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Link to original content: https://pubmed.ncbi.nlm.nih.gov/32978301
On the accuracy of official Chinese crop production data: Evidence from biophysical indexes of net primary production - PubMed Skip to main page content
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. 2020 Oct 13;117(41):25434-25444.
doi: 10.1073/pnas.1919850117. Epub 2020 Sep 25.

On the accuracy of official Chinese crop production data: Evidence from biophysical indexes of net primary production

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On the accuracy of official Chinese crop production data: Evidence from biophysical indexes of net primary production

Gengyuan Liu et al. Proc Natl Acad Sci U S A. .

Abstract

With rapid economic growth and urbanization, self-sufficiency in crop production has become central to China's agriculture policy. Accurate crop production statistics are essential for research, monitoring, and planning. Although researchers agree that China's statistical authority has considerably modernized over time, China's economic statistics have still been viewed as unreliable and often overstated to meet growth targets at different administrative levels. Recent increases in crop production reported by national statistics have also come under increasing scrutiny. This paper investigates crop production data quality from a planetary boundary perspective-comparing net primary production (NPP) harvested obtained from national statistics with satellite-driven NPP estimates that are supported by detailed observation of land cover, combined with observations on physical factors that limit plant growth. This approach provides a powerful means to check the plausibility of China's grain production statistics at different administrative levels that can generate insights about their discrepancies and can contribute to improved crop production measurements. We find some evidence of potential misreporting problems from the lower administration level where the risk of manipulation of statistics is higher. We also find problems from provincial-level major grain producers. These values can also affect the national totals. Although the numbers are affected by large uncertainties, we find that improving the spatial resolution of key agricultural parameters can greatly improve the reliability of the indicator that in turn can help improve data quality. More reliable production data will be vital for relevant research and provide better insights into food security problems, the carbon cycle, and sustainable development.

Keywords: China; HANPP; crop production; statistical data misreporting.

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Conflict of interest statement

The authors declare no competing interest.

Figures

Fig. 1.
Fig. 1.
(A and B) Spatial distribution of HANPPharv at the provincial level (A) and the prefectural level (B) in China in 2010.
Fig. 2.
Fig. 2.
(A–C) HANPPharv/NPPact map of China at the provincial level for 2010 (A) and 2014 (B) and at the prefectural level for 2010 (C).
Fig. 3.
Fig. 3.
The quantitative relationship between NPPact and Cropland HANPPharv and the changes with time, with the consumption of chemical fertilizers characterizing advances in agricultural technology. The ordinate on the left is how many times of NPPact or HANPPharv in all years related to HANPPharv (2000). The ordinate on the right is the times of fertilizers use related to fertilizers in 2000. The abscissa is the time.
Fig. 4.
Fig. 4.
Sensitivity analysis of the input parameters.
Fig. 5.
Fig. 5.
(A–C) HANPPharv/NPPact map of China at prefecture–city level after adjusting the harvest factor only (A) keeping everything else constant, after adjusting the maximum light use efficiency only (B), and after adjusting both parameters jointly (C).

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