SCIENCE AT THE SHINE DOME canberra 6 - 8 may 2009

Early-career researchers

Thursday, 7 May 2009

2008 Fenner Medal

Dr Michael McCarthy
University of Melbourne

Michael McCarthy obtained his PhD from the University of Melbourne, researching the use of stochastic population models for wildlife management. He completed postdoctoral fellowships at the Australian National University, the University of Adelaide, and UC Santa Barbara. He was a senior ecologist in the Australian Research Centre for Urban Ecology for six years, and is currently a principal research fellow in the School of Botany at the University of Melbourne. He will soon be appointed in a teaching and research role, with significant contributions to the University of Melbourne's new Master of Science degree. His research applies, develops and assesses quantitative methods for ecological research and environmental management. Study organisms are diverse including fungi, plants, invertebrates and vertebrates. He works across a range of disciplines that include ecology, mathematics, statistics and economics.

Resource allocation for efficient environmental management

Faced with substantial losses of biodiversity, emerging infectious diseases and global climate change, environmental managers must decide how to invest the resources they have available. Researchers in this field have previously determined how to allocate conservation resources among regions, design nature reserves, allocate funding to species conservation programs, design biodiversity surveys and monitoring programs, manage threatened, migratory or invasive species and invest in greenhouse gas mitigation schemes. However, these issues have not been addressed with a unified theory. Further, uncertainty is prevalent in environmental management, but this issue has been largely ignored in previous research. Ignoring uncertainty is risky, can lead to over-confidence in the chosen management strategy, and exposes managers to unexpected failure. I present a general theory for optimal environmental management that synthesises previous approaches to the topic and incorporates uncertainty. I show that the theory solves a diverse range of important problems of resource allocation. I illustrate this approach with two examples: conservation of biodiversity; and surveillance to detect the highly-pathogenic avian influenza H5N1 virus in Thailand. Considering uncertainty can lead to greater diversification of effort across different management options. I solve non-linear versions of these problems, with linear versions being equivalent to Markowitz's portfolio theory for allocation to financial portfolios. Thus, environmental management decisions are equivalent to investment decisions, with trade-offs between risk and return.