Improving the performance of tilapia farming under climate variation: perspective from bioeconomic modelling
2018
Cai, J. | Leung, P.S. | Luo Yongju | Yuan Xinhua | Yuan Yongming
Tilapia is the world’s most popular aquaculture species, farmed mostly in earthen ponds. Experience in China, the largest tilapia farming country, is used to develop and calibrate a bioeconomic model of intensive tilapia pond culture. The model is used to simulate the impacts of climate, technical and/or economic factors on farming performance and examines the performance of various farming arrangements under different conditions. The simulation results indicate that: (i) an increase in feed price, an increase in mortality, or a decrease in fish price significantly reduces profitability, whereas an increase in the cost of seed, labour, rent, electricity or water management has smaller impacts on profitability; (ii) considering the impact of water temperature on fish growth, the profitability of a production cycle starting at the optimum timing may be twice as high as one starting at the worst possible time; (iii) farming arrangements that maximize the profit of individual fish crops may not maximize overall profitability because of path dependency of farming performance; (iv) optimal farming arrangements that maximize overall profitability can significantly improve economic performance; (v) given no price discrepancy against small-size fish, harvesting at about 300 g in two-year-five-crop arrangements could increase overall enterprise profitability by up to 50 percent compared with harvesting at > 500 g in one-year-two-crop arrangements; and (vi) a two-tier farming system that separates nursing and outgrowing ponds could allow one-year-three-crop arrangements that enhance profitability by up to nearly 90 percent compared with the one-year-two-crop arrangements. With more refined information on fish growth under different farming conditions, the model could become a decision-making tool to help farmers design optimal farming arrangements.
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