Spatio-Temporal Dynamic Characteristics of Carbon Use Efficiency in a Virgin Forest Area of Southeast Tibet

Abstract

The sequestration of carbon in forests plays a crucial role in mitigating global climate change and achieving carbon neutrality goals. Carbon use efficiency (CUE) is an essential metric used to evaluate the carbon sequestration capacity and efficiency of Vegetation. Previous studies have emphasized the importance of assessing CUE at specific regions and times to better understand its spatiotemporal variations. The southeastern region of Tibet in the Qinghai-Tibet Plateau is recognized as one of the most biodiverse areas in China and globally, characterized by diverse vegetation types ranging from subtropical to temperate. In this study, we focused on Nyingchi, which is the largest virgin forest area in southeast Tibet, to explore the spatial-temporal dynamic characteristics of regional CUE based on MODIS remote sensing products. The following results were obtained: (1) On a monthly scale, regional CUE exhibits significant seasonal variations, with varying patterns among different vegetation types. Specifically, the fluctuation of CUE is the lowest in high-altitude forest areas and the greatest in grasslands and barrens. On an annual scale, forests exhibit higher fluctuations than areas with sparse vegetation and the overall volatility of CUE increased over the past 11 years. (2) There are regional differences in the trend of CUE changes, with a substantial downward trend in the Himalayan region and a significant upward trend in the residual branches of the Gangdise Mountains. More than 75% of the regions exhibit no persistent trend in CUE changes. (3) Vegetation type is the main determinant of the range and characteristics of vegetation CUE changes, while the geographical location and climatic conditions affect the variation pattern. CUE in the southern and northern regions of Nyingchi at 28.5°N exhibits different responses to temperature and precipitation changes, with temperature having a more significant impact on CUE.

Temporal and Spatial Dynamics in Carbon Utilization Efficiency and Driving Mechanisms in Southeast Tibet from 2012 to 2022

“…Following the classification method, the regional coefficient of variation (CV) is categorized into five levels: CV < 0.05 is considered low volatility, 0.05 ≤ CV < 0.10 is relatively low volatility, 0.10 ≤ CV < 0.15 is moderate volatility, 0.15 ≤ CV < 0.20 is relatively high volatility, and CV ≥ 0.20 is high volatility [40].…”