Aquaculture bioeconomics, what is that?

Have you ever wondered, am I harvesting at the best possible time? Should I produce through an intensive or extensive system in the region where I live? How much feed should I add to my tanks to optimize my production costs? Should I have multiple harvests or just one at the end of the cycle? Can my production be more sustainable? What is the risk associated to investing my money in an aquaculture farm? If so, you are in the right place. In this case we will introduce aquaculture bioeconomics, an emerging interdisciplinary science that can help us answer these and many other questions associated with the economic performance of our aquaculture company.

The management of an aquaculture business

Unlike other animal production industries, such as livestock, the aquaculture industry presents unique challenges for running a business. This is due to the effect of the interactions between the land, water, air; the great influence of the environment on the animals produced; the difficulty of manipulating the organisms; and the enormous variety of cultivated species of different groups, families and even phyla. In addition, there is an increase in complexity as a result of human intervention and decision-making such as intensity of production, the type of farming system, food handling; etc.

During the beginning of the blue revolution, the large profit margins obtained from cultivated species allowed the implementation of policies (both public and private) and the management of the business based on trial and error. However, increased competition, especially observed in species such as shrimp, has significantly reduced profit margins, making it necessary to increase knowledge, management, and control of production; so that it is possible to know the different effects that management decisions can cause without the need to risk production. At the same time, the need to optimize production processes is growing, to maximize profit margins previously punished.

What is bioeconomics?

To face the challenges presented by the industry and try to improve production control, producers began using interdisciplinary sciences that allow us to know the impacts on the economic performance of a company in a quantitative, rigorous and comparable way, taking into account the biology of cultured organisms, the engineering of facilities and the effects of environmental interactions. In aquaculture, the interdisciplinary science that takes all these aspects into account is known as bioeconomics.

The application of bioeconomics in the aquaculture scene is relatively recent, with the first works published during the 1970s, and it aims to analyze the effect of the interactions that exist between biological, environmental, economic and infrastructural systems.

To achieve its goal, bioeconomical sciences rely on systems theory, which’s premise is that it is possible to analyze a complex system by analyzing its components and the relationships that exist between them. Thus, it is possible to analyze aquaculture production from its different angles.

The main tool for bioeconomic analysis is modeling. A model is just a simplified representation of reality. Bioeconomic models do not seek to emulate the system exactly, but rather to find the key aspects that compose it, as well as their relationships, to understand the complexity of the system in the best possible way. The models can be of different types, with the mathematical models standing out mainly due to the multitude of possible management applications.

One of the main advantages of mathematical modeling is that they allow you to perform as many iterations as necessary, without investing large amounts of money (with high risk) in research and development through trial and error to improve production methods. In addition, it is this same capacity for iteration that, added to operations research techniques, makes it possible to find precise points for the optimization of production processes. This tool also allows you to make risk assessments, create benchmark points, and industry standards.

Finally, the inclusion of economic performance indicators expands the classically biological vision that has dominated most of the aquaculture landscape, this allows us to know if a production will be profitable and what are the critical points that must be improved.

Is bioeconomics only for big companies?

Despite being a sophisticated management system, bioeconomic analysis can be applied at any scale. The general steps to implement it are:

1.- Make the objective of the model clear: what do I want to achieve with the analysis? I may be looking for points that optimize the performance of my farm; or to identify the genetic line that maximizes the yield in my area; maybe I want to evaluate the viability of changing the production system or increasing my operating capacity, I may also want to know the risk at which incurred when applying for a loan, or the probability of incurring losses derived from the appearance of a disease.

2.- Evaluate the system: Each aquaculture farm has peculiarities. It is necessary to evaluate the infrastructure, the climate in the area, the physicochemical characteristics of the water, as well as to know the biology of the cultivated organisms. It is also necessary to know the market and its peculiarities, and finally, to establish and be clear about the relationships that exist between each of the components of the system.

3.- Model the system: Once known, it is necessary to proceed to the modeling of the system components and their interactions. The growth of organisms and their mortality can be modeled according to climatic characteristics and water quality as well as management decisions such as crop densities or the production model. The market aspects can be modelled as well, forecasting prices depending on supply and demand of the product, or evaluating the impacts on costs associated to changes in feed prices. One can also include environmental aspects to the model, looking for impacts of climate change or changes in water quality.

4.- Obtaining information: Once the system has been modeled, the information that will be used to parameterize the models must be obtained. That is, information from the farm that allows you to adjust the mathematical functions to the particularities of your production system. In this sense, stored data from previous productions are often used or, if necessary, a single pilot scale experiment can be carried out. Also, data for the region can be sometimes bought or obtained from research experiments deployed by local institutions. As mentioned in other articles published in this web, the term “information is power” is not trivial, the quality and quantity of the data used in further steps will determine the accuracy of the model.

5.- Model adjustment: Also known as parametrization. With the information and models ready, we proceed to obtain the parameters that best adjust the equations to the particularities of your farm. If the information is of good quality and sufficient, these parameters can be useful for a long time. There are several methods used to parametrize a model, most of them involve intricate statistics and mathematics. Luckily, there are several software packages that perform these calculations, reducing complexity and time consumed in the parametrization of each model.

6.- Validation and sensitivity: Once developed and adjusted, it is necessary to evaluate the robustness of the model, to know the limits in which it operates correctly and to know if it can predict the behavior of the system adequately. There is a series of statistical tools that allow this step, which is crucial to be able to trust the model developed, and just as mentioned in the step above, we can rely on software packages to perform the calculations, improving the amount of time dedicated to this step.

7.- Application of the model: Congratulations! You have developed your model properly, now you should only use it to meet its original objective, either using optimization software or simply through the economic analysis of the outputs, this model will allow you to better understand the behavior of your farm, allowing you to make better decisions.

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