University researchers in Switzerland, Canada and Australia have developed a new statistical model, which they believe can help fishermen reduce the amount of protected marine life that becomes unintentionally caught in their nets.
At sea, protected marine species – such as hammerhead sharks - and fish with no commercial value are often caught by accident and die needlessly. The scale of this bycatch problem is hard to measure, as fishing fleets often don’t report what they don’t bring back to shore.
According to a 2005 estimate by the United Nations Food and Agriculture Organization, over 6.8 million tons of sea life get thrown back over the side of boats into the sea every year as so-called fisheries discards. This figure is mainly for fish, and doesn’t include seabirds, mammals and turtles.
Statisticians from the University of Geneva, the Dalhousie University in Halifax, Canada, and the Australian National University in Canberra have devised a new method for predicting future bycatches more accurately.
The model examined a huge range of dynamic factors, explained Eva Cantoniexternal link, professor at the Research Center for Statistics at the University of Geneva’s School of Economics and Management (GSEM).
“The aim was not just to analyse the changes in the number of catches over time but also to study the different seasons and the weather, all the while factoring in the technical conditions: the depth of the nets, the seasons, the type of hooks used, whether light sticks were used or not, and the kind of vessel.”
Using this data, the teams identified the easily influenceable conditions such as the depth of the hooks, which would reduce the volume of non-marketable species caught.
It is now possible to estimate potential bycatches for a fishing expedition, say the researchers.
“When fishermen give us their voyage data, we can predict the incidental catch for hammerhead sharks, for example, with more precision,” said Cantoni.
The scientists believe their method can be used to support national environmental policies by prohibiting fishing at a certain depth at a particular time of year when it may involve too much bycatch.
They say their methodology, which is described in the journal Annals of Applied Statisticsexternal link, was created mainly for commercial fishing but can also be used in other research fields, including health economics, medicine and educational science.