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Agricultural trade impacts global phosphorus use and partial productivity

Nature Food volume 4, pages 762–773 (2023)Cite this article

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Abstract

The spatio–temporal distribution, flow and end use of phosphorus (P) embedded in traded agricultural products are poorly understood. Here we use global trade matrices to analyse the partial factor productivity of P (output per unit of P input) for crop and livestock products in 200 countries and their cumulative contributions to the export or import of agricultural products over 1961–2019. In these six decades, the trade of agricultural P products has increased global partial factor productivity for crop and livestock production and has theoretically saved 67 Tg P in fertilizers and 1.6 Tg P in feed. However, trade is now at risk of contributing to wasteful use of P resources globally due to a decline in trade optimality, as agricultural products are increasingly exported from low to high partial factor productivity countries and due to P embedded in imported agricultural products mainly lost to the environment without recycling. Integrated crop–livestock production systems and P-recycling technologies can help.

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Fig. 1: P flow in agricultural product trade and use across regions.
Fig. 2: Annual changes for trade functionality and optimality.
Fig. 3: Changes in fertilizer-P productivity for traded countries.
Fig. 4: Factors of P fertilizer productivity and crop product trade.
Fig. 5: Theoretical savings or wastage of fertilizer- and feed-P.

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Data availability

All data needed to evaluate the conclusions of this study are available in the paper itself and/or the Supplementary Information file. Source data are provided with this paper.

Code availability

The custom algorithm used for this study is available in the Methods and the Supplementary Information.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (U20A2047, T2222016, 32102496, 41925004); the Youth Innovation Promotion Association, CAS (2019101); Key R&D Program of Hebei (21327507D); Hebei Dairy Cattle Innovation Team of Modern Agro-industry Technology Research System (HBCT2018120206) and China Postdoctoral Science Foundation (2021M693395).

Author information

Author notes

  1. These authors contributed equally: Zhaohai Bai, Ling Liu.

Authors and Affiliations

  1. Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Soil Ecology, Center for Agricultural Resources Research, Institute of Genetic and Developmental Biology, The Chinese Academy of Sciences, Shijiazhuang, China

    Zhaohai Bai, Ling Liu & Lin Ma

  2. Xiongan Institute of Innovation, The Chinese Academy of Sciences, Xiongan, China

    Zhaohai Bai

  3. International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria

    Michael Obersteiner & Aline Mosnier

  4. Sustainable Development Solutions Network, Paris, France

    Aline Mosnier

  5. Interdisciplinary Research Center for Agriculture Green Development in Yangtze River Basin, College of Resources and Environment, Southwest University, Chongqing, China

    Xinping Chen & Lin Ma

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

    Zengwei Yuan

  7. Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, China

    Zengwei Yuan

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  1. Zhaohai Bai
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Contributions

Z.B. and L.M. developed the original research question and designed the paper. L.L. performed the original data collection and data processing and prepared the figures and tables. All the authors wrote and revised the paper.

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Correspondence to Zhaohai Bai or Lin Ma.

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Nature Food thanks Philip Haygarth, Johan Karlsson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Illustration of trade functionality and optimality.

Sensitivity of trade functionality and optimality (a), Crop productivity of exporting (b) and importing (c) countries in terms of calorie-corrected partial factor productivity of fertilizer-P, Livestock productivity of exporting (d) and importing (e) countries in terms of calorie-corrected partial factor productivity of feed from 1961 to 2019. Note: CPHE is the relative concentration of production in high-productivity countries applied to importing and exporting countries (CPHEim and CPHEex; dimensionless). CWPE is the CPHE weighted production efficacy applied to importing and exporting countries (CWPEim and CWPEex; M kcal kg-1 P). CPHE and CWPE were also defined as trade functionality and optimality in this study. The error bars represent the change of the maximum productivity at 98.5%, 99.0% and 99.5% contributions to the total traded products (n = 3).

Source data

Extended Data Fig. 2 Cumulative calorie-corrected productivity-trade distribution curves.

a-f, Crop productivity of exporting and importing countries in terms of calorie-corrected partial factor productivity of fertilizer-P. g-l, Livestock production in terms of calorie-corrected partial factor productivity. Note: CPHE is the relative concentration of production in high-productivity countries applied to importing and exporting countries (CPHEim and CPHEex, dimensionless). CWPE is the CPHE weighted production efficacy applied to importing and exporting countries (CWPEim and CWPEex, M kcal kg-1 P). The error bars represent the change of the maximum productivity at 98.5%, 99.0% and 99.5% contributions to the total traded products (n = 3).

Source data

Extended Data Fig. 3 Factors of feed-P productivity and livestock product trade.

The correlation between partial factor productivity of feed-P for livestock production (PFPlivestock) and impact factors (a), and the correlation between livestock products trade and impact factors (b) in the different countries for the two recent decades. Note: Exporting and importing countries are determined by the net livestock calorie trade per country during 2017 and 2019; Low and high PFPlivestock was determined by the PFPlivestock value of each country below or above global average PFPlivestock during 2017 and 2019. The left column represents contribution to export or import (in %); The colour and direction of arrows represent the changes of PFPlivestock and trade, determined by the slope of correlations and R2 values. The colour and size of circles represents the correlation of different factors with PFPlivestock and contribution to trade, respectively. The larger the values is, the larger the positive or negative effects are. The middle colour shaded squares represent the level of grazing intensity for different countries.

