ICES Journal of Marine Science - fishlarvae.org · production cognizant of ecosystemfactors Identify levelsof optimal stock production Evaluatecross-sector cumulative effects Evaluatewithin-sector

Contribution to the Themed Section: ‘Integrated assessments’

Introduction

Integrating what? Levels of marine ecosystem-based assessmentand management

Jason S. Link1* and Howard I. Browman2

1National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Office of the Assistant Administrator, 166 Water St, Woods Hole,MA 02543, USA2Marine Ecosystem Acoustics Group, Institute of Marine Research, Austevoll Research Station, 5392 Storebø, Norway

*Corresponding author: tel: 1 508 495 2340; fax: 1 508 495 2258; e-mail: [email protected]

Link, J. S., and Browman, H. I. 2014. Integrating what? Levels of marine ecosystem-based assessment and management – ICESJournal of Marine Science, 71: 1170–1173

Received 19 September 2013; accepted 31 January 2014; advance access publication 19 March 2014.

Integrated assessment requires examination of factors across biologicalhierarchies, taxonomic groups, ocean-use sectors, management objec-tives, and scientific disciplines. The articles in this theme set representattempts to clarify and elaborate upon what integrated assessments are,with a particular emphasis on how they are being implemented. Theaim of this themed article set is to clarify the use of integratedassessmentterminology and demonstrate, by presenting case studies, examples inwhich integrated ecosystem assessments serve as useful tools to imple-ment ecosystem-based management (EBM) while also identifyingchallenges that must be overcome for this to succeed.

In theory, EBM seeks to address the various natural and an-thropogenic pressures faced by the key components of marinesystems simultaneously. EBM also attempts to account for “cumu-lative impacts” that might otherwise be overlooked. Nascentattempts to implement EBM highlight the need—in practice—toaddress trade-offs across multiple objectives for a given system, ina coordinated and comprehensive manner. During the pastdecade, the discussion over EBM has shifted from “what is it andwhy should we do it” (Link, 2002; Browman and Stergiou, 2004,2005) to “how can we do it and when can we operationalize it”(Arkema et al., 2006; Link, 2010; Berkes, 2012). Marine EBM (e.g.Levin and Lubchenco, 2008; McLeod and Leslie, 2009) and similarecosystem-based efforts for more specific ocean-use sectors, such asecosystem-based fisheries management (EBFM; e.g. Pikitch et al.,2004; Link, 2010) or integrated coastal-zone management (e.g.Cicin-Sain and Knecht, 1998; Moksness et al., 2013), have becomethe mandated approach to managing ocean resources. EBM is a

major policy objective of many marine-oriented organizations—asis clear from a perusal of the strategic plans of organizations such asICES, PICES, FAO, UNEP, and NOAA. The need for integratedassessments frequently arises in the context of discussions overimplementing EBM.

The term “integrated assessments” is perceived as mysterious andultimately unhelpful because it suffers from a plurality of definitionsand it is used in a multitude of contexts—i.e. it has high linguistic un-certainty. That is why we pose the question in the title of this introduc-tion: what are we integrating and, hence, what are we assessing?

Returning to the EBM context for sustainably managing marineresources, we note that there are, in fact, multiple levels at which an“ecosystem approach” can be adopted in practice. To illustrate, wefocus on the fisheries sector. There are levels of application for EBMthat focus solely on fish stocks, levels that focus on fish stocks butwith ecosystem considerations incorporated, ecosystem levels thatfocus solely on the fisheries sector but for the full system of fisheriesand stocks, and the full set of ocean-use sectors impacted by andimpacting the fisheries sector (Table 1). For example, considerforage stocks such as small pelagic fish. For an ecosystem approachto fisheries (EAF) that takes a stock focus, one would need to considerthe effects of environmental factors (e.g. temperature changes orNAO events) and ecological factors (e.g. predator removals ormodels of multispecies interactions) in addition to targeted fisheriesremovals to truly grasp what is driving the population dynamics ofsuch stocks. Using the same type of focal species as an example, forEBFM that takes a system focus in the fisheries sector, one would

Published by Oxford University Press 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

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have to consider not only the impacts of other factors on these foragestocks, but also the dynamics of these forage stocks on other parts ofthe ecosystem. For instance, there are seabirds or marine mammalsthat have some form of protected or conservation status and thatare highly dependent on small pelagic forage fish. There are commer-cially targeted groundfish that are also major predators of these smallpelagic forage fish. There are also multiple fisheries operating on boththe groundfish and the small pelagic species. In such a case, clearly amore integrated, “bigger picture” evaluation of the whole system andhow itfits together isneeded toaddress thepotential trade-offsamongthe different uses of and impacts to these forage stocks. Further, ifthese forage stocks represent a key pathway of energy from lowertrophic levels to upper trophic levels (which they typically do), thenthe resilience, structure, and functioning of the system would needto be evaluated. For an EBM that covers all ocean-use sectors, consid-eration of these small pelagics and their role in the ecosystem is war-ranted in a broader context for anthropogenic drivers such as powerplant discharges (thermal impacts), eutrophication, toxin deposition,hydroelectric energy generation, dredging for navigation safety, andsimilar uses that might impact the habitats of these species. One can en-visionsimilarexamples forotherocean-use sectors,but facets of this fullrange of considerations across different levels of EBM are demonstratedin Mollmann et al. (2014). The salient point being that one can do inte-grated assessments at all these levels of application, but they are calleddifferent things.

For EBM that focuses only on single species of fish (Table 1, EAF),integrated stock assessments can/have been used. Certainly, classical

stock assessments integrate a wide array of standard data streams (e.g.Fournier and Archibald, 1982; Methot, 1989; Punt and Hilborn,1997;ICES, 2012). Here, integrated stock assessments, although oftentermed integrated assessments or integrated analyses, are referringto other factors beyond the typical catch, abundance, and biologydata, particularly bringing more statistical techniques and approachesinto consideration. These integrated stock assessments have been dis-cussed in many other contexts (e.g. Fournier and Archibald, 1982;Maunder and Punt, 2013; Methot and Wetzel, 2013). In this EAFcontext, such integrated stock assessments use extended stock assess-ment models that incorporate other facets of the ecology, oceanog-raphy, or environment to explain and predict stock dynamics (e.g.Maunder and Watters, 2003; Methot and Wetzel, 2013). A growingbodyof multispeciesmodelscan also explore somefacets of thesecon-siderations (e.g. Townsend et al., 2008; ICES, 2011) and, althoughthey could be used in an integrated stock assessment process andtheir outputs are often used as inputs into extended stock assess-ment models, they are not typically termed integrated stock assess-ment models themselves. Mollmann et al. (2014) provide anexcellent example covering the range of assessment models used toinform the management of living marine resources in the Baltic.Their ensemble approach of using multiple models to inform thedecision-making process has strong potential for both integratedstock assessments and advancing EBFM more broadly by providingmultiple perspectives on the same problem without being biasedfrom using onlya limited set of model assumptions, model structures,or modelling frameworks.

Table 1. Levels of application for EBM for the fisheries sector, with notes on particular features of each level

Feature

Level of EBM in fisheries sector

EBM EBFM EAF Classical FM

Sectoral focus All Fisheries Fisheries Fisheries

Focus of thebiologicalhierarchy

All Community/whole system Stock/population Stock/population

Aggregate Maybe multispecies

Evaluation processesused to do it

Integrated ecosystemassessments

Integrated ecosystemassessments, fisheriessector focus

Integrated stock assessments Stock assessments

Primary objective ofthe analysis

Address cross-sectortrade-offs

Address fishery sector, livingmarine resource trade-offs

Delineate status of stock/s Delineate status ofstock

Ascertain ecosystem goodsand services

Ascertain ecosystemproductivity

Ascertain stock productivity Ascertain stockproductivity

Identify best mix of servicesacross goods and services

Identify best mix of goodsacross fisheries and stocks

Identify levels of optimal stockproduction cognizant ofecosystem factors

Identify levels ofoptimal stockproduction

Evaluate cross-sectorcumulative effects

Evaluate within-sectorcumulative effects

Evaluate within-stock effects ofmultiple drivers

Evaluate within-stockeffects of fishing

Primary outputs fordecision criteria

Provide systemic referencepoints

Provide systemic referencepoints

Provide fishery stock referencepoints

Provide fishery stockreference points

Analytical toolsavailable to do it

EMs EMs ESAMs SAMsRA MSMs MSMsMSE RA MSE

MSE

EMs, ecosystem models; RA, risk analyses; MSE, management strategy evaluations; ESAMs, extended stock assessment models; MSMs, multispecies models; SAMs,stock assessment models; EBM, ecosystem-based management; EBFM, ecosystem-based fisheries management; EAF, ecosystem approaches to fisheries; FM,fisheries management. For full EBM, this would be consideration of all ocean-use sectors. For EBFM, this would be only the fisheries sector with an ecosystememphasis. For EAF, this would be fisheries management with inclusion of ecosystem considerations. For FM, there would be no explicit consideration ofecosystem features.

