Response of net primary productivity of vegetation to drought: A case study of Qinba Mountainous area, China (2001–2018)

Abstract

Drought can significantly affect the carbon cycle of ecosystems. The Qinba Mountains region has a high potential for developing carbon sink forestry due to its strong carbon fixation capacity. This study applied the Carnegie-Ames-Stanford approach (CASA) model calculate monthly net primary productivity (NPP) in the region from 2001 to 2018. The standardized precipitation evapotranspiration indices (SPEI1-12) at various time scales were also analyzed by the Thornthwaite method, along with the test of significance and sustainability (Sen-MK-Hurst) model, to examine the persistent characteristics of dry and wet changes in the Qinba Mountains. The results of the correlation analysis between NPP and SPEI at multiple time scales showed that regional vegetation NPP is significantly impacted by drought, with the most sensitive months being July and October. On average, there is a four-month cumulative effect of drought on NPP. About 45.49% and 19.99% of NPP in the Qinba Mountains region are extremely or heavily sensitive to drought, with grasses being the most sensitive, followed by cultivated plants, deciduous broadleaved forests, mixed forests, sparse forests, and shrublands. The study also found that 40.99% of the region is expected to become wetter and 14.9% is expected to become drier in the future. Understanding the response of NPP to drought in this region can help with the management of regional climate change for environmental regulation.

Keywords

• NPP
• SPEI
• Delayed effect
• Time scales
• Drought