An arms race between producers and scroungers can drive the evolution of social cognition

Abstract

The "social intelligence hypothesis" states that the need to cope with complexities of social life has driven the evolution of advanced cognitive abilities. It is usually invoked in the context of challenges arising from complex intragroup structures, hierarchies, and alliances. However, a fundamental aspect of group living remains largely unexplored as a driving force in cognitive evolution: the competition between individuals searching for resources (producers) and conspecifics that parasitize their findings (scroungers). In populations of social foragers, abilities that enable scroungers to steal by outsmarting producers, and those allowing producers to prevent theft by outsmarting scroungers, are likely to be beneficial and may fuel a cognitive arms race. Using analytical theory and agent-based simulations, we present a general model for such a race that is driven by the producer-scrounger game and show that the race's plausibility is dramatically affected by the nature of the evolving abilities. If scrounging and scrounging avoidance rely on separate, strategy-specific cognitive abilities, arms races are short-lived and have a limited effect on cognition. However, general cognitive abilities that facilitate both scrounging and scrounging avoidance undergo stable, long-lasting arms races. Thus, ubiquitous foraging interactions may lead to the evolution of general cognitive abilities in social animals, without the requirement of complex intragroup structures.

Keywords: game theory; intraspecific arms race; social foraging; social intelligence hypothesis..

Figure 1

Successful scrounging probability, σ, for different values of cognition effect size a and cognitive mutation effect size s. Dashed black line: a = 0.7, s = 1.5; solid gray line: a = 0.5, s = 0.5; solid black line: a = 0.5, s = 1.5; dashed gray line: a = 0, s = 1.5.

Figure 2

The selective advantage α_p to producers (solid line) and α_s to scroungers (dashed line) accorded by a (+1) cognitive mutation, as a function of d, the cognitive difference in favor of scroungers. The proportion of each foraging strategy is fixed at the proportion found to evolve in computer simulations (0.7 producing, 0.3 scrounging). Parameters values used: s = 1.5, a = 0.5, γ = 0.05.

Figure 3

Examples of GCM and SCM population dynamics in agent-based simulations, under various conditions. Black and white panels show producer frequency over time; color panels show mean cognitive level over time. GCM (b and f): 2 lines representing mean C levels for producers (red) and scroungers (teal); SCM (a and c–e): 4 lines representing mean level of specialized cognitive ability for producing, C _p, in producers (red) and scroungers (blue) and mean level of specialized cognitive ability for scrounging, C _s, in producers (orange) and scroungers (teal). In mixed strategy simulations (d and e), 0–50% producing is included under “scroungers,” 60–100% producing is included under “producers.” Where red line is not visible, it is hidden by the teal or blue lines. In all simulations, population size n = 100; cognitive cost is a fractional deduction of size γ = C/100 in GCM, γ = (C _p + C _s)/100 in SCM; scrounging success baseline probability a = 0.5; mutation rate μ = 0.01 for all genes; mutations in C/C _p/C _s increase or decrease cognitive ability by 1. Note that the y axis scales in colored panels vary. (a) SCM, pure producing/scrounging (PS), s = 1.5. (b) GCM, pure PS, s = 1.5. (c) SCM, pure PS, s = 0.5. (d) SCM, mixed PS, s = 1.5. (e) SCM, mixed PS, s = 1.5. (f) GCM, pure PS (fixed frequencies), random inwards migration of individuals with baseline cognitive level (C = 0).

Figure 4

Mean and standard error of cognitive level among foraging strategies in agent-based computer simulations of the GCM and SCM, under various assumptions. Each mean is calculated for generations 9901–10000, for 100 repeats of each simulation. Columns marked with (*) are means calculated for less than 90 repeats, that is, at least 10 repeats did not have the marked genotype in at least one of the 100 generations considered (see Table 2 for detailed account of valid data points). The 3 column groups in each subfigure correspond to different values of s, slope coefficient of the scrounging success probability function. All simulations are for population size n = 100, T = 50 time steps, G = 10000 generations, mutation rate µ = 0.01. (a) Pure social foraging strategies; cognitive level cost γ = 0. (b) Pure social foraging strategies; γ = C/100. (c) Mixed social foraging strategies (producing probability ≤0.5 alleles are grouped under “scrounger,” producing probability >0.5 alleles are grouped under “producer”); γ = C/100. (d) Pure social foraging strategies at fixed frequency of 0.3:0.7 scroungers to producers (i.e., no evolution in F gene); γ = C/100.