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A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change


Direct quantification of terrestrial biosphere responses to global change is crucial for projections of future climate change in Earth system models. Here, we synthesized ecosystem carbon-cycling data from 1,119 experiments performed over the past four decades concerning changes in temperature, precipitation, CO2 and nitrogen across major terrestrial vegetation types of the world. Most experiments manipulated single rather than multiple global change drivers in temperate ecosystems of the USA, Europe and China. The magnitudes of warming and elevated CO2 treatments were consistent with the ranges of future projections, whereas those of precipitation changes and nitrogen inputs often exceeded the projected ranges. Increases in global change drivers consistently accelerated, but decreased precipitation slowed down carbon-cycle processes. Nonlinear (including synergistic and antagonistic) effects among global change drivers were rare. Belowground carbon allocation responded negatively to increased precipitation and nitrogen addition and positively to decreased precipitation and elevated CO2. The sensitivities of carbon variables to multiple global change drivers depended on the background climate and ecosystem condition, suggesting that Earth system models should be evaluated using site-specific conditions for best uses of this large dataset. Together, this synthesis underscores an urgent need to explore the interactions among multiple global change drivers in underrepresented regions such as semi-arid ecosystems, forests in the tropics and subtropics, and Arctic tundra when forecasting future terrestrial carbon-climate feedback.

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Fig. 1: Global distribution of manipulative experiments and the magnitudes of experimental manipulations against model projections.
Fig. 2: Effects of different drivers on carbon-cycle variables.
Fig. 3: Local climate conditions and plant traits affecting carbon-cycle responses to global change drivers.
Fig. 4: Interaction types of two-driver pairs.

Data availability

The data supporting the results can be found in Song, J., Wan, S., Ru, J., Zhou, Z., Shao, P., Han, H., Lei, L., Wang, J., Li, X., Zhang, Q., Li, X., Su, F., Liu, B., Yang, F., Ma, G., Zhang, K., Hu, M., Yan, C., Zhang, A., Zhong, M., Hui, Y., Li, Y. & Zheng, M. Figshare


  1. 1.

    Curtis, P. S. & Wang, X. A meta-analysis of elevated CO2 effects on woody plant mass, form, and physiology. Oecologia 113, 299–313 (1998).

    PubMed  Google Scholar 

  2. 2.

    Rustad, L. E. et al. A meta-analysis of the responses of soil respiration, net nitrogen mineralization, and aboveground plant growth to experimental ecosystem warming. Oecologia 126, 543–562 (2001).

    CAS  PubMed  Google Scholar 

  3. 3.

    Xia, J. & Wan, S. Global response patterns of terrestrial plant species to nitrogen addition. New Phytol. 179, 428–439 (2008).

    CAS  PubMed  Google Scholar 

  4. 4.

    Lin, D., Xia, J. & Wan, S. Climate warming and biomass accumulation of terrestrial plants: a meta-analysis. New Phytol. 188, 187–198 (2010).

    PubMed  Google Scholar 

  5. 5.

    Wu, Z., Dijkstra, P., Koch, G. W., Peñuelas, J. & Hungate, B. A. Responses of terrestrial ecosystem to temperature and precipitation change: a meta-analysis of experimental manipulation. Global Change Biol. 17, 927–942 (2011).

    Google Scholar 

  6. 6.

    Beier, C. et al. Precipitation manipulation experiments—challenges and recommendations for the future. Ecol. Lett. 15, 899–911 (2012).

    PubMed  Google Scholar 

  7. 7.

    Knapp, A. K. et al. A reality check for climate change experiments: do they reflect the real world? Ecology 99, 2145–2151 (2018).

    PubMed  Google Scholar 

  8. 8.

    Kardol, P., De Long, J. R. & Sundqvist, M. K. Crossing the threshold: the power of multi-level experiments in identifying global change responses. New Phytol. 196, 323–326 (2012).

    PubMed  Google Scholar 

  9. 9.

