Small persistent humid forest clearings drive tropical forest biomass losses

  • Pan, Y. et al. The enduring world forest carbon sink. Nature 631, 563–569 (2024).

    Article 
    ADS 
    PubMed 
    CAS 

    Google Scholar
     

  • Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A. & Hansen, M. C. Classifying drivers of global forest loss. Science 361, 1108–1111 (2018).

    Article 
    ADS 
    PubMed 
    CAS 

    Google Scholar
     

  • Feng, Y. et al. Doubling of annual forest carbon loss over the tropics during the early twenty-first century. Nat. Sustain. 5, 444–451 (2022).

    Article 

    Google Scholar
     

  • Aragão, L. E. O. C. & Shimabukuro, Y. E. The incidence of fire in Amazonian forests with implications for REDD. Science 328, 1275–1278 (2010).

    Article 
    ADS 
    PubMed 

    Google Scholar
     

  • Asner, G. P. et al. Selective logging in the Brazilian Amazon. Science 310, 480–482 (2005).

    Article 
    ADS 
    PubMed 
    CAS 

    Google Scholar
     

  • Silva Junior, C. H. et al. Persistent collapse of biomass in Amazonian forest edges following deforestation leads to unaccounted carbon losses. Sci. Adv. 6, eaaz8360 (2020).

    Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Zhu, L. et al. Comparable biophysical and biogeochemical feedbacks on warming from tropical moist forest degradation. Nat. Geosci. 16, 244–249 (2023).

    Article 
    ADS 
    CAS 

    Google Scholar
     

  • Poorter, L. et al. Multidimensional tropical forest recovery. Science 374, 1370–1376 (2021).

    Article 
    ADS 
    PubMed 
    CAS 

    Google Scholar
     

  • Long, T. et al. 30 m resolution global annual burned area mapping based on Landsat images and Google Earth Engine. Remote Sens. 11, 489 (2019).

  • Vancutsem, C. et al. Long-term (1990–2019) monitoring of forest cover changes in the humid tropics. Sci. Adv. 7, eabe1603 (2021).

    Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Bourgoin, C. et al. Human degradation of tropical moist forests is greater than previously estimated. Nature 631, 570–576 (2024).

    Article 
    ADS 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • Bullock, E. L., Woodcock, C. E., Souza, C. Jr. & Olofsson, P. Satellite-based estimates reveal widespread forest degradation in the Amazon. Glob. Change Biol. 26, 2956–2969 (2020).

    Article 
    ADS 

    Google Scholar
     

  • Baccini, A. et al. Tropical forests are a net carbon source based on aboveground measurements of gain and loss. Science 358, 230–234 (2017).

    Article 
    ADS 
    MathSciNet 
    PubMed 
    CAS 

    Google Scholar
     

  • Pugh, T. A. M. et al. Role of forest regrowth in global carbon sink dynamics. Proc. Natl Acad. Sci. USA 116, 4382–4387 (2019).

    Article 
    ADS 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • Cook-Patton, S. C. et al. Mapping carbon accumulation potential from global natural forest regrowth. Nature 585, 545–550 (2020).

    Article 
    ADS 
    PubMed 
    CAS 

    Google Scholar
     

  • Heinrich, V. H. A. et al. Large carbon sink potential of secondary forests in the Brazilian Amazon to mitigate climate change. Nat. Commun. 12, 1785 (2021).

    Article 
    ADS 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • Moreno-Mateos, D. et al. Anthropogenic ecosystem disturbance and the recovery debt. Nat. Commun. 8, 14163 (2017).

    Article 
    ADS 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • Gao, X. et al. The importance of distinguishing between natural and managed tree cover gains in the moist tropics. Nat. Commun. 16, 6092 (2025).

    Article 
    ADS 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • Robinson, N. et al. Protect young secondary forests for optimum carbon removal. Nat. Clim. Change 15, 793–800 (2025).

    Article 
    ADS 

    Google Scholar
     

  • Lapola, D. M. et al. The drivers and impacts of Amazon forest degradation. Science 379, eabp8622 (2023).

    Article 
    PubMed 
    CAS 

    Google Scholar
     

  • Muller-Landau, H. C. et al. Patterns and mechanisms of spatial variation in tropical forest productivity, woody residence time, and biomass. New Phytol. 229, 3065–3087 (2021).

