Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 541492
Title Agent-based modelling of socio-ecological systems : Models, projects and ontologies
Author(s) Gotts, Nicholas M.; Voorn, George A.K. van; Polhill, J.G.; Jong, Eline de; Edmonds, Bruce; Hofstede, Gert Jan; Meyer, Ruth
Source Ecological Complexity (2018). - ISSN 1476-945X - 15 p.
DOI https://doi.org/10.1016/j.ecocom.2018.07.007
Department(s) PE&RC
Biometris (PPO/PRI)
Information Technology
WASS
Publication type Refereed Article in a scientific journal
Publication year 2018
Keyword(s) Agent-based model - Complexity - Ontology - Socio-ecological system
Abstract

Socio-Ecological Systems (SESs) are the systems in which our everyday lives are embedded, so understanding them is important. The complex properties of such systems make modelling an indispensable tool for their description and analysis. Human actors play a pivotal role in SESs, but their interactions with each other and their environment are often underrepresented in SES modelling. We argue that more attention should be given to social aspects in models of SESs, but this entails additional kinds of complexity. Modelling choices need to be as transparent as possible, and to be based on analysis of the purposes and limitations of modelling. We recommend thinking in terms of modelling projects rather than single models. Such a project may involve multiple models adopting different modelling methods. We argue that agent-based models (ABMs) are an essential tool in an SES modelling project, but their expressivity, which is their major advantage, also produces problems with model transparency and validation. We propose the use of formal ontologies to make the structure and meaning of models as explicit as possible, facilitating model design, implementation, assessment, comparison and extension.

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