Third Movement: Ecosystem-Based Fisheries Management (EBFM)

Sarah Schumann1

This is the third part of series entitled “The Case for Ecosystem-Based Fisheries Marketing: A Symphony in Four Movements.”

We ended the “second movement” of this series by asserting that the local seafood movement might provide an ideal foundation to import the principles of ecosystem-based fisheries management (EBFM) into marketplace activism. In this “third movement,” we provide a more detailed overview of EBFM, focusing on how its ecosystem-level approach addresses aspects of fisheries that single species fisheries management (SSFM) cannot. As a management framework, EBFM is still “under construction,” and much of the literature that has been published on EBFM is aspirational, rather than applied. This makes it an exciting time to engage seafood supply chain actors from boat to plate in gaining greater familiarity with this framework and helping guide implementation.

What is EBFM?

In its national EBFM Policy, NOAA Fisheries defines Ecosystem-Based Fisheries Management (EBFM) as:

a systematic approach to fisheries management in a geographically specified area that: contributes to the resilience and sustainability of the ecosystem; recognizes the physical, biological, economic, and social interactions among the affected fishery-related components of the ecosystem, including humans; and seeks to optimize benefits among a diverse set of societal goals (NOAA, 2016a).

NOAA’s EBFM Policy is accompanied by an EBFM Road Map declaring that “fisheries should be managed in an ecosystem context to ensure that interacting effects among fisheries, ecosystems, and human activities are accounted for. EBFM is an important approach to deal with changing conditions (NOAA, 2016b).”

These top-level guidance statements portend a growing consensus around the need to move away from the SSFM framework that has dominated modern fisheries management since its inception in the mid-20^th century, and move towards a more holistic EBFM framework. Additionally, many of the United States’ regional fishery management councils (RFMCs)2 have either developed EBFM plans, are in the process of developing EBFM plans, or have incorporated an ecosystem approach into their existing SSFM plans. Together, these trends suggest that a Kuhnian paradigm shift to EBFM (Mangel & Levin, 2005; Francis et al., 2007; Tudela & Short, 2005) is underway.

To comprehend the significance of these shifts, it is helpful to first review the underlying assumptions that have shaped fisheries management until now, to reflect on why these assumptions have been deemed inadequate, and then to contemplate how EBFM may be able to remedy these inadequacies.

SSFM is built on a reductionist framework that conceptualizes ecosystems as collections of single-species populations or stocks (Link, 2010). In fisheries lingo, a “stock” is “a group of fish of the same species that live in the same geographic area and mix enough to breed with each other when mature (NOAA, 2012).” In the SSFM framework, scientific research and modeling is driven towards fine-tuning estimates of stock abundance and biomass (measures of how many fish are in the stock) and measuring fishing mortality (a measure of how many fish are taken from the stock by fishing), and then incorporating these numbers into single-species profiles called stock assessments.

Management processes under SSFM involve comparing stock assessment numbers with pre-established reference points describing desired levels of biomass and fishing mortality, in order to determine whether the biomass and/or fishing mortality of a stock are too low, too high, or just right to achieve the desired yield, or harvest, from the fishery. While the calculations involved are complex, the premise is simple: if biomass and/or fishing mortality are too low or too high, managers can adjust fishing mortality levels by allowing more fishing or less fishing, with the goal of bringing these metrics to their desired levels.

Although SSFM has succeeded at stemming the tide of overexploitation in a number of fishery ecosystems around the world, it is “necessarily incomplete (Fogarty, 2014).” This is because its “underlying assumptions assume that processes internal to a stock and fishing mortality are by far the largest drivers of fish population dynamics (Link, 2010),” an assumption that is often incorrect. “Simply presuming that ceasing exploitation on an overfished stock will result in stock recovery ignores the uncertainty imposed by ecological processes,” according to Link (2002a). “Yet many of our fisheries models and texts implicitly, and often explicitly, assume stock recovery to be a given if fishing effort is reduced.”

SSFM’s blind spots include that it does not address “how a particular stock may be impacted by factors such as species interactions, predation mortality, forage limitations to growth or recruitment, thermal limitations to distribution, and other environmental constraints to growth, distribution, recruitment, etc. (Link, 2010).” Nor does SSFM “provide insights on changes in ecosystem structure and functioning, biodiversity, fishing gear impacts on habitat, needs of protected or rare species, ecosystem effects of discarding bycatch, fishing impacts on energy flows of a food web, etc. (Link, 2010).”

In other words, SSFM is built on a massive oversimplification – and as is often the case with oversimplifications, its long-term consequence is to increase convolution. According to Fogarty (2014), “If biological interactions are important, then trying to optimize the yield from individual species without accounting for these effects can only result in misleading management advice and expectations. When interacting species are covered by separate management plans, these plans unavoidably and actively work at cross-purposes.” And interspecies interactions are only one set of factors that SSFM oversimplifies; as the previous paragraph spells out, SSFM also misrepresents the importance of environmental factors in determining fishery yields.

