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Reduced phosphorus availability in paddy soils under atmospheric CO2 enrichment

Nature Geoscience volume 16, pages 162–168 (2023)Cite this article

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Abstract

Phosphorus is an essential element for plant metabolism and growth, but its future supply under elevated levels of atmospheric CO2 remains uncertain. Here we present measurements of phosphorus concentration from two long-term (15 and 9 years) rice free air carbon dioxide enrichment experiments. Although no changes were observed in the initial year of the experiments, by the end of the experiments soil available phosphorus had declined by more than 20% (26.9% and 21.0% for 15 and 9 years, respectively). We suggest that the reduction can be explained by the production of soil organic phosphorus that is not in a readily plant-available form, as well as by increased removal through crop harvest. Our findings further suggest that increased transfers of plant available phosphorus from biological, biochemical and chemical phosphorus under anthropogenic changes are insufficient to compensate for reductions to plant available phosphorus under long-term exposure to elevated CO2. We estimate that reductions to rice yields could be particularly acute in low-income countries under future CO2 scenarios without the input of additional phosphorus fertilizers to compensate, despite the potentially reduced global risk for phosphorus pollution.

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Fig. 1: Responses of plant and soil to eCO2 in two rice FACE experiments.
Fig. 2: Changes of soil available P concentrations under eCO2 relative to aCO2 in upland (non-rice) crops and paddy rice.
Fig. 3: Conceptual model illustrating the effects of eCO2 on soil P pools in paddy soils in the short term and long term.
Fig. 4: Changes in rice yield reduction and potential P pollution risks due to eCO2.

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Data availability

The data supporting the findings of this study are available within the Article and the Supplementary Information, and we have deposited the global dataset in the figshare repository (https://doi.org/10.6084/m9.figshare.21103078.v2 ref. 64). Global rice yield data of the 14 main rice-planting countries can be accessed from FAOSATA (http://faostat.fao.org/default.aspx, 2019). Global rice harvest area data for extracting global rice pixels are available from https://www.mapspam.info/data/. Global soil P pools and P budgets can be accessed at https://esdac.jrc.ec.europa.eu/content/global-phosphorus-losses-due-soil-erosion.

Code availability

Code used in data processing and figure generation is provided through https://doi.org/10.6084/m9.figshare.21098458.v2 (ref. 65).

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Acknowledgements

We acknowledge the enduring contributions of J. Zhu, who initiated and supervised study PL-M from 2004 to 2016, and G. Pan and X. Liu who established and supervised study PH from 2011. The FACE system instruments of study PL-M were supplied by the National Institute of Agro-Environmental Sciences and the Agricultural Research Center of Tohohu Region (Japan). We received funding from the Key-Area Research and Development Program of Guangdong Province, China (2020B0202010006 to C.Z.), the National Key Research and Development Program of China (2021YFD1700802 to Y.W.), the National Natural Science Foundation of China (42277026 to Y.W., 31870423 to C.Z. and 32001191 to L.S.), the Chinese Academy of Sciences ‘0-1’ program (ZDBS-LY-DQC020 to C.Z.), the Jiangsu Science and Technology Department (BM2022002 to C.Z.), Innovation Program of Institute of Soil Science (ISSASIP2201 to Y.W.), a Spanish Government grant (PID2019-110521GB-I00 to J.P.), French state aid managed by the ANR under the ‘Investissements d’avenir’ programme (ANR16-CONV-0003 to P.C.), and the Carbon Peaking and Carbon Neutrality Special Fund for Science and Technology from Nanjing Science and Technology Bureau (20221103 to C.Z.).

Author information

Author notes

  1. These authors contributed equally: Yu Wang, Yuanyuan Huang.

Authors and Affiliations

  1. State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China

    Yu Wang, Lian Song, Jiahui Yuan, Yujun Wang, Jishuang Zhang, Ye Tao, Shenqiang Wang, Gang Liu, Xiaoyuan Yan & Chunwu Zhu

  2. CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia

    Yuanyuan Huang

  3. Key Laboratory of Surficial Geochemistry, Ministry of Education, School of Earth Sciences and Engineering, Nanjing University, Nanjing, China

    Wei Li

  4. Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, China

    Yongguan Zhu

  5. Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China

    Yongguan Zhu

  6. Department of Renewable Resources, University of Alberta, Edmonton, Alberta, Canada

    Scott X. Chang

  7. School of Integrative Plant Science, Cornell University, Ithaca, NY, USA

    Yiqi Luo

  8. Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France

    Philippe Ciais

  9. CSIC, Global Ecology Unit CREAF-CSIC-UAB, Bellaterra, Spain

    Josep Peñuelas

  10. CREAF, Cerdanyola del Vallès, Spain

    Josep Peñuelas

  11. Adaptive Cropping Systems Laboratory, US Department of Agriculture, Agricultural Research Service, Beltsville, MD, USA

    Julie Wolf

  12. Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, Saskatchewan, Canada

    Barbara J. Cade-Menun

  13. Department of Entomology and Plan Pathology, North Carolina State University, Raleigh, NC, USA

    Shuijin Hu

  14. Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing, China

    Lei Wang

  15. School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, USA

    Dengjun Wang

  16. State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China

    Zengwei Yuan

  17. Tourism College, Henan Normal University, Xinxiang, China

    Jishuang Zhang

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  1. Yu Wang
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Contributions

Conceptualization was provided by C.Z., Yu Wang and Y.H., methodology by C.Z., Yu Wang, Y.H., J.Y., L.S., W.L., J.Z., Y.T. and G.L., investigations by C.Z., Yu Wang and Y.H., data curation by Yu Wang, Y.H., J.Y., L.S. and W.L., and formal analysis by Yu Wang, Y.H., J.Y., L.S., J.P. and S.X.C. Supervision was provided by C.Z. and Yu Wang. The original draft was written by Yu Wang, Y.H., L.S. and C.Z. The paper was reviewed and edited by Yu Wang, Y.H., L.S., S.X.C., Y.Z., Y.L., P.C., J.P., J.W., B.J.C.-M., S.H., D.W., Z.Y., Yujun Wang, S.W., X.Y. and C.Z.

