Large-scale afforestation is regarded as an effective natural climate solution. However, afforestation-induced changes in soil organic C (SOC) are poorly quantified due to the paucity of large-scale sampling data. Here, we provide the first comprehensive assessment of the afforestation impact on SOC stocks with a pairwise comparative study of samples from 619 control-and-afforested plot pairs in northern China. We found context-dependent effects of afforestation on SOC: afforestation increases SOC density (SOCD) in C-poor soils but decreases SOCD in C-rich soils, especially in deeper soil. Thus, the fixed biomass/SOC ratio assumed in previous studies could overestimate the SOC enhancement by afforestation. By extrapolating the sampling data to the entire region, we estimate that afforestation increased SOC stocks in northern China by only 234.9 ± 9.6 TgC over the last three decades. The study highlights the importance of including pre-afforestation soil properties in models of soil carbon dynamics and carbon sink projections.
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The data that support the findings of this study are available from the corresponding authors upon reasonable request.
Bastin, J. F. et al. The global tree restoration potential. Science 365, 76–79 (2019).
IPCC Climate Change 2014: Synthesis Report (eds Core Writing Team, Pachauri, R. K. & Meyer L. A.) (IPCC, 2014); http://ipcc.ch/report/ar5/
Global Forest Resources Assessment 2015 (FAO, 2016).
Lu, F. et al. Effects of national ecological restoration projects on carbon sequestration in China from 2001 to 2010. Proc. Natl Acad. Sci. USA 115, 4039–4044 (2018).
Yao, Y., Piao, S. & Wang, T. Future biomass carbon sequestration capacity of Chinese forests. Sci. Bull. 63, 1108–1117 (2018).
Fang, J., Chen, A., Peng, C., Zhao, S. & Ci, L. Changes in forest biomass carbon storage in China between 1949 and 1998. Science 292, 2320–2322 (2001).
Paul, K., Polglase, P., Nyakuengama, J. & Khanna, P. K. Change in soil carbon following afforestation. For. Ecol. Manag. 168, 241–257 (2002).
Guo, L. & Gifford, R. Soil carbon stocks and land use change: a meta-analysis. Glob. Change Biol. 8, 345–360 (2002).
Shi, S., Zhang, W., Zhang, P., Yu, Y. & Ding, F. A synthesis of change in deep soil organic carbon stores with afforestation of agricultural soils. For. Ecol. Manag. 296, 53–63 (2013).
Don, A., Schumacher, J. & Freibauer, A. Impact of tropical land-use change on soil organic carbon stocks—a meta-analysis. Glob. Change Biol. 17, 1658–1670 (2011).
Li, D., Niu, S. & Luo, Y. Global patterns of the dynamics of soil carbon and nitrogen stocks following afforestation: a meta-analysis. New Phytol. 195, 172–181 (2012).
Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).
Shvidenko, A. & Nilsson, S. A synthesis of the impact of Russian forests on the global carbon budget for 1961–1998. Tellus 55B, 391–415 (2003).
Piao, S. et al. The carbon balance of terrestrial ecosystems in China. Nature 458, 1009–1013 (2009).
Eighth National Forest Resource Inventory Report (2009–2013) (State Forestry Administration of the People’s Republic of China, 2014).
He, B., Chen, A., Wang, H. & Wang, Q. Dynamic response of satellite-derived vegetation growth to climate change in the Three North Shelter Forest region in China. Remote Sens. 7, 9998–10016 (2015).
Bryan, B. et al. China’s response to a national land-system sustainability emergency. Nature 559, 193–204 (2018).
Duan, H. et al. Assessing vegetation dynamics in the Three-North Shelter Forest region of China using AVHRR NDVI data. Environ. Earth Sci. 64, 1011–1020 (2011).
Houghton, R. The annual net flux of carbon to the atmosphere from changes in land use 1850–1990. Tellus Ser. B 51, 298–313 (1999).
Li, W. et al. Temporal response of soil organic carbon after grassland-related land-use change. Glob. Change Biol. 24, 4731–4746 (2018).
Peng, S. et al. Afforestation in China cools local land surface temperature. Proc. Natl Acad. Sci. USA 111, 2915–2919 (2014).
Shi, S. & Han, P. Estimating the soil carbon sequestration potential of China’s Grain for Green Project. Glob. Biogeochem. Cycles 28, 1279–1294 (2014).
Wang, W. et al. Changes in soil organic carbon, nitrogen, pH and bulk density with the development of larch (Larix gmelinii) plantations in China. Glob. Change Biol. 17, 2657–2676 (2011).
Binkley D. & Fisher R. Ecology and Management of Forest Soils 4th edn (Wiley-Blackwell, 2013).
Crowther, T. et al. Quantifying global soil carbon losses in response to warming. Nature 540, 104–108 (2016).
Zhu, J. et al. Carbon stocks and changes of dead organic matter in China’s forests. Nat. Commun. 8, 151 (2017).
Davidson, E. & Janssens, I. Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature 440, 165–173 (2006).
Harden, J. et al. Networking our science to characterize the state, vulnerabilities, and management opportunities of soil organic matter. Glob. Change Biol. 24, e705–e718 (2018).
