A framework for optimising capital investment and operations in livestock logistics

Despite the longevity, scale and importance of northern Australia's beef industry, recent disruptions to external markets have demonstrated a degree of vulnerability to shocks in the supply chain. Matching the industry's long-evident resilience to climatic variability with resilience to changes in markets and supply chains requires careful planning. One component of this is how investments in infrastructure will need to be planned to facilitate adaptive responses to market changes. This paper provides an outline of a modelling framework that links strategic and operational dynamic models of logistics along the supply chain from the property to the abattoir or port. A novelty of the methodology is that it takes into account the high granularity of individual livestock transport vehicle movements and the ability to scale up to an almost complete view of logistics costs across the entire beef industry of northern Australia. The paper illustrates how the methodology could be used to examine the effects of changes in logistics infrastructure on efficiency and costs using examples from the states of Northern Territory, Western Australia and Queensland.

A systematic approach to biological control agent exploration and prioritisation for prickly acacia (Acacia nilotica ssp. indica)

Agent selection for prickly acacia has been largely dictated by logistics and host specificity. Given that detailed ecological information is available on this species in Australia, we propose that it is possible to select agents based on agent efficacy and desired impact on prickly acacia demography. We propose to use the 'plant genotype' and 'climatic' similarities as filters to identify areas for future agent exploration; and plant response to herbivory and field host range as 'predictive' filters for agent prioritisation. Adopting such a systematic method that incorporates knowledge from plant population ecology and plant-herbivore interactions makes agent selection decisions explicit and allow more rigorous evaluations of agent performance and better understanding of success and failure of agents in weed biological control.