Abstract
Climate change is altering vegetation patterns on the Qinghai-Tibet Plateau, where diverse Köppen climate zones reveal complex ecological responses. Here, we advance from a categorical view of climate, represented by Köppen-Geiger classifications, to a continuous characterization of the climate heterogeneity index to better capture the link between climate and vegetation across 1- and 10-km scales. We show that climate heterogeneity strengthens vegetation–climate relationships across spatial scales, with its influence increasing 1.2-fold at coarse resolution compared to fine scales. This enhancement stems from this index providing critical heterogeneity information absent in coarse macroclimate data, thereby refining suitability predictions in regions where fine-scale topographic variability is unresolved. At finer 1-km scales, topographic heterogeneity inherently dominates, reducing the relative impact of climate heterogeneity. Overall, incorporating climate heterogeneity compensates for coarse-scale data limitations, enhancing suitability predictions where topographic detail is lost, thereby bridging macroclimate biases and microscale dynamics, and advancing robust ecological forecasting.
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Acknowledgements
We thank the data providers and developers of the publicly available datasets used in this study, including the Köppen–Geiger climate classification, vegetation, soil moisture, fractional vegetation cover, topographic, and bioclimatic datasets. We are grateful to colleagues and collaborators for helpful discussions and constructive feedback that improved this work. We also thank the reviewers for their constructive comments, which helped improve the clarity and rigor of this work. This study was supported by the National Natural Science Foundation of China (42525702, S.Z.; 42477508, Y.G.; W2521031, Y.G.; and 42407630, X.H.), Natural Science Foundation of Fujian Province (2024J01132005, Y.G.), and the Open Fund of Fujian Provincial Key Laboratory of Eco-Industrial Green Technology (WYKF-EIGT2024-1, Y.G.). D.C. was supported by Carbon Neutrality and Energy System Transformation (CNEST) Program and Tsinghua University (100008001). E.E.M. is funded by the Research Council of Finland (363501).
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Guan, Y., Wu, W., He, M. et al. Climate heterogeneity enhances macroclimate data-driven vegetation modeling on the Qinghai-Tibet Plateau. Nat Commun (2026). https://doi.org/10.1038/s41467-026-73158-1
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DOI: https://doi.org/10.1038/s41467-026-73158-1
