Models and Quantitative Assessment Tools

Development of Models and Quantitative Assessment Tools for Managing Biodiversity in Urban and Suburban Environments

M. McCarthy, K. Parris, R. van der Ree and M. McDonnell

ARCUE staff are involved in the development of models and quantitative techniques to predict the population dynamics of species in urban areas and their response to management. Issues being assessed include the effects of fragmentation and current management practices on species living in fragmented systems, efficient management of weed invasion, assessment and management of pest populations, optimal captive breeding and reintroduction strategies, and reconciling economic and ecological objectives. In addition to research papers, the outcomes of this research will include the development of models and decision support tools that could be used by government agencies and relevant community groups for the efficient management of natural resources in urban and suburban environments. More broadly, this research will contribute to a general theory for population management.

How best to manage species when faced with uncertainty and economic constraints

Comprises several components:

1. Standard methods of perturbation analysis of population matrix models (widely used by conservation managers) are being revised to explicitly include the financial costs of management. Further revision of these methods is examining the robustness of our decisions to variability in estimates of population parameters (survival rates etc.).

2. Methods of control of invasive predators are being explored, with the objective of maintaining viable native prey populations with a limited management budget. Traditional control options and the strategic timing of predator removal (with reference to predator population size) are being examined within a cost-based, stochastic framework.

3. Management decisions for optimal weed control are being devised. At present this research is focussed on optimising management effort in containing (not necessarily eradicating) an annual weed. Further work will explore how these optimal strategies change when linking removal effort to monitoring.

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