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Keywords:

  • Cellular automata;
  • Environmental heterogeneity;
  • Simulation;
  • Spatial scale;
  • Species diversity;
  • Species richness

Abstract

Question

How are heterogeneity–diversity relationships (HDRs) influenced by spatial structure in environmental variables, sampling grain and the extent of niche differentiation?

Methods

We developed a spatially explicit simulation model incorporating variable dispersal distances and competition strength on fractal landscapes. By varying the grain used to sample these models, we examined scaling patterns in HDR metrics at fine scales (sampling grain from 100 to 10 000 individuals, sampling extent ca. 260 000 individuals).

Results

Environmental geometry exerts an important influence on the ecological processes responsible for HDRs. Unique geometric characteristics of individual landscapes can greatly influence emergent community properties; field studies frequently use inadequate sample sizes to account for this phenomenon. Two opposing processes influence spatial scaling of HDRs: variance partitioning, which favours smaller-grained samples, and mass effects, which favour larger-grained samples. In assessing HDRs, diversity is more sensitive than species richness, and should be the preferred measure in field studies. The environmental geometry and age of a community interact: compared to high fractal dimension landscapes, low fractal dimension landscapes are slower to develop HDRs, but in the long term their HDRs will be higher.

Conclusions

Our study demonstrates that, despite the superficial simplicity of the concept, HDRs vary in complex and non-intuitive ways, and warrant further theoretical and empirical study. More generally, environmental geometry is likely to exert a strong influence on many emergent community processes, but we do not yet have a firm understanding of this relationship.