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.
Australia’s fisheries span a large area of ocean. Australia has the world’s third largest Exclusive Economic Zone (EEZ), with an area of over 8 million km2. This zone contains mainly Commonwealth managed fisheries, with State jurisdictions mainly in coastal waters up to the 3 nautical mile limit. Australia's total wild-catch fisheries gross value of production is $1.6 billion, of which 28% is from Commonwealth fisheries and 72% from the smaller coastal inshore fisheries managed by state jurisdictions. The wildcatch fisheries sector employs about 10,000 people across Australia (https://www.awe.gov.au/abares/research-topics/fisheries/fisheries-and-aquaculture-statistics/employment).
The commercial fishing industry has a network of thousands of vessels working mainly in inshore waters around Australia. They can supply a potential platform for extensive and fine scale spatial and temporal monitoring of the waters of the continental shelf (0-1200m), from the surface to the ocean floor. Given that their livelihoods depend on it, they have a keen understanding of oceanographic conditions with respect to fish behaviour, feeding and spawning and the various oceanographic factors that may influence this. In some fisheries (e.g. surface tuna longlining), fishers eagerly seek and use readily available fine-scale oceanographic data such as sea surface temperature and sea level, to improve their targeting and achieve higher resultant catch rates. For many other fisheries, however, it is the fine-scale sub-surface oceanographic conditions (feed layers, thermoclines, temperature at depth etc) that have a critical influence on their fishing dynamics. Unfortunately, this type of oceanographic data is far less readily available. Although fishers and scientists know these factors are important, the time series of fine scale spatial and temporal data relevant to fishery operations is not available to include in stock assessments. As a result, it is often assumed that variations in catch rates reflect changing stock abundance, when it may simply be a result of changing oceanographic conditions.
Marine scientists collect a vast range of oceanographic data using satellites, subsurface drones, and static and drifting buoys. Sea surface data, however, is much easier and more cost-effective to collect at high spatial and temporal resolutions than sub-surface data. Hence, understanding of sub-surface oceanographic conditions tends to be derived from modelling more than actual measurement. This may be sufficient at a wide-scale global or continental level, but it is not adequate at the fine-scale spatial and temporal resolution required for fisheries management.
The use of commercial fishing gear as a research data platform has been increasing in popularity internationally (https://www.frontiersin.org/articles/10.3389/fmars.2020.485512/full). A number of groups in Europe have been doing this for a decade (e.g Martinelli et al 2016), and New Zealand are also now involved (https://www.moanaproject.org/te-tiro-moana). However, this approach has yet to be implemented in Australia in a coordinated way. In particular, our approach dictates open access data served through the IMOS Australian Ocean Data Network (www.aodn.org.au) that can be collected once and used many times.
In this project we intend to instrument seafood sector assets (e.g Trawl Nets, longlines, pots) with fit-for- purpose quality-controlled (QC'd) temperature/pressure sensors to increase the sub-surface temperature data coverage around Australia’s shelf and upper slope regions (0-800m) at low cost. Not only will this assist in the collection of data at relevant spatial and temporal scales for use by fishers, but it will also provide a far more extensive level of QC’d data to oceanographers in near real time (NRT) for evaluation and ingestion into data-assimilating coastal models that will provide improved analysis and forecasts of oceanic conditions. In turn, this will also be of value to the fishing sector when used to standardise stock assessments.
Martinelli, M., Guicciardi, S., Penna, P., Belardinelli, A., Croci, C., Domenichetti, F., et al. (2016). Evaluation of the oceanographic measurement accuracy of different commercial sensors to be used on fishing gears. Ocean Eng. 111, 22–33. doi: 10.1016/J.OCEANENG.2015.10.037
This project seeks to position the NT seafood industry to have a clear understanding of suitable and cost effective, valued systems and processes for adoption. It is the critical first step required to aid a shift in the behaviour and culture from a government driven data collection process for legislative purposes, to a process that is trusted and valued by industry to deliver data insights beyond regulatory requirements. As a result, it will help position the NT wild harvest and aquaculture sectors with securing access, investment and development opportunities.
Current negotiations for access to Aboriginal-owned tidal waters have reached a critical point. A gap exists in understanding what level of industry adjustment might be required to ensure Indigenous investment in the industry is not unnecessarily impacted. Better understanding the full value of the NT seafood industry to the NT community could assist with all strategic decisions related to Blue Mud Bay negotiations, infrastructure investments – and help support investment in the industry going forward.
Without a plan to enhance the visibility of the wider socio-economic value and benefits of our industry, we will continue to face increasing pressure on our social licence to operate – which has the potential to impact all aspects of the local industry, including access, industry structure and increased fees. It will also limit our ability to identify the best opportunities for future growth and sustainability.
Further, there is limited availability of current financial and economic information for our individual NT wild harvest fisheries and sector specific aquaculture activities. Due to this lack of information there is little scope for economic analysis, hence limiting opportunities for providing advice to policy and decision makers.
