Abstract
Plant nitrogen availability critically limits plant growth and thus constrains terrestrial carbon sequestration. Growing evidence points to a recent decline in plant nitrogen availability, yet the global consistency of this trend and its underlying drivers remain unclear. Here, we reconstruct the spatiotemporal trajectory of plant nitrogen availability (1980–2020) using four machine-learning algorithms applied to a global database of 37,268 foliar stable nitrogen isotopes measurements and ancillary climate data. We first find high spatial heterogeneity in foliar stable nitrogen isotopes, primarily linked to mean annual temperature. Then, we discover that foliar stable nitrogen isotopes declined primarily during the 1980s, and subsequently remained stable across 44% of land areas. Moreover, the dominant driver in temporal variations of foliar stable nitrogen isotopes shifts from CO2 (1980–1988) to precipitation (1989–2020). These patterns collectively reveal divergent plant nitrogen availability trajectories and highlight the increasing role of precipitation in shaping terrestrial nitrogen cycles over the past decades.
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Data availability
The foliar δ15N data used in this study were compiled from previously published sources, including Craine et al. (https://datadryad.org/dataset/doi:10.5061/dryad.v2k2607), Tang et al. (https://datadryad.org/dataset/doi:10.5061/dryad.n02v6wx04), the TRY Plant Trait Database (https://www.try-db.org), AusTraits (https://austraits.org/), the Terrestrial Ecosystem Research Network (TERN) (https://www.tern.org.au), and the LBA-ECO datasets (https://www.earthdata.nasa.gov/centers/ornl-daac). Climatic variables were obtained from the Climate Research Unit Time-Series dataset (CRU TS v4.07), publicly available at https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.07/. Atmospheric NOy and NHx deposition data were derived from Tian et al. and are available at https://doi.org/10.1594/PANGAEA.942069. Historical annual atmospheric CO2 concentration data were obtained from NASA Goddard Institute for Space Studies (GISS) at https://data.giss.nasa.gov/modelforce/ghgases/. Global annual spatial atmospheric CO2 concentrations for the period 1980–2020 were obtained from Cheng et al. and are available at https://zenodo.org/records/5021361. The historical foliar δ15N data from 1980 to 2020 generated in this study have been deposited in the figshare https://doi.org/10.6084/m9.figshare.28782263. All data supporting the findings of this study are available on figshare at https://doi.org/10.6084/m9.figshare.30833297 or https://doi.org/10.6084/m9.figshare.28782263. Source data are provided with this paper.
Code availability
The R and python scripts used in the analyses are available at https://doi.org/10.6084/m9.figshare.28782263.
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Acknowledgements
We are grateful to Craine et al., the TRY Plant Trait Database (TRY), AusTraits, NASA’s Earth Science Data and Information System (ESDIS) Project, and the Terrestrial Ecosystem Research Network (TERN) for providing access to their foliar stable nitrogen isotope data. We also acknowledge the Climate Research Unit (CRU), NASA’s Goddard Institute for Space Studies (GISS), Cheng et al., and Tian et al. for access to climatic, atmospheric CO2, and nitrogen deposition data as appropriate. This study was funded by the National Natural Science Foundation of China (32325033, 32301387, 42301066), Shanghai Pilot Program for Basic Research (TQ20220102), and Fundamental and Interdisciplinary Disciplines Breakthrough Plan of the Ministry of Education of China (JYB2025XDXM904).
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S.T., E.C., and J.X. devised and conducted the analysis. S.T. collected the database and drafted the first manuscript. E.C., J.X. and Y.Q. provided critical suggestions on the method and results. All authors contributed to the writing and revising of the manuscript.
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Tang, S., Qiao, Y., Xia, J. et al. Joint control of precipitation and CO2 on global long-term patterns of plant nitrogen availability. Nat Commun (2026). https://doi.org/10.1038/s41467-026-70358-7
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DOI: https://doi.org/10.1038/s41467-026-70358-7


