An Approach to Estimate Probability of Presence and Richness of Fish Species

Absence of a species when it is not observed from a given area is ensured only when the probability of observation, when present, is 1. This condition is rarely satisfied in surveys of animals in natural environments, particularly with elusive targets such as fish. Detectability (probability of species encounter) is a function of probability of individual capture, which varies widely with sampling method, fish size, physical habitat, and number of individuals present in a given area. An empirical Bayesian approach was developed for estimating probability of presence for zero-catch samples, in which the number of individuals present for a species is predicted from independent samples and used as an empirical prior. The model was illustrated for 16 species of fish sampled in 121 blocked-off stream reaches in which samples were collected using one of five primary gear methods; treatment with an ichthyocide followed. All species present were caught by the primary gear in only 17 (14%) of the samples. Of the empirical Bayesian predictions of presence or absence from zero-catch samples, 69% were correct. Of these zero-catch samples, 20% of samples in which a species was present and 93% of samples in which a species was absent were correctly predicted. The mean species richness was 10.3, compared with 7.4 for species richness from catch data of (mean bias of −27.4%). The model predicted a mean of 9.6 species (mean bias of −3.3%). Sampling design and subsequent analysis should account for catchability and fish densities (predicted as functions of physical habitat variables) and area sampled in order to reliably estimate probability of presence by species and, subsequently, species richness.