分类： 地球科学 >> 地理学 提交时间： 2020-11-25 合作期刊: 《干旱区科学》
摘要： There are eight provinces and autonomous regions (Gansu Province, Ningxia Hui Autonomous Region, Xinjiang Uygur Autonomous Region, Inner Mongolia Autonomous Region, Tibet Autonomous Region, Qinghai Province, Shanxi Province, and Shaanxi Province) in Northwest China, most areas of which are located in arid and semi-arid regions (northwest of the 400 mm precipitation line), accounting for 58.74% of the country's land area and sustaining approximately 7.84×106 people. Because of drought conditions and fragile ecology, these regions cannot develop agriculture at the expense of the environment. Given the challenges of global warming, the green total factor productivity (GTFP), taking CO2 emissions as an undesirable output, is an effective index for measuring the sustainability of agricultural development. Agricultural GTFP can be influenced by both internal production factors (labor force, machinery, land, agricultural plastic film, diesel, pesticide, and fertilizer) and external climate factors (temperature, precipitation, and sunshine duration). In this study, we used the Super-slacks-based measure (Super-SBM) model to measure agricultural GTFP during the period 2000–2016 at the regional level. Our results show that the average agricultural GTFP of most provinces and autonomous regions in arid and semi-arid regions underwent a fluctuating increase during the study period (2000–2016), and the fluctuation was caused by the production factors (input and output factors). To improve agricultural GTFP, Shaanxi, Shanxi, and Gansu should reduce agricultural labor force input; Shaanxi, Inner Mongolia, Gansu, and Shanxi should decrease machinery input; Shaanxi, Inner Mongolia, Xinjiang, and Shanxi should reduce fertilizer input; Shaanxi, Xinjiang, Gansu, and Ningxia should reduce diesel input; Xinjiang and Gansu should decrease plastic film input; and Gansu, Shanxi, and Inner Mongolia should cut pesticide input. Desirable output agricultural earnings should be increased in Qinghai and Tibet, and undesirable output (CO2 emissions) should be reduced in Inner Mongolia, Xinjiang, Gansu, and Shaanxi. Agricultural GTFP is influenced not only by internal production factors but also by external climate factors. To determine the influence of climate factors on GTFP in these provinces and autonomous regions, we used a Geographical Detector (Geodetector) model to analyze the influence of climate factors (temperature, precipitation, and sunshine duration) and identify the relationships between different climate factors and GTFP. We found that temperature played a significant role in the spatial heterogeneity of GTFP among provinces and autonomous regions in arid and semi-arid regions. For Xinjiang, Inner Mongolia, and Tibet, a suitable average annual temperature would be in the range of 7°C–9°C; for Gansu, Shanxi, and Ningxia, it would be 11°C–13°C; and for Shaanxi, it would be 15°C–17°C. Stable climatic conditions and more efficient production are prerequisites for the development of sustainable agriculture. Hence, in the agricultural production process, reducing the redundancy of input factors is the best way to reduce CO2 emissions and to maintain temperatures, thereby improving the agricultural GTFP. The significance of this study is that it explores the impact of both internal production factors and external climatic factors on the development of sustainable agriculture in arid and semi-arid regions, identifying an effective way forward for the arid and semi-arid regions of Northwest China.
分类： 地球科学 >> 地球科学史 提交时间： 2020-10-20 合作期刊: 《干旱区科学》
摘要： Determining the mechanisms controlling the changes of wet and dry conditions will improve our understanding of climate change over the past hundred years, which is of great significance to the study of climate and environmental changes in the arid regions of Central Asia. Forest trees are ecologically significant in the local environment, and therefore the tree ring analysis can provide a clear record of regional historical climate. This study analyzed the correlation between the tree ring width chronology of Juniperus turkestanica Komarov and the standardized precipitation evapotranspiration index (SPEI) in Northwest Tajikistan, based on 56 tree ring samples collected from Shahristan in the Pamir region. Climate data including precipitation, temperature and the SPEI were downloaded from the Climate Research Unit (CRU) TS 4.00. The COFECHA program was used for cross-dating, and the ARSTAN program was used to remove the growth trend of the tree itself and the influence of non-climatic factors on the growth of the trees. A significant correlation was found between the radial growth of J. turkestanica trees and the monthly mean SPEI of February–April. The monthly mean SPEI sequence of February–April during the period of 1895–2016 was reconstructed, and the reconstruction equation explained 42.5% of the variance. During the past 122 a (1895–2016), the study area has experienced three wetter periods (precipitation above average): 1901–1919, 1945–1983 and 1995–2010, and four drier periods (precipitation below average): 1895–1900, 1920–1944, 1984–1994 and 2011–2016. The spatial correlation analysis revealed that the monthly mean SPEI reconstruction sequence of February–April could be used to characterize the large-scale dry-wet variations in Northwest Tajikistan during the period of 1895–2016. This study could provide comparative data for validating the projections of climate models and scientific basis for managing water resources in Tajikistan in the context of climate change.
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