Predicting the number of newly discovered rare species in an as-yet-unsurveyed sample

Abstract

In natural ecological communities, most species are rare and thus very likely to become extinct. As a consequence, the prediction and identification of rare species are of enormous value for conservation purposes. The main research question of interest is: how many newly found species will be rare in the next field survey? By using biodiversity information in an ecological sample, we developed an accurate estimator for estimating the number of new rare species (e.g., singletons, doubletons, and tripletons) that will be found in an as-yet-unsurveyed sample. A semi-numerical study showed that the proposed Bayesian-weight estimator accurately predicted the number of rare new species with low relative bias and relative root mean squared error and accordingly, high accuracy. Additionally, in this talk, I will employ some conservation-directed empirical applications to demonstrate the predicting power of the proposed method.