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A constraint on historic growth in global photosynthesis due to increasing CO2

  • 1.

    Friedlingstein, P. et al. Global carbon budget 2019. Earth Syst. Sci. Data 11, 1783–1838 (2019).

    ADS 

    Google Scholar 

  • 2.

    Ballantyne, A. P., Alden, C. B., Miller, J. B., Tans, P. P. & White, J. W. C. Increase in observed net carbon dioxide uptake by land and oceans during the past 50 years. Nature 488, 70–72 (2012).

    CAS 
    PubMed 
    ADS 

    Google Scholar 

  • 3.

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

    ADS 

    Google Scholar 

  • 4.

    Keenan, T. F. et al. Recent pause in the growth rate of atmospheric CO2 due to enhanced terrestrial carbon uptake. Nat. Commun. 7, 13428 (2016).

    CAS 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 

  • 5.

    Schimel, D., Stephens, B. B. & Fisher, J. B. Effect of increasing CO2 on the terrestrial carbon cycle. Proc. Natl Acad. Sci. USA 112, 436–441 (2015).

    CAS 
    PubMed 
    ADS 

    Google Scholar 

  • 6.

    Huntzinger, D. N. et al. Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions. Sci. Rep. 7, 4765 (2017).

    CAS 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 

  • 7.

    Walker, A. P. et al. Integrating the evidence for a terrestrial carbon sink caused by increasing atmospheric CO2. New Phytol. 229, 2383–2385 (2020).

    Google Scholar 

  • 8.

    Sun, Z. et al. Evaluating and comparing remote sensing terrestrial GPP models for their response to climate variability and CO2 trends. Sci. Total Environ. 668, 696–713 (2019).

    CAS 
    PubMed 
    ADS 

    Google Scholar 

  • 9.

    Smith, W. K. et al. Large divergence of satellite and Earth system model estimates of global terrestrial CO2 fertilization. Nat. Clim. Change 6, 306–310 (2016).

    ADS 

    Google Scholar 

  • 10.

    Li, W. et al. Recent changes in global photosynthesis and terrestrial ecosystem respiration constrained from multiple observations. Geophys. Res. Lett. 45, 1058–1068 (2018).

    ADS 

    Google Scholar 

  • 11.

    Wenzel, S., Cox, P. M., Eyring, V. & Friedlingstein, P. Projected land photosynthesis constrained by changes in the seasonal cycle of atmospheric CO2. Nature 538, 499–501 (2016).

    PubMed 
    ADS 

    Google Scholar 

  • 12.

    Ehlers, I. et al Detecting long-term metabolic shifts using isotopomers: CO2-driven suppression of photorespiration in C3 plants over the 20th century. Proc. Natl Acad. Sci. USA 112, 15585–15590 (2015).

    CAS 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 

  • 13.

    Campbell, J. E. et al. Large historical growth in global terrestrial gross primary production. Nature 544, 84–87 (2017).

    CAS 
    PubMed 
    ADS 

    Google Scholar 

  • 14.

    Eyring, V. et al. Taking climate model evaluation to the next level. Nat. Clim. Change 9, 102–110 (2019).

    ADS 

    Google Scholar 

  • 15.

    Winkler, A. J., Myneni, R. B. & Brovkin, V. Investigating the applicability of emergent constraints. Earth Syst. Dyn. 10, 501–523 (2019).

    ADS 

    Google Scholar 

  • 16.

    Hall, A., Cox, P., Huntingford, C. & Klein, S. Progressing emergent constraints on future climate change. Nat. Clim. Change 9, 269–278 (2019).

    ADS 

    Google Scholar 

  • 17.

    Keenan, T. F. & Williams, C. A. The terrestrial carbon sink. Annu. Rev. Environ. Resour. 43, 219–243 (2018).

    Google Scholar 

  • 18.

    Ryu, Y., Berry, J. A. & Baldocchi, D. D. What is global photosynthesis? History, uncertainties and opportunities. Remote Sens. Environ. 223, 95–114 (2019).

    ADS 

    Google Scholar 

  • 19.

    Winkler, A. J., Myneni, R. B., Alexandrov, G. A. & Brovkin, V. Earth system models underestimate carbon fixation by plants in the high latitudes. Nat. Commun. 10, 95 (2019).

    ADS 

    Google Scholar 

  • 20.

    Ainsworth, E. A. & Long, S. P. What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. New Phytol. 165, 351–372 (2005).