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For EBM in the fisheries sector that includes an ecosystem em-phasis (Table 1, EBFM), parts of integrated ecosystem assessmentscan/have been used. Integrated ecosystem assessments are, by theirnature, designed to be multisectoral (Levin et al., 2008, 2009) but,clearly, the overall process can be adopted for sector-specific applica-tions. A large part of doing EBFM at this level entails exploring trade-offs among different fishery fleets, targeted species, and non-targetedspecies. Mollmann et al. (2014) describe some facets of integrated eco-system assessments that have been used in the fishery sector for theBaltic, capitalizing on the other ecosystem factors that so readily andso obviously impact fish in that Sea. Samhouri et al. (2014) notehow features of integrated ecosystem assessments have, to date,largely been used to advance EBFM in a fisheries context in theUSA. They particularlyemphasize the important role of contextual in-formation and the use of indicators for ecosystem considerations inthe fisheries management process. The contributions to this articletheme setpresent variousrenditionsof an integrated ecosystem assess-ment process and, following from them, it is not difficult to envisionhow this approach could be adapted to other ocean-use sectors.

For all ocean-use sectors, integrated ecosystem assessments arethemost appropriate tool (Table 1, EBM). Nascent integratedecosys-tem assessment efforts have been underway for approximately half adecade, though mostly piecemeal and usually not in a fully imple-mented manner (Dickey-Collas, 2014). Progress from the fewinstances where integrated ecosystem assessments are beginning tobe more fully utilized is reported in this theme set, with notes onlessons learned (Samhouri et al., 2014) and guidelines for imple-menting integrated ecosystem assessments (Levin et al., 2014) high-lighted. This is done with the intention of better informing multipleocean-use sector management and avoiding the clashes that oftenarise when competing ocean-use sectors do not communicate theirobjectives. One of the key findings from both the Samhouri et al.and Levin et al. works is the importance of early and frequent engage-ment of stakeholders in the process. This observation is reinforced bythe frank insights about the development of the ICES approach tointegrated ecosystem assessment offered by Dickey-Collas (2014).

The North American examples on integrated ecosystem assess-ments are complemented by broader European perspectives (Dickey-Collas, 2014; Walther and Mollmann, 2014). These authors note pro-gress to-date on integrated ecosystem assessments in the ICES context,particularly identifying some important challenges facing their imple-mentation. They note that these challenges could in fact impede theability to fully embrace EBM. The European perspectives bemoanthe generally slow implementation of integrated ecosystem assess-ments. Yet an important point that Samhouri et al. (2014) make isthat it takes time to develop new processes and protocols, so delaysin the use of integrated ecosystem assessments and their productsshould not necessarily be viewed as a hurdle to overcome but rathera natural part of the research-to-operations developmental process.

One item that Walther and Mollmann note is the need to (re)-consider institutional structures and frameworks for using infor-mation generated from integrated ecosystem assessments. Thisobservation is repeated in other contributions to this theme set, es-pecially Samhouri et al. (2014). There may, in fact, be no clear, easy,or imminent answers, but that discussion should continue.Dickey-Collas (2014) notes that although the way forward mayindeed be messy, the need to consider broader factors when man-aging marine resources is highly warranted and an adaptable, in-novative approach across multiple considerations is very muchrequired—just as has been envisioned for integrated assessments.

We conclude by posing a few questions for readers to ponder.

† Are integrated assessments (integrated stock assessments or inte-grated ecosystem assessments) an improvement over how we doassessments now and, if so, how?

† Are integrated approaches important to consider as we movetowards implementing EBM at all of its various levels?

† Are the strengths and weaknesses of such integrated approachesreadily apparent?

† What needs to happen next to better use such integratedapproaches? What is impeding the fuller implementation ofthese approaches?

We trust that this themed set of articles will be as thought-provokingas it is informative. We hope that our start at delineating the levels ofEBM and the types of integrated assessments serves as a useful meansto minimize some of the linguistic uncertainty that often surroundsEBM. As we move forward with the implementation of EBM at allof its various levels, we hope that the clarifications provided here,the elucidations of the different integrated assessments, identificationof key challenges, and the examples demonstrated in the various con-tributions, serve to move forward the implementation of EBM.

AcknowledgementsHB’s editorial contribution to this article theme set was supportedby the Institute of Marine Research, Norway, Projects # 81529(“Fine scale interactions in the plankton”) and 83741 (“Scientificpublishing and editing”). We thank the authors who contributedto this theme set and our many colleagues who have discussed inte-grated assessments with us over the years.

ReferencesArkema, K. K., Abramson, S. C., and Dewsbury, B. M. 2006.

Marine ecosystem-based management: from characterization toimplementation. Frontiers in Ecology and the Environment, 4:525–532.

Berkes, F. 2012. Implementing ecosystem-based management: evolu-tion or revolution? Fish and Fisheries, 13: 465–476.

Browman, H. I., and Stergiou, K. I. 2004. Perspectives on ecosystem-based approaches to the management of marine resources. MarineEcology Progress Series, 274: 269–303.

Browman, H. I., and Stergiou, K. I. 2005. Politics and socio-economicsof ecosystem-based management of marine resources. MarineEcology Progress Series, 300: 241–296.

Cicin-Sain, B., and Knecht, R. 1998. Integrated Coastal and OceanManagement: Concepts and Practices. Island Press, Washington DC.

Dickey-Collas, M. 2014. Why the complex nature of integrated ecosys-tem assessments requires a flexible and adaptive approach. ICESJournal of Marine Science, 71: 1174–1182.

Fournier, D., and Archibald, C. P. 1982. A general theory for analyzing catchat age data. Canadian Journal of Fisheries and Aquatic Sciences, 39:1195–1207.

ICES. 2011. Report of the Working Group on Multispecies AssessmentMethods (WGSAM), 10–14 October 2011, Woods Hole, USA. ICESDocument CM 2011/SSGSUE:10. 229 pp.

ICES. 2012. Report on the Classification of Stock Assessment MethodsDeveloped by SISAM. ICES Document CM 2012/ACOM/SCICOM:01. 15 pp.

Levin, P. S., Fogarty, M., Matlock, G., and Ernst, M. 2008. Integratedecosystem assessments. US Department of Commerce, NOAATechnical Memorandum, NMFS-NWFSC 92. 20 pp.

Levin, P. S., Fogarty, M. J., Murawski, S. A., and Fluharty, D. 2009.Integrated ecosystem assessments: developing the scientific basisfor ecosystem-based management of the ocean. PLoS Biology, 7:e1000014. doi:1000010.1001371/journal.pbio.1000014.

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Levin, P. S., Kelble, C., Shuford, R., Ainsworth, C., deReynier, Y.,Dunsmore, R., Fogarty, M., et al. 2014. Guidance for implementationof integrated ecosystem assessments: a US perspective. ICES Journal ofMarine Science, this volume.

Levin, S. A., and Lubchenco, J. 2008. Resilience, robustness, and marineecosystem-based management. Bioscience, 58: 27–32.

Link, J. S. 2002. What does ecosystem-based fisheries managementmean? Fisheries, 27: 18–21.

Link, J. S. 2010. Ecosystem-Based Fisheries Management: ConfrontingTradeoffs. Cambridge University Press, Cambridge, UK.

Maunder, M., and Punt, A. 2013. A review of integrated analysis in fish-eries stock assessment. Fisheries Research, 142: 61–74.

Maunder, M. N., and Watters, G. M. 2003. A general framework for inte-grating environmental time series into stock assessment models: modeldescription, simulation testing, and example. Fisheries Bulletin, 101:89–99.

McLeod, K. L., and Leslie, H. M. (Eds) 2009. Ecosystem-BasedManagement for the Oceans. Island Press, Washington, DC.

Methot, R. D. 1989. Synthetic estimates of historical and current biomassof northern anchovy, Engraulis mordax. American Fisheries SocietySymposium, 6: 66–82.

Methot, R. M., and Wetzel, C. R. 2013. Stock synthesis: a biological andstatistical framework for fish stock assessment and fishery manage-ment. Fisheries Research, 142: 86–99.

Moksness, E., Dahl, E., and Stottrup, J. 2013. Global Challengesin Integrated Coastal Zone Management. Wiley-Blackwell,Oxford, UK.

Mollmann, C., Lindegren, M., Blenckner, T., Bergstrom, L., Casini, M.,Diekmann, R., Flinkman, J., et al. 2014. Implementing ecosystem-based fisheries management: from single-species to integrated eco-system assessment and advice for Baltic Sea fish stocks. ICESJournal of Marine Science, 71: 1187–1197.

Pikitch, E. K., Santora, C., Babcock, E. A., Bakun, A., Bonfil, R., Conover,D. O., Dayton, P., et al. 2004. Ecosystem-based fishery management.Science, 305: 346–347.

Punt, A. E., and Hilborn, R. 1997. Fisheries stock assessment and deci-sion analysis: the Bayesian approach. Reviews in Fish Biology andFisheries, 7: 35–63.

Samhouri, J., Haupt, A., Levin, P., Link, J., and Shuford, R. 2014. Lessonslearned from developing integrated ecosystem assessments to informmarine ecosystem-based management in the USA. ICES Journal ofMarine Science, 71: 1205–1215.

