title: Time-lag effects of global vegetation responses to climate change.
abstract: Climate conditions significantly affect vegetation growth in terrestrial ecosystems. Due to the spatial heterogeneity of ecosystems, the vegetation responses to climate vary considerably with the diverse spatial patterns and the time-lag effects, which are the most important mechanism of climate-vegetation interactive effects. Extensive studies focused on large-scale vegetation-climate interactions use the simultaneous meteorological and vegetation indicators to develop models; however, the time-lag effects are less considered, which tends to increase uncertainty. In this study, we aim to quantitatively determine the time-lag effects of global vegetation responses to different climatic factors using the GIMMS3g NDVI time series and the CRU temperature, precipitation, and solar radiation datasets. First, this study analyzed the time-lag effects of global vegetation responses to different climatic factors. Then, a multiple linear regression model and partial correlation model were established to statistically analyze the roles of different climatic factors on vegetation responses, from which the primary climate-driving factors for different vegetation types were determined. The results showed that (i) both the time-lag effects of the vegetation responses and the major climate-driving factors that significantly affect vegetation growth varied significantly at the global scale, which was related to the diverse vegetation and climate characteristics; (ii) regarding the time-lag effects, the climatic factors explained 64% variation of the global vegetation growth, which was 11% relatively higher than the model ignoring the time-lag effects; (iii) for the area with a significant change trend (for the period 1982-2008) in the global GIMMS3g NDVI (P < 0.05), the primary driving factor was temperature; and (iv) at the regional scale, the variation in vegetation growth was also related to human activities and natural disturbances. Considering the time-lag effects is quite important for better predicting and evaluating the vegetation dynamics under the background of global climate change.
authors: The State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing, 100875, China.|College of Global Change and Earth System Sciences, Beijing Normal University, Beijing, 100875, China.
authors: Donghai
authors: D
authors: Wu
authors: The State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing, 100875, China.
authors: Xiang
authors: X
authors: Zhao
authors: The State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing, 100875, China.|Department of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA.
authors: Shunlin
authors: S
authors: Liang
authors: State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China.|Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs and Ministry of Education, Beijing, 100875, China.
authors: Tao
authors: T
authors: Zhou
authors: State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China.|Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs and Ministry of Education, Beijing, 100875, China.
authors: Kaicheng
authors: K
authors: Huang
authors: The State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing, 100875, China.|College of Global Change and Earth System Sciences, Beijing Normal University, Beijing, 100875, China.
authors: Bijian
authors: B
authors: Tang
authors: The State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing, 100875, China.|College of Global Change and Earth System Sciences, Beijing Normal University, Beijing, 100875, China.
authors: Wenqian
authors: W
authors: Zhao
mesh_terms: D057231:Climate Change; D017753:Ecosystem; D016014:Linear Models; D008954:Models, Biological; D063245:Plant Development; D011891:Rain; D012914:Snow; D013472:Sunlight; D013696:Temperature; D013997:Time Factors
keywords: GIMMS3g NDVI; climate change; precipitation; solar radiation; temperature; time-lag effects; vegetation growth