Pathways for scale and discipline reconciliation: current socio-ecological modelling methodologies to explore and reconstitute human prehistoric dynamics

International audienceThis communication elaborates a plea for the necessity of a specific modelling methodology which does not sacrifice two modelling principles: explanation Micro and correlation Macro. Three goals are assigned to modelling strategies: describe, understand and predict. One tendency in historical and spatial modelling is to develop models at a micro level in order to describe and by that way, understand the connection between local ecological contexts, acquired through local ecological data, and local social practices, acquired through archaeology. However, such a method faces difficulties for expanding its validity: It is validated by its adequacy with local data, but the prediction step is unreachable and quite nothing can be said for places out where. On the other hand, building models at a far larger scale, for instance at the continent and even the world level, enhances the connection between ecology and its temporal variability. Such connections are based on well-founded theories but lower the " small causes, big effects " emergence corresponding to agent-based approaches and the related inherent variability of socio-ecological dynamics that one can notice at a lower scale. We then propose a plea for combining both elements for building large-scale modelling tools, which aims are to describe and provide predictions on long-term past evolutions, that include the test of explaining socio-anthropological hypotheses, i.e. the emergence and the spread of local social innovations

O tempora O mores: Building an epistemological procedure for modelling the socio-anthropological factors of rural Neolithic socio-ecological systems: Stakes, choices, hypotheses and constraints

International audienceTrying to model a rural society, and even more so a past and disappeared rural society, is a dangerous task in the sense that we deal with the complexity of a whole society whatever the purpose of the model, to integrate and/or to simplify in a proper manner. This article deals with this complexity mainly by exploring the least risky way to apprehend it: starting from the question to be modeled, it is possible to gradually define the different scales, the set of variables to be considered, and therefore the disciplines to be included and mobilized. Then comes only the evaluation of the data quality criteria but also of their source. We are continuing with the scheduling of modules describing the environment itself, the resource use practices, and finally societal rules. Finally, we discuss the methodological, social, and professional constraints in involving people in the creation of such models