On the spatial scaling of a complex adaptive system

In this experiment, grass, evergreen oaks, and deciduous oaks with contrasting albedos compete for space. Our novel contribution to the cellular automata approach is the coupling of a land surface energy balance to a simple box model of the planetary boundary layer. Thus we have a “moist” Daisyworld with a surface temperature determined by energy partitioning, and a “dry” Daisyworld with a surface temperature determined by the global energy balance. The negative feedback effect of leaf and planetary boundary layers is balanced by a positive feedforward effect caused by an escalating temperature-dependent plant death rate.

Within the context of this thought experiment, we looked at the non-linear spatial scaling of the Penman-Monteith equation, and the scaling of the variance with spatial resolution (i.e. a crude spectrum). We also look at the effects on non-linearity of the number of neighbors, and the scaling of microscale effects to the macroscale. Results will be given at the conference.

Biocomplexity is best defined as the emergence of complex geometric behavior from disarmingly simple ecological rules. “Complex adaptive systems” (CAS) are defined by three essential properties: order is emergent as opposed to predetermined, the system's history is irreversible, and the system's future is often unpredictable. Examples of complex adaptive systems include ecologies and economies.