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Article

Spatiotemporal Dynamics of Wetland Landscape Pattern and Its Driving Mechanisms in the Poyang Lake Region (2000–2020)

1
School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, China
2
Hubei Provincial Engineering Research Center of Urban Regeneration, Wuhan University of Science and Technology, Wuhan 430065, China
3
University of Chinese Academy of Sciences, Beijing 100049, China
4
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
*
Author to whom correspondence should be addressed.
Sustainability 2026, 18(10), 5084; https://doi.org/10.3390/su18105084 (registering DOI)
Submission received: 14 April 2026 / Revised: 10 May 2026 / Accepted: 12 May 2026 / Published: 18 May 2026
(This article belongs to the Section Environmental Sustainability and Applications)

Abstract

Poyang Lake represents China’s largest freshwater wetland. The wetland landscape has undergone substantial changes driven by climate change and intensive human activities. Nevertheless, long-term classified analyses of wetland evolution and quantitative assessments of its driving factors remain scarce in the region. Based on 21 Landsat images from 2000 to 2020, this study systematically examined the spatiotemporal dynamics of the wetland landscape. Analyses incorporated land-use dynamic degree, landscape metrics, transfer matrices, and standard deviational ellipses, with key driving forces identified via Pearson correlation and structural equation modeling. Results indicate a 3029.63 km2 reduction in wetland area, exhibiting contrasting trends between natural and artificial wetlands. The wetland centroid shifted 7.4 km southwestward. Connectivity of lake increased and fragmentation declined, whereas paddy field fragmentation intensified. Wetland evolution was predominantly driven by socioeconomic factors, whereas climate primarily influenced natural wetlands. The study elucidates the coupled effects of anthropogenic and natural factors, offering insights into wetland restoration and ecological security in the middle and lower Yangtze River. The findings suggest prioritizing natural wetland connectivity, controlling wetland-to-non-wetland conversion, and incorporating long-term remote-sensing monitoring into regional wetland restoration planning.
Keywords: natural and artificial wetlands; landscape metrics; land-cover change analysis; climate–hydrological factors; socioeconomic factors; remote-sensing monitoring natural and artificial wetlands; landscape metrics; land-cover change analysis; climate–hydrological factors; socioeconomic factors; remote-sensing monitoring

Share and Cite

MDPI and ACS Style

Duan, X.; Jin, Y.; Xu, H.; He, M. Spatiotemporal Dynamics of Wetland Landscape Pattern and Its Driving Mechanisms in the Poyang Lake Region (2000–2020). Sustainability 2026, 18, 5084. https://doi.org/10.3390/su18105084

AMA Style

Duan X, Jin Y, Xu H, He M. Spatiotemporal Dynamics of Wetland Landscape Pattern and Its Driving Mechanisms in the Poyang Lake Region (2000–2020). Sustainability. 2026; 18(10):5084. https://doi.org/10.3390/su18105084

Chicago/Turabian Style

Duan, Xiaoyan, Yiwei Jin, Hong Xu, and Minghui He. 2026. "Spatiotemporal Dynamics of Wetland Landscape Pattern and Its Driving Mechanisms in the Poyang Lake Region (2000–2020)" Sustainability 18, no. 10: 5084. https://doi.org/10.3390/su18105084

APA Style

Duan, X., Jin, Y., Xu, H., & He, M. (2026). Spatiotemporal Dynamics of Wetland Landscape Pattern and Its Driving Mechanisms in the Poyang Lake Region (2000–2020). Sustainability, 18(10), 5084. https://doi.org/10.3390/su18105084

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