Selection of shade tree species for agroforestry systems must take the complexity of these systems into account. Tree species selection should maximize the provision of ecosystem services while minimizing disservices. Selected species must be adapted to local agroecological conditions and cater to farmers' needs, while considering their preferences and constraints. The ShadeTreeAdvice methodology was developed to support said selection process using farmers' local ecological knowledge. It provides the steps to rapidly identify tree species and evaluate their impacts on a range of locally important ecosystem services. Results are uploaded to a decision support tool to tailor tree species recommendations to individual farmers' needs (www.shadetreeadvice.org). During the 5 year timeframe between 2016 and 2020, eight studies following this methodology were conducted in various coffee and cocoa growing regions across Africa, Asia and Central America. This article looks back at these studies to synthesize their findings and evaluate the methodology. We identified similarities in the use of tree species across different study areas, notably regarding leguminous and fruit tree species. We showed that the method was efficient to evaluate tree species' impacts on soil and climate regulation, crop production, and economic benefits. It was less efficient for evaluating impacts related to incidence of pests and diseases, often associated with knowledge gaps. The method also successfully allowed investigating the links between LEK and socio-economic groups or environmental factors. Furthermore, we suggest a series of improvements in the methodology for future studies. These improvements include (i) broadening the scope of studies beyond tree species provision of ecosystem services to include tree species impact on farming practices; (ii) allowing the comparison of tree performances in agroforestry systems versus in full sun; (iii) providing a clear pathway for validation of the results; (iv) using tree species' functional traits to generalize the results.
DOI:
https://doi.org/10.1002/pan3.10374Score Altmetric:
Dimensions Nombre de citations:
Année de publication
2022
Auteurs
Rigal, C.; Wagner, S.; Nguyen, M. P.; Jassogne, L.; Vaast, P.
Langue
English
Mots clés
tree species, agroforestry systems, methodology, farming systems, indigenous knowledge, ecosystem services
Géographique
Ghana, Uganda, China, Tanzania, Nicaragua, Viet Nam, Lao People's Democratic Republic
