How sensitive are elasticities of long-run stochastic growth to how environmental variability is modelled?

A functional trait approach to identifying life history patterns in stochastic environments

Temporal variation in demographic processes can greatly impact population dynamics. Perturbations of statistical coefficients that describe demographic rates within matrix models have, for example, revealed that stochastic population growth rates (log(λ s)) of fast life histories are more sensitive to temporal autocorrelation of environmental conditions than those of slow life histories. Yet, we know little about the mechanisms that drive such patterns. Here, we used a mechanistic, functional trait approach to examine the functional pathways by which a typical fast life history species, the macrodetrivore Orchestia gammarellus, and a typical slow life history species, the reef manta ray Manta alfredi, differ in their sensitivity to environmental autocorrelation if (a) growth and reproduction are described mechanistically by functional traits that adhere to the principle of energy conservation, and if (b) demographic variation is determined by temporal autocorrelation in food conditions. Opposite to previous findings, we found that O. gammarellus log(λ s) was most sensitive to the frequency of good food conditions, likely because reproduction traits, which directly impact population growth, were most influential to log(λ s). Manta alfredi log(λs ) was instead most sensitive to temporal autocorrelation, likely because growth parameters, which impact population growth indirectly, were most influential to log(λ s). This differential sensitivity to functional traits likely also explains why we found that O. gammarellus mean body size decreased (due to increased reproduction) but M. alfredi mean body size increased (due to increased individual growth) as food conditions became more favorable. Increasing demographic stochasticity under constant food conditions decreased O. gammarellus mean body size and increased log(λ s) due to increased reproduction, whereas M. alfredi mean body and log(λ s) decreased, likely due to decreased individual growth. Our findings signify the importance of integrating functional traits into demographic models as this provides mechanistic understanding of how environmental and demographic stochasticity affects population dynamics in stochastic environments.

Dispersal evolution and resource matching in a spatially and temporally variable environment

Metapopulations may consist of patches of different quality, and are often disturbed by extrinsic processes causing variation of patch quality. The persistence of such metapopulations then depends on the species' dispersal strategy. In a temporally constant environment, the evolution of dispersal rates follows the resource matching rule, i.e. at the evolutionarily stable dispersal strategy the number of competitors in each patch matches the resource availability in each patch. Here, we investigate how the distribution of individuals resulting from convergence stable dispersal strategies would match the distribution of resources in an environment which is temporally variable due to extrinsic disturbance. We develop an analytically tractable asexual model with two qualities of patches. We show that convergence stable dispersal rates are such that resource matching is predicted in expectation before habitat quality variation, and that the distribution of individuals undermatches resources after habitat quality variation. The overall flow of individuals between patches matches the overall flow of resources between patches resulting from environmental variation. We show that these conclusions can be generalized to organisms with sexual reproduction, and to a metapopulation with three qualities of patches when there is no mutational correlation between dispersal rates.

Non-timber forest product harvest in variable environments: modeling the effect of harvesting as a stochastic sequence

With increasing reports of overexploitation of wild plants for timber and non-timber forest products, there has been an increase in the number of studies investigating the effect of harvest on the dynamics of harvested populations. However, most studies have failed to account for temporal and spatial variability in the ecological conditions in which these species occur, as well as variability in the patterns of harvest intensity. In reality, local harvesters harvest at variable rather than fixed intensity over time. Here we used Markov chains to investigate how different patterns of harvesting intensity (summarized as return time to high harvest) affected the stochastic population growth rate (lambda(s)) and its elasticity to perturbation of means and variances of vital rates. We studied the effect of bark and foliage harvest from African mahogany Khaya senegalensis in two contrasting ecological regions in Benin. Khaya populations declined regardless of time between harvests of high intensity. Moreover, lambda(s) increased with decreasing harvesting pressure in the dry region but, surprisingly, declined in the moist region toward lambda(s) = 0.956. The stochastic elasticity was dominated by the stasis of juveniles and adults. The declining growth rate with decreasing harvest pressure in the moist region was mainly driven by the declining mean survival rates of juveniles and adults. Our results suggest that modeling the temporal variability of harvest intensity as a Markov chain better mimics local practices and provides insights that are missed when temporal variability in harvest intensity is modeled as independent over time and drawn from a fixed distribution.