Joining the incompatible: exploiting purposive lists for the sample-based estimation of species richness

The lists of species obtained by purposive sampling by eld ecol- ogists can be used to improve the sample-based estimation of species richness. A new estimator is here proposed as a modication of the dierence estimator in which the species inclusion probabilities are estimated by means of the species frequencies from incidence data. If the species list used to support the estimation is complete the estimator guesses the true richness without error. In the case of in- complete lists, the estimator provides values invariably greater than the number of species detected by the combination of sample-based and purposive surveys. An asymptotically conservative estimator of the mean squared error is also provided. A simulation study based on two articial communities is carried out in order to check the ob- vious increase in accuracy and precision with respect to the widely applied estimators based on the sole sample information. Finally, the proposed estimator is adopted to estimate species richness in the Maremma Regional Park, Italy.