Coffee production, particularly in shade-grown farms, plays a crucial role in the livelihoods of Mexican farmers. Shade-grown coffee systems are also recognised for supporting biodiversity and enhancing carbon capture. Nevertheless, the geographical heterogeneity of Mexico makes the selection of tree species in these agroforestry systems challenging. This study develops region-specific priority lists to conserve biodiversity, improve carbon capture, and support the livelihoods of producers across nine coffee-growing regions within the state of Chiapas. We identified the tree species distributed in each region using an extensive dataset from the Global Biodiversity Information Facility and a novel approach that enhanced spatial resolution of the prioritisation process, despite biases in collection efforts. A set of 23 criteria, including conservation status, carbon content, and documented uses by local communities, was compiled from databases and literature reviews and used to calculate a priority score for each species. Based on these scores, a list of 20 recommended species was generated for each region. However, additional participatory validation is needed to translate these lists into practice. A similarity analysis revealed that geographically proximate regions shared similar species composition. Overall, this study provides a transparent framework for regionally tailored shade-tree selection to inform conservation and restoration planning in coffee agroforestry landscapes.
Prioritisation of Native Tree Species for Biodiversity Conservation, Carbon Capture, and Livelihoods Improvement in Shade-Grown Coffee Regions of Chiapas, Mexico
Gianella, Maraeva;Ulian, Tiziana
2026-01-01
Abstract
Coffee production, particularly in shade-grown farms, plays a crucial role in the livelihoods of Mexican farmers. Shade-grown coffee systems are also recognised for supporting biodiversity and enhancing carbon capture. Nevertheless, the geographical heterogeneity of Mexico makes the selection of tree species in these agroforestry systems challenging. This study develops region-specific priority lists to conserve biodiversity, improve carbon capture, and support the livelihoods of producers across nine coffee-growing regions within the state of Chiapas. We identified the tree species distributed in each region using an extensive dataset from the Global Biodiversity Information Facility and a novel approach that enhanced spatial resolution of the prioritisation process, despite biases in collection efforts. A set of 23 criteria, including conservation status, carbon content, and documented uses by local communities, was compiled from databases and literature reviews and used to calculate a priority score for each species. Based on these scores, a list of 20 recommended species was generated for each region. However, additional participatory validation is needed to translate these lists into practice. A similarity analysis revealed that geographically proximate regions shared similar species composition. Overall, this study provides a transparent framework for regionally tailored shade-tree selection to inform conservation and restoration planning in coffee agroforestry landscapes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



