Models of tree-level hollow incidence in Victorian State forests

This paper details predictive models of tree-level hollow incidence for State forests in central and eastern Victoria. Models are based on the hollows component of the Statewide Forest Resource Inventory (SFRI), the most comprehensive database of hollow incidence in Australia. A two-stage methodology was used at the individual tree-level that in its first-stage generated a statement of the probability of hollows presence, and in its second-stage estimated the size of hollows. The hierarchical nature of SFRI data prompted the search for statistical methodology capable of explicitly modelling a complicated error structure. Subsequently, generalised linear mixed models (GLMMs) were used to estimate first-stage, tree-level models in the presence of spatial and nested dependence. The developed models were statistically and biologically plausible and performed well when validated using independent data. By overcoming the limitations facing previous research associated with insufficient data and inappropriate statistical methodology viable predictive models were developed. Tree-level models will help us understand patterns of hollow incidence, can be used for predictive purposes when individual-tree information is available, and can improve habitat tree retention guidelines.