Environment-Fish Biomass Model for Indian Ocean Reefs

This study addresses the underperformance of tropical reef fisheries despite their crucial role in supporting economies and food security. Assessing these fisheries is challenging due to logistical difficulties and costs.

To overcome these limitations, the researchers developed a production curve estimate using empirical data on fish biomass recovery in high-compliance closures, establishing maximum sustained yield (Bmsy). They utilized a multivariate machine learning model incorporating environmental and human influence indicators to estimate biomass and yields in approximately 10,815 Indian Ocean cells covering an area of about 6.25 km2 each.

Subsequent analyses determined the over- and under-fishing status of nations. The study revealed that Kenya, Tanzania, and Mozambique in East Africa had the lowest estimated biomass, resulting in an annual loss of 17,600 tons of commercially targeted fish, valued between US$50-150 million.

Similarly, the more populated islands of Reunion, Mauritius, Mayotte, and Comoros experienced an annual loss of 3,000 tons, equivalent to over US$9 million. Madagascar, with extensive reef coverage of 13,700 km2, exhibited larger variations in yields, estimating a loss of approximately 6,000 tons annually.

The findings highlight the potential value of Indian Ocean fisheries through increased restrictions, promoting target biomass recovery and economic gains.