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Weakening temperature control on the interannual variations of spring carbon uptake across northern lands

Nature Climate Change volume 7, pages 359–363 (2017)Cite this article

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Abstract

Ongoing spring warming allows the growing season to begin earlier, enhancing carbon uptake in northern ecosystems1,2,3. Here we use 34 years of atmospheric CO2 concentration measurements at Barrow, Alaska (BRW, 71° N) to show that the interannual relationship between spring temperature and carbon uptake has recently shifted. We use two indicators: the spring zero-crossing date of atmospheric CO2 (SZC) and the magnitude of CO2 drawdown between May and June (SCC). The previously reported strong correlation between SZC, SCC and spring land temperature (ST) was found in the first 17 years of measurements, but disappeared in the last 17 years. As a result, the sensitivity of both SZC and SCC to warming decreased. Simulations with an atmospheric transport model4 coupled to a terrestrial ecosystem model5 suggest that the weakened interannual correlation of SZC and SCC with ST in the last 17 years is attributable to the declining temperature response of spring net primary productivity (NPP) rather than to changes in heterotrophic respiration or in atmospheric transport patterns. Reduced chilling during dormancy and emerging light limitation are possible mechanisms that may have contributed to the loss of NPP response to ST. Our results thus challenge the ‘warmer spring–bigger sink’ mechanism.

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Figure 1: Time series of detrended anomalies.
Figure 2: The partial correlation coefficient of spring carbon uptake and temperature during different periods.
Figure 3: Spatial distribution of difference in average partial correlation coefficient of spring carbon flux (NEP, NPP and HR) and NDVI with March–June temperature between 1996–2012 and 1979–1995.

References

  1. Keeling, C. D., Chin, J. F. S. & Whorf, T. P. Increased activity of northern vegetation inferred from atmospheric CO2 measurements. Nature 382, 146–149 (1996).

    Article  CAS  Google Scholar 

  2. Randerson, J. T., Field, C. B., Fung, I. Y. & Tans, P. P. Increases in early season ecosystem uptake explain recent changes in the seasonal cycle of atmospheric CO2 at high northern latitudes. Geophys. Res. Lett. 26, 2765–2768 (1999).

    Article  CAS  Google Scholar 

  3. Richardson, A. D. et al. Influence of spring and autumn phenological transitions on forest ecosystem productivity. Phil. Trans. R. Soc. B 365, 3227–3246 (2010).

    Article  Google Scholar 

  4. Hourdin, F. et al. The LMDZ4 general circulation model: climate performance and sensitivity to parametrized physics with emphasis on tropical convection. Clim. Dynam. 27, 787–813 (2006).

    Article  Google Scholar 

  5. Krinner, G. et al. A dynamic global vegetation model for studies of the coupled atmosphere–biosphere system. Glob. Biogeochem. Cycles 19, GB1015 (2005).

    Article  Google Scholar 

  6. Dolman, A. J. et al. An estimate of the terrestrial carbon budget of Russia using inventory-based, eddy covariance and inversion methods. Biogeosciences 9, 5323–5340 (2012).

    Article  CAS  Google Scholar 

  7. McGuire, A. D. et al. An assessment of the carbon balance of Arctic tundra: comparisons among observations, process models, and atmospheric inversions. Biogeosciences 9, 3185–3204 (2012).

    Article  CAS  Google Scholar 

  8. Black, T. A. et al. Increased carbon sequestration by a boreal deciduous forest in years with a warm spring. Geophys. Res. Lett. 27, 1271–1274 (2000).

    Article  Google Scholar 

  9. Barichivich, J. et al. Large-scale variations in the vegetation growing season and annual cycle of atmospheric CO2 at high northern latitudes from 1950 to 2011. Glob. Change Biol. 19, 3167–3183 (2013).

    Article  Google Scholar 

  10. D’Arrigo, R. D. et al. Thresholds for warming-induced growth decline at elevational tree line in the Yukon Territory, Canada. Glob. Biogeochem. Cycles 18, GB3021 (2004).

    Google Scholar 

  11. Angert, A. et al. Drier summers cancel out the CO2 uptake enhancement induced by warmer springs. Proc. Natl Acad. Sci. USA 102, 10823–10827 (2005).

    Article  CAS  Google Scholar 

  12. Piao, S. et al. Evidence for a weaking relationship between interannual temperature variability and northern vegetation activity. Nat. Commun. 5, 5018 (2014).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  14. Piao, S. et al. Net carbon dioxide losses of northern ecosystems in response to autumn warming. Nature 451, 49–52 (2008).

    Article  CAS  Google Scholar 

  15. Takala, M. et al. Estimating Northern Hemisphere snow water equivalent for climate research through assimilation of space-borne radiometer and ground-based measurements. Remote Sens. Environ. 115, 3517–3529 (2011).

