Cropland forms the material basis for human survival and is an important determinant of national food security. Cropland net primary productivity, which is the basis of food production and an important indicator of cropland productivity, reflects the production capacity of crops under natural conditions. However, currently, only limited knowledge was available on the relationship among cropland area, cropland management measures, and cropland productivity in China. Hence, in the current study, we used the panel data model to quantify the effects of cropland area and various cropland management measures (e.g., fertilizer use, irrigation area, agricultural machinery power, pesticide use, and agricultural film use) on cropland total net primary productivity (TNPP). Results revealed that for the entire cropland in China, an increase in cropland area, fertilizer use, agricultural machinery power, pesticide use, and agricultural film use increased cropland TNPP, whereas an increase in irrigation area decreased cropland TNPP. Further, in grain-producing areas, an increase in cropland area, fertilizer use, irrigation area, agricultural machinery power, pesticide use, and agricultural film use resulted in an increase in cropland TNPP. Moreover, in grain-balanced areas, an increase in cropland area, fertilizer use, pesticide use, and agricultural film use led to an increase in cropland TNPP, while an increase in irrigation area and agricultural machinery power reduced cropland TNPP. Finally, in grain-consuming areas, increases in cropland area, irrigation area, pesticide use, and agricultural film use caused an increase in cropland TNPP, whereas increases in fertilizer use and agricultural machinery power reduced cropland TNPP. Therefore, it is necessary to prevent the encroachment of fertile cropland and, simultaneously, implement scientific management measures based on local conditions in croplands.
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Bai, X., et al. (2019). Assessing fertilizer use efficiency and its determinants for apple production in China. Ecological Indicators, 104, 268–278.
Chen, A., et al. (2019). A study on the arable land demand for food security in China. Sustainability, 11(17), 4769.
Choi, I. (2001). Unit root tests for panel data. Journal of international money and Finance, 20(2), 249–272.
D’Amour, C. B., et al. (2017). Future urban land expansion and implications for global croplands. Proceedings of the National Academy of Sciences, 114(34), 8939–8944.
Dogan, E., & Aslan, A. (2017). Exploring the relationship among CO2 emissions, real GDP, energy consumption and tourism in the EU and candidate countries: Evidence from panel models robust to heterogeneity and cross-sectional dependence. Renewable and Sustainable Energy Reviews, 77, 239–245.
Dong, H., Liu, T., Li, Y., Liu, H., & Wang, D. (2013). Effects of plastic film residue on cotton yield and soil physical and chemical properties in Xinjiang. Transactions of the Chinese Society of Agricultural Engineering, 29(8), 91–99.
Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica Journal of the Econometric Society, 55, 251–276.
Foley, J. A., et al. (2005). Global consequences of land use. Science, 309(5734), 570–574.
Fulin, W., Shengxue, Z., & Xiaoming, F. (2016). Improved estimation model and empirical analysis of relationship between agricultural mechanization level and labor demand. International Journal of Agricultural and Biological Engineering, 9(2), 48–53.
Gao, H., et al. (2019). Effects of plastic mulching and plastic residue on agricultural production: A meta-analysis. Science of the Total Environment, 651, 484–492.
Gong, D., Mei, X., Hao, W., Wang, H., & Caylor, K. K. (2017). Comparison of multi-level water use efficiency between plastic film partially mulched and non-mulched croplands at eastern Loess Plateau of China. Agricultural water management, 179, 215–226.
Gu, B., Zhang, X., Bai, X., Fu, B. and Chen, D. (2019). Four steps to food security for swelling cities. Nature, 566(7742), 31–33.
Hausman, J. A. (1978). Specification tests in econometrics. Econometrica: Journal of the econometric society, 46(6), 1251–1271.
He, C., Liu, Z., Xu, M., Ma, Q., & Dou, Y. (2017). Urban expansion brought stress to food security in China: Evidence from decreased cropland net primary productivity. Science of the Total Environment, 576, 660–670.
Heino, M., et al. (2018). Two-thirds of global cropland area impacted by climate oscillations. Nature Communications, 9(1), 1257.
Hong-yun, H. (2004). Development of irrigated agriculture in China—problems and challenges. Journal of Economics of Water Resources, 22, 54–59.
Imhoff, M. L., et al. (2004). The consequences of urban land transformation on net primary productivity in the United States. Remote Sensing of Environment, 89(4), 434–443.
Jiang, X. J., Liu, W., Wang, E., Zhou, T., & Xin, P. (2017). Residual plastic mulch fragments effects on soil physical properties and water flow behavior in the Minqin Oasis, northwestern China. Soil and Tillage Research, 166, 100–107.
