Abstract
Climate change reshapes forest biophysical effects, yet the impact direction and strength remain uncertain. Here we quantify the growing-season land surface temperature between forests and adjacent open land (∆LSTgs) and show contrasting temporal trends in ∆LSTgs across the globe during 2001–2023. Rising vapour pressure deficit (VPD) has emerged as the primary driver of these contrasting trends, surpassing other common climatic factors. By contrast, plant anisohydricity—an indicator of stomatal regulation behaviour—is the most important forest trait that negatively modulates the strength of the ∆LSTgs response to VPD variability. At low latitudes, forests are more isohydric, and rising VPD has exceeded the hydraulic safety margin, resulting in weakened cooling. Conversely, high-latitude forests are more anisohydric; VPD remains below the safety margin, and rising VPD thus leads to enhanced cooling. These results highlight that the overall climate benefits of global forests may be undermined if global VPD continues to intensify in future.
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Amplified local cooling effect of forestation in warming Europe
Data availability
The global VOD, LST, NDVI, VPD, WS, SW, Pre, SM, Tmin, Tmax, Tmean, tree height, tree cover, tree age, AGB, forest types, tree richness, LAI, root depth, SN, SOC and SCC data used for the analyses in this study are available online as follows. LPRM AMSR-E VOD: https://disc.gsfc.nasa.gov/datasets/LPRM_AMSRE_A_SOILM3_002/summary, https://disc.gsfc.nasa.gov/datasets/LPRM_AMSRE_D_SOILM3_002/summary, https://disc.gsfc.nasa.gov/datasets/LPRM_AMSR2_A_SOILM3_001/summary, https://disc.gsfc.nasa.gov/datasets/LPRM_AMSR2_D_SOILM3_001/summary; IMERG Precipitation: https://gpm.nasa.gov/data/directory; MOD11C3 LST product: https://lpdaac.usgs.gov/products/mod11c3v061/; TerraClimate VPD, SW, PRE, SM, Tmin, Tmax, Tmean product: https://www.climatologylab.org/terraclimate.html; CO2 product https://db.cger.nies.go.jp/dataset/ODIAC/DL_odiac2024.html; tree height product: https://glad.umd.edu/dataset/gedi/; tree cover product: https://glad.earthengine.app/view/global-forest-change; MOD13C2 NDVI product: https://lpdaac.usgs.gov/products/mod13c2v061/; above-ground biomass product: https://climate.esa.int/en/projects/biomass/data/; MCD12C1 forest type product: https://lpdaac.usgs.gov/products/mcd12c1v061/; MCD15A2H LAI product: https://www.earthdata.nasa.gov/data/catalog/lpcloud-mcd15a2h-061; SoilGrids SN, SCC, SOC: https://files.isric.org/soilgrids/latest/; tree richness dataset: https://doi.org/10.6084/m9.figshare.20055488 (ref. 71); tree age dataset: https://essd.copernicus.org/articles/13/4881/2021/; root depth dataset: https://github.com/yalingliu-cu/plant-strategies; MCD43C3 albedo product: https://lpdaac.usgs.gov/products/mcd43c3v061/; MOD16A2 LE product: https://lpdaac.usgs.gov/products/mod16a2v061/. Other source data used for this analysis are available via Zenodo at https://doi.org/10.5281/zenodo.2017425 (ref. 84). Source data are provided with this paper.
Code availability
The code used for this analysis is available via Zenodo at https://doi.org/10.5281/zenodo.20174250 (ref. 84).
References
Bonan, G. B. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449 (2008).
Google Scholar
Li, Y. et al. Local cooling and warming effects of forests based on satellite observations. Nat. Commun. 6, 6603 (2015).
Google Scholar
Su, Y. et al. Asymmetric influence of forest cover gain and loss on land surface temperature. Nat. Clim. Change 13, 823–831 (2023).
Google Scholar
Alkama, R. & Cescatti, A. Biophysical climate impacts of recent changes in global forest cover. Science 351, 600–604 (2016).
Google Scholar
Lee, X. et al. Observed increase in local cooling effect of deforestation at higher latitudes. Nature 479, 384–387 (2011).
