Estimating vulnerability under global change: modular modelling of pests

Abstract

Global change research and decision-making are conducted in an environment where there are many stakeholders, numerous targets and few resources. This calls for global collaboration and sharing of information on a scale that has not been attempted before. It demands a parsimonious approach to research, with the aim of enabling robust decisions to be made with the minimum of new information. Our approach to these problems has been to develop generic analytical tools, which in turn are used to foster collaboration through joint model development, testing and application. This collaboration is achieved through a workshop and networking process to establish ‘ CLIMEX’- or ‘ DYMEX’- Modelling Networks, and to extend the information to the wider community using the world wide web (WWW) (http://www.ento.csiro.au/research/pestmgmt/IPMModellingNetwork/index.htm). In this paper we outline key features of these modelling approaches and illustrate a ‘hypothesis-driven’ approach to climate-matching, using CLIMEX (http://www.ento.csiro.au/research/pestmgmt/climex/climex.htm) that contrasts with the usual, statistically based, pattern-matching of meteorological data without consideration of possible mechanisms that limit the geographical distribution. We illustrate the nature of a generic and modular simulation model built using DYMEX (http://www.ento.csiro.au/research/pestmgmt/dymex/dymexfr.htm), but emphasize the urgency for the scientific community to collect the data necessary to build reliable population models. We summarize results and conclusions from a global change workshop based on the use of both these software tools. They illustrate the advantages of the proposed approach as a means of building collaborative international research communities, which are able to avoid repetition by contributing their modules into a library of functions for sharing with other users.