Abstract:
Conflict over the best way to manage Oregon's public lands makes a land
planner's job extremely challenging. Multiple uses, federal mandates, and
constantly evolving knowledge all contribute to the difficulty of determining how to
best use the land. The Coastal Landscape Analysis and Modeling Study
(CLAMS) was developed in 1994 to help policy makers better evaluate potential
land management plans and to examine the effects and interactions of
ecological, economic, and social models on a regional scale. Geographic
Information Systems (GIS) are used in CLAMS to simulate and demonstrate the
spatial effects of alternative policies. The dynamic nature of land use and
planning lends itself well to GIS, a powerful computer-based tool that can
expediently illustrate different management scenarios.
One component of CLAMS focuses on social aspects, including
recreational use of forestlands. In 1997, a prototype model for assessing the
amount of recreation habitat was developed in the Coos Bay (Oregon) Bureau of
Land Management (BLM) District. The study served as an inventory for
recreation planners to identify the existing recreation opportunities. Geographic
Information Systems and the Recreation Opportunity Spectrum (ROS) were
combined in order to determine acreage of different recreation habitat types, or
ROS classes.
My project incorporates many features of the Coos Bay study (combining
GIS and ROS) but extends the geographic boundaries to include most of the
Oregon coast range. It also extends the analysis by integrating the recreation
model with a landscape change model7 to show how recreation opportunities
would change over a 100 year simulation of landscape conditions. It will provide
land planners and recreationists with information about the scope of recreational
experiences that they can expect to find in this geographic area.
Results illustrate that the greatest proportion of land falls into the
recreation category with the most developed or modified landscapes, and th.e
smallest quantity of land is at the primitive end of the spectrum. This holds true
for current and future conditions. These results are not surprising, given the
large degree of human modification in the CLAMS study area.
Collecting and generating spatial data offer immediate and long-term
benefits. They not only provide an inventory to land managers, but also help
fulfill CLAMS goals by examining the effects of land change over time.
