Characterizing multiscale effects of climatic factors on the temporal variation of vegetation in different climatic regions of China

Vegetation dynamics are sensitive to climatic warming and are affected by individual or combined climatic factors at different temporal scales with different intensities. Previous studies have unraveled the relationships between vegetation dynamics and individual climatic factors; however, it is unclear whether the effects of single or combined climatic factors on vegetation dynamics are dominant for different temporal scales, vegetation types, and climatic regions. The objective of this study was to explore scale-specific univariate and multivariate controls on vegetation over the period 1982–2015 using bivariate wavelet coherence (BWC), multivariate wavelet coherence (MWC), and multidimensional empirical mode decomposition (MEMD). The results indicated that significant vegetation dynamics were located mainly at scales of 1, 0.5, and 0.3 years. Vegetation variations were divided into seasonal (≤ 1 year), short-term (1–4 years), medium-term (4–8 years), and long-term (> 8 years) scales. The combined explanatory powers of seven climatic factors on the vegetation were greater at the short-term and long-term scales, whereas individual climatic factors, such as precipitation or temperature, might affect vegetation dynamics in some climatic regions at the seasonal and medium-term scales. The combined effect of climatic factors in the grassland of the Tibetan Plateau (TP) and the temperate grassland of Inner Mongolia (TGIM) were the greatest, which were 65.06% and 59.53%, respectively. The explanatory powers of climate on crop dynamics in both temperate humid and subhumid Northeast China and the TP were around 47%, whereas the controls of climate on crops in both the TGIM and the temperate and warm-temperate desert of Northwest China were around 39%. Cropland farming practices could alleviate the spatial variation of the relationships between climate and vegetation while enhancing the temporal difference of their relationships. Additionally, the dominant influencing factor among different regions varied greatly at the medium-term scale. Collectively, the results might provide an alternative perspective for understanding vegetation evolution in response to climatic changes in China.