Quantification of the Land Potential for Scaling Agroforestry in South Asia

Abstract

Trees are an integral part of the sustainable farming practices that can withstand extreme weather events, pest risks, and optimize land and water productivity to achieve food, fuel, fodder and nutritional security while safeguarding the environmental flows. This study was undertaken to analyze the landscape potential for the South Asian region in the geospatial domain utilizing the FAO’s land suitability criteria. The key datasets were derived from satellite remote sensing at a global and regional scale for land, soil, climate, and topography and were used to model the agroforestry suitability across South Asia. Furthermore, the agroforestry suitability categories and tree cover dominance were investigated with respect to the total geographical area, agriculture land cover and with climate variables to understand the present and future trends. The comprehensive analysis revealed that 69% of the total geographical area retains 55% and greater suitability for agroforestry. The analysis revealed that nearly 73.4% of the landscape is absent (0%) of tree cover, 7.1%, shows 1–10% and 19.5% area having more than 10% tree cover. The tree dominance/hotspot analyses in the agriculture land were found notably high in the multiple farming components such as home gardens. The single crop of irrigated and rain-fed croplands showed high land suitability towards agroforestry. Such land can be utilized to enhance the tree cover that suits locally as per the farmer’s need based on a community-driven participatory approach to bring the sustainability and resilience in degraded landscapes (FAO in Agroforestry for landscape restoration, 2017). The future climate data analysis showed a significant change in the distribution of temperature and precipitation that will influence future farming practices in South Asia. The agroforestry suitability and tree cover mapping results/analysis will assist crucially the agroforestry policymakers/planners in the various South Asian countries to implement and extend it to the new area. The analysis clearly shows that the advent of big data, remote sensing and GIS provide insights into the agroforestry interventions and scaling which further helps in building resilient landscapes for sustainable agri-food systems, livelihoods, safeguarding the environmental security and supporting some of the important sustainable development goals (SDGs).