Multicellular organization is particularly vulnerable to conflicts between different cell types when the body forms from initially isolated cells, as in aggregative multicellular microbes. Like other functions of the multicellular phase, coordinated collective movement can be undermined by conflicts between cells that spend energy in fuelling motion and ‘cheaters’ that get carried along. The evolutionary stability of collective behaviours against such conflicts is typically addressed in populations that undergo extrinsically imposed phases of aggregation and dispersal. Here, via a shift in perspective, we propose that aggregative multicellular cycles may have emerged as a way to temporally compartmentalize social conflicts. Through an eco-evolutionary mathematical model that accounts for individual and collective strategies of resource acquisition, we address regimes where different motility types coexist. Particularly interesting is the oscillatory regime that, similarly to life cycles of aggregative multicellular organisms, alternates on the timescale of several cell generations phases of prevalent solitary living and starvation-triggered aggregation. Crucially, such self-organized oscillations emerge as a result of evolution of cell traits associated to conflict escalation within multicellular aggregates.

Optimising the use of chemical pesticide is required in order to reduce the inevitable environmental and economic costs related to it. The consequences of chemical control are particularly tricky to foresee in the presence of pathogens, displaying heterogeneous traits involved in their life cycle, because its effect will likely differ across the population. In this work, we investigate the effects of trait-dependent pesticide on heterogeneous plant pathogens, by means of a minimal model connecting evolutionary and agricultural states of the system. We model a pathogen population displaying continuous levels of virulence and transmission. Control strategies are modelled by the quantity of pesticide released and its degree of correlation with the pathogen’s heterogeneous traits. We show that the pathogen population can adapt towards opposite evolutionary states, that may be reversed by chemical control due to its heterogeneous selective pressure. This dual behaviour triggers saturating effects in yield production, with respect to pesticide use. As a consequence, we show that maximising yield production and minimising pesticide application are conflicting objectives. We identify Pareto-efficient solutions, where the optimal pesticide type depends on the applied quantity. Our results provide a theoretical framework to explore how to harness heterogeneity in pathogen populations to our advantage.