Corresponding author

Correspondence to Chunwu Zhu.

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Nature Geoscience thanks David Ellsworth and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Xujia Jiang, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Variations of soil P factions under eCO2 and aCO2 in two China Rice FACE experiments.

The samples were collected at the rice harvest stage in agroecosystem with low-moderate P (PL-M) in 2004, 2009, 2015 and 2018, respectively. The high P (PH) agroecosystem samples were collected at the rice harvest stage in 2019. Data are means ± standard deviation (n = 3). PL-M and PH were initiated in 2004 and 2011, respectively. Statistical test results are provided in Table 1 and Supplementary Table 2.

Extended Data Fig. 2 Variations of 31P NMR spectra under elevated atmospheric CO2 (eCO2) in comparison with ambient CO2 (aCO2) concentrations in two China Rice FACE experiments.

a. b, 31P solid-state NMR spectra in 2018 (PL-M) and 2019 (PH) at the 0-10 cm soil layer. The peak at 2.6 ppm is indicative of apatite (Ca − P mineral, primary mineral P). c. d, 31P liquid-state NMR spectra in 2018 (PL-M) and 2019 (PH) at the 0-10 cm soil layer. The 31P NMR chemical shifts suggest the presence of orthophosphate (6 ppm), phosphate monoesters (4-5 ppm), phospholipids (1-2.5 ppm), DNA (-1 ppm), and pyrophosphate (-4 to -5 ppm); Pi in d refers to the sum of inorganic ortho-P and pyrophosphate, Po refers to the sum of phosphate monoesters and diester (mainly DNA-P). PL-M and PH were initiated in 2004 and 2011, respectively.

Extended Data Fig. 3 Straw biomass, grain yield, straw P content and grain P content under aCO2 and eCO2 in two rice FACE experiments.

Data were collected in 2018 from a low-moderate P (PL-M) agroecosystem, and in 2019 from a high P (PH) agroecosystem. Data are means ± standard deviation (n = 3). Asterisks denote the results of ANOVA and Tukey tests, and indicate significant differences between means at p < 0.05.

Extended Data Fig. 4 Rice yield and grain P content response to elevated CO2.

Dots indicate results of FACE experiments in Wuxi, Jiangdu, Changshu, Tsukuba, and Shizukuishi. The IQR indicates the interquartile range. The data are from references4,6,30,51,66,67,68,69,70,71,72,73,74,75.

Extended Data Fig. 5 In-situ images of rice roots at the heading stage in agroecosystems in high available P experiment.

The image on the left is for the aCO2 treatment, and the image on the right is for the eCO2 treatment. Data are means ± standard deviation (n = 3). Asterisks denote the results of ANOVA and Tukey tests, and indicate significant differences between means at p < 0.05.

Extended Data Fig. 6 Relationships between soil P fractions and microbial properties (Pearson correlation coefficients, r) under aCO2 and eCO2 in 2018 (PL-M) and 2019 (PH).

The values of p denote the results of ANOVA and Tukey tests, and described the significance for p < 0.05, p < 0.01, and p < 0.001. Soil available P, the sum of resin-P and NaHCO3-Pi; Secondary mineral P, NaOH-Pi; Primary mineral P, HCl-Pi; Organic P, the sum of NaHCO3-Po and NaOH-Po; Occluded P, residual P. Soil microbial properties include bacterial biomass (B), fungal biomass (F), the ratio of fungal to bacteria biomass (F:B ratio), biomass of arbuscular mycorrhizal fungi (AMF), and the activities of acid phosphatase (ACP), and alkaline phosphatase (ALP).

Extended Data Fig. 7 Soil available P under eCO2 relative to aCO2 in different systems based on new data from this study for farmland and the literature.

The values indicate the change (eCO2 - aCO2) for soil P pool sizes due to eCO2. Soil available P includes different indices including resin P, NaHCO3-Pi, and Olsen P (shown in Supplementary Table 1). The line and empty square in each box represent the median and mean, respectively. Whiskers mark the 10th and 90th percentiles, and the outliers are shown as dots. The number of experimental outcomes was defined as n.

Extended Data Fig. 8 Global distribution of rice yield reduction and potential P pollution risk.

a, Global distribution of yield reduction risk level (1: extremely low, 2: low, 3: medium, 4: high, 5: extremely high; see Methods). b, Global distribution of potential P pollution risk level (0: no risk, 1: with potential environment risk). Note the size of the squares does not represent the actual area of rice paddy fields in Panels a and b.

Extended Data Fig. 9 Bar plot of mean GDP per capita during 2010–2020 for 14 global rice grown countries according to the 2019 World Bank income classifications.

The error bar indicates the standard deviation of GDP per capita during 2010–2020, the horizontal red dash line indicates the threshold value for low-income and middle-high income countries, and the vertical red dash line indicates the grouping of low-income and middle-high countries. The IQR indicates the interquartile range.

Extended Data Fig. 10 Relationship between Olsen P and available P in paddy soil.

The data are from references76,77,78,79,80,81. The shaded area represents the 95% confidence interval for the fitted line.

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2, Tables 1–5 and references.

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Wang, Y., Huang, Y., Song, L. et al. Reduced phosphorus availability in paddy soils under atmospheric CO2 enrichment. Nat. Geosci. 16, 162–168 (2023). https://doi.org/10.1038/s41561-022-01105-y

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