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Keywords:

  • experimental design;
  • community structure;
  • competitive hierarchy;
  • non-linear model

Summary

1 Experiments on competition between plant species are frequently designed without considering the analysis stage of the study. We argue that this omission may lead to over-complication of the issue of designing experiments.

2 An overwhelming number of studies have shown that the effects on performance of competition in plant mixtures may be described by simple (hyperbolic) regression models. The most natural view of the problem of measuring plant competition is therefore as a problem in regression.

3 Only with experiments designed explicitly to apply regression analyses can phenomena such as frequency dependence and the size dependence of measures of competition be identified. In contrast to previous assertions, this means that designs that are based around, or allow, regression analysis are the most robust as such effects may be tested for using appropriate statistics.

4 Experiments are probably most easily designed to measure competition as a function of the density of interacting species, rather than biomass. This is because the per unit biomass effect of competition on performance is a function of density. Competition measures based on biomass will hence be dependent on the density at which the experiment is performed. Furthermore, the most effective way to manipulate biomass is through changing species’ densities.

5 In terms of economy of design, we would recommend simple additive series. Whilst this does not allow the role of frequency dependence to be analysed, this phenomenon appears to be rare in any case.