Townsend, H. M., Link, J. S., Osgood, K. E., Gedamke, T., Watters, G.M., Polovina, J. J., Levin, P. S., et al. (Eds). 2008. Report of theNEMoW (National Ecosystem Modeling Workshop). NOAATechnical Memorandum, NMFS-F/SPO-87. 93 pp.

Walther, Y., and Mollmann, C. 2014. Bringing integrated ecosystemassessments to real life—a scientific framework for ICES. ICESJournal of Marine Science, 71: 1183–1186.

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Original Article

Why the complex nature of integrated ecosystem assessmentsrequires a flexible and adaptive approach

Mark Dickey-Collas1,2*1ICES, H. C. Andersens Boulevard 44-46, DK-1553 Copenhagen, Denmark2Wageningen IMARES, 1970 AB, IJmuiden, The Netherlands

*Corresponding author: tel: +45 3338 6759; fax: +45 3338 6700; e-mail: [email protected]

Dickey-Collas, M. 2014. Why the complex nature of integrated ecosystem assessments requires a flexible and adaptive approach. – ICES Journal ofMarine Science, 71: 1174–1182.

Received 21 December 2013; accepted 31 January 2014; advance access publication 6 March 2014.

This article considers the approach taken by the ICES to integrated ecosystem assessments (IEAs) in the context of the wider evolution ofIEAs and the science/policy landscape within the ICES region. It looks forward and considers the challenges facing the development of IEAs,specifically those of scoping for objectives, participatory engagement, developing indicators and targets, risk analysis, and creating tools toevaluate management measures for marine anthropogenic activities. It concludes that expectations that the implementation of IEAs willtake an ordered, stepwise approach will lead to disappointment and frustration. This is a consequence of the need to operate in an adaptivemanner in a complex system. The ecosystem, the science support infrastructure, and the governance systems are all complex. Plus whenengaged in a debate about societal objectives, we expect to encounter a complex and changing landscape. As a community, the challenge isto find leverage mechanisms to encourage IEA efforts to provide insights and tools within resources. We will need to innovate and beresponsive to the complexity of the ecosystem and governance structures encountered when performing IEA.

Keywords: ecosystem approach, fisheries, HELCOM, MSFD, OSPAR, regionalization.

IntroductionThe concept of integrated ecosystem assessments (IEAs), in themarine sphere, germinated in response to the development of theecosystem approach to fisheries management (EAFM, Rice 2011).The political incentive behind EAFM is clear (Murawski, 2007;Jennings and Rice, 2011), but operationalizing it has been, andstill is, a challenge (Rice, 2011). The ecosystem approach is certainlynot a new approach (Jennings, 2004; Garcia and Cochrane, 2005)but it requires management to take a different path, althoughperhaps not a paradigm shift, to be successful (Sissenwine andMurawski, 2004; Murawski, 2007). Core to the ecosystem approachis managing the impact, or the pressure of humans on the marineecosystem; the human dimension (De Young et al., 2008; Rice,2011). Jennings (2004) sums this up as “The ecosystem approachis variously defined, but principally puts emphasis on a manage-ment regime that maintains the health of the ecosystem alongsideappropriate human use of the marine environment, for thebenefit of current and future generations.”

Jennings and Rice (2011) suggest that progress towards an ecosys-tem approach to fisheries has been slow because of the lack of specificenvironmental, social, and economic objectives, with no agreedguidance on trade-offs from policy-makers. They add that it isimpacted by a framework for decision-making in Europe with a fish-

eries policy that is skewed towards short-term national interests. It is

likely that the lack of guidance for trade-offs and objectives and a re-

luctance by those engaged in the debate to bring non-ecologists to the

table will hamper any push towards developing tools for the ecosys-

tem approach (Degnbol and McCay, 2006; Francis et al., 2011).

“The challenge for EAM/EBM will be to link the incremental

changes in selected indicators to a target end state to the societal

costs and benefits of achieving the end state ” (Murawski, 2007).Part of making an ecosystem approach operational is ensuring

that the interactions between fisheries and other sectors are equit-

able, with inclusiveness in decision-making (Levin et al., 2009;

Rice, 2011). This has led to the development of IEAs as a concept

(Link, 2012), although like the ecosystem approach, it is difficult

# International Council for the Exploration of the Sea 2014. All rights reserved.For Permissions, please email: [email protected]

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to provide a working definition for IEAs as they encompass a frame-work and executable practice. The ICES “benchmark” group on IEA(WKBEMIA) defined IEA as an interdisciplinary process of com-bining, interpreting, and communicating knowledge from diversescientific disciplines, in such a way that the interactions of aproblem can be evaluated and thus provide useful information todecision-makers (ICES, 2012a). Levin et al. (2009) define IEA as“a synthesis and quantitative analysis of information on relevantphysical, chemical, ecological and human processes in relation tospecified ecosystem management objectives”. Defining IEA is achallenge, especially because the suggested approach to IEA is adap-tive and iterative; learning by doing (De Young et al., 2008). I see IEAas a process that leads to the provision of joined-up and consistentadvice that addresses society’s needs to manage anthropogenicpressures on the marine ecosystem. Importantly, it does not leadto one answer, but provides the information and knowledge tofacilitate exploring the space for decision-making and policy devel-opment. It is regional in scope. In the ICES context, there is a distinctdifference between IEA and developing models of ecosystem func-tioning. A framework to make the IEA approach operational hasbeen evolving and can be traced through the documents fromFAO (2003), ICES (2005), and Levin et al. (2009). The frameworkcan be summed up as scoping, developing indicators and targets,risk analysis, assessing ecosystem status, then evaluating the strategyand return to any previous stage that requires further development(Levin et al., 2009). Samhouri et al. (2014) explore this frameworkfurther with specific case studies from the USA.

In an inherently chaotic system, we should aim to manage an-thropogenic impacts in an integrated manner and respond to un-foreseen changes as they occur without the requirement to be ableto quantify every functional relationship (Schellnhuber andSahagian, 2002; Clark et al., 2005). This requires an iterativeprocess linked to adaptive management. Linking a scientific inves-tigation to a societal debate on management objectives, trade-offs,and tools for analysis may well challenge those that see science as asearch for pure truth and not part of a societal debate. Manyargue that the science is not yet good enough, nor based on strongenough evidence to enter that debate. To paraphrase mythnumber 4 in Murawski (2007), people think that insufficient infor-mation limits the application of the ecosystem approach. This is alsoallied to the idea that a quantitative model of species interactionsamong all components is necessary to guide the ecosystem approach(myth 8 in Murawski 2007). It is necessary to understand the broaddynamics of the ecosystem state and function (a “macroscope” ap-proach, Schellnhuber and Sahagian, 2002). However, we will never

understand all the processes, and even if we did, it is unlikely that fullunderstanding would make our political decision-making easier.Rice (2011) stresses that the process must maximize the use of avail-able information rather than emphasize the areas of uncertainty.Likewise, the idea that we can “data-collect” our way to the ecosys-tem approach, or an IEA, must be recognized as a fallacy. Levin et al.(2009) point out that massing data simply cannot tell us how to im-plement EBM or determine priorities for management. They saythat reductionist approaches can result in researchers and policy-makers “drowning in data but gasping for knowledge”. Tallyingthe status or trends of various components cannot inform EBM(Levin et al., 2009). As Degnbol et al. (2006) claim, “improvementsin fisheries management will be realized not through the promotionof technical fixes but instead by embracing and responding to thecomplexity of the management problem”.

In this article, I reflect on my experience of working with IEAgroups over the last 2 years. I consider the approach taken by theICES community through it IEA groups in the context of thewider IEA debate. I also look forward and consider the challengesthat face the development of IEAs, specifically those of scoping forobjectives, developing indicators and targets, risk analysis, and cre-ating tools to evaluate measures to manage marine anthropogenicactivities. Almost all researchers involved in the development ofIEAs recognize that an adaptive and iterative process is crucial tosuccess (Samhouri et al., 2014). However, many members of theICES community have expressed frustration over the “institutionaland governance structures” and the limited resourcing of develop-ment that challenge implementation of IEAs (ICES, 2012a;Walther and Mollmann, 2014). In this article, I would like toexplore whether a clearly prescribed framework or high-level stra-tegic steering can be expected (Levin et al., 2014; Mollmann et al.,2014), and whether its absence is a block on progress?

ICES approachThe organizational approach used to develop IEAs by ICES isdescribed in Walther and Mollmann (2014). This approach hasevolved mostly through the efforts of individual researchers tobuild multidisciplinary teams and is characterized by regionalgroups, each acting in slightly different ways, to address slightly dif-ferent challenges. There is one group based in the northwestAtlantic, but the majority of groups work on European regionalseas. The new ICES strategic plan (ICES, 2014) places developingintegrated ecosystem understanding at its core for the next5 years. This puts the regional groups at the centre of the ICESnetwork. From the start, it is important to note that none of the

Table 1. ICES IEA Working Groups that were considered in this article, including plans for their future.

