Recent advances in the power of statistical and computational tools has permitted the growth of complex, highly parameterized, population ecological models, which offer the hope of dramatically increased scope and realism in modeling the relationship between population dynamics, demographic conditions and ecological conditions, crop production, social change, and cultural trait/institutional evolution. Such models greatly expand our inferential power beyond the early explanatory frameworks developed by Malthus , Verhulst  , Lotka , Volterra , and Boserup and Kaldor , which are now widely recognized to be constructed from too few parameters to adequately model complex system dynamics. The downside of these new population ecological models, however, lies in the fact that the numerical values utilized in their parameterizations have thus far been specified essentially ad hoc, and may be potentially unrepresentative of the empirical data in the early agrarian contexts they hope describe. In this paper, we advance the literature on coupled human-natural systems by providing a highly detailed statistical analysis of ecological conditions, crop production, and population dynamics in a pre-industrial agrarian population, in order to produce empirically derived estimates of the key parameters utilized in contemporary population ecological modeling, and thus better structure and constrain the scope of such models. Our results will have implications for models concerning the origins of agriculture and evolution of agrarian risk management institutions, models concerning the effect of extrinsic ecological conditions and population levels on crop yields, and population ecological models of social change and population collapse.
Paper coming soon.