Question: Could we better estimate plot species richness by asking several botanists to survey the same plots and using non-parametric estimators of richness? Location: Two French deciduous forests. Methods: Using replicated, independent censuses made by 11 professional botanists on the same eight 100-m² forest plots, I investigate the relative performance of different richness estimators (Lincoln-Petersen, Jackknife 1&2, Chao 1&2, Bootstrap, Chao Mth, Darroch) and the variation of their performance with the number of botanists (teams with two to eight botanists). I also assess the sensitivity of these estimators to the presence of misidentifications in the data Results: When misidentifications are removed, Chao Mth estimators converged the fastest to true richness but none of the tested estimators correctly accounted for differences in exhaustiveness between teams. Finally, all estimators were highly sensitive to misidentifications. Conclusions: Richness estimators are of little help in presence of misidentifications and they are ineffective at removing between-team discrepancies, strongly limiting their usefulness in practice. I present how surveys can be designed to remove misidentifications and limit between-team discrepancies. Assuming an adequate sampling design, a sensible sampling design for 100m² plots in temperate forests, would be using triplets of botanists and correcting data with the Chao N1. Pairs of botanists would already significantly improve the richness estimates but these estimates would be still biased low. Nonetheless, further research is needed to design new richness estimators more robust to observer effects.