Region Group Years active Future plans*

Baltic Sea WKIAB 2006WGIAB Annually 2007 to present 2014, 2015

Northwest Atlantic WGNARS Annually 2010 to present 2014, 2015, 2016Northeast Atlantic WGEAWESS 2011 and 2013 2014, 2015, 2016North Sea WGHAME 2010

WGINOSE Annually 2011 to present 2014, 2015, 2016Norwegian Sea WGINOR 2013 2014, 2015Barents Sea WGIBAR Yet to meet 2014, 2015, 2016

*Agreed terms of reference for these years.WKIAB- ICES/BSRP/HELCOM, Workshop on Developing a Framework for Integrated Assessment for the Baltic Sea; WGIAB-ICES/HELCOM, Working Group onIntegrated Assessments of the Baltic Sea; WGNARS, Working Group on the Northwest Atlantic Regional Sea; WGEAWESS, Working Group on EcosystemAssessment of Western European Shelf Seas; WGHAME, Working Group on Holistic Assessments of Regional Marine Ecosystems; WGINOSE, Working Group onIntegrated Assessments of the North Sea; WGINOR, Working Group on the Integrated Assessments of the Norwegian Sea; WGIBAR, Working Group on theIntegrated Assessments of the Barents Sea. More complete descriptions of the groups are given in Walther and Mollmann (2014).

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groups have been asked, or proposed themselves, to carry out anactual ecosystem assessment as yet. The groups have been taskedwith developing methods and tools for IEAs. When reading thereports of the ICES IEA groups (Table 1, and see Walther andMollmann, 2014), certain frustrations become apparent. Thegroups ask for high-level stewardship, there is a crying out for asimpler governance structure and clearer defined managementobjectives. A huge amount of work has been done by the groupsand the outputs have been substantial, with analysis of trends inthe state of the ecosystems, much focus on fisheries issues andinitial exploration of the Levin et al. (2009) approach. Whenreading the reports, it is also evident that some groups have falleninto traps that could hamper development of IEAs.

In my mind, there are some key issues that researchers need toconsider when pushing forward IEA. These key issues are basedon the work by FAO (2003), ICES (2005), and Levin et al. (2009)and can be grouped into the concepts and techniques (the practicalmethod development and implementation). The key concepts are:

(i) The human dimension—acknowledge that humans arecentral to the challenge. IEAs are management tools for main-taining the health of the ecosystem alongside the appropriatehuman use of the marine environment. IEAs are as muchabout a societal debate as about the results of a scientific study.

(ii) Ecosystems vary—there is no such thing as a marine ecosystemin equilibrium. This means that predictions beyond are knownknowledge should be challenged and the state of the ecosystemshould always be monitored. Links between components ofthe system and potential responses to management actionwill not be linear. Approaches that suggest that the futurewill behave like the past should be challenged.

(iii) Seek operational objectives—they are the cornerstone of IEAs.They are not usually predetermined, but best derived througha debate where stakeholders explore the consequences of theirobjectives through models and other tools. The process of howthe objectives are derived might be complex and multilayered.

(iv) Integrate across sectors—IEAs should aim to integrate acrossissues, sectors, and stakeholders. Although individual projectsor teams should always define the scope and limits of their work.

(v) Understanding is what matters—data acquisition is differentfrom knowledge acquisition. You will never fully understandthe system in which you operate, and it will always change.Collecting data in isolation without synthesis and testing ofideas will not build knowledge but be aware that even a fullunderstanding will not replace the societal debate requiredto make decisions.

(vi) Do it again and again—it is an iterative process. The methodsbeing developed should be part of an adaptive managementframework that will constantly evolve and change based onknowledge acquisition and the priorities of society.

On the practical side, the techniques used should consider:

(i) Scoping—of societal, managerial, and operational objectives.In addition to this, it is important to set spatial boundaries andthe subdivision of regions in relation to ecosystem dynamicsand management objectives. It is also practical to set the sec-toral boundaries too.

(ii) Monitoring—collecting datasets and monitoring of the eco-system. This should be associated with ecosystem modellingwith the overall aim to review the state of the system andmonitor progress of indicators in relation to thresholds ortargets.

(iii) Developing indicators, targets, and reference points—developing indicators for ecosystem functioning, performanceof management measures, decision rules, or communicationof management objectives and action. These indicators mustbe associated with targets and reference points.

(iv) Assessing cumulative effects—develop methods (quantitativeor qualitative) for assessing a range of anthropogenic pressuresboth unisectoral and multisectoral. Methods for combiningindicators need to be developed to allow an IEA to reach anoverall conclusion about the state of the ecosystem.

(v) Risk analysis—exploring risk analysis tools to provide infor-mation on potential scenarios and trade-offs associated withspecific decisions. Examining trade-offs by looking at risk ana-lysis in relation to potential management objectives fromacross sectors, or choices within a single sector.

What follows below is my personal interpretation of how we haveexplored the key ideas of IEAs in ICES. It is based on my readingof reports and discussions with the active IEA groups. The aim ofmy comments is to explore what we mean in practice in ICESwhen we work on IEAs and are aimed at setting the stage for thefurther development of IEAs throughout the ICES community.

ICES in its new strategic plan has set the target of carrying outexample IEAs in the next few years, so the efforts of the ICES com-munity now needs to include the execution of IEAs along with thefurther development of methods and tools. The current IEAgroups were tasked with method development. All groups havemade progress on building datasets and considering monitoringneeds. They acknowledge the need to set boundaries (regional, dis-cipline, and sector). Many suggest dividing their regions based onecosystem functioning, and a few appear to have considered theimpact of these divisions on management. Almost none of thegroups have carried out an effective scoping exercise. This isdespite links with regional seas conventions and probably reflectstheir interpretation of method development being their centralpurpose. Most groups suggest that governance issues preventeither participatory approaches or integration of managementacross marine sectors, which suggests that carrying out a scoping ex-ercise is crucial to method development and IEA implementation.

With regard to the overall concept of IEAs, there still appears tobe a reluctance to think conceptually about the human dimension. Itis not clear whether all the groups see IEA as tools to balance diversesocietal objectives. Some appear challenged with the concept thatindicators can exist that address societies priorities rather than eco-system functioning. All groups acknowledge that ecosystems areinfluenced by a range of drivers that impact at differing time-scales.Studies examining the trends in the state of the ecosystem dominatesome of the groups. Every group reports that they are struggling towork across sectors. Some groups appear unclear about the conceptof adaptive management, whereas others are developing techniquesto make use of their improving understanding. Many groupsprioritize data collection. As yet, there appears to be limited progresson developing methods to synthesize knowledge to inform orexplore potential management action. In my mind, some IEAresearchers see themselves as teams working on ecosystem

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description rather than IEAs as defined by WKBEMIA (ICES,2012a) or Levin et al. (2009).

The groups seem most confident and happiest when working inthe core ICES disciplines of fisheries and the ecology of marine verte-brates and copepods. Biodiversity and habitat quality/connectivityhave been considered by a minority of groups. On the Europeanside, up until 2013, no groups had really considered non-fishing-related pressures, but that has recently changed, especially with the de-velopment of the ecosystem overviews (ICES, 2013a; Walther andMollmann, 2014). Some participants appear to be aware of the mul-tiple roles played by indicators, and the contrasting ideas of indicatorsand targets for management and monitoring of the ecosystem state.The groups appear challenged by the prospect of proposing indica-tors; this is despite the large amount of work on indicators that hasbeen published by the ICES group WGECO (ICES, 2013b) over thelast decade. Most groups have had terms of references that askedfor indicator development and delivery, but few indicators havebeen forthcoming. Few IEA groups, as yet, have suggested thresholds,targets, or reference points for integrated advice, although the BalticIEA group has provided advice on future scenarios for multispeciesoptions for Baltic fisheries (Mollmann et al., 2014). Proposingtargets or reference points would facilitate a dialogue to startwith policy developers. In recent years, some groups have begundeveloping risk-based approaches and exploring methods toexplore trade-offs.

The conclusion of the ICES Benchmarking workshop on IEA(ICES, 2012a) was that almost none of these key concepts or activ-ities can be carried out in isolation or in a specific order. They devel-oped the idea of an IEA cloud, where the iterative process is notcircular, or linear, but is structured as a multidimensional matrix.It is well known that a multidimensional approach is difficult tosteer, and no one individual can be fully aware of all activitiesand all links, so the approach stresses the importance of teamsworking towards a shared vision, with a strong need for communi-cation between the main players.

Looking forwardConsidering all these issues, we must explore the opportunitiesoffered by the current system and view the perceived limitationsas challenges. Governance mechanisms are always challenging;whether in Europe or North America. Resources are becomingever more limited, despite large increases in governance challenges.Society expects informed decisions from policy developers and yetseems unprepared for the resource implications of that expectation.The sections below with further explore how we can use thestrengths in the ICES community to further develop IEAs specific-ally on the key techniques of scoping, use of indicators, risk analysis,and tools for management strategy evaluations.

