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Scientists calculate the size of errors in the calculation of generation time of endangered species

A new study shows that assumptions used by researchers to calculate the time between generations of endangered animals may give an overly optimistic picture of how quickly a species will die out.

By Majken Brahe Ellegaard Christensen, , 4/23/2019

To better initiate actions to save endangered animals, it is necessary to assess when a species will likely go extinct. The generation time is the average time that passes from when animals are born until they have offspring and can vary greatly between species.

It plays an important role in this assessment of extinction risk and can be calculated from the species’ survival and reproduction data. These data are, however, flawed or missing for many endangered species.

Researchers rely on assumptions about the species generation time in order to predict the extinction rate. Naturally, these assumptions will lead to errors in the prediction of generation time, but so far, these errors have not been systematically assessed.

In a study from 2019, postdoc Johanna Staerk, together with her colleagues, has calculated the size of these errors in generation time and found that they may have led to an overly optimistic view of the extinction risk of endangered animals.

The global biodiversity crisis

Over the past century, the world’s biodiversity has been rapidly declining. The rate at which species die out is now 100-1000 times as high as it should naturally be, according to postdoc Johanna Staerk from Biology Institute.

Her research group believes that our planet is currently in a biodiversity crisis, and the International Union for the Conservation of Nature (IUCN) has recently declared that now 27% of all species are threatened with extinction, and the World Wildlife Fund believes that the globe is currently experiencing its 6th mass extinction period.

What drives this extinction can be qualified from the so-called population models that Staerk works with. The models are designed to calculate the population number of a given species over time based on factors specific to the species, such as survival rate, reproduction and generation time.

Assumptions in generation time underestimate the species survival

The generation time is one of the most important factors in the assessment of a species’ extinction risk. The generation time indicates how fast a species can respond to environmental changes: the longer the generation time the slower a species can adapt for example to climate changes and may, therefore, be more likely go extinct. For example, the generation time of a mouse is only a few months, whereas the African elephant has a generation time of 22 years.

It is precisely the calculation of the generation time that Staerk has been dealing with. For her calculation, she uses data from 58 mammalian populations compiled by her collaborators from the University of Lyon as well as data from computer simulations. Here, she found that the methods that do not include the full survival and reproduction data can lead to significant errors in the calculation of generation time. She also proposed a new method that can accurately predict generation time when data is scarce, which predicts generation time from the species body mass, and reproductive lifespan.

She tested the influence of these errors on Red List assessments from IUCN and found that the assumptions in generation time may give an overly optimistic picture of the endangered animals' extinction risk.

Calculations can lead to improved Red List assessments of endangered animals

It is the first time that errors in generation time have been assessed with such high precision. By having a clear picture of the types of errors that impact generation time, conservationists can better account for these factors in extinction risk assessments, and hereby improve assessments for thousands of species. 

About the study

The paper has been published on March 14, 2019 in the Journal of Applied Ecology.

Photo: Johanna Staerk, postdoc at the Science Faculty, SDU.

Editing was completed: 23.04.2019