Google Scholar
Mahmood, R. et al. Land cover changes and their biogeophysical effects on climate. Int. J. Climatol. 34, 929–953 (2014).
Google Scholar
Claussen, M., Brovkin, V. & Ganopolski, A. Biogeophysical versus biogeochemical feedbacks of large-scale land cover change. Geophys. Res. Lett. 28, 1011–1014 (2001).
Google Scholar
Kan, F. et al. Diminished biophysical cooling benefits of global forestation under rising atmospheric CO2. Nat. Commun. 16, 4410 (2025).
Google Scholar
Alkama, R. et al. Vegetation-based climate mitigation in a warmer and greener world. Nat. Commun. 13, 606 (2022).
Google Scholar
Ge, J. et al. Local surface cooling from afforestation amplified by lower aerosol pollution. Nat. Geosci. 16, 781–788 (2023).
Google Scholar
Li, Y. et al. Amplified local cooling effect of forestation in warming Europe. Nat. Commun. 16, 8412 (2025).
Google Scholar
Oren, R. et al. Survey and synthesis of intra- and interspecific variation in stomatal sensitivity to vapour pressure deficit. Plant Cell Environ. 22, 1515–1526 (1999).
Google Scholar
Konings, A. G., Williams, A. P. & Gentine, P. Sensitivity of grassland productivity to aridity controlled by stomatal and xylem regulation. Nat. Geosci. 10, 284–288 (2017).
Google Scholar
Yuan, W. et al. Impacts of rising atmospheric dryness on terrestrial ecosystem carbon cycle. Nat. Rev. Earth Environ. 6, 712–727 (2025).
Google Scholar
Will, R. E., Wilson, S. M., Zou, C. B. & Hennessey, T. C. Increased vapor pressure deficit due to higher temperature leads to greater transpiration and faster mortality during drought for tree seedlings. New Phytol. 200, 366–374 (2013).
Google Scholar
Bachofen, C. et al. Stand structure of Central European forests matters more than climate for transpiration sensitivity to VPD. J. Appl. Ecol. 60, 886–897 (2023).
Google Scholar
Woodruff, D. R., Meinzer, F. C. & McCulloh, K. A. Height–related trends in stomatal sensitivity to leaf-to-air vapour pressure deficit in a tall conifer. J. Exp. Bot. 61, 203–210 (2010).
Google Scholar
Zhong, Z. et al. Disentangling the effects of vapor pressure deficit on northern terrestrial vegetation productivity. Sci. Adv. 9, eadf3166 (2023).
Google Scholar
Yan, W. et al. Differentiated influences of atmospheric dryness on urban plant cooling effect between temperate and tropical/subtropical zones. Urban Clim. 55, 101915 (2024).
Google Scholar
López, J., Way, D. A. & Sadok, W. Systemic effects of rising atmospheric vapor pressure deficit on plant physiology and productivity. Glob. Change Biol. 27, 1704–1720 (2021).
Google Scholar
Tardieu, F. Variability among species of stomatal control under fluctuating soil water status and evaporative demand. J. Exp. Bot. 49, 419–432 (1998).
Google Scholar
Garcia-Forner, N. et al. Responses of two semiarid conifer tree species to reduced precipitation and warming reveal new perspectives for stomatal regulation. Plant Cell Environ. 39, 38–49 (2016).
Google Scholar
Konings, A. G. & Gentine, P. Global variations in ecosystem-scale isohydricity. Glob. Change Biol. 23, 891–905 (2017).
Google Scholar
Li, Y. et al. Estimating global ecosystem isohydry/anisohydry using active and passive microwave satellite data. J. Geophys. Res. Biogeosci. 122, 3306–3321 (2017).
Google Scholar
Martínez–Vilalta, J. & Garcia–Forner, N. Water potential regulation, stomatal behaviour and hydraulic transport under drought. Plant Cell Environ. 40, 962–976 (2017).
Google Scholar
Bonan, G. B., Williams, M., Fisher, R. A. & Oleson, K. W. Modeling stomatal conductance in the earth system. Geosci. Model Dev. 7, 2193–2222 (2014).
Google Scholar
Roman, D. T. et al. The role of isohydric and anisohydric species in determining ecosystem-scale response to severe drought. Oecologia 179, 641–654 (2015).