    Article 
    PubMed 

    Google Scholar
     

  • Chazdon, R. L. Tropical forest recovery: legacies of human impact and natural disturbances. Perspect. Plant Ecol. Evol. Syst. 6, 51–71 (2003).

    Article 

    Google Scholar
     

  • Cushman, K. C. et al. Impact of a tropical forest blowdown on aboveground carbon balance. Sci. Rep. 11, 11279 (2021).

    Article 
    ADS 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • Poorter, L. et al. Biomass resilience of Neotropical secondary forests. Nature 530, 211–214 (2016).

    Article 
    ADS 
    PubMed 
    CAS 

    Google Scholar
     

  • Chen, N. et al. Revealing the spatial variation in biomass uptake rates of Brazil’s secondary forests. ISPRS J. Photogramm. Remote Sens. 208, 233–244 (2024).

    Article 
    ADS 

    Google Scholar
     

  • Heinrich, V. H. A. et al. The carbon sink of secondary and degraded humid tropical forests. Nature 615, 436–442 (2023).

    Article 
    ADS 
    PubMed 
    CAS 

    Google Scholar
     

  • Holcomb, A., Mathis, S. V., Coomes, D. A. & Keshav, S. Computational tools for assessing forest recovery with GEDI shots and forest change maps. Sci. Remote Sens. 8, 100106 (2023).

    Article 

    Google Scholar
     

  • Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).

    Article 
    ADS 
    PubMed 
    CAS 

    Google Scholar
     

  • Csillik, O. et al. A large net carbon loss attributed to anthropogenic and natural disturbances in the Amazon arc of deforestation. Proc. Natl Acad. Sci. USA 121, e2310157121 (2024).

    Article 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • Feng, Y. et al. Global patterns and drivers of tropical aboveground carbon changes. Nat. Clim. Change 14, 1064–1070 (2024).

    Article 
    ADS 

    Google Scholar
     

  • Hubau, W. et al. Asynchronous carbon sink saturation in African and Amazonian tropical forests. Nature 579, 80–87 (2020).

    Article 
    ADS 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • Qie, L. et al. Long-term carbon sink in Borneo’s forests halted by drought and vulnerable to edge effects. Nat. Commun. 8, 1966 (2017).

    Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Wulder, M. A. et al. The global Landsat archive: status, consolidation, and direction. Remote Sens. Environ. 185, 271–283 (2016).

    Article 
    ADS 

    Google Scholar
     

  • Masolele, R. N. et al. Mapping the diversity of land uses following deforestation across Africa. Sci. Rep. 14, 1681 (2024).

    Article 
    ADS 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • Zhao, Z. et al. Central African biomass carbon losses and gains during 2010–2019. One Earth 7, 506–519 (2024).

    Article 

    Google Scholar
     

  • Song, X.-P., Huang, C., Saatchi, S. S., Hansen, M. C. & Townshend, J. R. Annual carbon emissions from deforestation in the Amazon Basin between 2000 and 2010. PLoS ONE 10, e0126754 (2015).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Xu, Y. et al. Recent expansion of oil palm plantations into carbon-rich forests. Nat. Sustain. 5, 574–577 (2022).

    Article 

    Google Scholar
     

  • Espírito-Santo, F. D. B. et al. Size and frequency of natural forest disturbances and the Amazon forest carbon balance. Nat. Commun. 5, 3434 (2014).

    Article 
    ADS 
    PubMed 

    Google Scholar
     

  • Cochrane, M. A. & Laurance, W. F. Synergisms among fire, land use, and climate change in the Amazon. AMBIO 37, 522–527 (2008).

    Article 
    ADS 
    PubMed 

    Google Scholar
     

  • Silvestrini, R. A. et al. Simulating fire regimes in the Amazon in response to climate change and deforestation. Ecol. Appl. 21, 1573–1590 (2011).

    Article 
    PubMed 

    Google Scholar
     

  • Saito, M. et al. Fire regimes and variability in aboveground woody biomass in miombo woodland. J. Geophys. Rese. Biogeosci. 119, 1014–1029 (2014).

    Article 
    ADS 

    Google Scholar
     

  • Hansis, E., Davis, S. J. & Pongratz, J. Relevance of methodological choices for accounting of land use change carbon fluxes. Glob. Biogeochem. Cycles 29, 1230–1246 (2015).

