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. N atural populations often exhibit some degree of spatial structuring into metapopulations: ensembles of local populations (subpopulations) connected by migration (1). The effects of migration rate on the dynamics and stability of metapopulations have been extensively investigated theoretically (1). Analytical (2, 3) and simulation (4) studies have shown that even a simple system, consisting of two subpopulations (modeled by a pair of logistic maps) with a constant rate of to-and-fro migration, can exhibit rich dynamic behavior. In such systems, low, intermediate, and high migration rates have been shown to lead to complex, stable, and unstable dynamics, respectively (2-4). Similar results have been obtained with a variety of more realistic models (5-8). Potential stabilizing effects of migration have also been shown in studies on more complex systems (9-12). Although it has been empirically shown that migration can stabilize dynamics (13, 14), most metapopulation experiments have been carried out within the classical extinction-recolonization framework (15), which ignores the dynamics of population size. Thus, rigorous tests of theoretical predictions regarding the effects of migration rate on metapopulation dynamics are rare (13). Similarly, despite a large corpus of theoretical studies (16-18), the effects of migration rates on mean population size have rarely been investigated experimentally (19).Here, we report the effects of low (10%) and high (30%) migration rates on the dynamics of replicated laboratory metapopulations of the fruit fly Drosophila melanogaster in a 21-generation experiment (20). We quantified constancy stability (21) of the metapopulations and subpopulations with the use of a dimensionless measure of amplitude of fluctuation in population size over time (22). This statistic, which we call the fluctuation index (FI), is inversely related to stability. We also performed simulations (20) using a simple non-Drosophila-specific model to test whether the results reflect a simple effect of migration rates on typical population dynamics, or are due to some specific features of the life history and ecology of Drosophila cultures.Metapopulations with low levels of migration (henceforth LMMs) had lower FI values for metapopulation size than did either the control metapopulation...

There is considerable understanding about how laboratory populations respond to predictable (constant or deteriorating environment) selection for single environmental variables such as temperature or pH. However, such insights may not apply when selection environments comprise multiple variables that fluctuate unpredictably, as is common in nature. To address this issue, we grew replicate laboratory populations of Escherichia coli in nutrient broth whose pH and concentrations of salt (NaCl) and hydrogen peroxide (H 2 O 2 ) were randomly changed daily. After~170 generations, the fitness of the selected populations had not increased in any of the three selection environments. However, these selected populations had significantly greater fitness in four novel environments which have no known fitness-correlation with tolerance to pH, NaCl or H 2 O 2 . Interestingly, contrary to expectations, hypermutators did not evolve. Instead, the selected populations evolved an increased ability for energy-dependent efflux activity that might enable them to throw out toxins, including antibiotics, from the cell at a faster rate. This provides an alternate mechanism for how evolvability can evolve in bacteria and potentially lead to broad-spectrum antibiotic resistance, even in the absence of prior antibiotic exposure. Given that environmental variability is increasing in nature, this might have serious consequences for public health.

Global climate is changing rapidly and is accompanied by large‐scale fragmentation and destruction of habitats. Since dispersal is the first line of defense for mobile organisms to cope with such adversities in their environment, it is important to understand the causes and consequences of evolution of dispersal. Although dispersal is a complex phenomenon involving multiple dispersal‐components like propensity (tendency to leave the natal patch) and ability (to travel long distances), the relationship between these traits is not always straight‐forward, it is not clear whether these traits can evolve simultaneously or not, and how their interactions affect the overall dispersal profile. To investigate these issues, we subjected four large (n ∼ 2400) outbred populations of Drosophila melanogaster to artificial selection for increased dispersal, in a setup that mimicked increasing habitat fragmentation over 33 generations. The propensity and ability of the selected populations were significantly greater than the non‐selected controls and the difference persisted even in the absence of proximate drivers for dispersal. The dispersal kernel evolved to have significantly greater standard deviation and reduced values of skew and kurtosis, which ultimately translated into the evolution of a greater frequency of long‐distance dispersers (LDDs). We also found that although sex‐biased dispersal exists in D. melanogaster, its expression can vary depending on which dispersal component is being measured and the environmental condition under which dispersal takes place. Interestingly though, there was no difference between the two sexes in terms of dispersal evolution. We discuss possible reasons for why some of our results do not agree with previous laboratory and field studies. The rapid evolution of multiple components of dispersal and the kernel, expressed even in the absence of stress, indicates that dispersal evolution cannot be ignored while investigating eco‐evolutionary phenomena like speed of range expansion, disease spread, evolution of invasive species and destabilization of metapopulation dynamics.

