Agroforestry systems (AFS) and practices followed in India are highly diverse due to varied climatic conditions ranging from temperate to humid tropics. The estimated area under AFS in India is 13.75 million ha with the highest concentration being in the states of Uttar Pradesh (1.86 million ha), followed by Maharashtra (1.61 million ha), Rajasthan (1.55 million ha) and Andhra Pradesh (1.17 million ha). There are many forms of agroforestry practice in India ranging from intensified simple systems of monoculture, such as block plantations and boundary planting, to far more diverse and complex systems, such as home gardens. As a result, the biomass production and carbon sequestration potential of AFS are highly variable across different agro-climatic zones of India. Studies pertaining to the assessment of biomass and carbon storage in different agroforestry systems in the Indian sub-continent are scanty and most of these studies have reported region and system specific carbon stocks. However, while biomass and carbon stock data from different AFS at national scale has been scanty hitherto, such information is essential for national accounting, reporting of C sinks and sources, as well as for realizing the benefits of carbon credit to farmers engaged in tree-based production activities. Therefore, the objective of this study was to collate and synthesize the existing information on biomass carbon and SOC stocks associated with agroforestry practices across agro-climatic zones of India. The results revealed considerable variation in biomass and carbon stocks among AFS, as well as between different agro-climatic zones. Higher total biomass (>200 Mg ha⁻¹) was observed in the humid tropics of India which are prevalent in southern and northeastern regions, while lower total biomass (<50 Mg ha⁻¹) was reported from Indo-Gangetic, western and central India. Total biomass carbon varied in the range of 1.84 to 131 Mg ha⁻¹ in the agrihorticulture systems of western and central India and the coffee agroforests of southern peninsular India. Similarly, soil organic carbon (SOC) ranged between 12.26–170.43 Mg ha⁻¹, with the highest SOC in the coffee agroforests of southern India and the lowest in the agrisilviculture systems of western India. The AFS which recorded relatively higher SOC included plantation crop-based practices of southern, eastern and northeastern India, followed by the agrihorticulture and agrisilviculture systems of the northern Himalayas. The meta-analysis indicated that the growth and nature of different agroforestry tree species is the key factor affecting the carbon storage capacity of an agroforestry system. The baseline data obtained across various regions could be useful for devising policies on carbon trading or financing for agroforestry.

Land degradation has a substantial influence on food security, health, and socioeconomic development, highlighting the critical role that land plays as a resource necessary for maintaining life. As a result, agroforestry interventions become essential tactics for resource preservation and improving sustainable production. Many agroforestry techniques, including agri-horticulture, silvipasture, and agri-silviculture systems, have been developed over the course of substantial study in a variety of agroclimatic zones with the goal of reducing land degradation. The United Nations Convention to Combat Desertification has acknowledged these strategies as essential to reaching land degradation neutrality. The benefits of agroforestry techniques for reducing soil erosion and runoff, increasing soil fertility, and enhancing carbon sequestration are explained in this chapter. It is crucial to promote these affordable and sustainable technologies to guarantee their widespread adoption. As a result, putting in place agroforestry systems is essential for healing impacted regions and addressing issues with livelihoods, environmental sustainability, and food security. In order to make sure that stakeholders receive the proper incentives, national policy programs should incorporate the valuation of the advantages of soil protection. Furthermore, future research endeavors should prioritize the development of economically viable agroforestry systems designed to restore degraded lands, enhance water efficiency, and minimize competition between trees and crops.

Long term carbon sequestration in soil had been advocated in almost all the international forum to minimize the global warming. However, the extent of carbon storage in soil will depend on the type of vegetation it supports. The study examined different land use potentiality in sequestering carbon in soil on the basis of extent of tree component. In addition it was also investigated that how soil carbon is related with other physical and chemical parameters of the soil in different land uses. Farmers will adopt a particular land use system only if it fits in his socio-economic frame work. Hence, bioeconomics of different land uses were also calculated and compared. Extent of tree in the land use affected the physical and chemical properties of soil. The pH of the soil decreased from 6.09 to 5.09 and bulk density from 1.55 to 1.21 g/cm3 as the tree component increased. Available soil nitrogen increased from 97 to 143 kg/ha and organic carbon from 0.39 to 1.77 per cent. Out of the four soil depths surface soil had less pH, bulk density and moisture, however soil nitrogen and organic carbon was higher. Physical characters of the soil were found to be more related with organic carbon in land uses which are devoid of trees or when their number was less. However, as the tree component increases both physical and chemical component needs to be taken simultaneously to get better estimate of carbon. Agroforestry systems (agrihorticulture) seems to be better land use practices as they fulfill the needs of the farmers and can also earn carbon-credits thus increasing their income by 21 per cent.Â

To assess the impact of bamboo plantations on soil organic carbon (SOC) under prevailing climatic conditions, increase in temperature and soil amendments, the Roth C model was used. RothC is a promising model for the estimation of SOC changes in different land use systems. In the present study, the RothC model was used to predict the dynamics of SOC in the plantation of seven bamboo species under a usual scenario: increase temperature by 1 °C and 2 °C and farm yard manure (FYM) addition. The result revealed that RothC fairly predicts the SOC. The root mean square error (RMSE) value varied from 0.74 to 3.2 among seven bamboo species while comparing modeled and measured data. The increase in temperature resulted in a decrease in SOC. The decrease in SOC varied from 0.46 to 5.96 per cent as compared to the usual scenario, and the extent of the decrease varied from species to species. Among all species, the application of 9 t ha⁻¹ FYM was found appropriate for maintaining the initial SOC level during the initial stage of bamboo growth.

Fractal branching model is a non-destructive tool for biomass estimation. In the present paper we compared estimates of above ground tree biomass of Terminalia chebula and Emblica officinalis using usual method of biomass estimates and by employing Fractal Branching Analysis (FBA) model. Allometric equations were developed through FBA for above ground biomass of Terminalia chebula (B=0.1296D ^2.0827), branch biomass (B=0.0103D ^2.5388) and leaves+twig biomass (B=0.0529D ^1.3269). Similarly, equations were developed for Embilica officinalis for above ground biomass B=0.0655 D ^2.4042), branch biomass (B=0.0007 D ^3.35108) and for leaves+twig (B=0.0656 D ^1.621) (where B is Biomass and D is diameter of tree at breast height). While comparing the biomass estimate of both the methods using different descriptive statistics it was found that biomass equations developed through FBA model can fairly estimate the biomass as Maximum Error (ME) values ranged from 0.1 to 0.385 in Terminalia and from 0.068 to 0.289 in Embilica. The Coefficient of Residual Mass (CRM) values for both the species were also less than and near to one signifying good prediction by the FBA model. The experiment also showed that the method is fairly accurate and estimation for large number of trees, with different diameters, can be generated through the model thus saving precious time and resources.