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Diagnosing destabilization risk in global land carbon sinks


Global net land carbon uptake or net biome production (NBP) has increased during recent decades1. Whether its temporal variability and autocorrelation have changed during this period, however, remains elusive, even though an increase in both could indicate an increased potential for a destabilized carbon sink2,3. Here, we investigate the trends and controls of net terrestrial carbon uptake and its temporal variability and autocorrelation from 1981 to 2018 using two atmospheric-inversion models, the amplitude of the seasonal cycle of atmospheric CO2 concentration derived from nine monitoring stations distributed across the Pacific Ocean and dynamic global vegetation models. We find that annual NBP and its interdecadal variability increased globally whereas temporal autocorrelation decreased. We observe a separation of regions characterized by increasingly variable NBP, associated with warm regions and increasingly variable temperatures, lower and weaker positive trends in NBP and regions where NBP became stronger and less variable. Plant species richness presented a concave-down parabolic spatial relationship with NBP and its variability at the global scale whereas nitrogen deposition generally increased NBP. Increasing temperature and its increasing variability appear as the most important drivers of declining and increasingly variable NBP. Our results show increasing variability of NBP regionally that can be mostly attributed to climate change and that may point to destabilization of the coupled carbon–climate system.

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Fig. 1: Global distribution of NBP, NBPPV and NBPAR1 and their trends from 1981 to 2018.
Fig. 2: Regions with concomitantly increasing NBPPV and NBPAR1 present lower NBP and a lower increase of NBP over time.
Fig. 3: Contribution of biodiversity, N deposition, climate and land use to NBP, NBPPV, NBPAR1 and their trends.

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Data availability

Data supporting the findings of this study are available in the following open repositories: CAMS (!/dataset/cams-global-greenhouse-gas-inversion);CarboScope (;and atmospheric CO2 concentration ( from the TRENDY ensembles can be provided on request from Data to perform the statistical analyses, calculations and figures are publicly available at Figshare: data are provided with this paper.

Code availability

Code and data to perform the statistical analyses, calculations and figures are publicly available at Figshare:


  1. Fernández-Martínez, M. et al. Global trends in carbon sinks and their relationships with CO2 and temperature. Nat. Clim. Change 9, 73–79 (2019).

    Article  ADS  Google Scholar 

  2. Scheffer, M. et al. Early-warning signals for critical transitions. Nature 461, 53–59 (2009).

    Article  ADS  CAS  PubMed  Google Scholar 

  3. Dakos, V. et al. Slowing down as an early warning signal for abrupt climate change. Proc. Natl Acad. Sci. USA 105, 14308–14312 (2008).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  4. Gasser, T. et al. Path-dependent reductions in CO2 emission budgets caused by permafrost carbon release. Nat. Geosci. 11, 830–835 (2018).

    Article  ADS  CAS  Google Scholar 

  5. Zhu, Z. et al. Greening of the Earth and its drivers. Nat. Clim. Change 6, 791–795 (2016).

    Article  ADS  CAS  Google Scholar 

  6. Bastos, A. et al. Contrasting effects of CO2 fertilization, land-use change and warming on seasonal amplitude of Northern Hemisphere CO2 exchange. Atmos. Chem. Phys. 19, 12361–12375 (2019).

    Article  ADS  CAS  Google Scholar 

  7. 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  CAS  PubMed  PubMed Central  Google Scholar 

  8. Wang, S. et al. Recent global decline of CO2 fertilization effects on vegetation photosynthesis. Science 370, 1295–1300 (2020).

    Article  ADS  CAS  PubMed  Google Scholar 

  9. Peñuelas, J. et al. Assessment of the impacts of climate change on Mediterranean terrestrial ecosystems based on data from field experiments and long-term monitored field gradients in Catalonia. Environ. Exp. Bot. 152, 49–59 (2018).

    Article  Google Scholar 

  10. Terrer, C. et al. Nitrogen and phosphorus constrain the CO2 fertilization of global plant biomass. Nat. Clim. Change 9, 684–689 (2019).

    Article  ADS  CAS  Google Scholar 

  11. Gatti, L. V. et al. Amazonia as a carbon source linked to deforestation and climate change. Nature 595, 388–393 (2021).

    Article  ADS  CAS  PubMed  Google Scholar 

  12. Carpenter, S. R. & Brock, W. A. Rising variance: a leading indicator of ecological transition. Ecol. Lett. 9, 311–318 (2006).

    Article  CAS  PubMed  Google Scholar 

  13. Dakos, V., Nes, E. H. & Scheffer, M. Flickering as an early warning signal. Theor. Ecol. 6, 309–317 (2013).

    Article  Google Scholar 

  14. Sillmann, J., Daloz, A. S., Schaller, N. & Schwingshackl, C. in Climate Change 3rd edn (ed. Letcher, T. M.) 359–372 (Elsevier, 2021).

  15. Reichstein, M. et al. Climate extremes and the carbon cycle. Nature 500, 287–295 (2013).

    Article  ADS  CAS  PubMed  Google Scholar 

  16. Wang, X. et al. A two-fold increase of carbon cycle sensitivity to tropical temperature variations. Nature 506, 212–215 (2014).