    PubMed 

    Google Scholar 

  • 21.

    De Kauwe, M. G., Keenan, T. F., Medlyn, B. E., Prentice, I. C. & Terrer, C. Satellite based estimates underestimate the effect of CO2 fertilization on net primary productivity. Nat Clim. Change 6, 892–893 (2016).

    ADS 

    Google Scholar 

  • 22.

    Cernusak, L. A. et al Robust response of terrestrial plants to rising CO2. Trends Plant Sci. 24, 578–586 (2019).

    CAS 
    PubMed 

    Google Scholar 

  • 23.

    Piao, S. et al. Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends. Glob. Change Biol. 19, 2117–2132 (2013).

    ADS 

    Google Scholar 

  • 24.

    Haverd, V. et al. Higher than expected CO2 fertilization inferred from leaf to global observations. Glob. Change Biol. 26, 2390–2402 (2020).

    ADS 

    Google Scholar 

  • 25.

    Friedlingstein, P. et al. Uncertainties in CMIP5 climate projections due to carbon cycle feedbacks. J. Clim. 27, 511–526 (2014).

    ADS 

    Google Scholar 

  • 26.

    Zhao, F. et al. Role of CO2, climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: a multimodel analysis. Biogeosciences 13, 5121–5137 (2016).

    CAS 
    ADS 

    Google Scholar 

  • 27.

    Le Quéré, C. et al. Global carbon budget 2017. Earth Syst. Sci. Data 10, 405–448 (2018).

    ADS 

    Google Scholar 

  • 28.

    Running, S. W. & Zhao, M. Daily GPP and Annual NPP (MOD17A2/A3) Products NASA Earth Observing System MODIS Land Algorithm User’s Guide v. 3 (MODIS Land Team, 2015).

  • 29.

    Jung, M. et al. Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations. J. Geophys. Res. 116, https://doi.org/10.1029/2010JG001566 (2011).

  • 30.

    Zeng, N. et al. Agricultural Green Revolution as a driver of increasing atmospheric CO2 seasonal amplitude. Nature 515, 394–397 (2014).

    CAS 
    PubMed 
    ADS 

    Google Scholar 

  • 31.

    Long, S. P. Modification of the response of photosynthetic productivity to rising temperature by atmospheric CO2 concentrations: has its importance been underestimated? Plant Cell Environ. 14, 729–739 (1991).

    CAS 

    Google Scholar 

  • 32.

    Stevens, N., Lehmann, C. E. R., Murphy, B. P. & Durigan, G. Savanna woody encroachment is widespread across three continents. Glob. Change Biol. 23, 235–244 (2017).

    ADS 

    Google Scholar 

  • 33.

    Fleischer, K. et al. Amazon forest response to CO2 fertilization dependent on plant phosphorus acquisition. Nat. Geosci. 12, 736–741 (2019).

    CAS 
    ADS 

    Google Scholar 

  • 34.

    Myneni, R. B. et al. Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sens. Environ. 83, 214–231 (2002).

    ADS 

    Google Scholar 

  • 35.

    Cernusak, L. A. et al. Tropical forest responses to increasing atmospheric CO2: current knowledge and opportunities for future research. Funct. Plant Biol. 40, 531–551 (2013).

    CAS 
    PubMed 

    Google Scholar 

  • 36.

    Ainsworth, E. A. & Rogers, A. The response of photosynthesis and stomatal conductance to rising [CO2]: mechanisms and environmental interactions. Plant Cell Environ. 30, 258–270 (2007).

    CAS 
    PubMed 

    Google Scholar 

  • 37.

    Baig, S., Medlyn, B. E., Mercado, L. M. & Zaehle, S. Does the growth response of woody plants to elevated CO2 increase with temperature? A model-oriented meta-analysis. Glob. Change Biol. 21, 4303–4319 (2015).

    ADS 

    Google Scholar 

  • 38.

    Yang, J. et al. Low sensitivity of gross primary production to elevated CO2 in a mature eucalypt woodland. Biogeosciences 17, 265–279 (2020).

    CAS 
    ADS 

    Google Scholar 

  • 39.

    McMurtrie, R. E., Comins, H. N., Kirschbaum, M. U. F. & Wang, Y. P. Modifying existing forest growth models to take account of effects of elevated CO2. Aust. J. Bot. 40, 657–677 (1992).

    CAS 

    Google Scholar 

  • 40.