Interestingly, the partial success of SSFM in recent decades makes ecosystem factors more, rather than less, important in fisheries management. Before the rules of SSFM were made stricter in the 1990s, the impacts of fishing were intense enough to mask these other factors. However, “as fishing mortality rates are brought under control, interspecific interactions, climate and environmental forcing, and other factors become more important relative to the effects of fishing and therefore more critical to address (Fogarty, 2014).”

Despite a growing consensus around the need for EBFM, there is little consensus on what ecological properties EBFM should optimize (Gislason et al., 2000) or how an operating framework for implementation might be constructed (Tudela & Short, 2005). Partly as a result, the long-advocated transition from SSFM to EBFM has been slow (Pitcher et al., 2009) and has faced some resistance from within the fisheries science and management community (Francis, 2007), including “a perception that ‘we don’t actually know how to do it’ (Link, 2002a, 2010).”

While such resistance to innovation may be inevitable in the government arena, where legislative prescriptions and the threat of litigation may constrain fisheries managers’ appetite to try new things, the private sector can get away with being more imaginative. The vision of a marketplace-based analogue to EBFM that we will describe in the “fourth movement” of this series proceeds from this hopeful prospect. In our “first movement,” we described how sustainable seafood movement leaders paired consumer activism with policy advocacy in the 1990s, so that initiatives like the Marine Stewardship Council (MSC) and Seafood Watch reinforced efforts to end overfishing through the 1996 Sustainable Fisheries Act.3 We suggest that a similar two-track strategy might yield similar gains for EBFM.

Through the launch of EBFM-based marketplace initiatives, it may be possible to accustom seafood supply chain actors, consumers, and policy makers to thinking about seafood in terms of ecosystems, thereby leveraging the “discursive effects” (Bostrom & Klintman, 2008; see the “first movement” of this publication) of such initiatives. Such “practice” may help overcome the entrenchment of reductionist single-species thinking and instate a more systems-based conceptual framework, while enabling stakeholders to test-drive ecosystem-based paradigms in the marketplace before fully committing to EBFM in the government sphere. Before any of that can happen, however, we must establish what the objectives of any ecosystem-based approach should be. We turn our attention to this task below.

Shifting into ecosystem-level thinking

Because EBFM operates at a higher level of ecological organization than SSFM – the ecosystem, rather than its constituent species – it must define goals at the ecosystem level, too. The stock-based reference points that are the foundation of SSFM are only minimally useful in EBFM, and EBFM requires ecosystem-level objectives that can be paired with ecosystem-level indicators to tell managers whether ecosystems are meeting, or failing to meet, these objectives.

In this section, we will review the objectives of SSFM and the process through which SSFM operationalizes its objectives through stock-based reference points. In the following section, we will discuss how the objectives of EBFM might be defined, and in the section after that, we will consider what kind of metrics might take the place of SSFM reference points in an ecosystem-based management framework.

As noted above, SSFM revolves around a set of standards, or reference points, that are applied at the stock level. Reference points are computed for each stock with the goal of attaining Maximum Sustainable Yield (MSY) from the stock. MSY is “typically thought of as the largest average catch that can be continuously taken from a stock under existing environmental conditions. That is, maximum sustainable yield is the greatest number of fish that can be caught each year without impacting the long-term productivity of the stock (Cooper, 2006).” Scientists use available information on a fish stock’s growth rate, reproduction, natural mortality, and fishing mortality to project the size of the stock in the future. Then, they compute a harvest level that is predicted to result in MSY from the stock year after year.

For many stocks, computation of MSY involves an assumed relationship between the size of the stock and its rate of increase. Such “stock-recruitment” models presume that a stock’s rate of increase will decrease as a stock approaches its carrying capacity (defined as the maximum population size that a stock can attain given current environmental conditions, such as availability of prey, abundance of predators, and habitat limitations). Because fish stocks are thought to compensate for fishery removals by producing more fish, SSFM holds that decreasing the size of a fish stock relative to its carrying capacity through fishing actually increases the overall production from that stock, above what it would be if it was not fished at all. This “surplus production” can then be captured by the fishery year after year, the theory goes.

To maximize yields from a fishery (i.e., attain MSY), scientists calculate the precise level of harvest that will cause a stock to generate the largest amount of biomass as a result of surplus production. As a general rule of thumb, most populations produce MSY when they are fished down to about 50% of their virgin biomass (i.e., what their population biomass would be in the absence of fishing). By allowing fishing at this level – and no greater – SSFM attempts to maximize annual production from a stock without undercutting the stock’s ability to produce the same amount of production in future years.