Jiye, B., Xiufen, W., & Daolin, Z. (2008). Effect of plastic-film mulch on crop yield. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 24(11), 172–175.
Kaledhonkar, M. J., Meena, B. L., & Sharma, P. C. (2019). Reclamation and nutrient management for salt-affected soils. Indian Journal of Fertilisers, 15(5), 566–575.
Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of econometrics, 90(1), 1–44.
Kuang, W., Liu, J., Dong, J., Chi, W., & Zhang, C. (2016). The rapid and massive urban and industrial land expansions in China between 1990 and 2010: A CLUD-based analysis of their trajectories, patterns, and drivers. Landscape and Urban Planning, 145, 21–33.
León, C. J., Arana, J. E., & Hernández Alemán, A. (2014). CO2 emissions and tourism in developed and less developed countries. Applied Economics Letters, 21(16), 1169–1173.
Li, M., & Zhao, L. G. (2009). Agricultural labor force aging phenomenon and the effect on agricultural production: Evidence from Liaoning Province. Issues in Agricultural Economy, 10, 12–18.
Li, Z. T., & Liang, L. W. (2018). Analysis on regional types of grain production and evolution of grain production models in China. Geographical Research, 37(5), 937–953.
Li, S., & Li, X. (2019). The mechanism of farmland marginalization in Chinese mountainous areas: Evidence from cost and return changes. Journal of Geographical Sciences, 29(4), 531–548.
Lin, W., Liu, W., Zhou, S., & Liu, C. (2019). Influence of plastic film mulch on maize water use efficiency in the Loess Plateau of China. Agricultural Water Management, 224, 105710.
Liu, X., et al. (2019). Global urban expansion offsets climate-driven increases in terrestrial net primary productivity. Nature Communications, 10(1), 1–8.
Luo, X., Liao, J., Zang, Y., & Zhou, Z. (2016). Improving agricultural mechanization level to promote agricultural sustainable development. Transactions of the Chinese Society of Agricultural Engineering, 32(1), 1–11.
Maddala, G. S., & Wu, S. (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and statistics, 61(S1), 631–652.
Minhas, P. S., Ramos, T. B., Ben-Gal, A., & Pereira, L. S. (2020). Coping with salinity in irrigated agriculture: Crop evapotranspiration and water management issues. Agricultural Water Management, 227, 105832.
Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and statistics, 61(S1), 653–670.
Pei, F., Li, X., Liu, X., Wang, S., & He, Z. (2013). Assessing the differences in net primary productivity between pre-and post-urban land development in China. Agricultural and forest meteorology, 171, 174–186.
Potter, C. S., et al. (1993). Terrestrial ecosystem production: a process model based on global satellite and surface data. Global Biogeochemical Cycles, 7(4), 811–841.
Potter, C. S., Klooster, S., & Brooks, V. (1999). Interannual variability in terrestrial net primary production: Exploration of trends and controls on regional to global scales. Ecosystems, 2(1), 36–48.
Qi, Y., et al. (2018). Macro-and micro-plastics in soil-plant system: Effects of plastic mulch film residues on wheat (Triticum aestivum) growth. Science of the Total Environment, 645, 1048–1056.
Qiu, H., Luan, H., Li, J., & Wang, Y. (2014). Impacts of risk aversion on farmer households' behaviour of overusing chemical fertilizers. Chinese Rural Economy, 3, 85–96.
Ren, W., Tian, H., Liu, M., Zhang, C., Chen, G., Pan, S., Felzer, B., & Xu, X. (2007). Effects of tropospheric ozone pollution on net primary productivity and carbon storage in terrestrial ecosystems of China. Journal of Geophysical Research: Atmospheres, 112(D22). https://doi.org/10.1029/2007JD008521
Renard, D., & Tilman, D. (2019). National food production stabilized by crop diversity. Nature, 571(7764), 257–260.
Rost, S., et al. (2009). Global potential to increase crop production through water management in rainfed agriculture. Environmental Research Letters, 4(4), 044002.
Salazar, C., & Rand, J. (2020). Pesticide use, production risk and shocks. The case of rice producers in Vietnam. Journal of Environmental Management, 253, 109705.
Schreinemachers, P., et al. (2020). How much is too much? Quantifying pesticide overuse in vegetable production in Southeast Asia. Journal of Cleaner Production, 244, 118738.
