Multivariate environment-fish biomass model informs sustainability and lost income in Indian Ocean coral reefs

Abstract

Many tropical reef fisheries are underperforming relative to maximum sustained yields despite their importance for the economies and food security of natural resource dependent people. Assessments of fisheries in tropical reefs have been hampered by the logistic difficulty and costs of making empirical estimates of sustainable yields in multi-species fisheries. To overcome this limitation, we used empirical fish biomass recovery data in high-compliance closures to create a production curve estimate that established biomass and yields at maximum sustained yield (Bmsy). A multivariate machine learning model using environmental and human influence proxies made biomass and yield estimates in 10,815 ∼6.25 km2 Indian Ocean cells. Subsequent analyses determined the national over- and under-fishing status. Identified proxies of travel time from markets, depth, and fisheries management were the main drivers of biomass and subsequent status. The East African countries of Kenya, Tanzania, and Mozambique had 18,500 km2 of reef and the lowest regional estimated biomass - losing 17,600 tons of commercial target fish per year. Therefore, the estimated loss is between US$ 50–150 million per year depending on the worth in the fisheries trade's value chain The more populated islands of Reunion, Mauritius, Mayotte, and Comoros have smaller areas (5000 km2) and losing 3000 tons/year, and >US$ 9 million per year. Madagascar has many reefs (13,700 km2) and larger variation in yields with an estimated loss of ∼6000 tons/y. Increased restrictions could greatly increase the value of Indian Ocean fisheries by promoting the recovery of target biomass and recovering lost income.