This “surplus production theory” is the foundation of SSFM. “Briefly the dogma was this,” wrote Larkin (1977) in his essay, “An Epitaph for the Concept of Maximum Sustained Yield.” “Any species each year produces a harvestable surplus, and if you take that much, and no more, you can go on getting it forever and ever.” During the 20^th century, driven by the era’s “mechanistic worldview” (Mangel and Levin, 2005), MSY became “enshrined in national policy documents, incorporated in international treaties, and, in effect, became synonymous in most people’s minds with sound management (Larkin, 1977).”

In the 1970s and 1980s, when U.S. fishing fleets were small, surplus production theory dictated that fisheries managers should build up harvesting capacity to the point at which it was capable of maximizing -- and capturing -- surplus production. But by the end of the 20^th century, when many fish stocks were being fished at harvest levels higher than their scientifically determined MSY (i.e., overfished), this theory dictated a reduction in harvests to end overfishing. As a result, a new conservationist paradigm took hold in fisheries management and many stocks entered “rebuilding” plans. As we saw in our “first movement,” around this time, MSY became embedded not only in SSFM but also in the “back stage” workings of the sustainable seafood movement, where it remains foundational to efforts such as the MSC, Seafood Watch, and other certifications and ratings schemes.

Although Larkin’s 1977 “epitaph” was at least four decades premature in declaring MSY obsolete as a basis for fisheries management, it gave voice to a growing disillusionment with single-species metrics as a basis for fisheries management. Since that time, many scientists have echoed these feelings. Their critiques revolve around two claims: first, that SSFM ignores environmental factors, and second, that it ignores relationships between species (Fogarty 2014). We will address each of these points in turn, and reflect on how EBFM may help rectify these shortcomings.

The first claim – that SSFM ignores environmental factors – is based on an observation that the modeling of fish stock dynamics generally assumes static environmental conditions and has typically failed to consider that these conditions might vary or change as a result of natural or human drivers. SSFM’s myopic focus on a single driver of change on yields -- the impact of fishing mortality -- may be due to the fact that in some legal frameworks, including the framework established under the U.S. Magnuson Stevens Fishery Conservation and Management Act, this is the only factor that fishery managers are authorized to control (Caddy and Cochrane, 2001).

However, the need to account for the role of environmental variables has become increasingly apparent as some overexploited fisheries have struggled to rebuild despite imposition of strict rebuilding plans. For these fisheries, management may not be successful without better understanding of how environmental variables affect production (Caddy and Cochrane, 2001). Environmental effects include both natural cyclical changes, such as El Nino, as well as human-induced climate change, eutrophication and degradation of coastal ecosystems, which are to some degree within human control (Caddy and Cochrane, 2001; Caddy and Seijo, 2005). According to Caddy and Cochrane (2001), “These factors must now be added to the previously narrower definition of the scope of fisheries management (namely to control fishing effort) and clearly fisheries and environmental management must be combined in some way in the future.”

The second claim – that MSY ignores relationships between species – has been accompanied by calls for fisheries management to shift from a basis in population ecology (a focus on understanding dynamics of a single population or stock, where other species are only considered inasmuch as they affect target species) to a basis in community ecology, which focuses explicitly on interactions between stocks and species (Mangel and Levin, 2005). Anchoring fisheries management in a community ecology perspective may lead to different guidance and strategies than under the current population ecology perspective.

Perhaps most importantly, a community ecology perspective calls into question the notion that achieving MSY simultaneously for multiple harvested and interacting species – a goal that is implicit in SSFM – is even possible. As Larkin remarked in his 1977 “epitaph,” “To speak of MSY for any one of the fish species in effect argues that somehow or other the interrelations among the species won’t have any effect. While this could be true in the short-term, it is difficult to imagine in the long-term.” Brown et al. (1976) confirmed this supposition through modeling, and found that the sum of single-species MSY estimations for all exploited species in the Northwest Atlantic was greater than the level of production estimated to be possible from the system as a whole. In the ensuing decades, “Results from a wide spectrum of multispecies and ecosystem models support the view that simultaneously extracting single-species MSYs from an assemblage of interacting species is not possible (Fogarty, 2014).”

Because “it may be energetically impossible to simultaneously maximize yields for multiple species (Link, 2002b, 2010),” a more honest view of fisheries management might start by considering which stocks the management system should attempt to maximize, and abandon the notion of attaining MSY for others. This is why Link (2010) states, “Without confronting tradeoffs directly, we will never be able to do EBFM. Doing EBFM is all about confronting tradeoffs.” To be clear, EBFM does not create interspecies tradeoffs; it simply acknowledges them, in the same way that SSFM does not resolve interspecies tradeoffs; it simply ignores them.

