Sutirth Dey

Stability via asynchrony in Drosophila metapopulations with low migration rates.

Very few experimental studies have examined how migration rate affects metapopulation dynamics and stability. We studied the dynamics of replicate laboratory metapopulations of Drosophila under different migration rates. Low migration stabilized metapopulation dynamics, while promoting unstable subpopulation dynamics, by inducing asynchrony among neighboring subpopulations. High migration synchronized subpopulation dynamics, thereby destabilizing the metapopulations. Contrary to some theoretical predictions, increased migration did not affect average population size. Simulations based on a simple non–species-specific population growth model captured most features of the data, which suggests that our results are generalizable.

Stabilizing biological populations and metapopulations through Adaptive Limiter Control

Despite great interest in techniques for stabilizing the dynamics of biological populations and metapopulations, very few practicable methods have been developed or empirically tested. We propose an easily implementable method, Adaptive Limiter Control (ALC), for reducing the magnitude of fluctuation in population sizes and extinction frequencies and demonstrate its efficacy in stabilizing laboratory populations and metapopulations of Drosophila melanogaster. Metapopulation stability was attained through a combination of reduced size fluctuations however, and synchrony at the subpopulation level. Simulations indicated that ALC was effective over a range of maximal population growth rates, migration rates and population dynamics models. Since simulations using broadly applicable, non-species-specific models of population dynamics were able to capture most features of the experimental data, we expect our results to be applicable to a wide range of species.

The evolution of population stability as a by-product of life-history evolution

Proposed mechanisms for the evolution of population stability include group selection through longterm persistence, individual selection acting directly on stability determining the demographic parameters, and the evolution of stability as a by-product of life-history evolution. None of these hypotheses currently has clear empirical support. Using two sets of Drosophila melanogaster populations, we provide experimental evidence of stability evolving as a correlated response to selection on traits not directly related to demography. Four populations (FEJs) were selected for faster development and early reproduction for 125 generations, and the other four (JBs) were ancestral controls. All FEJ and JB populations have been maintained on discrete generations at moderate density, thus eliminating differential selection on stability determining demographic parameters. We derived eight small populations from each FEJ and JB population, and subjected four small populations each to either stabilizing or destabilizing food regimes. Census data on these 64 small populations over 20 generations clearly showed that the FEJ populations have significantly less temporal fluctuations in their numbers in both food regimes compared to their controls. This greater stability of the FEJ populations is probably a by-product of the evolution of reduced fecundity and pre-adult survivorship, as a correlated response to selection for rapid development.

Local Perturbations Do Not Affect Stability of Laboratory Fruitfly Metapopulations

Background A large number of theoretical studies predict that the dynamics of spatially structured populations (metapopulations) can be altered by constant perturbations to local population size. However, these studies presume large metapopulations inhabiting noise-free, zero-extinction environments, and their predictions have never been empirically verified. Methodology/Principal Findings Here we report an empirical study on the effects of localized perturbations on global dynamics and stability, using fruitfly metapopulations in the laboratory. We find that constant addition of individuals to a particular subpopulation in every generation stabilizes that subpopulation locally, but does not have any detectable effect on the dynamics and stability of the metapopulation. Simulations of our experimental system using a simple but widely applicable model of population dynamics were able to recover the empirical findings, indicating the generality of our results. We then simulated the possible consequences of perturbing more subpopulations, increasing the strength of perturbations, and varying the rate of migration, but found that none of these conditions were expected to alter the outcomes of our experiments. Finally, we show that our main results are robust to the presence of local extinctions in the metapopulation. Conclusions/Significance Our study shows that localized perturbations are unlikely to affect the dynamics of real metapopulations, a finding that has cautionary implications for ecologists and conservation biologists faced with the problem of stabilizing unstable metapopulations in nature.

A comparison of six methods for stabilizing population dynamics

Over the last two decades, several methods have been proposed for stabilizing the dynamics of biological populations. However, these methods have typically been evaluated using different population dynamics models and in the context of very different concepts of stability, which makes it difficult to compare their relative efficiencies. Moreover, since the dynamics of populations are dependent on the life-history of the species and its environment, it is conceivable that the stabilizing effects of control methods would also be affected by such factors, a complication that has typically not been investigated. In this study, we compare six different control methods with respect to their efficiency at inducing a common level of enhancement (defined as 50% increase) for two kinds of stability (constancy and persistence) under four different life-history/environment combinations. Since these methods have been analytically studied elsewhere, we concentrate on an intuitive understanding of realistic simulations incorporating noise, extinction probability and lattice effect. We show that for these six methods, even when the magnitude of stabilization attained is the same, other aspects of the dynamics like population size distribution can be very different. Consequently, correlated aspects of stability, like the amount of persistence for a given degree of constancy stability (and vice versa) or the corresponding effective population size (a measure of resistance to genetic drift) vary widely among the methods. Moreover, the number of organisms needed to be added or removed to attain similar levels of stabilization also varies for these methods, a fact that has economic implications. Finally, we compare the relative efficiencies of these methods through a composite index of various stability related measures. Our results suggest that Lower Limiter Control (LLC) seems to be the optimal method under most conditions, with the recently proposed Adaptive Limiter Control (ALC) being a close second.

