Modern pollen–vegetation studies from the Sajnekhali Island Wildlife Sanctuary, Sundarbans, Eastern India
Modern pollen–vegetation studies are crucial for the calibration and interpretation of fossil pollen assemblages. In eastern India, knowledge regarding the relationship between pollen deposition and the modern-day vegetation is required to make use of fossil pollen data, which is still scant. To fill this gap, the present study deals with the pollen analysis of 20 surface sediment samples from the Sajnekhali Island Wildlife Sanctuary, Sundarbans, India. The palynological results show that 20 genera in 18 families are identified, of which 16 major pollen taxa are recorded under mangrove and its associate groups. To understand potential drivers changing pollen abundance in the surface samples, a detrended correspondence analysis (DCA) is conducted to typify the environmental gradients among samples. The DCA of the modern pollen assemblages reveals the taxa defining the environmental gradient from inland to the margin of the island. The primary gradient appears to be the salinity tolerance of mangroves from near the water margin to the less salt-tolerant taxa. Axis 1 describes 62.5% of the variance in the dataset. The secondary axis appears to describe the gradient in subtaxa away from the mangrove. Axis 2 describes 4.5% of the variance in the dataset. Rhizophora mucronata, Avicennia marina, Sonneratia apetala, Excoecaria agallocha, Heritiera fomes, Bruguiera gymnorrhiza, Xylocarpus granatum and Nypa fruticans are recorded as the dominant pollen taxa that follow a salinity gradient. All modern pollen rain appears compatible with the actual floristics of the area. Thus, the present study indicates that the mangrove environment is well represented in the pollen record and displays close linkages between pollen composition and native parent plants in the area. This pollen dataset fills an information gap and is useful in understanding and interpreting the palaeoecology and palaeoenvironment of tropical marshes of similar environments.
