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Heavy tailed frequency vs. size statistics describe forest fires across broad biophysical gradients, but what, if anything, do they reveal about the fundamental mechanisms which lead to complexity in terrestrial ecosystems? Earth scientists have focused on temporal variations in fire statistics as a means for probing the impact of human intervention and fire suppression on natural landscapes, and the cycles of perturbation and renewal in disturbance ecology. At the same time, abstract forest fire models have arisen as paradigms for two competing frameworks for complex systems. These are self-organized criticality (SOC), which emphasizes fuel connectivity in random configurations at a critical density, and highly optimized tolerance (HOT), which emphasizes specialized high-density configurations which are tuned for robustness in an uncertain environment. We are using observed statistics and fire scar shapes to (1) draw fundamental distinctions between the SOC and HOT mechanisms for complexity, and (2) evaluate the long term effects of extreme weather and suppression in a high-fidelity, predictive forest fire simulation environment HFire. Observations and the HFire simulations are both in striking agreement with an abstract model based on HOT, which suggests that identifying robustness tradeoffs which underlie resilience in different fire regimes may be key to understanding the long term evolution of forest ecosystems, and evaluating sensitivities to climate change and forest management strategies.
This work is a collaboration with Max Moritz @ Cal Poly San Luis Obispo.