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Abstract: The south-west of Australia is being affected by a warming, drying trend in its climate. In response to these changing climatic conditions, as well as changes in farm commodity price relativities, farmers have adjusted their mix of enterprises to favour cereal production. As a result, an increasing potential source of cereal straw for bioenergy production has emerged. This paper examines how temporal and spatial costs of cereal straw accumulation may affect the establishment of a bioenergy plant in the region, with climate change impacts being highlighted. Logistics models based on mathematical programming are constructed for a range of plant sizes. Modelling results identify the cost structures of cereal straw accumulation for these plant sizes. Plant sizes are characterised by different cost structures and levels of volatility in their costs of grain accumulation. The profitability of bioenergy production based on cereal straw in this region of Australia is particularly exposed to climate variability, especially for larger plant sizes. The projected change in climate supports a relatively small reduction in the costs of cereal straw accumulation. These findings will affect decision-making over investment in a long-lived specific asset such as a bioenergy processing plant. [Copyright &y& Elsevier]

Abstract: Ethanol production is increasingly commonplace in many grain-producing regions. This paper uses the grain-producing region of south-western Australia to illustrate spatial and temporal aspects of grain accumulation costs for ethanol production. Specifically, this study examines how price variability of various wheat grades, combined with spatial and temporal variability in production of those grades, affects the costs of grain accumulation. These costs are the main components of an ethanol plant''s operating costs so lessening these costs can offer a comparative advantage for a plant owner. Logistics models based on mathematical programming are constructed for a range of plant sizes and locations for ethanol production. Modelling results identify low-cost sites that generate cost savings, in present value terms, of between 5 and 7.5 per cent, depending on plant size, over the 9-year study period. At all locations, small to medium-sized plants offer advantages of lower and less variable costs of grain accumulation. Yet, all locations and all plant sizes are characterised by marked volatility in the cost of grain accumulation. The profitability of ethanol production based on wheat in this region of Australia is particularly exposed to any prolonged period of high grain prices relative to petroleum prices, given current biofuel-policy settings in Australia. [Copyright &y& Elsevier]

• A mathematical programming approach for the multi-action problem is proposed (MAMP). • A new MIP model that includes fragmentation penalty in actions (MAMP-E) is presented. • The models are applied to the Mitchell River basin in Queensland, Australia. • MIP models get shorter execution times and higher quality solutions. • The MAMP-E model obtains higher ecological benefits than the MAMP model. Planning for management actions that address threats to biodiversity is important for securing its long term persistence. However, systematic conservation planning (SCP) has traditionally overlooked this aspect and just focused on identifying priority areas without any recommendation on actions needed. This paper develops a mixed integer mathematical programming (MIP) approach for the multi-action management planning problem (MAMP), where the goal is to find an optimal combination of management actions that abate threats, in an efficient way while accounting for connectivity. An extended version of the MAMP model (MAMP-E) is also proposed that adds an expression for minimizing fragmentation between different actions. To evaluate the efficiency of the two models, they were applied to a case study corresponding to a large area of the Mitchell River in Northern Australia, where 45 species of freshwater fish are exposed to the presence of four threats. The evaluation compares our exact MIP approach with the conservation planning software Marxan and the heuristic approach developed in Cattarino et al. (2015). The results obtained show that our MIP models have three advantages over their heuristic counterparts: shorter execution times, higher solutions quality, and a solution quality guarantee. Hence, the proposed MIP methodology provides a more effective framework for addressing the multi-action conservation problem. [ABSTRACT FROM AUTHOR]