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A hierarchical zero‐inflated Poisson regression model for stream fish distribution and abundance
Author(s) -
Boone E.L.,
StewartKoster B.,
Kennard M.J.
Publication year - 2012
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.1145
Subject(s) - poisson regression , abundance (ecology) , poisson distribution , fish <actinopterygii> , regression , econometrics , zero inflated model , multilevel model , statistics , computer science , mathematics , ecology , fishery , biology , population , demography , sociology
Ecologists are frequently confronted with the challenge of accurately modelling species abundance. However, this task requires one to deal with both presence/absence as well as abundance. Traditional Poisson regression models are not adequate when attempting to deal with both issues simultaneously. Zero‐inflated regression models have been proposed to deal with this problem with much success. We extend these models to incorporate both a multilevel hierarchical structure and spatial correlation. The model is illustrated using a dataset concerning the Hypseleotris galii (Fire‐tailed Gudgeon), a native species to eastern Australia. Copyright © 2011 John Wiley & Sons, Ltd.