Incorporation of predictive models of banana prawn catch for MEY-based harvest strategy development for the Northern Prawn Fishery

Rik C. Buckworth, Bill, W H Venables, E Lawrence, Thomas Kompas, Sean Pascoe, Long Chu, F Hill, Trevor Hutton, P Rothlisberg

    Research output: Book/ReportCommissioned report

    Abstract

    NON TECHNICAL SUMMARY: OUTCOMES ACHIEVED TO DATE The methods developed in this project are a means of predicting potential catch in the White Banana Prawn fishery of the Northern Prawn Fishery catch. This is an essential basis for setting pre-season management controls for the banana prawn fishery that target and deliver Maximum Economic Yield (MEY). A prediction of potential catch is necessary in this fishery to determine either a Total Allowable Catch (TAC) or a catch rate-based trigger, based on a Maximum Economic Yield (MEY) target. Because prawn prices are affected by catch levels, a prediction of potential catch is necessary to both calculations. The approaches developed here have increased the suite of tools available to improve management performance of fisheries. Many fisheries are subject to large, environmentally-driven fluctuations in the abundance of target species. This study provides an example of the analysis of the response of these fisheries to the environmental drivers. The outcome of this tool development is that, ultimately, assessments might be developed for such fisheries and, moreover, it might then be also possible to ascertain economic attributes to address MEY targets. The outputs from this work were a necessary requirement for a subsequent management strategy evaluation project, to compare the performance of TACs and catch rate triggers set using the current project's outputs, with the existing management controls. The ultimate outcome from both projects will be the improved economic performance of the Northern Prawn Fishery, and concomitant community benefit. The project has been generally well-accepted by industry and fishery managers, as well as the scientific community. KEYWORDS: White banana prawns, Penaeus merguiensis, northern Australia, rainfall, environmental correlation, environmental drivers, catch prediction, abundance estimation, partially-linear models, Maximum Economic Yield, price elasticity, bioeconomic model Australian Government fisheries management policy has generated an impetus for output controls for management in the NPF and, consequently, a need to predict potential catch on which to establish annual TACs. Alternative controls include catch rate triggers (the current approach) and a modification of the latter approach, in which catch rate triggers are calculated to achieve an MEY target. The White Banana Prawn, Penaeus merguiensis, is a short-lived, fecund, tropical species whose annual catches have varied markedly - around eight-fold - over the history of the fishery. Although fishermen and others associated with prawn fisheries have long known that there is a strong relationship between banana prawn catches and rainfall, description of statistical relationships that are adequate for predictions of catch at the large spatial scale of the Northern Prawn Fishery (NPF) has been elusive. A further constraint, given the short life cycle of P. merguiensis, is that the annual opening of the season is around 1 April each year, which follows closely their recruitment to the fishery. Therefore, factors affecting recruitment strength can only be measured up to February in the same year. A feasibility project (Venables et al. 2011) built a partially-linear model relating the annual total catches to rainfall indices for each of nine separate common banana prawn stock regions within the Northern Prawn Fishery (NPF). The predicted potential catch for the fishery was simply the sum across predictions for nine individual stock regions. Although successful, the model was unstable and difficult to fit in some regions. In this project, we built upon this earlier work, particularly to make the model more stable and to investigate the uncertainties in the model and its predictions. We developed the economic tools necessary to address MEY goals. These tools enable the prediction of the response of prawn price to landings of banana prawn, and the calculation of catch and effort co
    Original languageEnglish
    Place of PublicationCanberra Australia
    PublisherCSIRO Publishing
    Commissioning bodyFisheries Research and Development Corporation. CSIRO Marine & Atmospheric Research, Brisbane
    Number of pages130
    Edition1st
    ISBN (Print)9781486302857
    DOIs
    Publication statusPublished - 2014

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