From actors to agents in socio-ecological systems models

Area of Science:

• Socio-ecological systems modeling
• Environmental social science
• Computational social science

Background:

• The ecosystem service concept highlights human roles in socio-ecological systems (SESs).
• Existing SES models often lack detailed representation of human behavior and decision-making.
• Agent-based modeling (ABM) offers a promising approach to address this gap.

Purpose of the Study:

• To review and discuss alternative methods for representing human behavior in SES models using ABM.
• To explore empirical grounding of ABM through social surveys.
• To propose advancements for scaling ABM in SES research.

Main Methods:

• Literature review of ABM applications in SES.
• Conceptual development of 'human functional types' analogous to plant functional types.
• Discussion on integrating institutional agents and human-environment coupling.

Main Results:

• ABM provides a flexible framework for modeling human behavior and decision-making in SESs.
• Empirical grounding via social surveys enhances ABM realism.
• The concept of human functional types facilitates scaling ABM to larger geographical areas.

Conclusions:

• Advancing ABM requires generalizing beyond case studies and incorporating human functional types.
• Representing institutional agents is crucial for understanding governance and policy feedbacks.
• Improved coupling of human-environment systems will enhance the application of the ecosystem service concept.