Modelling forests as social-ecological systems: A systematic comparison of agent-based approaches

• Published in: Environmental modelling & software : with environment data news Vol. 175; p. 105998
• Main Authors: Ekström, Hanna, Droste, Nils, Brady, Mark
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.04.2024
• Subjects: ABM; Agricultural Science, Forestry and Fisheries; Agricultural Sciences; Biologi; Biological Sciences; Complex adaptive system; Ecology; Economics; Ekologi; Forest management; Forest Science; Lantbruksvetenskap och veterinärmedicin; Lantbruksvetenskap, skogsbruk och fiske; Model choice; Nationalekonomi; Natural Sciences; Naturvetenskap; SES; Skogsvetenskap; Social Sciences Interdisciplinary; Tvärvetenskapliga studier; SES; Forest management; Model choice; Complex adaptive system; ABM
• ISSN: 1364-8152; 1873-6726; 1873-6726
• DOI: 10.1016/j.envsoft.2024.105998

The multifunctionality of forest systems calls for appropriately complex modelling approaches to capture social and ecosystem dynamics. Using a social-ecological systems framework, we review the functionality of 31 existing agent-based models applied to managed forests. Several applications include advanced cognitive and emotional decision-making, crucial for understanding complex sustainability challenges. However, far from all demonstrate representation of key elements in a social-ecological system like direct interactions, and dynamic representations of social and ecological processes. We conclude that agent-based approaches are adequately complex for simulating both social and ecological subsystems, but highlight three main avenues for further development: i) robust methodological standards for calibration and validation of agent-based approaches; ii) modelling of agent learning, adaptive governance and feedback loops; iii) coupling to ecological models such as dynamic vegetation models or species distribution models. We round-off by providing a set of questions to support social-ecological systems modelling choices. •We systematically compare the functionality of agent-based models of managed forests.•Most reviewed models are relatively specific in purpose.•Only few represent key elements to capture social-ecological complexity.•Thereby we provide a guide for informing model choices.