A joint study involving both Scottish and Dutch pelagic sectors has produced data that is central to better understanding of the reproductive cycles of pelagic stocks.
The resulting paper is the first outcome of a PhD studentship co-funded by the University of Aberdeen, the Pelagic Freezer-Trawler Association (PFA) and the Scottish Pelagic Fishermen’s Association (SPFA) which aims to explore the biological and ecological applicability of industry-collected data on herring and mackerel.
PFA chief science officer Martin Pastoors and his SFPA counterpart Steve Mackinson played an important role in the realisation of the scientific research by making this industry-collected data available for analysis. The muscle fat data of herring has been collected by Scottish and Dutch pelagic trawlers during the herring and mackerel fisheries between 2005 and 2020.
Fat content in fish provides an indication of the condition of individual fish and, in many fish species, forms the basis of the annual reproductive cycle. Fat content is not routinely measured in scientific surveys but it is routinely measured in commercial pelagic fisheries.
For this study, fat measurements of herring by the Scottish and Dutch fishing industries were used to compare patterns in fat content throughout the year. The fat content of herring increased from 4.5% in May to 16.1% in June and then decreased again to 9% in September. The fat content in some years deviated from the average pattern. Research into possible explanations for these deviations is still ongoing. The study validates the scientific use of routinely collected fat content data from pelagic fish processors.
‘This study shows that the fishing industry can contribute unique types of data to scientific research, which can improve our understanding of fish stocks,’ said Martin Pastoors, emphasising the importance of collaboration between science and the pelagic fishing industry.
‘It is exciting to see how data that has been collected by so many different processors, when brought together, suddenly forms a powerful source of information. This also shows that there are great benefits in co-operating between different processors: the sum of the collective is clearly larger than the sum of the different parts.’