    Dukes, J. S., Classen, A. T., Wan, S. & Langley, J. A. Using results from global change experiments to inform land model development and calibration. New Phytol. 204, 744–746 (2014).

    PubMed  Google Scholar 

  10. 10.

    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 

  11. 11.

    Medlyn, B. E. et al. Using ecosystem experiments to improve vegetation models. Nat. Clim. Change 5, 528–534 (2015).

    Google Scholar 

  12. 12.

    Norby, R. J. et al. Model-data synthesis for the next generation of forest free-air CO2 enrichment (FACE) experiments. New Phytol. 209, 17–28 (2016).

    CAS  PubMed  Google Scholar 

  13. 13.

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

    CAS  PubMed  Google Scholar 

  14. 14.

    Ahlström, A. et al. The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink. Science 348, 895–899 (2015).

    PubMed  Google Scholar 

  15. 15.

    Schuur, E. A. G. et al. Climate change and the permafrost carbon feedback. Nature 520, 171–179 (2015).

    CAS  Google Scholar 

  16. 16.

    IPCC Climate Change 2014: Synthesis Report (eds. Core Writing Team, Pachauri R. K. & Meyer L. A.) (IPCC, 2014).

  17. 17.

    Lamarque, J.-F. et al. Global and regional evolution of short-lived radiatively-active gases and aerosols in the Representative Concentration Pathways. Clim. Change 109, 191–212 (2011).

    CAS  Google Scholar 

  18. 18.

    Melillo, J. M. et al. Soil warming, carbon-nitrogen interactions, and forest carbon budgets. Proc. Natl Acad. Sci. USA 108, 9508–9512 (2011).

    CAS  PubMed  Google Scholar 

  19. 19.

    Hopkins, F. M., Torn, M. S. & Trumbore, S. E. Warming accelerates decomposition of decades-old carbon in forest soils. Proc. Natl Acad. Sci. USA 109, E1753–E1761 (2012).

    CAS  PubMed  Google Scholar 

  20. 20.

    Hoeppner, S. S. & Dukes, J. S. Interactive responses of old-field plant growth and composition to warming and precipitation. Global Change Biol. 18, 1754–1768 (2012).

    Google Scholar 

  21. 21.

    Liu, W., Zhang, Z. & Wan, S. Predominant role of water in regulating soil and microbial respiration and their responses to climate change in a semiarid grassland. Global Change Biol. 15, 184–195 (2009).

    Google Scholar 

  22. 22.

    Reich, P. B. et al. Effects of climate warming on photosynthesis in boreal tree species depend on soil moisture. Nature 562, 263–267 (2018).

    PubMed  Google Scholar 

  23. 23.

    Liu, L. et al. A cross-biome synthesis of soil respiration and its determinants under simulated precipitation changes. Global Change Biol. 22, 1394–1405 (2016).

    Google Scholar 

  24. 24.

    Mahecha, M. D. et al. Global convergence in the temperature sensitivity of respiration at ecosystem level. Science 329, 838–840 (2010).

    CAS  PubMed  Google Scholar 

  25. 25.

    Dacal, M., Bradford, M. A., Plaza, C., Maestre, F. T. & García-Palacios, P. Soil microbial respiration adapts to ambient temperature in global drylands. Nat. Ecol. Evol. 3, 232–238 (2019).

    PubMed  PubMed Central  Google Scholar 

  26. 26.

    Knapp, A. K. & Smith, M. D. Variation among biomes in temporal dynamics of aboveground primary production. Science 291, 481–484 (2001).

    CAS  PubMed  Google Scholar 

  27. 27.

    Knapp, A. K. et al. Consequences of more extreme precipitation regimes for terrestrial ecosystems. BioScience 58, 811–821 (2008).

    Google Scholar 

  28. 28.

    Knapp, A. K., Ciais, P. & Smith, M. D. Reconciling inconsistencies in precipitation-productivity relationships: implications for climate change. New Phytol. 214, 41–47 (2017).

