Experimental & theoretical investigation of the dynamics & stability of single populations and metapopulations of drosophila melanogaster in the laboratory

Abstract

For my doctoral thesis, I have used a combination of experiments and simulations to investigate the various factors that affect the dynamics and stability of spatiallystructured as well as spatially unstructured populations. A brief description of my work is as follows: Metapopulation stability Although classical population ecology theory treats individuals as being homogeneously distributed over space, most natural populations exhibit some degree of spatial structuring into metapopulations: ensembles of local populations (henceforth, subpopulations) that are connected by migration. Using Ricker-based coupled map lattice simulations, I show that the precise spatial arrangement of the subpopulations does not interact with migration in determining metapopulation stability. This indicates that the fine-scale details of the spatial arrangement of subpopulations can often be safely ignored while modeling metapopulation dynamics. In a continuation of this work, I show that, at least for systems in which the subpopulations follow Ricker dynamics, maximum metapopulation stability is attained at intermediate migration rates, regardless of whether the migration rate is density-dependent, density-independent or stochastic. However, migration rate can stabilize the dynamics of a metapopulation only when the migration events take place very frequently. These results were found to be robust to different spatial arrangements of patches. 4 The above studies indicated that a metapopulation would be most stable at intermediate rates of migration - a prediction that I tested using laboratory metapopulations of Drosophila melanogaster. I show that a low migration rate (10%) stabilizes D. melanogaster metapopulations by inducing asynchrony between neighboring subpopulations. On the other hand, higher migration rate (30%) synchronizes the neighboring subpopulations, thus leading to metapopulation instability. Simulations based on a simple non-species specific population growth model (Ricker map) captured most features of the data, suggesting that the results are generalizable. A subsequent simulation study indicated that, contrary to the concern raised by some other workers, asynchrony at intermediate migration rates is a very likely outcome in real metapopulations. I have also empirically investigated the effects of constant localized perturbations on the stability of metapopulations. The experimental data suggests that constant addition of individuals to a particular subpopulation in every generation stabilizes that population locally, but does not have an effect on the dynamics of the metapopulation in any way. Simulations of the experimental system, based on the Ricker map, were able to recover the empirical findings, indicating the generality of the results. I also simulated the possible consequences of perturbing more subpopulations, increasing the strength of perturbations and different rates of migration, but found that none of these conditions were expected to alter the outcomes of our experiments. Finally, I show that the main results of this study are robust to the presence of local extinctions in the metapopulation. 5 Stability of spatially unstructured populations Prior studies have indicated that the dynamics of D. melanogaster single populations are affected by three major density-dependent feedback loops: larval density acting on 1) larval survivorship and 2) adult fecundity, and 3) the effects of adult density on adult fecundity. In an experimental study on replicate D. melanogaster single populations, I altered the relative strengths of these loops by manipulating the quantity and quality of nutrition available to the larvae and the adults. This study led to several insights into how the three density-dependent loops interact to shape the dynamics of D. melanogaster populations in the laboratory. In an experimental study, I examined the effects of four different rates of adult mortality (control, 20%, 40% and 60%) on the stability of replicate D. melanogaster single populations under two different nutritional regimes. When the intrinsic growth rate was low, there was no significant effect of different mortality rates on stability. However, under high rates of intrinsic growth, the effects of mortality rates on stability varied based on the index chosen to quantify stability. Specifically, under high growth rates, the variation in population size (as measured by coefficient of variation, CV) across generations, decreased monotonically with increasing rates of mortality. However, the average one-step fluctuation in population size (as measured by fluctuation index, FI) was significantly larger at lower mortality rate (20%). The extinction probabilities of the low mortality treatment were also found to be different from the controls. 6 I also investigated the issue of evolution of population stability as a result of selection acting on the life history of organisms. Although there were several hypotheses about the mechanism of evolution of population stability, none of them had any empirical support. A previous study had provided the first experimental demonstration that population stability can evolve as a correlated (and not direct) response to selection on life-history traits. In a subsequent study, which extends the above work, I show that the evolution of one type of stability property (constancy) does not necessarily guarantee that other stability properties would also evolve simultaneously. Moreover, manifestation of stability properties was found to depend critically on the fine details of the environment under which the populations are maintained. Finally, in another experimental study, I demonstrate that minor variations in pre-assay rearing conditions can lead to systematic bias in life-history traits like fecundity. This underlines the importance of an often-neglected source of stochastic variations that can potentially affect the dynamics of populations, even under controlled laboratory conditions.