This dataset describes habitat suitability for feral pig breeding and persistence in northern Australia during the wet season. It is the result of a spatially-explicit, resource-based and regional-scale habitat model that integrated expert knowledge on feral pig breeding requirements and home range movements as well as seasonal variability in environmental conditions.
The modelled habitat suitability index (HSI) can theoretically range between 0 and 100, with higher values indicating better habitat quality for feral pig breeding. Due to modelling methods and assumptions, HSI values in this dataset effectively range between 11 and 81. They can be broadly classified as follows: HSI ≥ 60 = highly suitable habitat; HSI ≥ 40 = moderately suitable habitat; HSI < 40 = unsuitable habitat.
Predicted habitat suitability should not be confused with actual feral pig occurrence. Individuals may be sighted at any time in unsuitable breeding habitat. Conversely, suitable breeding habitat may remain unoccupied. While there is a link between habitat suitability and population density, this may not always be straightforward (i.e. comparable habitat may carry vastly different actual or potential densities depending on the nature and quality of available resources).
Feral pig habitat suitability in northern Australia was modelled for two seasonal scenarios. The wet season scenario captured favourable conditions during the late wet season, when resources required by feral pigs are generally abundant and widely distributed across the region. It was developed using spatial proxies averaged across two months (March/April) over five years (2010 to 2014). Seasonal model results were validated against four independent distributional data sets.
Underlying model parameters were elicited from experts. This dataset represents results from an expert-averaged model run. The model contained a variable "Disturbance stress" for which no spatial proxies were available. In this dataset, we assumed a uniformly “high” intensity and frequency of control activities, which likely overestimated disturbance and may undervalue habitat suitability in situations where there is actually little management.
A detailed description of modelling methods and assumptions is provided in Froese et al. 2017 (https://doi.org/10.1371/journal.pone.0177018).