve our understanding of the geologic framework of the central Virginia seismic zone, which has a long record of historical and prehistoric seismicity.
The Lahore 7.5-minute quadrangle contains the contact between Ordovician to Silurian, dioritic and granodioritic rocks of the Lahore and Ellisville plutons and older metasedimentary and metavolcanic rocks. The Lahore quadrangle is northeast of the Ferncliff and Louisa, Va., quadrangles, where the Shores complex is intruded by the Ellisville pluton along the pluton’s southwestern margin. The new mapping in the Lahore quadrangle shows that the Shores complex continues northeast of the Ellisville pluton. A northeast-trending mafic- and ultramafic-bearing belt within the Shores complex is a fault-bounded accretionary zone (accretionary wedge) between rocks of the Chopawamsic Formation and Laurentian slope-and-rise deposits. In the Lahore quadrangle, this belt contains several mappable, northeast- to southwest-trending mafic bodies and also includes small exposures of gabbro and talc schist.
The Lahore quadrangle contains structures of both early- and late-Paleozoic age that correspond to the Taconic and Alleghanian orogenies. Taconic (Late Ordovician) S1 schistosity in layered rocks is typically fine-grained and parallel to compositional layering, when present. Alleghanian (Pennsylvanian) S2 schistosity is coarser and more micaceous than S1 and is locally accompanied by a lineation that is represented by mineral lineations, micro-crenulations, or mullion fabric, and represents the hinges of F2 folds. A foliation in the plutonic rocks is represented by an equilibrium assemblage of aligned mafic minerals and is early Paleozoic in age.
Metamorphic grade in the non-plutonic rocks of the Lahore quadrangle ranges from lower-greenschist to the northwest to upper-greenschist to the southeast, as represented by mineral assemblages in non-plutonic rocks. The biotite isograd may be, in part, lithologically controlled by the contact between the informally-named Hardware and Byrd Mill formations, and locally affected by contact metamorphism by the Lahore pluton (western part of map). The Taconic garnet isograd is defined by the sparse presence of small (less than 1 millimeter), euhedral garnet crystals. Both the biotite and garnet isograds continue along strike to the southwest into the Ferncliff and Louisa quadrangles, where the isograds have been identified as Ordovician age (Taconic orogeny) based on muscovite, biotite, and amphibole 40Ar/39Ar cooling ages.
Regionally, the most common trend and plunge of joints is northwest and subvertical, respectively, and orthogonal to the regional strike of foliation. Early Mesozoic extension may have reactivated the Harris Creek fault (southeast corner of map), a late Paleozoic (Alleghanian orogeny) transpressional fault that marks the contact between granodiorite of the Ellisville pluton and the Chopawamsic Formation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191110","usgsCitation":"Burton, W.C., 2019, Preliminary bedrock geologic map of the Lahore 7.5-minute quadrangle, Orange, Spotsylvania, and Louisa Counties, Virginia: U.S. Geological Survey Open-File Report 2019–1110, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20191110.","productDescription":"1 Sheet: 37.00 x 34.00 inches; ReadMe; Database; Metadata","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098254","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":399417,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109624.htm"},{"id":371645,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2019/1110/LahoreVAOFR20191110_database.zip","text":"Geodatabase","linkFileType":{"id":6,"text":"zip"}},{"id":371644,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2019/1110/ofr20191110_openaccess.zip","text":"Open Access","linkFileType":{"id":6,"text":"zip"}},{"id":371643,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2019/1110/LahoreVAOFR20191110Metadata.zip","text":"Metadata","linkFileType":{"id":6,"text":"zip"}},{"id":371642,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/2019/1110/ofr20191110_readme.txt","text":"Read Me","linkFileType":{"id":2,"text":"txt"}},{"id":371347,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2019/1110/ofr20191110.pdf","text":"Geologic Map","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1110"},{"id":370151,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1110/coverthb.jpg"}],"scale":"24000","country":"United States","state":"Virginia","county":"Louisa County, Orange County, Spotsylvania County","otherGeospatial":"Lahore 7.5-minute quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78,\n 38.125\n ],\n [\n -77.875,\n 38.125\n ],\n [\n -77.875,\n 38.25\n ],\n [\n -78,\n 38.25\n ],\n [\n -78,\n 38.125\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Florence Bascom Geoscience Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The U.S. Geological Survey National Crustal Model (NCM) is being developed to assist with earthquake hazard and risk assessment by supporting estimates of ground shaking in response to an earthquake. The period-dependent intensity and duration of shaking depend upon the three-dimensional seismic velocity, seismic attenuation, and density distribution of a region, which in turn is governed to a large degree by geology and how that geology behaves under varying temperatures and pressures.
A three-dimensional temperature model is presented here to support the estimation of physical parameters within the U.S. Geological Survey NCM. The crustal model is defined by a geological framework consisting of various lithologies with distinct mineral compositions. A temperature model is needed to calculate mineral density and bulk and shear modulus as a function of position within the crust. These properties control seismic velocity and impedance, which are needed to accurately estimate earthquake travel times and seismic amplitudes in earthquake hazard analyses. The temperature model is constrained by observations of surface temperature, temperature gradient, and conductivity, inferred Moho temperature and depth, and assumed conductivity at the base of the crust. The continental plate is assumed to have heat production that decreases exponentially with depth and thermal conductivity that exponentially changes from a surface value to 3.6 watts per meter-Kelvin at the Moho. The oceanic plate cools as a half-space with a geotherm dependent on plate age. Under these conditions, and the application of observed surface heat production, predicted Moho temperatures match Moho temperatures inferred from seismic P-wave velocities, on average. As has been noted in previous studies, high crustal temperatures are found in the western United States, particularly beneath areas of recent volcanism. In the central and eastern United States, elevated temperatures are found from southeast Texas, into the Mississippi Embayment, and up through Wisconsin. A USGS ScienceBase data release that supports this report is available and consists of grids covering the NCM across the conterminous United States, for example, surface temperature and temperature gradient, that are needed to produce temperature profiles.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191121","usgsCitation":"Boyd, O.S., 2020, Temperature model in support of the U.S. Geological Survey National Crustal Model for seismic hazard studies: U.S. Geological Survey Open-File Report 2019–1121, 15 p., https://doi.org/10.3133/ofr20191121.","productDescription":"Report: iv, 15 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-109788","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":437241,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SL2PVR","text":"USGS data release","linkHelpText":"TherMod"},{"id":399419,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109626.htm"},{"id":371516,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P935DT1G","text":"USGS data release","linkHelpText":"Grids in support of the U.S. Geological Survey Thermal Model for Seismic Hazard Studies"},{"id":371515,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1121/ofr20191121.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1121"},{"id":371514,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1121/coverthb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS-966
Denver, CO 80225-0046
The Bi-State Distinct Population Segment (Bi-State DPS) of greater sage-grouse (Centrocercus urophasianus, hereinafter “sage-grouse”) represents a genetically distinct and geographically isolated population that straddles the border between Nevada and California. The primary threat to these sage-grouse populations is the expansion of single-leaf pinyon (Pinus monophylla) and Utah juniper (Juniperus osteosperma) into sagebrush ecosystems, which fragments and reduces population connectivity and survival. Other important threats include low water availability during brood-rearing, particularly during drought, and increased predation by common ravens (Corvus corax), a generalist predator often associated with anthropogenic resource subsidies. Although the Bi-State DPS occurs at high elevations relative to sage-grouse range-wide, changes in historical wildfire cycles and the conversion of native shrubs to invasive annual grasslands still threaten these populations. The Bi-State DPS has undergone multiple federal status assessments and associated litigation. For example, in October of 2013, the Bi-State DPS was proposed for listing as threatened under the Endangered Species Act of 1973 by the U.S. Fish and Wildlife Service (USFWS), then withdrawn in April 2015. The withdrawal decision was challenged, and in May 2018, a Federal district court ordered the withdrawal decision to be vacated, and USFWS was required to re-open the October 2013 listing evaluation.
In response, the U.S. Geological Survey (USGS), with State and Federal collaborators, embarked on a multipronged analysis to provide current and best available science regarding population status of sage-grouse within the Bi-State DPS. Using data from a long-term monitoring program, we carried out four analytical study objectives, and here, we provide preliminary results of these analyses. First, we used integrated population modeling (IPM) to predict annual population abundance and annual finite rate of population change for the Bi-State DPS, as a whole, and for each subpopulation between 1995 and 2018. Because sage-grouse exhibit population cycles (periodic increases and decreases in abundance across approximately 6- to 10-year wavelengths), we estimated trends across three nested temporal scales that represent one (11 years), two (18 years), and three (24 years) complete population cycles. These estimates of relatively long-term averaged population change account for temporal (that is, interannual) variation. Our model predicted population abundance for the Bi-State DPS during 2018 at 3,305 individuals (2,247–4,683), with the majority occupying Bodie Hills and Long Valley. The model also predicted cyclic dynamics in abundance through time with evidence of 24-year population growth and slight trends of decline over the past 18 years. Specifically, across the Bi-State DPS as a whole, we estimated annual average at 0.99, 0.99, and 1.02 over the one, two, and three population cycles, which equated to a 10.5 percent, 16.6 percent decrease, and 60.0 percent increase in abundance over the 11-, 18-, and 24-year cycles. Estimated abundance in 2018 had not reached numbers lower than those predicted during 1995. However, we found spatial variation in population trends across the three cycles. Bodie Hills subpopulation comprised the greatest (1,521) and exhibited average annual greater than 1.0 across all periods resulting in average annual increases of 7 percent. This relatively large subpopulation has grown 5 times larger than what was predicted in 1995 while experiencing cyclical dynamics within that period.