EBFM’s explicit admission of tradeoffs is intended to manage expectations about what an ecosystem can deliver. For instance, it is not possible to maximize populations of competing species at once, or maximize the production of both a predator and its prey. In its myopic focus on managing the parts of an ecosystem (i.e., fish stocks), SSFM has given little consideration to the relationships between them (Murawski, 2000), and how these relationships may undermine the very objectives that SSFM seeks to attain. Fogarty (2014) remarks: “Unfortunately, trade-offs do not go away when ignored. They do, however, lead to suboptimal decisions and outcomes.”

Objectives of EBFM

Now that we have illustrated the insufficiency of single-species sustainability benchmarks like MSY for managing fisheries in an ecosystem context, we turn to the question of what goals, if any, might be more appropriate at the ecosystem level. Is there such a thing as “sustainability” for an ecosystem as a whole? If so, what exactly are we trying to sustain? Specific ecosystem components that we value the most? Specific ecosystem services? A particular ecological configuration? A set of ecosystem processes? System-level properties, like “biodiversity”? Something more abstract, like “resilience”? These questions are not only at the core when moving forward with EBFM, but also when designing the “fourth movement” that we are calling “ecosystem-based fisheries marketing.”

As we probe further into this line of thought, the false security associated with SSFM gives way to unsettling ambiguity. Untethered from the reductionist simplicity (or oversimplicity) of MSY, we find ourselves sliding into a sea of competing values and bumping up against the inevitable limits of what science can know, predict, or control about the natural world. If we grasp for familiar laymen’s concepts like ecosystem “health” and “integrity,” we find that they crumble under the lens of scientific scrutiny. According to Link,

Ecosystem health is ill-defined and a misnomer… [E]cosystems can exhibit multiple states that are just as functional as any other. Some states are certainly more desirable than others, but all are viable... Ecosystem integrity is also an ill-defined term often used in the context of ecosystem sustainability. How does one measure, reproduce, or evaluate integrity? This term implies that unless something is done, whatever that may be, the critical processes in an ecosystem will break and cease to function… [In reality] ecosystems will continue to function, albeit at different configurations (Link 2002b).

Since no ecosystem configuration is objectively superior to any other configuration, science alone cannot specify what the goals of EBFM should be. Rather, deciding what to aim for in the ecosystem context is a public policy question. In the U.S. fisheries management setting, it is a question for the regional fisheries management councils to answer with input from stakeholders and in keeping with their mandates as outlined by the Magnuson Stevens Act. Answering these questions is the first step in constructing a theory of change behind what EBFM initiatives seek to accomplish. Although this paper cannot offer clear directives on these questions, we will review a few reflections that have been put forth by leading thinkers in the scientific community.

Fogarty (2014) proposes that the objective of EBFM could be “to maintain system-wide productivity within defined bounds and establish mechanisms to protect individual ecosystem components” and “to provide sufficient resilience to allow the system as a whole to remain within stochastic bounds defined by past levels of variability.” To do this, he says, “We should replace the concept of single-species MSY, with its focus on time-invariant equilibrium processes, with a dynamic ecosystem yield concept that recognizes shifting environmental states and the probabilistic nature of production processes at different levels in the food web.”

Cury et al. (2005) propose a “viability approach” that “recognizes the indeterminacy of natural systems and the difficulty of achieving consensus around goals.” Observing that it may be easier to agree on the ecosystem properties that one wishes to avoid, rather than those that one wishes to achieve, these authors state:

In a system where uncertainty is overwhelming… the best strategy might not be to optimize the goods and services that can be extracted from the different species available, but rather to define the range of catches of the different species that can be extracted without compromising overall ecosystem dynamics.

Other scientists have suggested other frameworks. Link (2002b) proposes the term “ecosystem state sustainability” to refer to the persistence of a desired state in a system. Zabel et al. (2003) propose the phrase “ecologically sustainable yield” (ESY, as opposed to MSY), which they define as “the yield an ecosystem can sustain without shifting to an undesirable state.” Murawski (2000) proposes a concept that he calls “ecosystem overfishing,” defined as a condition under which fishery catches, non-harvest mortality, and habitat degradation result in any of the following:

• the biomass of at least one important species assemblage falls below minimum biologically acceptable limits,

• diversity of communities or populations declines significantly as a result of fishing, selective harvesting, or other factors;

• selective harvesting and harvest rates lead to greater interannual variation in population that would result from lower harvest rates;

• changes in species composition or population demographics as a result of fishing decrease the resilience of the ecosystem to nonbiological disturbance;

• harvest rate patterns among interacting species lead to lower cumulative net economic or social benefits that would result from a less intense overall fishing pattern;

• harvest of prey species impairs the viability of ecologically important non-resource species such as mammals, turtles and seabirds.