ScopingA concern of the ICES IEA groups, and a key factor in an IEA, is ascoping exercise to establish higher and lower (operational) objec-tives for managing the impact of humans on the ecosystem (Levinet al., 2009). You should “balance diverse societal objectives”(FAO, 2003). This is no mean feat as the perceived reality of eachstakeholder will be based on a different understanding of the func-tioning of the system (Verweij and van Densen, 2010) and, thus,probably lead to a different notion of the impact of a managementaction on their activity (Delaney and Hastie, 2007). Policy objectivesand research initiatives are in a state of continuous flux; observe theshift in terms of research priorities from environmental protection

to “green growth” in the EU Horizon 2020 research programme. It isoften said that scoping is an initial activity, but in reality scoping isrequired continuously throughout the process (ICES, 2012a;Samhouri et al., 2014). In ICES, a wealth of experience has been gen-erated in describing objectives through participatory modelling ofsingle stock fisheries management plans (where scientists and stake-holders work together to build and explore the models used to testmanagement plans) and exploring policy objectives for marinespatial planning (e.g. Schwach et al., 2007; Degnbol and Wilson,2008; Mackinson et al., 2011; Dankel et al., 2012; Rockmann et al.,2012). This participatory approach is really what is required inIEA. Scoping must be a dialogue between stakeholders. Often thepolicy developers, industrial concerns or NGOs are not aware ofthe potential options and trade-offs until they see the ability of thetools or the dynamics of the models. Scientists can operate as “trans-parency brokers” exploring policy options with the range of stake-holders (P. Degnbol, ICES, pers. com.), thus providing useableknowledge (Haas, 2004). Our experience in ICES of developingmultispecies advice for the Baltic and North Sea shows that a keyaspect of providing advice is finding the appropriate communica-tion approach to describe the trade-offs (ICES, 2012b). This com-munication approach comes before any consideration of themanagement/policy objectives. Assuming that policy developersknow what they want before an IEA exercise is unrealistic.Assuming that there is one set of unified managers, with one object-ive, is even more unlikely (van Leeuwen et al., 2012).

One of the most important parts of the scoping exercise is to es-tablish boundaries around the conceptual space being covered bythe IEA, the factors that will be integrated and the objectives thatwill be included. The range of relevant time-scales, from short-termgoals to longer-term objectives, must also be scoped so that develo-pers of IEAs are aware of the multiple spatial and temporal scales atwhich IEAs operate (De Young et al., 2008).

In some cases, the policy agenda jumps ahead of scienceknow-how (Rice, 2011). A good example of this is the MarineStrategy Framework Directive (MSFD; EC, 2008) in the EU.The MSFD can be viewed as an imposition and clarification of thehigher management objectives (Good Environmental Status, GES)for the EU marine environment including fisheries (Ratza et al.,2010). However, in practice, many suggest that the MSFD is ambigu-ous with unclear boundaries and conflicting objectives (van Leeuwenet al., 2012; Ounanian et al., 2012). Trying to define the operationalobjectives and the indicators from the MSFD is difficult with theGES descriptors being a mixture of ecosystem components, attri-butes, and pressures (S. Jennings, CEFAS, pers. com.). However, itcan be viewed as the result of a politically imposed scoping exercise.Thus, in the EU, despite the MSFD’s ambiguities, researchers have aset of objectives by which to operate. The remaining challenge is toresolve the issue of trade-offs and priorities for the multitude ofGES descriptors. Few natural scientists have experience operating ina participatory process as “transparency brokers” and developingindicators that relate to societal interests/priorities. Researchersmay feel awkward moving from their training in biology/ecologyinto the participatory decision-making realm, but this is what isrequired.

Indicators and targetsIndicators can be viewed as an interface between science and policy(Heink and Kowarik, 2010) with some arguing that they have morevalue to policy-makers than to scientists (Levin et al., 2010).Indicators are needed to provide information on the state of the


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ecosystem, and the progress of management in relation to objectives(Jennings, 2005). Indicators are quantifiable metrics that reflectchanges in ecosystem attributes (Samhouri et al., 2009) and the per-formance of an indicator is quantified by the ability to detect and/orpredict trends in ecosystem attributes (Fulton et al., 2005). We alsorequire metrics for monitoring overall state, and I would class thesemonitoring indicators as conceptually different from IEA indica-tors, which are target-oriented and specific for management action.

There is a wealth of studies on defining indicators and targetsfor both the marine ecosystem-based approach and IEAs. Mostare based on case studies and often use different ecosystem ortrophic models to test the how the indicators are chosen and thesuitability of the indicators themselves (Trenkel and Rochet, 2003;Fulton et al., 2005; Methratta and Link, 2006; Samhouri et al.,2009; Kershner et al., 2011). It is paramount to remember thepurpose of indicators. As Levin et al. (2010) says: “It is temptingfor natural scientists to advocate indicators that provide maximalinformation about ecosystem structure and function without con-sideration of societal values”. Providing maximal information onecosystem structure and function may negate the indicators’ rolein melding social and natural science (Levin et al., 2010).Informing society that an ecosystem is changing in a dramaticmanner without indicating what it means or how to resolve theproblem would negate an indicators role. In the ICES context,the policy objectives cannot be forgotten. The optimal portfolio ofindicators is one that ensures appropriate scientific information iscaptured while also maximizing the value of the indicators forpolicy-makers (Levin et al., 2010). As indicators sit at the interfacebetween science and policy they should be expected to changeover time as society’s objectives change (Samhouri et al., 2012).There are often very pressing needs which can be quickly addressed(Jennings and Le Quense, 2012) and marine scientists that work inthe applied field should be careful not to deflect focus away from themain issues.

Indicators (with associated targets/reference points) serveseveral purposes; to define the expected objectives, track progresstowards those objectives and communicate trends in compleximpacts to a non-specialist audience (Fulton et al., 2005; Jennings,2005). The portfolio of indicators should contain complementaryindicators that exclude redundant metrics, i.e. be resource efficient(Samhouri et al., 2009; ICES, 2013b; Large et al., 2013). Rice andRochet (2005) stress that the number of indicators should belimited, as indicators will be incorporated into a range of rolesand must be communicable to a wider audience. Some potentialindicators will reflect the same trends in ecosystem attributes overtime; Levin et al. (2010) comment that this might be the case forsome societally important indicators (e.g. abundance of differentspecies of large sea mammals) which also do not provide thatmuch information on ecosystem functioning. The building of theportfolio will involve compromise.

Much has been said about the selection process for indicators.Levin et al. (2010) describe this process as indicator mapping.Nonetheless, there is broad agreement about the criteria for asses-sing indicators (ICES, 2013b). The indicators must be sensitiveand specific to changes in ecosystem attributes and responsive tochanges in human activities (Rice, 2003; Jennings, 2005; Rice andRochet, 2005). Rice and Rochet (2005) provide an 8-step frameworkfor selecting indicators, including scoping. They list the importantcriteria as concreteness, theoretical basis, public awareness, cost,measurement, availability of historical data, sensitivity, responsive-ness, and specificity. The criteria appear to be accepted by the

research community and have been further developed by ICES(2013b). The 8-stage framework can lead to subjective choices(Rochet and Rice, 2005; Piet et al., 2008). Fulton et al. (2005),Samhouri et al. (2010, 2012), and Kaplan et al. (2012) use ecosystemmodels to assist in the selection of appropriate indices. There is adanger that when working with indicators you assume that causal-ities are linear (Samhouri et al., 2010, 2012). This approach appearsto ignore the likelihood of alternative stable states, hysteresis, and in-herent non-linearity in the underlying responses of the ecosystem(Heath, 2012; Denderen and Kooten, in press).

As part of their method development, it would be constructivefor the IEA groups in ICES to further consider indicators andengage with policy developers to show the ramifications of decisionsabout targets. Many nations have independently proposed indica-tors through the MSFD, and both OSPAR and HELCOM (the re-gional sea conventions for the NE Atlantic and the Baltic,respectively) now have long lists of either proposed or potentialindicators. So some management objectives and associated indica-tors have been provided. The ICES IEA groups are in a strong pos-ition to explore whether these indicators are of value and show theirrelative utility.

RiskRisk analysis provides an accountable and transparent frameworkfor prioritizing actions in management, particularly in thebroader context of the ecosystem approach to fisheries (ICES,2009). Samhouri and Levin (2012) propose that ecosystem-basedrisk should be scored along two axes of information: the exposureof a population to an activity and the sensitivity of the populationto that activity. Following the same line of argument aboutscoping and indicators, the subjective value-based nature of objec-tives requires recognition that risk analysis is a decision support tool,not a decision-making tool. Risk analysis can also bring in factorssuch as cost of monitoring or research into the decision-makingprocess. It is often argued that first a qualitative assessment ofrisks be undertaken (a screening out of low-risk activities) followedby a detailed assessment (often quantitative). Some IEA groupssuggest that risk analysis should be operationalized into a predictivemeasure of the effectiveness of management actions, rather than anexploration of trade-offs.

Accounting for the unpredictability of human behaviour is also achallenge when investigating fisheries systems (Fulton et al., 2011).The following uncertainties may need to be assessed when consider-ing any fisheries management cycle; resource dynamics, reporting,monitoring, assessment, management decisions, implementation,and fishing activity (Fulton et al., 2011). This approach appears tobe just as valid when considering any anthropogenic pressure onthe system. When thinking about IEAs specifically, the error andscale of the chosen indicators should be considered, thus accountingfor the degree of signal and noise (Jennings, 2005). If managersrespond and act based on noise rather than signal, they risk squan-dering the credibility of everyone involved (Jennings, 2005). Thus,an assessment of risk is crucial.

