Aquaculture industry is considered by financial institutions as high risk due to failures caused by epizootics, natural disasters, and poor planning and monitoring. Bioeconomic modeling should be used in aquaculture to plan, monitor and determine cost effectiveness and risk to reduce uncertainty and increase profits from ongoing or new projects. A review of bioeconomic modeling in tilapia aquaculture is presented here.
Bioeconomic models are mathematical tools that make it possible to estimate the success of a production project, or to evaluate projects to produce organisms in progress, in order to optimize their production and increase their profitability. These facilitate the representation of the production process, considering biological, environmental and economic factors, and allow the simulation of different production scenarios and then the application of different optimization methodologies.
In addition, they allow for quantifying the production process and weighing the importance of the various components that intervene, directly and indirectly, in each of the links of the chain of production, distribution and marketing. They answer questions related to economic feasibility, use of time and movements, optimization of resources and operational areas.
The Food and Agriculture Organization of the United Nations estimates that aquaculture will produce more than 50% of fish production for human consumption in 2030.
Specifically, the growth of tilapia production in the decade 2010–2020 was higher (43%) than the growth of world aquaculture (34%), respectively, indicating that tilapia aquaculture is increasing at a faster rate than other species.
Despite this progress, financial institutions consider aquaculture a high risk economic activity. For example, in salmon, the infectious salmon anemia virus appeared in the region of Los Lagos in Chile in August 2007, and in tilapia, the TiLV virus, the etiological agent of the lake tilapia disease, was discovered in Israel in 2014.
Additionally, there are environmental variables, such as hurricanes, floods and periods with atypical temperatures, that have seriously affected some projects. For this reason, effective tools, such as bioeconomy models, are required to increase the certainty of projects.
In this work, a meta-analysis of the literature on bioeconomic modeling in aquaculture, covering a period of 26 years (1994–2020) is presented to know the actual status of bioeconomic modeling in aquaculture, particularly in tilapia, published in scientific journals worldwide.
Materials and Methods
The data for the study was obtained by searching published scientific content using several search engines. Once the results of each engine were obtained, the articles that included keywords in the title, such as analysis, bioeconomic modeling, bioeconomy, tilapia, aquaculture or a mixture of these, were selected.
The selected articles were then classified into dimensions. The models of those papers dealing with the tilapia bioeconomy were reviewed in detail to know the approaches followed by the authors and to identify potential aspects for their improvement.
A total of 68 articles were selected out of 260 found in the search, containing bioeconomic modeling in aquaculture. These were selected if a mathematical model was developed or employed that considers biological, environmental and economic elements.
These articles were written in 19 different countries or regions (Figure 1), with Mexico being the country with the highest number of published articles (20). Shrimps were the group of species with more articles (15), followed by tilapia (12), sea bream (11), salmon and carp with 3 articles each, and the rest of the species with two or one publication.
The characteristics of the 12 bioeconomic models published on tilapia were presented in the study: 11 of them were theoretical models adjusted with data obtained from commercial farms, while one of them presents an empirical model developed through data obtained through previous experiments.
“These models deal with four tilapia species and were classified in the categories of (a) management and (b) economic viability, depending on the objective for which they were used.”
Management papers (9) dealt with optimization of harvest times, optimal feed rations, diet evaluation, effects of size heterogeneity, and the integration of aquaculture with aquaponic tomato production. The remaining three articles on economic viability seek to determine, through simulations, the economic viability of tilapia growing out in semi-intensive systems.
They evaluate the economic impact of tilapia production in monocultures and polycultures, as well as the impact of replacing standard feeds with plant ingredients. All tilapia bioeconomic models share a common structure composed of biological, management and economic sub-models (Table 1).
The biological sub-model aims for the estimation of the growth, either in weight or in size of the organisms according to the environmental conditions provided by the production system.
The most commonly used equations to quantify growth in weight (Equations 1–3) and size (Equation 4) along a period, using initial weight, asymptotic weight of the organism, anabolism, catabolism and temperature as input parameters are presented in the Figure 2.
The management sub-model aims for the evaluation of the production process over time, to estimate total biomass and weight dispersion, survival rate, feeding rate and the expected food conversion factor, at a given the projected food ration, total ammoniacal nitrogen concentration, culture density in a number of individuals and biomass density.
