Work

Projecting trends of arabica coffee yield under climate change: A process-based modelling study at continental scale

Year: 2025

Type: article

Abstract: CONTEXTClimate change may lead to negative impacts on coffee production, such as reduced yields. Addressing this issue requires identifying climate risks and assessing the adaptation potential of agronomic practices across spatial and environmental gradients.OBJECTIVEThis study aimed to assess the impact of climate change on arabica coffee yields at continental scale and evaluate a specific adaptation measure, i.e. increasing shade tree density in agroforestry settings, by simulating the physiological links between coffee growth, climatic factors and agronomic management.METHODSAfter evaluating the performance of the process-based model DynACof in simulating arabica yields (using data from previuos studies), we developed a new tool called G-DynACof, a modelling framework for spatializing DynACof on a regional scale using extensive climate projections and soil geodata. We used G-DynACof to simulate trends of potential coffee yields in Latin America and Africa using an ensemble of downscaled and biased-corrected climate projections for the period 2036-2065 compared to an historical period 1985-2014.RESULTS AND CONCLUSIONSDespite considerable uncertainties due to the scarcity of information on agronomic management at the regional scale, our results indicate that crop yields are likely to decrease between 23% and 35% in Latin America and between 16% and 21% in Africa, depending on the Shared Socioeconomic Pathway (SSP) considered (SSP1-2.6 and SSP5-8.5, respectively). Yield variations were very eterogeneous in space, with yields increasing at high altitudes and low latitudes, indicating a possible future shift of production areas. In our simulations, the effect of increasing the density of shade trees was very eterogeneous in space and its potential for adaptation to climate change remained unclear, requiring further investigation.SIGNIFICANCEImpact analyses and adaptation modelling of coffee agrosystems, together with socio-economic indicators, can delineate realistic, comprehensive, integrated risk assessments and support effective adaptation recommendations.

Source: Agricultural Systems

DOI: 10.1016/j.agsy.2025.104353

Authors: Raniero Della Peruta, Valentina Mereu, Donatella Spano, Serena Marras, Rémi Vezy, Antonio Trabucco