Variation in soil organic carbon stock with forest type in tropical forests of Kanyakumari Wildlife Sanctuary, Western Ghats, India.

Abstract

Sequestration of atmospheric carbon-dioxide in biospheric carbon (C) pools is a key strategy towards climate change mitigation. Soil is a huge C reservoir and its storage potential varies greatly with forest types. Therefore, in the present study, the soil organic carbon (SOC) storage pattern was assessed from 70 plots laid at three selected forest types comprising seven study sites at Kanyakumari Wildlife Sanctuary, Western Ghats, India: tropical dry deciduous (TDD I and TDD II), tropical semi-evergreen (TSE I and TSE II) and tropical evergreen forest (TEF I, TEF II and TEF III) at three depths (0-10, 10.1-20 and 20.1-30 cm). Statistical analyses were performed to understand the relationships between SOC stocks with other predictor variables. The SOC stock varied markedly with forest type and site-wise. The SOC ranged from 58 (TEF III) to 123.6 (TDD I) Mg C/ha with a mean of 84.9 ± 4.4 Mg C/ha at 0-30 cm depth. SOC stock decreased, while soil bulk density increased with increase in soil depth. The TDD forest type (115.6 Mg C/ha) stocked the highest SOC compared to TEF (75.1 Mg C/ha) and TSE (68.9 Mg C/ha) forest types. Of the total SOC stock (0-30 cm), 44.2, 32.0 and 23.8% were stored in 0-10, 10.1-20 and 20.1-30 cm respectively in all the forest types. In contrast, litter C stock were high in TEF and TSE forest types and low in TDD forest type. SOC showed significant (P < 0.01) negative relationships with bulk density, litter C, and vegetation attributes. The SOC stock stored in the study sites amount to 212.9 (TEF III) to 453.6 (TDD I) Mg of CO2 equivalents. The present study reveals that forest type and site characteristics have a profound impact on SOC stock, which would, in turn, exert a great bearing on the ecosystem C cycling. These results would also enhance our ability to evaluate the role of these forest types in soil C sequestration and for developing and validating SOC models for tropical forest ecosystems.