The resilience of the phosphorus (P) cycling network is critical to ecosystem functioning and human activities. Although P cycling pathways have been previously mapped, a knowledge gap remains in evaluating the P network’s ability to withstand shocks or disturbances. Applying principles of mass balance and ecological network analysis, we examine the network resilience of P cycling in China from 1600 to 2012. The results show that changes in network resilience have shifted from being driven by natural P flows for food production to being driven by industrial P flows for chemical fertilizer production. Urbanization has intensified the one-way journey of P, further deteriorating network resilience. Over 2000–2012, the network resilience of P cycling has decreased by 11% owing to dietary changes towards more animal-based foods. A trade-off between network resilience improvement and increasing food trade is also observed. These findings can support policy decisions for enhanced P cycling network resilience in China.
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All computer codes generated in MATLAB 2019a and R version 3.6.1 for this study are available from the corresponding authors upon reasonable request.
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This work was supported by the National Natural Science Foundation of China (71874014, 51721093, 71704055, 71704015 and 41661144023), the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement CIFTRESS no. 840205, Natural Science Funds for Distinguished Young Scholar of Guangdong Province, China (2018B030306032) and the Fundamental Research Funds for the Central Universities.
The authors declare no competing interests.
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Extended Data Fig. 1 Distribution of values for the resilience of the P cycling network in China during 1600–2012.
The resilience values of the P cycling network during 1600–2012 are distributed in the curve of the theoretical relationship between resilience and α. Source data
The contribution of each category of P demand to the total P demand is shown in a different colour. Source data
Food structure is calculated as the sum of P content in all foods except for grain divided by P content in grain. Source data
Extended Data Fig. 4 Uncertainties in the efficiency, redundancy, α, and resilience of the P cycling network in China during 1600–2012.
Uncertainties are calculated by Monte Carlo simulation sampling 10,000 times. The upper boundary of the range indicates maximum values; the lower boundary of the range represents minimum values; and the solid line stands for average values. Source data
The overly efficient area is separated from the overly redundant area by the line where α = 0.3679 in the figure. Source data
The maximum value of resilience is 0.3679 in the figure. Source data
Resilience, α, and efficiency and redundancy of the P cycling network in China during 1600–2012.
Relative contributions of changes in efficiency and redundancy to changes in the resilience of the P cycling network in China during 1600–2012.
Relative contributions of changes in concentration degree of P flows, node inter-dependency and node inter-independency to changes in efficiency, redundancy, and resilience of the P cycling network in China during 1600–2012.
Contributions of changes in links and nodes to changes in the resilience of the P cycling network in China during 2000–2012.
The P flow network of China in 2012.
α and resilience of the P cycling network in China during 1600–2012.
Human P demand in China during 1950–2012.
Food structure in China during 1950–2012.
Uncertainties in the efficiency, redundancy, α, and resilience of the P cycling network in China during 1600–2012.
α values for the 149-node and 16-node P cycling networks in China during 1600–2012.
Network resilience for the 149-node and 16-node P cycling networks in China during 1600–2012.
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Liang, S., Yu, Y., Kharrazi, A. et al. Network resilience of phosphorus cycling in China has shifted by natural flows, fertilizer use and dietary transitions between 1600 and 2012. Nat Food 1, 365–375 (2020). https://doi.org/10.1038/s43016-020-0098-6
Nature Food (2020)