Conversely, other smaller subpopulations within the Bi-State DPS exhibited average annual equal to or less than 1.0 resulting in estimated 10-year risks of extirpation ranging from 2.0 to 76.1 percent. In general, evidence of decline among smaller subpopulations was greatest for the most recent period (2008–18) compared to a period that encompassed three full population cycles (24-year). This difference coincides with an intense period of drought that began in 2012.
For comparative purposes as part of this first objective, we conducted a similar analysis for populations of sage-grouse within Nevada and California but outside the Bi-State DPS. We developed a region-wide and distance-weighted IPM using lek count from Nevada Department of Wildlife (NDOW) and California Department of Fish and Wildlife (CDFW) databases and with telemetry data collected by USGS across 12 sage-grouse subpopulations. Our models predicted similar patterns in population cycling outside the Bi-State DPS but with much stronger evidence of long-term declines across 24 years. Specifically, median averaged across each year of the 11-, 18-, and 24-year periods resulted in average annual values of 0.94, 0.97, and 0.99, respectively. These values equate to 41.0 percent, 38.5 percent, and 21.3 percent declines over the corresponding periods.
Second, we used lek count data in a state-space modeling framework to compare trends in population abundance across different spatial scales (that is, leks versus Bi-State DPS). This hierarchical framework allowed us to disentangle declines associated with climate conditions as opposed to other local level factors that might signal the need for management intervention. Specifically, we identified 7 leks that were both declining and recently decoupled from larger spatial scale trends, typically governed by climatic conditions (referred to as soft or hard signals). The goal of this analysis was to provide an early warning system that might have implications for conservation actions at local scales.
Third, we developed phenological (spring, summer–fall, and winter) and reproductive life stage (nesting, early brood-rearing, and late-brood rearing) based resource selection functions using various environmental covariates. We report rankings of variable importance for each season and life stage, developed maps of habitat selection indices (HSI), binned categories representing low, moderate, and high classes of quality (where any category greater than or equal to low indicated selected habitat) for each phenological season and life stage, and produced composite maps by selected phenological and reproductive stage to estimate annual habitat.
Fourth, we used for each lek within the Bi-State DPS to carry out a spatial analysis that quantified substantial changes in the distribution of occupied habitat across long- (24-year) and short- (11-year) term periods. Owing to differences among available datasets, the long-term analysis primarily reflected spatial shifts among subpopulations comprising the majority of the Bi-State DPS (that is, Bodie Hills and Long Valley) while the short-term analysis also quantified changes among subpopulations along the periphery. Over long and short-term periods, the overall distribution of occupied habitat (as measured by 99 percent utilization distributions intersecting any quantified habitat) was reduced by 20,573 ha and 55,492 ha, respectively. Occupied core areas (as measured by 50 percent utilization distributions intersecting any quantified habitat) over long-term periods were solely located in Bodie Hills and Long Valley. Although nearly all subpopulations experienced contractions in occupied overall and core distribution, Bodie Hills experienced spatial expansion that occurred with concomitant spatial contraction at Long Valley over both periods. Subpopulations at the northern (Pine Nuts), central (Sagehen) and southern (White-Mountains) extents of the Bi-State DPS also experienced spatial contraction over the short-term period. These findings, coupled with those of population trends, indicate long-term patterns in redistribution of sage-grouse from Long Valley and peripheral subpopulations to Bodie Hills. That is, sage-grouse subpopulations at the periphery are declining while the largest population at the core is increasing, which could have meaningful impacts on overall metapopulation persistence. We provide evidence for loss of occupied habitat (reduced distribution) given local extirpation of subpopulations.
Fifth, we calculated percentages of selected phenological, life stage, and annual habitat that each subpopulation contributed to the Bi-State DPS. We then intersected these maps with a composite estimate of occupied habitat from the fourth objective and calculated percentages of selected habitat likely occupied by sage-grouse that each subpopulation contributed to the Bi-State DPS. These values provide evidence for loss of occupied habitat and subsequent reductions in spatial distribution given reductions in abundance and, in some cases, extirpation of leks within subpopulations.
Lastly, we carried out an initial in-depth analysis of selection for irrigated pastures and wet meadows during the brood-rearing stage for the Long Valley subpopulation. We chose this subpopulation because it represents a population core, representing 26.5 percent of total sage-grouse within the Bi-State DPS, and has exhibited long-term declines in abundance and distribution. This subpopulation is highly sensitive to precipitation and other factors that influence water availability. Models predicted higher use of the interior portions of irrigated pastures and wet meadows during late brood-rearing period, which represented a potentially risky use of habitat that was exacerbated during periods of low moisture (for example, drought, reduced water delivery, or both). Sage-grouse typically used edges of riparian areas and pastures, largely because the interior of these mesic areas consisted of considerably less overhead concealment cover (for example, shrubs) that likely resulted in a higher risk of mortality. We found that a lack of water delivery to pastures in the form of overwinter precipitation or diversion ditches increased the movements of sage-grouse to the interior of pastures. Although further investigation of water delivery impacts on chick survival are warrented, our initial findings regarding resource selection may explain recent declines in population growth at Long Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191149","collaboration":"Prepared in cooperation with the U. S. Fish and Wildlife Service, Bureau of Land Management, California Department of Fish and Wildlife, Nevada Department of Wildlife, and the U.S. Forest Service","usgsCitation":"Coates, P.S., Ricca, M.A., Prochazka, B.G., O’Neil, S,T., Severson, J.P., Mathews, S.R., Espinosa, S., Gardner, S., Lisius, S., and Delehanty, D.J., 2020, Population and habitat analyses for greater sage-grouse (Centrocercus urophasianus) in the bi-state distinct population segment—2018 update: U.S. Geological Survey Open-File Report 2019–1149, 122 p., https://doi.org/10.3133/ofr20191149.","productDescription":"x, 122 p.","onlineOnly":"Y","ipdsId":"IP-113768","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":371329,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1149/ofr20191149.pdf","text":"Report","size":"8.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1149"},{"id":371330,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1149/ofr20191149_hirez.pdf","text":"Report — High resolution graphics","size":"82.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1149 Hi Rez"},{"id":371328,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1149/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 -120.234375,\n 38.90813299596705\n ],\n [\n -119.92675781249999,\n 38.436379603\n ],\n [\n -119.72900390625001,\n 37.50972584293751\n ],\n [\n -118.85009765625,\n 36.90597988519294\n ],\n [\n -117.83935546874999,\n 36.12900165569652\n ],\n [\n -117.586669921875,\n 36.1733569352216\n ],\n [\n -117.31201171875001,\n 35.862343734896484\n ],\n [\n -116.806640625,\n 36.075742215627\n ],\n [\n -115.224609375,\n 35.79108281624994\n ],\n [\n -115.587158203125,\n 37.125286284966805\n ],\n [\n -117.23510742187501,\n 38.62545397209084\n ],\n [\n -119.5751953125,\n 39.16414104768742\n ],\n [\n -120.234375,\n 38.90813299596705\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
Multiple aquifer tests were conducted in Lovelock, Nevada, to determine hydraulic conductivity and storage properties to be used with the numerical groundwater flow model of the lower Humboldt River Basin while accounting for the influence of surface features with a modeling component. The numerical model will ultimately provide the Nevada Division of Water Resources (NDWR) with information regarding the impacts of groundwater pumping on the Humboldt River, allowing the Nevada State Engineer to make informed decisions in the conjunctive management of the State’s groundwater and surface water resources. Seven slug tests, one single-well pumping test, and two multi-well pumping tests were conducted to evaluate properties of shallow Lahontan clays and silts; shallow fluvial deposits; and coarser, water-bearing deposits of the younger alluvium. Aquifer tests were conducted between March 2017 and April 2018. Results indicate aquifers in the Lovelock Valley have transmissivity ranging between 0.0001 and 95,000 feet squared per day (ft2/day). The results of these tests provide constraints on hydraulic properties for a numerical groundwater flow model being developed for a capture study in the lower Humboldt River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191133","collaboration":"Prepared in cooperation with the Nevada Division of Water Resources","usgsCitation":"Nadler, C., 2020, Analysis of aquifer framework and hydraulic properties of Lovelock Valley, Lovelock, Nevada: U.S. Geological Survey Open-File Report 2019–1133, 48 p., https://doi.org/10.3133/ofr20191133.","productDescription":"Report: viii, 48 p.; Data Release","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-098941","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":399425,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109593.htm"},{"id":371146,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1133/ofr20191133.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"}},{"id":371147,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LIL7PZ","linkHelpText":"Supplemental data for analysis of aquifer framework and hydraulic properties of Lovelock Valley, Lovelock, NV"},{"id":371145,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1133/coverthb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Humboldt River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.597412109375,\n 39.14710270770074\n ],\n [\n -114.70825195312501,\n 39.14710270770074\n ],\n [\n -114.70825195312501,\n 41.91045347666418\n ],\n [\n -118.597412109375,\n 41.91045347666418\n ],\n [\n -118.597412109375,\n 39.14710270770074\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 95819
This geologic map of the Greater Antilles and the Virgin Islands is a compilation of information from the literature, integrated to provide a seamless geologic map of the region. The geology shown on sheet 1 covers Cuba, the island of Hispaniola, which includes Haiti and the Dominican Republic, Jamaica, the Cayman Islands, Puerto Rico, and the U.S. and British Virgin Islands. A second more detailed sheet shows the geology of Puerto Rico and the Virgin Islands. The map units shown here are integrated across the islands of the Greater Antilles and the Virgin Islands.
