Thursday, January 31, 2013

These diamonds are a fishery manager’s best friend

Have you heard that all marine fisheries are doomed? After a study he published with co-authors in 2006, Boris Worm, a professor at Dalhousie University, claimed “if the long-term trend continues, all fish and seafood species are projected to collapse within my lifetime -- by 2048.” Anyone who has paid any attention to news reports over the past decade will realize this claim is not the first or the only that fisheries management is failing, although it may be the most extreme.

Don’t believe everything you hear. Some of these doom and gloom pronouncements may have elements of truth in them, but they all do a disservice to fisheries management because they seem to suggest that there is a right answer, usually a plea for a general decrease in fishing pressure or a call for a specific technique, most often a closed fishing area. In today’s blog, I hope to convince you that there is no such thing as a right answer, but that there is an effective process for coming up with good solutions. I’m sure it won’t surprise you that this process does not include doom and gloom pronouncements. Instead, it focuses on two inherent attributes of fisheries: their uncertainty and the differences of opinion among stakeholders on objectives.

The key to uncertainty is recognizing and characterizing it in terms that are relevant to stakeholders and policy-makers. I have already discussed uncertainty extensively and encourage you to review previous blog postings if this subject is of interest. Today I will focus on conflicting objectives. To start, I need to reiterate a point from the rocket science approach to fisheries. When setting catch limits, rarely can I give advice about the implications of an annual quota in isolation. A seemingly irresponsibly high quota might end up meeting the economic needs and be part of a sustainable plan if it is paired with commitments to set low quotas in the future. Conversely, many seemingly reasonable quotas may be wildly irresponsible if the quota will remain the same in subsequent years even if there is evidence of stock decline. In short, to understand the implications of fisheries quotas, we need to analyze the whole system.

There are a few key objectives that come up in the design of most quota-setting systems. Let’s start with two fairly simple ones—high catches versus constant catches—and simplify matters by assuming that we have exceptional information so that there is no uncertainty. Even in this simple case, small-scale and large-scale fishing groups are likely to have distinct objectives. The small-scale operations probably have a greater need for regular catches on a daily, weekly, or at least monthly basis. Subsistence fishers, those who catch food for their households, would be a good example. By contrast, a large corporate fishing operation may be in a position to weather ups and downs in catches even over months or years. In general, constancy of catches is beneficial to all fishing-related businesses, from the fishermen themselves, who have better economic conditions with consistent income, to restaurants and fish markets, which benefit from having a consistent supply of seafood. Nevertheless, fishing operations will vary in their tolerance of catches that vary from one month or one year to the next, and the size of the operation will influence that tolerance.

Fig. 1--Diamond of high catch peformance.
Stock and flow are policy choices.
Performance: Green = high, Red = low.
Recall from the blog that compared fish, water, and methane that we can think of many environmental systems as a stock and a flow. We have choices for the target stock level (in this case, number of fish left in the ocean) and the characteristics of the flow (in this case the shape of our quota-setting policy combined with the productivity of the fish stock). These policy options can be represented in a diamond shape, which when used properly can be a fisheries manager’s best friend. Like the gemstone diamond, this one has color. We can represent performance based on a given objective, ranging from high performance in green to poor performance in red. The colors change across the surface of the diamond, call that its cut. When it comes to average catches, we get best performance from fisheries that have intermediate stock levels (Fig. 1). Too few fish and the population will suffer from a lack of reproductive output. Too many fish and much of the potential productivity will be “lost” to the ecosystem. When we consider that the productivity of a stock varies from one year to the next, it turns out that highly responsive policies provide higher average catches than more constant ones because they keep the population from drifting even temporarily to sizes that would be less productive (again, Fig. 1). The details of how quickly performance drops and the exact location of the peak—the color and cut of the diamond—will vary based on ecological factors, but the general attributes are consistent across fisheries.

Fig. 2--Diamond of constant catch performance.
Constant catches respond very differently to various policies. This objective is influenced exclusively by the flow properties, as shown in Fig. 2. Note that the best policies for average catches are the worst for constancy. We could find some happy medium somewhere near the middle of the diamond. However, because fishing operations have different tolerances for unpredictable catches, they will not agree on where this happy medium lies. Smaller scale operations, which require regular catch and income, will prefer policies pretty far to the left while larger scale operations will want somewhat more responsive policies because they are willing to trade off some fluctuations in catches in order to catch more fish overall.

Fig. 3--Diamonds of ecosystem function (top)
and sustainability (bottom).
In real-life, the situation is more complicated. We have groups that care about the ecosystem function of the fish population. These groups include conservation organizations as well as people who have an interest in other aspects of the same ecosystem, for example fishing operations that target a predator of the fish in question. When we consider ecosystem function, a high stock will be of paramount importance (Fig. 3, top). This conflicts with the high catch performance because the productivity that is “lost” to the ecosystem as far as catches are concerned provides benefits elsewhere. Although less important, natural flows (neither too high nor too low) will be best for maintaining ecosystem services (Fig. 3, top). Once again, the nuances of these performance results, the color and cut of this diamond, will vary depending on ecological conditions.

Uncertainty also plays a key role. The performances in terms of average and constancy of catch, above, are based on the assumption that we know the long-term productivity of the stock. In reality, the majority of stocks lack even an educated estimate of productivity. For the rest, the estimates range from moderately to highly uncertain. The most recent two blog posts have made the point that sustainability can be achieved, even in the face of uncertainty, through responsive management, light fishing (and thus a high stock size), or a combination of both. Thus, the sustainability of various fisheries policies drops from a peak on the upper right portion of the policy diamond to a minimum on the bottom left (Fig. 3, bottom). Sustainability affects everyone who has an interest in fisheries, but once again this diamond’s color and cut depend on social, economic, and ecological characteristics.

Together, these four objectives: high catches, constant catches, ecosystem functions, and sustainability, capture the majority of concerns various groups have about quota-setting policies. Unfortunately, they give conflicting advice. The right answer will differ among groups depending on their social and economic circumstances and how much they value each of these objectives. Thus, we do a disservice anytime we present a ‘right’ answer. Doing so is simply a way of justifying one’s own preference by treating it as if it was an objective finding of science. We can do better by presenting the trade-offs to everyone involved in the management arena. These diamonds do exactly that. When interest groups are better informed about the consequences of long-term policies, like quota-setting rules, they will have more investment in their design and application. Of equal importance, when groups are more informed about the trade-offs that their opponents face, they are more likely to work constructively and devise long-lasting solutions.

As always, your comments are appreciated.


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