Sampling strategies for the assessment of tree species diversity

This paper aims at proposing efficient vegetation sampling strategies. It describes how the estimation of species richness and diversity of moist evergreen forest is affected by (1) sampling design (simple random sampling, random cluster sampling, systematic cluster sampling, stratified cluster sampling), (2) choice of species richness estimators (number of observed species vs. non-parametric estimators) and (3) choice of diversity index (Simpson vs. Shannon). Two sites are studied : a 28-ha area situated in the Western Ghats of India and a 25-ha area located at Pasoh in Peninsular Malaysia. The results show that : (1) whatever the sampling strategy, estimates of species richness depend on sample size in these very diverse forest ecosystems which contain many rare species; (2) Simpson's diversity index reaches a stable value at low sample sizes while Shannon's index is affected more by the addition of rare species with increasing sample size; (3) cluster sampling strategies provide a good compromise between cost and statistical efficiency; (4) 300 - 400 sample trees grouped in small clusters (10-50 individuals) are enough to obtain unbiased and precise estimates of Simpson's index; (5) the local topography of the Western Ghats has a major influence on forest composition, the steep slopes being richer and more diverse than the ridges and gentle slopes : (6) stratified cluster sampling is thus an interesting alternative to systematic cluster sampling. (Résumé d'auteur

Tree diversity in western Kenya: using profiles to characterise richness and evenness

Species diversity is a function of the number of species and the evenness in the abundance of the component species. We calculated diversity and evenness profiles, which allowed comparing the diversity and evenness of communities. We applied the methodology to investigate differences in diversity among the main functions of trees on western Kenyan farms. Many use-groups (all trees and species that provide a specific use) could not be ranked in diversity or evenness. No use-group had perfectly even distributions. Evenness could especially be enhanced for construction materials, fruit, ornamental, firewood, timber and medicine, which included some of the most species-rich groups of the investigated landscape. When considering only the evenness in the distribution of the dominant species, timber, medicine, fruit and beverage ranked lowest (> 60% of trees belonged to the dominant species of these groups). These are also use-groups that are mainly grown by farmers to provide cash through sales. Since not all communities can be ranked in diversity, studies that attempt to order communities in diversity should not base the ordering on a single index, or even a combination of several indices, but use techniques developed for diversity ordering such as the Renyi diversity profile. The rarefaction of diversity profiles described in this article could be used in studies that compare results from surveys with different sample sizes