Thursday, August 7, 2008 - 10:15 AM

SYMP 16-7: Food-dependent demography: Dynamically linking environment and population

Charlotte T. Lee and Shripad Tuljapurkar. Stanford University

Background/Question/Methods

A crucial step in understanding the reciprocal dynamics of humans and ecosystems is to forge quantitative links between human population and the physical and biotic environment. Past efforts to do so typically involve estimating potential agricultural production, and from it a “carrying capacity.” While this approach is useful in focusing on food, a dynamic population theory must include the effect on food production of labor supply (which varies with population structure) and the feedback from available food to survival and reproduction (which determine future labor supply). We present a model for food-dependent human demography that explicitly includes this feedback. Hunger, its biological effects, and social responses to food shortage are key elements of this new approach.

Results/Conclusions

Focusing on expanding populations, where colonization of new areas or the adoption of agriculture has recently occurred or where we consider large spatial scales, we show that hunger reaches a steady-state value that depends on crop yield, demography, and age-specific labor. We then show how population growth rate depends on hunger. Our results extend the classic demographic relationship between stable growth rate and net reproductive rate to nonlinear food-dependent growth. Our model provides a natural framework to explore the additional important effects of biological and social factors such as climate, soil fertility, and cultivation technology. We discuss the potential for food-dependent demographic instability and its implications for populations experiencing temporary hardship. Finally, we briefly describe the dynamics of populations whose growth is eventually limited by the area of arable land. We close by coupling food-dependent demography directly with a model for agroecosystem dynamics in Kohala, Hawai'i.