Abstract

Although New Zealand rock lobster (Jasus edwardsii) fisheries can be assessed with a sophisticated Bayesian length‐based model, these assessments are expensive and time consuming; they cannot be conducted for each area every year. Harvest control rules are increasingly important management tools in New Zealand rock lobster fisheries. Recent work has developed and evaluated procedures for rebuilding or maintaining lobster stocks based on criteria agreed by stakeholders. Most management procedures depend on a single abundance index, often catch per unit of effort (CPUE). When management procedures react slowly to changes in vulnerable biomass, allowable catches get out of phase with the stock, causing large oscillations in both catches and CPUE. Lags between data and management actions and “latent years” are features of rules that reduce responsiveness. This study explores ways to improve the responsiveness of harvest control rules by using additional data to predict changes in vulnerable biomass. Four data sets are examined: CPUE trends, pre‐recruit indices, puerulus settlement indices, and size frequencies. Only pre‐recruit indices, which were explored with a simple delay‐difference model based on parameter estimates from recent assessments, appeared to have immediate potential for use in improving management procedures.

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