Spatial distribution of dominant plants species according to local environmental gradients

Abstract

At the current stage of vegetation ecology development as a science it has not been reached consensus between the competing theories trying to explain vegetation pattern emerging under the influence of underlying environmental gradients. It is still not clear what is the response of different plant species towards the influence of complex gradients? This study tries to revise some classical and temporary hypotheses concerning species response surface/curve shape along environmental gradients – whether it is symmetric (Gaussian) or with other shape. It also attempts to check if species modes along complex gradients are distributed randomly, uniformly or they are clumped, as well as to inspect the species mode distribution among species importance value octaves – whether it is lognormal or lograndom. Field samples were gathered using gradsect method for laying down sampling plots. Obtained data were analyzed in the context of four complex gradients – elevation, habitat dryness, slope inclination and slope convexity. CCA ordination, GAM and LOEES regression and nonparametric correlation were used as analyzing tools. We have found that species response surface/curves do not have symmetric shape but rather they show asymmetric and complex forms. Mode distribution of dominant tree and shrub species was random but that of herbs followed clumped pattern. When species mode distribution was divided into octaves, trees and shrubs showed lograndom distribution but all species together had lognormal one. Herbs alone do not conform to neither lognormal nor lograndom distributional patter. It seems that each species has its own response shape towards the environment, determined by its physiology, interaction with other species and historical events. It is hoped that the current study will add a little drop to the vast ocean of vegetation ecology knowledge helping with the clarification of the basic understanding of the vegetation pattern.