    Article  Google Scholar 

  16. Viovy, N. & Ciais, P. CRUNCEP data set for 1901–2012 Tech. Rep. V. 4 (Laboratoire des Sciences du Climat et de l’Environnement, 2014); https://www.earthsystemgrid.org/browse/viewActivity.html?activityId=ff9d6ffb-f0b9-11e2-aa24-00c0f03d5b7c

    Google Scholar 

  17. Goulden, M. L. et al. Sensitivity of boreal forest carbon balance to soil thaw. Science 279, 214–217 (1998).

    Article  CAS  Google Scholar 

  18. Kaminski, T., Giering, R. & Heimann, M. Sensitivity of the seasonal cycle of CO2 at remote monitoring stations with respect to seasonal surface exchange fluxes determined with the adjoint of an atmospheric transport model. Phys. Chem. Earth 21, 457–462 (1996).

    Article  Google Scholar 

  19. Fu, Y. H. et al. Declining global warming effects on the phenology of spring leaf unfolding. Nature 526, 104–107 (2015).

    Article  CAS  Google Scholar 

  20. Yu, H., Luedeling, E. & Xu, J. Winter and spring warming result in delayed spring phenology on the Tibetan Plateau. Proc. Natl Acad. Sci. USA 107, 22151–22156 (2010).

    Article  CAS  Google Scholar 

  21. Stine, A. R. & Huybers, P. Arctic tree rings as recorders of variations in light availability. Nat. Commun. 5, 3836 (2014).

    Article  CAS  Google Scholar 

  22. Thoning, K. W., Kitzis, D. R. & Crotwell, A. Atmospheric Carbon Dioxide Dry Air Mole Fractions from Quasi-Continuous Measurements at Barrow, Alaska (NOAA ESRL Global Monitoring Division, 2014); ftp://aftp.cmdl.noaa.gov/data/trace_gases/co2/in-situ/surface/brw/co2_brw_surface-insitu_1_ccgg_DailyData.txt

    Google Scholar 

  23. Thoning, K. W., Tans, P. P. & Komhyr, W. D. Atmospheric carbon dioxide at Mauna Loa observatory. 2. Analysis of the NOAA GMCC data, 1974–1985. J. Geophys. Res. 94, 8549–8565 (1989).

    Article  CAS  Google Scholar 

  24. Harris, J. M. et al. An interpretation of trace gas correlations during Barrow, Alaska, winter dark periods, 1986–1997. J. Geophys. Res. 105, 17267–17278 (2000).

    Article  CAS  Google Scholar 

  25. Cooperative Global Atmospheric Data Integration Project Multi-Laboratory Compilation of Synchronized and Gap-Filled Atmospheric Carbon Dioxide Records for the Period 1979–2012 (obspack_co2_1_GLOBALVIEW-CO2_2013_v1.0.4_2013-2-23) (NOAA Global Monitoring Division, 2013); http://dx.doi.org/10.3334/OBSPACK/1002

  26. Chevallier, F. et al. Inferring CO2 sources and sinks from satellite observations: method and application to TOVS data. J. Geophys. Res. 110, D24309 (2005).

    Article  Google Scholar 

  27. Stohl, A., Forster, C., Frank, A., Seibert, P. & Wotawa, G. The Lagrangian particle dispersion model FLEXPART version 6.2. Atmos. Chem. Phys. 5, 2461–2474 (2005).

    Article  CAS  Google Scholar 

  28. Stohl, A., Forster, C. & Eckhardt, S. et al. A backward modeling study of intercontinental pollution transport using aircraft measurements. J. Geophys. Res. 108, 4370 (2003).

    Article  Google Scholar 

  29. Mitchell, T. D. & Jones, P. D. An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int. J. Climatol. 25, 693–712 (2005).

    Article  Google Scholar 

  30. Tucker, C. J. et al. An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. Int. J. Remote Sens. 26, 4485–4498 (2005).

    Article  Google Scholar 

  31. Piao, S., Friedlingstein, P., Ciais, P., Viovy, N. & Demarty, J. Growing season extension and its impact on terrestrial carbon cycle in the Northern Hemisphere over the past 2 decades. Glob. Biogeochem. Cycles 21, GB3018 (2007).

    Google Scholar 

  32. Wang, X. et al. Has the advancing onset of spring vegetation green-up slowed down or changed abruptly over the last three decades? Glob. Ecol. Biogeogr. 24, 621–631 (2015).

    Article  CAS  Google Scholar 

  33. Buitenhuis, E. T., Rivkin, R. B., Sailley, S. & Le Quéré, C. Biogeochemical fluxes through microzooplankton. Glob. Biogeochem. Cycles 24, GB4015 (2010).

