Estimating parameters of neutral communities: From one single large to several small samples

The neutral theory of S. P. Hubbell postulates a two-scale hierarchical framework consisting of a metacommunity following the speciation¿drift equilibrium characterized by the ``biodiversity number¿¿ h, and local communities following the migration¿drift equilibrium characterized by the ``migration rate¿¿ m (or the ``fundamental dispersal number¿¿ I). While Etienne¿s sampling formula allows simultaneous estimation of h and m from a single sample of a local community, its applicability to a network of (rather small) samples is questionable. We define here an alternative two-stage approach estimating h from an adequate subset of the individuals sampled in the field (using Ewens¿ sampling formula) and m from community samples (using Etienne¿s sampling formula). We compare its results with the simultaneous estimation of h and m (one-stage estimation), for simulated neutral samples and for 50 1-ha plots of evergreen forest in South India. The one-stage approach exhibits problems of bias and of poor differentiability between high-h, low-m and low-h, high-m solution domains. Conversely, the two-stage approach yielded reasonable estimates and is to be preferred when several small, scattered plots are available instead of a single large one