Aggregation of individual trees and patches in forest succession models: capturing variability with height structured, random, spatial distributions

Theor Popul Biol. 1998 Dec;54(3):213-26. doi: 10.1006/tpbi.1998.1378.

Abstract

Individual based, stochastic forest patch models have the potential to realistically describe forest dynamics. However, they are mathematically intransparent and need long computing times. We simplified such a forest patch model by aggregating the individual trees on many patches to height-structured tree populations with theoretical random dispersions over the whole simulated forest area. The resulting distribution-based model produced results similar to those of the patch model under a wide range of conditions. We concluded that the height- structured tree dispersion is an adequate population descriptor to capture the stochastic variability in a forest and that the new approach is generally applicable to any patch model. The simplified model required only 4.1% of the computing time needed by the patch model. Hence, this new model type is well-suited for applications where a large number of dynamic forest simulations is required.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bias
  • Climate
  • Ecosystem
  • Models, Biological*
  • Monte Carlo Method*
  • Numerical Analysis, Computer-Assisted*
  • Population Density
  • Population Dynamics*
  • Reproducibility of Results
  • Stochastic Processes*
  • Time Factors
  • Trees / anatomy & histology
  • Trees / growth & development*