The Preliminary Study Of Methods To Calculate Biomass Trends, Exploitation Rate And Surplus Production From Survey Index And Catch Data.

This study showed how to calculate the trends in biomass; exploitation rate and surplus production by using the survey index and catch data to rebuild the histories of surveyed fishery, which a changing with respect to time. If the survey data and historical catch data of fishery are available, and the relationship between surveyed biomass index and absolute biomass is known the history of surplus production from the fishery can be estimated. This study analyzed in four different fisheries, one real fishery and three simulated fisheries. The real fishery data come from the monkfish (Lophius americanus) stock in the eastern America, prpvided by the National Marine Fisheries Service (NMFS). The three simulated fisheries were estimated by Monte Carlo simulation, the white noises were generated from Box-Muller method; the levels (Coefficient of Variation, CV) were 1%, 10%, 30% and 50%.The analytical result of monkfish fishery in eastern America indicates that the historical trends in surplus production of this fishery were not sensitive to the current assumption of biomass, though the absolute value of surplus production varied with the variation of the assumption of current population biomass. In the mid 1970s, when the biomass increased greatly, there was considerable growth of surplus production, v/hich became negative when biomass decreased. The result showed that the surplus production of monkfish stock was the highest during the low level of bionass in 1990s.In the over-exploited fishery, catch data and 0.1% of biomass were used to simulate the biomass index in an over-exploited population to calculate the trends in biomass, catch, exploitation rate and su plus production. The estimatedresult showed that the lowest biomass at low white noise level (1%, 10%) were corresponding to the highest surplus production and additionally exploitation rate was high when biomass was low. White noisd in 30%, the biomass was high then decreased with negative surplus production. When biomass increases, surplus production fluctuates around 0 and does not correspond to the low biomass. When the white noise level was 50%, surplus production was high at high biomass. When the white noise level was 30% and 5-year running average was used, low biomass corresponded to high surplus production. But when the white noise was 50% and biomass was low, the surplus production fluctuated around 0.The simulated fishery 2 showed ah under-exploited fishery, which imposed catch effort was less than the optimal catch effort. The biomass was unexploited in beginning. When the white noise levels Were low (1% to 10%), biomass was decreasing. When catch and exploitation rate are decreasing, biomass can be recovered. Less than 30% white noise, when biomass decreases surplus production and exploitation rate increases. When white noise level was high (50%), there was no obvious relationship among the trends in biomass, catch and surplus production. When 5-year rtinnirlg average was used, the trends in biomass catch and surplus production were hot obvious (for 30% and 50% of white noise). In all cases, the biomass could fee recovered when Exploitation rate was declining.The sihiulated fishery 3 showed a "6ne-way trip" fishery, which the imposed fishing effort is higher than the optimal effort. No matter catch and exploitation rate decrease or increase, the blbmass could not be recovered. But one exception was when the white noise leVbl was (50%); the biomass seemed to be recovered.