# Decoupling the Impacts of Climate Change and Human Activities on Terrestrial Vegetation Carbon Sink
## 5 Conclusions  
This study built a Modis NPP-R\({}_{\rm h}\) model to estimate the NEP in CCZ from 2000 to 2020. Spatiotemporal variation and trends in the NEP time series were then explored. We decoupled the contributions of CC and HA to the variations in NEP. Additionally, we analyzed the changes in NEP in different land use types. Our study aims to provide scientific insights into the management of the terrestrial carbon balance in coastal areas across latitudes. The primary findings are as follows:  
1. NEP across CCZ from north to south shows an obvious spatial heterogeneity, which exhibits a pattern of higher values in the south and lower values in the north. Zhejiang Province was identified as the dividing line of this south-north distribution difference in NEP. The multi-year mean value of NEP in the areas south of Zhejiang Province was 711.62 gC m\({}^{-2}\) yr\({}^{-1}\), while that in the area north of Zhejiang Province was only 285.36 gC m\({}^{-2}\) yr\({}^{-1}\).
2. The hotspot clusters of NEP also show a distinct north-south difference. The high-value cluster of NEP is mainly distributed in the provinces to the south of Zhejiang Province, the low-value cluster is mainly composed of most cities in the north of Zhejiang Province, and there is a highly significant cold-value cluster of NEP in the Beijing-Tianjin-Hebei region. The area experiencing an increasing trend in NEP significantly outweighed that displaying a decreasing trend, signaling a broad enhancement of NEP across CCZ over the past 21 years.
3. Temperature mainly affects the magnitude of NEP in CCZ while precipitation mainly dominates the spatial heterogeneity of NEP. The policymaking of terrestrial carbon sink management in CCZ should take full account of its north-south difference and internal similarity to improve efficiency and reduce unnecessary costs.
4. CC and HA are the main reasons for the changes in NEP in CCZ. NEP changes in provinces north of Zhejiang are mainly characterized by double-driven improvement. On the contrary, single-factor-induced degradation types of NEP are mainly observed in provinces south of Zhejiang. HA in eleven provinces accounted for more than 50% of NEP changes, indicating that HA plays a dominant role in NEP variations.
5. Forests and farmland are the main contributors to the magnitude of NEP in CCZ, and in the context of the constraints of the carbon neutrality target, it is necessary to consider the possible NEP changes that will be triggered by land use planning to ensure the realization of carbon neutrality.  
Conceptualization, S.D. and X.-C.W.; Methodology, S.D., W.R., X.-C.W. and X.Z.; Software, S.D. and F.L.; Formal analysis, W.R. and L.X.; Resources, S.D.; Data curation, S.D., F.L. and L.X.; Writing--original draft, S.D.; Writing--review & editing, W.R., X.D., F.L., X.-C.W., L.X. and X.Z.; Supervision, [PERSON], X.-C.W. and X.Z.; Project administration, X.D.; Funding acquisition, X.-C.W. All authors have read and agreed to the published version of the manuscript.  
This study was supported by the Fundamental Research Funds for the Central Universities (310400209523) and the specific research fund of the Innovation Platform for Academicians of Hainan Province (No. YSPTZX202308).  
The original data presented in the study are openly available on the websites, which are provided in the Section 2.2 of this paper.  
The authors declare no conflict of interest.