Application Of Forecasting In Determining Efficiency Of Fisheries Management Strategies Of Artisanal Labeo Mesops Fishery Of Lake Malawi

The Labeo mesops together with its family members, the cyprinids have been reported declining in population. The exploitation levels are not matching the species carrying capacity for the populations to rejuvenate. As such several management strategies including restocking were put in place to restore the fishery. There is a need to quantify the efficiency of these strategies in managing and restoring the species fishery. The study aimed at modelling and forecasting Labeo mesops (Ntchira), yield from artisanal fishery on Lake Malawi in Mangochi district based on time series data on catches of the species during the years of 1976 to 2012 collected from the Department of Fisheries in Malawi. The study considered Autoregressive Integrated Moving Average (ARIMA) processes to select an appropriate stochastic model for forecasting the species yield. The appropriate model was chosen based on ARIMA (p, d, q). The Autocorrelation function (ACF), Partial autocorrelation (PACF), Akaike Information Criteria (AIC), Box�Ljung statistics, correlogram and distribution of residual errors were estimated. The selected modelwas ARIMA (0, 1, 1) for forecasting the artisanal landings of Labeo mesops from Lake Malawi in Mangochi District from the year 2013 to 2022. The forecast showed that the species could have already collapsed since the forecast were in negatives meaning that the stock of Labeo mesopsmay no longer be available by the year 2022 in the landings holding other factors constant. The study showed that the current fisheries management strategies are failing to manage the artisanal Labeo mesops fishery in the region as it is succumbing to the theory of �Tragedy of Commons�.

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