long time period. This ability to provide a variety of outputs and to examine the important aspect of 

 stock productivity is a major advantage of this method. 



By providing a means to probe the relationships between variables and to examine the effect of 

 hypotheses on stock abundance and productivity, the life cycle method could contribute toward an 

 improved understanding of the system and the refinement of the program. The life cycle approach 

 should make it possible to isolate, within the confines of the model, the effects of the program and 

 allows them to be examined independent of real-world variation in non-program effects. 



However, the method does have drawbacks. First, it lacks the intuitive appeal of the 

 observational methods. The product of the life-cycle approach is knowledge about the system rather 

 than simply the number of fish. While of obvious importance, knowledge can only be converted to fish 

 production by an effective management structure that can deal with the information. The nature of the 

 management structure is outside the purview of MEG and this discussion. 



A second drawback to the life-cycle approach is that it lacks real-time application. This approach 

 would not yield annual predictions of effects, nor would it attempt to explain year-to-year variation in 

 returns. Instead, it would deal with the reasons for long-term trends in returns, efficacy of types of 

 measures, and the state of our knowledge. Compliance with the Council's policies (Section 204) could 

 not be easily assessed by the use of a model by itself. For instance, the Council's goal that harvest 

 rates will be controlled to support rebuilding, will require a year-to-year monitoring of harvest rates. 

 This would be more aptly addressed by compiling information collected from existing monitoring 

 programs such as that being conducted under the Pacific Salmon Treaty process or various state and 

 tribal management programs. 



3. MEG Recommendation 



MEG examined the above methods with the goal of designing a program that would permit the 

 effect of program measures to be isolated from other effects, and would maximize the opportunity to 

 learn from grogram implementation. MEG reached two conclusions: 



1 . No single measure of the program progress was found. Different indices address different 

 aspects of the problem of monitoring and evaluating the fish and wildlife program. 



2. No method was found that would directly (e.g., experimentally) identify the effects of the program 

 as distinct from non-program effects. It was MEG's conclusion that program effects would have 

 to be isolated by analytical methods such as the life-cycle approach described above. 



None of the methods examined would completely address the Council policy of assessing 

 genetic risks in production planning, although many genetic aspects could be incorporated into a life 

 cycle model. MEG suggests addressing genetic risks in part as a topic separate from the more 

 quantitative measures discussed so far. The recommendation from MEG is that the Council utilize a 

 four component measure of progress that consists of: 



a. A measure of annual juvenile population. 



b. An estimate of annual adult equivalent production. 



c. A life cycle analysis of stock productivity. 



d. A program to monitor the genetic impacts of management actions. 



Juvenile population would be indexed annually to provide an initial indication of the effect of the 

 program on the salmon and steelhead production. Juvenile population would first be indexed for 

 subbasins selected according to an overall experimental design as discussed below. A second stage 

 would be to estimate the size of the annual outmigration, probably at Bonneville Dam, and to estimate 



