Our Research Approach

The SORTIE-ND research programme in northern British Columbia aims to improve our understanding of important processes that control forest dynamics in natural and managed forests. Our approach is to study ecosystem processes that affect fine-scale and short-term interactions among individual trees to provide insight into long-term forest response to natural and managed disturbances. We believe that linking empirical studies to models is the best approach for answering the many questions foresters and ecologists have regarding site, stand and landscape conditions in future forested landscapes.

We think the historical focus of forestry on predictable timber yields is shifting to broader issues such as sustaining the full function and dynamics of forested ecosystems, maintaining biodiversity and ecological resilience, and providing for a variety of ecosystem services of value to humanity. The SORTIE-ND research programme in BC embraces the notion that forest ecosystems, as well as the human communities that depend on them, are complex adaptive systems and that forestry research must develop tools better suited to deal with ecosystem complexity, variability, unpredictability, and adaptability.

For example, forest management in BC has been based on a regulatory framework that imposes consistent standards of practice, often via a limited set of prescriptions, but with an expectation of predictable, reliable future results (e.g., timber yield). This management tactic is based on an implied understanding of forest succession as regular and unchanging. This view can no longer be supported in light of current understanding of ecological dynamics, let alone projections of a changing climate. Studying and viewing forests as complex systems and managing for ecological resilience and complexity needs to be explicitly incorporated into forestry research. More information about complex systems and complexity can be found in Key Concepts.

Forest ecosystems are fundamentally a network of interacting elements. In SORTIE-ND we try to understand and represent the important elements (termed behaviours in the model) of the forest ecosystems that affect tree recruitment, growth and mortality. The interactions among individual trees and their spatially heterogeneous environment are inherently local in nature acting at a neighbourhood scale over restricted distances. Unfortunately, traditional growth and yield models that are deterministic and non-spatial are not very useful in this context. Models that use trees as individual modeling agents and are spatially explicit represent a significant advancement.

Forests exhibit elements of quasi-chaotic and uncertain behaviours as a result of interactions among many non-linear relationships. Development of forests include many components of randomness (e.g., seed dispersal, neighbourhood composition, windstorms), but forests do not develop randomly. Complex behaviour is best represented using a "bottom-up" approach to modeling. Each hierarchical element is modeled as a discrete agent or object state, where each entity has functions that are characterized by relationships described by rules (or equations) and constant values or variables.

In SORTIE-ND, the forest is represented by a large collection of interacting trees that are followed both in time (in steps of at least one year) and space. Those trees are currently divided among seedlings, saplings, adult trees and snags. Population-level dynamics are simulated by summing the collective activities of numerous individuals. Each tree is a discrete object that is described with various attributes (size, growth rate, age, crown morphology, and so on). Each tree's (individual) behavior is modeled with rules that describe the interactions with other individuals (e.g., effect of species and distance of neighbours on growth of individual trees) or its environment (e.g., growth of seedlings in relation to available light levels). We often use likelihood methods and model selection techniques to select the most supported model based on our data.

In SORTIE-ND, many of the interactions have non-linear relationships and/or have random events associated with them. The non-linearity of many interactions, the stochastic behavior of some objects and processes, and the large number of objects, rules and stochastic events makes SORTIE-ND a good example of a modeling approach aimed at being able to represent complex behaviour in forests.