Laboratory evolution of population stability in Drosophila: constancy and persistence do not necessarily coevolve.

1. Despite considerable theoretical work, the evolution of population stability has rarely been investigated empirically. Moreover, it is not clear whether different stability properties of a population evolve together, or independently. 2. We investigate the evolution of two aspects of population stability using laboratory populations of Drosophila melanogaster selected for faster preadult development and early reproduction, and their matched controls. 3. We show that the constancy stability of the selected populations is significantly higher than their controls, confirming a previous observation that population stability can evolve as a by-product of life-history evolution. This enhanced constancy stability is due to a reduced maximal per capita growth rate, brought about by a reduction in fecundity of the selected populations as a result of the trade-off between developmental rate and fecundity. 4. Persistence stability, as reflected by the probability of extinction, does not differ significantly between selected and control populations. 5. We also show how seemingly trivial experimental details, such as the protocol for restarting extinct populations, can interact with life-history traits to alter the manifestation of the stability properties of a population.

Niche construction in evolutionary theory: the construction of an academic niche?

1Evolutionary Biology Laboratory, Evolutionary and Organismal Biology Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur, Bengaluru 560 064, India 2Animal Behaviour and Sociogenetics Laboratory, Evolutionary and Organismal Biology Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur, Bengaluru 560 064, India 3Department of Biological Sciences, Indian Institute of Science Education and Research Mohali, Knowledge City, Sector 81, SAS Nagar, P.O. Manauli, Mohali, Punjab 140 306, India 4Population Biology Laboratory, Biology Division, Indian Institute of Science Education and Research Pune, Dr. Homi Bhabha Road, Pune 411 008, India *For correspondence. E-mail: tncvidya@jncasr.ac.in; tncvidya@gmail.com.

Stabilizing Spatially-Structured Populations through Adaptive Limiter Control

Stabilizing the dynamics of complex, non-linear systems is a major concern across several scientific disciplines including ecology and conservation biology. Unfortunately, most methods proposed to reduce the fluctuations in chaotic systems are not applicable to real, biological populations. This is because such methods typically require detailed knowledge of system specific parameters and the ability to manipulate them in real time; conditions often not met by most real populations. Moreover, real populations are often noisy and extinction-prone, which can sometimes render such methods ineffective. Here, we investigate a control strategy, which works by perturbing the population size, and is robust to reasonable amounts of noise and extinction probability. This strategy, called the Adaptive Limiter Control (ALC), has been previously shown to increase constancy and persistence of laboratory populations and metapopulations of Drosophila melanogaster. Here, we present a detailed numerical investigation of the effects of ALC on the fluctuations and persistence of metapopulations. We show that at high migration rates, application of ALC does not require a priori information about the population growth rates. We also show that ALC can stabilize metapopulations even when applied to as low as one-tenth of the total number of subpopulations. Moreover, ALC is effective even when the subpopulations have high extinction rates: conditions under which another control algorithm had previously failed to attain stability. Importantly, ALC not only reduces the fluctuation in metapopulation sizes, but also the global extinction probability. Finally, the method is robust to moderate levels of noise in the dynamics and the carrying capacity of the environment. These results, coupled with our earlier empirical findings, establish ALC to be a strong candidate for stabilizing real biological metapopulations.

A possible tradeoff between developmental rate and pathogen resistance in Drosophila melanogaster

, there is little empirical informationon the genetic correlations between immune function andlife-history traits. One hypothesis about immune functionrelated tradeoffs is that they are mediated via the conflict-ing demands of resource allocation to immune defense andother life-history related traits, and there is now some em-pirical evidence for this from studies on

Escherichia coli populations adapt to complex, unpredictable fluctuations by minimizing trade-offs across environments.

In nature, organisms are simultaneously exposed to multiple stresses (i.e. complex environments) that often fluctuate unpredictably. Although both these factors have been studied in isolation, the interaction of the two remains poorly explored. To address this issue, we selected laboratory populations of Escherichia coli under complex (i.e. stressful combinations of pH, H2O2 and NaCl) unpredictably fluctuating environments for ~900 generations. We compared the growth rates and the corresponding trade‐off patterns of these populations to those that were selected under constant values of the component stresses (i.e. pH, H2O2 and NaCl) for the same duration. The fluctuation‐selected populations had greater mean growth rate and lower variation for growth rate over all the selection environments experienced. However, whereas the populations selected under constant stresses experienced trade‐offs in the environments other than those in which they were selected, the fluctuation‐selected populations could bypass the across‐environment trade‐offs almost entirely. Interestingly, trade‐offs were found between growth rates and carrying capacities. The results suggest that complexity and fluctuations can strongly affect the underlying trade‐off structure in evolving populations.