A hierarchical zero-inflated Poisson regression model for stream fish distribution and abundance
Author(s)
Boone, EL
Stewart-Koster, B
Kennard, MJ
Year published
2012
Metadata
Show full item recordAbstract
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.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.
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Journal Title
Environmetrics
Volume
23
Issue
3
Subject
Mathematical sciences
Environmental sciences
Freshwater ecology