FORECAST Model for Forest Growth & Ecosystem Dynamics
Purpose: Project the development of stand-level forest attributes (height, diameter, volume, carbon, snags, coarse woody debris, etc.) for particular ecosystems and climate conditions over time.
FORECAST is an ecosystem-based, stand-level, forest growth simulator. Ecosystem dynamics are projected using representations of key ecological processes, which makes it possible to build and test theories about the processes that drive ecosystems (i.e. climatic conditions). The model was designed to accommodate a wide variety of harvesting and silvicultural systems in order to compare and contrast their effect upon forest productivity, stand dynamics, and various biophysical indicators of non-timber values. Outputs include a wide range of stand attributes (heights, diameters, volumes, snags, coarse woody debris, etc.).
The model uses a hybrid approach whereby local growth and yield data are combined with other data to derive estimates of the rates of key ecosystem processes related to the productivity and resource requirements of selected species. FORECAST uses relatively simple measures of decomposition, nutrient cycling, light competition, and other ecosystem properties to simulate forest growth and ecosystem dynamics under changing management conditions. Growth occurs in annual time steps. Depending upon the species, plant populations within the model can be initiated from seed and/or vegetatively, and stand development can occur with or without competition from non-target tree species and understory populations.
FORECAST has been subject to on-going development and testing for over 3 decades and its application documented in almost 40 refereed publications. The model has been applied in many parts of Canada, Europe (Norway, Spain, and the UK), China, and Cuba. Recently, FORECAST has been equipped to simulate the effect of soil moisture availability, climate and alternative climate regimes on ecosystem productivity. This updated version (FORECAST-climate) also includes the full suite of capabilities of the original FORECAST model.