ESTIMATING SPECIES OCCURRENCE, ABUNDANCE, AND DETECTION PROBABILITY USING ZERO‐INFLATED DISTRIBUTIONS

Publisher: John Wiley & Sons Inc

E-ISSN: 1939-9170|89|10|2953-2959

ISSN: 0012-9658

Source: Ecology, Vol.89, Iss.10, 2008-10, pp. : 2953-2959

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Researchers have developed methods to account for imperfect detection of species with either occupancy (presence–absence) or count data using replicated sampling. We show how these approaches can be combined to simultaneously estimate occurrence, abundance, and detection probability by specifying a zero‐inflated distribution for abundance. This approach may be particularly appropriate when patterns of occurrence and abundance arise from distinct processes operating at differing spatial or temporal scales. We apply the model to two data sets: (1) previously published data for a species of duck, Anas platyrhynchos, and (2) data for a stream fish species, Etheostoma scotti. We show that in these cases, an incomplete‐detection zero‐inflated modeling approach yields a superior fit to the data than other models. We propose that zero‐inflated abundance models accounting for incomplete detection be considered when replicate count data are available.