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1. chinaXiv:202011.00131 [pdf]

Can climate change influence agricultural GTFP in arid and semi-arid regions of Northwest China?

FENG,Jian; ZHAO,Lingdi; ZHANG,Yibo; SUN,Lingxiao; YU,Xiang; YU,Yang
Subjects: Geosciences >> Geography

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.

submitted time 2020-11-25 From cooperative journals:《Journal of Arid Land》 Hits2686Downloads235 Comment 0

2. chinaXiv:201810.00188 [pdf]

Seasonal differences in climatic controls of vegetation growth in the Beijing–Tianjin Sand Source Region of China

SHAN, Lishan; YU, Xiang; SUN, Lingxiao; HE, Bin; WANG, Haiyan; XIE, Tingting
Subjects: Geosciences >> History of Geosciences

Launched in 2002, the Beiing–Tianjin Sand Source Control Project (BTSSCP) is an ecological restoration project intended to prevent desertification in China. Evidence from multiple sources has confirmed increases in vegetation growth in the BTSSCP region since the initiation of this project. Precipitation and essential climate variable-soil moisture (ECV-SM) conditions are typically considered to be the main drivers of vegetation growth in this region. Although many studies have investigated the inter-annual variations of vegetation growth, few concerns have been focused on the annual and seasonal variations of vegetation growth and their climatic drivers, which are crucial for understanding the relationships among the climate, vegetation, and human activities at the regional scale. Based on the normalized difference vegetation index (NDVI) derived from MODIS and the corresponding climatic data, we explored the responses of vegetation growth to climatic factors at annual and seasonal scales in the BTSSCP region during the period 2000–2014. Over the study region as a whole, NDVI generally increased from 2000 to 2014, at a rate of 0.002/a. Vegetation growth is stimulated mainly by the elevated temperature in spring, whereas precipitation is the leading driver of summer greening. In autumn, positive effects of both temperature and precipitation on vegetation growth were observed. The warming in spring promotes vegetation growth but reduces ECV-SM. Summer greening has a strong cooling effect on land surface temperature. These results indicate that the ecological and environmental consequences of ecological restoration projects should be comprehensively evaluated.

submitted time 2018-10-29 From cooperative journals:《Journal of Arid Land》 Hits4579Downloads951 Comment 0

3. chinaXiv:201803.00010 [pdf]

Model based decision support system for land use changes and socio-economic assessments

YU, Yang; CHEN, Xi; HUTTNER, Philipp; HINNENTHAL, Marie; BRIEDEN, Andreas; SUN, Lingxiao; DSE, ISMarkus
Subjects: Physics >> General Physics: Statistical and Quantum Mechanics, Quantum Information, etc.

Hydrological models are often linked with other models in cognate sciences to understand the interactions among climate, earth, water, ecosystem, and human society. This paper presents the development and implementation of a decision support system (DSS) that links the outputs of hydrological models with real-time decision making on social-economic assessments and land use management. Discharge and glacier geometry changes were simulated with hydrological model, water availability in semi-arid environments. Irrigation and ecological water were simulated by a new commercial software MIKE HYDRO. Groundwater was simulated by MODFLOW. All the outputs of theses hydrological models were taken as inputs into the DSS in three types of links: regression equations, stationary data inputs, or dynamic data inputs as the models running parallel in the simulation periods. The DSS integrates the hydrological data, geographic data, social and economic statistical data, and establishes the relationships with equations, conditional statements and fuzzy logics. The programming is realized in C++. The DSS has four remarkable features: (1) editable land use maps to assist decision-making; (2) conjunctive use of surface and groundwater resources; (3) interactions among water, earth, ecosystem, and humans; and (4) links with hydrological models. The overall goal of the DSS is to combine the outputs of scientific models, knowledge of experts, and perspectives of stakeholders, into a computer-based system, which allows sustainability impact assessment within regional planning; and to understand ecosystem services and integrate them into land and water management.

submitted time 2018-02-28 From cooperative journals:《Journal of Arid Land》 Hits1794Downloads873 Comment 0

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