Balancing ecological complexity in predictive models: a reassessment of risk models in the mountain pine beetle system.

Published online
26 Mar 2008
Content type
Journal article
Journal title
Journal of Applied Ecology

Nelson, W. A. & Potapov, A. & Lewis, M. A. & Hundsdörfer, A. E. & He FangLiang
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The nature of ecological risk assessment is to predict the probability of an event, such as extinction or invasion, in a location where the event has rarely occurred. This typically requires developing risk models from data on events in different locations. One perplexing challenge in developing these models is to find the optimal balance of model complexity that reflects the tactical details of a system, but is sufficiently strategic to be applicable under a wide range of situations. Here we address the balance of complexity in risk models for the mountain pine beetle system. Mountain pine beetles (Dendroctonus ponderosae Hopkins) are destructive pests of pine forests in western North America. Much effort has gone into collecting empirical evidence and developing mechanistic models of infestation dynamics, which has resulted in a wealth of process-based information. Current risk models, however, are based solely on indices of stand susceptibility that do not incorporate much of this ecological understanding. In practice, current risk models have proven ineffective at predicting the risk or extent of an infestation. We assemble an ecological framework of the beetle-host interaction that allows us to compare across phenomenological and mechanistic models. We demonstrate that current risk models predict only ranked risk among forest stands, as opposed to absolute risk, and thereby provide an explanation for their limited ability to predict risk in practice. By comparing existing models with the ecological framework, we identify the primary factors determining risk, and propose which dynamical processes should be modelled explicitly, and which might be strategically abstracted. Synthesis and applications. Balancing model complexity in predictive risk models is challenging for systems with complex ecology and imperfect information. Here we draw together a wide range of empirical and modelling work in the mountain pine beetle system to develop a strategic framework of the ecological interactions. Through this framework, we demonstrate why current risk models have been ineffective in predicting risk, and suggest a starting point for future risk models that explicitly describe the dynamical processes necessary to predict absolute risk.

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