    Luo, Y., Sims, D. A., Thomas, R. B., Tissue, D. T. & Ball, J. T. Sensitivity of leaf photosynthesis to CO2 concentration is an invariant function for C3 plants: a test with experimental data and global applications. Global Biogeochem. Cycles 10, 209–222 (1996).

    CAS 
    ADS 

    Google Scholar 

  • 41.

    Li, Q. et al. Leaf area index identified as a major source of variability in modeled CO2 fertilization. Biogeosciences 15, 6909–6925 (2018).

    CAS 
    ADS 

    Google Scholar 

  • 42.

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

    CAS 
    PubMed 
    ADS 

    Google Scholar 

  • 43.

    Zaehle, S. et al. Evaluation of 11 terrestrial carbon-nitrogen cycle models against observations from two temperate free-air CO2 enrichment studies. New Phytol. 202, 803–822 (2014).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 44.

    De Kauwe, M. G. et al. Where does the carbon go? A model-data intercomparison of vegetation carbon allocation and turnover processes at two temperate forest free-air CO2 enrichment sites. New Phytol. 203, 883–899 (2014).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 45.

    Stocker, B. D. et al Drought impacts on terrestrial primary production underestimated by satellite monitoring. Nat. Geosci. 12, 264–270 (2019).

    CAS 
    ADS 

    Google Scholar 

  • 46.

    Williamson, M. S. et al Emergent constraints on climate sensitivities. Rev. Mod. Phys. 93, 025004 (2021).

    MathSciNet 
    CAS 
    ADS 

    Google Scholar 

  • 47.

    Sanderson, B. et al. On structural errors in emergent constraints. Earth Syst. Dyn. Discuss. https://doi.org/10.5194/esd-2020-85 (2021).

  • 48.

    Fisher, J. B., Huntzinger, D. N., Schwalm, C. R. & Sitch, S. Modeling the terrestrial biosphere. Annu. Rev. Environ. Resour. 39, 91–123 (2014).

    Google Scholar 

  • 49.

    Arora, V. K. et al. Carbon-concentration and carbon-climate feedbacks in CMIP5 earth system models. J. Clim. 26, 5289–5314 (2013).

    ADS 

    Google Scholar 

  • 50.

    Ballantyne, A. et al. Accelerating net terrestrial carbon uptake during the warming hiatus due to reduced respiration. Nat. Clim. Change 7, 148–152 (2017).

    CAS 
    ADS 

    Google Scholar 

  • 51.

    Forkel, M. et al. Enhanced seasonal CO2 exchange caused by amplified plant productivity in northern ecosystems. Science 351, 696–699 (2016).

    CAS 
    PubMed 
    ADS 

    Google Scholar 

  • 52.

    Friedlingstein, P. et al. On the contribution of CO2 fertilization to the missing biospheric sink. Global Biogeochem. Cycles 9, 541–556 (1995).

    CAS 
    ADS 

    Google Scholar 

  • 53.

    Farquhar, G. D., von Caemmerer, S. & Berry, J. A. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta 149, 78–90 (1980).

    CAS 
    PubMed 

    Google Scholar 

  • 54.

    Myneni, R. B., Keeling, C. D., Tucker, C. J., Asrar, G. & Nemani, R. R. Increased plant growth in the northern high latitudes from 1981 to 1991. Nature 386, 698–702 (1997).

    CAS 
    ADS 

    Google Scholar 

  • 55.

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

    CAS 
    ADS 

    Google Scholar 

  • 56.

    Keenan, T. F. et al. Increase in forest water-use efficiency as atmospheric carbon dioxide concentrations rise. Nature 499, 324–327 (2013).

    CAS 
    PubMed 
    ADS 

    Google Scholar 

  • 57.

    Ukkola, A. M., Keenan, T. F., Kelley, D. I. & Prentice, I. C. Vegetation plays an important role in mediating future water resources. Environ. Res. Lett. 11, 094022 (2016).

    ADS 

    Google Scholar 

  • 58.

    Donohue, R. J., Roderick, M. L., McVicar, T. R. & Farquhar, G. D. Impact of CO2 fertilization on maximum foliage cover across the globe’s warm, arid environments. Geophys. Res. Lett. 40, 3031–3035 (2013).

    CAS 
    ADS 

    Google Scholar 

  • 59.

