Can additional abundance indices improve harvest control rules for New Zealand rock lobster (Jasus edwardsii) fisheries?

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.

Strong relationships between levels of puerulus settlement and recruited stock abundance in the red rock lobster (Jasus edwardsii) in New Zealand

“…Our analyses shed no light on which of these two has most weight, but the spatial and temporal consistencies in settlement patterns (Booth et al, 2007), together with the strong correlations reported here, persuade us that by no means does the full burden for lack of consistency between the settlement record and the modelled recruitment lie with the settlement record. Further, the lack of consistency between the settlement indices and fishery performance described by Bentley et al (2005b) may lie in the improbably small lags they used between settlement and recruitment to the fishery (e.g., just 3 years for CRA 7) and, apparently, the amalgamating of male and female CPUE data in fisheries where the sexes recruit at very different ages.…”

“…We found no concurrence between field estimates of recruitment and modelled estimates of fishery recruitment when a 2-year lag between settlement and recruitment to the model was applied, suggesting that year-to-year rates of recruitment to the fishery have been interpreted differently in the two approaches. Bentley et al (2004aBentley et al ( , 2005b concluded that settlement indices were not useful in predicting fishery performance because of the lack of consistency with modelled recruitment. As emphasised by Bentley et al (2004a), this may be because (1) the estimates of recruitment from stock assessments may be imprecise -at least in part because the stock assessment model is designed primarily to model that part of the population that is vulnerable to the fishery, not recruitment; and/or (2) the collector indices may not be providing good information on recruitment.…”

Practical stakeholder-driven harvest policies for groundfish fisheries in British Columbia, Canada

“…In particular, long-term declines were likely where initial choices for exploitation rates were based on biased biomass estimates. Data-based procedures have been developed and adopted for Namibian hake and South African west coast rock lobster (Rademeyer et al, 2007) and New Zealand rock lobster (Bentley et al, 2005), although procedures for hake and rock lobster in South Africa were both considered interim in the absence of better quality data for future model-based procedures.…”

Evaluating alternative management strategies for bigeye tuna, <i>Thunnus obesus</i>, in the Indian Ocean

“…A management strategy, also referred to as a "management procedure" (Bentley and Langley 2012), a "harvest control rule" (Kell et al 1999, Breen 2009, and a "decision rule" (Bentley et al 2005), is a group of regulations defined with key management parameters to address certain management objectives (Deroba and Bence 2008). Fishing mortality of the next year can be determined directly or indirectly using a defined management strategy based on the status of the stock and/or exploitation determined in a stock assessment.…”