Why is economics not a complex systems science?

The article argues that economics will have to become a complex systems science before economists can comfortably incorporate institutionalist and evolutionary economics into mainstream theory. The article compares the complex adaptive system of John Foster with that of standard economic theory and illustrates the difference through an examination of familiar production function. The place of neoclassical, Keynesian economics in complex systems is considered. The article concludes that convincing, multiple models have been made possible by the increase in widely available computing power available.

National whoppercropper - risk management discussion support software

It is a paradox that in a country with one of the most variable climates in the world, cropping decisions are sometimes made with limited consideration of production and resource management risks. There are significant opportunities for improved performance based on targeted information regarding risks resulting from decision options. WhopperCropper is a tool to help agricultural advisors and farmers capture these benefits and use it to add value to their intuition and experience. WhopperCropper allows probability analysis of the effects of a range of selectable crop inputs and existing resources on yield and economic outcomes. Inputs can include agronomic inputs (e.g crop type, N fertiliser rate), resources (e.g soil water at sowing), and seasonal climate forecast (SOI phase). WhopperCropper has been successfully developed and refined as a discussion-support process for decision makers and their advisers in the northern grains region of Australia. The next phase of the project will build on the current project by extending its application nationally and enhancing the resource management aspects. A commercial partner, with over 800 advisor clients nationally, will participate in the project.

Optimising profitability and environmental trade-offs in managing cropping systems using differential evolution

Whilst traditional optimisation techniques based on mathematical programming techniques are in common use, they suffer from their inability to explore the complexity of decision problems addressed using agricultural system models. In these models, the full decision space is usually very large while the solution space is characterized by many local optima. Methods to search such large decision spaces rely on effective sampling of the problem domain. Nevertheless, problem reduction based on insight into agronomic relations and farming practice is necessary to safeguard computational feasibility. Here, we present a global search approach based on an Evolutionary Algorithm (EA). We introduce a multi-objective evaluation technique within this EA framework, linking the optimisation procedure to the APSIM cropping systems model. The approach addresses the issue of system management when faced with a trade-off between economic and ecological consequences.

Common and endangered species: How does society allocate support for their conservation?

Examines how society allocates support for species’ conservation when numbers involved are large and resources are limited. Rational behaviour suggests that species in urgent need of conservation will receive more support than those species that are common. However, we demonstrate that in the absence of balanced knowledge common species will receive support more than they would otherwise receive despite society placing high existence values on all species. Twenty four species, both common and endangered and some with a restricted distribution, are examined. We demonstrate that balanced information is vital in order to direct more support for species that are endangered than those that are not. Implications for conservation stemming from the findings are discussed.