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Add as preferred source In the last few centuries, mammals and other animals have been going extinct at least 100 times faster than they did before humans arrived on the scene. So who will be next? Which species are most likely to survive, and which will die out?
New research shows that, when deciding which species need protecting, extinction risk factors of the past can be powerful—but they're not perfect.
That's the takeaway of a new study of extinction patterns among tropical forest mammals worldwide, ranging from opossums to elephants.
The results are important because of the world's roughly 6,000 known mammals, 1 in 4 are on track to disappear within the century, according to the Union for the Conservation of Nature (IUCN).
Identifying the species that are most vulnerable is key to protecting them while there's still time. But many species are a black box. Some 770 mammal species evaluated by the IUCN—nearly 15%—are considered "data deficient," meaning scientists just don't have enough information on their numbers or where they live to determine whether they need protection.
To bridge the gaps, scientists sometimes look to large-scale trends over time. But just how well do studies of extinction risk in centuries and millennia gone by predict species' vulnerability today?
An international team of researchers tackled the question in a study published in the journal Science Advances .
Led by researchers from the Norwegian University of Life Sciences and Wageningen University & Research, in close collaboration with Michigan State University and others, the team combined images of wildlife taken by automatic cameras with fossil records and species range data covering the past 130,000 years, before and after modern humans spread around the globe.
Of the 210 species they looked at, 199 are still here walking the earth, from porcupines and anteaters to monkeys and bears. Some, like Asian elephants and leopards in Africa, have disappeared from certain regions but are still hanging on in others. Eleven species have been lost entirely. Among them were giant pangolins that grew up to nine feet (2.7 meters) long, saber-toothed cats weighing half a ton and mastodons. Vanished.
The analysis, spanning 64 forest sites across Africa, Asia and the Americas, revealed that the types of species identified as most at risk aren't always consistent from one time frame to the next.
Looking back over the past 130,000 years, the mammal species that were most vulnerable were those with large bodies, small brains, a carnivorous diet and slow rates of reproduction.
These patterns were remarkably similar at local, regional and global scales.
The results were not entirely surprising, said Michigan State University professor Lydia Beaudrot, one of the lead authors of the research. Similar traits have been linked to extinction risk in other studies.
But things changed when researchers compared these long-term patterns with more recent data from camera traps and elsewhere.
For instance, while the research showed that larger brains gave species an edge over the past 130,000 years, some previous studies have suggested that large brains can be a liability among mammals today.
Conversely, other traits that made species vulnerable in the past, such as large body size and slow reproduction, were instead linked with resilience today.
It may be that larger mammals with long generation lengths tend to thrive in sites where camera traps were installed, which were mostly in protected areas where animals are less likely to be targeted by human hunters.
Whatever the reason for their relative advantage or disadvantage, Beaudrot said, "the traits associated with survival are different."
The team hopes their work will help researchers better identify at-risk mammals and focus conservation efforts where they're needed most.
"We can't just assume that large-scale patterns apply at smaller scales," Beaudrot added. "We have to take the temporal dimension into account."
Simon D. Schowanek et al, Predictors of extinction risk in large tropical forest mammals: From global to local, Science Advances (2026). DOI: 10.1126/sciadv.aeb7543
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