• BiodivR;
  • central Africa;
  • diversity patterns;
  • effective number of species;
  • herbarium collections;
  • rarefaction principles;
  • similarity index;
  • subsampling procedure


We compiled herbarium specimen data to provide an improved characterization of geographic patterns of diversity using indices of species diversity and floristic similarity based on rarefaction principles. A dataset of 3650 georeferenced plant specimens belonging to Orchidaceae and Rubiaceae endemic to Atlantic Central Africa was assembled to assess species composition per half-degree or one-degree grid cells. Local diversity was measured by the expected number of species (Sk) per grid cell found in subsamples of increasing size and compared with raw species richness (SR). A nearly unbiased estimator of the effective number of species per grid cell was also used, allowing quantification of ratios of ‘true diversity’ between grid cells. Species turnover was measured using a presence/absence-based similarity index (Sørensen) and an abundance-based index that corrects for sampling bias (NNESS). Our results confirm that the coastal region of Cameroon is more diverse in endemic species than those more inland. The southern part of this coastal forest is, however, as diverse as the more intensively inventoried northern part, and should also be recognized as an important center of endemism. A strong congruence between Sørensen and NNESS similarity matrices lead to similar delimitations of floristic units. Hence, heterogeneous sampling seems to confer more bias when measuring patterns of local diversity using raw species richness than species turnover using Sørensen index. Overall, we argue that subsampling methods represent a useful way to assess diversity gradients using herbarium specimens while correcting for heterogeneous sampling effort.

Abstract in French is available in the online version of this article.