An empirically informed agent-based model of a Nepalese smallholder village

Roxburgh, N., Evans, A., GC, R. K., Malleson, N., Heppenstall, A. and Stringer, L. (2021) An empirically informed agent-based model of a Nepalese smallholder village. MethodsX, 8, 101276. (doi: 10.1016/j.mex.2021.101276) (PMID:34434796) (PMCID:PMC8374244)

Abstract

Agent-based modelling methodologies offer a number of advantages when it comes to socio-ecological systems research. In particular, they enable experiments to be conducted that are not practical or feasible to conduct in real world settings; they can capture heterogeneity in agent circumstances, knowledge, behaviour, and experiences; and they facilitate a multi-scale, causal understanding of system dynamics. However, developing detailed, empirically informed agent-based models is typically a time and resource intensive activity. Here, we describe a detail-rich, ethnographically informed agent-based model of a Nepalese smallholder village that was created for the purpose of studying the impact of multiple stressors on mountain communities. In doing so, we aim to make the model accessible to other researchers interested in simulating such communities and to provide inspiration for other socio-ecological system modellers. • The model is described using the ODD protocol. • The number of replicate runs required for experiments is discussed, and the model validation and sensitivity analysis processes that have been conducted are explained. • Suggestions are made for how the model can practically be used and for how model outputs can be analysed.

• Item Type: Articles
• Additional Information: This work was funded by the White Rose Social Sciences DTP (ES/J500215/1).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Heppenstall, Professor Alison
• Authors: Roxburgh, N., Evans, A., GC, R. K., Malleson, N., Heppenstall, A., and Stringer, L.
• College/School: College of Social Sciences > School of Social and Political Sciences > Urban Studies
• Journal Name: MethodsX
• Publisher: Elsevier
• ISSN: 2215-0161
• ISSN (Online): 2215-0161
• Published Online: 31 March 2021
• Copyright Holders: Copyright © 2021 The Author(s)
• First Published: First published in MethodsX 8:101276
• Publisher Policy: Reproduced under a creative commons licence