Journal of Geographical Sciences >
Rocky desertification poverty in Southwest China: Progress, challenges and enlightenment to rural revitalization
Zuo Taian (1984-), PhD and Associate Professor, specialized in soil and water conservation and desertification combating. E-mail: zuotaian@cque.edu.cn |
Received date: 2021-11-15
Accepted date: 2022-04-02
Online published: 2022-09-25
Supported by
National Social Science Foundation of China(20AJY005)
National Natural Science Foundation of China(41901214)
Natural Science Foundation of Chongqing(cstc2021jcyj-msxmX0963)
Social Science Planning Program of Chongqing(2019YBGL075)
Social Science Planning Program of Chongqing(2021SZ27)
Humanities and Social Science Program of Chongqing(19SKGH132)
Scientific Research Project of Chongqing University of Education(KY202125C)
Regional Tourism Research Centre of Chongqing University of Education(2021XJPT07)
Rocky desertification poverty (RDP) refers to rural poverty triggered or exacerbated by rocky desertification, which deprives farmers of opportunities for improving their financial conditions through agricultural production. As China implements strategies including building a moderately prosperous society, targeted poverty alleviation, and rural revitalization, issues concerning RDP have become the work foci for the Chinese government and research hotspots for Chinese academic circles. This paper provides a thorough review of the history, progress, challenges and prospects based on decades of RDP studies in Southwest China. First, we review the origin, definitions and historical development trends of RDP. Over nearly four decades, research on RDP can be framed as four stages: start-up, poverty alleviation and ecological reconstruction, rocky desertification comprehensive control and green development. We find that RDP research progress appears to be directly related to the Chinese government’s policy support and decision-making in mitigating RDP. Second, previous findings are reviewed and summarised regarding four research aspects: relationship exploration between rocky desertification and rural poverty, mechanisms of rocky desertification for exacerbating poverty, strategies for eliminating RDP and anti-poverty benefit evaluations of rocky desertification control efforts. Third, the remaining challenges are identified and summarised, including the challenges of conducting theoretical research on RDP and consolidating achievements in eliminating RDP. We find that while many achievements have been made in the study of RDP in recent decades, the completeness and systematism of the theoretical system remain weak, and the guidance for empirical research is still insufficient. Finally, this research is fundamental in achieving rural revitalization in rocky desertification areas. The key to eliminating RDP lies in scientific rural transformation development. Given that the karst ecological environment in the subtropical zone is fragile, these regions should build a new rural regional economic system, abandon extensive and predatory development that sacrifices the environment and resources, and promote the transition from backwards development modes to high-quality and sustainable development. This paper will contribute to the current understanding of the issues of RDP, provide theoretical support for the realization of rural revitalization in rocky desertification areas and provide other countries with China’s experience in poverty alleviation.
ZUO Taian , ZHANG Fengtai , ZHANG Junyi , GAO Lei , YU Shijie . Rocky desertification poverty in Southwest China: Progress, challenges and enlightenment to rural revitalization[J]. Journal of Geographical Sciences, 2022 , 32(7) : 1357 -1382 . DOI: 10.1007/s11442-022-2001-x
Figure 1 Rocky desertification in the karst area of Southwest China: (a) landscape of the rocky desertification in Puding County, Guizhou Province, in 2014 (photo by Fengtai Zhang); (b) two farmers ploughing the poor land in Puding County, Guizhou, in 2014 (photo by Fengtai Zhang); (c) landscape of rocky desertification in Shizhu County, Chongqing Municipality, in 2020 (photo by Taian Zuo) |
Figure 2 The vicious cycle of rocky desertification exacerbating poverty |
Figure 3 The process of rocky desertification exacerbating poverty |
Figure 4 The effective control modes of rocky desertification in the karst area of Southwest China: (a) and (b) the Dingtan Pepper mode in Zhenfeng County, Guizhou Province, in 2015 (photo by Junyi Zhang); (c)-(f) the Puding mode in Puding County, Guizhou, in 2015 (photo by Fengtai Zhang) |