Developing tools and evaluations of strategyICES has many in-house experts in management strategy evalu-ation, but they tend towards evaluating the effect of single-speciesfisheries on single-species populations (Kraak et al., 2010). Thereare notable exceptions where scientists have started to considerthe other effects of fishing activities on multispecies targets, theeffect of mixed fisheries, closed areas, and impact on benthic


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communities and on elasmobranchs (Mackinson et al., 2009; Ulrichet al., 2011; Gascuel et al., 2012; Kraak et al., 2012; Rijnsdorp et al.,2012, etc.) but studies that integrate across pressures or that investi-gate cumulative effects are still rare (Stelzenmuller et al., 2010; Fodenet al., 2011). There are various examples of good practice of manage-ment evaluation coming from IEA work (Sainsbury et al., 2000;Smith et al., 2007; Ojaveer and Eero, 2011; Heath, 2012; Kaplanet al., 2012, 2013).

Jennings and Rice (2011) suggest a two-tier approach to evaluat-ing impact and potential management measures, by assessing bothsingle-sector and multisectoral activities. There appears to be pro-gress in understanding single-sector impacts, with researchers con-sidering the effects of one type of activity on many components ofthe ecosystem. Cumulative effects should consider how social andeconomic aspects of ocean uses covary or compete and howimpacts of multiple ocean uses contribute to status and trends of

Figure 1. The description of the science and policy landscape in which ICES operates, taken from the ICES strategic plan (2014–2018; ICES, 2014).# ICES. The examples are not exhaustive. Acronyms: Baltic Marine Environment Protection Commission (HELCOM), Convention for theProtection of the Marine Environment of the North-East Atlantic (OSPAR), Convention on Biological Diversity (CBD), Convention on InternationalTrade in Endangered Species of Wild Fauna and Flora (CITES), European Environment Agency (EEA), European Union (EU), Food and AgricultureOrganization of the United Nations (FAO), General Fisheries Commission in the Mediterranean (GFCM), International Arctic Science Committee(IASC), International Commission for the Conservation of Atlantic Tunas (ICCAT), International Council for the Exploration of the Sea (ICES),International Council for Science (ICSU), Intergovernmental Panel on Climate Change (IPCC), Intergovernmental Panel on Biodiversity andEcosystem Services (IPBES), Intergovernmental Oceanographic Commission (IOC), Mediterranean Science Commission (CIESM), NorthwestAtlantic Fisheries Organization (NAFO), North Atlantic Salmon Conservation Organization (NASCO), North Atlantic Marine MammalCommission (NAMMCO), North East Atlantic Fisheries Commission (NEAFC), North Pacific Marine Science Organization (PICES), ScientificCommittee on Oceanic Research (SCOR), Statistical Office of the European Communities (EUROSTAT), United Nations Development Program(UNDP), United Nations Environment Program (UNEP).


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ecosystem components or attributes. Cumulative effects will not beadditive but be complex and responsive (ICES, 2012c). A multisec-torial approach may lead to the conclusion that one sector domi-nates the anthropogenic impact (e.g. the impact of fishing onbenthic communities; Foden et al., 2011), which is a usefulfinding when looking at the next stages of implementing manage-ment actions, but you need a multisectoral approach to arrive atthis conclusion. It has also been suggested that cumulative assess-ments across multiple sectors are extremely sensitive to theassumed weightings between sectors (Stelzenmuller et al., 2010).This area of research needs much more attention and Rice suggeststhat the initial barrier to development is a lack of cross-sectoral data-sets, and institutional blocks to exchange between researchers fromindividual sectoral fields (J. Rice, pers. com., DFO, Canada). Themove to integrated data management policies and in Europe,closer collaborations with (and between) regional sea commissionswill hopefully aid this process.

The ICES IEA groups were instigated to develop methods for theadvisory process. Their role was to provide tools and methods. Thus,the groups were not expected to carry out complete IEAs asdescribed by FAO (2003), ICES (2005), and Levin et al. (2009),namely to assess the ecosystem status and evaluate potential man-agement strategies. They should, however, be encouraged to pickup any developmental requirements after the evaluation of the strat-egy and work on following iterations of the process. It is probablynow time for the advisory process of ICES to use the tools thathave been developed by carrying out example IEAs.

The science and policy landscape for IEAs in ICESGovernance and research structures are layered, complex, and oftencontradictory with poor communication between those layers.There is no central funding mechanism, no simple decision-makingbody, and society does not speak with one voice. Within ICES, weneed to find a leverage mechanism that can encourage the IEAgroups to continue progress. Society also has the right to make deci-sions based on its evolving political processes. We must note mythnumber 5 of Murawski (2007); that the ecosystem approach is toodifficult to apply in multinational regional management organiza-tions. Complexity in governance should not be an excuse to avoiddeveloping approaches. The balance between conservation and util-ization strategies will be a matter of societal choice and negotiation,consistent with the operating principles of any agreement(Murawski, 2007). Therefore, to succeed, we must embrace the com-plexity of the decision-making and implementation framework(Degnbol et al., 2006).

The science and policy landscape in which ICES scientistsoperate is complex (Figure 1, taken from ICES 2014). ICES scientistsare experienced in describing and exploring complex marine ecosys-tems. When considering IEAs, they must prepare to enter thecomplex system of governance and participatory engagement inthe translation of societal objectives into their assessments, or atleast work in teams that include researchers that are prepared toengage in dialogue with the governance system. We can learnfrom “complex systems science” that our frameworks are useful toconceptualise our challenges, but new structures and approachesemerge from engagement in a complex system (Mitleton-Kelly,2003). Adaptability of the approach taken is key. It could beargued that ICES scientists had little direct input into the twomain outcomes of the 2014 EU Common Fisheries Policy (CFP)reform, namely the landing obligation (discard ban) and thefirming up of the political meaning of the MSY. EU society has

accepted a triumvirate EU governance mechanism (Commission,Council, and Parliament) that led to this reform and the mechanismis complex and the outcome unpredictable. Now that the CFPreform has been agreed upon, ICES scientists have to assess its con-sequences for the sustainability of fisheries. We will be adaptive anditerative in our approach to the reformed CFP. Should we expect anyless of our approach to IEAs?

ConclusionThere have been significant advances in the development ofintegrated ecosystem approaches in ICES, especially on investigat-ing variability in environmental drivers and the incorporation offisheries management trade-offs in a dynamic ecosystem(e.g. multispecies catch options in Baltic Sea fisheries). IEAs arenow a central element of the ICES strategy. The community isdynamic and looking forward to making further progress on thechallenges of IEAs. There are opportunities and, as shown byWalther and Mollmann (2014), incremental progress has beenmade. Ecosystem-based management (EBM) is a US national prior-ity within the National Oceans Policy, and to affect EBM, the IEAsare seen as best practice. In Europe, the MSFD and HELCOM andOSPAR are demanding a different approach to science and newmethods to providing advice on the management of anthropogenicpressures. In my view, IEA research should be encouraged that con-siders the portfolios of indicators, should develop tools for evaluat-ing management measures (that incorporate risk), and shouldfurther develop dialogue with stakeholders.

When engaging in a debate about societal objectives, we shouldexpect to encounter a complex and changing landscape. Thus, our re-sponse should be adaptive and iterative. The expectation of anordered process is not only likely to lead to disappointment and frus-tration, but is also actually not an optimum approach. We shouldplan, and build strategies that can be measured, but thoseplans should be responsive as we expect change and unforeseenconsequences of our actions. The field of managing anthropogenicpressures on the marine ecosystem is complex with many inter-dependencies, but the challenge is to provide insights from ourscience with the resources available. We will need to innovate andfind new ways to respond to the complexity of the managementproblem. A straight path might not necessarily be the route thatgets you home.

AcknowledgementsThe article is based on an internal ICES report that I wrote in 2012. Itwas widely circulated and I received much input from across theICES community. This feedback was greatly appreciated. I wouldlike to thank Simon Jennings, Jake Rice, Jason Link, HowardBrowman, and Steve Murawski for their help. Poul Degnbol isalso thanked for his comments on the manuscript.

ReferencesClark, W. C., Crutzen, P. J., and Schellnhuber, H. J. 2005. Science for

Global Sustainability: Toward a New Paradigm. John F. KennedySchool of Government Faculty Research Working Paper Series,RWP 05-032, pp. 1–28.

Dankel, D. J., Aps, R., Padda, G., Rockmann, C., van der Sluijs, J. P.,Wilson, D. C., and Degnbol, P. 2012. Advice under uncertainty inthe marine system. ICES Journal of Marine Science, 69: 3–7.

Degnbol, P., Gislason, H., Hanna, S., Jentoft, S., Nielsen, J. R.,Sverdrup-Jensen, S., and Wilson, D. C. 2006. Painting the floorwith a hammer: technical fixes in fisheries management. MarinePolicy, 30: 534–543.


by How

ard Brow

man on July 2, 2014


Dow

nloaded from


Degnbol, P., and McCay, B. J. 2006. Unintended and perverse conse-quences of ignoring linkages in fisheries systems. ICES Journal ofMarine Science, 64: 793–797.

Degnbol, P., and Wilson, D. C. 2008. Spatial planning on the North Sea: acase of cross-scale linkages. Marine Policy, 32: 189–200.

