This report has provided a framework for assessing selected species of fish and wildlife with regard to various management actions, conducting an integrated fish-wildlife and aquatic-terrestrial assessment of ecological assemblages, and determining effects on ecological functions of fish and wildlife communities.  We have based our work on accepted and published ecological theory, and the models and databases we have used have undergone extensive review.  However, much remains to be empirically validated.  For example, many of the assumptions concerning the functional assessments – such as the value of functional redundancy (number of species with the same general ecological roles) in providing greater ecosystem stability and resilience to undue perturbations – remain to be tested in many ecological communities throughout the Columbia Basin.

As well, this report has made good progress toward explicitly addressing the recommendations in the report “Return to the River 2000: Restoration of salmonid fishes in the Columbia River ecosystem” (Independent Scientific Group 2000).  Their recommendations included: address the basin and landscape, address the coupling of species to their associated ecosystem, address multiple species of native fish and wildlife, address the entire life cycle, address ecological functions of salmon and other species, build on a conceptual foundation of ecologically-based scientific principles, and work from a set of linked visions, goals, and objectives.  We have worked toward meeting these recommendations.

The major lessons and concepts to be taken from our report include:

1.  Major historic changes. – The USA portion of the Columbia Basin has undergone major change, since early historic times, that has resulted in the declining distribution and abundance of some native fish and wildlife species and habitats.  Our results are consistent with other findings (Covington et al. 1994, Covington and Moore 1994, DellaSala et al. 1995, Hessburg 1993, Hessburg et al. 2000, Jensen and Bourgeron 1994, Quigley et al. 1996). 

2.  Extending the paradigm. – Our work has extended these previous analyses by providing integrated fish-wildlife assessments and functional analyses.  More specifically, we have: (1) expanded the wildlife habitat map and the SHP wildlife database to the entire USA portion of the Columbia Basin (and our Canadian colleagues are expanding these to include the Canadian portion of the Basin); (2) linked the theory and application of fish and wildlife population models as a basis for a transdisciplinary analysis (sensu Regier 1978); and (3) developed an assessment procedure to link management activities to habitats, KECs, fish and wildlife populations, and integrated ecological functions.

We address several levels of ecological systems: populations, species assemblages, communities, and ecosystems.  The EDT and HCI modeling address populations.  The SHP databases address wildlife species assemblages.  The functional analyses address species and community functions.  All of these combined address ecosystem conditions. 

3.  Predicting management influences and cumulative effects. – The current and potential future influences of management activities and land-use planning on fish and wildlife populations, communities, and ecosystems are difficult to predict precisely.  Such influences are sometimes difficult to separate from complicating factors and background natural variations inherent in such systems.  However, we provide a framework by which such influences can be analyzed in a repeatable and testable fashion by using specific models (e.g., the EDT model, Figure IV.A.4, Figure IV.A.5) and databases (e.g., the SHP database Figure IV.C.17). 

The influence of cumulative effects can be addressed in the Framework process by at least two techniques. The first involves conducting functional analyses to assess effects of multiple management changes on fish and wildlife species’ habitats, and thus on the species and their ecological roles (key ecological functions). In turn, results can be interpreted as influencing positively, neutrally, or negatively the functional aspects of the ecosystem.  The second involves the step-up process where the combination of management actions for a small focused area (e.g., 6-HUC) can be combined with the management actions from other small areas to assess the cumulative effects of management actions over larger areas. For some species and habitats (e.g., beaver and headwater aquatic systems), the step-up assessment is necessary.

4.  Testable hypotheses. – We suggest that local (e.g., watershed) and global (e.g., Columbia Basin) influences predicted from these models and databases can constitute a set of testable management hypotheses that can be generated in a repeatable, scientific manner.  Through monitoring and adaptive management studies, the models and databases, and selected predictions of ecological ramifications of management effects, can be studied empirically. Results can be used to re-evaluate goals and questions, to formulate new hypotheses to be tested with modified management, as needed and to refine the models and data. 

 5.  Toward a step-down process. – The Assessment Framework we present in this report can be used in a step-down process to evaluate potential management influences in smaller areas, namely subbasins and eventually watersheds and 6-HUCs.  In this manner, subbasin and watershed managers can evaluate effects of alternative management activities on fish and wildlife species and communities (including ecological functions).  This would help determine the most effective or most desirable sets of management activities to reach clearly stated resource management objectives for a given subbasin.  Also, the Framework allows for a step-up process where aggregations of subbasins and stochastic data developed at the lower levels can be evaluated at the higher province and basin levels to assure that management actions are compatible and, to prioritize which subbasin might need the most immediate management attention. 

6.  Managing under uncertain outcomes. – There will always be uncertainty in predicting the future.  We advise that users of this document, and of any subsequent refinement of our analysis methods and findings, understand the sets of assumptions we discussed previously.  Uncertainty in outcomes can be stated as spreads of potential outcomes, such as expressed by ranges of values, confidence intervals, etc.  Uncertainty in outcomes does not mean lack of scientific understanding of the systems, and thus that “anything goes” in terms of management.  Rather, such uncertainty may mean that selected response variables of the system – selected species, ecological functions, or measures of community composition or performance – might be monitored over time to better determine whether the populations, communities, and ecosystems are changing as predicated by objectives, goals, and visions. Then, management activities, as well as models and databases, can be re-evaluated and amended as needed, in a true adaptive management framework.

 

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