Google Scholar
Su, Y. et al. Pervasive but biome-dependent relationship between fragmentation and resilience in forests. Nat. Ecol. Evol. 9, 1670–1684 (2025).
Google Scholar
Carter, G. A. Primary and secondary effects of water content on the spectral reflectance of leaves. Am. J. Bot. 78, 916–924 (1991).
Google Scholar
Sims, D. A. & Gamon, J. A. Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: a comparison of indices based on liquid water and chlorophyll absorption features. Remote Sens. Environ. 84, 526–537 (2003).
Google Scholar
Shaw, R. H. & Pereira, A. R. Aerodynamic roughness of a plant canopy: a numerical experiment. Agric. Meteorol. 26, 51–65 (1982).
Google Scholar
Raupach, M. R., Finnigan, J. J. & Brunei, Y. Coherent eddies and turbulence in vegetation canopies: the mixing-layer analogy. Boundary-Layer Meteorol. 78, 351–382 (1996).
Google Scholar
Zhang, C. et al. Seasonal and long-term dynamics in forest microclimate effects: global pattern and mechanism. npj Clim. Atmos. Sci. 6, 116 (2023).
Google Scholar
Pitman, A. J. et al. Importance of background climate in determining impact of land-cover change on regional climate. Nat. Clim. Change 1, 472–475 (2011).
Google Scholar
Seneviratne, S. I. et al. Investigating soil moisture–climate interactions in a changing climate: a review. Earth–Sci. Rev. 99, 125–161 (2010).
Google Scholar
Su, Y. et al. Quantifying the biophysical effects of forests on local air temperature using a novel three-layered land surface energy balance model. Environ. Int. 132, 105080 (2019).
Google Scholar
Schoppach, R. & Sadok, W. Differential sensitivities of transpiration to evaporative demand and soil water deficit among wheat elite cultivars. Environ. Exp. Bot. 84, 1–10 (2012).
Google Scholar
Medina, S. et al. The plant–transpiration response to vapor pressure deficit (VPD) in durum wheat. Front. Plant Sci. 9, 1107 (2019).
Google Scholar
Cernusak, L. A., Goldsmith, G. R., Arend, M. & Siegwolf, R. T. W. Effect of vapor pressure deficit on gas exchange in wild–type and abscisic acid-insensitive plants. Plant Physiol. 181, 1573–1586 (2019).
Google Scholar
Li, J. & Li, X. Response of stomatal conductance of two tree species to vapor pressure deficit in three climate zones. J. Arid Land 6, 771–781 (2014).
Google Scholar
Martínez-Vilalta, J. et al. A new look at water transport regulation in plants. New Phytol. 204, 105–115 (2014).
Google Scholar
Meinzer, F. C. et al. Mapping ‘hydroscapes’ along the iso- to anisohydric continuum of stomatal regulation of plant water status. Ecol. Lett. 19, 1343–1352 (2016).
Google Scholar
Novick, K. A., Konings, A. G. & Gentine, P. Beyond soil water potential: an expanded view on isohydricity including land–atmosphere interactions. Plant Cell Environ. 42, 1802–1815 (2019).
Google Scholar
Biederman, J. A. et al. CO2 exchange and evapotranspiration across dryland ecosystems of southwestern North America. Glob. Change Biol. 23, 4204–4221 (2017).
Google Scholar
Chen, C. et al. Biophysical impacts of Earth greening largely controlled by aerodynamic resistance. Sci. Adv. 6, eabb1981 (2020).
Google Scholar
Zeng, Z. et al. Climate mitigation from vegetation biophysical feedbacks during the past three decades. Nat. Clim. Change 7, 432–436 (2017).
Google Scholar
Winckler, J. et al. Nonlocal effects dominate the global mean surface temperature response to the biogeophysical effects of deforestation. Geophys. Res. Lett. 46, 745–755 (2019).
Google Scholar
Luo, X. et al. Local and nonlocal biophysical effects of historical land use and land cover change in CMIP6 models and the intermodel uncertainty. Earth’s Futur. 12, e2023EF004220 (2024).
Google Scholar
Friedl, M. & Sulla–Menashe, D. MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 0.05Deg CMG V061. NASA LP DAAC https://doi.org/10.5067/MODIS/MCD12C1.061 (2022).
