“When we are trying to catch fish, if we can avoid steaming off in an unproductive direction we can reduce diesel consumption,” Matthew Dodd, Sealord’s general manager of information technology, said.
“Another big part of the sustainability picture is minimising bycatch of non-quota species. We want to use the data to make better decisions about where we fish to reduce our chances of bycatch and focus our efforts on high quota species.”
Using 30 years’ worth of trawl data from Sealord for two key species its catches – hoki and jack mackerel – Datacom built a predictive model for the ‘Catch Per Unit of Effort’, which is a key measure of the abundance of a target species and the accuracy of a fishing plan.
Datacom combined the trawling data with environmental and oceanographic data and satellite imagery. It also included data points such as surface temperature, ocean currents, salinity and levels of chlorophyll – the green pigment in the phytoplankton that forms the basis of food chains in the oceans.
Preliminary analysis of the Sealord trawling data revealed a large disparity between effort and catch, but the predictive model also proved to be an accurate predictor of past fishing success.
As well as reducing fuel consumption and overall costs, using the advanced analytics could lead to more efficient harvesting strategies and help optimise route planning for trawlers. In the future Sealord and Datacom intend to add more quality sets of data to the model, particularly for fish species where limited data was currently available.
Sealord resources manager for fishing operations, Charles Heaphy, said the data helped cut through the complexity of fishing commercially.
“If we can spot trends early we’ll be in a position to understand our fishery better. That’s why we need these big data sets and a way to look through the noise,” Heaphy said.
Sealord plans to share its analytics platform with the Deepwater Group, an industry partnership that represents quota owners of New Zealand’s deepwater fisheries and aims to optimise sustainable management of the fisheries.
Combining data sets from other industry players would improve the predictive power of the model.
Heaphy said a pilot project, which was part of the government-funded Project Moana scientific modelling effort, involved attaching sensors to fishing nets to supply real-time water temperature readings.
Sealord was also adding sensors to its fishing vessels to more accurately monitor diesel use and the performance of engines and boilers.
High tech future of fishing | Stuff.co.nz
