Lonely hearts or sex in the city? Density-dependent effects in mating systems

Abstract

Two very basic ideas in sexual selection are heavily influenced by numbers of potential mates: the evolution of anisogamy, leading to sex role differentiation, and the frequency dependence of reproductive success that tends to equalize primary sex ratios. However, being explicit about the numbers of potential mates is not typical to most evolutionary theory of sexual selection. Here, we argue that this may prevent us from finding the appropriate ecological equilibria that determine the evolutionary endpoints of selection. We review both theoretical and empirical advances on how population density may influence aspects of mating systems such as intrasexual competition, female choice or resistance, and parental care. Density can have strong effects on selective pressures, whether or not there is phenotypic plasticity in individual strategies with respect to density. Mating skew may either increase or decrease with density, which may be aided or counteracted by changes in female behaviour. Switchpoints between alternative mating strategies can be density dependent, and mate encounter rates may influence mate choice (including mutual mate choice), multiple mating, female resistance to male mating attempts, mate searching, mate guarding, parental care, and the probability of divorce. Considering density-dependent selection may be essential for understanding how populations can persist at all despite sexual conflict, but simple models seem to fail to predict the diversity of observed responses in nature. This highlights the importance of considering the interaction between mating systems and population dynamics, and we strongly encourage further work in this area.

Figure 1

Proportions of unsuccessful males in two simple simulated scenarios. Each dot is an outcome of one simulation run, where locations of 100 individuals were randomly distributed to a square area of two-dimensional space. The size of the area is h×h units, where h leads to the density as indicated on the x axis (i.e. density=100/h²). In (a), males vary in their resource-holding power (RHP), drawn from a normal distribution (mean 0, variance 1). Female locations are not explicitly modelled, but a male is assumed to be unsuccessful in acquiring matings, if there is another male with higher RHP within less than one unit of distance; otherwise he is successful. In the scenario marked with open dots in (b), both males and females are randomly distributed in space, males vary in their attractiveness to females (drawn from a normal distribution, mean 0, variance 1), and every female mates by choosing the most attractive male among those located within one distance unit (if no male is available there, females choose the closest one). The filled dots in (b) mark a similar scenario, but add a component where males follow the distribution of females: after the distribution of females is determined, male locations are recalculated until no male is further away than 0.5 distance units from a female.

Figure 2

Evolution can increase the proportion of coercive males, x, beyond the extinction boundary if mating skew is not allowed to depend on population density. (a) Future frequency of the A allele, x(t+1), against current frequency, x(t); see Appendix for allele definitions. If mating skew depends on density, the advantage of coercive males disappears faster (i.e. the solid line approaches and crosses the diagonal, which is marked as the dotted line). The process stabilizes at an equilibrium x*=0.324, which allows population persistence (solid line). Density-independent mating skew increases x(t) up till the extinction threshold (dashed line). (b) Evolution over time, showing the numbers of individuals carrying the ‘a’ or ‘A’ allele, if mating skew depends (solid lines) or does not depend (dashed line) on density. The results are derived according to the model in the Appendix, which assumes ‘fast–slow’ dynamics, where evolutionary equilibria are approached at a slower pace than ecological equilibria. However, results do not change qualitatively if these two timescales are equal (not shown). Parameter values: m_max=5, f=0.5, F=1.5, k=0.001, K=1000, which implies that extinction occurs when x≥2/3.