Variation in Vegetation Composition and Structure across Mudflat Areas in the Yellow River Delta, China
Year: 2024
Type: article
Abstract: 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.
Source: Remote Sensing
DOI: 10.3390/rs16183495
Institutions: Chinese Academy of Sciences, Institute of Geographic Sciences and Natural Resources Research, State Key Laboratory of Resources and Environmental Information System, Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Aerospace Information Research Institute
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
SDG: Life on land
Open Access status: gold
Estimated APC paid: $3,069
Awards: G2746028381, G7486770615, G8478856234
OpenAlex ID: W4402677325
