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ESTIMATING SPECIES OCCURRENCE, ABUNDANCE, AND DETECTION PROBABILITY USING ZERO‐INFLATED DISTRIBUTIONS
Author(s) -
Wenger Seth J.,
Freeman Mary C.
Publication year - 2008
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1890/07-1127.1
Subject(s) - abundance (ecology) , replicate , occupancy , sampling (signal processing) , relative abundance distribution , relative species abundance , ecology , statistics , biology , computer science , mathematics , filter (signal processing) , computer vision
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.