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Abstract
The status of a fishery is often defined as the probability of fishing mortality rate exceeding a perilous level for long‐term sustainability. Lobster stock assessments are often subject to large uncertainty in input data and high levels of natural variability in lobster life history processes, which calls for incorporating uncertainty associated with both indicator and management reference points in an evaluation of biological risk of overfishing. Using a Monte Carlo simulation approach, we evaluated the impacts of uncertainty in modelling on the determination of the status of the Taitung spiny lobster (Panulirus penicillatus) fishery (Taiwan), which has not been quantitatively determined despite its commercial importance. The commonly used biological reference points derived from the per recruit model (F 0.1 the fishing mortality rate where the slope of the curve of yield‐per‐recruit model is 10% of the maximum slope and F 4Q%, the fishing mortality rate that reduces the expected egg production for a cohort of female lobsters to 40% of that produced in the absence of a fishery of the egg‐per‐recruit model) were influenced by uncertainties associated with lobster life history and fishery parameters. A large uncertainty in the current fishing mortality rate (F cnr) and estimates of biological reference points (F BRPs) increased the uncertainty in determining the risk of overexploitation throughout the confidence levels of the stochastic decision‐making framework. This simulation study suggests that the target reference point of F 40% is less sensitive to the input parameters’ uncertainty than F 0.1 We suggest a further evaluation of other F‐based references points and development of biomass‐based reference points before final selection and implementation for the management of the Taitung lobster fishery.
