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The Murray dairy region produces approximately 1.85 billion litres of milk each year, representing about 20 % of Australia's total annual milk production. An ongoing production challenge in this region is the management of the impacts of heat stress during spring and summer. An increase in the frequency and severity of extreme temperature events due to climate change may result in additional heat stress and production losses. This paper assesses the changing nature of heat stress now, and into the future, using historical data and climate change projections for the region using the temperature humidity index (THI). Projected temperature and relative humidity changes from two global climate models (GCMs), CSIRO MK3.5 and CCR-MIROC-H, have been used to calculate THI values for 2025 and 2050, and summarized as mean occurrence of, and mean length of consecutive high heat stress periods. The future climate scenarios explored show that by 2025 an additional 12-15 days (compared to 1971 to 2000 baseline data) of moderate to severe heat stress are likely across much of the study region. By 2050, larger increases in severity and occurrence of heat stress are likely (i.e. an additional 31-42 moderate to severe heat stress days compared with baseline data). This increasing trend will have a negative impact on milk production among dairy cattle in the region. The results from this study provide useful insights on the trends in THI in the region. Dairy farmers and the dairy industry could use these results to devise and prioritise adaptation options to deal with projected increases in heat stress frequency and severity.

Studies on decision-making processes are generally aimed at identifying farmers' needs and predicting farmers' reactions to technical innovations. In the present paper we study these decision-making processes, with reference to dairy farms, to build a whole-farm computer model (WFM) which simulates farmers' actions. In this study, (i) a multi-tool and multi-step methodology is proposed, which can also be qualified as an iterative and interactive methodology to reveal decision rules and (ii) a generic structure to formalise how action is conducted, termed 'structure for action modelling' (SAM). In the case of forage crop-dairy cattle systems, we have tested the current methodology to capture the decision rules and the SAM to represent action concerning farm management. An 'immersion' approach, inspired by the ethnographic approach has been adapted to access operational technical decisions (taken on a daily basis). This study helped in understanding how detailed and large approaches can be complementary and can facilitate identification of what can be generalised in a conceptual model. To define the generic structure (SAM), a set of descriptive variables concerning technical operations has been selected. The conceptual model generated is composed of decision rules reconstructed by researchers with farmers' committed participation. The validation method is based on participatory approaches and on comparing of actions simulated by the model with practices on the ground. Not contesting the fact that farmers plan their action, this study also revealed the importance of adjustments in action. For example, 20 to 55% of the time the planned food ration is not distributed to the milking cows because of forage unavailability. We also discuss how this structure can facilitate integration of decision mechanisms in biophysical models and how such an integration of adjustment decision rules can produce more realistic simulations of technical actions. Error of biotechnical evaluations done by the WFM is reduced from about 25% to about 10% with the application of the proposed method.