Seydehmet, J., et al. (2018). Irrigation salinity risk assessment and mapping in arid oasis, Northwest China. Water, 10(7), 966.
Siliverstovs, B., Kholodilin, K. A., & Thiessen, U. (2011). Does aging influence structural change? Evidence from panel data. Economic Systems, 35(2), 244–260.
Sun, B., et al. (2012). Agricultural non-point source pollution in China: Causes and mitigation measures. Ambio, 41(4), 370–379.
Sun, Y., Hu, R., & Zhang, C. (2019). Does the adoption of complex fertilizers contribute to fertilizer overuse? Evidence from rice production in China. Journal of Cleaner Production, 219, 677–685.
Wang, Y., Zhu, Y., Zhang, S., & Wang, Y. (2018). What could promote farmers to replace chemical fertilizers with organic fertilizers? Journal of Cleaner Production, 199, 882–890.
Woodsong, C. (1994). Old farmers, invisible farmers: Age and agriculture in Jamaica. Journal of Cross-Cultural Gerontology, 9(3), 277–299.
Wu, L., Qin, F., Feng, J., & Huang, J. (2019). Regional climate effects of plastic film mulch over the cropland of arid and semi-arid regions in Northwest China using a regional climate model. Theoretical and Applied Climatology 1–15.
Xu, X., et al. (2019). Quantifying the impacts of climate variability and human interventions on crop production and food security in the Yangtze River Basin, China, 1990–2015. Science of the Total Environment, 665, 379–389.
Yan, H., Liu, J., Huang, H. Q., Tao, B., & Cao, M. (2009). Assessing the consequence of land use change on agricultural productivity in China. Global and Planetary Change, 67(1–2), 13–19.
Yan, H. M., Liu, J. Y., Huang, H. Q., Dong, J. W., Xu, X. L., & Wang, J. B. (2012). Impacts of cropland transformation on agricultural production under urbanization and Grain for Green Project in China. Acta Geographica Sinica, 67(5), 579–588.
Yan, Y., et al. (2018a). Assessing the impacts of urban sprawl on net primary productivity using fusion of Landsat and MODIS data. Science of the Total Environment, 613, 1417–1429.
Yan, Y., Liu, X., Ou, J., Li, X., & Wen, Y. (2018b). Assimilating multi-source remotely sensed data into a light use efficiency model for net primary productivity estimation. International journal of applied earth observation and geoinformation, 72, 11–25.
Yan, Y., Liu, X., Wen, Y., & Ou, J. (2019). Quantitative analysis of the contributions of climatic and human factors to grassland productivity in northern China. Ecological Indicators, 103, 542–553.
Yan, Y., Xu, X., Liu, X., Wen, Y., & Ou, J. (2020). Assessing the contributions of climate change and human activities to cropland productivity by means of remote sensing. International Journal of Remote Sensing, 41(5), 2004–2021.
Yang, J., & Lin, Y. (2019). Spatiotemporal evolution and driving factors of fertilizer reduction control in Zhejiang Province. Science of The Total Environment, 660, 650–659.
Yang, M., Zhao, X., Meng, T., & Xin, X. (2019). What are the driving factors of pesticide overuse in vegetable production? evidence from Chinese farmers. China Agricultural Economic Review, 11(4), 672–687.
Yu, Q., Xiang, M., Wu, W., & Tang, H. (2019). Changes in global cropland area and cereal production: An inter-country comparison. Agriculture, Ecosystems & Environment, 269, 140–147.
Zeng, L. S., Zhou, Z. F., & Shi, Y. X. (2013). Environmental problems and control ways of plastic film in agricultural production. Applied Mechanics and Materials, 295–298, 2187–2190.
Zhao, N., & Li, X. G. (2017). Effects of aspect–vegetation complex on soil nitrogen mineralization and microbial activity on the Tibetan Plateau. CATENA, 155, 1–9.
This work was funded by the National Science Foundation for Young Scientists of China (No. 42007406), the Special Project for Guangzhou Science and Technology Innovation and Development (NO.006290499067), and the Fundamental Research Funds for the Non-key Project of South China Institute of Environmental Science, MEE (No. PM-zx703-202002-054).
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The authors declare no conflict of interest.
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Yan, Y., Liu, X. & Wen, Y. Quantification of the Relationship Among Cropland Area, Cropland Management Measures, and Cropland Productivity Using Panel Data Model. Int. J. Plant Prod. 14, 689–702 (2020). https://doi.org/10.1007/s42106-020-00113-5
- Cropland net primary productivity
- Panel data model
- Cropland area
- Cropland management measures