    Article 
    ADS 
    CAS 

    Google Scholar
     

  • Houghton, R. & Nassikas, A. A. Global and regional fluxes of carbon from land use and land cover change 1850–2015. Glob. Biogeochem. Cycles 31, 456–472 (2017).

    Article 
    ADS 
    CAS 

    Google Scholar
     

  • Grassi, G. et al. Reconciling global-model estimates and country reporting of anthropogenic forest CO2 sinks. Nat. Clim. Change 8, 914–920 (2018).

    Article 
    ADS 
    CAS 

    Google Scholar
     

  • Achard, F. et al. Determination of tropical deforestation rates and related carbon losses from 1990 to 2010. Glob. Change Biol. 20, 2540–2554 (2014).

    Article 
    ADS 

    Google Scholar
     

  • Harris, N. L. et al. Global maps of twenty-first century forest carbon fluxes. Nat. Clim. Change 11, 234–240 (2021).

    Article 
    ADS 

    Google Scholar
     

  • Pearson, T. R. H., Brown, S., Murray, L. & Sidman, G. Greenhouse gas emissions from tropical forest degradation: an underestimated source. Carbon Balance Manag. 12, 3 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Xu, L. et al. Changes in global terrestrial live biomass over the 21st century. Sci. Adv. 7, eabe9829 (2021).

    Article 
    ADS 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • Khairoun, A., Mouillot, F., Chen, W., Ciais, P. & Chuvieco, E. Coarse-resolution burned area datasets severely underestimate fire-related forest loss. Sci. Total Environ. 920, 170599 (2024).

    Article 
    PubMed 
    CAS 

    Google Scholar
     

  • Dalagnol, R. et al. Mapping tropical forest degradation with deep learning and Planet NICFI data. Remote Sens. Environ. 298, 113798 (2023).

    Article 

    Google Scholar
     

  • Dupuis, C., Fayolle, A., Bastin, J.-F., Latte, N. & Lejeune, P. Monitoring selective logging intensities in central Africa with Sentinel-1: a canopy disturbance experiment. Remote Sens. Environ. 298, 113828 (2023).

    Article 

    Google Scholar
     

  • Slagter, B. et al. Monitoring direct drivers of small-scale tropical forest disturbance in near real-time with Sentinel-1 and -2 data. Remote Sens. Environ. 295, 113655 (2023).

    Article 

    Google Scholar
     

  • Alencar, A. A. C. et al. Long-term Landsat-based monthly burned area dataset for the Brazilian biomes using deep learning. Remote Sens. 14, 2510 (2022).

    Article 
    ADS 

    Google Scholar
     

  • Santoro, M. et al. Design and performance of the Climate Change Initiative Biomass global retrieval algorithm. Sci. Remote Sens. 10, 100169 (2024).

    Article 

    Google Scholar
     

  • Enright, N. J., Fontaine, J. B., Bowman, D. M., Bradstock, R. A. & Williams, R. J. Interval squeeze: altered fire regimes and demographic responses interact to threaten woody species persistence as climate changes. Front. Ecol. Environ. 13, 265–272 (2015).

    Article 

    Google Scholar
     

  • Bennett, A. C. et al. Sensitivity of South American tropical forests to an extreme climate anomaly. Nat. Clim. Change 13, 967–974 (2023).

    Article 
    ADS 

    Google Scholar
     

  • Shapiro, A. et al. Small scale agriculture continues to drive deforestation and degradation in fragmented forests in the Congo Basin (2015–2020). Land Use Policy 134, 106922 (2023).

    Article 

    Google Scholar
     

  • Hansen, M. C., Stehman, S. V. & Potapov, P. V. Quantification of global gross forest cover loss. Proc. Natl Acad. Sci. USA 107, 8650 (2010).

    Article 
    ADS 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • Ferro, P. D. et al. Regional-scale assessment of burn scar mapping in southwestern Amazonia using burned area products and CBERS/WFI data cubes. Fire 7, 67 (2024).

    Article 

    Google Scholar
     

  • Pessôa, A. C. M. et al. Intercomparison of burned area products and its implication for carbon emission estimations in the Amazon. Remote Sens. 12, 3864 (2020).

