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Abstrato

Carbon Stock Assessment in the Vegetation of the Chitteri Reserve Forest of the Eastern Ghats in India Based on Non-Destructive Method Using Tree Inventory Data

Pragasan LA

Carbon stock assessment in the vegetation of forest ecosystems has attracted worldwide attention following their role in the mitigation of greenhouse gas and climate change. The aim of the present study was to assess the total carbon stock of trees in the Chitteri reserve forest of the Eastern Ghats in India, based on tree inventory. The entire stretch of the forest covering 742 km2 area was divided into twenty grids of 6.25 km × 6.25 km, and from each grid a transect of size 5 m × 1000 m was established. A total of 5022 live trees (≥ 9.5 cm diameter at breast height) representing 143 species were inventoried from the twenty transects (totaling 10 ha). Carbon stock of each tree was determined by a non-destructive method following standard allometric equation using the tree diameter. The total carbon stock of the tree vegetation for the 10 ha sampled in the Chitteri reserve forest was 585.50 tonnes. The average carbon stock for the twenty 0.5 ha transect was 29.28±21.7 tonne. The minimum and maximum carbon stock estimated for the 20 transects was 1.98 t/0.5 ha and 76.89 t/0.5 ha, respectively. The average carbon stock sequestered by a single tree was 0.12±0.24 t/tree. The maximum carbon value was observed for Mangifera indica (1.73 t/tree) and the minimum was for Glycosmis pentaphylla (0.01 t/tree). However, overall contribution to the total carbon stock of tree vegetation in the Chitteri reserve forest was observed greater for Memecylon edule (8.5 %), followed by Canthium dicoccum var. dicoccum (7.4 %), Anogeissus latifolia (6.4 %), Albizia amara (4.9 %) and Mangifera indica (4.4 %). A significant strong positive relationship was observed between carbon stock with tree density (R2=0.689), but not with tree diversity (R2=0.422) and with altitude (R2=0.399) of forest location.

Isenção de responsabilidade: Este resumo foi traduzido usando ferramentas de inteligência artificial e ainda não foi revisado ou verificado.