Mapping of potential fishing zones in support of fisheries management in West Africa

Abstract

The distribution pattern of three tuna species viz. Skipjack (Katsuwonus pelamis), Yellowfin (Thunnus albacares) and Bigeye (Thunnus obesus) and key environmental factors were analyzed to develop potential fishing zone (PFZ) maps to support fisheries resource management in West Africa. The PFZ maps were developed from a Generalized Additive Model built from a binomial distribution with a probit link function. Inputs into the model were presence- absence data generated from tuna catch records from Ghana as well as sea surface temperature (SST), sea surface heights (SSH), geostrophic currents (UV) and salinity (SSS) datasets covering latitudes 10°S to 40°N and longitudes 35°W to 15°E in the period 2014-2015. Results from the analyses showed a non-linear response pattern with varying relationships among the environmental factors. The major fishing grounds identified from the outputs of the predictive model corresponded with regions where SST was between 21 and 28.5 °C, SSH above 0.05 m, geostrophic current speed above 0.25 m/s and SSS levels above 33.5 ppt. High tuna distribution was consistent with the major upwelling regions, suggesting that the dynamics of the upper ocean may account for the observed spatial pattern. Outputs from the model can provide a quick overview of the possible areas where tuna is likely to aggregate and the potential fishing grounds where monitoring and surveillance need to be intensified.