Evaluation of nanobubble technology in aquaculture
Strategic Planning Workshop for Yellowtail Kingfish Stock Assessment in South-Eastern Australia
Improving and promoting fish-trawl selectivity in the Commonwealth Trawl Sector (CTS) and Great Australian Bight Trawl Sector (GABTS) of the Southern and Eastern Scalefish and Shark Fishery (SESSF)
Integrating recreational fishing information into harvest strategies for multi-sector fisheries
Integration of recreational fishing (RF) into harvest strategies (HS) is necessary for many fisheries in Australia, to account for catches that can equal or exceed commercial catch for some key species and to address biological and experiential objectives of the RF sector. Both the Productivity Commission’s report Marine Fisheries and Aquaculture (2016) and the ICES Report from the Working Group Recreational Fishing Surveys (2018) recommend formal integration of RF into stock assessments and harvest strategies. Failure to do so puts sustainable management goals and legislated state and Commonwealth fisheries requirements at risk.
Equitable and quantitative inclusion of RF in harvest strategies is rare. This stems from a traditional focus on the commercial sector and budgetary challenges involved with representatively sampling RF. It is therefore unclear: 1) what types of RF data and monitoring best service stock assessments, (2) which data also track indicators of recreational objectives (often related to the fishing experience), and (3) how to integrate harvest strategy components for multiple sectors. The need to address these knowledge gaps was highlighted by the FRDC priority research call in 2018 - “Integrating recreational fishery data into harvest strategies for multi-sector fisheries in New South Wales”. NSW provides an important test case for addressing issues around RF integration that are faced by most jurisdictions.
Harvest strategy development for multi-sector fisheries requires a transparent and defensible process due to complexities in addressing diverse objectives and apprehension among stakeholder groups. Structured workshops that use easily-understandable, interactive decision support tools and involve independent experts and stakeholder representatives are likely to provide best outcomes. ‘FishPath’ is a leading harvest strategy decision support tool and “bottom up” engagement philosophy that allows experts and stakeholders to interactively contribute to harvest strategy development in a transparent workshop setting. However, it requires additional development in recreational and multi-sector contexts.
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Project products
Estimating the biomass of fish stocks using novel and efficient genetic techniques
Evaluation of practical technologies for Perfluoroalkyl (PFA) remediation in marine fish hatcheries
Developing automated data cleansing and validation processes for fisheries catch and effort data
During a recent national Fisheries Statistics Working Group meeting, data managers from all Australian states highlighted and discussed the likely high prevalence of inaccurate or fraudulent data supplied by fishers and accrued through data-entry errors. Current data quality control measures in each jurisdiction are largely heterogeneous, undocumented and often rely on manual checks by clerks or analysts that are labour intensive and costly and not routinely executed. Because many of these checks occur during manual data entry of paper-based records, these are likely to become obsolete as reliance on electronic reporting increases, with data entered directly by fishers through online portals or mobile applications.
There is a need to develop automated data cleansing and diagnostic procedures that can be applied post-hoc or retrospectively to large fisheries databases to detect and flag errors and outliers and provide subsets of reliable catch and effort data for stock assessments and other analyses. This project will contribute towards addressing these issues, by developing automated processes to routinely assess newly entered fisheries catch and effort data for errors, retrospectively quantify error rates in existing data and assess their likely influence on the outputs of stock assessment analyses. The outcomes will help improve the quality and accuracy of catch and effort data used in routine stock assessments, and in turn lead to more sustainable management of wild capture fisheries resources.