coordinating the number of ships at sea in relation to the number of fish. A sustainable fishery, one that provides a reliable and abundant harvest year after year, regenerates fish at about the same rate as they are being caught. Successful replenishment requires an appropriate balance of ships and fish. Balancing is easier said than done when in practice it is impossible to observe and count the number of fish in the sea, when fishing technology is advancing and when there is a natural human propensity to prefer growth and the prosperity it brings. Imagine we could reliably count the fish stock and observe the regeneration of fish through time. What new light would this new data shed on the rise and fall of Bonavista and the policy options to avoid catastrophic decline in the fish population? In our simulator we can choose to observe and report variables that, in real life, would be unobservable. Use the colour palette and paintbrush to reinstate the original coloured trajectories for the Fish stock (blue) and New fish per year (red). You will find the appropriate colours on the top row of the palette. (If you accidentally set the background colour of the chart to blue or red, which can happen if you don't align the paintbrush with the variable name, don't panic. Simply return to the colour palette, select light grey, and repaint the background. Then try again to re-colour the trajectories.) The resulting chart will look like Figure 1.10, with all the trajectories clearly visible, except that yours will be in colour.
Consider the behaviour over time of the fish stock (line 1). For the first 10 years of the simulation the number of fish grows swiftly because effectively there is a natural fishery (no ships) that is underpopulated relative to its carrying capacity. In years 10–15 commercial fishing begins and each year more ships are sent to sea (line 4). Nevertheless, the fish population continues to increase. These are the early growth years of the Bonavista community. During this entire period the catch is rising (line 3), but is always below the rate of regeneration (new fish per year, line 2). The fishery is sustainable with growing population. In years 15–20 the catch continues to rise steadily in line with fleet expansion, but the fish stock begins to decline gently as the catch exceeds the number of new fish per year (line 3 rises above line 2). This excess of catch over regeneration is not necessarily a problem for long-term sustainability because harvesting is actually stimulating the regeneration of fish, as shown by the steady increase in new fish per year. A harvested fishery, even a well-run one, will always have a fish population considerably lower than the maximum fishery size.
Figure 1.10 Simulation of harvested fishery showing all trajectories
Herein lies a fundamental dilemma for fisheries management. Who is to say whether a decline in fish population is a problem or not? It could just be a sign of effective harvesting in a period of growth. Moreover, and this is vitally important to remember, nobody knows for certain how many fish of a given species are in the fishery. At best there are estimates subject to measurement error, bias and even manipulation. So it is very difficult in practice to make fish stock itself (how many fish are believed to be in the sea) the basis for investment policy (how many ships to purchase). Much more persuasive evidence comes from the catch. The simulation shows catch rising all the way through to year 25 and beyond. The temptation, even in years 20–25, is to believe that further fleet expansion is both desirable and justified. The conflicting signals from fish stock (a weak signal at best) and the catch (a strong and tangible signal of immediate economic and personal importance to fishermen and fleet operators) form the basis of the coordination problem in fisheries. Throughout year 25 and even into year 26 it is not unreasonable to continue fleet expansion even though the invisible fish population is in steady decline.
However, in year 25 something of vital significance happens under water, hidden from all but the fish themselves. The number of new fish per year (line 2) peaks and then starts to decline. This is the first evidence, a kind of early warning signal, that the fishery is being overfished. Fish density is now so low that regeneration is suppressed. The fishery teeters on the brink of catastrophe. The rate of population decline (the steepness of line 1) increases. But the catch keeps on rising throughout year 26 so no action is taken to curtail fleet expansion. In year 27 the catch itself peaks and then declines, gradually at first. This is the first tangible evidence of stock depletion underwater, but even so the signal is likely to be ignored until the trend proves conclusive and until the fishing community persuades itself to limit fishing. In the simulator, we assume that new ship purchasing continues apace until year 30. By then the fish stock has fallen to around 400, only 10 % of the maximum fishery size. The regeneration rate (new fish per year) is still in decline and far below the much reduced catch. Measures to halt investment and to idle ships in years 30 to 40, drastic though they are, are too little too late. Bonavista's fish have all but gone and with them the industry on which the community depends. By year 35 there are so few fish left (only 16!) that, even with a total ban on fishing, it would take two decades to rebuild the stock to its value in year 10 when our imagined Bonavista first began commercial fishing.
Now you are familiar with the gaming simulator, you can use it to test alternative approaches to growing and developing the Bonavista fishery. First press the ‘Reset’ button to obtain a new blank time chart and to re-initialise the simulator. Next, without altering either slider, press the ‘Run’ button twice in order to simulate 10 years of natural growth in the fish population so that Bonavista inherits a well-stocked fishery. Then re-simulate the same fleet expansion as before – two ships per year for years 10–25. You will find yourself back in Bonavista's heyday with a fleet of 30 ships and a history of 15 years of steady growth in the catch. Now it is your responsibility to steer the community toward a sustainable future that avoids the errors of the past. For realism you may, as before, want to ‘grey-out’ the trajectories for fish stock and new fish per year. What is happening to the fish stock underwater is difficult to know, vague and often subject to controversial interpretation. Also bear in mind the practical political difficulties of curtailing growth and of idling ships in a community that depends on fishing. Think about plausible adjustments to the two sliders at your disposal. It is a good discipline to note your intentions, and the reasoning behind them, before simulating. Imagine you first have to convince the Bonavista community and fishermen to adopt your plan. Then, when you are ready, simulate, analyse the trajectories and try to make sense of the outcome. Was the result what you expected? If not then why? If you don't like the result then try again.
Although in principle it is possible to create a sustainable Bonavista it is very difficult to do so in practice or even in a simulator, particularly when you inherit a fleet of 30 ships following 15 years of successful economic growth. The fisheries simulator is one example of a dynamically complex system, of which there are others in this book and many more in life. Often such systems give rise to puzzling performance through time – performance far below the achievable and, despite the best of intentions, not what people (stakeholders in the system) want. In this case, the fishery is prone to catastrophic decline when perhaps all that fishermen desire, and the fishing community wants, is growth, more and better ships, and a higher standard of living. Dynamic complexity stems from the connections and interdependencies that bind together social and business systems. When a change happens in one part of the system (e.g. more ships are purchased) sooner or later it has implications elsewhere, and vice versa. Moreover, these implications are not always obvious and are often counterintuitive (e.g. more ships can lead to a greater rate of fish regeneration, but not always).
Dynamic complexity does not necessarily mean big, detailed and complex, involving hundreds or thousands of interacting components. Indeed, as the fisheries simulator shows, dynamic complexity and puzzling performance can arise from only a few interacting components. What matters is not so much the raw number of components but the intricacy with which they are bound together.
Such intricacy involves time delays, processes of stock accumulation (such as the accumulations of ships and of fish), non-linearities (such as the hump-shaped relationship
