Peter Hayman

Climate change through the farming systems lens: challenges and opportunities for farming in Australia

Abstract. Adaptation to and mitigation of climate change in Australian agriculture has included research at the plant, animal, and soil level; the farming system level; and the community and landscape level. This paper focuses on the farming systems level at which many of the impacts of a changing climate will be felt. This is also the level where much of the activity relating to adaptation and mitigation can usefully be analysed and at which existing adaptive capacity provides a critical platform for further efforts. In this paper, we use a framework of nested hierarchies introduced by J. Passioura four decades ago to highlight the need for research, development and extension (RDE) on climate change at the farming systems level to build on more fundamental soil, plant, and animal sciences and to link into higher themes of rural sociology and landscape science. The many questions asked by those managing farming systems can be categorised under four broad headings: (1) climate projections at a local scale, (2) impacts of climate projections on existing farming systems, (3) adaptation options, and (4) risks and opportunities from policies to reduce emissions. These questions are used as a framework to identify emerging issues for RDE in Australian farming systems, including the complex balance in on-farm strategies between adapting to climate change and reducing greenhouse gas concentrations. Climate is recognised as one of the defining features of different farming systems in Australia. It follows that if the climate changes, farming systems will have to shift, adapt, or be transformed into a different land use. Given that Australian farming systems have been adaptive in the past, we address the question of the extent to which research on adaptation to climate change in farming systems is different or additional to research on farming systems in a variable climate.

Placing the power of real options analysis into the hands of natural resource managers - taking the next step.

This paper explores heuristic methods with potential to place the analytical power of real options analysis into the hands of natural resource managers. The complexity of real options analysis has led to patchy or ephemeral adoption even by corporate managers familiar with the financial-market origins of valuation methods. Intuitively accessible methods for estimating the value of real options have begun to evolve, but their evaluation has mostly been limited to researcher-driven applications. In this paper we work closely with Bush Heritage Australia to evaluate the potential of real options analysis to support the intuitive judgement of conservation estate managers in covenanting land with uncertain future conservation value due to climate change. The results show that modified decision trees have potential to estimate the option value of covenanting individual properties while time and ongoing research resolves their future conservation value. Complementing this, Luehrmans option space has potential to assist managers with limited budgets to increase the portfolio value of multiple properties with different conservation attributes.

Modelling heatwaves in viticultural regions of southeastern Australia

The production of quality wine grapes is sensitive to heatwaves, especially at key phenostages such as flowering and ripening. Climatological models of heatwaves with application in viticulture need to account for (a) a range of meteorological variables, (b) intensity, (c) duration and (d) timing of events. The meteorological variable most commonly associated with heatwaves is maximum temperature; however, high minimum temperatures associated with heatwaves are also relevant for viticulture. Intensity should be expressible as either exceeding a categorical threshold such as 35°C or a relative threshold such as the 90th percentile. In addition to the chance of heatwaves of a given intensity and duration for the growing season (September to April), viticulturists are interested in monthly and fortnightly windows to account for the timing of critical phenostages. The model presented here is an attempt to meet these four requirements. The model is stochastic and incorporates seasonality and daily persistence of temperature through a Markov process and implies that frequency (or the return period) of heatwaves decreases (increases) geometrically with each additional day of duration. The final model is expressed as a simple equation involving a single location-specific parameter, M, which relates to the maritime influence. The model was tested over the viticultural regions of southeastern Australia by comparison with observed data, and by assessing the physical and climatological meaning of parameter M. Cross-validated model estimates of annual frequency of heatwaves were in good agreement with observations. The parameter M proved robust and physically meaningful: it is location-specific, its isopleths have the qualitative impression of sea-breeze or maritime influence and it is quantitatively related to the skewness of the summertime maximum temperature distribution.

Valuing seasonal climate forecasts in a state-contingent manner

We applied state-contingent theory to climate uncertainty at a farm level to assess the value of seasonal climate forecasts in the Central West region of NSW. We find that modelling uncertainty in a state-contingent manner results in a lower estimate of forecast value than the typical expected value approach. We attribute this finding to a more conservative long-term farm plan in the discrete stochastic programming (DSP) model, which is better balanced for climate uncertainty. Hence, a climate forecast, even though it still revises probabilities held by farmers, does not call forth such large changes in farm plans and associated farm incomes. We then use the DSP model to assess how attributes of a hypothetical forecasting system, particularly its skill and timeliness, as well as attributes of the decision environment, influence its value. Lastly, we assess the value of current operational forecast systems and show that the value derived from seasonal climate forecasts is relatively limited in the case study region largely because of low skill embodied in forecasts at the time when major farm decisions are being made.

Irrigation and Drought in a Southern Australian Climate that is Arid, Variable, and Changing

This chapter attempts to shed light on the recent crisis by briefly examining how irrigation and climate have been thought about in Australia in the past and how this is likely to change in the future. The focus is the irrigation block and vineyard level of the South Australian Riverland. The chapter summarizes opportunities and limits to adaptation options, including further gains in efficiency, closer monitoring of water requirements, and the use of weather and climate forecasts. We conclude by observing the complexity of thinking about drought in a climate that is arid, variable, and changing. Irrigation in Australia was designed to turn arid regions into an oasis. A century later, drought has forced a major and unplanned restructure. Many irrigators hope that it is just a drought, some worry that rather than a cyclical drought, we are seeing manifestation of a drying, and that the real worry is an increasing aridity.

A Systems Approach to Climate Risk in Rainfed Farming Systems

Climate is a major source of risk in rainfed farming systems. Systems thinking from natural sciences is used to define and explore concepts of weather, climate and climate change before discussion of how climate data can be used in simulation models of agricultural production systems. We then use systems engineering to consider the nature of climate risk and the use of seasonal climate forecasts in managing risk in rainfed cropping decisions in case studies from Australia and the Philippines. Finally, we consider some of the human factors in managing climate risk using soft systems methodology.