    Article  ADS  CAS  PubMed  Google Scholar 

  17. Barnosky, A. D. et al. Approaching a state shift in Earth’s biosphere. Nature 486, 52–58 (2012).

    Article  ADS  CAS  PubMed  Google Scholar 

  18. Buermann, W. et al. Climate-driven shifts in continental net primary production implicated as a driver of a recent abrupt increase in the land carbon sink. Biogeosciences 13, 1597–1607 (2016).

    Article  ADS  CAS  Google Scholar 

  19. Luyssaert, S. et al. CO2 balance of boreal, temperate, and tropical forests derived from a global database. Glob. Change Biol. 13, 2509–2537 (2007).

    Article  ADS  Google Scholar 

  20. Peñuelas, J. et al. Shifting from a fertilization-dominated to a warming-dominated period. Nat. Ecol. Evol. 1, 1438–1445 (2017).

    Article  PubMed  Google Scholar 

  21. Fernández-Martínez, M. et al. Nutrient availability as the key regulator of global forest carbon balance. Nat. Clim. Change 4, 471–476 (2014).

    Article  ADS  Google Scholar 

  22. Fernández-Martínez, M. et al. Spatial variability and controls over biomass stocks, carbon fluxes and resource-use efficiencies in forest ecosystems. Trees Struct. Funct. 28, 597–611 (2014).

    Article  Google Scholar 

  23. Ciais, P. et al. Five decades of northern land carbon uptake revealed by the interhemispheric CO2 gradient. Nature 568, 221–225 (2019).

    Article  ADS  CAS  PubMed  Google Scholar 

  24. Tilman, D., Lehman, C. L. & Thomson, K. T. Plant diversity and ecosystem productivity: theoretical considerations. Proc. Natl Acad. Sci. USA 94, 1857–1861 (1997).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  25. de Mazancourt, C. et al. Predicting ecosystem stability from community composition and biodiversity. Ecol. Lett. 16, 617–625 (2013).

    Article  PubMed  Google Scholar 

  26. Sakschewski, B. et al. Resilience of Amazon forests emerges from plant trait diversity. Nat. Clim. Change 6, 1032–1036 (2016).

    Article  ADS  Google Scholar 

  27. Fernández‐Martínez, M. et al. The role of climate, foliar stoichiometry and plant diversity on ecosystem carbon balance. Glob. Change Biol. 26, 7067–7078 (2020).

    Article  ADS  Google Scholar 

  28. Musavi, T. et al. Stand age and species richness dampen interannual variation of ecosystem-level photosynthetic capacity. Nat. Ecol. Evol. 1, 0048 (2017).

    Article  Google Scholar 

  29. Anderegg, W. R. L. et al. Hydraulic diversity of forests regulates ecosystem resilience during drought. Nature 561, 538–541 (2018).

    Article  ADS  CAS  PubMed  Google Scholar 

  30. IPBES: Summary for Policymakers. In The Global Assessment Report on Biodiversity and Ecosystem Services (eds Díaz, S. et al.) 1–56 (IPBES, 2019).

  31. Heath, J. P. Quantifying temporal variability in population abundances. Oikos 115, 573–581 (2006).

    Article  Google Scholar 

  32. Fernández-Martínez, M., Vicca, S., Janssens, I. A., Martín-Vide, J. & Peñuelas, J. The consecutive disparity index, D, as measure of temporal variability in ecological studies. Ecosphere 9, e02527 (2018).

    Article  Google Scholar 

  33. Kreft, H. & Jetz, W. Global patterns and determinants of vascular plant diversity. Proc Natl Acad Sci USA 104, 5925–5930 (2007).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  34. Ackerman, D. E., Chen, X. & Millet, D. B. Global nitrogen deposition (2° × 2.5° grid resolution) simulated with GEOS-Chem for 1984–1986, 1994–1996, 2004–2006, and 2014–2016 (University of Minnesota, 2018);

  35. Harris, I., Jones, P. D. D., Osborn, T. J. J. & Lister, D. H. H. Updated high-resolution grids of monthly climatic observations—the CRU TS3.10 Dataset. Int. J. Climatol. 34, 623–642 (2013).

    Article  Google Scholar 

  36. Graven, H. D. et al. Enhanced seasonal exchange of CO2 by northern ecosystems since 1960. Science 341, 1085–1089 (2013).

    Article  ADS  CAS  PubMed  Google Scholar 

  37. Wang, K. et al. Causes of slowing-down seasonal CO2 amplitude at Mauna Loa. Glob. Change Biol. 26, 4462–4477 (2020).

    Article  ADS  Google Scholar 

  38. Tilman, D., Reich, P. B. & Knops, J. M. H. Biodiversity and ecosystem stability in a decade-long grassland experiment. Nature 441, 629–632 (2006).

    Article  ADS  CAS  PubMed  Google Scholar 

  39. Liang, J. et al. Positive biodiversity–productivity relationship predominant in global forests. Science 354, aaf8957–aaf8957 (2016).

