The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

NilsDroste

Nils Droste

Associate professor

NilsDroste

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

Author

  • Hanna Ekström
  • Nils Droste
  • Mark Brady

Summary, in English

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.

Department/s

  • Department of Political Science
  • Lund University
  • Department of Economics
  • AgriFood Economics Centre, SLU

Publishing year

2024-04

Language

English

Publication/Series

Environmental Modelling and Software

Volume

175

Document type

Journal article review

Publisher

Elsevier

Topic

  • Ecology
  • Forest Science

Keywords

  • ABM
  • Complex adaptive system
  • Forest management
  • Model choice
  • SES

Status

Published

ISBN/ISSN/Other

  • ISSN: 1364-8152