    PubMed  Google Scholar 

  29. 29.

    Huxman, T. E. et al. Convergence across biomes to a common rain-use efficiency. Nature 429, 651–654 (2004).

    CAS  PubMed  Google Scholar 

  30. 30.

    Smith, M. D. et al. Global environmental change and the nature of aboveground net primary productivity responses: insights from long-term experiments. Oecologia 177, 935–947 (2015).

    PubMed  Google Scholar 

  31. 31.

    Trugman, A. T. et al. Tree carbon allocation explains forest drought-kill and recovery patterns. Ecol. Lett. 21, 1552–1560 (2018).

    CAS  PubMed  Google Scholar 

  32. 32.

    Litton, C. M., Raich, J. W. & Ryan, M. G. Carbon allocation in forest ecosystems. Global Change Biol. 13, 2089–2109 (2007).

    Google Scholar 

  33. 33.

    Meier, I. C. & Leuschner, C. Belowground drought response of European beech: fine root biomass and carbon partitioning in 14 mature stands across a precipitation gradient. Global Change Biol. 14, 2081–2095 (2008).

    Google Scholar 

  34. 34.

    Vicca, S. et al. Urgent need for a common metric to make precipitation manipulation experiments comparable. New Phytol. 195, 518–522 (2012).

    CAS  PubMed  Google Scholar 

  35. 35.

    Reinsch, S. et al. Shrubland primary production and soil respiration diverge along European climate gradient. Sci. Rep. 7, 43952 (2017).

    PubMed  PubMed Central  Google Scholar 

  36. 36.

    Leakey, A. D. B. et al. Elevated CO2 effects on plant carbon, nitrogen, and water relations: six important lessons from FACE. J. Exp. Bot. 60, 2859–2876 (2009).

    CAS  PubMed  Google Scholar 

  37. 37.

    Mooney, H. A., Drake, B. G., Luxmoore, R. J., Oechel, W. C. & Pitelka, L. F. Predicting ecosystem responses to elevated CO2 concentrations. BioScience 41, 96–104 (1991).

    Google Scholar 

  38. 38.

    Fatichi, S. et al. Partitioning direct and indirect effects reveals the response of water-limited ecosystems to elevated CO2. Proc. Natl Acad. Sci. USA 113, 12757–12762 (2016).

    CAS  PubMed  Google Scholar 

  39. 39.

    Hovenden, M. J., Newton, P. C. D. & Wills, K. E. Seasonal not annual rainfall determines grassland biomass response to carbon dioxide. Nature 511, 583–586 (2014).

    CAS  PubMed  Google Scholar 

  40. 40.

    Hovenden, M. J. et al. Globally consistent influences of seasonal precipitation limit grassland biomass response to CO2. Nat. Plants 5, 167–173 (2019).

    CAS  PubMed  Google Scholar 

  41. 41.

    Obermeier, W. A. et al. Reduced CO2 fertilization effect in temperate C3 grasslands under more extreme weather conditions. Nat. Clim. Change 7, 137–141 (2017).

    CAS  Google Scholar 

  42. 42.

    Norby, R. J., Wullschleger, S. D., Gunderson, C. A., Johnson, D. W. & Ceulemans, R. Tree responses to rising CO2: implications for the future forest. Plant Cell Environ. 22, 683–714 (1999).

    CAS  Google Scholar 

  43. 43.

    Terrer, C., Vicca, S., Hungate, B. A., Phillips, R. P. & Prentice, I. C. Mycorrhizal association as a primary control of the CO2 fertilization effect. Science 353, 72–74 (2016).

    CAS  Google Scholar 

  44. 44.

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

    Google Scholar 

  45. 45.

    Nie, M., Lu, M., Bell, J., Raut, S. & Pendall, E. Altered root traits due to elevated CO2: a meta-analysis. Global Ecol. Biogeogr. 22, 1095–1105 (2013).

