Abstract

Sri Lanka is a tropical island biodiversity hotspot with luxurious yet extremely vulnerable mangrove vegetation encompassing its coastline. The country has been a pioneer in mangrove conservation and rehabilitation since the unfortunate Indian Ocean tsunami disaster incident in 2004. Still, most mangrove restoration efforts have failed primarily because of a poor understanding of environment–vegetation interactions in local mangrove settings. The current study examined the vegetation structure, and soil chemical properties of Vidattaltivu mangrove forest, a complex coastal ecosystem on the northern coast of Sri Lanka characterized by dry climatic conditions. We employed several statistical approaches, namely simple correlation, generalized linear models (GLM), principal component analysis (PCA), and canonical correlation analysis (CCA), to understand soil–vegetationinteractions. Results indicated Vidattaltivu as a growing secondary mangrove forest, and soil salinity and nutrients showed to be the main drivers of the variability in mangrove vegetation structure and composition. The performance of most mangrove species (i.e., stand basal area and biomass) declined with increasing soil salinity, whereas Avicennia marina thrived at high salinities. Results of PCA and subsequent CCA suggested that mangrove soil and vegetation exist in a reciprocating multivariate system. Soil pH, salinity, organic matter, K, Mg, Ca, Cu, Ni, Zn, and Mn were identified as fundamental soil chemical properties that preserve and support mangrove vegetation. In return, tree density, tree height, stand basal area, tree biomass, and vegetation complexity sustained the soil as primary forest structural attributes.

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