TY - JOUR

T1 - The utility of farmer ranking of tree attributes for selecting companion trees in coffee production systems

AU - Dumont, Emilie Smith

AU - Gassner, Anja

AU - Agaba, Genevieve

AU - Nansamba, Ruth

AU - Sinclair, Fergus

PY - 2019/8

Y1 - 2019/8

N2 - There is increasing interest in the potential of agroforestry to improve the productivity and sustainability of coffee production, but designing management options is knowledge intensive. Tree-crop interactions and the biophysical and socio-economic factors influencing farmers’ decision-making about companion trees are complex and context-specific but fine scale data relating to them are rarely available. A novel method was used to analyse trees ranked by farmers for a range of attributes and evaluate the consistency of farmers’ knowledge underpinning decisions about tree management in coffee production systems in Rwanda. Farmers’ knowledge about tree planting was changing, in line with new shade management recommendations being promoted alongside a limited number of tree species, often freely distributed through eco-certification initiatives. Farmers had detailed knowledge about soil and water conservation processes associated with trees, but they traded these off against perceived competition for light, water and nutrients with coffee. The competitiveness of trees with coffee was influenced by combinations of attributes related to: crown architecture, foliage properties and growth patterns; as well as how trees responded to management, and, their utility. Farmers consistently ranked 20 tree species for 12 attributes (five related to ecology, four to management and three to utility). Given the paucity of data on tree attributes for many species, systematically acquired and consistent local knowledge complements global scientific information and can be useful in bridging knowledge gaps relating to the integration of tree diversity in coffee production systems, which is an increasingly important strategy for smallholder farmers adapting to climate change.

AB - There is increasing interest in the potential of agroforestry to improve the productivity and sustainability of coffee production, but designing management options is knowledge intensive. Tree-crop interactions and the biophysical and socio-economic factors influencing farmers’ decision-making about companion trees are complex and context-specific but fine scale data relating to them are rarely available. A novel method was used to analyse trees ranked by farmers for a range of attributes and evaluate the consistency of farmers’ knowledge underpinning decisions about tree management in coffee production systems in Rwanda. Farmers’ knowledge about tree planting was changing, in line with new shade management recommendations being promoted alongside a limited number of tree species, often freely distributed through eco-certification initiatives. Farmers had detailed knowledge about soil and water conservation processes associated with trees, but they traded these off against perceived competition for light, water and nutrients with coffee. The competitiveness of trees with coffee was influenced by combinations of attributes related to: crown architecture, foliage properties and growth patterns; as well as how trees responded to management, and, their utility. Farmers consistently ranked 20 tree species for 12 attributes (five related to ecology, four to management and three to utility). Given the paucity of data on tree attributes for many species, systematically acquired and consistent local knowledge complements global scientific information and can be useful in bridging knowledge gaps relating to the integration of tree diversity in coffee production systems, which is an increasingly important strategy for smallholder farmers adapting to climate change.

KW - Rwanda

KW - Local knowledge

KW - Agroforestry

KW - Ecosystem services

KW - Shade

U2 - 10.1007/s10457-018-0257-z

DO - 10.1007/s10457-018-0257-z

M3 - Article

VL - 93

SP - 1469

EP - 1483

JO - Agroforestry Systems

JF - Agroforestry Systems

SN - 0167-4366

IS - 4

ER -