Population cycles and their analysis

Regular cycles in animal abundance were first observed in the long-term records of fUr-trading companies and gamekeepers. Cycles have also been reported from many studies of voles and lemmings and in certain forest Lepidoptera (Myers, 1988). Population ecologists have been fascinated by cycles at least since Elton drew attention to them in 1924. In part, this fascination is attributable to the striking nature of a phenomenon that is crying out for an explanation. But there are also sound scientific reasons for the preoccupation. First, cyclic populations, almost by definition, exist at different times at a wide range of densities. They therefore offer good opportunities (high statistical power) for detecting such density-dependent effects as might exist, and integrating these with density-independent effects in an overall analysis of abundance. Furthermore, regular cycles constitute a pattern with a relatively high ratio of 'signal' to 'noise' (compared, say, to totally erratic fluctuations, which may appear to be mostly noise). Since any analysis of abundance is likely to seek ecological explanations for the signal and attribute noise to stochastic perturbations, it is obviously helpful to know clearly which is signal and which is noise.

Explanations for cycles are usually classified as emphasizing either extrinsic or intrinsic factors. The former, acting from outside the population, may be food, predators or parasites, or some periodic fluctuation in the environment itself. Intrinsic factors are changes in the phenotypes of the organisms themselves (which might in turn reflect changes in genotype): changes in aggressiveness, in the propensity to disperse, in reproductive output, and so on. Below we examine studies on population cycles in three systems, all of which we have touched on previously: the red grouse (Section 14.6.2), the snowshoe hare (and lynx) (Section 14.6.3) and microtine rodents (Section 14.6.4). In each case, it will be important to bear in mind the problems of disentangling cause from effect; that is, of distinguishing factors that change density from those that merely vary with density. Equally, it will be important to try to distinguish the factors that affect density (albeit in a cyclic population) from those that actually impose a pattern of cycles (see also Berryman, 2002; Turchin, 2003).

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