The importance of the variance around the mean effect size of ecological processes

Experiments in ecology are usually designed to provide tests of hypotheses on the influence of the mean intensity of causal processes, whereas the variance around mean effects has been largely overlooked as a causal force in biological assemblages. Repetition of experiments in space and time provides an estimate of this variability at specific scales, but does not explain how changes in variance generate structure in assemblages and the extent to which variance and mean intensity interact. This paper seeks to identify suitable procedures for empirical analyses on the influence of variance and mean intensity of predictor ecological variables on spatial and temporal patterns in natural populations. A survey of the ecological literature indicates that temporal variability in studies of disturbance and in analyses of consumer-resource interactions is generally expressed in terms of frequency of events. This is inappropriate, as frequency confounds the variance with the mean effect size of a process. A possible solution to the problem involves experimental designs in which levels of intensity and those of variability are chosen independently over explicit spatial or temporal scales and treated as fixed, orthogonal factors. Examples are offered for various scenarios of consumer-resource interactions along with indications for statistical tests of hypotheses. Such novel approaches have important ramifications for understanding variability in a wide range of ecological contexts and for predicting the response of assemblages to increased environmental fluctuations, including those expected under modified climate conditions.