Details

Autor(en) / Beteiligte

• Chen, Chen
• He, Bin
• Yuan, Wenping
• Guo, Lanlan
• Zhang, Yafeng

Titel

Increasing interannual variability of global vegetation greenness

Ist Teil von

• Environmental research letters, 2019-12, Vol.14 (12), p.124005

Ort / Verlag

Bristol: IOP Publishing

Erscheinungsjahr

2019

Link zum Volltext

Quelle

Free E-Journal (出版社公開部分のみ）

Beschreibungen/Notizen

• Despite the long-term greening trend in global vegetation identified in previous investigations, changes in the interannual variability (IAV) of vegetation greenness over time is still poorly understood. Using Global Inventory Modeling and Mapping Studies normalized difference vegetation index (NDVI) third generation data and corresponding meteorological data from 1982 to 2015, we studied the changes and drivers of the IAV of vegetation greenness as indicated by the coefficient of variation of vegetation greenness at a global scale. Dry and high-latitude areas exhibited high NDVI variability whereas humid areas exhibited relatively low NDVI variability. We detected an increase in the global IAV of vegetation greenness over time using a 15 year moving window. Spatially, we observed significant increases in the IAV of vegetation greenness in greater than 45% of vegetated areas globally and decreases in 21%. Our comparison of ecological models suggests good performance in terms of simulating spatial differences in vegetation variability, but relatively poor performance in terms of capturing changes in the IAV of vegetation greenness. Furthermore, the dominant climate variables controlling changes in the IAV of vegetation greenness were determined spatially using principal component regression and partial least squares regression. The two methods yielded similar patterns, revealing that temperature exerted the biggest influence on changes in the IAV of vegetation greenness, followed by solar radiation and precipitation. This study provides insights into global vegetation variability which should contribute to an understanding of vegetation dynamics in the context of climate change.