A commonality across these proposed frameworks is the notion that fishery harvests (and other human impacts) should be managed to avoid pushing an ecosystem into a state that lies beyond some sort of multidimensional limit. This is akin to the socio-ecological notion of “resilience,” which may be defined as “the capacity of a system to absorb disturbance and reorganize while undergoing change so as to retain essentially the same function, structure, identity, and feedbacks (Walker et al., 2004).⁠” As resilience declines, ecosystems are thought to become more vulnerable, enabling progressively smaller external events to cause major shifts (Folke et al., 2004).

By and large, resilience thinkers come from a very different epistemological background than fishery scientists, one with roots in ecology, geography, and anthropology. Their thinking is focused less on the kind of quantitative certainty that occupies fisheries scientists, and more on setting up socio-ecological conditions that can thrive under uncertainty. Some resilience thinkers call for a change from the existing paradigm of command-and-control or “stabilized optimal production” – SSFM being one example -- to one based on designing adaptive systems in uncertain environments to secure essential ecosystem services (Holling & Meffe, 1996).

In our view, resilience thinking has much to offer in the context of EBFM. Grounding EBFM in resilience thinking -- rather than attempting to replicate the kind of “static optimal production” framework that forms the basis for SSFM -- averts unresolvable questions such as what the optimal ecosystem state would look like, and acknowledges that even if we could define an optimal state, we almost certainly lack the tools to attain it.

In the next section, we turn our attention to the topic of ecosystem-level assessment. If objectives (the subject of this section) are expressions of “what we are trying to accomplish” through management, then assessment (the subject of the next section) is the means of knowing whether we’re accomplishing it, and of helping us figure out what we need to do differently if we’re not. To set up a successful operating framework for EBFM, any objectives that are chosen will ultimately need to be measurable in some way; if they are not, then they will be purely aspirational and not operational. In the next section, we review current thinking on what kinds of assessment and measurement may be appropriate for informing EBFM.

Assessing the state of an ecosystem

As with goal-setting, assessment and tracking will mean something different at the ecosystem level (under EBFM) than at the stock level (under SSFM). Although it is tempting to search for metrics of ecosystem state that can serve as ecosystem-level analogues to the stock-based reference points used in SSFM (e.g., NEFMC 2010), it seems likely that “[o]wing to its systemic nature… the knowledge of exploited marine ecosystems will never permit at the ecosystem level the kind of mechanistic approach usually followed in single stock management (Tudela & Short, 2005).”

Many observers have concluded that no single metric can reflect multiple ecosystem goals simultaneously (Murawski, 2000) and that it may be more appropriate, when thinking at the ecosystem level, to base management on a suite of metrics (Bundy et al., 2010; Link et al., 2002; Link, 2005). Moreover, since indicators of ecosystem state tend not to be absolute (Bundy et al., 2010), managers may need to evaluate them along a gradient rather than as binary decision criteria (Link, 2005). Link et al. (2002) conclude that concept of reference “directions” may be more useful in EBFM than reference “points,” although for many indicators it may be also be feasible and useful to set up warning thresholds and limits that would trigger a greater level of scrutiny and management action if reached (Link, 2005).

Following these lines of thinking, some authors have proposed the concept of an indicator dashboard. Such a dashboard could include a suite of biological, physical, and even socioeconomic indicators (Link, 2010). Appropriate indicators should be directional, sensitive to change, unambiguous, and expressive or representative of key processes (Link, 2010). They should illuminate at least one of four ecosystem attributes that are relevant to ecosystem state: resource potential, ecosystem structure and functioning, conservation of functional diversity, and ecosystem stability and resistance to perturbations (Bundy et al., 2010). Some indicators, at least, must be responsive to fishing, so that they show something about the impacts of fishing on an ecosystem and can be addressed through fisheries management (Coll et al., 2010; Rice, 2000).

Below, we review a handful of indicators that have been proposed for inclusion in EBFM indicator dashboards.

Biomass of the system. The total biomass of all species in a system may be a useful indicator of resource potential (i.e., availability of fish to harvest). This indicator is expected to decline as a result of heavy fishing pressure (Bundy et al., 2010).

Species composition. The composition of species within a system is related to ecosystem structure and function. Changes in species composition are also important to note from an economic and marketing perspective.

• Species richness is the number of species in the system (Link, 2005). A decline in species richness would presumably indicate perturbation of the ecosystem and is likely to make the system more vulnerable to shocks.

