Rainfall and Elevation Influence the Local-Scale Distribution of Tree Community in the Southern Region of Western Ghats Biodiversity Hotspot (India)

Shijo Joseph,Ch Sudhakar Reddy,V K Srivastava,A P Thomas,K Anitha,M S R Murthy

doi:10.1155/2012/576502

Abstract

The present study characterises the tree communities with respect to topographic and climatic variables and identifies the most important environmental correlate of species richness in the southern region of Western Ghats Biodiversity Hotspot, India. Digitally derived environmental variables in combination with tree species richness information were analysed using Canonical Correspondence Analysis (CCA) to characterise the communities. Multiple regression technique based on stepwise backward elimination was used to identify the most important environment correlate of species richness. Canonical correspondence analysis results in six major tree communities along the first and second axes. Rainfall is the dominant environmental gradient influencing vegetation patterns on the first CCA axis while elevation showed the highest correlation with the second CCA axis. Backward elimination regression technique yielded rainfall as the most important environmental correlate of species richness. Results were in agreement with the observations in the Neotropics that rainier areas maintain high species diversity.

Highlights

Tropical forests are unique in many aspects such as high diversity [1], high standing biomass and carbon storage [2], and global net primary productivity [3]
Canonical correspondence analysis was performed for 169 species recorded on 206 plots with 5 environmental variables to understand the tree community composition of the study area
The low rainfall (1500 m) and slope by montane shola community

Summary

Introduction

Tropical forests are unique in many aspects such as high diversity [1], high standing biomass and carbon storage [2], and global net primary productivity [3]. Information on distribution of tree communities along environmental gradients has vital role in understanding their ecology as well as their conservation and management Quantification of such species-environment relationships yields valuable insights into ecological processes such as resource partitioning and niche differentiation [12] and forms the core of predictive geographical modelling in ecology [13]. Today’s concern about biodiversity losses and ecosystem services suggest that forest classifications based on species composition are needed, along with the information on how many species are shared between different forest types. This information in combination with the key environmental correlates is important for natural reserve area planning and management under global change scenarios

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