Data management and governance framework development for fishing and aquaculture
FRDC requires mechanisms to assess and govern the data for which it is custodian or may become custodian of. FRDC requires a data governance framework that builds on the concepts of the NFF Farm Data Code and other Agricultural data best practices for use by FRDC data stakeholders. A data governance framework will ensure that FRDC BAU and project data is captured, managed and distributed with accountability, consistency, security and meets defined standards throughout the data lifecycle. As a coordinating industry body, it is essential that FRDC leads the way with a robust, considered approach to data management. This will place FRDC as a best practice example, it will enable consistent discussion and guidance to stakeholders and data partners and will provide a consistent foundation for overall trust and capability in the use of data as well as providing a foundation for the FRDC to maximise the value of data created through the Australian innovation system. It is expected that subsets of the FRDC data governance framework will be developed in the future to extend support to FRDC stakeholderss.
Trials of oceanographic data collection on commercial fishing vessels in SE Australia
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
Article
Project products
Tactical Research Fund: Nutrient and phytoplankton data from Storm Bay to support sustainable resource planning
Knowledge of changing environmental conditions and productivity as a result of climate change is essential for adaptive management. In addition to direct applicability to fisheries and aquaculture in southern Tasmania, this information will have numerous important applications to other industries and stakeholders in the broader catchment.
CSIRO and TAFI have established a program (INFORMD- Inshore network for observation and regional management: Derwent-Huon) to guide multiple use coastal zone development and management. Storm Bay is an integral component of the INFORMD region and a priority is to understand both the short term (climate variability) and long-term (climate change) drivers of productivity in the region and link these to production of fisheries and aquaculture. CSIRO have a project investigating novel observing technologies (NOTe) to characterize the Derwent to shelf environment and TAFI will fund a charter vessel to monthly sample water column environmental variables, and support the CSIRO observing system. Thus an opportunity exists to obtain nutrient and productivity data in the Storm Bay region in a very cost-effective manner by collaborating with the existing research program.
Important background information is that the East Australian Current is predicted to penetrate further south causing significant warming and decreased productivity. Previous work (Harris et al 1991) showed that the nutrient status of waters clearly indicated the influence of the EAC, and primary producers indicated the productivity of the region, demonstrating the potential for Storm Bay to act as an indicator of productivity for Southern and Eastern Tasmania. Such information is important to understanding changes in fisheries and aquaculture production and, as a consequence, to assist with developing climate change adaptive management strategies.
This project also provides an opportunity for FRDC to invest in a project that will have significant influence on multiple use management in Australia.
Final report
This project has provided preliminary data on environmental conditions in Storm Bay that is assisting managers and marine industries to better understand effects of climate change and climate variability on fisheries and aquaculture in the region, including changing currents and primary productivity. This information is being used to inform the development of climate change adaptive management strategies for commercial and recreational fisheries and for the potential expansion of salmon aquaculture into Storm Bay. The environmental characterisation of Storm Bay is also supporting planning in the region, by providing baseline data and data for projects modelling the bay’s water circulation and ecosystem dynamics. This information will support the development of multiple use management plans for the region.
Keywords: Climate variability, Storm Bay, water quality, productivity, offshore salmon aquaculture