文献信息：
Wang Sitong1, Bai Xuemei1, Zhang Xiaoling1, Reis Stefan, Chen Deli, Xu Jianming, Gu Baojing*. Urbanization can benefit agricultural production with large-scalefarming in China[J]. Nature Food, 2021. DOI: 10.1038/s43016-021-00228-6
Nature Food为Nature新子刊，最新影响因子暂无。
Abstract: Urbanization has often been considered a threat to food security since it is likely to reduce the availability of croplands. Using spatial statistics and scenario analysis, we show that an increase in China’s urbanization level from 56% in 2015 to 80% in 2050 would actually release 5.8 million hectares of rural land for agricultural production—equivalent to 4.1% of China’s total cropland area in 2015. Even considering the relatively lower land fertility of these new croplands, crop production in 2050 would still be 3.1–4.2% higher than in 2015. In addition, cropland fragmentation could be reduced with rural land release and a decrease in rural population, benefiting large-scale farming and environmental protection. To ensure this, it is necessary to adopt an integrated urban–rural development model, with reclamation of lands previously used as residential lots. These insights into the urbanization and food security debate have important policy implications for global regions undergoing rapid urbanization.
Fig. 1 Changes in urban, rural and cropland areas and rural population. a, Changes in the rural built-up area (left y axis) and population (right y axis) from 2000–2015. b, Changes in urban, rural and cropland areas under various scenarios. Urban and rural refer to built-up lands occupied by people living in urban and rural built-up areas, respectively.
Fig. 2 Spatial changes in land use with an urbanization level of 80% in 2050. From 2015–2050, new released croplands would be concentrated in the NCP (A), MLYRP and Northeast China Plain, while the most intensive urban expansion areas would be the Beijing–Tianjin–Hebei region, Yangtze River Delta (B) and Pearl River Delta (C). Maps showing the distribution of land use changes at urbanization levels of 56, 70 and 90% (by 2015, 2030 and 2050, respectively) are provided in Extended Data Figs. 1 and 2. The base map was applied without endorsement using data from the Database of Global Administrative Areas (GADM; https://gadm.org/).
Fig. 3 Changes in crop production at the county level. a–f, County-level changes in crop production from 2000–2015 (a), from urbanization level 56% (2015) to urbanization level 80% (2050) without rural land being reclaimed (b), from urbanization level 56% (2015) to urbanization level 70% (2030) with rural land being reclaimed, as predicted by SOC (c), from urbanization level 56% (2015) to urbanization level 80% (2050) with rural land being reclaimed, as predicted by SOC (d), from urbanization level 56% (2015) to urbanization level 70% (2030) with rural land being reclaimed, as predicted from the yield of 2015 (e) and from urbanization level 56% (2015) to urbanization level 80% (2050) with rural land being reclaimed, as predicted from the yield of 2015 (f). The inset bar chart shows the overall changes for 2000–2015 and each scenario in the future for China as a whole (Supplementary Table 6). The base map was applied without endorsement using data from the GADM (https://gadm.org/).
Fig. 4 Changes in per-capita cropland of rural residents at the county level. a–d, Changes in cropland from 2000–2015 (a), from urbanization level 56% (2015) to urbanization level 80% (2050) without rural land being reclaimed (b), from urbanization level 56% (2015) to urbanization level 70% (2030) with rural land being reclaimed, as predicted by SOC (c) and from urbanization level 56% (2015) to urbanization level 80% (2050) with rural land being reclaimed, as predicted by SOC (d). The inset bar chart shows the overall changes for 2000–2015 and each scenario in the future for China as a whole (Supplementary Table 7). The base map was applied without endorsement using data from the GADM (https://gadm.org/).
Fig. 5 Methods for predicting urban and rural land use change. a, An urban built-up area in 2015. b, Pick up a square with 10 × 10 grids, set the value of urban land to 1 and set the value of all other land uses to 0. c, Count all of the values in the square and calculate the priority level for the central grid using equation (1). d, Example of the priority level of urban expansion. e, An example of cropland and rural built-up area distribution in 2015. f, Pick up a square with 3 × 3 grids, set the value of cropland to 1 and set the value of rural built-up area to 10. g, Count all of the values in the square and calculate the priority level for the central grid using equation (2). h, Example of the priority level of rural land being reclaimed. The inset plot shows a typical case of regional land use. The yellow background denotes croplands; the grey grids denote urban lands; and the scattered purple grids denote rural lands.
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