A machine-learning algorithm predicts that more than half of the thousands of species whose conservation status has yet to be assessed are probably in danger of disappearing for good

To effectively protect a species, conservationists need key pieces of information: where it lives and what threats it faces. Yet scientists lack these basic data for thousands of species around the world, making it impossible to know how they’re faring—let alone to take steps to ensure their survival.

For these “data deficient” species, a new study published in Communications Biology on August 4 suggests that no news is probably not good news. The authors used machine-learning methods to predict the conservation status of 7,699 data-deficient species—from fish to mammals—and found that 56 percent are likely threatened with extinction. The findings are especially concerning, given that just 28 percent of species whose conservation status is known are deemed to be at risk of disappearing, says lead author Jan Borgelt, a doctoral candidate in industrial ecology at the Norwegian University of Science and Technology. “Things could be much worse than we actually realize,” he adds.

Rachel Nuwer

Link to Rachel Nuwer’s article in Scientific American

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