Spatiotemporal variation of net primary productivity influenced by climatic variables in the karst area of China

Abstract

Karst area is one of the most ecologically fragile regions. Monitoring spatial and temporal variation of net primary productivity (NPP) and its response to climate change are essential for vegetation restoration. In this study, we used the CASA (Carnegie-Ames-Stanford Approach) model to estimate the NPP in the karst area of China during 2001 to 2019. We analyzed the response of multi-scale NPP to climate change by using Theil-Sen Median trend analysis, partial correlation analysis and time lag analysis. The results showed that the average NPP was 399.06 gC·m−2, decreased from southeast to northwest, with an annual increase rate of 1.93 gC·m−2 from 2001 to 2019. The broadleaf forest had the highest NPP, and summer NPP accounted for 48.12% of annual NPP. Climate change significantly promotes the increase of NPP in the early growing season. Partial correlation analysis showed that NPP was more correlated with precipitation (0.20) than temperature (0.12), this phenomenon was more pronounced in some arid regions. Where precipitation caused a decrease in NPP during the rainy season. The time lag of NPP to temperature change was shorter than precipitation, indicating that NPP is more sensitive to temperature in most regions. The time lag of NPP to temperature changes was very short in spring. Whereas, even in arid regions, the time lag of NPP to precipitation changes was still long. This study can deepen our knowledge of the response of NPP to climate change in karst ecosystems.