Fishing Down through the Food Web

Villy Christensen Institute for the Oceans and Fisheries University of British Columbia 2202 Main Mall, Vancouver BC, Canada V6T 1Z4. E-mail: [email protected] Villy Christensen is a professor at UBC, and he leads the development of the Ecopath with Ecosim (EwE) modeling approach and software, which is coordinated through an international consortium with 25 institutional members. His research is focused on modeling the future ocean. “Fishing Down Through the Food Web”—What was I thinking when I dreamed up that title for the American Institute of Fisheries Research Biologists symposium at the 2014 American Fisheries Society Annual Meeting? Given the raging debate on whether we’re fishing down, up, or through the food web (Branch 2015, this issue), it seems an indecisive compromise— but it actually reflects what I think about the debate: we’re doing it all. Let me explain: the “fishing down the food web” process was defined as follows: “In unfished areas we can expect ecosystems to be in some sort of balance, often with relatively high abundances of predatory fish. Initially, fisheries may target the larger, predatory, and often higher-priced species. Gradually, the fishing pressure will make the larger species more scarce, and fishing will move towards the smaller species” (Christensen 1996, p. 429). The definition describes an evolutionary process that explains what happens over time as an ecosystem is exploited. For coastal marine ecosystems, this is a process that has taken place over millennia, in deeper waters over decades (Pauly et al. 2003). Fishing down the food web was thus conceived to imply a gradual reduction in the abundance of large, long-lived, hightrophic- level species and a replacement by smaller, short-lived, low-trophic-level, more productive species for both catches and ecosystems. Based on this, I speculated, “We may expect potential catches to increase if we fish out the predators and fish on their prey instead. If the prey is one trophic level below the target fish species, might we be able to increase the catches by a factor of 10?” The factor of 10 comes in because productivity increases by close to an order of magnitude by trophic level, given that the average trophic transfer efficiency between trophic levels is around 0.1 (Pauly and Christensen 1995).

Figure 1. Average fish catch (log scale per unit area per year) vs. average trophic level of the catch for 36 ecosystems (redrawn from Christensen 1996).

Figure 1. Average fish catch (log scale per unit area per year) vs. average trophic
level of the catch for 36 ecosystems (redrawn from Christensen 1996).

Empirically, the factor of 10 is not far off. Based on a suite of ecosystem models, I found that ecosystems in which fisheries were operating one trophic level lower on average had eight times higher catch (Figure 1). So, there is a gain to be obtained by fishing down or through the food web, at least with regard to food quantity. Evaluation of the fishing down the food web process was made operational in a study that used the Food and Agriculture Organization of the United Nations’ catch statistics to show that the mean trophic level of fishery catch (or “mean trophic level of catch”) had declined globally and regionally since 1950 (Pauly et al. 1998). In some regions, notably the heavily exploited Northeast Atlantic, the catches increased over the first part of the time series while mean trophic level of catch decreased, but later on both the catches and mean trophic level of catch decreased. The resulting “backward-bending” time series curves were interpreted as bad news for the ecosystem because fewer and smaller fish being caught is alarming. Since then, many studies have used time series of mean trophic level of catch to evaluate whether fishing down the food web was occurring for a wide range of ecosystems globally (e.g., Stergiou and Christensen 2011). The results have diverged. Sometimes you see it, sometimes you don’t. There are indeed a number of associated biases, as initially pointed out by Caddy et al. (1998), and since then by many others (discussed by Branch 2015). One important bias is that fishing strategies may change because of incentives. Fishing strategies most certainly change, and it is no surprise to me. My father would shift between catching tuna, shrimp, cod, herring, and plaice, among others, all based on season and market conditions. Still, I am convinced that the long-term process that is involved in exploiting natural ecosystems is based on fishing down the food web because ecological history tells us so. It happened in terrestrial ecosystems when hunting was a way of life, and it happens in aquatic systems as a rule. It’s a rule, though, not a law, and market forces and management can certainly change the trajectory. We see this happening now in the parts of the world where fisheries management is effective (Hilborn and Ovando 2014) and fishing pressure is being reduced to the sustainable level. That is good news. Not all parts of the world have good management or reporting systems in place, and we do need information about what is happening in ecosystems. We need indicators, and the mean trophic level of catch is a candidate indicator. It is not perfect— not even close—but it is easy to estimate from catch statistics and available information. Furthermore, it is easy to understand, and it is widely accepted. Combined, this almost makes it a “pretty good” indicator (sensu Hilborn 2010). The mean trophic level of catch has been adopted by the Convention on Biological Diversity (CBD) as a key indicator (known as the Marine Trophic Index) for evaluating the conservation status of marine ecosystems globally. This means that close to 200 countries are obligated to report trends in mean trophic level of catch to the CBD. It encourages the countries to evaluate their catch statistics and consider ecological connections as part of their involvement in the CBD, and this by itself holds a promise of progress. Is reporting mean trophic level of catch meaningful on its own? Not really. There can indeed be numerous explanations for trends in mean trophic level of catch, as is often the case with indicators. Temperature is an example. No doctor would diagnose a patient solely on body temperature. We cannot expect that any single indicator will provide a complete picture. It is necessary to consider more indicators, even though this makes communication to non-scientists less clear. For evaluating trends, a pretty good accompanying indicator to mean trophic level of catch is the fishing-in-balance indicator (Pauly et al. 2000), which evaluates whether a change in catch is matched by a corresponding change in mean trophic level of catch, the logic being that if the mean trophic level of catch decreases, then catches should increase correspondingly if fishing is “in balance.” Two indicators are much better than one, especially when they are easy to estimate and understand and contribute to the conclusions that can be drawn. Still, they are only indicators: indicators of a process, which for unmanaged systems is on a trajectory toward loss of biodiversity but for which smart management systems can change the future. ACKNOWLEDGMENTS With thanks to the American Institute of Fisheries Research Biologists for organizing and supporting the “Are We Still Fishing Down the Food Web?” symposium at the 144th Annual Meeting of the American Fisheries Society in Quebec City. Special thanks to Sean Lucey, Steven Cadrin, and Dick Beamish for the organization and follow-up and to Trevor Branch for good and constructive discussions before, during, and after the symposium. I also thank the two anonymous reviewers for suggestions that improved the manuscript. Funding from NSERC is also acknowledged. REFERENCES Branch, T. A. 2015. Fishing impacts on food webs: multiple working hypotheses. Fisheries, this issue. Caddy, J. F., J. Csirke, S. M. Garcia, R. J. R. Grainger, D. Pauly, and R. F. V. Christensen. 1998. How pervasive is “fishing down marine food webs”? Science 282(5393): 1383a. Christensen, V. 1996. Managing fisheries involving predator and prey species. Reviews in Fish Biology and Fisheries 6(4):417–442. 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