Smallholder Coffee in the Global Economy—A Framework to Explore Transformation Alternatives of Traditional Agroforestry for Greater Economic, Ecological, and Livelihood Viability

Abstract

Sixty percent of global coffee is produced from farms of <5 ha. Studies show that returns from such farms do not generate a living income for producers or workers threatening supplies. Smallholders use agroforestry to reduce coffee production costs, diversify income and address livelihood needs. We undertook a three-phase analysis to test the following hypothesis. Current coffee agroforestry must shift from a low labor, low risk-stable return, slowly-changing matrix to more active management of species and stem turnover in system renovation cycles targeted to sustaining, reorienting and intensifying ecosystem-based benefits to coffee production, diversified income and household food. First, we conducted a document survey of current traditional tree diversity, research trends, and market drivers for more benefits-oriented agroforestry. Second, we proposed a framework for multiple benefits quantification converting tree use characteristics and density into five categories of benefits, each with sub-categories which we tested using previously collected data of stem density by species from coffee agroforestry in northern Nicaragua. Third, we modeled radiation in mixed canopy scenarios using the program SExI- FS based on modifications of species and density to target food and income diversification and tested our framework by quantifying benefits. We found that smallholder coffee faces farms decreasing coffee margins, labor scarcity, new pests and climate variability best addressed with targeted and adaptive shifts in coffee varieties and associated trees. Increasing data demands from certification and regulations provide a basis more data-driven coffee farm management. Our data bases of stem density by species of established agroforestry systems were sufficient to identify gaps in food and income benefits which were addressed in the scenarios thereby verifying the hypothesis. The benefits ranking both of current systems and three scenarios also provided insights into data collection specifications for a more rigorous academic test of the hypothesis and data-driven grower strategies for agroforestry transformation.