The Greater Antilles and the Virgin Islands, although they appear to reflect the character of a magmatic arc, actually represent multiple, distinct geologic features. Only in Cuba are there unquestioned Jurassic-age, and perhaps older, rocks present. On the islands of Hispaniola (Haiti and the Dominican Republic) and Puerto Rico, metamorphic assemblages contain rocks that may be of Jurassic age. Ophiolite assemblages that may include rocks of Jurassic age are present in Cuba, the Dominican Republic, Haiti, and Puerto Rico. Metamorphic rocks of Cretaceous age are more widespread, present in Cuba, Hispaniola, and the U.S. and British Virgin Islands. Cretaceous plutonic rocks are present in Cuba and Puerto Rico, as well as in the Dominican Republic (in the Cordillera Central and in the eastern part of the country). Gabbro and trondhjemite of inferred Early Cretaceous age are present in the U.S. Virgin Islands. Cretaceous volcanic rocks are widespread in Cuba, Hispaniola, Puerto Rico, and the Virgin Islands; they are of variable age and do not appear to reflect a single arc system. Cretaceous volcanic rocks are also found in Jamaica, in inliers on the eastern part of the island. Eocene volcanic rocks are prominent in southern Cuba, Haiti, eastern Jamaica, Puerto Rico, and the Virgin Islands. Volcanic rocks possibly as young as early Miocene are present in the southern Dominican Republic; the youngest volcanic rocks in the region are the Low Layton Lavas of Jamaica of late Miocene age and alkali basalt of Quaternary age on Hispaniola.
Carbonate rocks are an important component of the sedimentary section in the Greater Antilles, which is as old as Jurassic in Cuba and as young as Holocene in many areas. In Cuba, Early Cretaceous sedimentary rocks tend to be dominantly carbonates; volcanic clasts and debris are not present until the Late Cretaceous in Cuba, as well as in Jamaica and Puerto Rico. In contrast, Early Cretaceous volcaniclastic sedimentary rocks are common in the Virgin Islands. Olistostrome deposits are commonly described in latest Cretaceous and Eocene rocks; in the Paleocene and the early Eocene, these deposits are commonly associated with mélange units. Volcanic debris and tuff are common in sedimentary rocks of Paleocene and Eocene age, typically associated with carbonate rocks. Sedimentary rocks that postdate the Eocene either are dominantly carbonates or are mixed clastic and carbonate rocks in which the clastic component reflects erosion of earlier units, including older carbonate rocks. Rocks that contain lignite, which are only present in Cuba and on Hispaniola, generally are of Miocene age.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191036","usgsCitation":"Wilson, F.H., Orris, G., and Gray, F., 2019, Preliminary geologic map of the Greater Antilles and the Virgin Islands: U.S. Geological Survey Open-File Report 2019–1036, pamphlet 50 p., 2 sheets, scales 1:2,500,000 and 1:300,000, https://doi.org/10.3133/ofr20191036.","productDescription":"Pamphlet: iv, 50 p.; 2 Sheets: 51.00 x 34.00 inches and 46.10 x 24.93 inches; 2 Tables; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098596","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":399410,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109592.htm"},{"id":399409,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109591.htm"},{"id":371178,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2019/1036/ofr20191036_spatialdata.zip","text":"OFR 2019-1036 spatial data","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2019-1036 Spatial Data"},{"id":371177,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1036/ofr20191036_table2.xlsx","text":"Table 2","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2019-1036 Table 2 XLSX"},{"id":371176,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1036/ofr20191036_table2.pdf","text":"Table 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1036 Table 2 PDF"},{"id":371173,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1036/ofr20191036_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1036"},{"id":371175,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2019/1036/ofr20191036_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1036 Sheet 2"},{"id":371174,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2019/1036/ofr20191036_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1036 Sheet 1"},{"id":371172,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1036/coverthb2.jpg"}],"scale":"2500000","country":"Cuba, Dominican Republic, Great Britain, Haiti, Jamaica, United States","otherGeospatial":"Greater Antilles, Hispaniola, Puerto Rico, Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.517578125,\n 23.725011735951796\n ],\n [\n -85.4296875,\n 22.105998799750566\n ],\n [\n -83.84765625,\n 20.138470312451155\n ],\n [\n -76.2890625,\n 15.623036831528264\n ],\n [\n -69.169921875,\n 15.792253570362446\n ],\n [\n -61.435546875,\n 16.46769474828897\n ],\n [\n -60.64453125000001,\n 17.895114303749143\n ],\n [\n -61.52343749999999,\n 21.04349121680354\n ],\n [\n -72.50976562499999,\n 22.187404991398775\n ],\n [\n -82.265625,\n 24.046463999666567\n ],\n [\n -85.517578125,\n 23.725011735951796\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Science Center
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
Dos Palmas Preserve is a Colorado Desert oasis and wetland in Riverside County, California, located near the base of the Orocopia Mountains and northeast of the Salton Sea. The original source of water for the oasis was artesian springs that developed at the base of the Orocopia Mountains, but more abundant water supplies were later provided to Dos Palmas Preserve when the Coachella Canal was built and water seeped from unlined parts of the canal. As a result of this abundant water supply in a desert setting, Dos Palmas Preserve, managed by the Bureau of Land Management, is now a wildlife preserve that became home to multiple plants, fowl, insects, rodents, reptiles, and bats, including some endangered and threatened species. More recently, sections of the Coachella Canal have been lined, resulting in a reduction of water seepage and threatening the sustainability of parts of Dos Palmas Preserve. Faults usually act as barriers to groundwater flow and Dos Palmas Preserve is only a few kilometers from the active trace of the San Andreas Fault, where splays of the fault trend through the area. Additionally, numerous closely spaced faults that have been mapped at the surface northwest of Dos Palmas Preserve are believed to extend southward into the Dos Palmas Preserve, where they are covered by alluvium. Thus, evaluation of the subsurface lithology and structure is needed to determine how the current allocation of water from the Coachella Canal affects various parts of Dos Palmas Preserve.
To better understand the distribution of the shallow lithology, faulting, and groundwater in Dos Palmas Preserve, the U.S. Geological Survey, in collaboration with the Bureau of Land Management, conducted a seismic survey across the northern part of Dos Palmas Preserve. The seismic survey was designed to “map” the upper part of the aquifer system and to more precisely locate faults that may affect groundwater flow in Dos Palmas Preserve. In this report, we present seismic velocity and reflection images of the shallow subsurface and relate those images to interpretative structures and stratigraphy that may affect groundwater at Dos Palmas Preserve.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191130","usgsCitation":"Catchings, R.D., Goldman, M.R., Chan, J.H., Sickler, R.R., Rymer, M.J., and Criley, C.J., 2020, Seismic evaluation of shallow-depth structure, faulting, and groundwater variations across the Dos Palmas Preserve, Riverside County, California: U.S. Geological Survey Open-File Report 2019–1130, 21 p., https://doi.org/ 10.3133/ofr20191130.","productDescription":"Report: vi, 21 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-101151","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":399421,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109590.htm"},{"id":371135,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WQJ5EH","text":"USGS data release","description":"USGS Data Release","linkHelpText":"2015 high resolution seismic acquisition at Dos Palmas Preserve, Mecca, California"},{"id":371134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1130/ofr20191130.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1130"},{"id":371133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1130/coverthb.jpg"}],"country":"United States","state":"California","county":"Riverside County","otherGeospatial":"Dos Palmas Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.0925,\n 33.2881\n ],\n [\n -115.4408,\n 33.2881\n ],\n [\n -115.4408,\n 33.6419\n ],\n [\n -116.0925,\n 33.6419\n ],\n [\n -116.0925,\n 33.2881\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
