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variants of Ecological Systems, such as pine versus oak within pine-oak Ecological
               Systems.

               The National Landcover Dataset (NLCD) (http://landcover.usgs.gov/uslandcover.php),
               the USGS GAP Analysis dataset (http://gapanalysis.nbii.gov/portal/server.pt), and the
               national LandFire map (http://www.landfire.gov) data set are all done at 30 m spatial
               resolution.  While useful, none of these maps seemed adequate to facilitate
               management and conservation efforts at fine enough spatial and thematic (number of
               mapped types) resolution for Oklahoma.  Therefore, the following criteria were set
               forward for the Ecological Systems map:

               Conform to the National Ecological Systems Classification framework
               Collect quantitative, georectified ground data (>3000 points) in support of the mapping
               Spatial resolution at 10 m
               Thematic resolution at >175 mapped types, including ruderal or invasive types
               Polygon-based, to facilitate easy modifications
               Summarized and interpreted for natural resource managers

               Aspects of the work flow included coordination between OU, ODWC, and MoRAP, and
               coordination among MoRAP staff members with diverse skill sets.  A fairly complex and
               time –intensive set of tasks was performed.  In broad outline, these steps included
               (Figure 2):

                   1.  Identification of mapping targets.  This step took the shape of a two-day meeting
                       with staff from ODWC, OU, and MoRAP.  Draft mapping targets were developed
                       from the Ecological Systems classification for the USA, and naming conventions
                       were adopted and modified from the Texas mapping effort.
                   2.  Collection of field data.  A standardized, quantitative, spatially specific
                       methodology was used to collect >3,000 field observations.
                   3.  Remote sensing classification of land use/landcover.  Three date mosaics of
                       Thematic Mapper Satellite Imagery were used to perform a supervised
                       classification (see methods, below).
                   4.  Development of abiotic information.  Soil groups from county digital soil surveys
                       formed the backbone of this effort, and the development of these from
                       information supplied by the National Resources Conservation Service (NRCS)
                       was an iterative process.  Soil groups were created initially from the ecological
                       site types, viewed, and revised, sometimes by hand, as needed.  Digital elevation
                       model (DEM)-derived variables were also used.  Percent slope was the only
                       DEM-derived variable used, though other geomorphic parameters were included





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