An Agent-Based Model to Study LCLU Change on Colonist Farms in the Northern Ecuadorian Amazon
Stephen
J.
Walsh, University of North Carolina at Chapel Hill, swalsh@email.unc.edu
(Presenting)
Carlos
F.
Mena, University of San Francisco at Quito, cmena@usfq.edu.ec
Brian
G.
Frizzelle, University of North Carolina at Chapel Hill, brian_frizzelle@unc.edu
George
P.
Malanson, University of Iowa, george-malanson@uiowa.edu
Richard
E.
Bilsborrow, University of North Carolina at Chapel Hill, richard_bilsborrow@unc.edu
LCLU change associated with tropical deforestation is complex -- links and feedbacks between population and environment create dynamic trajectories with emergent properties. The tropical rainforest of the Northern Ecuadorian Amazon (NEA) is an area where complex interactions occur among a number of important and diverse stakeholders, in part, because of feedbacks between spatial patterns and rates of LCLU change on household farms seen as an emergent property at the advancing fronts of frontier development. These feedbacks in turn constrain future changes in LCLU and the interactions between people and environment.
We are motivated by questions that seek understanding in broad areas human-environment interactions and complex systems: How does a complex approach help explore the internal mechanisms and provide plausible explanations? How do results derived from applying complexity theory help in understanding decision-making across levels of social organization ranging from individual households to national governments? How do fundamental characteristics of complex dynamics of coupled natural-human systems and the limits of predictability pertain to sustainable development? How will complexity theory help us understand LCLU change in the frontier of human-environment interactions?
Using a spatial simulation modeling approach, we continue to draw upon a longitudinal survey of colonist farm households conducted in 1990 & 1999, a survey of colonist communities conducted in 2000, an ethnographic survey of indigenous households followed by an expanded survey of indigenous households and communities conducted in 2001, an assembled satellite time-series of LCLU change for 1973-2006, and GIS coverages of infrastructure, geographic access, and resource endowments of farms from which we have develop rules for our Agent Based Model (ABM) that incorporates the land use decision-making behavior of agricultural colonists, who are responsible for the greatest changes that have occurred in the NEA.
The ABM integrates the basic behavioral characteristics and activities of colonist households as the basic building block. The agents differ in important characteristics and behaviors and have dynamic interactions, in that the behavior of agents changes over time as the agents adapt to a changing environment, including changes in the characteristics and behavior of the other key stakeholders, learn from experience through feedbacks, or &ldquodie&rdquo as they fail to alter behavior relative to new conditions and/or factors. The dynamics that describe how the systems change are generally nonlinear, sometimes even chaotic, and seldom in any long-term equilibrium. Individual agents may organize themselves into groups or hierarchies that influence how the underlying system will evolve over time. Complex adaptive systems are self-organized systems that combine local processes to produce holistic systems. They are emergent and self-organizing in that macro-level behaviors emerge from the collective actions of individual agents, as agents learn through experience, change, and develop or alter feedbacks.
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