    Google Scholar 

  46. 46.

    Suter, D. et al. Elevated CO2 increases carbon allocation to the roots of Lolium perenne under free-air CO2 enrichment but not in a controlled environment. New Phytol. 154, 65–75 (2002).

    CAS  Google Scholar 

  47. 47.

    Arnone, J. A. et al. Dynamics of root systems in native grasslands: effects of elevated atmospheric CO2. New Phytol. 147, 73–85 (2000).

    CAS  Google Scholar 

  48. 48.

    Iversen, C. M. Digging deeper: fine-root responses to rising atmospheric CO2 concentration in forested ecosystems. New Phytol. 186, 346–357 (2010).

    PubMed  Google Scholar 

  49. 49.

    Hungate, B. A. et al. The fate of carbon in grasslands under carbon dioxide enrichment. Nature 388, 576–579 (1997).

    CAS  Google Scholar 

  50. 50.

    Van Groenigen, K. J., Qi, X., Osenberg, C. W., Luo, Y. & Hungate, B. A. Faster decomposition under increased atmospheric CO2 limits soil carbon storage. Science 344, 508–509 (2014).

    PubMed  Google Scholar 

  51. 51.

    Song, J. et al. Elevated CO2 does not stimulate carbon sink in a semi-arid grassland. Ecol. Lett. 22, 458–468 (2019).

    PubMed  Google Scholar 

  52. 52.

    Luo, Y. & Weng, E. Dynamic disequilibrium of the terrestrial carbon cycle under global change. Trends Ecol. Evol. 26, 96–104 (2011).

    PubMed  Google Scholar 

  53. 53.

    LeBauer, D. S. & Treseder, K. K. Nitrogen limitation of net primary productivity in terrestrial ecosystems is globally distributed. Ecology 89, 371–379 (2008).

    PubMed  Google Scholar 

  54. 54.

    Janssens, I. A. et al. Reduction of forest soil respiration in response to nitrogen deposition. Nat. Geosci. 3, 315–322 (2010).

    CAS  Google Scholar 

  55. 55.

    Vicca, S. et al. Fertile forests produce biomass more efficiently. Ecol. Lett. 15, 520–526 (2012).

    CAS  PubMed  Google Scholar 

  56. 56.

    Verlinden, M. S. et al. Favorable effect of mycorrhizae on biomass production efficiency exceeds their carbon cost in a fertilization experiment. Ecology 99, 2525–2534 (2018).

    PubMed  Google Scholar 

  57. 57.

    Friedlingstein, P., Joel, G., Field, C. B. & Fung, I. Y. Toward an allocation scheme for global terrestrial carbon models. Global Change Biol. 5, 755–770 (1999).

    Google Scholar 

  58. 58.

    Smithwick, E. A., Lucash, M. S., McCormack, M. L. & Sivandran, G. Improving the representation of roots in terrestrial models. Ecol. Modell. 291, 193–204 (2014).

    CAS  Google Scholar 

  59. 59.

    Ye, C. et al. Reconciling multiple impacts of nitrogen enrichment on soil carbon: plant, microbial and geochemical controls. Ecol. Lett. 21, 1162–1173 (2018).

    PubMed  Google Scholar 

  60. 60.

    Leuzinger, S. et al. Do global change experiments overestimate impacts on terrestrial ecosystems? Trends Ecol. Evol. 26, 236–241 (2011).

    PubMed  Google Scholar 

  61. 61.

    Dieleman, W. I. J. et al. Simple additive effects are rare: a quantitative review of plant biomass and soil process responses to combined manipulations of CO2 and temperature. Global Change Biol. 18, 2681–2693 (2012).

    Google Scholar 

  62. 62.

    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. Global Change Biol. 21, 4303–4319 (2015).

    Google Scholar 

  63. 63.

    Zhou, L. et al. Interactive effects of global change factors on soil respiration and its components: a meta-analysis. Global Change Biol. 22, 3157–3169 (2016).

