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. 2024 Apr 5;10(14):eadl0335.
doi: 10.1126/sciadv.adl0335. Epub 2024 Apr 3.

Threat of mining to African great apes

Jessica Junker  1   2   3 , Luise Quoss  1   2 , Jose Valdez  1   2 , Mimi Arandjelovic  2   4 , Abdulai Barrie  5 , Geneviève Campbell  3 , Stefanie Heinicke  6 , Tatyana Humle  3   7 , Célestin Y Kouakou  8   9 , Hjalmar S Kühl  2   10   11 , Isabel Ordaz-Németh  3   10 , Henrique M Pereira  1   2   12 , Helga Rainer  13 , Johannes Refisch  14 , Laura Sonter  15   16   17 , Tenekwetche Sop  3   10
Affiliations

Threat of mining to African great apes

Jessica Junker et al. Sci Adv. .

Abstract

The rapid growth of clean energy technologies is driving a rising demand for critical minerals. In 2022 at the 15th Conference of the Parties to the Convention on Biological Diversity (COP15), seven major economies formed an alliance to enhance the sustainability of mining these essential decarbonization minerals. However, there is a scarcity of studies assessing the threat of mining to global biodiversity. By integrating a global mining dataset with great ape density distribution, we estimated the number of African great apes that spatially coincided with industrial mining projects. We show that up to one-third of Africa's great ape population faces mining-related risks. In West Africa in particular, numerous mining areas overlap with fragmented ape habitats, often in high-density ape regions. For 97% of mining areas, no ape survey data are available, underscoring the importance of increased accessibility to environmental data within the mining sector to facilitate research into the complex interactions between mining, climate, biodiversity, and sustainability.

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Figures

Fig. 1.
Fig. 1.. Schematic overview of the approximate potential direct (10 km) and indirect threats (50 km) on apes linked to mining activities.
Expected high and moderate to lower risk of impact is indicated by red and yellow pointers, respectively.
Fig. 2.
Fig. 2.. Spatial distribution of mining and ape density.
Bivariate choropleth showing the relationship between mining density (using 50-km buffers around mining locations) and ape density in (A) West Africa (operational = 18.4%; preoperational = 81.6%), in (B) Central Africa (operational = 8.3%; preoperational = 91.7%), and in (C) East Africa (operational = 12.2%; preoperational = 87.8%). Each color change indicates a 20% quintile change in mining and ape density. Lower bounds for both mining and ape density are indicated in the color matrix.
Fig. 3.
Fig. 3.. Box plots comparing the average difference in randomly selected samples of ape densities between areas within a 10-km buffer of preoperational and operational mining areas and randomly selected nonmining areas across countries in West Africa, Central Africa, and East Africa.
The dotted line indicates no difference between these areas. Values above the dotted line indicate that mining areas are located more often in areas with high than low ape densities and vice versa. Nigeria and Rwanda are excluded as they do not include pixels that occur inside the ape range. Significant differences are marked with an asterisk (*P < 0.01, **P < 0.001). WA, West Africa; CA, Central Africa; EA, East Africa.
Fig. 4.
Fig. 4.. Overlap between ape density distribution and mining areas in Africa.
(A) Proportion of ape population threatened by mining (operational and preoperational mining areas) with a 10-km buffer (dark shades) and with a 50-km buffer (light shades) for range countries in the different regions. Total regional estimates of the proportion of ape populations threatened by mining in (B) West Africa, in (C) Central Africa, and in (D) East Africa.
See this image and copyright information in PMC

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