Spatial modelling to estimate the risk of feral pigs to pig farm biosecurity in south-eastern Australia
J. G. Froese A B D , J. V. Murray B , J. J. Perry C and R. D. van Klinken BA The University of Queensland, St Lucia, QLD 4072.
B Commonwealth Scientific and Industrial Research Organization (CSIRO), Dutton Park, QLD 4102.
C CSIRO, Douglas, QLD 4811.
D Corresponding author. Email: jens.froese@uq.net.au
Animal Production Science 55(12) 1456-1456 https://doi.org/10.1071/ANv55n12Ab117
Published: 11 November 2015
Freedom from many high priority diseases is a key competitive advantage for the Australian pork industry (Brookes et al. 2014). Despite a strict quarantine system, exotic diseases may be introduced and establish in wild or feral animal populations. Pearson (2012) showed that some production-limiting pathogens are already endemic to feral pigs around piggeries in Australia. Pearson (2012) also found that the risk of pathogen transmission from feral pigs coming into contact with domestic herds is low but not negligible. This scoping study aimed to investigate whether spatial modelling can help to identify ‘farm biosecurity hotspots’, where the risk of exposure by domestic pig herds to diseases carried by surrounding feral pig populations is greatest.
The study area, south-eastern Australia, contains almost 90% of the national domestic pig herd (ABS 2015). Relative risk of exposure was defined as the proportion of land within estimated risk zones around piggeries that coincided with suitable feral pig habitat. Habitat suitability was modelled using a participatory approach adapted from Murray et al. (2014) that combined expert knowledge, probabilistic modelling and spatial analysis. The model was calibrated for southern Queensland and extended to the broader study area. As suitability was influenced by the variable availability of key resources such as water, food and cover, seasonal (summer or winter) and climatic (above or below average rainfall periods) scenarios were analysed in this study. Only highly suitable habitat (probability > 0.5) was considered. Location data (partly based on post code) was obtained for 1,908 commercial piggeries. Following Pearson (2012), a circular zone within 0–100 m around piggeries was considered high risk and within 100–500 m moderate risk of exposure.
Results were aggregated by state to show broad spatial trends in both habitat suitability and risk of exposure. The model predicted on average that 32.9% of the study area was suitable feral pig habitat. However, this varied by scenario and state from 6.4% under drought conditions in NSW to 81% during wet periods in Victoria. Consequently, relative risk of exposure to feral pigs also differed considerably across scenarios and states (Table 1). Risk was highest during the winter growing season in Victoria (>94%) and lowest during arid summer conditions in NSW (<13%). Averaged across all states and scenarios, the proportion of high and moderate risk zones coinciding with feral pig habitat was 46.4% and 47.1% respectively. The results from this scoping study indicated that across the study area many piggeries are located in the vicinity of highly suitable feral pig habitat, particularly when abundant resources allow feral pigs to extend their range. To confidently assess risk of exposure at the property level, modelling would benefit from more comprehensive piggery location data as well as information on farm types, existing biosecurity measures and disease prevalence in feral pigs. Results of the habitat suitability model also need to be validated in the farming systems of Victoria.
References
ABS (2015) Agricultural commodities, Australia, 2013-14. Australian Bureau of Statistics Cat. no. 7121.0. (ABS: Canberra)Brookes VJ, Hernández-Jover M, Cowled B, Holyoake PK, Ward MP (2014) Preventive Veterinary Medicine 113, 103–117.
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Murray JV, Berman DM, van Klinken RD (2014) Biological Invasions 16, 2403–2425.
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Pearson HE (2012) ‘Understanding and mitigating the risk of pathogen transmission from wild animals to domestic pigs in Australia.’ PhD thesis, The University of Sydney, Australia.
This project was funded in part by Australian Pork Limited. Expert elicitation supported by Queensland Murray-Darling Committee. Piggery location data provided by Eric Neumann, Epi-Insight Ltd.