A wavelet coherence approach to zoning supply-demand matching of carbon sequestration service.

Carbon sequestration (CS) is an important regulating service provided by ecosystem which plays an important role in mitigating global climate change. However, there is often a spatial mismatch between the carbon sequestration supply and demand (CSSD), which makes it difficult to reduce carbon emissions and increase carbon sinks to achieve local carbon balance. Therefore, it is important to clarify the optimal scale of the spatial matches and mismatch between CSSD and delimit spatial units for implementing effective management policies and realizing rational allocation of resources. Taking Hunan Province, China as an example, this study evaluated CSSD in 2001 and 2017, and identified the optimal scale of spatial matching based on wavelet coherence analysis. The results showed that from 2001 to 2017, CS supply in Hunan Province increased by 6.69 %, and CS demand increased by 260.50 %. 8.13 km was the optimal scale of spatial matches and mismatches of CSSD, and Hunan Province could be divided into 3446 spatial units including four types, High supply-High demand (HS-HD), Low supply-Low demand (LS-LD), High supply-Low demand (HS-LD) and Low supply-High demand (LS-HD) according to the combination of CSSD values in each spatial unit. Based on the changes of spatial units from 2001 to 2017, the key regions in need of ecological protection were identified. The spatial units delimited in this study can support accurate monitoring and management under the background of improving the "one map" of territorial space in Hunan Province. This study provided a spatial zoning approach based on wavelet coherence analysis and put forward suggestions for land use management, in order to drive the achievement of carbon peaking and carbon neutrality targets in China.