Stability and complexity in microcosm communities
Jeremy Fox, NERC Centre for Population Biology, Imperial College, Silwood Park, Ascot, Berkshire SL5 7PY, UK. Tel. + 44 (0) 20 75942471. Fax: + 44 (0) 1344 873173. E-mail: email@example.com
- 1Theory predicts that communities comprising many species connected randomly by strong interactions are unlikely to exhibit stable, feasible equilibria (i.e. positive equilibria to which all species will return following perturbation), making the observed complexity of natural communities very surprising. This prediction has never been tested experimentally in speciose communities.
- 2We tested this prediction using long-term data from experimental communities of bacteria, protists and small metazoans in laboratory microcosms. Initial communities varied in species richness ( S ), composition and connectance ( C ; the fraction of possible interspecific interactions that are actually realized).
- 3Many initial communities lost species to extinction (unstable and/or infeasible communities), but population densities and species compositions subsequently stabilized.
- 4We used logistic regression to describe the probability that an initial community would be stable and feasible as a function of complexity [( SC ) 1/2 ]. Probability of a stable, feasible equilibrium declined with complexity, as predicted by theory.
- 5We also found that communities converged in connectance over time, so that at the end of the experiment connectance was independent of species richness. Monte Carlo simulations indicated that this result was highly improbable if extinctions occurred at random with respect to connectedness. Connectance is also independent of species richness in well-resolved natural food webs, a pattern usually ascribed to phylogenetic and/or physiological constraints on diet breadth. However, such constraints cannot explain our results. Trophic interactions causing non-random extinctions may provide a novel explanation for patterns in the connectance and species richness of whole food webs.