Design and Crime (And other Diatribes)

Revista de Filosofia da Unidade de Investigação em Ciência, Tecnologia e Sociedade da Universidade Lusófona

The East Atlantic Bluefin Tuna Fisheries: Stock Collapse or Recovery?

A discrete time, multi-gear, and age structured bio-economic model is developed for the East Atlantic bluefin tuna fisheries, a paradigmatic example of the difficulties faced in managing highly migratory fish stocks. The model is used to analyse alternative management strategies for the Regional Fisheries Management Organisation (RFMO) managing this fishery, and to investigate some of the policy implications. For the various scenarios, the optimal stock level varies between 500–800,000 tonnes, which compares with a stock level of 150,000 tonnes in 1995. In other words, there is a very strong case for rebuilding the stock. Moreover, the sustainability of the stock is threatened unless a recovery programme is implemented; indeed, the alternative may be stock collapse. Second, to rebuild the stock, Draconian measures are called for: either outright moratoria over fairly lengthy periods, or possibly a more gradual approach to steady state given by a Total Allowable Catch (TAC) at a low level for an extended period of time. Third, the cost of inefficient gear structure is very high indeed.

Systems thinking: learning or driving?

The ability to foresee how behaviour of a system arises from the interaction of its components over time - i.e. its dynamic complexity – is seen an important ability to take effective decisions in our turbulent world. Dynamic complexity emerges frequently from interrelated simple structures, such as stocks and flows, feedbacks and delays (Forrester, 1961). Common sense assumes an intuitive understanding of their dynamic behaviour. However, recent researches have pointed to a persistent and systematic error in people understanding of those building blocks of complex systems. This paper describes an empirical study concerning the native ability to understand systems thinking concepts. Two different groups - one, academic, the other, professional – submitted to four tasks, proposed by Sweeney and Sterman (2000) and Sterman (2002). The results confirm a poor intuitive understanding of the basic systems concepts, even when subjects have background in mathematics and sciences.

Systems thinking: learning or driving?

The ability to foresee how behaviour of a system arises from the interaction of its components over time - i.e. its dynamic complexity – is seen an important ability to take effective decisions in our turbulent world. Dynamic complexity emerges frequently from interrelated simple structures, such as stocks and flows, feedbacks and delays (Forrester, 1961). Common sense assumes an intuitive understanding of their dynamic behaviour. However, recent researches have pointed to a persistent and systematic error in people understanding of those building blocks of complex systems. This paper describes an empirical study concerning the native ability to understand systems thinking concepts. Two different groups - one, academic, the other, professional – submitted to four tasks, proposed by Sweeney and Sterman (2000) and Sterman (2002). The results confirm a poor intuitive understanding of the basic systems concepts, even when subjects have background in mathematics and sciences.