• Species diversity is a composite of richness (number of species present) and evenness (how close their abundances are). Fisheries can alter diversity through unequal removals of target and non-target species (Rice, 2000). However, diversity indices can be difficult to interpret because they combine two facets – species richness and evenness -- which “may work in opposite directions and their effects are confounding, so that major changes in a community may result in similar diversity indices (Bianchi et al., 2000).” As a result, there is no clear optimal value (Murawski, 2000) and interpreting diversity indices often requires scientists to look at constituent species to understand trends (Rice, 2000).

• Biomass of key functional groups4 is an important indicator because changes in functional group biomass can reflect changes in energy flow within a system. Moreover, some community configurations (relative aggregate biomass of one group versus another) may be more desirable from a commercial perspective or less sustainable from an ecological perspective than others (Link, 2005).

  • Total biomass of flatfish: an increase in flatfish biomass can indicate a heavily fished ecosystem (Link, 2005).

  • Total biomass of pelagic fish within a system: an increase in pelagic biomass can indicate predatory release,5 while a decrease in biomass may indicate insufficient forage base (Link, 2005).

  • Total biomass of scavenger populations (e.g., crabs, sculpins, starfish): scavenger populations tend to increase after fishing pressure is applied to an area, and may indicate excessive fishing pressure.

  • Biomass of gelatinous zooplankton: blooms of gelatinous zooplankton can be associated with overfishing, climate change, and eutrophication (Link, 2005).

• Species composition can also be conceptualized in proportional terms.

  • Proportion of predatory fish in a system: this indicator is expected to decline under heavy fishing pressure (Bundy et al., 2010).

• Community structure can also be assessed through the use of ordination techniques (matrices showing the abundance of different species at different sampling sites) and dominance curves (graphs in which species are arranged in ranked order of abundance).

  • Ordination techniques: differences across an ordination matrix can highlight differential impacts of fishing on different species (Rice, 2000).

  • Dominance curves: changes over time in the steepness of the curves can highlight differential impacts of fishing on trophic structure (Rice, 2000).

Size. In terms of food web structure and function, size can be just as important as species. Size is relevant to ecological processes (it is a key factor in determining “who eats whom”), can be affected by fishing pressure, and has relevance for market potential (Link, 2005). Size-based indicators can be useful for detecting changes in size composition of organisms within a system, but they may be misleading in systems where there is large variation in recruitment of key species, because a very large year class will increase the proportion of smaller animals at first, and of larger animals in later years (Bianchi et al., 2000)

• Mean length of all species (Bundy et al., 2010; Link, 2005)

• Steepness of the slope of the size spectrum of all species in a system6 (Bianchi et al., 2000; Link, 2005)

Interactions. Another indicator of trophic relations is the mean number of interactions per species. This measure reflects the interconnectedness of a food web, which relates to its stability. Changes in this metric over time indicate changes in the structure and resilience of a food web (Link, 2005).

Lifespan. Mean lifespan of species within a system has been proposed as an indicator of ecosystem stability and resistance to perturbations (Bundy et al., 2010). This indicator is expected to decline under heavy fishing pressure (Bundy et al., 2010).

Fishery removals. All of the indicators we have discussed up to this point have focused on aspects of the organisms in the ecosystem, which are assessed through fisheries-independent scientific surveys. Another class of indicators looks at fishery landings and discards.

• Total volume of fishery removals: ecosystems can only produce a fixed amount of biomass per unit time; landings above a threshold may indicate that a warning boundary has been exceeded (Link, 2005).

• Ratio of total biomass to total landings (“inverse fishing pressure”): a reflection of the proportion of total biomass in the system that is removed by fishing (inverted so that it declines as a function of fishing, making it easier to interpret; Bundy et al., 2010).

• Percentage of primary production required to sustain fisheries (%PPR): a reflection of the ecological footprint of fisheries (Tudela et al., 2005).

Other landings-based indicators focus on the trophic level of landings:

• Mean trophic level of landings (TL): a reflection of the effects of fishing on different food web components (Tudela et al., 2005). This indicator is expected to decline with heavy fishing pressure (Bundy et al., 2010). This may occur as a result of “fishing down the food web,” in which fisheries sequentially shift to fish species at lower trophic levels as upper trophic levels are depleted (Pauly et al., 1998), or as a result of “fishing through the food web,” in which reductions in mean trophic level of landings result from sequential additions of fish species at lower trophic levels to the landings mix (Essington et al., 2006).

• Ratio of the primary production required to sustain fisheries (%PPR) to the mean trophic level of catches (TL): according to Tudela et al. (2005), “For a given %PPR, a fishery with a higher TL would be less disruptive than a fishery with a lower one. For a given TL, a fishery with a lower %PPR would be less disruptive than a fishery with a higher one.”

