Sampling strategies for the assessment of tree species diversity

Authors

  • Clémentine Gimaret-Carpentier,

    Corresponding author
    1. Laboratoire de biométrie, génétique et biologie des populations, UMR 5558 CNRS, Université Claude Bernard Lyon1, 43 bd du 11 novembre 1918, F-69622 Villeurbanne Cedex, France; Fax 04 78 89 2719
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  • Raphaël Pélissier,

    1. Laboratoire de biométrie, génétique et biologie des populations, UMR 5558 CNRS, Université Claude Bernard Lyon1, 43 bd du 11 novembre 1918, F-69622 Villeurbanne Cedex, France; Fax 04 78 89 2719
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  • Jean-Pierre Pascal,

    1. Laboratoire de biométrie, génétique et biologie des populations, UMR 5558 CNRS, Université Claude Bernard Lyon1, 43 bd du 11 novembre 1918, F-69622 Villeurbanne Cedex, France; Fax 04 78 89 2719
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  • François Houllier

    1. Institut français de Pondichéry, PO Box 33, 11 St Louis Street, 605001 Pondicherry, India
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*Corresponding author; E-mail gimaret@biomserv.univ-lyon1.fr

Abstract

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.

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