Integrated simulation tools for the bio-economic assessment of renewable resource systems
The project is funded by the "FAST" Programme (Partenariat Hubert Curien franco-australien de coopération pour la science et la technologie) jointly directed by the Australian Department of Innovation, Industry, Science and Research (DIISR), and by the French Ministry of Higher Education and Research, and the Ministry of Foreign Affairs.
In recent years, there has been a growing interest in the development of integrative simulation tools to represent and analyze the joint ecological and social dynamics of renewable resource systems.
These models allow exploration of the co-viability of renewable resources and their uses, taking into account a growing level of complexity, e.g. in relation to the influence of environmental drivers on ecological changes, or of economic and institutional drivers on resource uses. This interest has developed in a great diversity of contexts, in both land-based and aquatic resource systems. It has grown particularly quickly in the area of marine living resources management, with respect to the issue of marine fisheries sustainability. An important literature on the modeling of harvested marine ecosystems exists, with two broad areas of application: (i) models used as decision-aid tools for the assessment of managements scenarios of a particular resource system; and (ii) exploratory models used as a basis for the analysis of the key processes involved in the evolution of resource systems. In both types of models, attention is increasingly being devoted to the explicit representation of spatial and temporal evolutions of both ecological components and harvesting patterns. An implication for modeling is the greater degree of complexity that needs to be taken into account in the formal representation and analysis of the biological and economic dynamics of marine resource systems. Various modeling techniques have been used to date. Both optimization and system dynamics simulation techniques have been applied to fairly simple descriptions of the spatial and temporal evolution of fishing effort. Optimization and simulation techniques have also been used in more complex bioeconomic models involving several marine species harvested by several fleets in different zones.
These approaches have usually been based on differential equation systems, hence with relatively aggregated representations of the human and biological components of marine fisheries (fish stocks, fishing fleets). Agent-based modeling has been proposed as an interesting approach to deal with local, rather than global interactions, and suggested as an alternative for the representation of behavioral processes, particularly but not exclusively, in the social component of models. Such studies pose a challenge for modelers, as they require the integration of processes occurring at different scales, the empirical knowledge of each process being available at a certain scale only. In particular, the advantages of coupling individual-based representations of human behavior with aggregated representations of biological processes in the simulation of marine resource systems warrant specific investigation.
The aim of the project is to explore the issues related to the development of formal modelling approaches of complex system interactions such as encountered in a spatially explicit dynamic representation of a coastal fishery.
The project is strongly linked to a co-tutelle PhD research project co-funded by IFREMER and the University of Tasmania, and cosupervised by the project team, on the following subject: "Bio-economic impact assessment of changes in the regulation of access to fisheries: the case of Individual Transferable Quotas in Australian coastal fisheries", which has started at the end of 2007
The project is constructed around two workshops planned in conjunction with the schedule of the PhD research. The workshops will aim at bringing together French and Australian researchers, including but not limited to the PhD student and the researchers involved in supervising the PhD project, to work specifically on modeling issues: