Navigating simplicity and complexity of social-ecological systems through a dialog between dynamical systems and agent-based models
CoRR(2024)
摘要
Social-ecological systems (SES) research aims to understand the nature of
social-ecological phenomena, to find effective ways to foster or manage
conditions under which desirable phenomena, such as sustainable resource use,
occur or to change conditions or reduce the negative consequences of
undesirable phenomena, such as poverty traps. Challenges such as these are
often addressed using dynamical systems models (DSM) or agent-based models
(ABM). Both modeling approaches have strengths and weaknesses. DSM are praised
for their analytical tractability and efficient exploration of asymptotic
dynamics and bifurcation, which are enabled by reduced number and heterogeneity
of system components. ABM allows representing heterogeneity, agency, learning
and interactions of diverse agents within SES, but this also comes at a price
such as inefficiency to explore asymptotic dynamics or bifurcations. In this
paper we combine DSM and ABM to leverage strengths of each modeling technique
and gain deeper insights into dynamics of a system. We start with an ABM and
research questions that the ABM was not able to answer. Using results of the
ABM analysis as inputs for DSM, we create a DSM. Stability and bifurcation
analysis of the DSM gives partial answers to the research questions and direct
attention to where additional details are needed. This informs further ABM
analysis, prevents burdening the ABM with less important details and reveals
new insights about system dynamics. The iterative process and dialogue between
the ABM and DSM leads to more complete answers to research questions and
surpasses insights provided by each of the models separately. We illustrate the
procedure with the example of the emergence of poverty traps in an agricultural
system with endogenously driven innovation.
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