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. 2022 Nov 11;8(45):eabm9982.
doi: 10.1126/sciadv.abm9982. Epub 2022 Nov 9.

The direct drivers of recent global anthropogenic biodiversity loss

Pedro Jaureguiberry  1 , Nicolas Titeux  2   3   4 , Martin Wiemers  2   5 , Diana E Bowler  3   6   7 , Luca Coscieme  8 , Abigail S Golden  9   10 , Carlos A Guerra  3   11 , Ute Jacob  12   13 , Yasuo Takahashi  14 , Josef Settele  2   3   15 , Sandra Díaz  1 , Zsolt Molnár  16 , Andy Purvis  17   18
Affiliations

The direct drivers of recent global anthropogenic biodiversity loss

Pedro Jaureguiberry et al. Sci Adv. .

Abstract

Effective policies to halt biodiversity loss require knowing which anthropogenic drivers are the most important direct causes. Whereas previous knowledge has been limited in scope and rigor, here we statistically synthesize empirical comparisons of recent driver impacts found through a wide-ranging review. We show that land/sea use change has been the dominant direct driver of recent biodiversity loss worldwide. Direct exploitation of natural resources ranks second and pollution third; climate change and invasive alien species have been significantly less important than the top two drivers. The oceans, where direct exploitation and climate change dominate, have a different driver hierarchy from land and fresh water. It also varies among types of biodiversity indicators. For example, climate change is a more important driver of community composition change than of changes in species populations. Stopping global biodiversity loss requires policies and actions to tackle all the major drivers and their interactions, not some of them in isolation.

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Figures

Fig. 1.
Fig. 1.. Dominance hierarchies of the five studied direct drivers of biodiversity loss.
(A) Overall hierarchy (N = 154 studies) and (B) hierarchies for terrestrial, marine, and freshwater realms. Area of the circle for each driver is proportional to its dominance score (20) (indicated inside with 95% confidence interval; possible range = 0 to 4). Arrows linking pairs of drivers show the significance of the dominance difference between them based on bootstrapping: Arrow thickness reflects unadjusted P values (thin: P < 0.1, intermediate: P < 0.05, thick: P < 0.01, no arrow: P ≥ 0.1), and arrow shading reflects P values adjusted for multiple testing (black: P < 0.05, gray: P ≥ 0.05). The central triangle in (B) reports the significance of differences in the among-driver dominance hierarchy between pairs of realms (***: randomization P < 0.001; *: P < 0.05; ns: P > 0.5). N gives numbers of studies available for the analysis within each realm. The steepness of the driver hierarchy also rejects the null hypothesis that all drivers have the same impact overall (steepness = 0.405, P = 0.0001), in the terrestrial realm (steepness = 0.465, P < 0.0001), and in the marine realm (steepness = 0.479, P < 0.001), but not in fresh water (steepness = 0.292, P = 0.13).
Fig. 2.
Fig. 2.. Land/sea use change and direct exploitation are the main drivers in all regions.
Area of the circle for each driver is proportional to its dominance score (20) (indicated inside with 95% confidence interval; possible range = 0 to 4) within each IPBES region. Arrows linking pairs of drivers show the significance of the dominance difference between them based on bootstrapping: Arrow thickness reflects unadjusted P values (thin: P < 0.1, intermediate: P < 0.05, thick: P < 0.01, no arrow: P ≥ 0.1), and arrow shading reflects P values adjusted for multiple testing (black: P < 0.05, gray: P ≥ 0.05). N gives numbers of studies available for the analysis within each region.
Fig. 3.
Fig. 3.. The main drivers of biodiversity loss differ among the six EBV classes.
Area of the circle for each driver is proportional to its dominance score (20) indicated inside the circle (possible range = 0 to 4). One-way arrows linking pairs of drivers show the significance of the dominance difference between them based on bootstrapping. Two-way arrows between EBV classes indicate significant pairwise differences in their driver dominance hierarchies based on randomization tests. For all arrows, thickness reflects unadjusted P values (thick: P < 0.01, intermediate: P < 0.05, thin: P < 0.1, no arrow: P ≥ 0.1) and shading reflects P values adjusted for multiple testing (black: P < 0.05, gray: P ≥ 0.05). N gives numbers of studies available for the analysis within each EBV class. The question mark indicates the very uncertain rankings for genetic composition because of small sample size. EBV class icons created by C. Gutiérrez of the Humboldt Institute (Bogotá, Colombia) for GEO BON.
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