Variation in Vegetation Composition and Structure across Mudflat Areas in the Yellow River Delta, China
Variations in vegetation composition and structure are significant signals of the succession of mudflat ecosystems and have important indicative roles in mudflat ecosystem degradation. Due to poor accessibility of vast even mudflat areas, variation in vegetation composition and structure across mudflat areas remains unclear in the Yellow River Delta (YRD), China. We provided an UAV multispectral orthomosaic with 10 cm ground sample distance to classify and compare the vegetation composition and structure across mudflat areas in the YRD. The vegetation classification overall accuracy achieved 95.0%. We found that although a significant difference (p < 0.05) was checked out in terms of the Shannon–Wiener diversity index (from 1.33 to 0.92) and evenness index (from 0.96 to 0.66) among the eight subareas from land to sea, all four dominant vegetation communities (S. salsa, L. bicolor, T. chinensis, and P. australis) were discovered at all eight subareas. Our findings support the idea that the regional environment and local microtopography are the predominant forces for variation in vegetation composition and structure across mudflat areas. From the perspective of vegetation restoration and conservation, changing the local microtopography will be an interesting way to enhance the vegetation diversity of the mudflat ecosystems in the YRD.
Authors
- Chong Huang (ORCID: https://orcid.org/0000-0003-0779-8214)
- Wei Wu (ORCID: https://orcid.org/0000-0001-6548-1544)
- Shuxuan Wang (ORCID: https://orcid.org/0000-0002-1111-1318)
- He Li (ORCID: https://orcid.org/0000-0002-3360-4746)
- Xin Zhang (ORCID: https://orcid.org/0000-0003-0394-7972)
- Lei Shi
- Qingsheng Liu
Institutions
- China University of Political Science and Law (CN)
- Chinese Academy of Sciences (CN)
- Aerospace Information Research Institute (CN)
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application (CN)
- Institute of Geographic Sciences and Natural Resources Research (CN)
Publication Details
- Journal
- Remote Sensing
- Published
- 2024-09-20
- DOI
- https://doi.org/10.3390/rs16183495
- Citations
- 5
- Primary Topic
- Coastal wetland ecosystem dynamics
- Type
- article
- Field-Weighted Citation Impact
- 2.29
Funders
- National Key Research and Development Program of China