Validation of Large Scale Process-Oriented Models for Managing Natural Resource Populations: A Case Study

The validation of models used in population management can be complicated by the number of component parts and by the large temporal and spatial scales often necessary. This is especially true for models developed for the analysis of management policy in forest-pest situations. In the case study considered here, a large-scale spruce budwormforest simulation model (Jones, 1979) was tested by comparing its output with data collected annually by the Maine Forest Service survey at 1000 sites from 1975 to 1980. In practice, model validation usually involves a comparison of observations, independent of those used to construct the model, with overall model output. This ‘typical’ validation was performed. In addition, separate tests were conducted on the model’s major components. These components represent the forest protection policy, the budworm-forest dynamics, and pest control efficacy. The model’s output was not always consistent with the Maine survey data. In some situations, compensating inaccuracies in different model components allowed the overall model output to reasonably represent the overall behavior of the system. There were also problems in scaling the findings of studies of nonlinear population dynamics from small experimental plots to the much larger spatial scales used in the models. The results of this validation imply that some modification of the optimal management strategies suggested by the models is appropriate. This paper concerns the validation of large-scale, process-oriented models in general. The spruce budworm-forest model is discussed as an illustrative case study.