The marine fisheries sector in India supports livelihood of four million people and earn a significant amount of foreign exchange through export of marine fish and its products. Historic data showed that the total marine fish production in India maintains an overall upward trend with fluctuations. Periodic assessment of major fishery resource groups is necessary to manage the fishery for sustainability. Among different species groups, 50 commercially important resource groups accounting for about 97% of the national annual landings were individually studied by Markov Chain modeling of annual growth rates in landings. In addition, the time series data on landings of these marine fishery resource groups were analyzed randomness using ‘runs test’. Limiting probabilities for all the nine defined states of each Markov Chain process were determined and status of the resources was derived based on limiting probabilities. Runs test on the time series sequences showed 19 of them having random behavior. It was found through Markov Chain modeling that 16 of the marine fishery resources have probability more than 0.8 to confine their annual growth rate between -0.25% and +0.25% providing high confidence regarding stable yield from harvest indicating stability of their stocks.

Marine fish landings, resource assessment, modeling, Markov Chain, runs test, time series data