The Impact of Seasonality and Response Period on Qualifying the Relationship between Ecosystem Productivity and Climatic Factors over the Eurasian Steppe

Remote Sensing

Qi Liu¹  Jiahua Zhang¹  Quan Liu¹  Fengmei Yao¹  Xianglei Meng¹  Hairu Zhang² 

[1] College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China;National Academy of Economic Strategy, Chinese Academy of Social Sciences, Beijing 102488, China;

关键词: Eurasian Steppe;    solar-induced chlorophyll fluorescence;    climatic factors;    seasonality;    response period;   

DOI  :  10.3390/rs13163159

来源: DOAJ

【 摘 要 】

As climate change intensifies, surface vegetation productivity and carbon exchange between terrestrial ecosystems and the atmosphere are significantly affected by the variation of climatic factors. Due to the sensitivity of grasslands to these climatic factors, it is crucial to understand the response of vegetation greenness, or carbon exchange within grasslands, to environment factor dynamics. In this study, we used solar-induced chlorophyll fluorescence (SIF), precipitation (P), vapor pressure deficit (VPD), evaporative stress (ES), and root zone soil moisture (RSM) derived from remote sensing, reanalysis, and assimilation datasets to explore the response of vegetation greenness within Eurasian Steppe to climatic factors. Our results indicated deseasonlization based on the Seasonal-Trend decomposition using Loess (STL) method, which was an effective means to remove the seasonality disturbances that affect the qualification of the relationship between SIF and the four climatic factors. The response of SIF had a time lag effect on these climatic factors, and the longer the response period, the greater the impact on the correlation of SIF with P, VPD, ES, and RSM. We also found, among the four factors, that the response of SIF to ES was the timeliest. The findings of this study emphasized the impact of the seasonality and time lag effect on the dynamic response between variables, and provided references to the attribution and monitoring of vegetation greenness and ecosystem productivity.

【 授权许可】

Unknown