Evaluating organic carbon fractions, temperature sensitivity and artificial neural network modeling of CO2 efflux in soils: Impact of land use change in subtropical India (Meghalaya). (October 2018)

• Record Type: Journal Article
• Authors: Thangavel, Ramesh; Kanchikerimath, Manjaiah; Sudharsanam, Abinandan; Ayyanadar, Arunachalam; Karunanithi, Rajasekar; Deshmukh, Nishant Anandrao; Vanao, Ngachan Shishom
• Is Part Of: Ecological indicators. Volume 93(2018)
• Page Start: 129
• Page End: 141
• Publication Date: 2018-10
• Subjects: Carbon management index -- Carbon fractions -- Land use -- Soil CO2 efflux -- Temperature sensitivity -- Artificial neural network; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2018.04.077
• Languages: English
• ISSNs: 1470-160X

Abstract

Graphical abstract: Highlights: Land conversion from fallow to orchards increases soil organic carbon stocks, fractions and CO2 efflux. Labile carbon fractions are more sensitive to land use changes than other fractions. Fruit orchards are the promising strategy for enhancing C sequestration in degraded ecosystems. Land use change increases the sensitivity of soil CO2 efflux to the temperature. The experimental CO2 efflux values had good agreement with the predicted values in ANN. Abstract: The present study investigates the changes in land use pattern from fallow land (control) to fruit orchards on soil organic carbon (SOC) dynamics especially, organic carbon stocks, fractions, and CO2 efflux. The SOC fractions such as total organic carbon (TOC), particulate organic carbon (POC), readily oxidizable carbon (ROC), non-labile carbon (CNL ), microbial biomass carbon (MBC), carbon management index (CMI) and their sensitivity to land use change were the focus of this study. The organic carbon fractions showed increasing trend (19.4–46%) under fruit orchards compared to control. Furthermore, the orchard with P. persica recorded the highest mean SOC stocks (59.4 Mg ha −1 ) and TOC (3.03 g 100 g −1 ) while orchard with C. reticulata showed the highest ROC (6.11 g kg −1 ) and MBC (401 mg kg −1 ). Fruit orchards were characterized by high Cmic:CTOC (microbial quotient; qMIC) and POC: TOC ratios, indicating an increase in substrate availability. Furthermore, the CMI was highest under C. reticulata (226.4) followed by P. guajava (173.3), whereas P. communis showed relatively lower value (160.5). While, upper soil layer (0–15 cm) exhibited higher organic carbon stock and fractions viz., 35.1 % and 58.3%, respectively compared to the subsurface soil (15–75 cm) in all orchards. The labile SOC fractions (POC, ROC, and MBC) showed a positively significant correlation with TOC and CO2 efflux indicating that these labile fractions are the sensitive indicators of soil quality changes and improvements. Soil CO2 efflux exhibited a pronounced variation corresponding to land use change with values ranging from 22.80 µg C g −1 h −1 (fallow land) to 27.39 µg C g −1 h −1 ( P. guajava ). With temperature increment from 25 to 35 °C, the soil CO2 efflux increased from 55% ( P. persica ) to 88% (fallow) with an average increase of 72%. However, the microbial metabolic quotient (qCO2 ), also called as specific respiratory activity (SRA), was relatively lower (40.9 µg CO2 mg MBC −1 ) in orchards compared to fallow land (50.4 µg CO2 mg MBC −1 ). A multi-layered Artificial Neural Network model (ANN) was also developed, and the experimental CO2 efflux values obtained from different land uses are in good agreement with the predicted CO2 efflux. We conclude that, labile SOC fractions are highly sensitive to land use change and could be effectively used as the sensitive indicators along with CMI for land use change under mid-altitude subtropical ecosystems. In addition, fruit orchards could store more carbon thus could be a potential option to mitigate global warming.