UAV-based modelling of vegetation recovery under extreme habitat stresses in the water level fluctuation zone of the Three Gorges Reservoir, China
Impoundment of the Three Gorges Reservoir on the upper Yangtze River has remarkably altered hydrological regime within the dammed reaches, triggering structural and functional changes of the riparian ecosystem. Up to date, how vegetation recovers in response to compound habitat stresses in the water level fluctuation zone remains inexplicitly understood. In this study, plant above-ground biomass (AGB) in a selected water level fluctuation zone was quantified to depict its spatial and temporal pattern using unmanned aerial vehicle (UAV)-derived multispectral images and screened empirical models. The contribution of multiple habitat stressors in governing vegetation recovery dynamics along the environmental gradient were further explored. Screened random forest models indicated relatively higher accuracy in AGB estimation, with R2 being 0.68, 0.79 and 0.62 during the sprouting, growth, and mature period, respectively. AGB displayed a significant linear increasing trend along the elevational gradient during the sprouting and early growth period, while it showed an inverted U-shaped pattern during late growth and mature period. Flooding duration, magnitude and timing was found to exert greater negative effects on plant sprouting and biomass accumulation and acted as decisive factors in governing the elevation-dependent pattern of AGB. Localized spatial variations in AGB were modulated by other stressors such as sediment burial, soil erosion, soil moisture and nutrient content. Occurrence of episodic summer floods and vegetation distribution were responsible for an inverted U-shaped pattern of AGB during the late growth and mature period. Generally, AGB reached its peak in August, thereafter an obvious decline by a unprecedent dry-hot climatic event. The water level fluctuations with cumulative flooding effects exerted substantial control on AGB temporal dynamics, while climatic condition played a secondary role. Herein, further restorative efforts need to be directed to screening suitable species, maintaining favorable soil condition, and improving vegetation pattern to balance the many trade-offs.
| Item Type | Article |
|---|---|
| Open Access | Not Open Access |
| Additional information | This work was supported by the Science Fund for Distinguished Young Scholars of Chongqing(cstc2021jcyj-jqX0026), the Special Fund for Youth Team of Southwest University (SWU -XDJH202306), Fundamental Research Funds for the Central Universities (SWU020013), and National Natural Science Foundation of China (U2040207). The contribution by ALC was funded by the UK Research and Innovation –Biotechnology and Biological Sciences Research Council (UKRI -BBSRC) via grant award BB/X010961/1 (Resilient Farming Futures) – specifically work package 2 - BBS/E/RH/230004B;Detecting agroecosystem ‘resilience’ using novel data science methods |
| Keywords | Vegetation recovery dynamics, Above ground biomass, Habitat stresses, Water level fluctuation zone, Three Gorges Reservoir |
| Project | Resilient Farming Futures, Resilient Farming Futures (WP2): Detecting agroecosystem ‘resilience’ using novel data science methods |
| Date Deposited | 05 Dec 2025 10:41 |
| Last Modified | 19 Dec 2025 14:57 |
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