Quantitative predictions from competition theory with an incomplete knowledge of model parameters tested against experiments across diverse taxa

Abstract

The capacity of community ecology for making quantitative predictions is often limited by incomplete empirical information which precludes obtaining reasonable estimates of model parameters. This is particularly the case for communities with large species richness S since it is practically impossible to perform the S monoculture experiments (to obtain the species carrying capacities) plus the S×(S−1)/2 pairwise experiments (required to estimate the entire set of interspecific interaction coefficients of the interaction or community matrix). However quantitative predictive tools are vital for understanding the fate of ecological communities.Here we derive an analytical approximation for predicting the relative yield total (or equivalently the mean relative yield) as a function of the mean intensity of the interspecific competition and the species richness. The rationale is that with incomplete information on model parameters it seems more reasonable to attempt to predict “macroscopic” or mean quantities, defined for the whole community of competing species, rather than making detailed “microscopic” predictions, like species abundances.This method, with only a fraction of the model parameters (carrying capacities and competition coefficients), is able to predict accurately empirical measurements covering a wide variety of taxa −algae, plants, protozoa, etc.Our aim with this approach is to contribute in making community ecology a more quantitative and predictive science. We argue that such parsimonious modeling is preferable than more realistic/complex theories involving additional parameters which can be very difficult to measure.