    Article  Google Scholar 

  34. Le Quéré, C. et al. Global carbon budget 2015. Earth Syst. Sci. Data 7, 349–396 (2015).

    Article  Google Scholar 

  35. Cotrim da Cunha, L., Buitenhuis, E. T., Le Quéré, C., Giraud, X. & Ludwig, W. Potential impact of changes in river nutrient supply on global ocean biogeochemistry. Glob. Biogeochem. Cycles 21, GB4007 (2007).

    Article  Google Scholar 

  36. Aumont, O., Maier-Reimer, E., Blain, S. & Monfray, P. An ecosystem model of the global ocean including Fe, Si, P colimitations. Glob. Biogeochem. Cycles 17, 1060 (2003).

    Article  Google Scholar 

  37. Kalnay, E. et al. The NCEP/NCAR 40-year reanalysis project. Bull. Am. Meteorol. Soc. 77, 437–471 (1996).

    Article  Google Scholar 

  38. Liu, Q. et al. Temperature, precipitation, and insolation effects on autumn vegetation phenology in temperate China. Glob. Change Biol. 22, 644–655 (2016).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This study was supported by the National Natural Science Foundation of China (41530528), the International Partnership Program of Chinese Academy of Sciences (Grant No. 131C11KYSB20160061), the BELSPO STEREO project ECOPROPHET (SR00334), the 111 Project (B14001), and National Youth Top-notch Talent Support Program in China. P.C., I.A.J. and J.P. acknowledge support from the European Research Council through Synergy grant ERC-2013-SyG-610028 ‘P-IMBALANCE’. Analysis of FLEXPART was conducted within the LATICE project at the University of Oslo. J.Mao and X.Shi are supported by the Biogeochemistry-Climate Feedbacks Scientific Focus Area project funded through the Regional and Global Climate Modeling Program in the Climate and Environmental Sciences Division (CESD) of the Biological and Environmental Research (BER) Program in the US Department of Energy Office of Science. Oak Ridge National Laboratory is managed by UT-BATTELLE for DOE under contract DE-AC05-00OR22725.

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Authors and Affiliations

  1. Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100085, China

    Shilong Piao & Tao Wang

  2. Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China

    Shilong Piao, Zhuo Liu, Shushi Peng, Mengtian Huang, Yitong Yao & Zaichun Zhu

  3. Center for Excellence in Tibetan Earth Science, Chinese Academy of Sciences, Beijing 100085, China

    Shilong Piao & Tao Wang

  4. Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ, Gif-sur-Yvette 91191, France

    Philippe Ciais, Frédéric Chevallier & Xin Lin

  5. School of Earth, Energy and Environmental Sciences, Stanford University, Stanford, California 94305-2210, USA

    Anders Ahlstrom

  6. Department of Geosciences, University of Oslo, PO Box 1047 Blindem, 0316 Oslo, Norway

    John F. Burkhart

  7. Department of Biology, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium

    Ivan A. Janssens

  8. School of Environmental Science and Engineering, South University of Science and Technology of China, Shenzhen 518055, China

    Su-Jong Jeong

  9. Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA

    Jiafu Mao & Xiaoying Shi

  10. National Oceanic and Atmospheric Administration Earth Systems Research Laboratory (NOAA/ESRL), 325 Broadway, Boulder, Colorado 80305, USA

    John Miller & Pieter P. Tans

  11. Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder 80309, USA

    John Miller

  12. Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China

    Anwar Mohammat

  13. Department of Earth and Environment, Boston University, 675 Commonwealth Avenue, Boston, Massachusetts 02215, USA

    Ranga B. Myneni

  14. CREAF, Cerdanyola del Valles, Barcelona 08193, Catalonia, Spain

    Josep Peñuelas

  15. CSIC, Global Ecology Unit CREAF-CEAB-CSIC-UAB, Cerdanyola del Valles, Barcelona 08193, Catalonia, Spain

    Josep Peñuelas

  16. NILU—Norwegian Institute for Air Research, PO Box 100, 2027 Kjeller, Norway

    Andreas Stohl

Authors
  1. Shilong Piao
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  18. Xiaoying Shi
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  19. Andreas Stohl
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  20. Yitong Yao
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  21. Zaichun Zhu
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Contributions

S.Piao designed the research; Z.L., T.W. and P.P.T. performed measurements of CO2 data analysis; S.Peng, T.W. and Z.L. performed ORCHIDEE modelling and transport analysis; F.C., J.F.B. and A.S. performed footprint analysis; S.Piao drafted the paper; and all authors contributed to the interpretation of the results and to the text.

Corresponding author

Correspondence to Shilong Piao.

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Piao, S., Liu, Z., Wang, T. et al. Weakening temperature control on the interannual variations of spring carbon uptake across northern lands. Nature Clim Change 7, 359–363 (2017). https://doi.org/10.1038/nclimate3277

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