Movement of entomophagous arthropods in agricultural landscapes: links to pest suppression

Entomophagous arthropods can provide valuable biological control services, but they need to fulfill their life cycle in agricultural landscapes often dominated by ephemeral and disturbed habitats. In this environment, movement is critical to escape from disturbances and to find resources scattered in space and time. Despite considerable research effort in documenting species movement and spatial distribution patterns, the quantification of arthropod movement has been hampered by their small size and the variety of modes of movement that can result in redistribution at different spatial scales. In addition, insight into how movement influences in-field population processes and the associated biocontrol services is limited because emigration and immigration are often confounded with local-scale population processes. More detailed measurements of the habitat functionality and movement processes are needed to better understand the interactions between species movement traits, disturbances, the landscape context, and the potential for entomophagous arthropods to suppress economically important pests.

Spatio-temporal environmental correlation and population variability in simple metacommunities

Natural populations experience environmental conditions that vary across space and over time. This variation is often correlated between localities depending on the geographical separation between them, and different species can respond to local environmental fluctuations similarly or differently, depending on their adaptation. How this emerging structure in environmental correlation (between-patches and between-species) affects spatial community dynamics is an open question. This paper aims at a general understanding of the interactions between the environmental correlation structure and population dynamics in spatial networks of local communities (metacommunities), by studying simple two-patch, two-species systems. Three different pairs of interspecific interactions are considered: competition, consumer-resource interaction, and host-parasitoid interaction. While the results paint a relatively complex picture of the effect of environmental correlation, the interaction between environmental forcing, dispersal, and local interactions can be understood via two mechanisms. While increasing between-patch environmental correlation couples immigration and local densities (destabilising effect), the coupling between local populations under increased between-species environmental correlation can either amplify or dampen population fluctuations, depending on the patterns in density dependence. This work provides a unifying framework for modelling stochastic metacommunities, and forms a foundation for a better understanding of population responses to environmental fluctuations in natural systems.

The co-evolution of multiply-informed dispersal: information transfer across landscapes from neighbors and immigrants

Dispersal plays a key role in natural systems by shaping spatial population and evolutionary dynamics. Dispersal has been largely treated as a population process with little attention to individual decisions and the influence of information use on the fitness benefits of dispersal despite clear empirical evidence that dispersal behavior varies among individuals. While information on local density is common, more controversial is the notion that indirect information use can easily evolve. We used an individual-based model to ask under what conditions indirect information use in dispersal will evolve. We modeled indirect information provided by immigrant arrival into a population which should be linked to overall metapopulation density. We also modeled direct information use of density which directly impacts fitness. We show that immigrant-dependent dispersal evolves and does so even when density dependent information is available. Use of two sources of information also provides benefits at the metapopulation level by reducing extinction risk and prolonging the persistence of populations. Our results suggest that use of indirect information in dispersal can evolve under conservative conditions and thus could be widespread.

Evolution of predator dispersal in relation to spatio-temporal prey dynamics: how not to get stuck in the wrong place!

The eco-evolutionary dynamics of dispersal are recognised as key in determining the responses of populations to environmental changes. Here, by developing a novel modelling approach, we show that predators are likely to have evolved to emigrate more often and become more selective over their destination patch when their prey species exhibit spatio-temporally complex dynamics. We additionally demonstrate that the cost of dispersal can vary substantially across space and time. Perhaps as a consequence of current environmental change, many key prey species are currently exhibiting major shifts in their spatio-temporal dynamics. By exploring similar shifts in silico, we predict that predator populations will be most vulnerable when prey dynamics shift from stable to complex. The more sophisticated dispersal rules, and greater variance therein, that evolve under complex dynamics will enable persistence across a broader range of prey dynamics than the rules which evolve under relatively stable prey conditions.

Confounding environmental colour and distribution shape leads to underestimation of population extinction risk

The colour of environmental variability influences the size of population fluctuations when filtered through density dependent dynamics, driving extinction risk through dynamical resonance. Slow fluctuations (low frequencies) dominate in red environments, rapid fluctuations (high frequencies) in blue environments and white environments are purely random (no frequencies dominate). Two methods are commonly employed to generate the coloured spatial and/or temporal stochastic (environmental) series used in combination with population (dynamical feedback) models: autoregressive [AR(1)] and sinusoidal (1/f) models. We show that changing environmental colour from white to red with 1/f models, and from white to red or blue with AR(1) models, generates coloured environmental series that are not normally distributed at finite time-scales, potentially confounding comparison with normally distributed white noise models. Increasing variability of sample Skewness and Kurtosis and decreasing mean Kurtosis of these series alter the frequency distribution shape of the realised values of the coloured stochastic processes. These changes in distribution shape alter patterns in the probability of single and series of extreme conditions. We show that the reduced extinction risk for undercompensating (slow growing) populations in red environments previously predicted with traditional 1/f methods is an artefact of changes in the distribution shapes of the environmental series. This is demonstrated by comparison with coloured series controlled to be normally distributed using spectral mimicry. Changes in the distribution shape that arise using traditional methods lead to underestimation of extinction risk in normally distributed, red 1/f environments. AR(1) methods also underestimate extinction risks in traditionally generated red environments. This work synthesises previous results and provides further insight into the processes driving extinction risk in model populations. We must let the characteristics of known natural environmental covariates (e.g., colour and distribution shape) guide us in our choice of how to best model the impact of coloured environmental variation on population dynamics.

Quorum sensing and density-dependent dispersal in an aquatic model system

Many organisms use cues to decide whether to disperse or not, especially those related to the composition of their environment. Dispersal hence sometimes depends on population density, which can be important for the dynamics and evolution of sub-divided populations. But very little is known about the factors that organisms use to inform their dispersal decision. We investigated the cues underlying density-dependent dispersal in inter-connected microcosms of the freshwater protozoan Paramecium caudatum. In two experiments, we manipulated (i) the number of cells per microcosm and (ii) the origin of their culture medium (supernatant from high- or low-density populations). We found a negative relationship between population density and rates of dispersal, suggesting the use of physical cues. There was no significant effect of culture medium origin on dispersal and thus no support for chemical cues usage. These results suggest that the perception of density – and as a result, the decision to disperse – in this organism can be based on physical factors. This type of quorum sensing may be an adaptation optimizing small scale monitoring of the environment and swarm formation in open water.