    Smith, N. G. & Dukes, J. S. Plant respiration and photosynthesis in global-scale models: incorporating acclimation to temperature and CO2. Glob. Change Biol. 19, 45–63 (2013).

    ADS 

    Google Scholar 

  • 60.

    De Kauwe, M. G. et al. A test of the ‘one-point method’ for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis. New Phytol. 210, 1130–1144 (2016).

    PubMed 

    Google Scholar 

  • 61.

    Maire, V. et al. The coordination of leaf photosynthesis links C and N fluxes in C3 plant species. PLoS ONE 7, e0038345 (2012).

    ADS 

    Google Scholar 

  • 62.

    Smith, N. G. & Keenan, T. F. Mechanisms underlying leaf photosynthetic acclimation to warming and elevated CO2 as inferred from least-cost optimality theory. Glob. Change Biol. 26, 806–834 (2020).

    Google Scholar 

  • 63.

    Lloyd, J. & Farquhar, G. The CO2 dependence of photosynthesis, plant growth responses to elevated atmospheric CO2 concentrations and their interaction with soil nutrient status. I. General principles and forest ecosystems. Funct. Ecol. 10, 4–32 (1996).

    Google Scholar 

  • 64.

    Ehleringer, J. & Björkman, O. Quantum yields for CO2 uptake in C3 and C4 plants: dependence on temperature, CO2, and O2 concentration. Plant Physiol. 59, 86–90 (1997).

    Google Scholar 

  • 65.

    Bernacchi, C. J., Singsaas, E. L., Pimentel, C., Portis, A. R. Jr & Long, SP. Improved temperature response functions for models of Rubisco-limited photosynthesis. Plant, Cell Environ. 24, 253–259 (2001).

    CAS 

    Google Scholar 

  • 66.

    Prentice, I. C., Dong, N., Gleason, S. M., Maire, V. & Wright, I. J. Balancing the costs of carbon gain and water transport: testing a new theoretical framework for plant functional ecology. Ecol. Lett. 17, 82–91 (2014).

    PubMed 

    Google Scholar 

  • 67.

    Wang, H. et al. Towards a universal model for carbon dioxide uptake by plants. Nat. Plants 3, 734–741 (2017).

    CAS 
    PubMed 

    Google Scholar 

  • 68.

    Huber, M. L. et al. New international formulation for the viscosity of H2O. J. Phys. Chem. Ref. Data 38, 101–125 (2009).

    CAS 
    ADS 

    Google Scholar 

  • 69.

    Still, C. J., Berry, J. A., Collatz, G. J. & DeFries, R. S. Global distribution of C3 and C4 vegetation: carbon cycle implications. Global Biogeochem. Cycles 17, 6-1–6-14 (2003).

    ADS 

    Google Scholar 

  • 70.

    Zhu, Z. et al. Global data sets of vegetation leaf area index (LAI)3g and fraction of photosynthetically active radiation (FPAR)3g derived from global inventory modeling and mapping studies (GIMMS) normalized difference vegetation index (NDVI3g) for the period 1981 to 2. Remote Sens. 5, 927–948 (2013).

    ADS 

    Google Scholar 

  • 71.

    Zhao, M. & Running, S. W. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science 329, 940–943 (2010).

    CAS 
    PubMed 
    ADS 

    Google Scholar 

  • 72.

    Gallego-Sala, A. et al. Bioclimatic envelope model of climate change impacts on blanket peatland distribution in Great Britain. Clim. Res. 45, 151–162 (2010).

    Google Scholar 

  • 73.

    Veroustraete, F. On the use of a simple deciduous forest model for the interpretation of climate change effects at the level of carbon dynamics. Ecol. Modell. 75–76, 221–237 (1994).

    Google Scholar 

  • 74.

    Jiang, C. & Ryu, Y. Multi-scale evaluation of global gross primary productivity and evapotranspiration products derived from Breathing Earth System Simulator (BESS). Remote Sens. Environ. 186, 528–547 (2016).

    ADS 

    Google Scholar 

  • 75.

    Zhang, S. et al. Evaluation and improvement of the daily boreal ecosystem productivity simulator in simulating gross primary productivity at 41 flux sites across Europe. Ecol. Modell. 368, 205–232 (2018).

    CAS 

    Google Scholar 

  • 76.

    Liu, Y., Hejazi, M., Li, H., Zhang, X. & Leng, G. A hydrological emulator for global applications-HE v1.0.0. Geosci. Model Dev. 11, 1077–1092 (2018).

