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This dataset depicts roads built on the Tongass National Forest prior to 1960. This dataset is part of a larger analysis of road building and timber harvest on the Tongass National Forest, compiled for the report Scientific Basis for Roadless Area Conservation (http://www.consbio.org/cbi/projects/show.php?page=roadless/roadless.htm), pp 70-73. Road segments from a US Forest Service roads layer were attributed to the most likely decade in which the road was built, as determined by an analysis of connectivity to clearcuts on the Tongass National Forest from that decade. It was assumed that following 1960, harvests required access to mills or extraction sites, and thus roads connecting to them were most likely built...
This dataset depicts roads built on the Tongass National Forest during the 1960s. This dataset is part of a larger analysis of road building and timber harvest on the Tongass National Forest, compiled for the report Scientific Basis for Roadless Area Conservation (http://www.consbio.org/cbi/projects/show.php?page=roadless/roadless.htm), pp 70-73. Road segments from a US Forest Service roads layer were attributed to the most likely decade in which the road was built, as determined by an analysis of connectivity to clearcuts on the Tongass National Forest from that decade. It was assumed that following 1960, harvests required access to mills or extraction sites, and thus roads connecting to them were most likely built...
These data were compiled for the use of training natural feature machine learning (GeoAI) detection and delineation. The natural feature classes include the Geographic Names Information System (GNIS) feature types Basins, Bays, Bends, Craters, Gaps, Guts, Islands, Lakes, Ridges and Valleys, and are an areal representation of those GNIS point features. Features were produced using heads-up digitizing from 2018 to 2019 by Dr. Sam Arundel's team at the U.S. Geological Survey, Center of Excellence for Geospatial Information Science, Rolla, Missouri, USA, and Dr. Wenwen Li's team in the School of Geographical Sciences at Arizona State University, Tempe, Arizona, USA. Figure 1 shows the areal boundary (cyan) of Bachelor...
This dataset depicts roads built on the Tongass National Forest during the 1970s. This dataset is part of a larger analysis of road building and timber harvest on the Tongass National Forest, compiled for the report Scientific Basis for Roadless Area Conservation (http://www.consbio.org/cbi/projects/show.php?page=roadless/roadless.htm), pp 70-73. Road segments from a US Forest Service roads layer were attributed to the most likely decade in which the road was built, as determined by an analysis of connectivity to clearcuts on the Tongass National Forest from that decade. It was assumed that following 1960, harvests required access to mills or extraction sites, and thus roads connecting to them were most likely built...
Due to the great differences in knowledge and availability of information on the biodiversity of the different marine regions from Mexico, it was decided to use the opinion of experts for the identification of the high-priority sites for the conservation of the marine biodiversity that includes coasts, the oceans and islands. For this aim, an experts workshop was conducted in October 2005 to determine the marine and coastal high-priority sites for conservation in Mexico. The workshop was organized by CONABIO, CONANP, Pronatura and TNC. After the workshop, the resulting sites were delimited and validated by means of an internet Wiki site, which served like a vestibule for the exchange of information and opinions...
This dataset depicts roads built on the Tongass National Forest during the 1990s. This dataset is part of a larger analysis of road building and timber harvest on the Tongass National Forest, compiled for the report Scientific Basis for Roadless Area Conservation (http://www.consbio.org/cbi/projects/show.php?page=roadless/roadless.htm), pp 70-73. Road segments from a US Forest Service roads layer were attributed to the most likely decade in which the road was built, as determined by an analysis of connectivity to clearcuts on the Tongass National Forest from that decade. It was assumed that following 1960, harvests required access to mills or extraction sites, and thus roads connecting to them were most likely built...
A new 30-m spatial resolution global shoreline vector (GSV) was developed from annual composites of 2014 Landsat satellite imagery. The semi-automated classification of the imagery was accomplished by manual selection of training points representing water and non-water classes along the entire global coastline. Polygon topology was applied to the GSV, and the resulting polygons were mapped into four size classes of islands: Continental Mainlands, Big Islands (greater than 1 km2), Small Islands (less than or equal to 1 km2 and greater than or equal to 0.0036 km2), and Very Small Islands (less than 0.0036 km2).
Categories: Data;
Types: ArcGIS Map Package,
Downloadable;
Tags: Geography,
Remote Sensing,
USGS Science Data Catalog (SDC),
global,
islands
This dataset displays the boundaries of Intact Forest Landscapes for the islands in the Tongass region of the state of Alaska. Intact Forest Landscapes for islands are defined as areas at least 500 hectares that are absent of human disturbance visible on satellite imagery (e.g., roads, logging, mining, settlement). For more information, see the full report, available on the Global Forest Watch website (www.globalforestwatch.org), or the Conservation Biology Institute website (http://www.consbio.org/cbi/projects/show.php?page=alaska).
This dataset depicts roads built on the Tongass National Forest during the 1980s. This dataset is part of a larger analysis of road building and timber harvest on the Tongass National Forest, compiled for the report Scientific Basis for Roadless Area Conservation (http://www.consbio.org/cbi/projects/show.php?page=roadless/roadless.htm), pp 70-73. Road segments from a US Forest Service roads layer were attributed to the most likely decade in which the road was built, as determined by an analysis of connectivity to clearcuts on the Tongass National Forest from that decade. It was assumed that following 1960, harvests required access to mills or extraction sites, and thus roads connecting to them were most likely built...
We investigated whether foraging habitat, sex, or fidelity to a foraging area effected blood mercury concentrations in western gulls (Larus occidentalis) from three colonies on the west coast of the United States. Dataset includes total mercury concentrations in western gulls from three colony locations and associated foraging habitat of individual gulls. These data support the following publication: Clatterbuck, C.A., Lewison, R.L., Orben, R.A., Ackerman, J.T., Torres, L.G., Suryan, R.M., Warzybok, P., Jahncke, J. and Shaffer, S.A., 2021. Foraging in marine habitats increases mercury concentrations in a generalist seabird. Chemosphere, p.130470.
Categories: Data;
Tags: Environmental Health,
Pacific Ocean,
USGS Science Data Catalog (SDC),
Wildlife Biology,
biota,
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