The 2009 World Bank study “The Costs to Developing Countries of Adapting to Climate Change: New Methods and Estimates” clearly states that the costs of Climate Change to global fisheries may reach an estimated US$ 9.64 billion in the year 2050. The estimated cost to developing countries could be as high as US$ 7 billion. These revenue projections reflect climate induced changes in ocean ecology and their impact on fish stocks. The complex relationships involved include management practices and therefore offer the potential for actual recovery in fish stocks if governments and/or managers implement appropriate controls on fishing activity. Worm et al. in Rebuilding Global Fisheries (2009) describe how merging different management approaches can facilitate the rebuilding of fisheries in diverse locations.
An adaptable harvesting policy for fish stocks responding to climate change and other stressors is clearly needed. Meeting this need appears possible through integration of a prototype policy cycle model (Woodcock, 2008) with prototype density-dependent growth and predator-prey harvesting models implemented in systems dynamics software. The policy cycle model simulates the major processes in the development and implementation of public policies (Lester and Stewart, 2000 and Anderson, 2003, for example).
Predator and prey populations may exhibit sustained oscillations, which can be altered by changing the rate of harvesting of the prey species in the models. There is room to add additional relationships with chlorophyll levels, ocean temperatures, and bait fish activity in order to create clearer links between the expected changes in ocean ecology and the predicted response of fish stocks. It appears that the working models of the population dynamics and policy cycle permit an informed manager to anticipate population behavior and avoid catastrophe.
The policy cycle model shows that rapid events can affect timely changes in harvesting rates while slower events impede the recovery process of a fishery under climate change and harvesting stresses. This echoes other applications of the policy cycle model to military conflict and causes of societal violence (Woodcock, Christensson, and Dockery, 2009). Those models have demonstrated that slow changes in policy responding to military or societal challenges can lead to the undermining of friendly forces or to increased levels of societal violence. Based on this prototype systems-dynamics-based policy-cycle-models have been implemented to examine the impact of harvesting levels and policy dynamics on the availability of fish stocks.
Results of a series of preliminary model-based experiments involving responses to notional fish growth and harvesting are presented and discussed in the context of the harvesting-related behavior of actual fisheries. A brief look at the Eastern Canadian fishery over the period 1950-2000 provides some illustration of the concept. Application of the model to the Tuna fishery of the Warm Pool North-East of Australia (a large marine ecosystem), and specifically the use of the model in the management of the North-Eastern Australian Yellow Fin Tuna fishery was considered. These activities provide a basis for defining adaptable harvesting policies that would promote self-sustaining fisheries in fragile environments.
|Keywords:||Fisheries Management, Climate Change Impacts Ocean Fish Stocks, Policy-related Management Models, Predator-Prey Models, Managing Sustainable Fish Stocks in a Changing Environment|
Affiliate Professor, The School of Public Policy, George Mason University, Fairfax, Virginia, USA
Professor of Geography and Director of Corporate Engagement, Office of the Vice-President for Research and Economic Development, George Mason University, Fairfax, Virginia, USA
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