    ADS 

    Google Scholar 

  • 77.

    Yuan, W. et al. Increased atmospheric vapor pressure deficit reduces global vegetation growth. Sci. Adv. 5, aax1396 (2019).

    ADS 

    Google Scholar 

  • 78.

    Haverd, V. et al. A new version of the CABLE land surface model (Subversion revision r4601) incorporating land use and land cover change, woody vegetation demography, and a novel optimisation-based approach to plant coordination of photosynthesis. Geosci. Model Dev. 11, 2995–3026 (2018).

    CAS 
    ADS 

    Google Scholar 

  • 79.

    Melton, J. R. & Arora, V. K. Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0. Geosci. Model Dev. 9, 323–361 (2016).

    CAS 
    ADS 

    Google Scholar 

  • 80.

    Oleson, K. W. et al. Technical Description of Version 4.0 of the Community Land Model (CLM) (National Center for Atmospheric Research, 2013).

  • 81.

    Tian, H. et al. North American terrestrial CO2 uptake largely offset by CH4 and N2O emissions: toward a full accounting of the greenhouse gas budget. Clim. Change 129, 413–426 (2015).

    CAS 
    PubMed 
    ADS 

    Google Scholar 

  • 82.

    Jain, A. K., Meiyappan, P., Song, Y. & House, J. I. CO2 emissions from land-use change affected more by nitrogen cycle, than by the choice of land-cover data. Glob. Change Biol. 19, 2893–2906 (2013).

    ADS 

    Google Scholar 

  • 83.

    Reick, C. H., Raddatz, T., Brovkin, V. & Gayler, V. Representation of natural and anthropogenic land cover change in MPI-ESM. J. Adv. Model Earth Syst. 5, 459–482 (2013).

    ADS 

    Google Scholar 

  • 84.

    Clark, D. B. et al. The Joint UK Land Environment Simulator (JULES), model description—Part 2: Carbon fluxes and vegetation dynamics. Geosci. Model Dev. 4, 701–722 (2011).

    ADS 

    Google Scholar 

  • 85.

    Smith, B. et al. Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model. Biogeosciences 11, 2027–2054 (2014).

    ADS 

    Google Scholar 

  • 86.

    Sitch, S. et al. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Glob. Chang. Biol. 9, 161–185 (2003).

    ADS 

    Google Scholar 

  • 87.

    Keller, K. M. et al. 20th century changes in carbon isotopes and water-use efficiency: tree-ring-based evaluation of the CLM4.5 and LPX-Bern models. Biogeosciences 14, 2641–2673 (2017).

    CAS 
    ADS 

    Google Scholar 

  • 88.

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

    ADS 

    Google Scholar 

  • 89.

    Guimberteau, M. et al. ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation. Geosci. Model Dev. 11, 121–163 (2018).

    CAS 
    ADS 

    Google Scholar 

  • 90.

    Zeng, N., Mariotti, A. & Wetzel, P. Terrestrial mechanisms of interannual CO2 variability. Global Biogeochem. Cycles 19, https://doi.org/10.1029/2004GB002273 (2005).

  • 91.

    Kato, E., Kinoshita, T., Ito, A., Kawamiya, M. & Yamagata, Y. Evaluation of spatially explicit emission scenario of land-use change and biomass burning using a process-based biogeochemical model. J. Land Use Sci. 8, 104–122 (2013).

    Google Scholar 

  • 92.

    Fernández-Martínez, M. et al. Atmospheric deposition, CO2, and change in the land carbon sink. Sci. Rep. 7, 9632 (2017).

    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 

  • 93.

    Ciais, P. et al. Large inert carbon pool in the terrestrial biosphere during the Last Glacial Maximum. Nat. Geosci. 5, 74–79 (2012).

    CAS 
    ADS 

    Google Scholar 

  • 94.

    Cheng, L. et al. Recent increases in terrestrial carbon uptake at little cost to the water cycle. Nat. Commun. 8, 110 (2017).

    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 

  • 95.

    Ueyama, M. et al. Inferring CO2 fertilization effect based on global monitoring land-atmosphere exchange with a theoretical model. Environ. Res. Lett. 15, 084009 (2020).

    CAS 
    ADS 

    Google Scholar 

  • 96.

    Pastorello, G. et al. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Sci. Data 7, 225 (2020).

    PubMed 
    PubMed Central 

    Google Scholar 


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