Repeated sampling and grain-size analysis of surficial sediments along the sandy shorelines of Louisiana is necessary to characterize coastal-zone sediment properties and evaluate sediment transport patterns within the nearshore environments. In 2008, and again in 2015 and 2016, sediment grab samples were collected along the shorelines of the western Chenier plain, the Isles Dernieres (Raccoon, Whiskey, Trinity and East Islands), the Lafourche delta (Timbalier Islands, Caminada Headland, and Grand Isle), the modern delta (Grand Terre Islands from Chaland Headland to Sandy Point), and the Chandeleur Islands (from Curlew Island to Hewes Point). The samples were collected as part of the Louisiana Coastal Protection and Restoration Authority (CPRA) Barrier Island Comprehensive Monitoring (BICM) Program in collaboration with the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS–SPCMSC) and the University of New Orleans Pontchartrain Institute for Environmental Studies (UNO–PIES). Physical properties of the samples (sediment grain size and sorting) were measured and provided in data reports to CPRA. Additional samples collected by the USGS from around Breton Island in 2014 and 2015 supplemented the 2015–2016 BICM data to complete the coastwide dataset. This report compares the results of the 2008 and 2015–2016 sedimentologic analyses and documents changes in composition (percent sand) and mean sediment grain size between the two time periods. At most sample sites, differences in mean grain size varied by less than ±0.25 Φ. The largest changes occurred at sites located near tidal inlets or along rapidly eroding shorelines.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191132","collaboration":"Prepared in cooperation with the University of New Orleans and Louisiana Coastal Protection and Restoration Authority","usgsCitation":"Bosse, S.T., Flocks, J.G., Bernier, J.C., Georgiou, I.Y., Kulp, M.A., and Brown, M., 2019, Louisiana Coastal Zone sediment characterization; comparison of sediment grain sizes for samples collected in 2008 and 2015–2016 from the western Chenier plain to the Chandeleur Islands, Louisiana—Louisiana Barrier Island Comprehensive Monitoring (BICM) Program: U.S. Geological Survey Open-File Report 2019–1132, 17 p., https://doi.org/10.3133/ofr20191132.","productDescription":"vi, 17 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-107806","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":371101,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1132/report-thumb.jpg"},{"id":371102,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1132/ofr20191132.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1132"},{"id":399424,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109589.htm"},{"id":399423,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109588.htm"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.8333,\n 29.6667\n ],\n [\n -93,\n 29.6667\n ],\n [\n -93,\n 29.7889\n ],\n [\n -93.8333,\n 29.7889\n ],\n [\n -93.8333,\n 29.6667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
The United States Geological Survey (USGS) provided technical support to the Washington Department of Ecology (Ecology) in their assessment of the role groundwater plays in contributing pollutant loading to the Green-Duwamish River near Seattle, Washington. Ecology is developing watershed hydrology models of the Green-Duwamish watershed, and need to assign realistic contaminant concentrations to the various Hydrologic Response Units represented in their models. The USGS compiled existing groundwater quality data in the Green-Duwamish watershed, and this report summarizes results and interpretation of the dataset, including identifying data gaps and needs for further research and monitoring. The sources of existing data were the USGS’s National Water Information System, Ecology’s Environmental Information Management System, and a compilation of several studies by Leidos, a scientific research company. The water-quality parameters of interest included polychlorinated biphenyl (PCB) Aroclors and congeners, phthalates, carcinogenic polycyclic aromatic hydrocarbons (cPAHs), arsenic, copper, and zinc. Results were grouped into the four subwatersheds delineated in Ecology’s hydrology models: Duwamish, Lower Green, Soos, and Upper Green. Results from the Duwamish subwatershed were further sub-divided by the USGS into the Lower Duwamish, containing land adjacent to the Lower Duwamish Waterway Superfund site, and the Upper Duwamish, containing the remaining area of the Duwamish subwatershed. Groundwater quality data in the Lower Duwamish were treated separately because there is known contamination in this area. The availability of water quality data varied by subwatershed as follows: phthalate data was only available within the Duwamish, PCB data was available within the Duwamish and Lower Green, cPAH data was available within the Duwamish, Lower Green, and Soos, and data for arsenic, copper, and zinc were available within all four subwatersheds. More than 99 percent of the available data was within the Duwamish subwatershed, identifying a need for additional monitoring of groundwater quality in the other subwatersheds.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191131","collaboration":"Prepared in cooperation with the Washington State Department of Ecology","usgsCitation":"Senter, C.A., Conn, K.E., Black, R.W., Welch, W.B., and Fasser, E.T., 2020, Assessment of existing groundwater quality data in the Green-Duwamish watershed, Washington: U.S. Geological Survey Open-File Report 2019-1131, 35 p., https://doi.org/10.3133/ofr20191131.","productDescription":"iv, 35 p.","onlineOnly":"Y","ipdsId":"IP-111911","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":371094,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1131/coverthb2.jpg"},{"id":371095,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1131/ofr20191131.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1131"},{"id":399422,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109587.htm"}],"country":"United States","state":"Washington","otherGeospatial":"Green-Duwamish watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.26684570312499,\n 47.59505101193038\n ],\n [\n -122.420654296875,\n 47.60245929546312\n ],\n [\n -122.43713378906249,\n 47.51349065484327\n ],\n [\n -122.431640625,\n 47.32393057095941\n ],\n [\n -122.420654296875,\n 47.18597932702905\n ],\n [\n -122.3876953125,\n 47.010225655683485\n ],\n [\n -122.288818359375,\n 46.912750956378915\n ],\n [\n -122.2283935546875,\n 46.781254534638606\n ],\n [\n -122.0855712890625,\n 46.558860303117164\n ],\n [\n -121.59667968749999,\n 46.32417161725691\n ],\n [\n -121.39892578125,\n 46.32796494040746\n ],\n [\n -121.30004882812499,\n 46.49839225859763\n ],\n [\n -121.168212890625,\n 46.78501604269254\n ],\n [\n -121.36596679687499,\n 46.991494313050424\n ],\n [\n -121.95922851562501,\n 47.4355191531953\n ],\n [\n -122.26684570312499,\n 47.59505101193038\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
The Atlantic Coastal Plain, the southeasternmost physiographic province in the United States, is underlain by strata that regionally dip gently eastward and gradually thicken toward the Atlantic Ocean basin. These strata, ranging in age from Middle Jurassic to Holocene, accumulated along the eastern margin of North America after the break-up of the supercontinent Pangaea during the Early Jurassic. In the east-central United States north of Florida, Cape Hatteras is the point of land that most closely approaches the eastern edge of the Atlantic Continental Shelf of the United States. In 1946, Esso (now part of ExxonMobil) drilled a deep oil exploration well to basement rock near the Cape Hatteras lighthouse. No oil or gas was found there, or in any of the other test wells that were drilled within the onshore North Carolina Coastal Plain. Recent work indicates that the top of the oil window lies at 9,000 feet near the base of the Cape Hatteras Esso #1 test well. Therefore, any mature petroleum source rocks that may be present in the North Carolina Coastal Plain are only likely to be found east of the present coastline.
Although the Cape Hatteras test well did not produce oil or gas, it did produce a wealth of stratigraphic information about the outer portion of the onshore Atlantic Continental Shelf. Advances in global stratigraphic correlation, in tandem with our analyses of calcareous nannofossils and dinoflagellate cysts (dinocysts) from the Cape Hatteras test-well spot samples have produced significant advances beyond earlier interpretations of this well and other deep test wells inshore of Cape Hatteras. These results, when coupled with work done offshore of Cape Hatteras, have allowed us to create a more detailed cross section of the North Carolina Coastal Plain and adjacent continental shelf than previously possible.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191145","usgsCitation":"Weems, R.E., Self-Trail, J.M., and Edwards L.E., 2019, Cross section of the North Carolina coastal plain from Enfield through Cape Hatteras: U.S. Geological Survey Open-File Report 2019–1145, 2 sheets, https://doi.org/10.3133/ofr20191145.","productDescription":"2 Sheets: 40.00 x 37.00 inches and 35.00 x 37.00 inches","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-102465","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":399432,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109585.htm"},{"id":370654,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1145/ofr20191145_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1145"},{"id":371011,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1145/ofr20191145_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1145"},{"id":370630,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1145/coverthb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.6513671875,\n 34.63320791137959\n ],\n [\n -75.5419921875,\n 34.63320791137959\n ],\n [\n -75.5419921875,\n 36.1733569352216\n ],\n [\n -77.6513671875,\n 36.1733569352216\n ],\n [\n -77.6513671875,\n 34.63320791137959\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Florence Bascom Geoscience Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The Community for Data Integration (CDI) is a community of practice whose purpose is to build the U.S. Geological Survey knowledge base in data integration. This annual report describes the various presentations, activities, and outcomes of the CDI monthly forums, working groups, trainings, and other CDI-sponsored events in fiscal year 2018. The report also describes the objectives of the 10 CDI-funded projects for the year. The CDI had a topical theme for fiscal year 2018—Risk assessment and hazards vulnerability in support of integrated predictive science capacity. This report describes how the community coordinated its activities around this theme.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191123","usgsCitation":"Hsu, L., and Colasuonno, L., 2019, Community for Data Integration 2018 annual report: U.S. Geological Survey Open-File Report 2019–1123, 26 p., https://doi.org/10.3133/ofr20191123.","productDescription":"v, 26 p.","onlineOnly":"Y","ipdsId":"IP-106299","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":370860,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1123/coverthb.jpg"},{"id":370861,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1123/ofr20191123.pdf","text":"Report","size":"5.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1123"}],"contact":"Director, Science Analytics and Synthesis
