Response Surface Experimental Designs for Investigating Interspecific Competition

Abstract

Competition is an important interaction in ecology, and many experiments have been done to examine the effects of intraspecific and interspecific competition. Unfortunately, most of these experiments have been done using either substitution or additive experimental designs. Substitution designs, and to a lesser extent additive designs, severely limit the useful inferences that ecologists can draw from the resulting data. Response surface experimental designs, which vary the densities of two competing species independently, offer the advantage of being able to compare the fits of alternative competition models and to estimate model parameters. This kind of experimental design has been relatively little used in ecology to date. I consider the use of response surface designs from two perspectives. The first is the optimal allocation of experimental effort among density treatments, with the goal of distinguishing among alternative models. Second, I compare the ability of six response surface designs to estimate known competition coefficients correctly, using simulated data. Low densities and densities near equilibrium in one generation tend to return similar densities the following generation and thus provide little or no information for comparing alternative population models. Experimental designs that span a wide range of densities, including high densities above carrying capacities, provide more accurate parameter estimates in general, but low densities are helpful for estimating population growth rates. Designs that are not fully factorial are one compromise solution that can yield accurate parameter estimates for models and yet require less experimental effort than full factorial surfaces. In general, response surfaces are a powerful class of experimental design and offer potentially stronger connections between empirical and theoretical approaches than traditional experimental designs.

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“…The probability of species coexistence is estimated using a competition model under a range of simplified environments and is encapsulated by the competition coefficient parameter (Damgaard, 1998;Inouye, 2001). Estimating competition coefficients may improve predictions of persistence of crop alleles within weedy populations across generations and the success of hybrids within weedy populations over a growing season.…”

“…1; Damgaard, 1998;Inouye, 2001). We measured the lifetime fecundity of F 3 plants in a common garden at UMBS.…”

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