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ClimateWNA was used to downscale historical data and future climate projections to a 1-km 2 grid. ClimateWNA is a program that generates both directly calculated and derived climate variables for specific locations across western North America (Wang et al. 2012) using Parameter-elevation Regressions on Independent Slopes Model (PRISM). We generated annual, seasonal and monthly climate data for the period 1961 to 1990. For future climate projections, we used the SRES A2 greenhouse-gas emissions scenario from the IPCC Fourth Assessment Report. We generated five sets of future climate projections averaged for the time period 2070-2099: BCCR BCM2.0, CCCMA CGCM3, CSIRO MK 3.0, INMCM 3.0, MIROC3.2 MEDRES. Downloads:...
Fish distribution in Umpqua National Forest. The cover was built at two locations and by two people. Cottage Grove prepared the Cottage Grove district fish distribution and the Supervisors office prepared the fish distribution for Tiller, North Umpqua, and Diamond Lake districts. The SO then merged the two layers together. The fish distribution layer was developed using the existing stream layer, then identifying those streams and stream breaks for each fish species. The streams that don't have any fish distribution were deleted fom the layer. Arcview was the program used to create the layer utilizing heads-up digitizing to identify the breaks. This cover was built at a map scale of 1:24000.
Vegetation types from Kuchler (1975) potential vegetation map were aggregated into 35 classes as part of the VEMAP project (Vegetation/Ecosystem Modeling and Analysis Project, Kittel et al. 1995). Functional vegetation types were reclassified (grouped in ArcMap) by the Conservation Biology Institute to reflect the classification scheme used by Brendan Rogers.
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USGS Topo Map Vector Data (Vector) 6739 Calico Butte, Nevada 20180816 for 7.5 x 7.5 minute Shapefile
Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
Types: Citation;
Tags: 7.5 x 7.5 minute,
7.5 x 7.5 minute,
Combined Vector,
Combined Vector,
Combined Vector,
![]() Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
Types: Citation;
Tags: 7.5 x 7.5 minute,
7.5 x 7.5 minute,
Combined Vector,
Combined Vector,
Combined Vector,
![]() Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
Types: Citation;
Tags: 7.5 x 7.5 minute,
7.5 x 7.5 minute,
Combined Vector,
Combined Vector,
Combined Vector,
![]() Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
Types: Citation;
Tags: 7.5 x 7.5 minute,
7.5 x 7.5 minute,
Combined Vector,
Combined Vector,
Combined Vector,
![]() Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
![]() Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
![]() Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
![]() Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
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