Delaney, A. E., and Hastie, J. E. 2007. Lost in translation: differences inrole identities between fisheries scientists and managers. Ocean andCoastal Management, 50: 661–682.

van Denderen, P. D., and van Kooten, T. in press. Size based speciesinteractions shape herring and cod population dynamics in theface of exploitation. Ecosphere, doi.org/10.1890/ES13–00164.1.

De Young, C., Charles, A., and Hjort, A. 2008. Human Dimensions ofthe Ecosystem Approach to Fisheries: an Overview of Context,Concepts, Tools and Methods. Fisheries Tech. Paper, 489. FAO,Rome. 165 pp.

EC. 2008. Directive 2008/56/EC of the European Parliament and of theCouncil. Establishing a framework for community action in the fieldof marine environmental policy (Marine Strategy FrameworkDirective). EC, Brussels.

FAO. 2003. Fisheries management. 2. The ecosystem approach tofisheries. FAO, Rome. 121pp.

Foden, J., Rogers, S. I., and Jones, A. P. 2011. Human pressures on UKseabed habitats: a cumulative impact assessment. Marine EcologyProgress Series, 428: 33–47.

Francis, T. B., Levin, P. S., and Harvey, C. J. 2011. The perils and promiseof futures analysis in marine ecosystem-based management. MarinePolicy, 35: 675–681.

Fulton, E. A., Smith, A. D. M., and Punt, A. E. 2005. Which ecologicalindicators can robustly detect effects of fishing? ICES Journal ofMarine Science, 62: 540–551.

Fulton, E. A., Smith, A. D. M., Smith, D. C., and van Putten, I. E. 2011.Human behaviour: the key source of uncertainty in fisheries man-agement. Fish and Fisheries, 12: 2–17.

Garcia, S. M., and Cochrane, K. L. 2005. Ecosystem approach to fisher-ies: a review of implementation guidelines. ICES Journal of MarineScience, 62: 311–318.

Gascuel, D., Merino, G., Doring, R., Druon, J. N., Goti, L., Guenette, S.,Macher, C., et al. 2012. Towards the implementation of an integratedecosystem fleet-based management of European fisheries. MarinePolicy, 36: 1022–1032.

Haas, P. M. 2004. When does power listen to truth? A constructivist ap-proach to the policy process. Journal of European Public Policy, 11:569–592.

Heath, M. R. 2012. Ecosystem limits to food web fluxes and fisheriesyields in the North Sea simulated with an end-to-end food webmodel. Progress in Oceanography, 102: 42–66.

Heink, U., and Kowarik, I. 2010. What are indicators? On the definitionof indicators in ecology and environmental planning. EcologicalIndicators, 10: 584–593.

ICES. 2005. Guidance on the application of the ecosystem approach tomanagement of human activities in the European marine environ-ment. ICES Co-operative Research Report 273, 22 pp.

ICES. 2009. Report of the Study Group on Risk Assessment andManagement Advice (SGRAMA). ICES Document CM 2009/RMC: 14. 36 pp.

ICES. 2012a. Report of the Workshop on Benchmarking IntegratedEcosystem Assessments (WKBEMIA). ICES Document CM 2012/SSGRSP: 08. 30 pp.

ICES. 2012b. Report of the Workshop on North Sea and Baltic SeaMultispecies Trade-offs (WKM-Trade). ICES Document CM2012/ACOM: 71. 15 pp.

ICES. 2012c. Report of the Working Group on the Ecosystem Effects ofFishing Activities (WGECO). ICES Document CM 2012/ACOM:26. 192pp.

ICES. 2013a. Report of the Working Group on the ICES ACOM/SCICOM Workshop on Ecosystem Overviews (WKECOVER).ICES Document CM ACOM/SCICOM: 01. 135 pp.

ICES. 2013b. Report of the Working Group on the Ecosystem Effects ofFishing Activities (WGECO). ICES Document CM 2013/ACOM:25. 117 pp.

ICES. 2014. ICES strategic plan 2014–2018. ICES Copenhagen. 19 pp.

Jennings, S. 2004. The ecosystem approach to fishery management: asignificant step towards sustainable use of the marine environment?Marine Ecology Progress Series, 274: 279–282.

Jennings, S. 2005. Indicators to support an ecosystem approach to fish-eries. Fish and Fisheries, 6: 212–232.

Jennings, S., and Le Quesne, W. J. F. 2012. Integration of environmentaland fishery management in Europe. ICES Journal of Marine Science,69: 1329–1332.

Jennings, S., and Rice, J. 2011. Towards an ecosystem approach to fish-eries in Europe: a perspective on existing progress and future direc-tions. Fish and Fisheries, 12: 125–137.

Kaplan, I. C., Gray, I. A., and Levin, P. S. 2013. Cumulative impactsof fisheries in the California Current. Fish and Fisheries.doi:10.1111/j.1467–2979.2012.00484.x.

Kaplan, I. C., Horne, P. J., and Levin, P. S. 2012. Screening CaliforniaCurrent fishery management scenarios using the Atlantisend-to-end ecosystem model. Progress in Oceanography, 102: 5–18.

Kershner, J., Samhouri, J. F., James, C. A., and Levin, P. S. 2011. Selectingindicator portfolios for marine species and food webs: a Puget soundcase study. PLoS one, 6: e25248.

Kraak, S. B. M., Kelly, C. J., Codling, E. A., and Rogan, E. 2010. On scien-tists’ discomfort in fisheries advisory science: the example ofsimulation-based fisheries management-strategy evaluations. Fishand Fisheries, 11: 119–132.

Kraak, S. B. M., Reid, D. G., Gerritsen, H. D., Kelly, C. J., Fitzpatrick, M.,Codling, E. A., and Rogan, E. 2012. 21st century fisheries manage-ment: a spatio-temporally explicit tariff-based approach combiningmultiple drivers and incentivising responsible fishing. ICES Journalof Marine Science, 69: 590–601.

Large, S. I., Fay, G., Friedland, K. D., and Link, J. S. 2013. Defining trendsand thresholds in responses of ecological indicators to fishing andenvironmental pressures. ICES Journal of Marine Science, 70:755–767.

van Leeuwen, J., van Hoof, L., and van Tatenhove, J. 2012. Institutionalambiguity in implementing the European Union Marine StrategyFramework Directive. Marine Policy, 36: 636–643.

Levin, P. S., Damon, M., and Samhouri, J. F. 2010. Developing meaning-ful marine ecosystem indicators in the face of a changing climate.Stanford Journal of Law, Science and Policy, 2: 36–48.

Levin, P. S., Fogerty, M. J., Murawski, S. A., and Fluharty, D. 2009.Integrated ecosystem assessments: developing the scientific basisfor ecosystem-based management of the ocean. PLoS Biology, 7:e1000014.

Levin, P. S., Kelble, C. R., Shuford, R., Ainsworth, C., de Reynier, Y.,Dunsmore, R., Fogarty, M. J., et al. 2014. Guidance for implementa-tion of integrated ecosystem assessments: a US perspective. ICESJournal of Marine Science, 71: 1198–1204.

Link, J. S. 2012. Overview of Ecosystem-based Management andIntegrated Ecosystem Assessments. CalCOFI Reports, 53: 91–92.

Mackinson, S., Deas, B., Beveridge, D., and Casey, J. 2009. Mixed-fisheryor ecosystem conundrum? Multispecies considerations informthinking on long-term management of North Sea demersal stocks.Canadian Journal of Fisheries and Aquatic Sciences, 66: 1107–1129.

Mackinson, S., Wilson, D. C., Galiay, P., and Deas, B. 2011. Engaging sta-keholders in fisheries and marine research. Marine Policy, 35: 18–24.

Methratta, E. T., and Link, J. S. 2006. Evaluation of quantitative indica-tors for marine fish communities. Ecological Indicators, 6: 575–588.

Mitleton-Kelly, E. 2003. Complex Systems and Evolutionary Perspectiveson Organisations: the Application of Complexity Theory toOrganisations. Advanced Series in Management. Elsevier ScienceLtd, Oxford, UK. 257 pp.

Mollmann, C., Lindegren, M., Blenckner, T., Bergstrom, L., Casini, M.,Diekmann, R., Flinkman, J., et al. 2014. Implementing ecosystem-


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based fisheries management: from single-species to integrated eco-system assessment and advice for Baltic Sea fish stocks. ICESJournal of Marine Science, 71: 1187–1197.

Murawski, S. A. 2007. Ten myths concerning ecosystem approaches tomarine resource management. Marine Policy, 31: 681–690.

Ojaveer, H., and Eero, M. 2011. Methodological challenges in assessingthe environmental status of a marine ecosystem: case study of theBaltic Sea. PLoS One, 6: e19231.

Ounanian, K., Delaney, A., Raakjaer, J., and Ramirez-Monsalve, P. 2012.On unequal footing: stakeholder perspectives on the marine strategyframework directive as a mechanism of the ecosystem-based ap-proach to marine management. Marine Policy, 36: 658–666.

Piet, G. J., Jansen, H. M., and Rochet, M-J. 2008. Evaluating potentialindicators for an ecosystem approach to fishery management inEuropean waters. ICES Journal of Marine Science, 65: 1449–1455.