Google Scholar
Potapov, P. et al. The global 2000–2020 land cover and land use change dataset derived from the Landsat archive: first results. Front. Remote Sens. 3, 856903 (2022).
Google Scholar
Wan, Z., Hook, S. & Hulley, G. MODIS/Terra Land Surface Temperature/Emissivity Monthly L3 Global 0.05Deg CMG V061. NASA LP DAAC https://doi.org/10.5067/MODIS/MOD11C3.061 (2021).
Google Scholar
Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).
Google Scholar
Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A. & Hegewisch, K. C. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci. Data 5, 170191 (2018).
Google Scholar
Oda, T. & Maksyutov, S. ODIAC Fossil Fuel CO2 Emissions Dataset (ODIAC2024). Center Glob. Environ. Res. NIES https://doi.org/10.17595/20170411.001 (2024).
Google Scholar
Ulmer, M., Scheidegger, C. & Bühlmann, P. Spectrally deconfounded random forests. J. Comput. Graph. Stat. 35, 758–768 (2025).
Google Scholar
Liu, P. et al. Quantile regression forests for predictor selection in standardized anomaly postprocessing. SOLA 21, 132–142 (2025).
Google Scholar
Hastie, T. J. Generalized additive models. in Statistical Models in S (ed Hastie, T. J.) 249–307 (Routledge, 2017).
Roberts, D. R. et al. Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure. Ecography 40, 913–929 (2017).
Google Scholar
Akaike, H. A new look at the statistical model identification. IEEE Trans. Autom. Control 19, 716–723 (1974).
Google Scholar
Berdugo, M. et al. Global ecosystem thresholds driven by aridity. Science 367, 787–790 (2020).
Google Scholar
Anderegg, W. R. L. et al. Meta-analysis reveals that hydraulic traits explain cross-species patterns of drought-induced tree mortality. Proc. Natl Acad. Sci. USA 113, 5024–5029 (2016).
Google Scholar
Franks, P. J., Drake, P. L. & Froend, R. H. Anisohydric but isohydrodynamic: seasonally constant plant water potential gradient. Plant Cell Environ. 30, 19–30 (2007).
Google Scholar
West, A. G. et al. Diverse functional responses to drought in a Mediterranean-type shrubland. New Phytol. 195, 396–407 (2012).
Google Scholar
Baba, K., Shibata, R. & Sibuya, M. Partial correlation and conditional correlation as measures of conditional independence. Aust. N. Z. J. Stat. 46, 657–664 (2004).
Google Scholar
Hoerl, A. E. & Kennard, R. W. Ridge regression: biased estimation for nonorthogonal problems. Technometrics 12, 55–67 (1970).
Google Scholar
Shen, P. et al. Biodiversity buffers the response of spring leaf unfolding to climate warming. Nat. Clim. Change 14, 863–868 (2024).
Google Scholar
Potapov, P. et al. Mapping and monitoring global forest canopy height through integration of GEDI and Landsat data. Remote Sens. Environ. 253, 112165 (2021).
Google Scholar
Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).
Google Scholar
Besnard, S. et al. Mapping global forest age from forest inventories, biomass and climate data. Earth Syst. Sci. Data 13, 4881–4896 (2021).
Google Scholar
Santoro, M. & Cartus, O. ESA Biomass Climate Change Initiative (Biomass_cci): global datasets of forest above–ground biomass, v6.0. Centre Environ. Data Anal. https://doi.org/10.5285/af60720c24404f329d31405f63659247 (2025).
Liang, J. et al. Co–limitation towards lower latitudes shapes global forest diversity gradients. Nat. Ecol. Evol. 6, 1423–1437 (2022).
Google Scholar
Myneni, R., Knyazikhin, Y. & Park, T. MODIS/Terra Leaf Area Index/FPAR 8-Day L4 Global 500 m SIN Grid V061. NASA LP DAAC https://doi.org/10.5067/MODIS/MOD15A2H.061 (2021).
Google Scholar
Liu, Y., Konings, A. G., Kennedy, D. & Gentine, P. Global coordination in plant physiological and rooting strategies in response to water stress. Glob. Biogeochem. Cycles 35, e2020GB006758 (2021).
