Mixedwood forests consisting of a broad range of species combinations, successional stages, and spatial patterns cover a large area throughout BC. From a resource perspective they are highly valuable both as sources of fibre and as areas rich in biodiversity. Research into the production ecology of mixedwood ecosystems has illustrated that mixtures of conifers and broadleaf species can be more productive and relatively more healthy (lower risk of disease and pest attack) than pure stands. Explanations for such benefits have focused on the differential utilization of resources (light, nutrients and water) and the positive impacts of broadleaf species on nutrient cycling rates and mycorrhizal networks. The exceptionally dynamic nature of mixedwood forests presents a number of management challenges, not the least of which is how best to project the growth and development of different types of mixedwoods and associated management systems. Currently in BC there is a fundamental disconnect between the majority of models being used to simulate growth and yield in mixedwood stands and the underlying biological processes governing forest growth dynamics in such stands. The research community devotes much effort and resources to measuring and trying to understand such processes with the often-stated goal of improving our capabilities to model the growth of complex stands. Yet, the majority of models used in BC to predict the growth dynamics and associated yield of such stands contain little or no representation of these fundamental ecological processes and thus cannot effectively incorporate such knowledge. Rather, to meet the broader objectives of sustainable forest management, we must expand our modelling capabilities to develop a better understanding of the biological processes regulating forest growth dynamics so that we can make reasonable long-term projections of forest growth under changing conditions. The ecosystem-based approach to stand growth and development modelling employed by the FORECAST model includes an explicit representation of the key ecosystem processes regulating growth dynamics and competition for limited resources. Process rates are derived through an internal calibration procedure which relies on past observations of forest growth to constrain model behaviour (see Section 3.1 for a complete description). The primary objective of this project was to evaluate the capability of the ecosystem management model FORECAST to project patterns of stand growth and dynamics in mixedwood forests by comparing model output against data from long-term field trials in different mixedwood stand types in both the SBS and ICH BEC zones.
Seely, Brad A., Kimmins, J.P. (Hamish). 2006. Evaluation of an ecosystem-based approach to mixedwood modelling. Forest Investment Account (FIA) - Forest Science Program. Forest Investment Account Report