Finally, with regard to the economic sub-models, all the authors seek to determine the economic viability of the project, starting by quantifying total costs from fixed costs to variable costs, gross income and net profits.
These economic parameters allow for calculating cash flows and profitability through parameters such as the net present value (NPV), internal rate of return (IRR), and cost-benefit during the life of the project.
In all cases, the three sub-models worked independently but received input information from the others to be processed with mathematical models, to finally generate output information that feeds the next submodel.
Discussion and conclusions
In this work, it has been pointed out that at a global level, there is a sustained trend towards an increase in the production of aquatic resources, and that this trend is supported only in aquaculture since fisheries have reached their maximum sustainable level.
However, the main problem facing aquaculture is that being an economic activity, profit margins are frequently narrow and sometimes nil (Saha et al., 2022). This is possibly due to poor planning, control and monitoring of production and the occurrence of external factors that are difficult to control but are feasible to measure, analyze and learn from them.
“Like protected agriculture, it would be ideal for aquaculture to evolve towards the modernization of production systems to produce more and in less volume, with fewer risks, and with control of variables, such as water temperature, which greatly influences the growth and survival of organisms and disease control.”
However, much of the world’s aquaculture is carried out in a rustic way, without control of environmental variables and with little knowledge of production costs (Saha et al., 2022).
The 68 articles found are of high quality since they were published in prestigious specialized journals, which can be found with the criteria described in this work in the four search engines used. However, if the time of the analysis (26 years) is taken into account, the scientific productivity in this field was low (2.6 articles/ year) in relation to the growth of world aquaculture.
“Possibly, this is due to a low diffusion of the advantages of having bioeconomic models and the complexity with which scientists present their models to users, generally in the form of scientific articles that are difficult for producers and planners or financial institutions to understand and apply.”
The relationship between the degree of the use of bioeconomic models and the lack of knowledge among industry professionals to work with mathematical and optimization models, the need for the development of models to be accompanied by the development of decision-making support systems, or the creation of interfaces that make it possible for the user to take advantage of these developments, are crucial aspects of understanding the current situation and the main future challenges.
A large number of endogenous and exogenous factors lead to farmers needing decision support systems for operational issues, such as seeding and harvesting dates, or strategic issues, such as site selection. Simulations and optimizations would help farmers reduce uncertainty.
The analysis of all sub-models (the biological, the management or production, and the economic) made is it possible to create a conceptual diagram of the bioeconomic model for tilapia (Figure 3), based on the System Dynamics Theory, in which all independent sub-models interact with each other to produce profitability information.
This is the logic of the production process; that is, it first focuses on the development of organisms, including the effect of temperature that affects their growth, then the management that is given, and then the economic part that depends on biomass and the costs of the production.
However, all papers analyzed lacked a risk submodel (Figure 3) to parameterize and understand not only the behavior of the results under the conditions considered normal, but also to simulate what would happen within the uncertainty of the system.
Risk sub-models have been introduced in bioeconomic modeling of other species, such as shrimp making sensitivity analyses to see to what extent the project could collapse or reach the goals we set for ourselves, or by carrying out more complex analyses, such as the Monte Carlo simulation (Martinez and Seijo, 2001).
In conclusion, this work provides valuable information that shows that the aquaculture bioeconomy is advancing, but slowly, as a tool to support the development of the world aquaculture. Low-cost and easily accessible, user-friendly software, such as Excel, is required to apply the existing and future models, which could be improved with a risk sub-model to make sensitivity analyses.
This is a summarized version developed by the editorial team of Aquaculture Magazine based on the review article titled “BIOECONOMIC MODELLING IN TILAPIA AQUACULTURE: A REVIEW” developed by: Dorantes-de-la-O, J. – Centro de Investigaciones Biológicas del Noroeste, La Paz, México, Maeda-Martínez, A. – Centro de Investigaciones Biológicas del Noroeste S.C., Tepic, México, Espinosa-Chaurand, L. and Garza-Torres, R. – Centro de Investigaciones Biológicas del Noroeste S.C., Tepic, México and Consejo Nacional de Ciencia y Tecnología.
The original article, including tables and figures, was published on MARCH, 2023 through REVIEWS IN AQUACULTURE.
The full version can be accessed online through this link: DOI: 10.1111/raq.12817