PP042-02
Dynamic Global Hunter-gatherer Model Reveals Key Role of Seasonality in Population Density via Diet Composition

Tuesday, 15 December 2020: 05:33
Virtual
Dan Zhu, Peking University, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Beijing, China, Eric Galbraith, Autonomous University of Barcelona, Cerdanyola del Vallès (Bellaterra), Spain; McGill University, Earth and Planetary Science, Montreal, Canada, Victoria Reyes-García, Autonomous University of Barcelona, Barcelona, Spain and Philippe Ciais, LSCE Laboratoire des Sciences du Climat et de l'Environnement, Gif-Sur-Yvette, France
Abstract:
The dependence of ancient hunter-gatherers on local Net Primary Production (NPP) to provide food played a major role in shaping long-term human population dynamics. Observations of contemporary hunter-gatherers have shown an overall correlation between population density and NPP, but with a thousand-fold variation in population density per unit NPP that remains unexplained. Here we build the first process-based hunter-gatherer model that is coupled to a realistic global terrestrial biosphere model. The model explicitly simulates human foraging activities (gathering and hunting) and the resultant carbon (energy) flows among vegetation, animals, and hunter-gatherers, the outcome of which determines human reproduction and mortality rates and thus population dynamics. Our results reveal a strong, previously unrecognized effect of growing season length, whereby hunter-gatherers are forced to consume high fractions of meat in the diet where growing seasons are short, which leads to as much as 100-fold decrease in human population density sustained by the same annual primary production as a result of trophic inefficiency. This emergent behavior of the process-based model is well supported by an analysis of ethnographic data of contemporary hunter-gatherers. Our new process-based approach has the potential to greatly improve the estimates of ancient human population densities and their dynamical responses to past environmental changes.