approach with economic considerations. However, these models turned out to be too
simplistic for effective management.
Currently, bio-economic models incorporating fishermen’s motivations are being
used as the basis for establishing individualized quota systems. These bio-economic
models that include fishermen’s motivations have been successfully implemented in
Canada, Iceland, Australia, Namibia, and other countries. This is a good example of the
need to include social sciences in what had previously been considered a marine
biological problem.
Individualized transferable catch quotas (ITQs) can and do alter fishermen’s
incentives so as to favor sustainable harvesting. Real world fish populations are
components of highly complex ecosystems having spatial, temporal and other
structures. Recognition of these structures may be essential for good management. To
mention one typical case: spawning areas may attract fishing activity because of the
high concentration of fish, but uncontrolled fishing in such areas can result in severe
overfishing. The use of protected “no-take” areas to protect breeding stocks would lead
to greater long-term catches. However, fishermen may oppose protected areas because
they typically reduce catch rates temporarily. Under an ITQ management system, the
fisherman may be economically motivated to favor protected areas, which will increase
the future value of their quota.
Hence, a mathematical challenge is to search for effective incentive systems.
One approach is to use agent-based models to explore the balance of cooperative and
competitive behavior that emerges in fishing communities under different incentive
scenarios.
Fish increase in size and economic value as they grow older. Age-structured
models are used to estimate the optimal age of capture, and regulation of the mesh size
of fishing nets is then used to achieve this optimum. ITQ-based fishermen typically
support such regulation, even though short term catch rates may be reduced. Yet
another important structure is genetic; maintenance of genetic diversity, for example in
salmon populations, is essential for sustainable management. This is a serious issue in
fisheries that capture mixtures of different genotypes.
Contrary to the predictions of a simple aggregated model, disaggregated models
exhibit circumstances under which optimal management may require greater levels of
fishing effort than occurs under unregulated exploitation. Not much work has been done
in this area; it is ripe for mathematical exploration.
It would be desirable to manage fisheries on the basis of ecosystem structure.
This introduces serious modeling challenges because of the complexity and limited
observability of marine systems. Approaches that might be tractable are to aggregate
into species groups, to identify critical resources that act as bottlenecks in the population
dynamics, or to use single species models incorporating constraints designed to
conserve ecosystem structure.
Linkages between the oceans and the atmosphere are critical for future climate
conditions on earth. Examples include:
- Heat exchange (the oceans store more than 99% of combined ocean and
atmospheric heat, transfer of which takes place on a slow time scale). - Ocean acidification (increased atmospheric CO2 has resulted in severe ocean
acidification, which is affecting marine life globally)