ArticleScientific data2025
A dataset of forest regrowth in globally key deforestation regions.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- A dataset of forest regrowth in globally key deforestation regions.Scientific data · 2025Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Deforestation-induced forest loss largely affects both the carbon budget and ecosystem services. Subsequent forest regrowth plays a crucial role in ecosystem restoration and carbon replenishment. However, there is an absence of comprehensive datasets explicitly delineating the forest regrowth following deforestation. Here we employed multiple remotely sensed datasets to generate the first dataset capturing forest structural regrowth, including forest height, aboveground biomass (AGB), leaf area index (LAI), and fraction of photosynthetically active radiation (FPAR), subsequent to deforestation in globally key deforestation regions at a 30 m spatial resolution. The regrowth index for each structural parameter includes regrowth ratios and rates at 5-year intervals spanning primarily from 1985 to 2020. This dataset provides a nuanced understanding of forest regrowth following deforestation across spatial, temporal, and structural scales, thereby facilitating accurate quantification of forest carbon budget and enhancing assessments of forest ecological services.
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