Increasing interannual variability of global vegetation greenness
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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2019-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/ab4ffc |
| _version_ | 1827870429843292160 |
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| author | Chen Chen Bin He Wenping Yuan Lanlan Guo Yafeng Zhang |
| author_facet | Chen Chen Bin He Wenping Yuan Lanlan Guo Yafeng Zhang |
| author_sort | Chen Chen |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-12T15:57:41Z |
| format | Article |
| id | doaj.art-64a547eb6ce64b278ee7906fa97adf7c |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T15:57:41Z |
| publishDate | 2019-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-64a547eb6ce64b278ee7906fa97adf7c2023-08-09T14:48:17ZengIOP PublishingEnvironmental Research Letters1748-93262019-01-01141212400510.1088/1748-9326/ab4ffcIncreasing interannual variability of global vegetation greennessChen Chen0Bin He1https://orcid.org/0000-0002-9088-262XWenping Yuan2Lanlan Guo3Yafeng Zhang4State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University , Beijing 100875, People’s Republic of ChinaState Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University , Beijing 100875, People’s Republic of ChinaSchool of Atmospheric Sciences, Sun Yat-Sen University , Guangzhou, People’s Republic of ChinaAcademy of Disaster Reduction and Emergency Management, School of Geography, Beijing Normal University , Beijing 100875, People’s Republic of ChinaState Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University , Beijing 100875, People’s Republic of ChinaDespite 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.https://doi.org/10.1088/1748-9326/ab4ffcvegetation greennessincreaseglobalinterannual variability |
| spellingShingle | Chen Chen Bin He Wenping Yuan Lanlan Guo Yafeng Zhang Increasing interannual variability of global vegetation greenness Environmental Research Letters vegetation greenness increase global interannual variability |
| title | Increasing interannual variability of global vegetation greenness |
| title_full | Increasing interannual variability of global vegetation greenness |
| title_fullStr | Increasing interannual variability of global vegetation greenness |
| title_full_unstemmed | Increasing interannual variability of global vegetation greenness |
| title_short | Increasing interannual variability of global vegetation greenness |
| title_sort | increasing interannual variability of global vegetation greenness |
| topic | vegetation greenness increase global interannual variability |
| url | https://doi.org/10.1088/1748-9326/ab4ffc |
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