    Google Scholar 

  64. 64.

    Yue, K. et al. Influence of multiple global change drivers on terrestrial carbon storage: additive effects are common. Ecol. Lett. 20, 663–672 (2017).

    PubMed  Google Scholar 

  65. 65.

    Larsen, K. S. et al. Reduced N cycling in response to drought, warming, and elevated CO2 in a Danish heathland: synthesizing results of the CLIMAITE project after two years of treatments. Global Change Biol. 17, 1884–1899 (2011).

    Google Scholar 

  66. 66.

    Hungate, B. A., Dukes, J. S., Shaw, M. R., Luo, Y. & Field, C. B. Nitrogen and climate change. Science 302, 1512–1513 (2003).

    CAS  PubMed  Google Scholar 

  67. 67.

    Shaw, M. R. et al. Grassland responses to global environmental changes suppressed by elevated CO2. Science 298, 1987–1990 (2002).

    CAS  PubMed  Google Scholar 

  68. 68.

    Lu, M. et al. Responses of ecosystem carbon cycle to experimental warming: a meta-analysis. Ecology 94, 726–738 (2013).

    PubMed  Google Scholar 

  69. 69.

    Wang, X. et al. Soil respiration under climate warming: differential response of heterotrophic and autotrophic respiration. Global Change Biol. 20, 3229–3237 (2014).

    Google Scholar 

  70. 70.

    Wand, S. J., Midgley, G. F., Jones, M. H. & Curtis, P. S. Responses of wild C4 and C3 grass (Poaceae) species to elevated atmospheric CO2 concentration: a meta-analytic test of current theories and perceptions. Global Change Biol. 5, 723–741 (1999).

    Google Scholar 

  71. 71.

    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 

  72. 72.

    Luo, Y., Hui, D. & Zhang, D. Elevated CO2 stimulates net accumulations of carbon and nitrogen in land ecosystems: a meta-analysis. Ecology 87, 53–63 (2006).

    PubMed  Google Scholar 

  73. 73.

    Sillen, W. M. A. & Dieleman, W. I. J. Effects of elevated CO2 and N fertilization on plant and soil carbon pools of managed grasslands: a meta-analysis. Biogeosciences 9, 2247–2258 (2012).

    CAS  Google Scholar 

  74. 74.

    Tian, D., Wang, H., Sun, J. & Niu, S. Global evidence on nitrogen saturation of terrestrial ecosystem net primary productivity. Environ. Res. Lett. 11, 024012 (2016).

    Google Scholar 

  75. 75.

    De Boeck, H. J. et al. Global change experiments: challenges and opportunities. BioScience 65, 922–931 (2015).

    Google Scholar 

  76. 76.

    Estiarte, M. et al. Few multi-year precipitation-reduction experiments find a shift in the productivity-precipitation relationship. Global Change Biol. 22, 2570–2581 (2016).

    Google Scholar 

  77. 77.

    Kreyling, J., Jentsch, A. & Beier, C. Beyond realism in climate change experiments: Gradient approaches identify thresholds and tipping points. Ecol. Lett. 17, 125–e1 (2014).

    PubMed  Google Scholar 

  78. 78.

    Jentsch, A., Kreyling, J. & Beierkuhnlein, C. A new generation of climate-change experiments: events, not trends. Front. Ecol. Environ. 5, 365–374 (2007).

    Google Scholar 

  79. 79.

    Thompson, R. M., Beardall, J., Beringer, J., Grace, M. & Sardina, P. Means and extremes: building variability into community-level climate change experiments. Ecol. Lett. 16, 799–806 (2013).

    PubMed  Google Scholar 

  80. 80.

    Kayler, Z. E. et al. Experiments to confront the environmental extremes of climate change. Front. Ecol. Environ. 13, 219–225 (2015).

    Google Scholar 

  81. 81.

