Fig 1.
Age-structured learning strategies.
A and D are extreme strategies with heavy reliance on vertical transmission (panel A) or horizontal transmission (panel D). Panels B and C show data from Hewlett et al. (2011), which reflect differences in learning strategies employed by the Aka, a hunter-gatherer population (panel B) and the neighbouring Aka and Bofi agriculturalists (panel C). Age classes are numbered on the x-axis.
Fig 2.
The spread of a cultural trait changes based on learning life histories.
Frequency of T in a population where the trait arises at a frequency of 0.001 in all age classes Parameters were: b = 5, s1 = 0.5, s2 = s3 = s4 = 0.6, s5 = 0.2, wf = 1, ws = 0.05. Starting population size was 100 individuals and the simulation ran for 5000 time steps. Starting age structure was uniform with 20% of the population in each age class. Panels A, B, C, and D show results of the model for learning strategies corresponding to the strategies from Fig 1: A. Late horizontal or oblique learning, B. hunter-gatherer population, C. agriculturalist population, D. early horizontal or oblique learning.
Fig 3.
Differences in frequency after 5000 time steps between a trait with a fitness effect and a neutral trait for different learning strategies.
Panel A shows results for a trait that increases fertility and panel B shows those results for a trait that increases survival. Parameters are b = 4, s1 = 0.6, s2 = s3 = s4 = 0.7, s5 = 0.4. For panel A ws = 0 and for panel B wf = 0. Starting population size was 100 individuals and the simulation ran for 5000 time steps. Starting age structure was uniform with 20% of the population in each age class.
Fig 4.
Mean frequency of the cultural trait T in the population when T increases fertility.
In panel (A), T does not construct a learning niche (ϵ = 0) and in panel (B), it does construct a learning niche (ϵ = 1). Other parameters: wf = 1, vb = 0.6, ω = N = 5. Starting population size was 100 individuals and the simulation ran for 5000 time steps. Starting age structure was uniform with 20% of the population in each age class. Survival parameters as in Fig 3.
Fig 5.
Mean frequency of the cultural trait T in the population when T decreases fertility.
In panel (A), T does not construct a learning niche (ϵ = 0) and in panel (B), it does construct a learning niche (ϵ = 1). Other parameters: wf = −2, vb = 0.6, ω = N = 5. Starting population size was 100 individuals and the simulation ran for 5000 time steps. Starting age structure was uniform with 20% of the population in each age class. Survival parameters as in Fig 3.
Fig 6.
The effect of learning life history on population size.
The size of a population starting at 50 individuals after 2,500 model time steps for a predominantly vertically learning population (Panel A) and a predominantly horizontally learning population (Panel B). Here, b = 3, s1 = s2 = s3 = s4 = 0.6, s5 = 0.4, pv = ph = 0.6, wf = 1.7, and ws = 0. Starting age structure was uniform with 20% of the population in each age class.