Theories and Models of Species Abundance

Three theories of explanation for the observed patterns of species abundance in samples from animal and plant communities are reviewed. These are the nichepreemption hypothesis associated with the log-series distribution, the theory based on the central-limit theorem to explain the truncated lognormal distribution, and the explanations associated with a recently published model of community dynamics. The relative performance of the log-series, lognormal, and dynamics models in predicting the species abundance in 222 samples from a wide range of communities is examined. The log-series provides the best prediction of only 4% of the samples, because there were either too few rare species or, more usually, the common species were too abundant. Only 28% of samples, those with a mode in the species-abundance distribution, may be described by a truncated lognormal, but even in these cases the lognormal parameters cannot reasonably be used to predict the abundance of species in the whole community. The species abundance in 94% of the samples may be explained by one of the predictions of the dynamics model. For most samples, the model predicts a concave dominance-diversity curve with a large number of rare species, but indicates that there may be a smaller proportion of rare species in communities where population growth is less restricted by competition or mortality. It is concluded that the theories associated with the log-series and lognormal models, which have been criticized previously for a lack of ecological realism, provide unsatisfactory explanations for species abundance because they are conceptually unsound and the models on which they are based rarely provide a satisfactory description of samples. This conclusion undermines the use of the diversity index associated with these models. The dynamics model predicts the species-abundance pattern of most samples with greater accuracy and provides an explanation of species abundance based on recognized and testable ecological principles.