Aboveground net primary productivity of vegetation along a climate-related gradient in a Eurasian temperate grassland: spatiotemporal patterns and their relationships with climate factors

详细信息    查看全文

• 作者：Tian Gao ; Bin Xu ; Xiuchun Yang ; Songqiu Deng ; Yuechen Liu…
• 关键词：Temperate steppe ; Aboveground net primary productivity ; Remote sensing ; Spatiotemporal patterns ; Growing season air temperature ; Growing season precipitation
• 刊名：Environmental Earth Sciences
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：76
• 期：1
• 全文大小：
• 刊物类别：Earth and Environmental Science
• 刊物主题：Geology; Hydrology/Water Resources; Geochemistry; Environmental Science and Engineering; Terrestrial Pollution; Biogeosciences;
• 出版者：Springer Berlin Heidelberg
• ISSN：1866-6299
• 卷排序：76

文摘

Accurate assessments of spatiotemporal patterns in net primary productivity and their links to climate are important to obtain a deeper understanding of the function, stability and sustainability of grassland ecosystems. We combined a satellite-derived NDVI time-series dataset and field-based samples to investigate spatiotemporal patterns in aboveground net primary productivity (ANPP), and we examined the effect of growing season air temperate (GST) and precipitation (GSP) on these patterns along a climate-related gradient in an eastern Eurasian grassland. Our results indicated that the ANPP fluctuated with no significant trend during 2001–2012. The spatial distribution of ANPP was heterogeneous and decreased from northeast to southwest. The interannual changes in ANPP were mainly controlled by year-to-year GSP; a strong correlation of interannual variability between ANPP and GSP was observed. Similarly, GSP strongly influenced spatial variations in ANPP, and the slopes of fitted linear functions of the GSP–ANPP relationship increased from arid temperate desert grassland to humid meadow grassland. An exponential function could be used to fit the GSP–ANPP relationship for the entire region. An improved moisture index that combines the effects of GST and GSP better explained the variations in ANPP compared with GSP alone. In comparisons with the previous studies, we found that the relationships between spatiotemporal variations in ANPP and climate factors were probably scale dependent. We imply that the quantity and spatial range of analyzed samples contribute to these different results. Multi-scale studies are necessary to improve our knowledge of the response of grassland ANPP to climate change.