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.
Highlights
Agent-based modelling methodologies offer a number of advantages when it comes to socio-ecological systems research
We describe an empirically informed agent-based model (ABM) of a rural Nepalese village
Particular strengths of the ABM include: (a) the fact that it runs at daily timesteps, enabling socio-ecological dynamics to be studied at high temporal resolution; (b) the multiple scales at which processes can be observed – individual, household, and village; (c) its empirically informed nature; and (d) its unusually detailed depiction of demographic processes, livelihoods, and villager finances
Summary
Nicholas Roxburgh a, Andrew Evans b, Raj K. Agent-based modelling methodologies offer a number of advantages when it comes to socio-ecological systems research. 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. 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. Method name: Nepal Stressor Interaction Model (Nepal SIM) Keywords: Simulation, Agriculture, Livestock, Socio-ecological system, Stressors, Shocks, Earthquakes, Multi-scale, Population synthesis, Nepal Article history: Received 3 December 2020; Accepted 14 February 2021; Available online 31 March 2021. Subject Area: More specific subject area: Method name: Name and reference of original method: Resource availability:
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