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

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

doi:10.1111/ecog.05110

Tobias Andermann, Alexandre Antonelli + Show 3 more

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https://doi.org/10.1111/ecog.05110

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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.

Highlights

We are in the middle of a massive biodiversity crisis (Barnosky et al 2011, Davis et al 2018, Díaz et al 2019)
We argue that including Generation length (GL) should be the standard practice when modeling extinction risks based on International Union for Conservation of Nature (IUCN) data, because
We describe our approach of simulating future extinctions and IUCN status transitions on the example of birds (Aves)

Summary

Introduction

We are in the middle of a massive biodiversity crisis (Barnosky et al 2011, Davis et al 2018, Díaz et al 2019). Extinction risks have been steadily increasing for as long as we have been keeping record, with no indications of a slowdown (Ceballos et al 2015). It is crucial to predict the number of future extinctions that shape the future biodiversity, whether in terms of species, phylogenetic, or functional diversity (Davis et al 2018, Cooke et al.2019, Pimiento et al 2020). An important use of such predictions is to aid conservation prioritization (Mooers et al 2008). All predictions require reliable estimates of extinction risk. The main global initiative to quantify extinction risks across animal and plant species is the IUCN Red List (IUCN Red List 2019), which categorizes the conservation status of organisms based on expert assessments. Since 2001, the IUCN has adopted the IUCN v3.1 evaluation system for determining species' conservation statuses

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