U.S. Geological Survey
National Center, MS 108
12201 Sunrise Valley Drive
Reston, VA 20192
Predation and habitat degradation by non-native species are principal terrestrial threats to the federally endangered Hawaiian Petrel (ʻuaʻu, Pterodroma sandwichensis) and Hawaiian Goose (nēnē, Branta sandvicensis) within Haleakalā National Park (HALE), Maui, Hawaiʻi. Since 1981, HALE has maintained a network of live traps to control invasive mammalian predators and protect these endangered birds. To evaluate trapping efficiency in HALE, we evaluated four types of trap outcomes for the years 2000–14: Bait Lost (62 percent), No Event (23 percent), Trap Triggered (10 percent), and Predator Event (Rat Caught, Cat Caught, or Mongoose Caught; 4 percent). We used a multinomial logistic regression model to explore trends in the probabilities of broad outcomes (No Event, Other Event [Bait Lost or Trap Triggered], or Predator Event [Rat Caught, Cat Caught, or Mongoose Caught]). Temporal variations in the probabilities of No Event, Other Event, or Predator Event were best explained by ʻuaʻu season (off-season, pre-laying, incubation, or nestling), month, year, and seasonal rainfall with greater probabilities of Predator Event during the ʻuaʻu nestling period (July–October). The probability of Predator Event or Other Event decreased with increased rainfall. Spatial analysis showed that percent vegetative cover and vegetation type best explained variations in the probabilities of trapping outcomes with the probability of Predator Event being greatest in developed and tree covered areas. The proportion of trapping events that resulted in Rat Caught was at least 20 times greater than the proportions of events resulting in Cat or Mongoose Caught throughout the 15-year management period. Temporal analysis showed that season, year, and maximum temperature best explained variations in probabilities of Predator Event; the probability of Rat Caught was greatest during the ʻuaʻu pre-laying and incubation periods (February–June), was greater during periods of warmer maximum temperatures, and overall, increased over the 15-year management period. The probability of Mongoose Caught was greatest during the ʻuaʻu offseason (November–January), decreased through time (2000–14), and decreased with increasing weekly maximum temperatures. Trends in Cat Caught were hard to detect because of small sample sizes, though slight trends indicated cat captures were most frequent during the ʻuaʻu off season and less frequent through time (2000–14). The probability of a Cat Caught event was also negatively correlated with weekly temperatures. Spatial analysis showed elevation best explained variations in probabilities of capture for rats, cats, and mongoose. Overall, predator catches were fewer at higher elevations, and of predators caught at higher elevations, the clear majority were rats. Our results are being used by HALE Endangered Wildlife Management staff to evaluate existing methods for predator control and efficacy of existing trap-based control strategies intended to protect ʻuaʻu and nēnē.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191122","collaboration":"Prepared in cooperation with Haleakalā National Park","usgsCitation":"Kelsey, E.C., Adams, J., Czapanskiy, M.F., Felis, J.J., Yee, J.L., Kaholoaa R.L., and Bailey, C.N., 2019, Trends in mammalian predator control trapping events intended to protect ground-nesting, endangered birds at Haleakalā National Park, Hawaiʻi: 2000–14: U.S. Geological Survey Open-File Report 2019–1122, 27 p., https://doi.org/10.3133/ofr20191122.","productDescription":"Report: vi, 28 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-104150","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":370049,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98RJ12I","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Trap records used to analyze trends in mammalian predator control trapping events intended to protect ground-nesting, endangered birds at Haleakalā National Park, Hawai'i (2000 - 2014)"},{"id":370036,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1122/ofr20191122.pdf","text":"Report","size":"22.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1122"},{"id":370035,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1122/coverthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Haleakalā National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -156.275743,20.586349 ], [ -156.275743,20.795098 ], [ -156.020951,20.795098 ], [ -156.020951,20.586349 ], [ -156.275743,20.586349 ] ] ] } } ] }","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Director,
Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
The abandoned hydraulic mine pit at Malakoff Diggins near Grass Valley, California, can produce large volumes of eroded sediment transportable by storm runoff. Sediment-laden water discharged from the pit is a major source of heavy metals to Humbug Creek and the South Yuba River. To develop a comprehensive sediment budget for the Malakoff Diggins mine pit and identify sources of sediment and metals within the pit that can become entrained as suspended sediment in runoff discharged from the pit, the U.S. Geological Survey, working in cooperation with the California Department of Water Resources, the California Department of Parks and Recreation, and the Nevada Irrigation District, used terrestrial laser scanning technology to quantify eroded volumes and erosion rates of sedimentary units exposed in the pit walls. The results for eroded volumes and rates reported here are part one of a three-part study.
High-resolution terrestrial laser scanning surveys were repeated annually from 2014 through 2017, including before and after dry and wet winters, measuring centimeter-scale topographic changes to quantify the volume of sediment eroded from outcrops at Malakoff Diggins State Historic Park, located on the western slope of the northern Sierra Nevada about 17 kilometers northeast of Grass Valley, California. Terrestrial laser scanning enabled construction of three-dimensional maps of the complex outcrop surfaces, which could not be mapped non-destructively or in sufficient detail with traditional surveying techniques. Eroded volumes from discrete sedimentary units were calculated at four study sites (numbered 1, 2, 4, and 5) throughout the mine pit for the December 2014 to August 2017 period.
Eroded volumes at the four study sites during the 32-month study ranged from 288 plus or minus (±) 13 cubic meters (m3) of sediment at site 1 to 8,517±145 m3 at site 4. Annual erosion rates at the four study sites ranged from 0.06±0.01 cubic meters per square meter per year (m3/m2/yr) at site 4 to 0.14±0.01 m3/m2/yr at site 2. The total eroded volume documented with terrestrial laser scanning at all four study sites from December 2014 to August 2017 was 12,934±334 m3 of sediment, and the average annual erosion rate for the four study sites was 0.10±0.04 m3/m2/yr.
Horizontal erosional-change maps indicate that a variety of erosional processes were responsible for the eroded sediment volume. These included areally broad and smaller-scale processes such as persistent dry ravel, periodic sheet wash, and frost heave and more localized and larger-scale processes such as coalescing fluvial incision, rotational landslides, and translational block-fall failures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191124","collaboration":"In cooperation with the California Department of Water Resources, the California Department of Parks and Recreation, and the Nevada Irrigation District","usgsCitation":"Howle, J.F., Alpers, C.N., Ward, A.J., Bond, S., and Curtis, J.A., 2019, Quantifying erosion rates by using terrestrial laser scanning at Malakoff Diggins State Historic Park, Nevada County, California, 2014–17: U.S. Geological Survey Open-File Report 2019–1124, 39 p., https://doi.org/10.3133/ofr20191124.","productDescription":"Report: viii, 39 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-087722","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":399420,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109574.htm"},{"id":370127,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1124/coverthb.jpg"},{"id":370129,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H3VNSN","linkHelpText":"Terrestrial Laser Scanning Data from Malakoff Diggins State Historic Park, Nevada County, California, 2014–17"},{"id":370128,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1124/ofr20191124.pdf","text":"Report","size":"12.