Species Extinction Threat Vastly Underestimated

By Will Parker on July 3, 2008 in News

Extinction risks for populations of endangered species are likely being underestimated by as much as 100-fold because of a mathematical “misdiagnosis,” suggests a new study by a University of Colorado at Boulder researcher.

CU-Boulder’s Brett Melbourne said current mathematical models used to determine extinction threat, or “red-listed” status, of species worldwide overlook random differences between individuals in a given population. Such differences, which include variations in male-to-female sex ratios as well as size or behavioral variations between individuals, have an unexpectedly large effect on extinction risk calculations, contends Melbourne.

“When we apply our new mathematical model to species extinction rates, it shows that things are worse than we thought,” explained Melbourne. “By accounting for random differences between individuals, extinction rates for endangered species can be orders of magnitude higher than conservation biologists have believed.” Melbourne’s paper on the subject has just been published in Nature.

Currently, extinction risk models are based primarily on two factors. One is the number of random events adversely affecting individuals within a population – the accidental drowning of a rock wallaby, for example. The second risk factor used widely in extinction risk models is the impact of external, random events like temperature and rainfall fluctuations that can influence birth and death rates of individuals in a population. But Melbourne says that two additional factors – sex ratio variations and physical variation between individuals within a population – have been ignored or mischaracterized by most extinction risk modelers. “There has been a tendency to misdiagnose randomness between individuals in a population by lumping it with random factors in the environment, and this underestimates the extinction threat,” he said.

In the new study, the researchers monitored populations of beetles in lab cages and the results were used to test the new mathematical models. “The results showed the old models misdiagnosed the importance of different types of randomness, much like miscalculating the odds in an unfamiliar game of cards because you didn’t know the rules,” said Melbourne.

For some large, high-profile endangered species like mountain gorillas, biologists can collect data on specific individuals to help develop and track extinction trajectories, he said. “But for many other species, like stocks of marine fish, the best biologists can do is to measure abundances and population fluctuations, and it’s these species that are most likely to be misdiagnosed,” said Melbourne. “We suggest that extinction risk for many populations of conservation concern need to be urgently re-evaluated with full consideration of all factors contributing to stochasticity,” the study concluded.