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> Abstract: Blue Mountains Monitoring
Blue Mountains Monitoring Framework
by S. Stafford and J. Lorenz (OSU)
The Blue Mountains Natural Resources Institute (BMNRI) is interested
in investigating the feasibility of implementing a Geographic Information
System (GIS) to monitor the health of forests and rangeland in the
Blue Mountains of southeast Washington and northeast Oregon. There
has been great interest in establishing programs to monitor forest
health at all levels - from the federal regulatory agencies to private
land owners - and at all scales - from small plots to large watersheds
and regional landscapes. Monitoring efforts contribute to new paradigms
in ecosystem management as well as fulfilling mandated responsibilities.
We chose to take an ecosystem approach to defining "Forest
Health." The definition we have used in this report is a stable,
ecologically sound ecosystem that supports a diversity of resources
and contributes to a diversity of products satisfying a diverse
human population. We believe that a world view of "forest health"
should be taken from an ecosystem perspective. The ecosystem perspective
encompasses linkages between the biotic, physical, and social environments
The information summarized and synthesized in this report was obtained
from two information gathering meetings in Pendleton, Oregon in
October and November, 1992 8 to identify the critical ecological
and sociological questions that address the key components to monitor
forest health in the Upper Grande Ronde Watershed. In addition,
the authors attended a meeting of the Upper Grande Ronde Model Watershed
Project Technical Working Group and conducted telephone interviews
with several GIS specialists within the region to compile the information
on GIS data layers. The four Blue Mountain National forests monitoring
plans were reviewed in detail - the Umatilla, Wallowa-Whitman, Ochoco,
and Malheur - as well as other monitoring documents.
First, we outlined a set of goals about various intrinsically important
resource elements. Then we described the types of data that would
be required to address these goals by listing measurable parameters.
This was followed by an investigation of existing databases - focussing
primarily in Oregon because the Upper Grande Ronde River basin was
selected as a case study for this report.
This report is about GIS and monitoring. Clearly, GIS and monitoring
are not synonymous activities. GIS, monitoring, and research frameworks
obviously will require a complex organizational structure. The success
of monitoring and research should be demonstrable in enhancing our
abilities to make management decisions across ecosystems and landscapes.
We identified nine resource elements:
- Air Quality
- Climatic Factors
- Human Benefits
- Substrate (Soils, Geology, Geomorphology)
- Water Quality
- Water Quantity
- Wildlife and Fish
Examples of 'healthy" conditions for each resource element
were identified and a corresponding list of parameters that could
be measured to determine baselines and trends was identified.
The major GIS players we identified were:
- Boise Cascade
- Bonneville Power Authority&127;
- Confederated Tribes of the Umatilla
- EMAP/Forest Health Monitoring (FHM)
- GAP Biodiversity Program
- National Forests
- Oregon Department of Fish and Wildlife
- Oregon Water Resources Department
- Pacific Meridian
- State GIS Center
At this time, a strict comparison of existing GIS coverages and
attributes with measurable parameters proposed in this study is
impossible because our proposed measurable parameters are not defined
well enough to conduct such an exercise. Coverages and attributes
of some programs are still at the level of proposal and need further
definition before adoption.
Reviewing available databases against the proposed measurable parameters
offered the following insights:
- A number of agencies have experience in GIS, monitoring and
research. These agencies have experience and data that could be
incorporated into a BMNR1 GIS/Monitoring program.
- Currently, gaps in data collection can be classified in terms
of geographic coverage, scale, resource element, and frequency
- EMAP-Forests/FHM offers an excellent model for sampling.
- Entry points into GIS could be made with partnerships with
BPA and the GAP Biodiversity Program. Products to demonstrate
the potential of using GIS to make landscape/ecosystem-level management
decisions could be created now, prior to initiating a complex
- The State GIS Center in Salem is establishing distributive
network capabilities and GIS archives that could be used by BMNRI.
- Incorporating human benefits into a monitoring framework will
be challenging because what to monitor and how to interpret these
data is not as clear as in the physical and life sciences.
- Satellite imagery provides a synthesis of many parameters integrated
over broad landscapes. This could be very useful for trend detection.
- Shared data across ownership boundaries will require a new
level of cooperation between public and private landowners.
- There are several critical issues regarding data accessibility
and proprietary rights that may limit capabilities for data sharing.
Findings of this study suggest more planning is required prior
to implementing a GIS/monitoring program for the Blue Mountain region.
The issues that need addressing can be categorized into three groups:
Technology, Science/Data, and Policy. Responsibilities of the Technology
Group would be to design a system of hardware, software, and networks.
The Science/Data Group should focus on links among research, management,
and restoration; data priorities; data collection and standards;
and sampling strategies. The Policy Group should address issues
of administrative structure; interagency cooperation; privacy; and
data accessibility. We estimate pre-implementation planning to take
between 12 and 18 months and will require a coordinator.
Beginning the GIS/monitoring in a trial region of the Blue Mountains
may be a valuable exercise for testing all aspects of implementation.
The area selected for field testing should include several public
and private ownerships to represent the myriad of challenges that
will be faced across the entire region.
Information is lacking on values, attitudes and expectations. This
is the greatest data gap in this project. Applying data on human
benefits to natural resource management is poorly developed compared
to the application of data from the physical and life sciences.
This suggests that incorporating some of the proposed measurable
parameters into a monitoring system will lag behind others. As the
monitoring plan develops, managers should realize that human dimensions
of resource management will be added.
The question of how data will be used to make landscape-level management
decisions is a significant issue. Using new technologies and paradigms
in resource management may require new administrative approaches.
We conclude that using GIS to monitor forest and rangeland health
in the Blue Mountains is indeed feasible. Existing GIS programs
within other agencies offer the potential for mutually beneficial
partnerships. BMNRI cooperators, other state, and federal agencies
all appear willing to cooperate with this effort. Instituting a
program that can lead to ecosystem-level management across ownership
boundaries offers exciting new challenges for everyone.