Patterns of environmental variation influence the utility, and thus evolution, of different learning strategies. We use stochastic,individual-based evolutionary models to assess the relative advantages of 15 different learning strategies (genetic determination,individual learning, vertical social learning, horizontal/oblique social learning, and contingent combinations of these) when competing in variable environments described by 1/f noise. When environmental variation has little effect on fitness, then genetic determinism persists. When environmental variation is large and equal over all time-scales ("white noise") then individual learning is adaptive. Social learning is advantageous in "red noise" environments when variation over long time-scales is large. Climatic variability increases with time-scale, so that short-lived organisms should be able to rely largely on genetic determination. Thermal climates usually are insufficiently red for social learning to be advantageous for species whose fitness is very determined by temperature. In contrast, population trajectories of many species, especially large mammals and aquatic carnivores, are sufficiently red to promote social learning in their predators. The ocean environment is generally redder than that on land. Thus, while individual learning should be adaptive for many longer-lived organisms, social learning will often be found in those dependent on the populations of other species, especially if they are marine. This provides a potential explanation for the evolution of a prevalence of social learning, and culture, in humans and cetaceans.
We used this individual-based model to show that, in environmental conditions dominated by red noise, extirpation may be an outcome of the evolution of cultural capacity. In red noise environments individual learning may be selected from the population. If the social learning system comes to lack sufficient individual learning or cognitively costly adaptive biases, behavior ceases tracking environmental variation. Then, when the environment does change, fitness declines and the population may collapse or even be extirpated. The modeled scenario broadly fits some human population collapses and might also explain nonhuman extirpations. Varying model parameters showed that the fixation of social learning is less likely when individual learning is less costly, when the environment is less red or more variable, with larger population sizes, and when learning is not conformist or is from parents rather than from the general population. Once social learning is fixed, extirpation is likely except when social learning is biased towards successful models. Thus, the risk of population collapse may be reduced by promoting individual learning and innovation over cultural conformity, or by preferential selection of relatively fit individuals as models for social learning.
Slides and References:
Download a PDF version of the slides for this talk.
Download Whitehead and Richerson, The evolution of conformist social learning can cause population collapse in realistically variable environments, Evolution and Human Behavior 30 (2009) 261-273.
About the speakers:
Contact Information:
Hal Whitehead
Department of Biology
Dalhousie University
Halifax, Nova Scotia, Canada
902-494-3723
902-494-3736
hwhitehe@dal.ca