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An estimated two billion people worldwide currently suffer from micronutrient malnutrition, and almost one billion are calorie deficient. Providing adequate nutrition is a growing global challenge. Seafood is one of the most important sources of both protein and micronutrients for many, yet production from wild capture fisheries has stagnated. In contrast, aquaculture is the world’s fastest-growing food production sector, and now supplies over half of all seafood consumed globally. Mariculture, or the farming of brackish and marine species, accounts for roughly one-third of all aquaculture production and has received increasing attention as a potential supplement for wild-caught marine fisheries. By analyzing global patterns in seafood reliance, malnutrition levels, and economic opportunity, this study identifies where mariculture has the greatest potential to improve human nutrition. We calculate a mariculture opportunity index for 117 coastal nations by drawing on a diverse set of seafood production, trade, consumption, and nutrition data. Seventeen primary variables are combined into country-level scores for reliance on seafood, opportunity for nutritional improvement, and opportunity for economic development of mariculture. The final mariculture opportunity score identifies countries with high seafood reliance combined with high nutritional and economic opportunity scores. We find that island nations in Southeast Asia and the Caribbean are consistently identified as countries with high mariculture opportunity. In other regions, nutritional and economic opportunity scores are not significantly correlated, and we discuss the implications of this finding for crafting appropriate development policy. Finally, we identify key challenges to ameliorating malnutrition through mariculture development, including insufficient policy infrastructure, government instability, and ensuring local consumption of farmed fish. Our analysis is an important step towards prioritizing nations where the economic and nutritional benefits of expanding mariculture may be jointly captured.
This is a submission to PeerJ for review.
Raw data and associated calculated metrics used in all analyses and figures
Sensitivity of final mariculture opportunity scores to relative zero to one rescaling of individual metrics
Top 10 and bottom 10 countries shown for each choice of scaling. Rescaled (simple) was the final mariculture opportunity result when each country-specific metric was divided by the top-scoring country in that metric. Scaled to 90th [80th] percentile was the final result when each country-specific metric was divided by the 90th [80th] percentile country in that metric, with all countries above that percentile for that metric receiving a score of 1. Overall concordance between the rankings produced by the three scaling choices was high and significant (Kendall’s W 0.925; p<<0.05). 80th percentile scaling was used for all subsequent analyses.
Results of sensitivity analysis investigating the impact of the exclusion of individual variables on opportunity scores
Numbers represent the mean and standard deviation of the change in economic opportunity, nutritional opportunity, and seafood reliance scores, as well as overall mariculture opportunity score across countries (columns) when the global analysis is re-run without each variable (rows). Blank cells indicate no change (because removing, e.g., trade balance only affects the economic opportunity and final opportunity score, not the nutritional or seafood reliance scores).