Forest mosaics

Authors: Alex Tee Neng Heng, David G. Green

In these models, a landscape is simulated by a cellular automaton in which each cell represents an area of land. The state of the cell represents the kind of plants (“veg”) growing in that area.

How to use the simulation

You can set up many different model scenarios by selecting options and setting parameters. The main options and parameters are:

  • Name: Name of vege in the model
  • age: Expected lifespan of each vege
  • Adult: Age at which each vege matures
  • Fire prob: Probability of fire ignites in the vege
  • Fire killed: Is the vege killed by fire?
  • Fec: Fecundity of each vege
  • Disp: Seed dispersal distances for each vege
  • Etax: Environmental response of a single taxon
  • ega: Lower limit of vege range
  • egb: Lower limit of optimal range
  • egc: Upper limit of optimal range
  • egd: Upper limit of vege range


Scenarios provide preset combinations of options and parameters to
create models of particular kinds of ecological situations.

  • Salt Marsh: mangroves with different levels of salt tolerance compete on a salinity gradient from fresh water to sea water. Mangroves trade off growth rate for salinity tolerance.
  • Weed invasion: Invaders are suppressed from spreading by existing plant cover. They cannot spread until the density of empty sites reaches a critical level where they become connected, leading to an explosion in the invading population.
  • Diversity loss: Competition can drive species to local extinction. The number of species that persist depends partly on dispersal range.
  • Competing species – Plant species compete for space. With global (long range) dispersal, the species mix. With short range dispersal, they separate into clumps.
  • Gradients (+ dispersal): these scenarios place an environmental gradient across the space (from left to right). The response of each species to the gradient is given by the ETAX parameters.

Some experiments and scenarios

  • Try each scenario and watch what happens to the distribution of species.
  • With each scenario, try changing values of parameters to see the effect. In particular, look at the effect of local versus global seeding and the effect of disturbances.


  • Green, D.G., Klomp, N.I., Rimmington, G.R. & Sadedin, S. (2005). Complexity in Landscape Ecology. Kluwer, Amsterdam.
  • Green, D.G. and Sadedin, S. (2005). Interactions matter – Complexity in landscapes and ecosystems. Ecological Complexity In press.
  • Green, D.G. (1994). Connectivity and complexity in ecological systems. Pacific Conservation Biology 1(3), 194-200.

Demo screenshot