Accounting for the movement of fish and boats
Balancing the needs of conservation with its impacts on fisheries is important when designing marine reserve networks
Commonly used design tools based on static models are good at placing reserves to avoid short-term losses to fisheries
Static models perform poorly for designing reserves that bring benefits to fisheries in the longer-term (>10 years)
Tools based on dynamic models are better at designing reserves that provide long-term benefits to fisheries
The design of marine reserves is always contentious. Marine reserves are areas closed to fishing to protect native plants and animals, so protection often comes at a cost to local fishing industries who will be excluded from fishing in some places. Australia’s Great Barrier Reef Marine Protected Area, for example, was rezoned in 2004 to have 33.3% of its area as no fishing zones. The process was highly contentious and cost the Federal Government around $250 million in compensation pay-outs to fisheries. Clearly, balancing the needs of conservation with its impacts on fisheries is important for both people and economies.
The tools used to design marine reserves have often been criticized for being too simplistic. The most commonly used tools apply static models which only analyse spatial patterns in habitats. This approach typically assumes that fisheries profits are reduced by the amount that was generated in areas designated as reserves. Consequently, these tools may put reserves in the wrong places that cost fisheries too much of their catch.
To address this problem, we compared the tools commonly used to design reserves with more ‘realistic’ tools (Brown et al, 2015). Our realistic tools use dynamic models that account for the movement of fish in and out of reserves, as well as the displacement of fishing boats after reserves are implemented. The standard tools do not account for the movement of fish and boats.
We compared the tools in two places, California’s Marine Protected Area system (which was completed in 2011) and a new Marine Protected Area system in Tun Mustapha Park, Malaysia (which is currently being implemented).
We found that the standard tools were highly inaccurate at estimating how much fishing profits would be lost because of a proposed reserve network. Depending on the situation, the standard tools could under or over-estimate the cost of reserves to fisheries sometimes by more than 20% of the present day profits.
Surprisingly, despite their inaccuracy in estimating the costs to fisheries, the standard tools were reasonably good at designing marine reserve networks that minimized impacts on fisheries, while meeting targets for conservation. The reason for this apparent contradiction was that the standard tools were good at getting correct the relative value of different places to fisheries – at least in the short-term.
Over the longer-term, for instance 10 or more years, the more realistic tools designed much better reserve networks that both benefitted fisheries and met conservation goals. The realistic tools were able to strategically place reserves in places that would ensure ‘spill-over’ of fish larvae from reserves to outside areas, where they could be caught. The standard tools could not create reserve networks that provided this synergy between conservation and fisheries.
Unfortunately, it is not feasible to use our more realistic tools in every circumstance. They require a lot of data and development time to create. All this is expensive and may be beyond the resources of many management agencies. Where possible, however, we recommend this approach.
In the absence of cheap and realistic models, we suggest that the standard tools provide reasonably good reserve networks. However, the standard tools should not be used to estimate compensation payouts for fisheries.
More info: Chris Brown firstname.lastname@example.org
Brown CJ, C White, M Beger, HS Grantham, BS Halpern, CJ Klein, PJ Mumby, VJD Tulloch, M Ruckelhaus & HP Possingham (2015). Fisheries and biodiversity benefits of using static versus dynamic models for designing marine reserve networks. Ecosphere 6(10):182. http://dx.doi.org/10.1890/ES14-00429.1