Abstract Identifying effective adaptation strategies for coastal communities dependent on marine resources and impacted by climate change can be difficult due to the dynamic nature of marine ecosystems. The task is more difficult if current and predicted shifts in social and economic trends are considered. Information about social and economic change is often limited to qualitative data. A combination of qualitative and quantitative models provide the flexibility to allow the assessment of current and future ecological and socio-economic risks and can provide information on alternative adaptations. Here, we demonstrate how stakeholder input, qualitative models and Bayesian belief networks (BBNs) can provide semi-quantitative predictions, including uncertainty levels, for the assessment of climate and non-climate-driven change in a case study community. Issues are identified, including the need to increase the capacity of the community to cope with change. Adaptation strategies are identified that alter positive feedback cycles contributing to a continued decline in population, local employment and retail spending. For instance, the diversification of employment opportunities and the attraction of new residents of different ages would be beneficial in preventing further population decline. Some impacts of climate change can be combated through recreational bag or size limits and monitoring of popular range-shifted species that are currently unmanaged, to reduce the potential for excessive removal. Our results also demonstrate that combining BBNs and qualitative models can assist with the effective communication of information between stakeholders and researchers. Furthermore, the combination of techniques provides a dynamic, learning-based, semi-quantitative approach for the assessment of climate and socio-economic impacts and the identification of potential adaptation strategies.

Item Type:	Refereed Article
Keywords:	climate change, qualitative modelling, Bayesian belief network, fisheries, socio-economic, stakeholder input
Research Division:	Agricultural, Veterinary and Food Sciences
Research Group:	Fisheries sciences
Research Field:	Fisheries sciences not elsewhere classified
Objective Division:	Animal Production and Animal Primary Products
Objective Group:	Fisheries - wild caught
Objective Field:	Fisheries - wild caught not elsewhere classified
UTAS Author:	Frusher, SD (Professor Stewart Frusher)
ID Code:	88621
Year Published:	2014
Web of Science® Times Cited:	21
Deposited By:	Sustainable Marine Research Collaboration
Deposited On:	2014-02-11
Last Modified:	2017-11-04
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