Table 5. Comparison of five richness estimators based on 1,000 simulation data sets under a log-normal model with S = 1,000 and CV = 1.35.

See Table 1 for the notations of the estimators.

Size n (Observed richness)	Estimator	Average estimate	Bias	Sample s.e.	Average estimated s.e.	Sample RMSE	95% CI coverage rate
1,000 (481.1)	${\hat{S}}_{\mathrm{Chao1}}$	783.4	−216.6	51.6	50.6	222.7	0.07
	${\hat{S}}_{\mathrm{Jack1}}$	738.2	−261.8	23	23.5	262.8	0
	${\hat{S}}_{\mathrm{CB}}$	1,896	896	1,285.1	1,429.3	1,565.6	1
	${\hat{S}}_{\mathrm{LB}}$	982.8	−17.2a	192.2	187.6	192.8	0.85
	${\hat{S}}_{\mathrm{GP}}$	907.3	−92.7	99.1	96.9	135.7a	0.87a
2,000 (661.1)	${\hat{S}}_{\mathrm{Chao1}}$	874.5	−125.5	35.9	35.2	130.6	0.16
	${\hat{S}}_{\mathrm{Jack1}}$	913.9	−86.1	22.3	21.5	89	0.04
	${\hat{S}}_{\mathrm{CB}}$	1,067.3	67.3	80	79.5	104.4	0.96a
	${\hat{S}}_{\mathrm{LB}}$	991.4	−8.6a	114.6	109.4	114.8	0.9
	${\hat{S}}_{\mathrm{GP}}$	951.9	−48.1	66.6	66.1	82.2a	0.91
4,000 (818.2)	${\hat{S}}_{\mathrm{Chao1}}$	940.9	−59.1	24.4	23.1	64	0.44
	${\hat{S}}_{\mathrm{Jack1}}$	1,011.1	11.1	19	17.6	22a	0.89
	${\hat{S}}_{\mathrm{CB}}$	973.7	−26.3	26.5	26.5	37.3	0.77
	${\hat{S}}_{\mathrm{LB}}$	995.1	−4.9a	62.1	61.1	62.3	0.89
	${\hat{S}}_{\mathrm{GP}}$	979.4	−20.6	41.7	41.2	46.5	0.92a
8,000 (923.1)	${\hat{S}}_{\mathrm{Chao1}}$	978.9	−21.1	14.2	14	25.4	0.77
	${\hat{S}}_{\mathrm{Jack1}}$	1,034.2	34.2	13.4	12.8	36.7	0.22
	${\hat{S}}_{\mathrm{CB}}$	976.9	−23.1	12	12.1	26	0.49
	${\hat{S}}_{\mathrm{LB}}$	1,000.9	0.9a	32.8	33.2	32.8	0.91
	${\hat{S}}_{\mathrm{GP}}$	995.2	−4.8	22.7	23.2	23.2a	0.94a

Notes.

^adenotes the smallest bias, smallest RMSE, and figure closest to 95% coverage.