Comparative performance of species richness estimation methods

Abstract

In most real-world contexts the sampling effort needed to attain an accurate estimate of total species richness is excessive. Therefore, methods to estimate total species richness from incomplete collections need to be developed and tested. Using real and computer-simulated parasite data sets, the performances of 9 species richness estimation methods were compared. For all data sets, each estimation method was used to calculate the projected species richness at increasing levels of sampling effort. The performance of each method was evaluated by calculating the bias and precision of its estimates against the known total species richness. Performance was evaluated with increasing sampling effort and across different model communities. For the real data sets, the Chao2 and first-order jackknife estimators performed best. For the simulated data sets, the first-order jackknife estimator performed best at low sampling effort but, with increasing sampling effort, the bootstrap estimator outperformed all other estimators. Estimator performance increased with increasing species richness, aggregation level of individuals among samples and overall population size. Overall, the Chao2 and the first-order jackknife estimation methods performed best and should be used to control for the confounding effects of sampling effort in studies of parasite species richness. Potential uses of and practical problems with species richness estimation methods are discussed.

Host correlates of diversification in avian lice

“…Their reliability has been tested and compared under controlled conditions (Walther & Morand, 1998).…”

Assessment of richness estimation methods on macroinvertebrate communities of mountain ponds in Castilla y León (Spain)

“…The real debate is about choosing the best estimator for a particular study, taxonomical group or data set. This is a controversial issue, still under study, because different authors reach different conclusions on which is the best estimator, as shown by contrasting results obtained in their studies by, for example, Colwell and Coddington (1994); Walther and Morand (1998); Chiarucci et al (2003); Foggo et al (2003) and Hortal et al (2006). Therefore, until more conclusive information is available, checking the suitability of several estimators seems a convenient starting point when studying little known communities.…”

“…They are all standard, widely used methods that have been previously tested and discussed by a number of authors under different circumstances (e.g. Palmer, 1990;Colwell and Coddington, 1994;Coddington et al, 1996;Condit et al, 1996;Carlton and Robison, 1998;Chazdon et al, 1998;Walther and Morand, 1998;Gotelli and Colwell, 2001;Walther and Martin, 2001;Petersen and Meier, 2003).…”

“…The performance of several of these estimators have been carried out and compared in a number of studies (Chazdon et al, 1998;Keating et al, 1998;Peterson and Slade, 1998;Walther and Morand, 1998;Chiarucci et al, 2001;Walther and Martin, 2001;Brose, 2002;Longino et al, 2002;Borges and Brown, 2003;Chiarucci et al, 2003;Melo et al, 2003;Brose and Martinez, 2004; see review in Walther and Moore, 2005). However, in freshwaters their use has mostly been restricted to stream invertebrates (Melo and Froehlich, 2001) and lake zooplankton (Dumont and Segers, 1996;Arnott et al, 1998).…”

Sample-based Estimation of Regional Forest Tree Species Richness

“…Estimators of species richness may differ in sensitivity to the sampling design due to differential reliance on the number and relative incidence of species observed in a sample (Haas & Stokes, 1998;Mao & Lindsay, 2007;Walther & Morand, 1998); thus the four estimators can only provide an example of how the sample design and choice of sampling unit can affect estimators of richness. On the other hand, their appeal to forest tree species richness estimation will increase if they also demonstrate insensitivity to the design for sample collection (EQ, STR, SRS) and choice of sampling unit (CLU, T1).…”