Mutual interference is common and mostly intermediate in magnitude

Abstract

Background: Interference competition occurs when access to resources is negatively affected by the presence of other individuals. Within a species or population, this is known as mutual interference, and it is often modelled with a scaling exponent, m, on the number of predators. Originally, mutual interference was thought to vary along a continuum from prey dependence (no interference; m = 0) to ratio dependence (m = -1), but a debate in the 1990's and early 2000's focused on whether prey or ratio dependence was the better simplification. Some have argued more recently that mutual interference is likely to be mostly intermediate (that is, between prey and ratio dependence), but this possibility has not been evaluated empirically.

Results: We gathered estimates of mutual interference from the literature, analyzed additional data, and created the largest compilation of unbiased estimates of mutual interference yet produced. In this data set, both the alternatives of prey dependence and ratio dependence were observed, but only one data set was consistent with prey dependence. There was a tendency toward ratio dependence reflected by a median m of -0.7 and a mean m of -0.8.

Conclusions: Overall, the data support the hypothesis that interference is mostly intermediate in magnitude. The data also indicate that interference competition is common, at least in the systems studied to date. Significant questions remain regarding how different factors influence interference, and whether interference can be viewed as a characteristic of a particular population or whether it generally shifts from low to high levels as populations increase in density.

Figure 1

The distribution of unbiased mutual interference values in the literature. A. The distribution of m estimates gathered from studies in the literature that used the unbiased approaches of Methods 2 and 3 (see "Approaches to estimating mutual interference" for details). This histogram shows that most estimates of mutual interference cover continuously the range from a little above 0 to a little below -1. Two estimates were particularly large, at -2, but were highly precise and thus cannot be dismissed as errors. The special cases of prey dependence, when m = 0, and ratio dependence, when m = -1, are shown, and although both occur, intermediate interference is the most common state. B. A comparison of the distribution for the two unbiased approaches. Both approaches overall produce similar histograms, but the large values of -2 were produced using Method 3.

Figure 2

Examples of the effect of consumer and resource density on resource uptake rate. A. In some studies, a range of consumer and resource densities was available, allowing the use of Method 3 to fit all data to a functional response. In this case, the parasitoid Brachymeria regina parasitized the butterfly Pieris rapae. Data from [18]. B. In other studies, a broader range of resource densities than consumer densities were available. This study shows the success of knots (Calidris canutus) foraging on mussels (Mytilus edulis). Data from [20]. C. In several studies, only variation in consumer density could be related to resource uptake rates, in which case Method 4 was used. These data show the kill rate for wolves (Canis lupus) foraging on moose (Alces alces). Data from [16]. D. In an extension of Method 4, some studies reported variation in metabolic rates associated with population density. In this case, the protist Tetrahymena pyriformis growing in axenic culture. Data from [29].

Figure 3

The distribution of mutual interference values in the literature from potentially biased methods. A. The distribution of m estimates gathered from studies in the literature that used the potentially biased approach of Method 4 (see " Approaches to estimating mutual interference" for details). This histogram shows that most estimates of mutual interference using this approach are similar to the unbiased approaches, but there are several large estimates that were produced with very low confidence (see Additional file 1 - data set). The special cases of prey dependence, when m = 0, and ratio dependence, when m = -1 are shown. B. The distribution of m estimates using the new approach of Method 5. This histogram shows that most estimates of mutual interference using this approach are similar to the unbiased approaches, but fitting of the whole functional response model often failed, and thus most of these are produced using the reduced power-function alternative.