Environmental science: estimating carbon stocks in dryland trees in Africa | Nature | Nature Portfolio

Research Press Release


Nature

March 2, 2023

Environmental sciences: Estimating the carbon stocks of trees in African drylands

A study of trees (regarding 10 billion trees) in semi-arid sub-Saharan Africa provides detailed estimates of carbon stocks in this ecosystem, reports a paper. ,Naturewill be published in The data, compiled from more than 300,000 satellite images, will help advance our understanding of the carbon cycle and provide useful information for scientists, policy makers, dryland restorers and farmers. can be a resource.

Trees provide various benefits to the ecosystem. For example, they provide refuge for animals, provide food for animals, contribute to the economy, and play an important role in the carbon cycle and climate system. These roles are particularly important in dryland ecosystems. Detailed data on dryland trees are important and scarce for efforts such as climate change mitigation, carbon accounting, and ecosystem protection and restoration.

In this study, Compton Tucker and colleagues address this record gap, assessing more than 9.9 billion trees on approximately 10 million square kilometers of land in semi-arid sub-Saharan and north-equatorial Africa. clarified. A machine-learning approach was used to scrutinize high-resolution satellite imagery (326,523 points) to identify and map individual trees. As a result, they were able to estimate the amount of carbon stored in the leaves, timber and roots of individual trees. Carbon stock estimates are for ultra-arid regions (0-150 mm annual precipitation), arid regions (150-300 mm annual precipitation), semi-arid regions (300-600 mm annual precipitation), and dry semi-humid regions. (600-1000 mm annual rainfall). The average carbon stock of a tree was 51 kg carbon in ultra-arid regions, 63 kg carbon in dry regions, 72 kg carbon in semi-arid regions, and 98 kg carbon in semi-humid regions. Many previous studies have used different models to estimate carbon stocks in trees in the same target areas, but most of them overestimate the results.

doi:10.1038/s41586-022-05653-6

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