Article
Details
Citation
Silverthorn M, Yakubu SO & Falconer L (2025) Checklist and reporting framework to support documentation and communication of GIS-based Multi-Criteria Evaluation (MCE) models for aquaculture site selection. PLOS Sustainability and Transformation, 4 (1). https://doi.org/10.1371/journal.pstr.0000155
Abstract
Geographic Information Systems (GIS) are frequently used when conducting site suitability and site selection studies for aquaculture because the factors influencing the suitability of an area typically contain a spatial element. Multi-criteria evaluation (MCE), often based on the Weighted Linear Combination (WLC) method, is commonly used in aquaculture as it allows the combination of numerous and often conflicting interdisciplinary criteria and the evaluation of the trade-offs between them. GIS-based MCE models can be implemented in different ways according to the modelling objectives, but a lack of transparency and unclear information on characteristics of the model and output(s) can affect their use in real-world decisions. This study analysed 71 scientific articles that developed and used GIS-based MCE for aquaculture site selection and site suitability modelling. The articles were identified using the PRISMA systematic review protocol and covered a wide range of locations, species, and production systems. Data on the reported model characteristics were extracted from the scientific articles and analysed to identify trends, similarities, and differences in the information provided within the studies. The analysis revealed inconsistencies in how models were described, with some articles missing important information that could limit their use for many aquaculture planning decisions. Based on these findings, a checklist and reporting framework were produced that can be used to ensure important information is easily accessible alongside GIS-based MCE models and their outputs. The checklist and reporting framework can act as a template to provide clear and consistent documentation that will facilitate the use of models and outputs by end users who may not have been involved in the modelling process and are unfamiliar with the technical aspects.
Status | Published |
---|---|
Funders | MRC Medical Research Council |
Publication date | 31/01/2025 |
Date accepted by journal | 05/12/2024 |
URL | http://hdl.handle.net/1893/36620 |
Publisher | Public Library of Science |
Publisher URL | https://doi.org/10.1371/journal.pstr.0000155 |
ISSN | 2767-3197 |
eISSN | 2767-3197 |
People (2)
Research Fellow, Institute of Aquaculture
Post Doctoral Research Fellow, Institute of Aquaculture