Socio-economic differences between hunter-gatherers living in forest camps and a town camp.

<p><i>(a)</i> mean and 95% CI of the amount of bride price that men paid, <i>(b)</i> the frequency of wage labour in each location.</p

Future Discounting in Congo Basin Hunter-Gatherers Declines with Socio-Economic Transitions

<div><p>Humans have a tendency to discount the future; that is we value small, short-term rewards over larger, long-term rewards. The degree of future discounting, however, changes in response to socio-ecological factors. Here, we study Mbendjele BaYaka hunter-gatherers of northern Congo and their farmer neighbours to investigate adaptations in inter-temporal preferences in humans. We argue that in immediate-return systems, where food storage is absent and egalitarianism is enforced through levelling mechanisms, future discounting is an adaptive strategy to prevent wealth accumulation and the emergence of hierarchies. This ensures food sharing and allows for survival in unpredictable environments where there is risk of an energy shortfall. On the other hand, when food storage is made possible by the emergence of agriculture or as seen in some delayed-return hunter-gatherer populations, wealth accumulation, hierarchies and lower discount rates become the adaptive strategy. Therefore, individuals in immediate-return, egalitarian societies will discount the future more than those in non-egalitarian, delayed-return societies. Consistent with the predictions we found that market integration and socio-economic transitions decrease the future discounting in Mbendjele hunter-gatherers. Our measures of socio-economic differences marked this transition in hunter-gatherers living in a logging town. The degree of future-discounting was the same between more market-integrated hunter-gatherers and their farmer neighbours.</p></div

Proportion of participants that chose to receive one cube today in 3 Mbendjele camps and one Bantu farmer village.

<p>Camp 1 and camp 2 were located in the forest; camp 3 was located in the town. Error bars indicate 95% confidence intervals.</p

Lifecycle model of human groups.

<p>SCG refers to single-celled groups (a representation of small-scale, unstructured human groups); MCG refers to multicellular groups (a representation of large-scale, structured human groups). Red SCGs (SCGs on low-productivity patches) are shown as red circles with white filling, while blue SCGs (SCGs on high-productivity patches) are shown as blue circles with white filling. SCGs proliferate either by budding or going to war with the adjacent groups. Transition from SCGs to a MCG occurs when a number of (default value = 4) adjacent blue SCGs reach to a certain percentage (default value = 90%) of their carrying capacities and fuse. A MCG expands via growing or going to a war with adjacent groups.</p

Decrease in the number of MCGs after <i>t</i> = 1000 in our simulation with the default condition that lasted 1660 years.

<p>From <i>t</i> = 1000 to around <i>t</i> = 1300 MCGs fluctuate around the same numbers, however during the last 330 simulation years the number of MCGs decreases exponentially until only one MCG dominates the whole landscape.</p

Effect of patch aggregation on the number of cells and on the number of MCGs formed over 600 years.

<p>Significantly more MCGs are formed when the patches are aggregated. Plots on the left: change in the numbers of cells belonging to MCGs (black line), red SCGs (red line) and blue SCGs (blue line) over 600 years. Lines correspond to the mean numbers in 15 replicates and vertical bars mark standard deviations for corresponding years. Plots on the right: number of MCGs formed during 5 replicates of an experiment. a) LP and HP patches are randomly distributed (default condition). b) At least 49 HP patches are aggregated. c) At least 81 HP patches are aggregated. Other conditions are the same as the default condition.</p

Change in the number of cells belonging to MCGs (black line), red SCGs (red line) and blue SCGs (blue line) over 600 years in 9 replicates of a numerical experiment with high LP/ HP patch ratio.

<p>The initial conditions are the same as the default condition, except for the LP/HP patch ratio = 3:1.</p

Model flow chart.

<p>See main text and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0138496#pone.0138496.s001" target="_blank">S1 Information</a> for detailed description.</p

Effect of threshold for birth of MCGs (i.e. fusion of blue SCGs) on the number of cells and on the number of MCGs formed over 600 years.

<p>When the threshold is lowered, MCGs start to form earlier and reach to higher numbers. Plots on the left: change in the numbers of cells belonging to MCGs (black line), red SCGs (red line) and blue SCGs (blue line) over 600 years. Lines correspond to the mean numbers in 15 replicates and vertical bars are standard deviations for corresponding years. Plots on the right: number of MCGs formed during 5 replicates of an experiment. a) Threshold for fusion = 4 (default condition). b) Threshold for fusion = 3. c) Threshold for fusion = 2. All other conditions are the same as the baseline conditions.</p

Effect of constant for cost functions and growth rate on the number of cells and on the number of MCGs formed over 600 years.

<p>Plots on the left: change in the numbers of cells belonging to MCGs (black line), red SCGs (red line) and blue SCGs (blue line) over 600 years. Lines correspond to the mean numbers in 15 replicates and vertical bars mark standard deviations for corresponding years. Plots on the right: number of MCGs formed during 5 replicates of an experiment. a) Growth rate on LP patches = 0.01, on HP patches = 0.03, constant (<i>c</i>) = 0.001 (default condition). b) Growth rate on LP patches = 0.01, on HP patches = 0.03, constant (<i>c</i>) = 0.1. c) Growth rate on LP patches = 0.005, growth rate on HP patches = 0.01, constant (<i>c</i>) = 0.001. All other initial conditions are the same as the default conditions.</p