Bioeconomic modelling in tilapia aquaculture: A review

The global production of aquatic resources is increasing at the rate of 3.3 million tons per year, main thanks to aquaculture. However, this industry is considered by financial institutions as high risk due to failures caused by epizootics, natural disasters and poor planning and monitoring. Bioeconomic modelling is a progressive branch of social science that seeks to integrate the disciplines of economics and biology to create theories that better explain economic events using a biological basis and vice versa. This should be used in aquaculture to plan, monitor, and determine cost-effectiveness and risk, to reduce uncertainty and increase profits of ongoing or new projects. A meta-analysis of the literature on bioeconomic modelling in aquaculture during 26 years (19942020) was performed, using four search engines. Sixty-eight articles were published in 23 journals, on 25 groups of species or species. The most studied were shrimp, tilapia, seabream, salmon and carp. From these, 12 articles dealt with tilapia models that shared similar biological, management and economic sub-models. In the 26-year analysis, the global scientific productivity in this field is low (2.6 articles/year) in relation to the growth of world aquaculture. Bioeconomic modelling peaked during the decade from 2004 to 2014 with 5.6 papers/year, but then declined to only 0.83 articles/year from 2015 to 2020. This is possibly due to the low diffusion among producers, planners and financial institutions of the advantages of the models and the difficulty to use them if friendly and readily available software is lacking.

Automated summary

The global production of aquatic resources is increasing thanks to aquaculture, but this industry is considered high risk due to failures caused by epizootics, natural disasters, and poor planning. Bioeconomic modeling, which integrates economics and biology, should be used in aquaculture to reduce uncertainty and increase profits. However, the scientific productivity in this field is low, possibly due to a lack of awareness and user-friendly software.