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Forest succession is an ecological phenomenon that can span centuries. Although the concept of succession was originally formulated as a deterministic sequence of different plant communities by F. Clements more than a century ago, nowadays it is recognized that stochastic events and disturbances play a pivotal role in forest succession. In spite of that, forest maps and management plans around the world are developed and focused on a unique “climax” community, likely due to the difficulty of quantifying alternative succession pathways. In this research, we explored the possibility of developing a Markov Chain model to study multiple pathway succession scenarios in mixed forests of western red cedar, hemlock and Pacific silver fir on northern Vancouver Island (western Canada). We created a transition matrix using the probabilities of change between alternative ecological stages as well as red cedar regeneration. Each ecological state was defined by the dominant tree species and ages. Our results indicate that, compared to the traditional Clementsian, deterministic one-pathway succession model, which is unable to replicate current stand distribution of these forests in the region, a three-pathway stochastic succession model, calibrated by a panel of experts, can mimic the observed landscape distribution among different stand types before commercial logging started in the region. We conclude that, while knowing the difficulty of parameterizing this type of models, their use is needed to recognize that for a given site, there may be multiple “climax” communities and hence forest management should account for them.

Highlighting Complex Long-Term Succession Pathways in Mixed Forests of the Pacific Northwest: A Markov Chain Modelling Approach