What the foregoing discussion has shown is there is no “one size fits all” approach to assessing the current status of an ecosystem relative to the desired status of an ecosystem, in the same way that SSFM assesses stock biomass and fishing mortality relative to stock-specific biomass-based reference points. Despite Bundy et al.’s (2010) assertion that management “requires clear objectives, reference points, and control rules (that specify a management response when objectives are not met),” EBFM may never be able to match the “analytical and regulatory tractability” of MSY-based management or the degree to which SSFM provides for “the adoption of clearly defined standards for assessment and management (Fogarty, 2014).” This does not mean that EBFM is not worth pursuing or that fisheries managers should stick with SSFM. Rather, it means that the management system must find ways of tolerating greater levels of complexity and nuance as a fact of life.

Management strategies under EBFM

Until this point, we have discussed a suite of possible objectives for EBFM and a suite of indicators that can be used to measure ecosystem state relative to chosen objectives.

Together, these elements constitute what is needed to think at the ecosystem level. But what does it mean to act at the ecosystem level? In this section, we will review suggestions put forth in scientific literature and policy documents that spell out how decision-making and rule-setting might work under EBFM.

The basic unit of fisheries management in the U.S. is the Fishery Management Plan (FMP). FMPs are promulgated by the eight RFMCs¹ for all commercially or recreationally important stocks under their care. Creation of FMPs is laid out as a fundamental duty of the RFMCs in the Magnuson Stevens Act of 1976 and its subsequent reauthorizations, which dictate:

Each Council shall, in accordance with the provisions of this chapter—

(1) for each fishery under its authority that requires conservation and management, prepare and submit to the Secretary [of Commerce] (A) a fishery management plan, and (B) amendments to each such plan that are necessary from time to time (and promptly whenever changes in conservation and management measures in another fishery substantially affect the fishery for which such plan was developed) (16 U.S. Code § 1852(h)(1).

The Act also lays out the content that each FMP should include. Briefly, it states that FMPs should contain conservation and management measures to prevent overfishing and rebuild overfished stocks and to protect, restore, and promote the long-term health and stability of each fishery. Among other provisions, FMPs are required to:

(10) specify objective and measurable criteria for identifying when the fishery to which the plan applies is overfished… and, in the case of a fishery which the Council or the Secretary has determined is approaching an overfished condition or is overfished, contain conservation and management measures to prevent overfishing or end overfishing and rebuild the fishery;

(15) establish a mechanism for specifying annual catch limits in the plan (including a multiyear plan), implementing regulations, or annual specifications, at a level such that overfishing does not occur in the fishery, including measures to ensure accountability.

FMPS are also required to: identify essential fish habitat (EFH) for governed stocks; minimize, the extent practicable, adverse impacts to EFH caused by fishing; to identify other actions to encourage conservation and enhancement of EFH; to establish a standardized reporting methodology to assess the amount and type of bycatch occurring in the fishery; and to minimize, to the extent practicable, the amount of bycatch and bycatch mortality (16 U.S. Code § 1853(a)).

Each RFMC issues regulations through amendments and framework adjustments to its FMPs that are developed at intervals by FMP-specific Plan Development Teams (PDTs) consisting of members appointed from the scientific, government, and stakeholder communities. An FMP and its associated amendments and adjustments may govern a single species or stock, or a collection of interacting stocks that are caught together in the same area. For example, the Mid-Atlantic Fishery Management Council’s Bluefish FMP governs only bluefish (Potamus saltatrix), while the Pacific Fishery Management Council’s Groundfish FMP governs 86 species of skate, rockfish, cod, whiting, and flounders.

The siloed approach that characterizes SSFM is evident in many aspects of the structure we have just described. Populations that may be closely interconnected in the ocean (e.g., predators and prey) are often assigned to separate FMPs. Actions taken under FMPs are developed and proposed by teams who have expertise the specific fishery or fisheries assigned to each FMP, but not necessarily in other fisheries or aspects of the ecosystem. Annual catch limits are developed for species under each FMP based on single-species stock assessments and overfishing definitions calculated at the stock level, as described in earlier sections of this article, by scientists who are often experts in only those stocks. In conclusion, the FMP structure is inadequate for managing fisheries at the ecosystem level because each FMP breaks off a small chunk of the ecosystem and focuses on it in isolation from the rest of the system.

To refocus fisheries management on the whole-ecosystem level, supporters of EBFM recommend overlaying or replacing FMPs with Fishery Ecosystem Plans (FEPs). NOAA’s EBFM Road Map (NOAA, 2016b) defines FEPs as follows:

Fishery Ecosystem Plans (FEPs) are policy planning documents that the Councils or NOAA Fisheries may use to describe ecosystem objectives and priorities for fishery science and management, and to inform development of FMPs or FMP amendments… FEPs provide fisheries management with ecosystem-scale information on fundamental physical, chemical, biological, and socio-economic structures and functions of LMEs. They are valuable for describing the relationships between LMRs [living marine resources], human uses of those resources, and other human activities that affect LMRs and their habitats. By exploring fishery management options that simultaneously address multiple objectives, they may help the Councils, Commissions, tribes, RFMOs [regional fishery management organizations], NOAA Fisheries, and other agencies better address the cumulative effects of our actions on the environment.