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1124"},{"id":370856,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95RLMEI","linkHelpText":"Geochemical, Mineralogical, and Grain-Size Data for In Situ Solid Materials and Suspended Sediment at Malakoff Diggins State Historic Park, Nevada County, California"}],"country":"United States","state":"California","county":"Nevada County","otherGeospatial":"Malakoff Diggins State Historic Park","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-120.0032,39.448],[-120.0034,39.4331],[-120.0036,39.4181],[-120.0037,39.4049],[-120.0039,39.3909],[-120.0042,39.3741],[-120.0047,39.3451],[-120.005,39.3297],[-120.0047,39.3161],[-120.0124,39.3161],[-120.1867,39.3166],[-120.346,39.3165],[-120.3978,39.3166],[-120.5423,39.3155],[-120.6362,39.3151],[-120.6457,39.315],[-120.654,39.3104],[-120.6623,39.3103],[-120.6724,39.3098],[-120.6819,39.3065],[-120.6937,39.3023],[-120.7049,39.2977],[-120.709,39.2945],[-120.7161,39.2913],[-120.7262,39.2884],[-120.7309,39.2866],[-120.7356,39.2829],[-120.7456,39.2765],[-120.7526,39.2696],[-120.7572,39.265],[-120.7626,39.2636],[-120.7655,39.2599],[-120.7713,39.2558],[-120.7784,39.2539],[-120.7843,39.2484],[-120.7907,39.2429],[-120.796,39.2397],[-120.8019,39.2351],[-120.8095,39.2323],[-120.8202,39.2281],[-120.8249,39.2258],[-120.8278,39.2235],[-120.8401,39.2152],[-120.8531,39.2105],[-120.8582,39.195],[-120.8622,39.1905],[-120.8668,39.1832],[-120.884,39.1784],[-120.8875,39.177],[-120.8958,39.1756],[-120.9041,39.1759],[-120.9081,39.17],[-120.9075,39.1659],[-120.9134,39.165],[-120.9169,39.164],[-120.9234,39.1626],[-120.9263,39.1562],[-120.9286,39.1562],[-120.9363,39.1556],[-120.9368,39.1493],[-120.9479,39.1423],[-120.9508,39.1373],[-120.9672,39.1272],[-120.9747,39.1171],[-120.9829,39.1093],[-120.9882,39.111],[-120.9879,39.0947],[-120.9935,39.0788],[-120.9975,39.0724],[-120.9974,39.0674],[-120.9992,39.0656],[-121.0044,39.0614],[-121.0073,39.0569],[-121.0089,39.0519],[-121.0142,39.0468],[-121.0195,39.0449],[-121.0212,39.0404],[-121.0282,39.0376],[-121.0298,39.0312],[-121.0309,39.0249],[-121.0367,39.0193],[-121.0402,39.0148],[-121.0537,39.011],[-121.0578,39.0096],[-121.0649,39.0063],[-121.0696,39.0053],[-121.0755,39.0062],[-121.0803,39.0093],[-121.0899,39.0137],[-121.0987,39.0109],[-121.1054,39.0171],[-121.1101,39.0184],[-121.1184,39.0192],[-121.1204,39.0264],[-121.1252,39.0314],[-121.133,39.0353],[-121.1395,39.0353],[-121.1442,39.0311],[-121.1472,39.0324],[-121.1541,39.0255],[-121.1612,39.0245],[-121.1682,39.0195],[-121.1717,39.0185],[-121.1771,39.0189],[-121.1876,39.0124],[-121.1942,39.0155],[-121.2031,39.0158],[-121.2095,39.0117],[-121.2213,39.0124],[-121.2262,39.0191],[-121.2323,39.0236],[-121.2441,39.022],[-121.2513,39.0247],[-121.2644,39.0295],[-121.268,39.0308],[-121.2788,39.0365],[-121.2791,39.1938],[-121.2794,39.2287],[-121.2735,39.2324],[-121.2706,39.2356],[-121.2696,39.2416],[-121.2673,39.2439],[-121.2663,39.2534],[-121.2592,39.2548],[-121.2575,39.2589],[-121.2582,39.263],[-121.2655,39.2706],[-121.2561,39.2762],[-121.2473,39.2795],[-121.2409,39.2846],[-121.226,39.2816],[-121.2183,39.2831],[-121.2155,39.2917],[-121.2079,39.2964],[-121.2015,39.3019],[-121.1991,39.3024],[-121.2047,39.3118],[-121.203,39.3182],[-121.1978,39.3214],[-121.1979,39.3291],[-121.1902,39.3297],[-121.1849,39.3307],[-121.1821,39.338],[-121.1785,39.3389],[-121.175,39.339],[-121.1714,39.339],[-121.1678,39.3386],[-121.1654,39.3368],[-121.1636,39.3337],[-121.16,39.3328],[-121.1576,39.3347],[-121.1571,39.3378],[-121.1566,39.3428],[-121.1555,39.3478],[-121.1532,39.3497],[-121.1473,39.3498],[-121.1449,39.3493],[-121.1437,39.3507],[-121.145,39.3534],[-121.1445,39.3575],[-121.138,39.3617],[-121.1363,39.3667],[-121.1334,39.3699],[-121.127,39.375],[-121.1271,39.379],[-121.1057,39.3798],[-121.1027,39.3816],[-121.0986,39.3835],[-121.0945,39.3876],[-121.0892,39.3881],[-121.0862,39.3891],[-121.0845,39.3927],[-121.081,39.3946],[-121.0709,39.3938],[-121.0631,39.3921],[-121.0584,39.3949],[-121.053,39.3959],[-121.0483,39.3955],[-121.0465,39.3941],[-121.0458,39.3919],[-121.044,39.3901],[-121.0404,39.3897],[-121.0375,39.3906],[-121.034,39.3956],[-121.031,39.3961],[-121.0286,39.3953],[-121.0256,39.3917],[-121.0226,39.3908],[-121.0197,39.3949],[-121.0132,39.3977],[-121.0079,39.4005],[-121.0151,39.4054],[-121.0056,39.4064],[-120.9962,39.4124],[-120.9897,39.4116],[-120.9849,39.4112],[-120.9784,39.4163],[-120.9737,39.419],[-120.9588,39.4156],[-120.9517,39.4166],[-120.9464,39.4207],[-120.9415,39.4167],[-120.9297,39.4186],[-120.9255,39.421],[-120.9148,39.4215],[-120.9095,39.4261],[-120.9018,39.4235],[-120.8828,39.4291],[-120.8733,39.4288],[-120.8644,39.4321],[-120.8543,39.4349],[-120.843,39.4359],[-120.8383,39.4391],[-120.8335,39.4347],[-120.8263,39.4352],[-120.8174,39.438],[-120.8121,39.4372],[-120.8032,39.4391],[-120.7925,39.4419],[-120.7837,39.4479],[-120.7706,39.4507],[-120.7594,39.4549],[-120.7523,39.4573],[-120.7458,39.46],[-120.7428,39.4619],[-120.7411,39.4683],[-120.728,39.4697],[-120.7227,39.4743],[-120.721,39.4762],[-120.7157,39.4798],[-120.7134,39.483],[-120.714,39.488],[-120.7052,39.4967],[-120.7005,39.5008],[-120.6881,39.5087],[-120.6793,39.5142],[-120.6722,39.5179],[-120.6645,39.5216],[-120.6585,39.5221],[-120.6526,39.5231],[-120.6472,39.5227],[-120.6389,39.5227],[-120.6341,39.5232],[-120.6305,39.5196],[-120.6251,39.5192],[-120.5798,39.521],[-120.566,39.5152],[-120.5582,39.5116],[-120.5528,39.5085],[-120.5472,39.4954],[-120.5394,39.49],[-120.5345,39.4842],[-120.5326,39.4756],[-120.5331,39.4643],[-120.5265,39.4598],[-120.5186,39.4558],[-120.5079,39.4527],[-120.5061,39.45],[-120.506,39.4473],[-120.4578,39.4472],[-120.3071,39.4478],[-120.2874,39.4484],[-120.2749,39.448],[-120.1825,39.4485],[-120.1653,39.4482],[-120.1593,39.4482],[-120.1438,39.4483],[-120.1087,39.4485],[-120.0962,39.4485],[-120.0866,39.4486],[-120.0694,39.4487],[-120.0664,39.4482],[-120.0562,39.4482],[-120.0479,39.4483],[-120.0312,39.4484],[-120.0032,39.448]]]},\"properties\":{\"name\":\"Nevada\",\"state\":\"CA\"}}]}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
In keeping with our national mission, the USGS in Alaska provides timely and objective scientific information to help the Nation address issues and solve problems in five major topical areas (listed alphabetically):
The USGS in Alaska engages about 400 scientists and support staff working in three major science centers, Cooperative Research Units, and USGS centers outside Alaska, with a combined annual science budget of about $60 million. In just the last 5 years, the USGS in Alaska has produced scientific benefits resulting from more than 1,000 publications and about 250 technical reports. Publications relevant to Alaska can be conveniently searched by keyword through the USGS Publications Warehouse at https://pubs.er.usgs.gov/search?q=Alaska.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191141","usgsCitation":"Williams, D.M., and Powers, E.M., eds., 2019, U.S. Geological Survey — Department of the Interior Region 11, Alaska—2019 annual science report: U.S. Geological Survey Open-File Report 2019–1141, 79 p., https://doi.org/10.3133/ofr20191141.","productDescription":"xi, 79 p.","numberOfPages":"79","onlineOnly":"Y","ipdsId":"IP-111992","costCenters":[{"id":113,"text":"Alaska Regional Director's Office","active":true,"usgs":true}],"links":[{"id":399429,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109573.htm"},{"id":370887,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1141/ofr20191141.pdf","text":"Report","size":"31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1141"},{"id":370886,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1141/coverthb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-141.0007667541504,69.64681951728146],[-141.064453125,69.80172356231073],[-141.767578125,69.96043926902489],[-142.734375,70.1478274118401],[-143.26171875,70.25945200030638],[-144.99755859375,70.1925497583889],[-146.14013671875,70.21487465331137],[-147.43652343749997,70.32613725493573],[-148.40332031249997,70.51024068514326],[-149.47998046875,70.63448406630856],[-149.85351562499997,70.63448406630856],[-150.64453125,70.59802116106809],[-151.611328125,70.61261423801925],[-151.8310546875,70.7724429742589],[-152.02880859375,70.90226826757711],[-152.666015625,71.0098110139634],[-153.52294921875,71.05979781529196],[-154.31396484375,70.95969716686398],[-154.70947265625,71.20191973293133],[-155.41259765625,71.3219146980122],[-156.46728515625,71.45515260247822],[-157.10449218749997,71.34301347171373],[-157.58789062499997,71.21607526596131],[-157.91748046875,70.99550574822297],[-158.62060546875,70.9883492241249],[-159.30175781249997,70.98119010476937],[-159.98291015625,70.94535555009823],[-160.51025390625,70.73622993891799],[-160.90576171875,70.58341752317065],[-161.5869140625,70.45150843439349],[-161.78466796875,70.45885925640687],[-162.5537109375,70.34092679475283],[-163.05908203125,70.09552886456429],[-163.388671875,69.81689109911446],[-163.564453125,69.51914693717981],[-164.02587890625,69.15474044269264],[-164.90478515625,69.03714171275197],[-165.69580078124997,68.97416358340674],[-166.26708984375,69.01354605132325],[-166.376953125,68.80004113882613],[-166.66259765624997,68.5443150407769],[-167.1240234375,68.39918004344189],[-166.61865234375,68.17155518732503],[-166.5087890625,67.99110834539984],[-165.87158203125,67.8672645403614],[-164.61914062499997,67.47492238478702],[-164.24560546874997,67.23806155909902],[-164.091796875,67.02458758377148],[-163.10302734375,66.87834504307976],[-163.05908203125,66.73990169639414],[-162.66357421875,66.58321725728175],[-162.333984375,66.48697584176404],[-162.3779296875,66.34632215978135],[-163.2568359375,66.31103501145373],[-163.19091796875,66.55700652350038],[-163.76220703124997,66.73990169639414],[-164.46533203125,66.69647781801481],[-165.30029296875,66.55700652350038],[-166.1572265625,66.41674787052298],[-166.9482421875,66.24916310923315],[-167.3876953125,66.01801815922045],[-168.42041015625,65.56754970214311],[-168.02490234375,65.33017791526855],[-167.45361328125,65.18303007291382],[-166.9921875,64.86760781632728],[-166.7724609375,64.49172504435471],[-165