Resilience and Temporal Variability

Comparative research has provided evidence that resilience, when viewed from a species point of view, is dependent on body size. Usually large-bodied species show low rates of increase and thus lower resilience. In contrast, small-bodied species usually have more frequent reproductive output, and thus a faster response to perturbation, that is, higher resilience. These species can recover more quickly from sharp declines in density; as a result, it would make highly resilient species less variable. However, resilience can also lead to higher variability. This can be explained mainly by two processes: one has to do with the ability of some populations with high resilience to over-respond to mortality caused by a disturbance. First the population will overshoot the equilibrium density, as mortality lags behind the population growth rate. Then, the overshoot is followed by an undershoot, as the population declines below its equilibrium, as the birth rate now lags behind the mortality rate. The result can lead to population cycling or even more complex dynamics. The second process occurs when the equilibrium density itself is variable over time. If a species has a high rate of returning to equilibrium following a perturbation, it will track the fluctuations of the prevailing conditions, and subsequently, its density will be more variable as compared to a less resilient species that exists under more stable environmental conditions.

While the above arguments apply to single trophic levels, the resilience properties of a system with more than one trophic level can be quite different. For example, in a predator-prey system there is an increase in return times following a perturbation. In the following experiment, data are presented that show that populations with higher resilience can be more variable. Luckinbill and Fenton experimentally tested the equilibrium density of species of protozoa by manipulating trophic levels of bacteria they fed upon. The two species of ciliates Paramecium primaurelia and Colpidium campylum were cultured in Cerophyl medium inoculated with the bacterium Enterobacter aerogenes. The experiment included six replicate populations of each species for a period of 2 weeks until reaching their saturation limit in order to estimate how quickly these populations returned to equilibrium. Two of the replicates were untreated, serving as controls. Experimental populations then were perturbed from their equilibrium with two of these having reductions to almost zero and two following an experimental, twofold increase from equilibrium densities. Subsequently, the experimental populations were assessed for a period of a month. In Figure 2 density changes in experimental populations are depicted through time. Results show the convergence of experimental populations after perturbation to levels similar to the controls. But the two species did not respond at the same rate, with the smaller, faster-growing species C. campylum showing a more resilient dynamic. The experiment also tried to address the effects of resilience on variability by manipulating food concentrations in experimental populations. The authors' hypothesis was that slower-regulating species vary more widely because their response lags behind the imposed changes, while faster-regulating species follow the changing equilibrium more closely. The experimental results revealed a quite idiosyncratic pattern of response to varying food conditions, with the more resilient species becoming unstable tracking a fluctuating equilibrium, and less resilient species maintaining more stable population densities. The differential effects of the environmental manipulations were determined more by the frequency of the fluctuations than by their magnitude. Their results support the claim that more resilient populations can be more variable.

The above findings come from laboratory experiments and are subject to questioning, because of the control of exogenous forces. Field studies of some migratory bird populations in two habitats (farmland and woodland) in Britain showed that more resilient species show significantly less variability in the population density, a result consistent with the increase in variability in the population density with increasing body size. A possible dynamic

Figure 2 Populations of two ciliate species as they return to an equilibrium set by their food supply. After they had been growing with a constant level of their bacterial food supply, populations were either set to very low (triangles) or to very high densities (circles) or were left unchanged (squares). C. campylum (a) returns to equilibrium much more quickly than does P. primaurelia (b). Numbers, N, are scaled to their long-term average, K, so all lines eventually approach N/K = 1. Redrawn from Luckinbill LS and Fenton M (1978) Regulation and environmental variability in experimental populations of protozoa. Ecology 59: 1271-1276.

Figure 2 Populations of two ciliate species as they return to an equilibrium set by their food supply. After they had been growing with a constant level of their bacterial food supply, populations were either set to very low (triangles) or to very high densities (circles) or were left unchanged (squares). C. campylum (a) returns to equilibrium much more quickly than does P. primaurelia (b). Numbers, N, are scaled to their long-term average, K, so all lines eventually approach N/K = 1. Redrawn from Luckinbill LS and Fenton M (1978) Regulation and environmental variability in experimental populations of protozoa. Ecology 59: 1271-1276.

behavior of the system that explains how resilience can cause high variability is that of cycling. Usually, populations with high resilience are the ones that cycle, but the supporting data may lack the proper time duration to capture all system dynamics. Overall resilience is greater in small-bodied species, but the actual role of resilience on population variability might be hard to understand.

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