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Farmers' preferred tree species and their potential carbon stocks in southern Burkina Faso: Implications for biocarbon initiatives.

Kangbéni Dimobe | Jérôme Ebagnerin Tondoh | John C Weber | Jules Bayala | Korotimi Ouédraogo | Karen Greenough
PloS one | 2018

The success of terrestrial carbon sequestration projects for rural development in sub-Saharan Africa lies in the (i) involvement of local populations in the selection of woody species, which represent the biological assets they use to meet their daily needs, and (ii) information about the potential of these species to store carbon. Although the latter is a key prerequisite, there is very little information available. To help fill this gap, the present study was undertaken in four pilot villages (Kou, Dao, Vrassan and Cassou) in Ziro Province, south-central Burkina Faso. The objective was to determine carbon storage potential for top-priority woody species preferred by local smallholders. We used (i) participatory rural appraisal consisting of group discussions and key informant interviews to identify priority species and functions, and (ii) landscape assessment of carbon stocks in the preferred woody species. Results revealed 79 priority tree and shrub species grouped into six functions, of which medicine, food and income emerge as the most important ones for the communities. For these functions, smallholders overwhelmingly listed Vitellaria paradoxa, Parkia biglobosa, Afzelia africana, Adansonia digitata, Detarium microcarpum, and Lannea microcarpa among the most important tree species. Among the preferred woody species in Cassou and Kou, the highest quantity of carbon was stored by V. paradoxa (1180 ±209 kg C ha-1 to 2089±522 kg C ha-1) and the lowest by Grewia bicolor (5±1.2 kg C ha-1). The potential carbon stored by the preferred tree communities was estimated at 587.9 Mg C ha-1 (95% CI: 456.7; 719.1 Mg C ha-1) in Kou and256.8 Mg C ha-1 (95% CI: 67.6; 324.4 Mg C ha-1) in Cassou. The study showed that the species that farmers preferred most stored more carbon than species that were less preferred.

Pubmed ID: 30562359

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Software R package for multivariate analysis which takes into account different types of data structure. Data can be organized in groups of variable, groups of individuals, or into hierarchy of variables.

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