Forest Models

Abstract

There are different types of models that simulate the dynamics of forest ecosystems. The first forest models that were developed using relatively complex relationships consisted of growth and yield models. In this category, models were developed to predict the growth of forest ecosystems by considering forest stands as a single entity (whole-stand models) or by simulating the growth of individual trees to predict stand attributes (space-independent or -dependent individual-tree models). Continuous research efforts in the modeling of forest ecosystems subsequently led to the development of process-based and gap models. Process-based models simulate the ecophysiological processes that govern the dynamics of forest ecosystems to predict tree and stand productivity. They include mathematical representations of the physiological processes involved, such as photosynthesis, respiration, or nutrient uptake. Gap models, also known as succession models, simulate individual-tree growth and death and seedling establishment. They were designed to model the dynamics of species replacement through several generations under natural conditions or following disturbances. For instance, they are well adapted to simulate the succession that takes place when there are canopy openings following the death of dominant trees. Model evaluation is an essential milestone of model development to increase confidence in the predictions. Several validation methods were developed, but two methods have been commonly used: comparison of model outputs with observed data and evaluation of the biological consistency of the predictions.