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. 2025 Jul 1;16(1):5561.
doi: 10.1038/s41467-025-60662-z.

Mapping previously undetected trees reveals overlooked changes in pan-tropical tree cover

Shidong Liu #  1   2   3 , Jie Zhang #  2   4 , Li Wang  5 , Philippe Ciais  6 , Jianjun Zhang  7 , Josep Penuelas  8   9 , Biswajit Nath  10 , Iskid Jacquet  2 , Xia Wu  11 , Shengping Ding  3 , Wang Li  1 , Ni Huang  1 , Wanjuan Song  1 , WenJian Ni  1 , Zheng Niu  1
Affiliations

Mapping previously undetected trees reveals overlooked changes in pan-tropical tree cover

Shidong Liu et al. Nat Commun. .

Abstract

Detecting tree cover is crucial for sustainable land management and climate mitigation. Here we develop an automatic detection algorithm using high-resolution satellite data (<5 m) to map pan-tropical tree cover (2015-2022), enabling identification and change analysis for previously undetected tree cover (PUTC). Our findings reveal that neglecting PUTC represents 17.31 ± 1.78% of the total pan-tropical tree cover. Tree cover net decreased by 61.05 ± 2.36 Mha in both forested areas (63.93%) and non-forested areas (36.07%) between 2015 and 2022. Intense changes in tree cover are primarily observed in regions with PUTC, where the World Cover dataset with a resolution of 10 m often fails to accurately detect tree cover. We also conduct a sensitivity analysis to quantify the contributions f climate factors and anthropogenic impacts (including human activities and land use cover change) to tree cover dynamics. Our findings indicate that 43.98% of tree cover gain is linked to increased precipitation, while 56.03% of tree cover loss is associated with anthropogenic impacts. These findings highlight the need to include undetected tree cover in strategies combating degradation, climate change, and promoting sustainability. Fine-scale mapping can improve biogeochemical cycles modeling and vegetation-climate interactions, improving global change understanding.

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Conflict of interest statement

Competing interests: The authors declare no competing interests

Figures

Fig. 1
Fig. 1. pan-tropical tree cover.
a and b represent the spatial distribution of pan-tropical tree cover and that in different grid types, respectively. c is the proportion of pan-tropical tree cover in different grid types in different regions. Data for this figure are available at Zenodo (10.5281/zenodo.14892757).
Fig. 2
Fig. 2. Distribution of high-resolution PUTC.
a is the spatial distribution of the proportion of PUTC. b is the PUTC of a typical regional case. Data for this figure are available at Zenodo (10.5281/zenodo.14892757).
Fig. 3
Fig. 3. The spatiotemporal change of tree cover.
a is the change of tree cover in different grid types from 2015 to 2022. b is the spatial distribution of tree cover changes. c is the change in tree cover in different regions from 2015 to 2022. d is the contribution of non-forest grids to the change of tree cover. Data for this figure are available at Zenodo (10.5281/zenodo.14892757).
Fig. 4
Fig. 4. The contribution of driving factors for changes in tree cover.
a is the relationship between the change of tree cover and the proportion of PUTC in pan-tropical, where the directions of the arrows represent the offset direction of the average coordinates of the samples in a specific grid type relative to the coordinate origin (0, 0), representing the main location of the samples of that type. b−f represents the relationship between the proportion of tree cover changes and the proportion of PUTC within different types of grids. g shows the contributions of human activities, climate change, and LUCC to the changes in tree cover in the pan-tropical region. This result was calculated from 61 independent samples selected at different spatial locations in the tropics. Data are presented as mean values ± SD. Data for this figure are available at Zenodo (10.5281/zenodo.14892757).
Fig. 5
Fig. 5. Automatic detection algorithm for tree crown.
Data for this figure are available at Zenodo (10.5281/zenodo.14892757).
See this image and copyright information in PMC

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