.69580078124997,64.24459476798195],[-164.59716796875,64.29229248039543],[-164.13574218749997,64.26368374017731],[-163.49853515625,64.18724867664994],[-162.5537109375,64.27322328178595],[-161.82861328124997,64.24459476798195],[-161.52099609375,63.93737246791484],[-163.125,63.68524808030715],[-163.93798828125,63.41119772365924],[-164.5751953125,63.32254947641308],[-165.41015625,63.15435519659187],[-165.78369140625,62.75472592723178],[-166.26708984375,62.42090322195164],[-166.5966796875,62.155240711732425],[-166.48681640625,61.616843178481375],[-166.2451171875,61.23853141060282],[-165.849609375,60.8663124746226],[-166.5966796875,60.56537850464181],[-167.34375,60.468050120874615],[-167.80517578125,60.20707506634915],[-167.8271484375,60.09771842541544],[-167.89306640624997,59.93300042374631],[-167.03613281249997,59.712097173322924],[-166.640625,59.61221219518693],[-165.95947265624997,59.60109549032134],[-165.47607421874997,59.74532608213611],[-165.10253906249997,59.95501026206206],[-164.794921875,59.987997631212224],[-164.72900390624997,59.7563950493563],[-164.46533203125,59.54545678424146],[-163.8720703125,59.54545678424146],[-163.14697265625,59.60109549032134],[-162.26806640625,59.62332522313024],[-162.20214843749997,59.17592824927136],[-162.35595703125,58.81374171570782],[-162.57568359375,58.6769376725869],[-162.09228515625,58.39019698411526],[-161.455078125,58.39019698411526],[-160.68603515625,58.44773280389084],[-160.1806640625,58.516651799363785],[-159.71923828125,58.58543569119917],[-159.43359375,58.47072082411973],[-159.08203125,58.33256713195789],[-158.55468749999997,58.286395482881034],[-158.44482421874997,58.619777025081675],[-157.60986328125,58.52812515905843],[-158.00537109375,58.00809779306888],[-158.48876953125,57.468589192089354],[-159.49951171875,56.84897198026975],[-161.0595703125,56.389583525613055],[-164.9267578125,54.97761367069628],[-165.9814453125,54.470037612805754],[-168.55224609375,53.73571574532637],[-173.232421875,52.92215137976296],[-175.62744140624997,52.3755991766591],[-177.86865234375,52.13348804077147],[-178.9453125,50.98609893339354],[-178.00048828125,51.440312757160115],[-176.8359375,51.467696956223364],[-175.36376953125,51.7406361640977],[-171.826171875,52.119998657638156],[-167.62939453124997,52.9883372533954],[-166.728515625,53.186287573913305],[-165.9375,53.553362785528094],[-165.30029296875,53.76170183021049],[-164.3115234375,54.149567212540525],[-163.89404296875,54.29088164657006],[-163.3447265625,54.18815548107151],[-162.26806640625,54.07228265560388],[-162.09228515625,54.3549556895541],[-161.89453125,54.7246201949245],[-161.0595703125,54.80068486732233],[-160.400390625,54.67383096593114],[-159.19189453125,54.61025498157912],[-159.14794921875,55.07836723201515],[-158.79638671875,55.429013452407396],[-157.58789062499997,55.825973254619015],[-155.7421875,55.541064956111036],[-154.62158203125,56.01066647040695],[-153.47900390625,56.43820369358165],[-151.45751953125,57.397624055000456],[-151.4794921875,58.07787626787517],[-151.45751953125,58.75680543225761],[-149.74365234374997,59.38917842312835],[-148.51318359375,59.63443457494949],[-146.689453125,59.355596110016315],[-144.51416015625,59.75086102411168],[-144.3109130859375,59.87239799228177],[-143.8330078125,59.968758992382334],[-143.0694580078125,60.031929699115615],[-141.5533447265625,59.842055288480076],[-140.9051513671875,59.68160832698723],[-140.020751953125,59.478568831926395],[-139.1693115234375,59.234986238722],[-138.82873535156247,59.09138238455909],[-138.3233642578125,58.96983560365735],[-138.1146240234375,58.862064179600374],[-138.076171875,58.722598828043374],[-136.9775390625,58.19387126497797],[-136.56005859375,57.7862326105289],[-135.966796875,57.33838126552897],[-136.03271484375,57.052681978717494],[-135.81298828125,56.92099675839107],[-134.571533203125,55.8845546603819],[-134.2034912109375,55.56592203025787],[-133.8958740234375,55.263468250921285],[-133.7530517578125,55.06264118216743],[-133.6102294921875,54.64523407607479],[-133.2421875,54.635697306063854],[-130.6171417236328,54.70637513489091],[-130.62950134277344,54.72422365048395],[-130.62606811523438,54.73651472417763],[-130.65765380859375,54.762274228176494],[-130.62950134277344,54.78247406031503],[-130.5663299560547,54.79237225560392],[-130.49697875976562,54.82877675365454],[-130.42282104492188,54.87423625974835],[-130.34591674804688,54.91569803760518],[-130.27244567871094,54.97288463122321],[-130.18661499023438,55.062247951730015],[-130.18043518066406,55.091729515360875],[-130.15090942382812,55.12393783348962],[-130.14747619628906,55.14160209881279],[-130.10284423828125,55.19219635238084],[-129.97169494628906,55.28146181651345],[-129.97581481933594,55.30022902025666],[-130.02044677734375,55.33890835596374],[-130.0396728515625,55.45043679812318],[-130.0884246826172,55.496749338303694],[-130.12825012207028,55.58144971869657],[-130.10971069335938,55.68223010941079],[-130.14816284179688,55.71473455012689],[-130.15296936035156,55.7649857705176],[-130.12550354003906,55.80475427021683],[-130.0843048095703,55.82134464477078],[-130.00465393066406,55.90573012454021],[-130.00465393066406,55.9130425993163],[-130.0190734863281,55.912657766599715],[-130.00259399414062,56.00605986001467],[-130.10421752929688,56.12297419573329],[-130.24635314941406,56.09693875609652],[-130.3479766845703,56.12794955397159],[-130.42556762695312,56.14134155069025],[-130.4674530029297,56.24373146827144],[-130.55740356445312,56.249454174583384],[-130.5677032470703,56.25479459547735],[-130.62400817871094,56.2685236855868],[-130.78262329101562,56.36715174252849],[-131.08612060546875,56.40668363558357],[-131.16989135742188,56.44883107459549],[-131.473388671875,56.551913918713375],[-131.58119201660156,56.61204220477141],[-131.8352508544922,56.59843662755775],[-131.85997009277344,56.702620872371355],[-131.89979553222656,56.75347577609789],[-131.87232971191406,56.805765643008264],[-132.12432861328122,56.87374615531272],[-132.0467376708984,57.04521234171931],[-132.3687744140625,57.09149987857074],[-132.2472381591797,57.211056900559335],[-132.3680877685547,57.347273783306676],[-132.55210876464844,57.49516565182901],[-132.65853881835938,57.61562391374733],[-132.75466918945312,57.69680911844304],[-132.8693389892578,57.83853792318956],[-133.06983947753906,58.00082136594698],[-133.17283630371094,58.15404059343076],[-133.34518432617188,58.27628739957773],[-133.45985412597656,58.38731772556939],[-133.37608337402344,58.430481925680034],[-133.70567321777344,58.611194853078764],[-133.83956909179685,58.730440812979516],[-134.25979614257812,58.861354043320055],[-134.3360137939453,58.92414471817596],[-134.3140411376953,58.962755708753306],[-134.4060516357422,58.978683427688686],[-134.38133239746094,59.03878841190553],[-134.44656372070312,59.08820785301446],[-134.48501586914062,59.13121539881386],[-134.56329345703125,59.130510792073984],[-134.67933654785156,59.191757369765085],[-134.70130920410156,59.24973478117606],[-134.95742797851562,59.279914277804906],[-135.02883911132812,59.34649517787861],[-134.9897003173828,59.3877798237848],[-135.10093688964844,59.42622028594434],[-135.07827758789062,59.45275367774563],[-135.0274658203125,59.47473269180728],[-135.03021240234375,59.564245132658975],[-135.11810302734372,59.62367244601488],[-135.15586853027344,59.625061301654334],[-135.2190399169922,59.6632323288228],[-135.23345947265625,59.69650975428769],[-135.252685546875,59.69789559656873],[-135.36048889160156,59.73598378851403],[-135.4779052734375,59.79821644465919],[-135.94894409179688,59.6632323288228],[-136.1927032470703,59.63998787256213],[-136.34788513183594,59.60109549032134],[-136.25038146972656,59.56633207991906],[-136.24076843261716,59.55972296971678],[-136.24076843261716,59.52387204745182],[-136.3066864013672,59.46461714320982],[-136.36642456054688,59.4496126517294],[-136.47628784179688,59.46566371970234],[-136.46804809570312,59.28552611855346],[-136.49620056152344,59.27465233689575],[-136.4900207519531,59.26096748461385],[-136.5840911865234,59.166075318301345],[-136.8285369873047,59.16009179641602],[-136.8793487548828,59.13544273484683],[-137.28240966796875,59.0009698708429],[-137.449951171875,58.908900972391415],[-137.52548217773438,58.906418795609426],[-137.5000762939453,58.985760051467075],[-137.54127502441406,59.10478272378236],[-137.60787963867188,59.24376590151355],[-138.62617492675778,59.76746035005358],[-138.66600036621094,59.80961318716828],[-138.6797332763672,59.84481485969105],[-138.70582580566406,59.90650046741583],[-139.05258178710938,59.994179105518434],[-139.19952392578125,60.08950200748712],[-139.0711212158203,60.3187885497516],[-139.07386779785156,60.35243208301854],[-139.69253540039062,60.33544473468298],[-139.97955322265625,60.181818669034776],[-140.4595184326172,60.30858669066228],[-140.5199432373047,60.22003701633967],[-141.00128173828125,60.3058656567224],[-141.0007667541504,69.64681951728146]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-173.07586669921875,60.72157115165579],[-173.155517578125,60.69469537287745],[-173.15277099609375,60.64356945377967],[-173.08135986328125,60.61123754937553],[-173.04016113281247,60.58157148491742],[-173.08135986328125,60.53972302275651],[-173.089599609375,60.511343283202464],[-173.05938720703125,60.4788788301667],[-172.98248291015625,60.468050120874615],[-172.94677734374997,60.43689744859958],[-172.8424072265625,60.403001945865476],[-172.78472900390625,60.373144671593685],[-172.7105712890625,60.329667021005825],[-172.6611328125,60.3187885497516],[-172.5897216796875,60.309266913738156],[-172.49908447265625,60.31606836555203],[-172.4139404296875,60.3187885497516],[-172.35076904296875,60.3187885497516],[-172.30682373046872,60.29021531318375],[-172.2381591796875,60.29021531318375],[-172.17498779296875,60.30518536282736],[-172.2381591796875,60.333745513303114],[-172.34527587890625,60.378575