Data_Sheet_1_Aligning Agent-Based Modeling With Multi-Objective Land-Use Allocation: Identification of Policy Gaps and Feasible Pathways to Biophysically Optimal Landscapes.pdf
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
It is increasingly recognized in science and policy that landscapes need to be managed for multifunctionality. Multi-objective land-use allocation and agent-based modeling are two potent tools to explore the potential of landscapes to provide multiple ecosystem services. However, in the case of the former, the real-world feasibility of the biophysically optimal land-use configurations remains unclear. Meanwhile, agent-based models are not well-suited to recognize the biophysical potential of landscapes to provide multiple ecosystem services. In this paper, we propose an approach to align multi-objective optimization with agent-based modeling in order to investigate the economic, institutional and social feasibility of biophysically optimal landscapes. It especially allows to contrast biophysically optimized land-use patterns with the option space circumscribed by relevant policy frameworks. We argue that a structured comparison of biophysical optimization with an exploration of the parameter space of an agent-based model can be used to identify the real-world feasibility and the barriers to reaching multifunctional landscapes. We demonstrate the applicability of our approach by using it on a virtual landscape, which allows us to detect the importance of various economic, institutional and behavioral factors that facilitate or hamper moving the social–ecological system toward its biophysical potential. Particularly, we demonstrate the essential role of tailored policy instruments. Our approach can be useful in informing land-use policy with respect to its effectiveness and efficiency in achieving multifunctional landscapes.
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