Introductory Chapter: Plant Ecology

Yousaf, Zubaida; Ramazan, Habiba

doi:10.5772/intechopen.69926

Cited by 1 publication

(1 citation statement)

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“…Knowledge of how the nature and structure of temperate ecosystems vary across different places is crucial to set regional management and conservation targets. Phytosociology depicts the distribution of species in a given geographical area to better understand community structure (Yousaf 2017) and the nature of vegetation types.…”

Section: Introductionmentioning

confidence: 99%

Tree species composition, stand structure and distribution patterns across three Kashmir Himalayan forests, India

Dar

Parthasarathy

2022

Écoscience

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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 m2. 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.

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Section: Introductionmentioning

confidence: 99%