Time-lagged response of vegetation dynamics to climatic and teleconnection factors

Abstract

Understanding vegetation dynamics and its response to climate changes is important for revealing the mechanisms of terrestrial ecosystem behaviour, predicting future vegetation growth, and thus guiding environmental management. The Jing River Basin (JRB) and the Beiluo River Basin (BLRB), two typical ecoenvironmentally vulnerable regions on the Loess Plateau in China, were selected as case study regions. Based on long-term Normalized Difference Vegetation Index (NDVI) datasets, the time-lag relationships between NDVI and climatic factors (precipitation/temperature) as well as teleconnection factors (large-scale modes of climate variability and solar activity) were revealed. Additionally, ridge regression models were established to quantitatively explore the response of vegetation dynamics to climate change. Results indicate that: (1) NDVI in autumn showed significantly increasing trend (p < 0.01), whereas that in spring and summer was insignificant; (2) there was a time-lag of more than one month between spring/winter NDVI and precipitation/temperature behaviour, and summer NDVI exhibited no lag with temperature but a one month lag with precipitation; (3) regarding the time-lag effects, precipitation was the driving factor of NDVI variations in spring, whereas sunspots dominated NDVI variations in autumn; (4) when time-lagged teleconnection factors were considered, the explanation of the climate effect on the vegetation dynamics in three seasons all relatively increased by >95%, which indicates that the prediction accuracy of NDVI was significantly improved; (5) in summer, time-lagged climatic and teleconnection factors explained <20% of NDVI variations, whereas when soil moisture and base flow were considered, the explanation of NDVI changes in the JRB and BLRB relatively increased by 37.4% and 65.1%, respectively. These findings highlight that considering the time-lag effect of climatic and teleconnection factors has important significance for the accurate monitoring of underlying surface dynamics under changing environment.