Sampling strategies for the assessment of tree species diversity

Gimaret Carpentier C., Pélissier Raphaël, Pascal Jean Pierre, Houllier François. 1998. Sampling strategies for the assessment of tree species diversity. Journal of Vegetation Science, 9 : pp. 161-172.

Journal article ; Article de revue à facteur d'impact
Full text not available from this repository.

Autre titre : Stratégies d'échantillonnage pour l'évaluation de la diversité des espèces ligneuses

Abstract : 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)

Mots-clés Agrovoc : Plante ligneuse, forêt tropicale, Échantillonnage, Biodiversité, Ressource forestière, Méthode statistique

Mots-clés géographiques Agrovoc : Inde, Malaisie

Classification Agris : F70 - Plant taxonomy and geography
U10 - Computer science, mathematics and statistics

Auteurs et affiliations

  • Gimaret Carpentier C.
  • Pélissier Raphaël
  • Pascal Jean Pierre
  • Houllier François, CIRAD-AMIS-AMAP (FRA)

Autres liens de la publication

Source : Cirad - Agritrop (

View Item (staff only) View Item (staff only)

[ Page générée et mise en cache le 2021-02-28 ]