Fitness-dependent dispersal in metapopulations and its consequences for persistence and synchrony

1. We present a novel metapopulation model where dispersal is fitness dependent: the strength of migration from a site is dependent on the expected reproductive fitness of individuals there. Furthermore, individuals continue to migrate until they reach a suitable habitat where their expected fitness is above a threshold value.
2. Fitness-dependent dispersal has a very strong stabilizing effect on population dynamics, even when the intrinsic dynamics of populations in the absence of dispersal exhibit complex high-amplitude oscillations. This stabilizing effect is much stronger than that of the density-independent dispersal normally considered in metapopulation models.
3. Even when fitness-dependent dispersal does not stabilize the dynamics in a formal sense, it generally leads to simplification, with complex or even chaotic fluctuations being reduced to simple cycles.
4. This form of dispersal also has a strong tendency to synchronize local population dynamics across the spatial extent of the metapopulation.
5. These conclusions are robust to the addition of strong stochasticity in the migration threshold.     

Eco-evolutionary dynamics

Evolutionary ecologists and population biologists have recently considered that ecological and evolutionary changes are intimately linked and can occur on the same time-scale. Recent theoretical developments have shown how the feedback between ecological and evolutionary dynamics can be linked, and there are now empirical demonstrations showing that ecological change can lead to rapid evolutionary change. We also have evidence that microevolutionary change can leave an ecological signature. We are at a stage where the integration of ecology and evolution is a necessary step towards major advances in our understanding of the processes that shape and maintain biodiversity. This special feature about ‘eco-evolutionary dynamics’ brings together biologists from empirical and theoretical backgrounds to bridge the gap between ecology and evolution and provide a series of contributions aimed at quantifying the interactions between these fundamental processes.     

Slight phenotypic variation in predators and prey causes complex predator-prey oscillations

Predator-prey oscillations are expected to show a 1/4-phase lag between predator and prey. However, observed dynamics of natural or experimental predator-prey systems are often more complex. A striking but hardly studied example are sudden interruptions of classic 1/4-lag cycles with periods of antiphase oscillations, or periods without any regular predator-prey oscillations. These interruptions occur for a limited time before the system reverts to regular 1/4-lag oscillations, thus yielding intermittent cycles. Reasons for this behaviour are often difficult to reveal in experimental systems. Here we test the hypothesis that such complex dynamical behaviour may result from minor trait variation and trait adaptation in both the prey and predator, causing recurrent small changes in attack rates that may be hard to capture by empirical measurements. Using a model structure where the degree of trait variation in the predator can be explicitly controlled, we show that a very limited amount of adaptation resulting in 10–15% temporal variation in attack rates is already sufficient to generate these intermittent dynamics. Such minor variation may be present in experimental predator-prey systems, and may explain disruptions in regular 1/4-lag oscillations.     

Predator–vole interactions in northern Europe: the role of small mustelids revised

The cyclic population dynamics of vole and predator communities is a key phenomenon in northern ecosystems, and it appears to be influenced by climate change. Reports of collapsing rodent cycles have attributed the changes to warmer winters, which weaken the interaction between voles and their specialist subnivean predators. Using population data collected throughout Finland during 1986–2011, we analyse the spatio-temporal variation in the interactions between populations of voles and specialist, generalist and avian predators, and investigate by simulations the roles of the different predators in the vole cycle. We test the hypothesis that vole population cyclicity is dependent on predator–prey interactions during winter. Our results support the importance of the small mustelids for the vole cycle. However, weakening specialist predation during winters, or an increase in generalist predation, was not associated with the loss of cyclicity. Strengthening of delayed density dependence coincided with strengthening small mustelid influence on the summer population growth rates of voles. In conclusion, a strong impact of small mustelids during summers appears highly influential to vole population dynamics, and deteriorating winter conditions are not a viable explanation for collapsing small mammal population cycles.     

Population dynamics of the chydorid cladocera of a Southern Michigan Marl Lake

The seasonal population dynamics are described for 21 chydorid species in two shallow Scirpus subterminalis beds of Lawrence Lake, Michigan, USA. Six species were rare; four species were predominantly abundant. The dynamics of the populations followed no consistent pattern among the species. However, each species, with one exception, may follow the same pattern from year to year. Eight species overwintered under the ice as parthenogenetic individuals. Populations of Alonella excisa may be greatly reduced during the summer months because of competition with A. exigua.     

Evolution of cross-diffusion and self-diffusion

This article is concerned with the evolution of certain types of density-dependent dispersal strategy in the context of two competing species with identical population dynamics and same random dispersal rates. Such density-dependent movement, often referred to as cross-diffusion and self-diffusion, assumes that the movement rate of each species depends on the density of both species and that the transition probability from one place to its neighbourhood depends solely on the arrival spot (independent of the departure spot). Our results suggest that for a one-dimensional homogeneous habitat, if the gradients of two cross- and self-diffusion coefficients have the same direction, the species with the smaller gradient will win, i.e. the dispersal strategy with the smaller gradient of cross- and self-diffusion coefficient will evolve. In particular, it suggests that the species with constant cross- and self-diffusion coefficients may have competitive advantage over species with non-constant cross- and self-diffusion coefficients. However, if the two gradients have opposite directions, neither of the two dispersal strategies wins as these two species can coexist.     

Evolutionary Dynamics of Seed Size and Seedling Competitive Ability

We present a model for the evolutionary dynamics of seed size when there is a trade-off between seed size and seed number, and seedlings from large seeds are better competitors and have a higher precompetitive survival than seedlings from small seeds. We find that strong competitive asymmetry, high resource levels, and intermediate harshness of the precompetitive environment favor coexistence of plants with different seed sizes. If the evolution of seed size is mutation-limited and single mutations have only a small phenotypic effect, then an initially monomorphic population reaches the final evolutionarily stable polymorphic state through one or more discrete evolutionary branching events. At each such branching event, a given lineage already present in the population divides into two phenotypically diverging daughter lines, each with its own seed size. If the precompetitive survival of seeds and seedlings is high for small and large seeds alike, however, evolutionary branching may be followed by the extinction of one or more lineages. Various results presented here are model-independent and point the way to a more general evolutionary bifurcation theory describing how the number and stability properties of evolutionary equilibria may change as a consequence of changes in model parameters.