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.

No abstract

Dispersal syndromes (i.e. suites of phenotypic correlates of dispersal) are potentially important determinants of local adaptation in populations. Species that exhibit sexual dimorphism in their life history or behaviour may exhibit sex-specific differences in their dispersal syndromes. Unfortunately, there is little empirical evidence of sex differences in dispersal syndromes and how they respond to environmental change or dispersal evolution. We investigated these issues using two same-generation studies and a long-term (greater than 70 generations) selection experiment on laboratory populations of There was a marked difference between the dispersal syndromes of males and females, the extent of which was modulated by nutrition availability. Moreover, dispersal evolution via spatial sorting reversed the direction of interaction in one trait (desiccation resistance), while eliminating the sex difference in another trait (body size). Thus, we show that sex differences obtained through same-generation trait-associations ('ecological dispersal syndromes') are probably environment-dependent. Moreover, even under constant environments, they are not good predictors of the sex differences in 'evolutionary dispersal syndrome' (i.e. trait-associations shaped during dispersal evolution). Our findings have implications for local adaptation in the context of sex-biased dispersal and habitat-matching, as well as for the use of dispersal syndromes as a proxy of dispersal.This article is part of the theme issue 'Linking local adaptation with the evolution of sex differences'.

Periodic bottlenecks play a major role in shaping the adaptive dynamics of natural and laboratory populations of asexual microbes. Here we study how they affect the 'Extent of Adaptation' (EoA), in such populations. EoA, the average fitness gain relative to the ancestor, is the quantity of interest in a large number of microbial experimental-evolution studies which assume that for any given bottleneck size (N0) and number of generations between bottlenecks (g), the harmonic mean size (HM=N0g) will predict the ensuing evolutionary dynamics. However, there are no theoretical or empirical validations for HM being a good predictor of EoA. Using experimentalevolution with Escherichia coli and individual-based simulations, we show that HM fails to predict EoA (i.e., higher N0g does not lead to higher EoA). This is because although higher g allows populations to arrive at superior benefits by entailing increased variation, it also reduces the efficacy of selection, which lowers EoA. We show that EoA can be maximized in evolution experiments by either maximizing N0 and/or minimizing g. We also conjecture that N0/g is a better predictor of EoA than N0g. Our results call for a re-evaluation of the role of population size in predicting fitness trajectories. They also aid in predicting adaptation in asexual populations, which has important evolutionary, epidemiological and economic implications.

Density‐dependent dispersal (DDD) has been observed across taxa, and is expected to affect phenomena such as population dynamics, biological invasions, range expansions, and community assembly. However, little is known about whether the patterns of DDD are robust to changes in the environment. For example, the pre‐dispersal context could affect the physiology of organisms, which in turn could alter their DDD. Similarly, in sexually reproducing organisms, males and females might be differentially affected by the environment, with possible changes in their dispersal properties. To investigate some of these issues, we performed three independent experiments using laboratory populations of Drosophila melanogaster, which tested the effects of pre‐dispersal context, sex of the dispersers and presence of mates on DDD. A two‐patch dispersal setup was used to estimate the dispersal propensity and temporal dispersal profile of adult fruit flies. Comparing the data from two different pre‐dispersal contexts (variable and uniform pre‐dispersal adult densities), we found that longer pre‐dispersal exposure to higher densities led to stronger negative DDD in both males and females. Surprisingly, this change in DDD strength was accompanied by a switch in the direction of sex‐biased dispersal: from female‐biased dispersal at a low density to male‐biased dispersal at a high density. Moreover, we found that patterns of both density dependence and sex bias were contingent upon the interaction of males and females, as neither sex exhibited DDD in the absence of the other. Taken together, these results suggest that DDD and sex‐biased dispersal can be labile and be driven by the environmental context. Finally, we discuss the potential implications of these findings in terms of various ecological and evolutionary processes.