factoring in ocean colour data in the remote sensing technique used for fishery forecasts can vastly improve the reliability of prediction as well as the fish catch, claim Indian scientists.
Satellite-based forecasts usually rely only on sea surface temperature data. The method's reliability is just 50 per cent, though it increases yields by 40-50 per cent. Sea surface temperature data has two limitations. First, it can be remotely gauged only to a depth of less than a millimetre, failing to give a correct picture of the nutrient concentrations on which fish populations depend. Second, even modest surface winds or water current can distort the picture.
In comparison, the new technique devised by a team of scientists from the Space Applications Centre (sac) in Ahmedabad, and the Fishery Survey of India, Mumbai, has 70-90 per cent reliability and can enhance the yield 2-3 times. This is because ocean colour sensors (for chlorophyll) can detect signals far below (few tens of metres) the surface to gauge favourable conditions for fish breeding and aggregation, said the scientists led by R M Dwivedi of sac. The findings appeared in the December issue of the Indian Journal of Marine Sciences (Vol 34, No 4). The technique can considerably reduce the fishing pressure on coastal waters, they add.
Experiments showed the new technique improved the benefit-to-cost ratio of fishing for mechanised boats from 1.27 to 2.12 and for smaller boats from 1.3 to 2.14. In terms of profit, this would mean an increase from about 25 per cent now to more than 100 per cent.