Influence of vegetation phenology on modelling carbon fluxes in temperate deciduous forest by exclusive use of MODIS time-series data

Understanding the influence of vegetation phenology on modelling primary productivity, biomass, and natural carbon dynamics, as well as the underlying mechanisms, is crucial for assessing the vulnerability of terrestrial carbon pools under future changing climate conditions. Considering that the component fluxes of carbon sequestration, gross primary production (GPP) and ecosystem respiration (R _e), are dominant alternately during the course of the year, here we propose a new model for estimating the carbon sequestration of temperate deciduous forest exclusively based on Moderate Resolution Imaging Spectroradiometer (MODIS) time-series data, including land-surface temperature (LST), Terra night-time LST (LST′), enhanced vegetation index (EVI), land-surface water index (LSWI), fraction of absorbed photosynthetically active radiation (FPAR), and leaf area index (LAI). This study aims to reveal the main environmental control variables that contribute to the net ecosystem exchange (NEE) variations and to develop an improved model that accurately predicts NEE according to the growing and dormant seasons. The seasonality information was extracted from time series of MODIS NDVI data based on nonlinear least squares fits of asymmetric Gaussian model functions in the computer program, TIMESAT. The results suggest that the improved model could provide substantially better NEE estimates and well reflect the seasonal dynamics of the temperate deciduous forest. In addition, because both ecosystem photosynthesis and respiration are powerful during the growing season, all variables are strongly correlated with NEE at the 0.01 p-level, whereas only some parameters (temperature and water) are significant during the non-growing period due to dominant respiration and limited photosynthesis.