GTAP Resources: Resource Display
| GTAP Resource #6266 |
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"Land for Fish: Does plant-based fodder demand of aquaculture production affect agricultural markets?" by Heimann, Tobias and Ruth Delzeit Abstract Aquaculture fish production is a fast-growing food sector and increasingly relying on plant-based protein fodder to substitute fishmeal utilization. This study employs the global Computable General Equilibrium (CGE) Model DART to quantify the effects of plant-based fodder consumption by the aquaculture sector on agricultural markets and land-use. An important attribute of the model is the explicit modelling of oilseed oils and meals which are used in the livestock and aquaculture industry. This allows for a detailed characterisation of the fodder composition of aquaculture production. For this evaluation, we conduct a scenario analysis until 2030 simulating, first, the fish sector developments expected by FAO; second, a rebuilding of sustainable fish stocks; and third, a stronger expansion in aquaculture production with varying fishmeal supply in the third and fourth scenario. The results indicate direct effects of the expansion of aquaculture production, and the reduction of fishmeal in the fodder composition, on agricultural production and prices. However, reducing capture fisheries and fishmeal production to rebuild sustainable fish stocks, have lower effects on agricultural markets than a substantial annual growth of aquaculture production comparable to the first decade of this century. |
| Resource Details (Export Citation) | GTAP Keywords | ||||||||||||||||
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- Dynamic modeling - Land use - Food prices and food security - The GTAP Data Base and extensions |
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If you have trouble accessing any of the attachments below due to disability, please contact the authors listed above.
Public Access  Paper (1.3 MB) Replicated: 0 time(s) Presentation (3.1 MB) Replicated: 0 time(s)Restricted Access No documents have been attached. Special Instructions No instructions have been specified. |
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Last Modified: 9/15/2023 1:05:45 PM
