中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Human activities dominate a staged degradation pattern of coastal tidal wetlands in Jiangsu province, China

文献类型:期刊论文

作者Wang, Han; Zhou, Yuke; Wu, Jiapei; Wang, Chunxiao; Zhang, Ruixin; Xiong, Xiaoqing; Xu, Chang
刊名ECOLOGICAL INDICATORS
出版日期2023-10-01
卷号154页码:110579
ISSN号1470-160X
关键词Coastal tidal wetland Wetland degradation Classifications Change detection Landsat Google Earth Engine
DOI10.1016/j.ecolind.2023.110579
产权排序1
文献子类Article
英文摘要The tidal wetlands in Jiangsu Province (JS) play a crucial role as a major blue carbon sink in the eastern coastal area of China. These wetlands also contribute significantly function to biodiversity and the provision of ecosystem services. However, due to the escalating impact of anthropogenic activities and climatic changes, the ecological scope, structure, and function of tidal wetlands have changed drastically. This study aims to depict the spatiotemporal dynamics of these wetlands and explore the driving forces behind these changes. Based on the Google Earth Engine (GEE) platform, we conducted a comprehensive analysis of all the available Landsat imagery (5096 images, 30-m spatial resolution) using the Continuous Change Detection and Classification (CCDC) algorithm. The outputs consist of annual land cover maps of JS coastal zone, from 1990 to 2020. Results indicate that the generated coastal maps generally exhibit an exceptionally high average accuracy (92.62%) and there were 2666.54 km2 of tidal wetlands (Spartina alterniflora: 240.86 km2, Suaeda salsa: 37.31 km2, Phragmites australis: 150.63 km2, intertidal flat: 2158.18 km2, supratidal barren flat: 79.53 km2) in 2020, amounting to a 23.43% decrease of the initial year 1990. The tidal wetlands landscape had a staged decline during 1990-2020, and the hydrological vegetation habitat was the area with the greatest variability. Over the past three decades, the losses of tidal wetlands amounted to 1,466.22 km2, partially offset by gains of 650.05 km2. The two most substantial sources of losses were intertidal flat and Suaeda salsa with the most significant ratio of loss to gain (4.80, 10.31, respectively). Generally, we categorized tidal wetlands degradation into three transformation processes: human activities, species invasion, and natural succession. Human activities, particularly the conversion of intertidal flat into aquafarm, dominated the entire degradation process. Meanwhile, in the main driving analysis, we discovered that 60% of these losses and gains were directly tied to human activities. The indirect driving process includes natural coastal movements, climate change, unobservable human activities, and their aggregate effects, which gradually assist tidal wetlands ecosystems to re-establish and recover. The annual coastal wetland maps and detailed information on the evolutionary patterns and the corresponding drivers are valuable for identifying blue carbon distribution and enhancing the ecological services of the coastal zone.
WOS关键词VEGETATION INDEX NDVI ; TRENDS ; CLASSIFICATION ; CONSERVATION ; DISTURBANCE ; RECOVERY
WOS研究方向Biodiversity & Conservation ; Environmental Sciences & Ecology
语种英语
出版者ELSEVIER
WOS记录号WOS:001029015300001
源URL[http://ir.igsnrr.ac.cn/handle/311030/194589]  
专题生态系统网络观测与模拟院重点实验室_外文论文
作者单位1.Chinese Academy of Sciences
2.University of Chinese Academy of Sciences, CAS
3.China University of Mining & Technology
4.Ministry of Natural Resources of the People's Republic of China
推荐引用方式
GB/T 7714
Wang, Han,Zhou, Yuke,Wu, Jiapei,et al. Human activities dominate a staged degradation pattern of coastal tidal wetlands in Jiangsu province, China[J]. ECOLOGICAL INDICATORS,2023,154:110579.
APA Wang, Han.,Zhou, Yuke.,Wu, Jiapei.,Wang, Chunxiao.,Zhang, Ruixin.,...&Xu, Chang.(2023).Human activities dominate a staged degradation pattern of coastal tidal wetlands in Jiangsu province, China.ECOLOGICAL INDICATORS,154,110579.
MLA Wang, Han,et al."Human activities dominate a staged degradation pattern of coastal tidal wetlands in Jiangsu province, China".ECOLOGICAL INDICATORS 154(2023):110579.

入库方式: OAI收割

来源:地理科学与资源研究所

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