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MODELING AGROECOSYSTEMS AS COMPLEX, ADAPTIVE SYSTEMS

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:   No Citation available.
Authors:   N K Newlands
Keywords:   Adaptive, complex, ecosystem

Current challenges in modeling ecosystem structure and function based on multi-disciplinary concepts drawn from the study of complex adaptive systems are presented. To test alternate hypotheses related to these goals, different models are required and they can be differentiated by several main attributes: degree of determinism, degree of complexity, degree of discreteness versus continuity, degree of data-intensity versus sparseness and degree of linearity versus nonlinearity. Different approaches to representing and modeling ecosystems are showcased in three applications of research in progress: 1) Modeling greenhouse gas emissions to estimate potential bio-energy reductions and associated impacts on soil carbon and nitrogen, 2) spatially-explicit simulation of an agro-ecosystem model based on a high-resolution (daily, 10km) agro-climate grid for Canada, and 3) stochastic modeling to predict rates of de-nitrification and nitrous oxide production in freshwater and terrestrial ecosystems.

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