When I read statements like “11,417 sharks killed per hour” from organisations that claim to be science-based I am always concerned how people seem to latch onto the “statistic” and go on to repeat it as though it was a fact. Even if they link to the actual scientific publication - in this case it was a paper by Worm et al. — most seem to be incapable of writing in a scientific manner. They often don’t reference the study, describe the method, include the margins of error, or discuss the limitations of the study. For example, in this particular study, the authors estimated a total annual mortality of sharks of about 100 million sharks with a range of possible values between 63 and 273 million sharks. This is a big margin of error. However, what many forget is that for many of the parameters used, there is natural variation and observation error — and that is for the data we do have. Sadly much of the data is estimated and indirectly calculated — or doubly indirectly. In fact in the Worm paper they use the word ‘estimate’ 33 times and the words ‘assume’ or ‘assumption’ 32 times.
This is not a criticism. It is actually a complement to the authors. And for the record I don’t necessarily agree or disagree with their findings. I would simply ask questions such as is it possible to have that many sharks removed each year — 273 million sharks at an average weight of 36kg = 9.82 million tons meaning that 1 in every 8~9kg pulled from the sea would be from a shark? How much fin would this be? How much space would be needed to dry that much fin? Just questions off the top of my head. Anyway, the paper passed a peer review and was published in a respected scientific journal. But let’s be clear, it is pretty much a best guess. However, sharks and rays, along with our global fisheries, are probably in as much trouble as our climate is and we need to act cautiously, and scientists tend to err on the side of caution.
Case in point, scientists will tell you that science proves nothing, it only discards the null hypothesis and lends support for the alternative. Repeated over often enough and subject to peer review, then one starts to arrive at a theory rather than a hypothesis — e.g. the Theory of Evolution. Only when it is universally agreed upon can it become a law — and the biological sciences do not have any scientific laws — indeed they may never.
Why am I harping on about this now? Well in this era of “fake news” where apparently more people get their news indirectly via Facebook rather than directly from news outlets that have their journalistic integrity continually reviewed, it is more important that we stay vigilant. We need to avoid absolutes, criticise those that use them, and demand evidence. And now more than ever, as we lose our grip in this trumped up world, we need to demand data. With an estimated one in ten people on the planet reliant on seafood for their livelihoods, with an estimated 90% of our seafood species at maximum exploitation or on the verge of collapse, and with an estimated 60% of seafood wasted, lost or discarded through supply chains isn’t it about time we found out? Isn’t it time we stopped guessing with something so important? Isn’t time we move from opinions to data-supported facts? And if so, how do we do that? How do we incentivise the collection of data and continually reward the data producers? We think the answer to some of these challenges may lie in a token incentivised data ecosystem for the seafood and associated industries. We call it Fishcoin.