    Article 
    ADS 

    Google Scholar
     

  • van Wees, D. et al. Global biomass burning fuel consumption and emissions at 500 m spatial resolution based on the Global Fire Emissions Database (GFED). Geosci. Model Dev. 15, 8411–8437 (2022).

    Article 
    ADS 

    Google Scholar
     

  • Potapov, P. et al. Mapping global forest canopy height through integration of GEDI and Landsat data. Remote Sens. Environ. 253, 112165 (2021).

    Article 

    Google Scholar
     

  • Santoro, M. & Cartus, O. ESA Biomass Climate Change Initiative (Biomass_cci): global datasets of forest above-ground biomass for the years 2010, 2017, 2018, 2019 and 2020, v4. NERC EDS Centre for Environmental Data Analysis https://doi.org/10.5285/af60720c1e404a9e9d2c145d2b2ead4e (2023).

  • Petersson, H. et al. Individual tree biomass equations or biomass expansion factors for assessment of carbon stock changes in living biomass—a comparative study. For. Ecol. Manag. 270, 78–84 (2012).

    Article 

    Google Scholar
     

  • Potapov, P. et al. The last frontiers of wilderness: tracking loss of intact forest landscapes from 2000 to 2013. Sci. Adv. 3, e1600821 (2017).

    Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Hartung, M., Carreño-Rocabado, G., Peña-Claros, M. & van der Sande, M. T. Tropical dry forest resilience to fire depends on fire frequency and climate. Front. For. Glob. Change 4, 755104 (2021).

  • Nguyen, T. V. et al. Human-driven fire regime change in the seasonal tropical forests of central Vietnam. Geophys. Res. Lett. 50, e2022GL100687 (2023).

    Article 
    ADS 

    Google Scholar
     

  • Senf, C. & Seidl, R. Post-disturbance canopy recovery and the resilience of Europe’s forests. Glob. Ecol. Biogeogr. 31, 25–36 (2022).

    Article 

    Google Scholar
     

  • Fawcett, D. et al. Declining Amazon biomass due to deforestation and subsequent degradation losses exceeding gains. Glob. Change Biol. 29, 1106–1118 (2023).

    Article 
    ADS 
    CAS 

    Google Scholar
     

  • Giardina, C. P. Advancing our understanding of woody debris in tropical forests. Ecosystems 22, 1173–1175 (2019).

    Article 

    Google Scholar
     

  • Harmon, M. E. et al. Release of coarse woody detritus-related carbon: a synthesis across forest biomes. Carbon Balance Manag. 15, 1 (2020).

    Article 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • Zanne, A. E. et al. Termite sensitivity to temperature affects global wood decay rates. Science 377, 1440–1444 (2022).

    Article 
    ADS 
    PubMed 
    CAS 

    Google Scholar
     

  • Parton, W. J., Stewart, J. W. B. & Cole, C. V. Dynamics of C, N, P and S in grassland soils: a model. Biogeochemistry 5, 109–131 (1988).

    Article 
    CAS 

    Google Scholar
     

  • Ometto, J. P. et al. A biomass map of the Brazilian Amazon from multisource remote sensing. Sci. Data 10, 668 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Rodda, S. R. et al. LiDAR-based reference aboveground biomass maps for tropical forests of South Asia and Central Africa. Sci. Data 11, 334 (2024).

    Article 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • Xu, Y. Small persistent clearings in humid forests drive tropical forest biomass carbon losses. Zenodo https://doi.org/10.5281/zenodo.15869647 (2025).



  • ■ مصدر الخبر الأصلي

    نشر لأول مرة على: www.nature.com

    تاريخ النشر: 2026-01-07 02:00:00

    الكاتب: Yidi Xu

    تنويه من موقع “yalebnan.org”:

    تم جلب هذا المحتوى بشكل آلي من المصدر:
    www.nature.com
    بتاريخ: 2026-01-07 02:00:00.
    الآراء والمعلومات الواردة في هذا المقال لا تعبر بالضرورة عن رأي موقع “yalebnan.org”، والمسؤولية الكاملة تقع على عاتق المصدر الأصلي.

    ملاحظة: قد يتم استخدام الترجمة الآلية في بعض الأحيان لتوفير هذا المحتوى.

    Exit mobile version