Selected Publications

Common uncertainties in stock assessment relate to parameters or assumptions that strongly determine both the estimates of quantities of management interest (e.g. stock depletion) and related reference points (e.g. biomass at maximum sustainable yield). The risks associated with these uncertainties are often presented to managers in the form of decision tables. However, a formal evaluation of the risks from mis‐specifying an assessment model over time‐horizons spanning multiple assessment cycles requires closed‐loop simulation. There were two aims of this study: (a) develop an approach to identify and evaluate asymmetries in risk to yields and spawning biomass due to biases in key parameters and data sources in a stock assessment model, (b) quantify the relative importance of correctly specifying the various assessment attributes. A computationally efficient stock reduction analysis was evaluated using closed‐loop simulation to identify risks associated with a stock assessment with persistent positive and negative biases in the key parameters and inaccurate assumptions regarding data sources. Six types of assessment misspecification were examined, namely the assumed natural mortality rate, the assumed recruitment compensation ratio, the assumed age of maturity, a hyper‐stable or hyper‐deplete index of abundance, over‐ or under‐reporting of historical catch, and misspecification of the assumed shape of the selectivity curve. This study reveals large asymmetries in risk associated with common uncertainties in stock assessment processes. We highlight the value of reproducible and computationally efficient stock assessment models that can be investigated by closed‐loop simulation before being used for fisheries management.
In Fish and Fish., 2019

The cost, complexity and the lack of technical capacity in many countries have made the scientific assessment and sustainable management of data- poor fisheries a per- sistent problem. New and innovative approaches are needed to stop the ongoing decline of data- poor fisheries and loss of coastal biodiversity they are driving. In re- cent decades, marine protected areas have become the most preferred form of man- agement for study and have been widely implemented as broadly applicable powerful management tools for data- poor fisheries, but although clearly capable of building biomass within sanctuaries, their effectiveness for sustaining fisheries is proving more difficult to substantiate. This study suggests the new approach needed is actu- ally a return to the established basics of managing size selectivity. Previous studies have established the wisdom of managing size selectivity and fishing pressure to catch fish above the size or age of maturity, but their prescriptions are difficult to implement without age studies, or the capacity for controlling catches and fishing pressure. This study develops an easily implementable rule of thumb based simply on multiples of size of maturity and quantifies its benefit where controlling fishing pres- sure is not yet possible. Our study provides a timely reminder that even if used alone, size selectivity, the oldest form of management, still produces pretty good sustaina- ble yields. We suggest our rule of thumb can be used to prevent data- poor fisheries declining while capacity for more complex forms of assessment and management are developed.
In Fish & Fish., 2018

Recent Publications

More Publications

(2019). Misspecification in stock assessments: Common uncertainties and asymmetric risks. In Fish and Fish..


(2019). Comment on “A new approach for estimating stock status from length frequency data” by Froese et al. (2018). In ICES JMS.


(2018). Developing a functional definition of small-scale fisheries in support of marine capture fisheries management in Indonesia. In Marine Policy.

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