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Keywords:

  • competition indices;
  • competition intensity;
  • crowding;
  • interaction strength;
  • plant competition;
  • productivity gradients;
  • relative crowding

Summary

  • 1
    Controversy surrounds the measurement of competition intensity. Moreover, when biomass varies systematically along productivity and other environmental gradients, common indices of competitive outcome mask important ecological interactions.
  • 2
    This study presents two indices derived from how neighbours interact with target plants. The first, relative crowding, increases directly with the abundance of neighbours present and decreases inversely with the potential size and vigour of the target plant itself. The second, interaction strength, is the integral of suppression of the target by neighbours over the range of neighbour abundance. Relative crowding and interaction strength are derived independently, but when multiplied produce the commonly used relative competitive index, showing the biological underpinnings of the relative competition index in terms of crowding and strength of interaction. Since the new indices of relative crowding and interaction strength explicitly account for the amount of neighbour biomass, they serve as a valid method to track the effects of changing habitat conditions on the components of competition.
  • 3
    The new indices are applied to three published data sets. In each case, relative crowding increased with standing crop. In one case competition was reported as unchanged along a productivity gradient, whereas the new indices show that relative crowding and interaction strength both had significant patterns, but their effects were counteracting. These results do not fit current theories of competition. Further empirical studies are needed to see if competition theory needs revision.
  • 4
    Separating the mechanisms of competition into relative crowding and strength of interaction reveals previously hidden patterns that help bring to light underlying processes of competition along productivity gradients.