Trend Patterns of Vegetative Coverage and Their Underlying Causes in the Deserts of Northwest China over 1982-2008

• Published in: PloS one Vol. 10; no. 5; p. e0126044
• Main Authors: Zhang, Tianyi, Wang, Hesong
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 11.05.2015; Public Library of Science (PLoS)
• Subjects: Analysis; Atmospheric boundary layer; China; Climate; Climate change; Climate models; Desertification; Deserts; Drought; Drought index; Economic indicators; Ecosystem; Ecosystems; Environment; Environmental aspects; Geography; Laboratories; Models, Theoretical; Multiple regression models; Normalized difference vegetative index; Precipitation; Regression analysis; Regression models; Soil sciences; Studies; Trends; Vegetation index; Vegetation zones; Water shortages; China
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0126044

We identified the spatiotemporal patterns of the Normalized Difference Vegetation Index (NDVI) for the years 1982-2008 in the desert areas of Northwest China and quantified the impacts of climate and non-climate factors on NDVI changes. The results indicate that although the mean NDVI has improved in 24.7% of the study region; 16.3% among the region has been stagnating in recent years and only 8.4% had a significantly increasing trend. Additionally, 45.3% of the region has maintained a stable trend over the study period and 30.0% has declined. A multiple regression model suggests that a wetter climate (quantified by the Palmer Drought Severity Index, PDSI) is associated with higher NDVI in most areas (18.1% of significance) but these historical changes in PDSI only caused an average improvement of approximately 0.4% over the study region. Contrasting the regression results under different trend patterns, no significant differences in PDSI impacts were detected among the four trend patterns. Therefore, we conclude that climate is not the primary driver for vegetative coverage in Northwest China. Future studies will be required to identify the impacts of specific non-climatic factors on vegetative coverage based on high-resolution data, which will be beneficial in creating an effective strategy to combat the recent desertification trend in China.