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ESTIMATING SUSTAINABILITY OF A SIMPLE HUMAN SOCIETY AND ITS ASSOCIATED ECOSYTEM USING RESILIENCE AND FISHER INFORMATION
Citation:
Mayer**, A, C. W. Pawlowski**, AND H C. Cabezas*. ESTIMATING SUSTAINABILITY OF A SIMPLE HUMAN SOCIETY AND ITS ASSOCIATED ECOSYTEM USING RESILIENCE AND FISHER INFORMATION. Presented at MODSIM2003 International Cogress on Modelling & Simulation, Queensland, AUSTRALIA, July 14, 2003.
Description:
Sustainability applies to integrated systems comprising humans and the rest of nature. To be considered sustainable, human components (society, economy, law, etc.) that interact with ecosystems cannot decrease the resilience of ecosystem structures and functions (trophic linkages, biodiversity, biogeochemical cycles, etc.) upon which the human components depend. A mathematical theory embodying these concepts would be immensely valuable in humanity's efforts to determine the effects of human activity on the resilience of the ecosystems. However, resilience of ecosystems can be very difficult to measure when only data collected in the field is available. We propose that indicators based on Information Theory can be used to develop measures that bridge the natural and human systems and make sense of the disparate state variables of the system. Fisher Information measures the variation of a dynamic steady state based on the probability density function it generates. We investigate the relationship between ecosystem resilience and Fisher Information using a simple, deterministic ecosystem model. This model is formed by a series of differential Lotka-Volterra equations, and includes 10 species arranged in 5 trophic levels, in addition to two resource pools, one of which is only accessible to two of the four plant species. The human society is modeled as one of the 10 species, and in proportion to its population size can increase the growth rate of three domesticated species, and decrease the mass transfer between other species. We create perturbations in the system to explore its resilience to these perturbations, and the relationship between resilience and Fisher Information. Since Fisher Information tracks the variation in a system, we hypothesize its use as an index of ecosystem resilience, and therefore sustainability