Genetic diversity and structure in wild Robusta coffee (Coffea canephora A. Froehner) populations in Yangambi (DR Congo) and their relation to forest disturbance

Degradation and regeneration of tropical forests can strongly affect gene flow in understorey species, resulting in genetic erosion and changes in genetic structure. Yet, these processes remain poorly studied in tropical Africa. Coffea canephora is an economically important species, found in the understorey of tropical rainforests of Central and West Africa, and the genetic diversity harboured in its wild populations is vital for sustainable coffee production worldwide. Here, we aimed to quantify genetic diversity, genetic structure, and pedigree relations in wild C. canephora populations, and we investigated associations between these descriptors and forest disturbance and regeneration. Therefore, we sampled 256 C. canephora individuals within 24 plots across three forest categories in Yangambi (DR Congo), and used genotyping-by-sequencing to identify 18,894 SNPs. Overall, we found high genetic diversity, and no evidence of genetic erosion in C. canephora in disturbed old-growth forest, as compared to undisturbed old-growth forest. In addition, an overall heterozygosity excess was found in all populations, which was expected for a self-incompatible species. Genetic structure was mainly a result of isolation-by-distance, reflecting geographical location, with low to moderate relatedness at finer scales. Populations in regrowth forest had lower allelic richness than populations in old-growth forest and were characterised by a lower inter-individual relatedness and a lack of isolation-by-distance, suggesting that they originated from different neighbouring populations and were subject to founder effects. Wild Robusta coffee populations in the study area still harbour high levels of genetic diversity, yet careful monitoring of their response to ongoing forest degradation remains required.

The ECAT dataset: expert-validated distribution data of endemic and sub-endemic trees of Central Africa (Dem. Rep. Congo, Rwanda, Burundi)

In this data paper, we present a specimen-based occurrence dataset compiled in the framework of the Conservation of Endemic Central African Trees (ECAT) project with the aim of producing global conservation assessments for the IUCN Red List. The project targets all tree species endemic or sub-endemic to the Central African region comprising the Democratic Republic of the Congo (DR Congo), Rwanda, and Burundi. The dataset contains 6361 plant collection records with occurrences of 8910 specimens from 337 taxa belonging to 153 genera in 52 families. Many of these tree taxa have restricted geographic ranges and are only known from a small number of herbarium specimens. As assessments for such taxa can be compromised by inadequate data, we transcribed and geo-referenced specimen label information to obtain a more accurate and complete locality dataset. All specimen data were manually cleaned and verified by botanical experts, resulting in improved data quality and consistency.