An assessment of sample-based estimators of tree species richness in two wet tropical forest compartments in Panama and India

Abstract

International audienceWe assessed the performance of ten incidence-based estimators of tree species richness in simulated simple random sampling with fixed-area plots. Stem diameter-limited tree species and location data came from two species-rich wet tropical forest compartments in Panama and India. Lower limits of stem diameter were 1 cm and 30 cm, respectively. Estimators varied widely in their estimates of richness and their rankings changed frequently across sites and sample designs. A gamma-Poisson estimator was overall best according to a performance score of three accuracy statistics and sample size. However, until corroborated by further studies, Chao's 1981 non-parametric estimator is recommended for forest inventories with fixed-area plots

Estimation of tree species richness from large area forest inventory data: Evaluation and comparison of jackknife estimators

“…They focused on the bias, precision and accuracy of the seven jackknife estimators (Brose et al, 2003). Magnussen et al (2006) evaluated the generalized jackknife estimator, which is a linear combination of conventional jackknife estimators (Sharot, 1976). Chao (1987) found that the jackknife estimators were severely negatively biased for small sample sizes but performed better with increasing sample size.…”

“…Only few, though, have focused on evaluation and application of the estimators to tree species from forest inventories (Chazdon et al, 1998;Condit et al, 1996;Hellmann and Fowler, 1999;Magnussen et al, 2006;Palmer, 1990Palmer, , 1991Schreuder et al, 1999). www.elsevier.com/locate/foreco Walther and Moore (2005) gathered an extensive list of additional studies and summarized them by the species richness estimators.…”

“…The data sets used for research into plant species richness estimation come almost exclusively from ecological census plots (Condit et al, 1996;Magnussen et al, 2006). They generally show characteristics of relatively limited geographical coverage and small sample size.…”

A modified bootstrap procedure for cluster sampling variance estimation of species richness

“…Specifically, we estimate the sampling variance of six estimators of richness, among which the second-order jackknife [28,60] and two estimators by Chao have enjoyed some popularity in studies of forest tree species richness [23,27,35,37,38,49,56,57].…”

Estimating change in species richness from repeated sampling of incidence data

“…For the purpose of estimating forest tree species richness -at a given point in time -from species incidence data obtained from a probability-sample with fixed-area forest survey plots (quadrats), the analyst now has a choice of estimators with anticipated good performances provided the sample size is adequate (Magnussen & Boudewyn, 2008;Magnussen, Péllisier, He, & Ramesh, 2006;Magnussen, Smith, Kleinn, & Sun, 2010). The situation is different when it comes to estimation of change in richness since studies on the performance of estimators of temporal change in species richness have been lacking.…”