Kuzyakov, Y. Priming effects: interactions between living and dead organic matter. Soil Biol. Biochem. 42, 1363–1371 (2010).
Kuzyakov, Y., Friedel, J. & Stahr, K. Review of mechanisms and quantification of priming effects. Soil Biol. Biochem. 32, 1485–1498 (2000).
Hart, P., Rayner, J. & Jenkinson, D. Influence of pool substitution on the interpretation of fertilizer experiments with 15N. J. Soil Sci. 37, 389403 (1986).
Balesdent, J. et al. Atmosphere–soil carbon transfer as a function of soil depth. Nature 559, 599–602 (2018).
Schlesinger, W. & Lichter, J. Limited carbon storage in soil and litter of experimental forest plots under increased atmospheric CO2. Nature 411, 466–469 (2001).
Hong, S. et al. Afforestation neutralizes soil pH. Nat. Commun. 9, 520 (2018).
Li, Y., Piao, S., Chen, A., Ciais, P. & Li, L. Z. X. Local and teleconnected temperature effects of afforestation and vegetation greening in China. Natl Sci. Rev. 7, 897–912 (2020).
Piao, S. et al. Characteristics, drivers and feedbacks of global greening. Nat. Rev. Earth Environ. 1, 14–27 (2020).
Xiong, Y. & Li, Q. Soils in China (Press of Sciences, 1987).
Xie, Z. et al. Soil organic carbon stocks in China and changes from 1980s to 2000s. Glob. Change Biol. 13, 1989–2007 (2007).
Fang, J., Liu, G. & Xu, S. Biomass and net production of forest vegetation in China. Acta Ecologica Sinica 16, 497–508 (1996).
Yang, K., He, J., Tang, W., Qin, J. & Cheng, C. On downward shortwave and longwave radiations over high altitude regions: observation and modeling in the Tibetan Plateau. Agric. For. Meteorol. 150, 38–46 (2010).
Chen, Y. et al. Improving land surface temperature modeling for dry land of China. J. Geophys. Res. Atmos. 116, 999–1010 (2011).
Batjes, N. World Soil Property Estimates for Broad-scale Modelling (WISE30sec, v.1.0) Report 2015/01 (ISRIC Soil Data Hub, 2015).
Harmonized World Soil Database Version 1.2 (FAO, 2012).
Running, S. MOD17A3H v006 MODIS/Terra Net Primary Production Yearly L4 Global 500m SIN Grid (NASA, 2015); https://doi.org/10.5067/modis/mod17a3h.006
Vegetation Atlas of China (Press of Sciences, 2001).
Zhang, Y., Yao, Y., Wang, X., Liu, Y. & Piao, S. Mapping spatial distribution of forest age in China. Earth Space Sci. 4, 108–116 (2017).
Benjamini, Y. & Yekutieli, D. The control of false discovery rate in multiple testing under dependency. Ann. Stat. 4, 1165–1188 (2001).
Elith, J., Leathwick, J. & Hastie, T. Working guide to boosted regression trees. J. Anim. Ecol. 77, 802–813 (2008).
Friedman, J. Stochastic gradient boosting. Comput. Stat. Data Anal. 38, 367–378 (2002).
Friedman, J. & Meulman, J. Multiple additive regression trees with application in epidemiology. Stat. Med. 22, 1365–1381 (2010).
Zeng, Z., Chen, A., Piao, S., Rabin, S. & Shen, Z. Environmental determinants of tropical forest and savanna distribution: a quantitative model evaluation and its implication. J. Geophys. Res. Biogeosci. 119, 1432–1445 (2014).
This study was supported by the National Key R&D Program of China grant no. 2017YFA0604702, the Strategic Priority Research Program (A) of the Chinese Academy of Sciences grant no. XDA20050101 and National Natural Science Foundation of China grant no. 41988101.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended Data Fig. 2 Robustness test of the negative correlation between ΔSOCD and SOCD_c across six tree species groups.
The same methods are used with Extended Data Fig. 1.
The central lines in the box-whisker plots indicate the medians, and the bottom and top edges of the boxes indicate the 25th and 75th percentiles, respectively. The maximum whisker lengths are specified as 1.5 times the interquartile range, and outliers are marked using+. Independent sample t-tests with false discovery rate correction were conducted to compare the data of each group with 0. p > 0.05 for all five groups. A one-way ANOVA (post hoc LSD test) was also used to test the difference between groups (p = 0.07).
80% of the samples are randomly selected to train the model and the remaining are used for test, which is repeated for 10 times to avoid contingency.
The uncertainty is from standard errors between BRT models run for 100 times.
Three profiles were dug in each plot.
The bars indicate the frequency distribution of the coefficient of variations for soil organic carbon densities between three profiles in each plot.
Extended Data Fig. 8 Uncertainties of the thresholds estimated from bootstrapping method across six tree species and all groups pooled together.
Error bars indicate the 95% confidence intervals.
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Hong, S., Yin, G., Piao, S. et al. Divergent responses of soil organic carbon to afforestation. Nat Sustain (2020). https://doi.org/10.1038/s41893-020-0557-y