Ecology, Environment and Conservation Paper

Vol 24, Issue 4 2018; Page No.(1877-1886)

SOIL CO2 FLUX AND TEMPERATURE SENSITIVITY (Q10) IN NATURAL AND HUMAN IMPACTED ECOSYSTEMS OF SENAPATI DISTRICT, MANIPUR, INDIA

Ng Niiroua and Asha Gupta

Abstract

The present study was carried out to study the seasonal variation of soil CO2 flux and Q10 values for natural and human impacted ecosystem of Senapati district of Manipur. The natural Undisturbed mixed Oak Forest (UOF) which was dominated by Quercus serrata and co-dominated by Lyonia ovalifolia, Disturbed mixed oak forest (DOF) dominated by Quercusserrata and co-dominated by Quercusgriffithii, Pinuskesiya Plantation Forest (PPF) and Orchard Plantation Forest (OPF) dominated by Mangifera indica and co-dominated by Prunus domestica with their corresponding GPS coordinates located between 25° 12.067’ N to 25° 12.145’ N and 93° 59.915’E to 94°02.296’ E and at the elevation of 1146-1254 m msl. Soil temperature ranged from 12.87 ! to 23.78 C and soil moisture 29.09 % to 43.39%. Soil temperature is the most important factor controlling the soil respiration followed by soil moisture content. The highest-within the site variability of soil CO2 flux was obtained in the rainy season (August) and low respiration rate was computed in the winter (Jan, Feb) in all the land uses systems. An exponential equation best described the relationships between soil CO2 flux and soil temperature (r2 between 0.82 to 0.96) and between soils CO2 flux and soil moisture (r2 between 0.44 to 0.67). In the present study the Q10 values varied from 1.82 to 1.91. The Q10 values are in the order of DOF>OPF>UOF>PPF. The higher Q10 value in the DOF and OPF indicates that it might release more CO2 than the UOF and PPF. PPF and UOF show least temperature sensitivity under the present scenario of climate change and global warming suggesting the intact form of land use types. Careful analysis of these Q10 values may advance our understanding on the different environmental controls of Q10 of soil respiration and also improve our ability to predict the releasing potential of soil CO2 emission by different land use systems in present climate changing scenario.

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