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Assessing non-parametric estimators of species richness. A case study with birds in green areas of the city of Puebla, Mexico Our objective was to evaluate the performance of non-parametric estimators of spe-cies richness with real data. During the 2003 breeding season, bird communities were sampled in two green areas in the city of Puebla (Mexico), and the corresponding sample-based rarefaction curves were obtained. Mean data were adjusted to two non-asymptotic and seven asymptotic accumulation functions, and the best model was selected by means of reliability criteria in information theory. The cumulative Weibull and the beta-P functions were the best-fit models. Bias, precision and accuracy of five non-parametric estimators of species richness (ICE, Chao2, Jackknife 1, Jackknife 2, and Bootstrap) were then assessed for increasing sampling efforts (1-53 sampling units) against the asymptote of the selected accumulation functions. All the non-parametric estimators here evaluated underestimated true richness most of the time, specially in one of the sites. However, after combining data from the two assemblages, only ICE, and Jackknife 1 and 2 exhibited bias below 10% with different sampling efforts, and only Jackknife 1 was globally accurate (scaled mean squared error x 100 < 5%, even with low sampling efforts, ca. 20% of the total). Therefore, we propose using the Jackknife 1 non-parametric estimator as a lower limit to measure bird species richness in urban sites similar to those in the present study.