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Updated: Mar 17, 2026

Design and Use of an Apparatus for Quantifying Bivalve Suspension Feeding at Sea
Published on: September 5, 2018
Investigation of a novel approach for aquaculture site selection
Lynne Falconer1, Trevor C Telfer1, Lindsay G Ross1
1Institute of Aquaculture, University of Stirling, Stirling, FK9 4LA, United Kingdom.
Abstract:
This study investigated the potential use of two "species distribution models" (SDMs), Mahalanobis Typicality and Maxent, for aquaculture site selection. SDMs are used in ecological studies to predict the spatial distribution of species based on analysis of conditions at locations of known presence or absence. Here the input points are aquaculture sites, rather than species occurrence, thus the models evaluate the parameters at the sites and identify similar areas across the rest of the study area. This is a novel approach that avoids the need for data reclassification and weighting which can be a source of conflict and uncertainty within the commonly used multi-criteria evaluation (MCE) technique. Using pangasius culture in the Mekong Delta, Vietnam, as a case study, Mahalanobis Typicality and Maxent SDMs were evaluated against two models developed using the MCE approach. Mahalanobis Typicality and Maxent assess suitability based on similarity to existing farms, while the MCE approach assesses suitability using optimal values for culture. Mahalanobis Typicality considers the variables to have equal importance whereas Maxent analyses the variables to determine those which influence the distribution of the input data. All of the models indicate there are suitable areas for culture along the two main channels of the Mekong River which are currently used to farm pangasius and also inland in the north and east of the study area. The results show the Mahalanobis Typicality model had more high scoring areas and greater overall similarity than Maxent to the MCE outputs, suggesting, for this case study, it was the most appropriate SDM for aquaculture site selection. With suitable input data, a combined SDM and MCE model would overcome limitations of the individual approaches, allowing more robust planning and management decisions for aquaculture, other stakeholders and the environment.
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