    Article  PubMed  Google Scholar 

  40. Gessner, M. O. et al. Diversity meets decomposition. Trends Ecol. Evol. 25, 372–380 (2010).

    Article  PubMed  Google Scholar 

  41. Peguero, G. et al. Fast attrition of springtail communities by experimental drought and richness–decomposition relationships across Europe. Glob. Change Biol. 25, 2727–2738 (2019).

    Article  ADS  Google Scholar 

  42. Díaz, S. & Cabido, M. Vive la différence: plant functional diversity matters to ecosystem processes. Trends Ecol. Evol. 16, 646–655 (2001).

    Article  Google Scholar 

  43. Cardinale, B. J. Biodiversity improves water quality through niche partitioning. Nature 472, 86–91 (2011).

    Article  ADS  CAS  PubMed  Google Scholar 

  44. Ciais, P. et al. Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature 437, 529–533 (2005).

    Article  ADS  CAS  PubMed  Google Scholar 

  45. Scheffer, M. Critical Transitions in Nature and Society (Princeton University Press, 2009).

  46. Ostfeld, R. & Keesing, F. Pulsed resources and community dynamics of consumers in terrestrial ecosystems. Trends Ecol. Evol. 15, 232–237 (2000).

    Article  CAS  PubMed  Google Scholar 

  47. Chevallier, F. et al. CO2 surface fluxes at grid point scale estimated from a global 21 year reanalysis of atmospheric measurements. J. Geophys. Res. 115, D21307 (2010).

    Article  ADS  Google Scholar 

  48. Chevallier, F. et al. Toward robust and consistent regional CO2 flux estimates from in situ and spaceborne measurements of atmospheric CO2. Geophys. Res. Lett. 41, 1065–1070 (2014).

    Article  ADS  CAS  Google Scholar 

  49. Rödenbeck, C., Houweling, S., Gloor, M. & Heimann, M. CO2 flux history 1982–2001 inferred from atmospheric data using a global inversion of atmospheric transport. Atmos. Chem. Phys. 3, 1919–1964 (2003).

    Article  ADS  Google Scholar 

  50. Rödenbeck, C., Zaehle, S., Keeling, R. & Heimann, M. How does the terrestrial carbon exchange respond to interannual climatic variations? A quantification based on atmospheric CO2 data. Biogeosciences 15, 2481–2498 (2018).

  51. Sitch, S. et al. Recent trends and drivers of regional sources and sinks of carbon dioxide. Biogeosciences 12, 653–679 (2015).

    Article  ADS  Google Scholar 

  52. Fernández‐Martínez, M. & Peñuelas, J. Measuring temporal patterns in ecology: the case of mast seeding. Ecol. Evol. 11, 2990–2996 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Wood, S. N. Generalized Additive Models: An introduction with R 2nd edn (Chapman and Hall/CRC, 2017).

  54. Ohlson, J. A. & Kim, S. Linear Valuation Without OLS: The Theil–Sen Estimation Approach (SSRN, 2015);

  55. Komsta, L. Package mblm, 0.12.1: Median-based linear models (2013).

  56. Keeling, C. D. et al. in A History of Atmospheric CO2 and its effects on Plants, Animals, and Ecosystems (eds Ehleringer, J. R. et al.) 83–113 (Springer Verlag, 2005).

  57. Leroux, B. G., Lei, X. & Breslow, N. in Statistical Models in Epidemiology, the Environment and Clinical Trials (eds Halloran, M. & Berry, D.) 179–191 (Springer-Verlag, 2000).

  58. Lee, D. CARBayes: an R package for Bayesian spatial modeling with conditional autoregressive priors. J. Stat. Softw. 55, 1–24 (2013).

    Article  Google Scholar 

  59. Gonzalez, A. et al. Scaling‐up biodiversity–ecosystem functioning research. Ecol. Lett. 15, ele.13456 (2020).

    Google Scholar 

  60. R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).

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This research was funded by the Spanish Government project PID2019-110521GB-I00, the Fundación Ramón Areces project CIVP20A6621, the Catalan government project SGR2017-1005 and the European Research Council project ERCSyG-2013-610028 IMBALANCE-P. M.F.-M. was supported by a postdoctoral fellowship of the Research Foundation-Flanders (FWO) and by a fellowship from ‘la Caixa’ Foundation (ID 100010434), code LCF/BQ/PI21/11830010. This material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under Cooperative Agreement No. 1852977. Computing and data storage resources, including the Cheyenne supercomputer (doi:10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. We acknowledge the Scripps CO2 programme for providing the records of atmospheric CO2.

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M.F.-M., J.P. and I.A.J. planned and designed the research. F.C., C.R., S.S., P.F., V.A., D.G., A.K.J., D.L.L. and P.C.M. provided the data. M.F.-M. analysed the data. All previously mentioned authors, along with P.C., M.O., J.S., S.V. and H.Y., contributed substantially to the writing of the manuscript.

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Correspondence to Marcos Fernández-Martínez.

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Fernández-Martínez, M., Peñuelas, J., Chevallier, F. et al. Diagnosing destabilization risk in global land carbon sinks. Nature 615, 848–853 (2023).

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