    Zhu, K., Chiariello, N. R., Tobeck, T., Fukami, T. & Field, C. B. Nonlinear, interacting responses to climate limit grassland production under global change. Proc. Natl Acad. Sci. USA 113, 10589–10594 (2016).

    CAS  PubMed  Google Scholar 

  82. 82.

    Langley, J. A. & Megonigal, J. P. Ecosystem response to elevated CO2 levels limited by nitrogen-induced plant species shift. Nature 466, 96–99 (2010).

    CAS  PubMed  Google Scholar 

  83. 83.

    Smith, M. D. The ecological role of climate extremes: current understanding and future prospects. J. Ecol. 99, 651–655 (2011).

    Google Scholar 

  84. 84.

    Kreyling, J. et al. To replicate, or not to replicate—that is the question: how to tackle nonlinear responses in ecological experiments. Ecol. Lett. 21, 1629–1638 (2018).

    PubMed  Google Scholar 

  85. 85.

    De Martonne, E. Une nouvelle fonction climatologique: l’indice d’aridité. La Météorologie 2, 449–458 (1926).

    Google Scholar 

  86. 86.

    Hedges, L. V., Gurevitch, J. & Curtis, P. S. The meta-analysis of response ratios in experimental ecology. Ecology 80, 1150–1156 (1999).

    Google Scholar 

  87. 87.

    Lajeunesse, M. J. On the meta-analysis of response ratios for studies with correlated and multi-group designs. Ecology 92, 2049–2055 (2011).

    Google Scholar 

  88. 88.

    Viechtbauer, W. Conducting meta-analyses in R with the metafor package. J. Stat. Software 36, 1–48 (2010).

    Google Scholar 

  89. 89.

    R Development Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2010).

  90. 90.

    Jennions, M. D., Lortie, C. J., Rosenberg, M. S. & Rothstein, H. R. in Handbook of Meta-Analysis in Ecology and Evolution (eds Koricheva, J., Gurevitch, J. & Mengersen, K.) 207–236 (Princeton Univ. Press, 2013).

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We thank J. Wang (Hebei University), S. Yang (Institute of Botany, Chinese Academy of Sciences), L. Zhou (East China Normal University), C. Qiao (Xinyang Normal University) and H. Li (Henan University) for their help in meta-analyses and interaction analyses, and H. Li, Y. Liu (Institute of Tibetan Plateau Research, Chinese Academy of Sciences) and Y. He (Peking University) for their help in plotting figures. This work was financially supported by the National Natural Science Foundation of China (grant nos. 31430015 and 31830012). This study emerged from the INTERFACE Workshop in Beijing, China ( supported by the US NSF DEB-0955771. We also acknowledge support from the ClimMani COST action (ES1308).

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S.W. designed the research. J.S., J.R., Z.Z., P.S., H.H., D.W., L. Lei, J.W., Xiaona L., Q.Z., Xiaoming L., F.S., B.L., F.Y., G.M., G.L., Yanchun L., Yinzhan L., Z.Y., K.Z., Y.M., M.H., C.Y., A.Z., M. Zhong, Y.H., Y. Li. and M. Zheng collected the 2,230 publications. J.S., J.R., Z.Z. and Q.L. performed the data extraction and analysis as well as figure plotting. J.S., S.W. and S.P. wrote the first draft of the manuscript, and A.K.K., A.T.C., S.V., P.C., M.J.H., S.L., C.B., P.K., J.X., Y. Luo, D.G., J.A.L., J.Z., J.S.D., J.T., J.C., K.S.H., L.M.K., L.R., L. Liu, M.D.S., P.H.T., R.Q.T., R.J.N., R.P.P., S.N., S.F. and Y.W. contributed substantially to revisions.

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Correspondence to Shiqiang Wan.

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Cross-reference table of 1,119 experiments and 2,230 publications.

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Song, J., Wan, S., Piao, S. et al. A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change. Nat Ecol Evol 3, 1309–1320 (2019).

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