Assessment of Coastal Carbon Storage and Analysis of Its Driving Factors: A Case Study of Jiaozhou Bay, China

• Published in: Land (Basel) Vol. 13; no. 8; p. 1208
• Main Authors: Zhang, Longkun, Guan, Qingchun, Li, Hui, Chen, Junwen, Meng, Tianya, Zhou, Xu
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2024
• Subjects: Assessments; Biodiversity; Bird migration; blue carbon; Carbon; Carbon cycle; Carbon sequestration; CASA model; Climate change; Coastal management; Coastal zone; Data acquisition; Ecosystem management; Ecosystem services; Ecosystems; Global climate; InVEST model; Land management; Land use; land use change; Population density; Productivity; Radiation; Remote sensing; Socioeconomic factors; Socioeconomics; Temporal variations; Urbanization; Vegetation; Vegetation cover; Wetlands; China; Jiaozhou Bay
• DOI: 10.3390/land13081208
• ISSN: 2073-445X

Global climate change and coastal urbanization have significantly impacted the health and carbon storage of coastal zone ecosystems. Investigating the spatial and temporal variations in coastal carbon storage is crucial for developing effective strategies for land management and ecological protection. Current methods for evaluating carbon storage are hindered by insufficient accuracy and data acquisition challenges, necessitating solutions to enhance both reliability and precision. This study aims to assess the variations in carbon storage and annual carbon sequestration in the Jiaozhou Bay coastal zone from 1990 to 2020 and to identify the driving factors by integrating the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and Carnegie Ames Stanford Approach (CASA) models with remote sensing data and geographic detector methods. The findings suggest that Jiaozhou Bay has experienced a substantial decrease in carbon storage, declining by 17.4% from 1990 to 2020, and annual carbon sequestration, decreasing by 35.5% from 1990 to 2016, but has stabilized recently. Vegetation cover and water bodies play critical roles in regional carbon storage. Furthermore, the dynamics of carbon storage and land use patterns are significantly influenced by socioeconomic factors, including GDP and population density. A comparison of the InVEST and CASA models demonstrates consistency in their carbon storage and annual carbon sequestration assessments. Combining these models in future assessments can enhance the scientific rigor and accuracy of the research, providing more reliable evidence for ecosystem management and policy making.