Community associations and ecological drivers of understory vegetation across temperate forests of Kashmir Himalayas, India
2022
Ashaq Ahmad Dar | Narayanaswamy Parthasarathy
We assessed the understory vegetation types in temperate Kashmir Himalayan coniferous forests, their species composition and what function ecological drivers execute in shaping compositional trends using a multivariate statistical approach. The agglomerative clustering analysis depicted eight discrete plant associations in terms of herb species composition with simple underlying indicator species and ecological drivers. At one extreme, we found alpine and subalpine areas (Tanacetum multicaule Sch.Bip. – Aconitum heterophyllum Wall. ex Royle – Lomatogonium caeruleum (Royle) Harry Sm. ex B.L. Burtt community (TAL)) occupying high elevations (2961.88±205.56 m) with notable species richness (6.04), while lower (2459.36±94.07 m) areas are inhabited by Thalictrum minus L. – Galium aparine L. – Achillea millefolium L. (TGA) community. The Poa pratensis L.– Senecio chrysanthemoides DC. – Clinopodium umbrosum (M.Bieb.) Kuntze (PSC) community was most diverse, supported higher species diversity (Shannon=2.22±0.07; Simpson=0.84±0.01; Fisher's α=4.51±0.30) and also exhibited a maximum number of trails crossing the plot. Canonical Correspondence analysis (CCA) examined the species-ecological interactions and displayed a significant role of most studied environmental variables in the species distribution patterns. The latter in the decreasing significance order comprised precipitation (F = 2.3; p = 0.001), latitude (F = 2.15; p = 0.001), grazing (F = 1.56; p = 0.01), longitude (F = 1.63; p = 0.013), slope (F = 1.33; p = 0.07), elevation (F = 1.32; p = 0.07), aspect (F = 0.1; p = 0.47), trails (F = 0.78; p = 0.85) and mean monthly minimum temperature (F = 1.23; p = 0.172). The variance partitioning used to evaluate the comparative significance of topographic, climatic and disturbance factors on understory vegetation composition depicted that topography (14.26%) strongly partitioned the vegetation distribution subsequently followed by climatic (11.52%) and disturbance (4.49%) factors.
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