iucn_sim: a new program to simulate future extinctions based on IUCN threat status

Andermann, Tobias; Faurby, Søren; Cooke, Robert; Silvestro, Daniele; Antonelli, Alexandre

iucn_sim: a new program to simulate future extinctions based on IUCN threat status

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Journal article

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Andermann, Tobias

ORCID

Faurby, Søren

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Cooke, Robert

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Silvestro, Daniele

Antonelli, Alexandre

Date published

November 10, 2020

Abstract

The ongoing environmental crisis poses an urgent need to forecast the who, where and when of future species extinctions, as such information is crucial for targeting conservation efforts. Commonly, such forecasts are made based on conservation status assessments produced by the International Union for Conservation of Nature (IUCN). However, when researchers apply these IUCN conservation status data for predicting future extinctions, important information is often omitted, which can impact the accuracy of these predictions. Here we present a new approach and a software for simulating future extinctions based on IUCN conservation status information, which incorporates generation length information of individual species when modeling extinction risks. Additionally, we explicitly model future changes in conservation status for each species, based on status transition rates that we estimate from the IUCN assessment history of the last decades. Finally, we apply a Markov chain Monte Carlo algorithm to estimate extinction rates for each species, based on the simulated future extinctions. These estimates inherently incorporate the chances of conservation status changes and the generation length for each given species and are specific to the simulated time frame. We demonstrate the utility of our approach by estimating future extinction rates for all bird species. Our average extinction rate estimate for the next 100 yr across all birds is 6.98 × 10−4 extinctions per species‐year, and we predict an expected biodiversity loss of between 669 and 738 bird species within that time frame. Further, the rate estimates between species sharing the same IUCN status show larger variation than the rates estimated with alternative approaches, which reflects expected differences in extinction risk among taxa of the same conservation status. Our method demonstrates the utility of applying species‐specific information to the estimation of extinction rates, rather than assuming equal extinction risks for species assigned to the same conservation status.