Development and characterization of nuclear microsatellite markers for the African walnut Coula edulis Baill (Coulaceae).

PREMISE OF THE STUDY: Coula edulis Baill (Coulaceae) is a common tree species in the Guineo-Congolian forests producing an edible fruit known as African walnut, which is an important food and income resource for rural populations. However, the species suffers from a deficit of natural regeneration. We developed here nuclear microsatellite markers for C. edulis to be able to study the genetic structure of its natural populations and gene flow. METHODS AND RESULTS: A genomic library was obtained using the Illumina platform, and 21 polymorphic microsatellite loci were developed. The polymorphic microsatellites displayed eight to 22 alleles per locus (average: 14.2), with a mean expected heterozygosity ranging from 0.33 to 0.72 in five populations from Central and West Africa. CONCLUSIONS: The high polymorphism of the nuclear microsatellite markers developed makes them useful to investigate gene flow and the organization of genetic diversity in C. edulis, and to assess whether particular genetic resources require conservation efforts.

A map of African humid tropical forest aboveground biomass derived from management inventories.

Forest biomass is key in Earth carbon cycle and climate system, and thus under intense scrutiny in the context of international climate change mitigation initiatives (e.g. REDD+). In tropical forests, the spatial distribution of aboveground biomass (AGB) remains, however, highly uncertain. There is increasing recognition that progress is strongly limited by the lack of field observations over large and remote areas. Here, we introduce the Congo basin Forests AGB (CoFor-AGB) dataset that contains AGB estimations and associated uncertainty for 59,857 1-km pixels aggregated from nearly 100,000 ha of in situ forest management inventories for the 2000 - early 2010s period in five central African countries. A comprehensive error propagation scheme suggests that the uncertainty on AGB estimations derived from c. 0.5-ha inventory plots (8.6-15.0%) is only moderately higher than the error obtained from scientific sampling plots (8.3%). CoFor-AGB provides the first large scale view of forest AGB spatial variation from field data in central Africa, the second largest continuous tropical forest domain of the world.