Phenological Response of an Evergreen Broadleaf Tree, Quercus acuta, to Meteorological Variability: Evaluation of the Performance of Time Series Models

Phenological events are key indicators for the assessment of climate change impacts on ecosystems. Most previous studies have focused on identifying the timing of phenological events, such as flowering, leaf-out, leaf-fall, etc. In this study, we explored the characteristics of the green chromatic coordinate (GCC) values of the evergreen broadleaf tree (Quercus acuta Thunb.), which is a widely used index that serves as a proxy for the seasonal and physiological responses of trees. Additionally, we estimated their relationship with meteorological variables using time series models, including time series decomposition and a seasonal autoregressive integrated moving average with exogenous regressors (SARIMAX). Our results showed that the GCC values and the meteorological variables, which were collected at daily intervals, exhibited a strong autocorrelation and seasonality. This suggests that time series analysis methods are more suitable than ordinary least squares (OLS) regression methods for the fulfillment of statistical assumptions. The time series analysis results highlighted a strong association between precipitation and GCC variation in evergreen broadleaf trees, particularly during the dry season. These results improve our understanding of the response of plant phenology to climate change.