Trees, Forests and People (Dec 2021)

Spatial prediction of plant species richness and density in high-altitude forests of Indian west Himalaya

  • Balwant Rawat,
  • Kailash S. Gaira,
  • Sanjay Gairola,
  • Lalit Mohan Tewari,
  • Ranbeer S. Rawal

Journal volume & issue
Vol. 6
p. 100132

Abstract

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The spatial distributions of plant species are results of variable environmental gradients, including climatic and edaphic factors, biotic factors, different eco-physiological processes, species-specific characteristics, and resource requirements, thus producing spatial heterogeneity. The species distribution and their rate of change across elevational gradients in nineteen forest communities were studied using the quadrat method and statistical modeling tools. Pindari-Sunderdhunga-Kafni (PSK) area of the Kumaun region and the Lata-Tolma-Phagti (LTP) area in the Garhwal region in the buffer zone of Nanda Devi Biosphere Reserve were selected as the extensive study sites. A total of 4278 individual trees belonging to 42 families in the PSK site and 6436 individual trees belonging to 25 families in the LTP site were recorded across elevational gradients between 2050 to 3800 m a.s.l. Because of the narrow elevational range and complexity in the field-based data structure, Generalized Additive Model (GAM) was used to predict the rate of change of species richness and species density. The results showed a significant decrease in density at a rate of 319–355 ind ha-1 per 100 m elevation in the Pindari-Sunderdhunga-Kafni site (P < 0.01) while increasing patterns (53–56 ind ha-1 per 100 m elevation) in the Lata-Tolma-Phagti site (p < 0.01) was recorded. The decreasing trend for species richness was observed in Lata-Tolma-Phagti site significantly (p< 0.02) across elevation. This study, for the first time in the Indian Himalayan region, underlines the rate of change in species richness (per 1000 m elevation) and density (per 100 m elevation) across elevational gradients. The overall vegetation response may perhaps be considered as an influence of boundary constraint associated with different environmental factors; however, more datasets of vegetation dynamics and responses are required to further strengthen this premise.

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