Spatiotemporal Distribution and Influencing Factors of Carbon Storage in Chongming Coastal Wetlands

HAN Zhen, WENG Xuan, ZHOU Yi, HANG Jun, CHEN He, GU Wei

Journal of Changjiang River Scientific Research Institute ›› 2025, Vol. 42 ›› Issue (6) : 78-86.

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Journal of Changjiang River Scientific Research Institute ›› 2025, Vol. 42 ›› Issue (6) : 78-86. DOI: 10.11988/ckyyb.20240460
Soil and Water Conservation and Ecological Restoration

Spatiotemporal Distribution and Influencing Factors of Carbon Storage in Chongming Coastal Wetlands

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Abstract

[Objectives] In the context of global climate change, studies on coastal wetlands and their carbon sink capacity face both major opportunities and challenges. Therefore, investigating their spatiotemporal distribution is crucial for achieving the “dual carbon” goals. [Methods] Taking the coastal wetlands of Chongming Island, Shanghai, as the study area, Sentinel-2 remote sensing images in 2015, 2017, 2019, and 2021 were used. Based on corrected carbon density and land use derived from supervised classification, the spatiotemporal distribution characteristics of carbon storage were obtained. The influencing factors of carbon storage were quantitatively analyzed using the geodetector method. [Results] The periphery of Chongming Island is dominated by wetlands, with natural wetlands (mainly river-lake water bodies, grasslands, reed beds, and tidal flats) primarily distributed along the shoreline, while the inner area is non-wetland. The area of both artificial and natural wetlands increased significantly, by approximately 20 000 hm2. The carbon storage of Chongming Island first increased and then decreased, but wetland carbon storage remained high, showing an overall positive trend of annual increase (approximately 600 000 tons). Conversions from non-wetland to both natural and artificial wetlands led to increases in carbon storage, indicating the high carbon sequestration potential of coastal wetlands. Natural factors had a weak influence on wetland carbon storage in Chongming Island, whereas socioeconomic development had a stronger impact. The geodetector q-values for economic added value and land use intensity reached 0.79 and 0.82, respectively. The interactive effects of natural and human factors, such as GPP combined with economic added value and population, yielded a q-value of up to 0.99, highlighting the importance of human-nature harmony in enhancing carbon sequestration in wetlands. [Conclusion] Using meteorological data from Shanghai and Chongming Island, together with a carbon density correction model, the local carbon density of Chongming District was derived. This method has low data acquisition difficulty, as most meteorological data required for local carbon density calculations can be obtained from the study area’s statistical yearbooks, and pre-correction carbon density can be retrieved from other literature. The method is applicable to coastal wetlands and other “dual carbon” focus areas, enabling accurate acquisition of localized parameters and improving the accuracy of carbon storage estimation to some extent. Additionally, directly applying geodetector to carbon storage simplifies the analysis process compared to indirect detection via land cover types and improves accuracy. The results show that wetland areas are generally increasing, with a significant growth in the proportion of natural wetlands. Carbon storage in Chongming’s coastal wetlands has increased annually, indicating initial success in wetland conservation. Dual-factor interactive effects have a greater impact on coastal wetland carbon storage than single-factor effects, and carbon storage is greatly influenced by socioeconomic factors.

Key words

carbon storage / spatiotemporal distribution / driving factors / geodetector / Chongming Island

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HAN Zhen , WENG Xuan , ZHOU Yi , et al . Spatiotemporal Distribution and Influencing Factors of Carbon Storage in Chongming Coastal Wetlands[J]. Journal of Changjiang River Scientific Research Institute. 2025, 42(6): 78-86 https://doi.org/10.11988/ckyyb.20240460

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Spatial stratified heterogeneity is the spatial expression of natural and socio-economic process, which is an important approach for human to recognize nature since Aristotle. Geodetector is a new statistical method to detect spatial stratified heterogeneity and reveal the driving factors behind it. This method with no linear hypothesis has elegant form and definite physical meaning. Here is the basic idea behind Geodetector: assuming that the study area is divided into several subareas. The study area is characterized by spatial stratified heterogeneity if the sum of the variance of subareas is less than the regional total variance; and if the spatial distribution of the two variables tends to be consistent, there is statistical correlation between them. Q-statistic in Geodetector has already been applied in many fields of natural and social sciences which can be used to measure spatial stratified heterogeneity, detect explanatory factors and analyze the interactive relationship between variables. In this paper, the authors will illustrate the principle of Geodetector and summarize the characteristics and applications in order to facilitate the using of Geodetector and help readers to recognize, mine and utilize spatial stratified heterogeneity.

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