Soil organic carbon fractionation, carbon index, and microbial activity under different agroforestry systems in North Eastern Himalayas, India.

The potential of soil organic carbon fractions for agroforestry systems (AFSs) is not well understood. Five distinct AFSs were tested for its impact on soil organic carbon fractionation, carbon index, and microbial activity in North Eastern Himalayas, India. The mean labile carbon (LC) ranged from 4.55 to 5.43 kg soil across the land use systems. Napier system observed the lowest very labile carbon (VLC) 12.36 kg soil in 60-75-cm depth. The mean non labile carbon (NLC) ranged from 15.67 to 16.83 g kg soil across the land use. Highest less labile carbon (LLC) was observed in agri-horti-silviculture (AHS) followed by agri-silvi-horticulture (ASH) land use system. The black gram + mandarin + Alnus nepalensis land use recorded higher lability index (1.66) followed by maize + Schima wallichii (1.65) in 0-15-cm depth. Among the different land use systems, carbon pool index increased in all the depths over buckwheat + mandarin. The mean carbon management index (CMI) value ranged from 167.02 to 210.12 among the land use system. The mean CMI was highest in black gram + mandarin + Alnus nepalensis (210.12) followed by soybean + Ficus hookerii + guava (191.56), maize + Schima wallichii (281.71), and lowest in buckwheat + mandarin (167.02). Among the AFSs, black gram + mandarin + Alnus nepalensis showed greater amount of carbon pool index, lability index, and carbon management index and, hence, considered the best sustainable agroforestry system to sequester more carbon in the Sikkim Himalaya. Such system also retained more different organic carbon fractions. The mean CMI value ranged from 167.02 to 210.12 among AFSs. Acid phosphatase activity was more during the rainy season followed by winter and summer season. Similar trends were followed by the urease activity in all the three seasons. Overall conclusion from this investigation is that SOC fractions, carbon index, and microbial activity levels are strongly influenced by the prevailing agroforestry systems.