The Road Map states that FEPs can “serve as comprehensive management tools that incorporate trophic relationships among marine predators, prey, habitat, and human activities,” and it pledges NOAA’s support and guidance to RFMCs to “execute FEPs that are used as umbrella strategic planning documents to guide coordination and trade-off evaluation among Fishery Management Plans (FMPs), related documents, and other ecosystem components.”

Unlike FMPs, which treat stocks or species as the basic unit of management, FEPs are place-based. Examples of FEPs which have already been developed around the U.S. are displayed in the table below. Some of these FEPs are used as complements to existing FMPs, while others have replaced FMP-based management.

As discussed earlier in this article, one of the primary advantages of EBFM over SSFM is that it enables frank discussion about tradeoffs among competing objectives – for example, whether to maximize harvests of a predator species or its prey. EBFM practitioners have embraced a decision support framework called the Management Strategy Evaluation (MSE) to help managers and stakeholders weigh different potential management actions at the ecosystem level. When undertaking an MSE, managers utilize whole-ecosystem operating models to simulate the outcomes of alternative management strategies. An ecosystem model can be anything ranging from a qualitative conceptual model, to a quantitative food web model that integrates the relationships among predator, prey, and competitor relationships, to a complex whole-system model that encompasses a full range of physical, chemical, geological, biological, and socio-economic dimensions.

Through MSE, managers and stakeholders can “play around with” different potential actions and discover, through the model, how each simulated action may affect the many interconnected components present in a complex ecosystem. Then they can deliberate and ultimately select courses of action that align with system-level societal priorities. The range of priorities considered may include stock-level outcomes, such as yields of particular species of interest, as well as ecosystem-level priorities that are quantified with the kind of indicators that we presented in the previous section.

An advantage of the MSE approach is that it “forces the clarification of objectives, the evaluation of trade-offs, and the balancing of different views about the dynamics of resources and ecological dependencies and interactions (Sainsbury et al., 2000).” Another advantage is that it “emphasizes broad input from managers, stakeholders, and scientists… For example, hypotheses, performance measures, and candidate management strategies can be developed conceptually by these parties (Sainsbury et al., 2000).”

However, the approach also introduces new challenges. Namely, “The application of MSE to examine a wider range of ecosystem- and resource-use objectives will involve dealing with much greater levels of uncertainty and complexity than has been attempted to date (Sainsbury et al., 2000).” According to Collie et al. (2016), “The increase in holism that motivates the move towards EBFM can reduce uncertainty in management predictions if the appropriate data are available, but eventually the increase in the number of parameters will begin to increase uncertainty.”

NOAA’s EBFM Road Map acknowledges this, and states that investing in modeling capacity will be critical to the success of EBFM:

This is because a wide range of information and objectives needs to be synthesized and integrated… Before establishing reference points against which objectives can be measured, and before establishing MSE protocols and processes, the analytical basis for exploring ecosystem dynamics is required (NOAA 2016b).

Conclusion

As this review has hinted, U.S. fisheries management finds itself at an “in-between” stage. The need to shift to EBFM has been recognized for well over twenty years, yet the strictures of SSFM remain very much in place, entrenched in everything from the federal legislation that governs our nation’s fisheries to the norms of our fisheries science and management institutions to the mindsets of many of the individuals involved. If this feels confusing, perhaps it is because, as Tudela and Short (2005) observe:

…the [EBFM] concept has generated a situation that resembles a Khunian [sic] revolution (Khun [sic], 1962). It is obvious that [EBFM], if understood as a real change in the underlying paradigm of fisheries science, is challenging the validity of classical [SSFM] approaches. This is leading to a well-known situation (inherent to all scientific revolutions) of interim co-occurrence of both approaches, whose advocates are radically opposed to each other, generating a feeling of crisis. What makes this situation even more dramatic is that it concerns an ‘applied science’, one that is expected to help manage fundamental global food resources...

In the fourth and final “movement” in this series, we will outline a vision for a market-based “companion” movement to EBFM. In much the same way that the sustainable seafood movement played a role in escorting more robust and stringent SSFM measures into place through its discursive effects and market pull, we hope that a new, place-based marketplace accompaniment can likewise result in greater acceptance and momentum for EBFM as it struggles to break through this phase of Kuhnian “crisis.”

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