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Ecological and Social Models

More than a decade of working with integrating models has given us the impression that ecosystem models are more advanced than social system models for understanding the system, though there have been decades of social research into economic behavior, evolutionary behavior and market behavior (e.g., Cangelosi and Parisi 2001; Camerer et al. 2003). Four reasons for this occur to us, although these reasons are inter-related. First, despite the great distance between ecological theory and physics, ecosystems as subjects of natural science include more components that can be modeled through processes rather than using the rule-based approach most often adopted in societal models. An example we use in teaching comes to mind – image tossing 100 chickens into the air along some compass bearing, and mapping their landing places. If those chickens were dressed and frozen, one could predict their landing places quite accurately. But if those same chickens were alive, prediction would be all but impossible. Instead we must be content with describing a mean landing place and some deviation around that. Adding the freewill of the animal makes all the difference. Nobel laureate Richard Feynman put it more succinctly when he said “Imagine how much harder physics would be if electrons had feelings!” In short, societal models are replete with behaviors influenced by the free will of agents. This leaves models of social dynamics more likely to include a rule-based approach.

Second, ecosystems are more self-similar than human communities. Technically, the spatial autocorrelation in ecosystems is higher than in human neighborhoods. Imagine two forest patches separated by perhaps 10 km. What we know about the first patch is likely to apply, to some large degree, to the second patch. Now image a neighborhood of a few city blocks. What we may know about one family is likely not applicable to a family a few blocks away. Indeed, families living as neighbors may be quite distinct from each other. Our third point is closely related to our second. Ecologists are more comfortable than anthropologists at treating their subjects as similar units. Ecologists consider a herd of animals and emphasize the similarities. Anthropologists consider a group of people and see variability. The variability that is inherent within human populations has implications for power, poverty, inequality, development and ultimately sustainability of the social-ecological system. This is not to say that generalizations are not sought after; they are, but differences have real implications for people and the environment.

The fourth reason that comes to mind may be an outcome of the reasons already cited. There has been a greater embrace of simulation modeling in ecosystem science than in social sciences, and for a much longer time. By the 1980s, manuscripts were published that summarized the strides made in simulation modeling in ecology (e.g., Huston et al. 1988), whereas international meetings on social simulation only began this century, and the community pursuing social simulation is much smaller.

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