Table 1 Terrain, slope, soil erosion and rocky desertification in Southwest China |
Province | Terrain | Slope | Soil erosion | Rocky desertification | |||||
---|---|---|---|---|---|---|---|---|---|
Highest altitude (m) | Topographic relief | Slope >15° (km2) | Proportion (%) | Average slope (°) | Area (km2) | Occurrence rate (%) | Karst area (km2) | Rocky desertification area (km2) | |
Yunnan | 6740 | 2.696 | 247,300 | 64.46 | 20.19 | 102,140 | 25.92 | 108,600 | 23,520 |
Guizhou | 2900.6 | 1.398 | 86,700 | 48.50 | 16.08 | 47,710 | 27.08 | 121,200 | 24,700 |
Guangxi | 2141.5 | 0.586 | 99,100 | 40.71 | 13.84 | 38,880 | 16.37 | 81,700 | 15,330 |
Sichuan | 7556 | 3.529 | 295,500 | 60.60 | 20.26 | 111,040 | 22.58 | 69,100 | 6,700 |
Chongqing | 2796.8 | 1.310 | 43,100 | 51.48 | 17.35 | 25,450 | 30.89 | 30,100 | 7,730 |
Table 2 Overall variation of the cultivated land area in Southwest China from 2009 to 2018 (km2) |
Province | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2018 | Amplitude of variation | Relative variation rate |
---|---|---|---|---|---|---|---|---|---|---|---|
Yunnan | 62,439 | 62,401 | 62,335 | 62,249 | 62,198 | 62,075 | 62,085 | 62,078 | 62,118 | -321 | 0.70 |
Guizhou | 45,625 | 45,662 | 45,607 | 45,522 | 45,483 | 45,401 | 45,374 | 45,302 | 45,167 | -458 | 1.36 |
Guangxi | 44,305 | 44,247 | 44,215 | 44,143 | 44,195 | 44,103 | 44,023 | 43,951 | 43,884 | -421 | 1.28 |
Sichuan | 67,199 | 67,201 | 67,356 | 67,321 | 67,351 | 67,342 | 67,315 | 67,329 | 67,254 | 55 | 0.11 |
Chongqing | 24,384 | 24,429 | 24,497 | 24,513 | 24,563 | 24,547 | 24,305 | 23,825 | 23,725 | -659 | 3.65 |
Note: data are obtained from land use change survey. |
Table 3 Variations of the rural populations in Southwest China from 2009 to 2018 (million people) |
Province | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | Amplitude of variation | Relative variation rate |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Yunnan | 30.17 | 30.01 | 29.27 | 28.28 | 27.89 | 27.47 | 26.87 | 26.23 | 25.59 | 25.21 | -4.96 | 0.79 |
Guizhou | 26.63 | 23.01 | 22.56 | 22.15 | 21.77 | 21.04 | 20.47 | 19.85 | 19.32 | 18.89 | -7.74 | 1.40 |
Guangxi | 29.52 | 27.61 | 27.03 | 26.44 | 26.04 | 25.67 | 25.39 | 25.12 | 24.81 | 24.52 | -5.00 | 0.82 |
Sichuan | 50.17 | 48.07 | 46.83 | 45.61 | 44.67 | 43.71 | 42.92 | 41.96 | 40.85 | 39.79 | -10.38 | 1.00 |
Chongqing | 13.84 | 13.55 | 13.13 | 12.67 | 12.37 | 12.09 | 11.78 | 11.40 | 11.05 | 10.70 | -3.14 | 1.09 |
Note: the population data in 2010 were inferred from the demographic census of the year, while the population data in other years were revised from demographic census based on the annual population sampling survey. |
Table 4 The level of green development in Southwest China from 2007 to 2016 |
Evaluation item | Province | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 |
---|---|---|---|---|---|---|---|---|---|---|---|
State score | Yunnan | 0.113 | 0.117 | 0.126 | 0.137 | 0.151 | 0.159 | 0.164 | 0.166 | 0.172 | 0.183 |
Guizhou | 0.086 | 0.091 | 0.117 | 0.119 | 0.138 | 0.149 | 0.160 | 0.167 | 0.171 | 0.181 | |
Guangxi | 0.125 | 0.125 | 0.142 | 0.151 | 0.167 | 0.169 | 0.177 | 0.183 | 0.186 | 0.192 | |
Sichuan | 0.124 | 0.137 | 0.148 | 0.153 | 0.169 | 0.181 | 0.186 | 0.188 | 0.201 | 0.206 | |
Chongqing | 0.137 | 0.152 | 0.162 | 0.183 | 0.208 | 0.216 | 0.223 | 0.233 | 0.235 | 0.240 | |
Mean | 0.117 | 0.124 | 0.139 | 0.149 | 0.167 | 0.175 | 0.182 | 0.187 | 0.193 | 0.200 | |
Efficiency score | Yunnan | 0.933 | 0.898 | 1.066 | 0.912 | 0.890 | 0.894 | 0.885 | 0.907 | 0.927 | 0.980 |
Guizhou | 0.979 | 0.811 | 0.700 | 0.42 | 0.800 | 0.812 | 0.834 | 0.856 | 0.878 | 0.918 | |
Guangxi | 0.965 | 1.043 | 0.946 | 1.099 | 1.112 | 1.074 | 1.060 | 1.091 | 1.073 | 1.091 | |
Sichuan | 0.882 | 0.902 | 0.931 | 0.868 | 0.892 | 0.885 | 0.884 | 0.878 | 0.900 | 0.910 | |
Chongqing | 0.884 | 0.921 | 0.993 | 1.020 | 1.053 | 1.066 | 1.026 | 1.010 | 1.011 | 1.032 | |
Mean | 0.929 | 0.915 | 0.927 | 0.864 | 0.949 | 0.946 | 0.937 | 0.948 | 0.957 | 0.986 |
Note: the state score reflects the absolute level, and the efficiency score reflects improvements attributed to quantitative input. |
Figure 5 The PSR-based theoretical framework for rural transformation development in rocky desertification areas |
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