Integrated floristic, environmental, and hyperspectral characterization of wetland vegetation in lake Manzala: implications for ecosystem functioning

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DOAJPublished 2026Agriculture & Food ScienceAgricultural Biotechnology
Journal
Frontiers in Sustainable Food Systems
Publisher
Frontiers Media S.A.
Record source
DOAJ Research Library

Abstract / Description

IntroductionLake Manzala, the largest coastal lake in the Northeastern Nile Delta of Egypt, represents a highly disturbed wetland system shaped by strong environmental gradients and persistent anthropogenic pressure. This study integrates floristic surveys with field-based hyperspectral measurements to assess vegetation structure, ecological adaptation, and species-level spectral discrimination across lake shore, islet, and open-water habitats.MethodsFloristic analysis of georeferenced stands identified 55 vascular plant species belonging to 26 families, dominated by perennial taxa and widely distributed chorotypes. Hyperspectral reflectance data (350–2,500 nm) were collected using an ASD FieldSpec spectroradiometer to evaluate vegetation spectral behavior and physiological responses across different wetland habitats.ResultsVegetation composition varied markedly among habitats, with emergent and terrestrial species prevailing along lake shores, while floating and submerged hydrophytes dominated open-water zones. Hyperspectral measurements revealed strong species discrimination, particularly in the near-infrared (NIR) and red-edge regions. These wavelengths effectively separated emergent macrophytes (Phragmites australis and Typha domingensis) from submerged species (Ceratophyllum demersum and Potamogeton pectinatus), while shortwave infrared (SWIR) bands captured variations in leaf water content and biochemical composition. Vegetation indices indicated high productivity in Cyperus alopecuroides, Echinochloa stagnina, and P. pectinatus, whereas halophytic and stress-tolerant species exhibited lower NDVI and elevated stress and senescence indicators. One-way ANOVA confirmed significant interspecific spectral differences (p < 0.05).DiscussionBy integrating hyperspectral sensing with plant functional ecology, this study provides a robust, non-destructive approach for vegetation monitoring, species-level discrimination, and ecological assessment in complex wetland environments.
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