- Title
- Agent-based model development of a complex socio-ecological system: Methods for overcoming data and domain limitations
- Creator
- James, C. L
- Creator
- Bradshaw, Karen L
- Subject
- To be catalogued
- Date Issued
- 2023
- Date
- 2023
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/440189
- Identifier
- vital:73755
- Identifier
- xlink:href="https://doi.org/10.1016/j.ecoinf.2023.102224"
- Description
- Agent-based models (ABMs) are appropriate tools for modelling socio-ecological systems due to their ability to handle complexity. However, development of such models is often an intensive process. There are many tutorials on the general methods and steps in ABM development but there are not necessarily practical details on how to overcome certain challenges. Honeybush (Cyclopia spp.), a kind of fynbos vegetation found in the Western and Eastern Cape mountains, is an important ecological and agricultural product in South Africa. It is considered a complex system due to its variability and unpredictability. The honeybush tea industry faces the challenge of meeting emerging market demands while maintaining sustainable harvesting practices, in the midst of an uncertain future due to climate change. We created a prototype model, HoneybushModel, using the MARS framework, a C# multi-agent simulation toolkit. The model was validated using historic data. Whilst outlining the development processes used to create the Honeybush Model, this paper provides a methodology for the development of such models and demonstrates techniques for addressing data, domain and framework limitations. The implemented model also acts as a case study for similar systems that could be modelled using an ABM.
- Format
- computer
- Format
- online resource
- Format
- application/pdf
- Format
- 1 online resource (10 pages)
- Format
- Publisher
- Elsevier
- Language
- English
- Relation
- Ecological Informatics
- Relation
- James, C.L. and Bradshaw, K.L., 2023. Agent-based model development of a complex socio-ecological system: Methods for overcoming data and domain limitations. Ecological Informatics, 77, p.102224
- Relation
- Ecological Informatics volume 77 p. 102224 2023 1878-0512
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of the Creative Commons CC BY-NC-ND 4.0 License (Attribution-NonCommercial-NoDerivatives 4.0 International) https://creativecommons.org/licenses/by-nc-nd/4.0/
- Rights
- Open Access
- Hits: 121
- Visitors: 119
- Downloads: 5
Collections
RU Department of Computer Science
Bradshaw, Karen Lee (Assoc Prof)
SDG 09. Industry, Innovation and Infrastructure
SDG 15. Life On Land
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