303227215],[-172.364501953125,60.40164539086417],[-172.43041992187497,60.40571488624096],[-172.4798583984375,60.39757538658664],[-172.57598876953125,60.41249624776229],[-172.6556396484375,60.43689744859958],[-172.77374267578122,60.4788788301667],[-172.83416748046875,60.50052541051131],[-172.89459228515625,60.550527811064846],[-172.8863525390625,60.588316165776824],[-172.91656494140625,60.62606036274505],[-172.98797607421875,60.658377412327326],[-173.01544189453125,60.69469537287745],[-173.07586669921875,60.72157115165579]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-171.650390625,63.809167882566385],[-171.793212890625,63.82128765261384],[-171.80419921875,63.73147780336167],[-171.8426513671875,63.65601144183318],[-171.8865966796875,63.54365806976644],[-171.859130859375,63.42594585479083],[-171.7877197265625,63.34966546248425],[-171.62841796875,63.32501562217765],[-171.474609375,63.28306240110864],[-171.353759765625,63.29540792564745],[-171.2548828125,63.33980806067484],[-171.1395263671875,63.38413977217118],[-171.002197265625,63.389061297647125],[-170.760498046875,63.34966546248425],[-170.57373046875,63.32501562217765],[-170.41992187499997,63.27812271092345],[-170.343017578125,63.1989725264735],[-170.3594970703125,63.156835740093236],[-170.2496337890625,63.156835740093236],[-170.145263671875,63.156835740093236],[-170.0408935546875,63.14194929585152],[-169.9090576171875,63.087300267152735],[-169.8321533203125,63.03753005973634],[-169.7991943359375,62.990169510232555],[-169.8101806640625,62.95522304515911],[-169.74975585937497,62.922735326966595],[-169.617919921875,62.91523303947614],[-169.54650878906247,62.9502272814474],[-169.4915771484375,62.97270150065472],[-169.508056640625,62.99765260346662],[-169.4970703125,63.04251090966805],[-169.43664550781247,63.08978654472616],[-169.34326171874997,63.11712157280328],[-169.178466796875,63.13946747896222],[-169.1070556640625,63.14443090047572],[-168.958740234375,63.104699747121074],[-168.760986328125,63.112153479825004],[-168.67309570312497,63.203925767041305],[-168.662109375,63.26576978358972],[-168.7115478515625,63.3348780927218],[-168.92578125,63.366907787681754],[-169.07958984374997,63.366907787681754],[-169.25537109375,63.37183226679281],[-169.420166015625,63.376755901872734],[-169.5245361328125,63.389061297647125],[-169.6124267578125,63.43331707559086],[-169.705810546875,63.46278300222105],[-169.8211669921875,63.46523712749102],[-169.947509765625,63.48976680530999],[-170.0079345703125,63.59011870211632],[-170.0958251953125,63.658448979940175],[-170.2386474609375,63.704722429433225],[-170.4638671875,63.73390885572919],[-170.5902099609375,63.721751503619956],[-170.7659912109375,63.6779417467744],[-171.2164306640625,63.648697570849286],[-171.474609375,63.6779417467744],[-171.54052734375,63.75334975181205],[-171.650390625,63.809167882566385]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-170.40618896484375,57.022794415389725],[-170.3155517578125,57.043718234032625],[-170.22216796875,57.119841130872615],[-170.1947021484375,57.14518072479997],[-170.11505126953125,57.18985535714817],[-170.08209228515625,57.227042992549855],[-170.07110595703125,57.271618718194446],[-170.189208984375,57.23893512461504],[-170.2386474609375,57.22852971878346],[-170.32928466796875,57.22852971878346],[-170.3704833984375,57.22406936030381],[-170.49407958984375,57.20473490715757],[-170.41992187499997,57.12878649751151],[-170.364990234375,57.11387635258491],[-170.42266845703125,57.06910989239133],[-170.46112060546875,57.033257797376066],[-170.40618896484375,57.022794415389725]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-169.8321533203125,56.62904228542147],[-169.8211669921875,56.60486209416893],[-169.7991943359375,56.586716786451156],[-169.71405029296875,56.565536245992064],[-169.71405029296875,56.551913918713375],[-169.63165283203125,56.51707901932375],[-169.56024169921875,56.515563731608296],[-169.5025634765625,56.553427752820355],[-169.43115234375,56.58369172128337],[-169.43664550781247,56.626020608371924],[-169.56024169921875,56.63055303322322],[-169.6783447265625,56.62450967912138],[-169.8321533203125,56.62904228542147]]]}}]}","contact":"Director,
Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Beach erosion is a persistent problem along most open-ocean shores of the United States. Along the Arctic coast of Alaska, coastal erosion is widespread and threatens communities, defense and energy-related infrastructure, and coastal habitat. As coastal populations continue to expand and infrastructure and habitat are increasingly threatened by erosion, there is increased demand for accurate information regarding past and present trends and rates of shoreline movement.
Shoreline change was evaluated by comparing three to four historical shoreline positions derived from 1950s-era topographic surveys and black and white aerial photography, 1980s-era color-infrared Alaska High-Altitude Aerial Photography, 2003 natural color aerial photography, and 2010s-era natural color aerial photography. Long-term (1950s–2010s) and short-term (1980s–2010s) shoreline change rates were calculated using linear-regression and end-point methods, respectively, at transects spaced approximately every 50 meters along both the mainland and barrier island coasts.
Shoreline change rates calculated on more than 24,000 individual transects indicate that between 1948 and 2016 the northern coast of Alaska between Icy Cape and Cape Prince of Wales was slightly erosional, with 68 percent of the total transects showing shoreline retreat over the long term and 63 percent over the short term. However, only 9 percent of the total transects showed shoreline retreat greater than 1 meter per year (m/yr) over the long and short term, respectively. Mean rates of shoreline change of −0.2±0.1 and −0.2±0.3 m/yr, were calculated for the long and short term, respectively. Many rates measured were near the limit of our shoreline change uncertainty estimates. Erosion and accretion rates on individual transects ranged from −8.3 to +9.6 m/yr over the long term and −16.0 to +20.0 m/yr over the short-term analysis periods. The highest rates of erosion and accretion were associated with the formation and migration of inlets along barrier island coasts. The highest erosional rates of change were measured in the southern part of the study area between Sullivan Lake and Cape Prince of Wales. The highest accretional rates of change were measured in the northern part of the study area on the open-ocean coast of barrier islands fronting Kasegaluk Lagoon.
Open-ocean exposed shorelines compose 85 percent of all transects and 70 percent were erosional over the long term. Sheltered mainland-lagoon shorelines compose 15 percent of all transects in the study area and 58 percent were erosional over the long term. Although mean shoreline change rates were quite low along all coasts, exposed shorelines retreated at twice the rate (−0.2±0.1 m/yr) of sheltered shorelines (−0.1±0.1 m/yr). Barrier shoreline transects (includes barrier islands, spits, and beaches) compose 49 percent of the total transects and 56 percent of all exposed shoreline transects. Mean shoreline change rates on exposed barrier shorelines were only slightly greater than exposed mainland shorelines (−0.3±0.1 and −0.2±0.1 m/yr, respectively). Mean shoreline change rates on sheltered barrier shorelines were similar to sheltered mainland shorelines (−0.1±0.3 m/yr).
In contrast to the majority of the Nation’s shorelines, for all but three months of the year (July–September), the north coast of Alaska has historically been protected by landfast sea ice from processes such as waves, winds, and currents that typically drive coastal change on beaches in more temperate regions of the world. Projected and observed increases in periods of sea-ice-free conditions, as sea ice melts earlier and forms later in the year, particularly in the autumn, when large storms are more common in the Arctic, suggest that Arctic coasts will be more vulnerable to storm surge and wave energy, potentially resulting in accelerated shoreline erosion and terrestrial habitat loss in the future. Increases in air and sea water temperatures may also increase erosion of the ice-rich, coastal permafrost bluffs present along much of Alaska’s Arctic coast. More frequent shoreline change data collection and analysis in this rapidly changing environment should be considered in order to evaluate shoreline change trends in the future.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191146","usgsCitation":"Gibbs, A.E., Snyder, A.G., and Richmond, B.M., 2019, National assessment of shoreline change — Historical shoreline change along the north coast of Alaska, Icy Cape to Cape Prince of Wales: U.S. Geological Survey Open-File Report 2019–1146, 52 p., https://doi.org/10.3133/ofr20191146.","productDescription":"Report: vi, 52 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-111408","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":399433,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109572.htm"},{"id":370888,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1146/coverthb.jpg"},{"id":370889,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1146/ofr20191146.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1146"},{"id":370890,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H1S1PV","linkHelpText":"National assessment of shoreline change—A GIS compilation of updated vector shorelines and associated shoreline change data for the north coast of Alaska, Icy Cape to Cape Prince of Wales"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168.1194,\n 65.5739\n ],\n [\n -160.9839,\n 65.5739\n ],\n [\n -160.9839,\n 70.3322\n ],\n [\n -168.1194,\n 70.3322\n ],\n [\n -168.1194,\n 65.5739\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060