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The relationship between species richness and aboveground biomass (richness–biomass relationship) is a major facet of ecosystem functions and has stimulated debates over the past decades. However, we still lack basic knowledge on whether this relationship has consistent patterns across natural and human-impacted vegetation cover types. More importantly, the effects of disturbance and climatic conditions on species richness and aboveground biomass remain controversial. Using data from 197 0.5-ha plots established within a forest-savanna transition ecosystem, we determined three ecological vegetation covers via non-metric multidimensional scaling, obtained gridded climate data and calculated disturbance index from species succession guilds. We examined the consistency of the richness–biomass relationship across the vegetation covers using general linear models and further analysed the effects of disturbance and climatic conditions on this relationship using non-mixed and mixed linear models. We identified three vegetation cover types corresponding to Old-growth forests, Cocoa agroforests and Woodland savannas, suggesting a succession gradient from late-, mid-, and early-successions, respectively. Aboveground biomass consistently increased with species richness across the three vegetation cover types (i.e. positive relationship). Species richness interacts with climate humidity to increase aboveground biomass while interaction of species richness and disturbance rather decreases aboveground biomass consistently across the vegetation cover types. Our results provide insights into the relationship between diversity and ecosystem functions, having implications for ecosystem restoration and understanding ecological consequences of disturbance and climate change in the forest-savanna ecosystem. • Relationship between species richness & AGB across vegetation covers was studied. • Effects of climate and disturbance on species richness and AGB was analysed. • Increase in AGB with species richness is consistent across vegetation cover types. • Interaction between species richness and climate mediates increase in AGB. • But interaction between species richness and disturbance mediates decrease in AGB. [ABSTRACT FROM AUTHOR]

Khaya (Meliaceae) is a widespread genus of trees distributed from the tropical forests of Africa to Madagascar and the Comoros. Khaya species are very close morphologically and some contain considerable phenotypic and ecological diversity, raising the question of their delimitation: this is the case of Khaya anthotheca s.l. (sensu lato, including K. nyasica), which is often lumped with K. grandifoliola and K. ivorensis. We tested species delimitation within K. anthotheca by combining population‐genetic and morphological data. First, a visual inspection of over a thousand specimens suggested the existence of five morphogroups. Second, after genotyping 498 samples at 71 nuclear SNPs, Bayesian clustering analyses (STRUCTURE) first identified five genetic clusters (K1–K5), while further analyses subdivided K5 into two clusters. The six genetic clusters obtained are distributed in parapatry or allopatry from West Africa to East Africa, except for cluster K4, which is in sympatry with K3 in Central Africa. The partitioning of genetic clusters is also largely congruent with the morphogroups identified. The morphological differentiation of these clusters was confirmed by statistical analyses of 27 leaf characters. The clear‐cut genetic differentiation between clusters, with few admixed genotypes even in contact zones, argues for the recognition of distinct species following the biological species concept. Our analyses highlight that the current taxonomic treatment of Khaya underestimates by one‐half the total number of species. We identify two new species, circumscribe K. anthotheca and support the rehabilitation at the rank of species of three taxa considered to be synonyms of K. anthotheca (K. agboensis, K. euryphylla, K. nyasica). These results illustrate the strength of combining population‐genetic and morphological data to delineate an African rainforest tree species complex. [ABSTRACT FROM AUTHOR]