Explaining density-dependent regulation in earthworm populations using life-history analysis

At present there is little knowledge about how density regulates population growth rate and to what extent this is determined by life-history patterns. We compared density dependent population consequences in the Nicholsonian sense based oil experimental observations and life-history modeling for the earthworms Lumbricus terrestris and Eisenia fetida. Both species differ in their life-histories, L. terrestris being a relatively long-lived species with slow reproduction and occurring at low densities compared to E. Jetida which has a more opportunistic strategy with a high reproductive output. E.fetida is able to colonise new habitats rapidly and may occur at relatively high population densities. Density dependency of population growth rate was estimated by incorporating density dependent effects on reproduction and growth using a modified Euler equation. The results point out that E. fetida was not as strongly impacted by density as compared to L. terrestris. Population growth rate in E. fetida was hardly affected at low and moderate density, being reduced only at high level, this compares to L.terrestris where even relatively small density effects resulted in a strong negative effect on population growth rate. Our findings indicate that density-dependent regulation in earthworms can be quantified using life-history analysis. The outcomes are in agreement with empirical field observations for populations (i.e. L. terrestris occurs at low density, E. fetida at high density). Consideration of the potential importance of Nicholsonian density dependence for field populations of these two species in light of their known biology however produces counterintuitive conclusions. In E. fetida, although density tolerant, rapid population growth may mean this species may be subject to density dependent regulation. In L. terrestris, although density sensitive, complex behavioural ecology (surface activity, territoriality) may limit of feedback influence on population size.