Google Scholar
Poggio, L. et al. SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty. SOIL 7, 217–240 (2021).
Google Scholar
Peng, S. et al. Asymmetric effects of daytime and night-time warming on Northern Hemisphere vegetation. Nature 501, 88–92 (2013).
Google Scholar
Tibshirani, R. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B 58, 267–288 (1996).
Google Scholar
Duveiller, G., Hooker, J. & Cescatti, A. The mark of vegetation change on Earth’s surface energy balance. Nat. Commun. 9, 679 (2018).
Google Scholar
Zhang, M. et al. Response of surface air temperature to small-scale land clearing across latitudes. Environ. Res. Lett. 9, 034002 (2014).
Google Scholar
Luyssaert, S. et al. Land management and land-cover change have impacts of similar magnitude on surface temperature. Nat. Clim. Change 4, 389–393 (2014).
Google Scholar
Running, S., Mu, Q. & Zhao, M. MODIS/Terra Net Evapotranspiration 8-Day L4 Global 500 m SIN Grid V061. NASA LP DAAC https://doi.org/10.5067/MODIS/MOD16A2.061 (2021).
Google Scholar
O’Neill, B. C. et al. The scenario model intercomparison project (ScenarioMIP) for CMIP6. Geosci. Model Dev. 9, 3461–3482 (2016).
Google Scholar
Tebaldi, C. et al. Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6. Earth Syst. Dyn. 12, 253–293 (2021).
Google Scholar
Yang, X. et al. Amazon rainforests are rejuvenating their canopies by producing more photosynthetically efficient young leaves under climate change. Nat. Plants 12, 520–531 (2026).
Google Scholar
Zhang, C. Code to support ‘Globally constrained forest biophysical cooling benefits under rising atmospheric dryness’. Zenodo https://doi.org/10.5281/zenodo.20174250 (2026).
Acknowledgements
This study was supported by the National Natural Science Foundation of China (grant nos. 42225104 and 42471326), the Science and Technology Program of Guangdong (grant no. 2024B1212070012), the General Program of Guangdong Provincial Natural Science Foundation (grant no. 2024A1515012731) and the Chinese Academy of Sciences Project for Young Scientists in Basic Research (grant no. YSBR-086)
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Y.S. designed the study and wrote the initial manuscript; C.Z. collected the data, performed the analyses and wrote the initial manuscript; Z.L., W.Z., P.C., S.J., Y.W., J.L., J.C., S.Z., Y.Z., A.C., J.M.C., J.S., R.L., J.W., X.F., K.Y., W.Y. and X.C. reviewed and edited the manuscript. All authors contributed to the interpretation of the results and approved the final version of the manuscript.
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Nature Climate Change thanks Jun Ge and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Supplementary Figs. 1–19 and References.
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Source Data Fig. 1 (download XLSX )
Statistical source data for Fig. 1, including temporal trends in ΔLSTgs and VPD during 2001–2023, RF-based climate-variable importance scores, dominant-predictor percentages, partial dependence data and piecewise regression fits for the ΔLSTgs–VPD relationship, spatial estimates of SΔLSTgs_VPD, and grid-by-grid comparisons of SΔLSTgs_VPD below and above VPDcrit.
Source Data Fig. 2 (download XLSX )
Statistical source data for Fig. 2, including ecosystem-trait importance estimates from linear regression, ridge regression, partial correlation analysis and sequential regression; moving-window correlations between ecosystem anisohydricity and SΔLSTgs_VPD; and ΔLSTgs–VPD response curves across ecosystem anisohydricity bins.
Source Data Fig. 4 (download XLSX )
Statistical source data for Fig. 4, including VPDsafety for sustaining the biophysical cooling effect of global forests, regional percentages of forests where VPD2023 exceeded or remained below VPDcrit, and regionally averaged VPDsafety values.
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Zhang, C., Su, Y., Liao, Z. et al. Globally constrained forest biophysical cooling benefits under rising atmospheric dryness.
Nat. Clim. Chang. (2026). https://doi.org/10.1038/s41558-026-02677-y
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DOI: https://doi.org/10.1038/s41558-026-02677-y
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