Land Use Effect on Soil Organic Carbon Stocks, Microbial Biomass and Basal Respiration in Bundelkhand Region of Central India

• Published in: Agricultural research (India : Online) 2022-09, Vol.11 (3), p.454-464
• Main Authors: Singh, Nongmaithem Raju, Kumar, Dhiraj, Handa, A. K., Newaj, Ram, Prasad, Mahendra, Kamini, Kumar, Naresh, Ram, Asha, Dev, Inder, Bhatt, B. P., Chaturvedi, O. P., Arunachalam, A., Singh, L. Netajit
• Format: Article
• Language: English
• Subjects: Acacia nilotica; Agricultural land; Agricultural research; Agroforestry; Biodiversity; Biomass; Biomedical and Life Sciences; Carbon; Cell Biology; Full-Length Research Article; Land use; Life Sciences; Microorganisms; Organic carbon; Organic soils; Plant Biochemistry; Plant Ecology; Plant Genetics and Genomics; Plant Sciences; Plantations; Principal components analysis; Respiration; Soil depth; Soil quality; Soils
• ISSN: 2249-720X; 2249-7218
• DOI: 10.1007/s40003-021-00584-6

A field experiment was conducted at Indian Council of Agricultural Research (ICAR), Central Agroforestry Research India, Jhansi (U.P.), India, to assess the effect of land use on soil organic carbon stocks (SOCs), microbial biomass carbon (MBC) and basal respiration by selecting sixteen land uses including one cropland system. The results revealed that agroforestry system (AFS) performed better as compared to other land use systems. Acacia nilotica -based AFS has the highest SOCs (23.39 Mg ha −1 ), followed by Dalbergia sissoo -based AFS in 0–15 cm soil depth. Among the pure tree plantation, Jatropha curcas observed highest SOCs (15.78 Mg ha −1 ) in 0–15 cm soil depth. However, silvopasture system is able to build up (20.88 Mg ha −1 ) more SOCs than pure tree plantation systems. Soil MBC was also recorded significantly higher under Acacia nilotica -based AFS (764.61 µg g −1 ) in 0–15 cm depth, while the basal respiration was highest under silvopasture system irrespective of SOCs and MBC. Overall, our study results indicated that the SOC in the different land use systems is not only influenced by difference in age and density of tree but also largely controlled by different management practices adopted. The principal component analysis (PCA) data have shown that two major components (PC1 and PC2) have represented 70.90% of the total variation. And among the parameters, BR followed by soil organic carbon (SOC) was found to be the most sensitive factor while assessing the impact of land use changes on soil quality. We also found that SOCs, microbial biomass carbon and basal respiration have a strong correlation between each other.