Tree species composition, stand structure and distribution patterns across three Kashmir Himalayan forests, India. Issue 4 (2nd October 2022)

• Record Type: Journal Article
• Authors: Dar, Ashaq Ahmad; Parthasarathy, Narayanaswamy
• Is Part Of: Ecoscience. Volume 29:Issue 4(2022)
• Page Start: 311
• Page End: 324
• Publication Date: 2022-10-02
• Subjects: Coniferous forests -- canonical correspondence analysis (CCA) -- environmental drivers -- forest structure -- species distribution -- topography; Forêt coniférienne -- analyse canonique des correspondances -- facteurs environmentaux -- structure forestière -- répartition de espèces -- topographie; Ecology -- Periodicals; 577
• DOI: 10.1080/11956860.2022.2048534
• Languages: English
• ISSNs: 1195-6860

Abstract

ABSTRACT: Himalayan ecosystems provide a unique opportunity to analyze the determinants of species richness across large elevation gradients. Understanding forest diversity and structure is fundamental to set conservation priorities. A quantitative assessment of tree species was conducted in Kashmir Himalayan forests to ascertain their composition, stand structure and distribution in 143 plots of 50 × 50 m 2 . Altogether, 13 species were recorded, ranging from five in subalpine (SA) forests to 10 in mixed conifer (MC) forests. There was a compositional dissimilarity among forest types. Pinus wallichiana was the most important species in low-level blue pine (BP) forests, whereas Abies pindrow prevailed in mid-elevation MC and high-elevation SA forests. Pinaceae contributed around 98% of stems and was the most speciose family, followed by Sapindaceae and Betulaceae. Stand density and basal area differed among forest types and were significantly correlated with elevation and slope. The tree diameter class distribution displayed an approximate reverse J-shaped pattern indicating the influence of disturbance. As the first two axes of the canonical correspondence analysis explained more than 93% of the inertia in the species-environment relation, elevation and slope are the main drivers of species distribution. Information about these forest attributes could provide better ecological insights for sustainable forest management.