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Distribution of Mangroves and Soil Parameters in the Lothian Island of Sundarbans, India—A GIS Approach

In: Advances in Growth Curve and Structural Equation Modeling

Author

Listed:
  • Hema Gupta (Joshi)

    (Indian Statistical Institute, Agricultural and Ecological Research Unit
    Visva-Bharati, Department of Botany)

  • Monoranjan Ghose

    (Indian Statistical Institute, Agricultural and Ecological Research Unit)

Abstract

Tropical mangrove ecosystems are highly productive and provide extensive ecosystem services. This paper analyzes distribution of 21 mangrove species (thirteen true mangroves and eight mangrove associates) in relation to various tidal and edaphic factors. Species density, soil parameters and tidal inundation were explored in 40 sites of the Lothian Island of the Western Sundarbans. Only five species and two soil parameters varied significantly under different tidal inundations. Single-linkage hierarchical classification of species densities generated seven distinct species clusters. Stepwise regression of species densities with soil parameters explained a variation of 42% or higher. Calcium, phosphorus, nitrogen, pH, salinity and sand explained the maximum variation in species densities. Statistical method ‘kriging’ in the Arc GIS generated maps predicting distribution of species densities and selected soil parameters over the island. Maps illustrated highly saline northern mudflat region with a distinct seaward fringe of Avicennia alba and herb Acanthus ilicifolius. Soil nutrients like nitrogen, phosphorus and cations like sodium, calcium and magnesium were concentrated in the northern half of the island. Most of the species were concentrated in the middle- and southern-ridged portion of the island having lower soil salinity.

Suggested Citation

  • Hema Gupta (Joshi) & Monoranjan Ghose, 2018. "Distribution of Mangroves and Soil Parameters in the Lothian Island of Sundarbans, India—A GIS Approach," Springer Books, in: Ratan Dasgupta (ed.), Advances in Growth Curve and Structural Equation Modeling, pages 25-43, Springer.
  • Handle: RePEc:spr:sprchp:978-981-13-0980-9_2
    DOI: 10.1007/978-981-13-0980-9_2
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