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.