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Abstract

Blue Mountains Monitoring Framework

by S. Stafford and J. Lorenz (OSU)

EXECUTIVE SUMMARY

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 over time.

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
• Landscape/Land-use
• Substrate (Soils, Geology, Geomorphology)
• Vegetation
• 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 of sampling.
• 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 monitoring scheme.
• 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.