Rohan Nelson

From rainfall to farm incomes—transforming advice for Australian drought policy. II. Forecasting farm incomes

Australian drought policy is focussed on providing relief from the immediate effects of drought on farm incomes, while enhancing the longer term resilience of rural livelihoods. Despite the socioeconomic nature of these objectives, the information systems created to support the policy have focussed almost exclusively on biophysical measures of climate variability and its effects on agricultural production. In this paper, we demonstrate the ability of bioeconomic modelling to overcome the moral hazard and timing issues that have led to the dominance of these biophysical measures. The Agricultural Farm Income Risk Model (AgFIRM), developed and tested in a companion paper, is used to provide objective, model-based forecasts of annual farm incomes at the beginning of the financial year (July-June). The model was then used to relate climate-induced income variability to the diversity of farm income sources, a practical measure of adaptive capacity that can be positively influenced by policy. Three timeless philosophical arguments are used to discuss the policy relevance of the bioeconomic modelling. These arguments are used to compare the value to decision makers of relatively imprecise, integrative information, with relatively precise, reductionist measures. We conclude that the evolution of bioeconomic modelling systems provides an opportunity to refocus the analytical support for Australian drought policy towards the rural livelihood effects that matter most to governments and rural communities.

From rainfall to farm incomes—transforming advice for Australian drought policy. I. Development and testing of a bioeconomic modelling system

In this paper we report the development of a bioeconomic modelling system, AgFIRM, designed to help close a relevance gap between climate science and policy in Australia. We do this by making a simple econometric farm income model responsive to seasonal forecasts of crop and pasture growth for the coming season. The key quantitative innovation was the use of multiple and M-quantile regression to calibrate the farm income model, using simulated crop and pasture growth from 2 agroecological models. The results of model testing demonstrated a capability to reliably forecast the direction of movement in Australian farm incomes in July at the beginning of the financial year (July-June). The structure of the model, and the seasonal climate forecasting system used, meant that its predictive accuracy was greatest across Australias cropping regions. In a second paper, Nelson et al. (2007, this issue), we have demonstrated how the bioeconomic modelling system developed here could be used to enhance the value of climate science to Australian drought policy.

A Participatory Assessment of NRM Capacity to Inform Policy and Practice: Cross-Scale Evaluation of Enabling and Constraining Factors

The capacity of private landholders to manage natural resources is constrained and enabled by diverse, interconnected, and changing factors, which vary substantially across time and space. This context dependence of capacity makes it both a useful construct and a difficult one to evaluate, which makes targeting investment in capacity building across scales difficult. We detail results of a transferrable, place-based process for evaluating capacity of private land managers to manage natural resources across scales in New South Wales, Australia. A livelihoods approach was used to enable land managers to define, describe, and evaluate locally relevant indicators of NRM capacity. Constraints to capacity were perceived as externally imposed or related to poor vertical linkages between land managers and government agencies. Conversely, local characteristics of regional organizations, communities and individuals were often described as enabling capacity. There was substantial consistency across workshops and there were widespread indications of declining capacity to contribute to effective NRM.

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.