The vulnerability of the Australian beef industry to impacts of the cattle tick (Boophilus microplus) under climate change

Abstract

An integrated assessment is presented of the potential impacts of the cattle tick (Boophilus microplus Canestrini) on the Australian beefindustry under climate change. The project was carried out as a case study to test an impact assessment approach that was designed to integrate biological, production and socio-economic impacts on managed and natural systems. A climate-driven, tick population model was run for European, zebu and crossbred cattle breeds having different levels of resistance to cattle ticks. A geographical information system (GIS) was used to organise spatial data on climate scenarios and industry statistics and to undertake regional analyses.A comparison was made of the two available approaches to conducting impact assessments, namely a bottom-up approach using sensitivity analysis and a top-down approach using climate change scenarios from a global circulation model (GCM) (CSIRO, 1996). The output, in terms of the abundance of tick populations and reductions in cattle productivity for each breed showed significant expansions in potential geographical impacts. In the absence of any adaptation measures, the results indicated changes in the losses in live weight gain of cattle tick ranging from 7780 tonnes per year by 2030 to 21637 tonnes per year by 2100, in comparison with estimates for current losses of 6594 tonnes per year.The principal adaptation options available to the beef industry are to switch to breeds that are more resistant to cattle ticks, or to increase the frequency of treatments with various tick control products. In this paper we focus on switching breeds as an adaptive measure when appropriate damage thresholds are triggered under the climate change scenarios. When adaptation measures were put in place, the losses ranged from 4962 tonnes in 2030 to 5619 tonnes in 2100 compared with 2636 tonnes at present if all producers adopted the optimal breed structure. Optimal breed structure was defined as one that would prevent tick numbers per animal exceeding 100 ticks per animal for European and 700 ticks per animal for crossbred breeds of cattle in any week of the year under a tick control strategy that was suitable for present climatic conditions. The lower threshold for European breeds reflects their vulnerability to explosive increases in numbers because of their low resistance to ticks. The results of the analyses using the GCM scenarios were used in an economic model to calculate costs of lost live-weight gain for 2030, 2070 and 2100. The greatest increases in costs were incurred in the southern parts of the current distribution in Queensland and potentially in northern New South Wales if the present quarantine barrier failed.Given the great uncertainty of the nature of possible regional changes in climate, analyses of the sensitivity of losses in live weight gain to changes in climatic variables were also undertaken. The analyses included a measure of likely impacts of cattle tick on the beef cattle industry, in the absence of adaptation measures, as a baseline measure of sensitivity. The likely impacts on crossbred cattle were insensitive to the climatic variables.When adaptive breed changes were allowed, the economic impacts on the industry were insensitive to the GCM scenarios. This suggests that, at least in this instance, reducing the uncertainties in climate change scenarios is not a priority if the adaptation strategies can be implemented in a cost-effective manner. Finally we made a qualitative assessment of the sustainability and robustness of alternative approaches to adaptation and assessed regional vulnerability to cattle tick under climate change. The conclusions were so strongly dependent on assumptions about the future of other global changes, in particular the ability to maintain quarantine barriers and to retain effective acaricides at comparable costs to the present, that we strongly recommend that risk assessments of climate change extend to all relevant variables in involved in global change where possible.