Dataset Information

Key driving forces of desertification in the Mu Us Desert, China.

ABSTRACT: The temporal trends and key driving forces of desertification in the Mu Us Desert are representatives of most arid regions of Asia with a high risk of desertification. We analyzed the significance of Aeolian transport on desertification in the Mu Us Desert by field investigations, sampling, wind tunnel experiments, particle size and nutrient measurements, and statistics on aeolian transport potentials. The results showed that high intensities of aeolian processes may result in low differences in aeolian transport despite differences in the underlying sediments. When high desertification occurred in the 1970s, the annual losses of the ammonium N, nitrate N, available K, and available P were approximately 116, 312, 46,436, and 1,251 kg km^-2, respectively. After 2010, the losses were only 8, 20, 3,208, and 84 kg km^-2, which were generally only 6.7% of those in the 1970s. The results showed that although human activity may trigger desertification, the dramatic decline of aeolian transport and low nutrient loss may be the key driving forces for the occurrence of rehabilitation in this region.

SUBMITTER: Wang X

PROVIDER: S-EPMC5479821 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Key driving forces of desertification in the Mu Us Desert, China.

Wang Xunming X Cheng Hong H Li Hui H Lou Junpeng J Hua Ting T Liu Wenbin W Jiao Linlin L Ma Wenyong W Li Danfeng D Zhu Bingqi B

Scientific reports 20170621 1

The temporal trends and key driving forces of desertification in the Mu Us Desert are representatives of most arid regions of Asia with a high risk of desertification. We analyzed the significance of Aeolian transport on desertification in the Mu Us Desert by field investigations, sampling, wind tunnel experiments, particle size and nutrient measurements, and statistics on aeolian transport potentials. The results showed that high intensities of aeolian processes may result in low differences in ...[more]

PMID: 28638114

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Project description:BackgroundGlobal connectivity and environmental change pose continuous threats to dengue invasions from worldwide to China. However, the intrinsic relationship on introduction and outbreak risks of dengue driven by the landscape features are still unknown. This study aimed to map the patterns on source-sink relation of dengue cases and assess the driving forces for dengue invasions in China.MethodsWe identified the local and imported cases (2006-2020) and assembled the datasets on environmental conditions. The vector auto-regression model was applied to detect the cross-relations of source-sink patterns. We selected the major environmental drivers via the Boruta algorithm to assess the driving forces in dengue outbreak dynamics by applying generalized additive models. We reconstructed the internal connections among imported cases, local cases, and external environmental drivers using the structural equation modeling.ResultsFrom 2006 to 2020, 81,652 local dengue cases and 12,701 imported dengue cases in China were reported. The hotspots of dengue introductions and outbreaks were in southeast and southwest China, originating from South and Southeast Asia. Oversea-imported dengue cases, as the Granger-cause, were the initial driver of the dengue dynamic; the suitable local bio-socioecological environment is the fundamental factor for dengue epidemics. The Bio8 [odds ratio (OR) = 2.11, 95% confidence interval (CI): 1.67-2.68], Bio9 (OR = 291.62, 95% CI: 125.63-676.89), Bio15 (OR = 4.15, 95% CI: 3.30-5.24), normalized difference vegetation index in March (OR = 1.27, 95% CI: 1.06-1.51) and July (OR = 1.04, 95% CI: 1.00-1.07), and the imported cases are the major drivers of dengue local transmissions (OR = 4.79, 95% CI: 4.34-5.28). The intermediary effect of an index on population and economic development to local cases via the path of imported cases was detected in the dengue dynamic system.ConclusionsDengue outbreaks in China are triggered by introductions of imported cases and boosted by landscape features and connectivity. Our research will contribute to developing nature-based solutions for dengue surveillance, mitigation, and control from a socio-ecological perspective based on invasion ecology theories to control and prevent future dengue invasion and localization.

Project description:The desert ecosystem is an important part of the terrestrial ecosystem. Accurate estimations of the biomass and species richness of desert plants are of great value for maintaining ecosystem stability; however, current assessments remain a challenge due to the large spatial heterogeneity in biomass and species richness and difficulties posed by time-consuming field surveys, particularly in remote areas. In the present study, There were 527 sampling sites, and each sampling site contained approximately 9 quadrats. Approximately 4500 quadrats in total were taken from the Junggar Desert of northern Xinjiang, and the spatial distribution and factors driving the biomass and species richness of the desert ecosystem were quantitatively analyzed. The results showed that the average aboveground biomass, belowground biomass, litter, and the Patrick index of the Junggar Desert in northern Xinjiang were 115.42 gm-2, 924.77 gm-2, 13.06 gm-2, and 63, with values ranging from 2-708.12 gm-2, 120.25-3537.3 gm-2, 2-56.46 gm-2, and 0-377, respectively, The mean of the variation coefficient was 56.19%, 41.16%, 62.16% and 73.83%, suggesting moderate variation. The result is affected by the differences between the desert environment and climate. Climate factors had a relatively large impact on species richness, and the variation coefficient of species richness was large, indicating a large degree of dispersion of species richness. The direct influence of environmental and climatic factors on underground biomass (BGB) is relatively small, and its coefficient of variation is small. The spatial distribution of biomass and species richness in northern Xinjiang gradually decreased from west to east. Redundancy analysis showed that climate was the main factor driving desert biomass and species richness in northern Xinjiang, with an average independent explanatory power of 20.38% and 18.57%, respectively. Structural equation modeling indicated that climate factors, elevation, and community coverage had a direct positive effect on the aboveground biomass of the desert plants in northern Xinjiang and a direct negative effect on the belowground biomass. Moreover, climate factors and biological factors showed a direct positive effect on the species richness in northern Xinjiang.

Dataset Information

Key driving forces of desertification in the Mu Us Desert, China.

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Key driving forces of desertification in the Mu Us Desert, China.

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