Theory strikes back: a modelling and simulation theory building approach on the origin of  agriculture

Abstract

The domestication of plants and the origin of agricultural societies has been the focus of much theoretical discussion on why, how, when, and where this change happened. The 'when' and 'where' have been substantially addressed by bioarchaeology, thanks to advances in methodology and the geographical and chronological scope of evidence. However, the 'why' and 'how' have lagged in explanatory power. Armed with the evidence now available, we can return to theory by revisiting the mechanisms allegedly involved, disentangling their connection to the diversity of trajectories, being those protracted or sudden, and identifying the weight and role of the social and ecological parameters involved. We present the Human-Plant Coevolution (HPC) model, which represent the dynamics of coevolution between a human and a plant population. The model consists of an ecological positive feedback system (mutualism), which can be reinforced by positive evolutionary feedback (coevolution). The model is the result of wiring together relatively simple simulation models of population ecology and evolution, through a computational implementation in R. The HPC model shows that the dynamics producing the neolithisation are diverse and involve multiple factors, as has been widely stressed elsewhere, such as pre-adaptation, environmental change, demographic growth, diversification and intensification of subsistence strategies, among others. However, being a formal model, it also brings clarity to how factors are entangled and what are their effects over the trajectory of both human and plant populations under different conditions. Through the systematic exploration of the parameters of the model, we were able to identify the main causes of agriculture and domestication while capturing other nuances such as the existence of asymmetric dynamics (agriculture without domestication, and vice versa), the increasing dependence between mutualistic populations and the causes of large fluctuations in timing of change.Peer reviewe