Source data

Extended Data Fig. 4 Changes in feed-P productivity for traded countries.

a, c, high-productivity exporting (a) and importing (c) countries, b, d, low-productivity exporting (b) and importing (d) countries from 1961 to 2019. Geographical distribution of PFPlivestock for high or low productivity exporting and importing countries in 2019 (e), Top 20 exporting and importing countries in 2019 (f). Note: The dotted line in Extended Data Fig. 4a, b, d represents a shift in trade state. Map layers were obtained from site: https://datacatalog.worldbank.org/search/dataset/0038272/World-Bank-Official-Boundaries.

Source data

Extended Data Fig. 5 Cumulative curves of calorie corrected productivity-trade and its impact.

Cumulative productivity-trade distribution curves of exporting and importing countries for crop calorie corrected partial total P productivity (a), changes of the ratio between CWPEex and CWPEim (b), the summed (c) and average (d) theoretical saving or wastage of total P through trade from 1961 to 2019. Note: CPHE is the relative concentration of production in high-productivity countries applied to importing and exporting countries (CPHEim and CPHEex, dimensionless). CWPE is the weighted production efficacy, applied to importing and exporting countries (CWPEim and CWPEex, M kcal kg-1 P). The error bars represent the change of maximum productivity at 99.0% ± 0.50% contributions to the total traded products (n = 3 for summed theoretical total P saving, n = 10 for average theoretical total P saving).

Source data

Extended Data Fig. 6 Current cumulative productivity-trade distribution curves.

Crop calorie corrected partial fertilizer-P productivity (a), partial total P productivity (b) of exporting and importing countries in 2017/19. Note: CPHE is the relative concentration of production in high-productivity countries applied to importing and exporting countries (CPHEim and CPHEex, dimensionless). CWPE is the weighted production efficacy, applied to importing and exporting countries (CWPEim and CWPEex, M kcal kg-1 P). The error bars represent the change of the maximum productivity at 98.5%, 99.0% and 99.5% contributions to the total traded products (n = 3).

Source data

Extended Data Fig. 7 Changes of cumulative productivity-trade distribution curves after used the advanced technology in 2017/19.

Treated human waste (a-c), poultry manure (d), pig manure (e) and all waste (f).Note: CPHE is the relative concentration of production in high-productivity countries applied to importing and exporting countries (CPHEim and CPHEex, dimensionless). CWPE is the weighted production efficacy, applied to importing and exporting countries (CWPEim and CWPEex, M kcal kg-1 P). The error bars represent the change of the maximum productivity at 98.5%, 99.0% and 99.5% contributions to the total traded products (n = 3).

Source data

Extended Data Fig. 8 Sensitivity of functionality, optimality, P resource saving.

a-c, crop trade functionality (a), optimality (b), and ratio of optimality (c) at 98.0% ± 1.0%, d-f, crop trade functionality (d), optimality (e), and ratio of optimality (f) at 97.0% ± 2.0%. g-i, livestock trade functionality (g), optimality (h), and ratio of optimality (i) at 98.0% ± 1.0%, j-l, livestock trade functionality (j), optimality (k), and ratio of optimality (l) at 97.0% ± 2.0%. m-o, fertilizer-P saving at 99.0 ± 0.5% (m), 98.0% ± 1.0% (n), 97.0% ± 2.0% (o). p-r, fertilizer-P saving at 99.0 ± 0.5% (p), 98.0% ± 1.0% (q), 97.0% ± 2.0% (r). Note: Shading in Extended Data Fig. 8 a-c, g-i, n, q shows 1.0% sensitivity. Shading in Extended Data Fig. 8 d-f, j-l, o, r shows 2.0% sensitivity. Shading in Extended Data Fig. 8m, p shows 0.5% sensitivity.

Source data

Extended Data Fig. 9 Cumulative protein-corrected productivity-trade distribution curves.

a-f, crop productivity of exporting and importing countries in terms of protein-corrected partial factor productivity of fertilizer-P. g-l, livestock production in terms of protein-corrected partial factor productivity.

Source data

Extended Data Fig. 10 Cumulative curves of protein-corrected productivity-trade and its impact.

Cumulative productivity-trade distribution curves of exporting and importing countries for protein-corrected fertilizer-P (a), feed-P (d), and total P productivity (g). The summed theoretical saving of fertilizer-P (b), feed-P (e), and total P (h), average theoretical saving of fertilizer-P (c), feed-P (f), and total P (i) through trade from 1961 to 2019. Note: The error bars represent the change of the maximum productivity at 98.5%, 99.0% and 99.5% contributions to the total traded products (n = 3 for CPHE, CWPE and summed theoretical saving; n = 10 for average theoretical saving).

Source data

Supplementary information

Supplementary Information

Supplementary Methods, Figs. 1–10, Tables 1–4 and References.

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Bai, Z., Liu, L., Obersteiner, M. et al. Agricultural trade impacts global phosphorus use and partial productivity. Nat Food 4, 762–773 (2023). https://doi.org/10.1038/s43016-023-00822-w

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