Abstract
The terrestrial biosphere exchanges a large amount of CO2 with the atmosphere through photosynthesis and respiration, determining the magnitude of land carbon sink and consequently influencing the rate of global warming. The magnitudes of global photosynthesis and respiration, however, vary widely across models (100-200 PgC/year), constituting a key and persistent source of uncertainty in carbon cycle and climate modelling. Here, we argue that the uncertainty in the land carbon cycle modelling is largely attributable to the uncertainty in biogeography – the distribution of plant functional types (PFTs). Using an ensemble of dynamic global vegetation models (DGVMs), we find a strong dependence of total photosynthesis on total area for each PFT. The dependence allows us to reduce the spread of land carbon cycle estimates by ~75% using remote sensing-based PFT maps. We further find that 56 ± 21% of climate-driven changes in global photosynthesis modelled by DGVMs are caused by changes in PFT distribution in the last two decades. Our study identifies vegetation biogeography as a main controlling factor of uncertainty in land carbon cycle modelling and highlights the importance of biogeography-climate interactions in carbon cycle and climate studies.
| Original language | English |
|---|---|
| Article number | 912 |
| Journal | Nature Communications |
| Volume | 17 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2026 |
Funding
R.Z. and X.L. are supported by a NUS Foresight Grant awarded to X.L. (A-8002864-00-00) and a Tier 2 Academic Research Fund from the Singapore Ministry of Education (MOE-T2EP50222-0006). L.P.K. is supported by the Singapore National Research Foundation and Agency for Science, Technology and Research LCER Phase 2 funding programme (U2208D4101). ORNL is managed by UT-Battelle, LLC, for the DOE under contract DE-AC05-1008 00OR22725. F.H. is supported by the RUBISCO Science Focus Area, which is sponsored by Earth and Environmental Systems Sciences Division (EESSD) of the Office of Biological and Environmental Research (BER) in the US Department of Energy Office of Science. R.Z. and X.L. are supported by a NUS Foresight Grant awarded to X.L. (A-8002864-00-00) and a Tier 2 Academic Research Fund from the Singapore Ministry of Education (MOE-T2EP50222-0006). L.P.K. is supported by the Singapore National Research Foundation and Agency for Science, Technology and Research LCER Phase 2 funding programme (U2208D4101). ORNL is managed by UT-Battelle, LLC, for the DOE under contract DE-AC05-1008 00OR22725. F.H. is supported by the RUBISCO Science Focus Area, which is sponsored by Earth and Environmental Systems Sciences Division (EESSD) of the Office of Biological and Environmental Research (BER) in the US Department of Energy Office of Science.
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