Jumping the barrier: Does a glacier tongue affect species distribution along the elevation gradient in the subnival and nival belts? A case study on Mt. Kazbegi, Georgia, Central Great Caucasus Mountains

Abstract

Glaciers are a prominent feature in high mountains and can affect plant distribution along the gradients. However, the possible effect of glaciers on plant community structure at landscape scale has been little studied. We asked: if a glacier tongue crosses a slope laterally and potentially blocks dispersal and migrations, how can this affect vegetation structure and species composition below and above this barrier? A suitable study system is offered by slopes on Mt. Kazbegi, where we established a transect through the subnival and nival belts. We sampled vegetation below and above the glacier tongue and conducted direct gradient analyses to reveal possible effects of the glacier on patterns of species distribution and vegetation structure such as the ratio of solitary plants in vegetation patches. The obtained results indicate that the glacier tongue in our study does not cause a ?vegetation switch? in the usual sense of this phrase. However, it might contribute to an abrupt change in the share of solitary plants, as well as to a very rapid decline of plant abundance and species numbers above the glacier.

Gradient analysis of soil-plant interactions from the alpine-nival ecotone to the snowline on slopes of the Central Great Caucasus (Kazbegi Region, Georgia)

“…), slope angle (inclination), slope aspect, soil pH, plant available N, P, K, AMMT, SOM (%), vegetation projective cover (%) and plant community data (plant species and their frequency of occurrence). In our previous work we found that vegetation cover was reducing exponentially with increasing elevation (Kikvidze et al, 2020), and for statistical analyses we logtransformed cover data assuming a linear dependence of log-transformed cover on elevation. We used correlation analysis and multivariate ordination methods such as non-Metric Multidimensional Scaling (NMDS; Legendre, Gallagher, 2001), Principal Component Analysis (PCA; Mason, Gunst, 1985), and Canonical Correspondence Analysis (CCA; Palmer, 1993).…”