Author
Listed:
- Di Dong
(South China Sea Development Research Institute, Ministry of Natural Resources, Guangzhou 510300, China
Technology Innovation Center for South China Sea Remote Sensing, Surveying and Mapping Collaborative Application, Ministry of Natural Resources, Guangzhou 510300, China
Key Laboratory of Marine Environmental Survey Technology and Application, Ministry of Natural Resources, Guangzhou 510300, China)
- Huamei Huang
(South China Sea Development Research Institute, Ministry of Natural Resources, Guangzhou 510300, China
Technology Innovation Center for South China Sea Remote Sensing, Surveying and Mapping Collaborative Application, Ministry of Natural Resources, Guangzhou 510300, China)
- Qing Gao
(South China Sea Development Research Institute, Ministry of Natural Resources, Guangzhou 510300, China
Technology Innovation Center for South China Sea Remote Sensing, Surveying and Mapping Collaborative Application, Ministry of Natural Resources, Guangzhou 510300, China)
- Kang Li
(South China Sea Development Research Institute, Ministry of Natural Resources, Guangzhou 510300, China
Technology Innovation Center for South China Sea Remote Sensing, Surveying and Mapping Collaborative Application, Ministry of Natural Resources, Guangzhou 510300, China)
- Shengpeng Zhang
(South China Sea Development Research Institute, Ministry of Natural Resources, Guangzhou 510300, China
Technology Innovation Center for South China Sea Remote Sensing, Surveying and Mapping Collaborative Application, Ministry of Natural Resources, Guangzhou 510300, China)
- Ran Yan
(South China Sea Development Research Institute, Ministry of Natural Resources, Guangzhou 510300, China
Technology Innovation Center for South China Sea Remote Sensing, Surveying and Mapping Collaborative Application, Ministry of Natural Resources, Guangzhou 510300, China)
Abstract
Coastal blue carbon ecosystems serve as vital carbon sinks in global climate regulation, yet their long-term carbon storage dynamics remain poorly quantified at regional scales. This study quantified the spatiotemporal evolution of mangrove and salt marsh carbon storage in Guangdong Province, China, over three decades (1986–2020), by integrating a new mangrove and salt marsh detection framework based on Landsat image time series and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The proposed detection framework provided two coastal vegetation detection methods, exploring the potential of utilizing phenological features to improve the mangrove and salt marsh discrimination accuracy with Landsat data. The overall accuracies of both mangrove and salt marsh detection results exceeded 90%, suggesting good consistency with the validation data. The mangrove extent showed a trend of decreasing from 1986 to 1995, then fluctuated from 1995 to 2005, and presented an upward trend from 2005 to 2020. The overall trend of the salt marsh area was upward, with small fluctuations. The mangrove carbon storage in Guangdong increased from 414.66 × 10 4 Mg C to 490.49 × 10 4 Mg C during 1986–2020, with Zhanjiang having the largest mangrove carbon storage increase. The salt marsh carbon storage in Guangdong grew from 8.73 × 10 4 Mg C in 1986 to 14.39 × 10 4 Mg C in 2020, with Zhuhai as the salt marsh carbon sequestration hotspot. The temporal dynamics of carbon storage in mangroves and salt marshes could be divided into three stages, namely a decreasing period, a fluctuating period, and a rapid increase period, during which ecological and economic policies played a crucial role. The multi-decadal blue carbon datasets and their temporal-spatial change analysis results here can provide a scientific basis for nature-based climate solutions and decision-support tools for carbon offset potential realization and sustainable coastal zone management.
Suggested Citation
Di Dong & Huamei Huang & Qing Gao & Kang Li & Shengpeng Zhang & Ran Yan, 2025.
"Temporal and Spatial Patterns of Blue Carbon Storage in Mangrove and Salt Marsh Ecosystems in Guangdong, China,"
Land, MDPI, vol. 14(6), pages 1-27, May.
Handle:
RePEc:gam:jlands:v:14:y:2025:i:6:p:1130-:d:1661581
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