Ratza, H. J., Dorner, H., Scott, R., and Barbas, T. 2010. Complementaryroles of European and national institutions under the CommonFisheries Policy and the Marine Strategy Framework Directive.Marine Policy, 34: 1028–1035.

Rice, J. 2003. Environmental health indicators. Ocean and CoastalManagement, 46: 235–259.

Rice, J. 2011. Managing fisheries well: delivering the promises of an eco-system approach. Fish and Fisheries, 12: 209–231.

Rice, J. C., and Rochet, M.-J. 2005. A framework for selecting a suite ofindicators for fisheries management. ICES Journal of MarineScience, 62: 516–527.

Rijnsdorp, A. D., van Overzee, H. M. J., and Poos, J. J. 2012. Ecologicaland economic trade-offs in the management of mixed fisheries: acase study of spawning closures in flatfish fisheries. MarineEcology Progress Series, 447: 179–194.

Rochet, M-J., and Rice, J. C. 2005. Do explicit criteria help in selectingindicators for ecosystem-based fisheries management? ICESJournal of Marine Science, 62: 528–539.

Rockmann, C., Ulrich, C., Dreyer, M., Bell, E., Borodzicz, E.,Haapasaari, P., Hauge, K. H., et al. 2012. The added value of partici-patory modelling in fisheries management—what has been learnt?Marine Policy, 36: 1072–1085.

Sainsbury, K. J., Punt, A. E., and Smith, A. D. M. 2000. Design of oper-ational management strategies for achieving fishery ecosystemobjectives. ICES Journal of Marine Science, 57: 731–741.

Samhouri, J. F., Haupt, A. J., Levin, P. S., Link, J. S., and Shuford, R. 2014.Lessons learned from developing integrated ecosystem assessmentsto inform marine ecosystem-based management in the USA. ICESJournal of Marine Science, 71: 1205–1215.

Samhouri, J. F., Lester, S. E., Selig, E. R., Halpern, B. S., Fogarty, M. J.,Longo, C., and McLeod, K. L. 2012. Sea sick? Setting targets toassess ocean health and ecosystem services. Ecosphere, 3: 41.

Samhouri, J. F., and Levin, P. S. 2012. Linking land- and sea-based activ-ities to risk in coastal ecosystems. Biological Conservation, 145:118–129.

Samhouri, J. F., Levin, P. S., and Ainsworth, C. H. 2010. Identifyingthresholds for ecosystem-based management. PLoS One, 5: e8907.

Samhouri, J. F., Levin, P. S., and Harvey, C. J. 2009. Quantitative evalu-ation of marine ecosystem indicator performance using food webmodels. Ecosystems, 12: 1283–1298.

Schellnhuber, H. J., and Sahagian, D. 2002. The twenty-three GAIMquestions. Global Change Newsletter, 49: 20–21.

Schwach, V., Bailly, D., Christensen, A-S., Delaney, A. E., Degnbol, P.,van Densen, W. L. T., Holm, P., et al. 2007. Policy and knowledgein fisheries management: a policy brief. ICES Journal of MarineScience, 64: 798–803.

Sissenwine, M., and Murawski, S. A. 2004. Moving beyond ‘intelligenttinkering’: advancing an Ecosystem Approach to Fisheries. MarineEcology Progress Series, 274: 291–295.

Smith, A. D. M., Fulton, E. J., Hobday, A. J., Smith, D. C., and Shoulder,P. 2007. Scientific tools to support the practical implementation ofecosystem-based fisheries management. ICES Journal of MarineScience, 64: 633–639.

Stelzenmuller, V., Lee, J., South, A., and Rogers, S. I. 2010. Quantifyingcumulative impacts of human pressures on the marine environment:a geospatial modelling framework. Marine Ecology Progress Series,398: 19–32.

Trenkel, V. M., and Rochet, M-J. 2003. Performance of indicatorsderived from abundance estimates for detecting the impact offishing on a fish community. Canadian Journal of Fisheries andAquatic Sciences, 60: 67–85.

Ulrich, C., Reeves, S. A., Vermard, Y., Holmes, S. J., and Vanhee, W.2011. Reconciling single-species TACs in the North Sea demersalfisheries using the Fcube mixed-fisheries advice framework. ICESJournal of Marine Science, 68: 1535–1547.

Verweij, M. C., and van Densen, W. L. T. 2010. Differences in causal rea-soning about resource dynamics and consequences for the participa-tory debate on North Sea fisheries. Marine Policy, 34: 1144–1155.

Walther, Y., and Mollmann, C. 2014. Bringing integrated ecosystemassessments to real life: a scientific framework for ICES. ICESJournal of Marine Science, 71: 1183–1186.

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Original Article

Bringing integrated ecosystem assessments to real life:a scientific framework for ICES

Yvonne M. Walther1* and Christian Mollmann2*1Department of Aquatic Resources, Swedish University of Agricultural Sciences, Utovagen 5, SE-37137 Karlskrona, Sweden2Institute for Hydrobiology and Fisheries Science, Center for Earth System Research and Sustainability (CEN), University of Hamburg, KlimaCampus,Grosse Elbstrasse 133, D-22767 Hamburg, Germany

*Corresponding author: tel: +46 709 35 92 82; fax: +46 10 478 40 75; e-mail: [email protected]

Walther, Y., and Mollmann, C. 2014. Bringing integrated ecosystem assessments to real life: a scientific framework for ICES. – ICES Journal of MarineScience, 71: 1183–1186.

Received 10 March 2013; accepted 4 September 2013; advance access publication 13 November 2013.

An ecosystem approach to management (EAM) aims to secure a healthy ecosystem along with sustainable use of its goods and services. Althoughthe main principles of EAM are agreed upon and desirable, wider implementation of EAM is still a challenge. The difficulties stem from uncleardefinition and communication of the EAM, lack of routines or protocols to develop ecosystem-based advice, inappropriate institutional struc-tures, and communication issues between scientists, advisers, and managers. Integrated ecosystem assessment (IEA) is an instrument that hasproven to help in the implementation of EAM. For successful implementation of EAM and IEA in the European regional seas context, an inter-national forum is required that develops tailor-made EAM tools specific to the different regional ecosystems to overcome fragmented nationalstrategies. We describe a multinational peer network of working groups developed within the International Council for the Exploration of the Sea(ICES) under the auspice of Science Steering Group on Regional Sea Programmes. Available is a wealth of data, expertise, scientific methods, andmodels for each regional sea. This network can be instrumental in advancing IEA for the implementation of EAM in the North Atlantic seas.

Keywords: ecosystem approach to management (EAM), ecosystem-based management (EBM), integrated ecosystem assessment (IEA),International Council for Exploration of the Sea, The Science Steering Group on Regional Sea Programmes, Marine Strategy Framework Directive.

IntroductionThe idea of an ecosystem approach to management (EAM) is tomanage natural resources in a holistic way, by considering the inter-acting influences of multiple use sectors on the environment(McLeod and Leslie, 2009). The overall goal is to assure the healthof the ecosystem alongside appropriate use of the environment forthe benefit of future generations (Jennings, 2004). EAM has beena core debate of natural science and resource management forseveral decades (Grumbine, 1994) and the main principles ofEAM are generally agreed upon and desired by most policy-makers,managers, and scientists. Moreover, the intention to move towardsthe adoption of a comprehensive and integrated EAM is no longerjust an obscure future vision (Levin et al., 2009; Lubchenco et al.,2010; Tallis et al., 2010). But despite the political and societal will,as well as the availability of scientific concepts and information to

do EAM, the wider implementation of an EAM remains a challenge(Murawski, 2007; Rice, 2011).

Reasons for the difficulty in implementing EAM are manifold,among them unclear definition and communication of EAM toimportant user groups (e.g. fishers), resistance of advice and man-agement bodies to develop or revise their routines and protocolstowards ecosystem-based approaches, inappropriate institutionalstructures (i.e. sector-specific independent agencies), and commu-nication issues between scientists, advisers, and managers. Webelieve that overcoming the problems of implementing EAMneeds a forum that channels and translates relevant scientificresults into practically applicable EAM tools; a forum that developstailor-made EAM tools specific to different regional seas’ challengesand needs, thereby overcoming national defragmentation as seen inthe European Union; and last but not least, a forum that furthers the

#2013 International Council for the Exploration of the Sea. Published by Oxford University Press. All rights reserved.For Permissions, please email: [email protected]

ICES Journal of

Marine ScienceICES Journal of Marine Science (2014), 71(5), 1183–1186. doi:10.1093/icesjms/fst161

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communication between science and advisory bodies, and eventu-ally to managers.

Here we describe the bottom-up development of, the presentwork on, and the potential future for implementing EAM via amultinational peer network of working groups within theInternational Council for the Exploration of the Sea (ICES),under the auspice of the SCICOM Steering Group on theRegional Sea Programmes (SSGRSP). We suggest that thisnetwork will be instrumental in developing and advancing inte-grated ecosystem assessments (IEA) towards further implementa-tion of EAM in the North Atlantic seas.

IEA: a concept for EAM implementationOften, EAM is seen as a complex, scientifically driven process that ishampered by lack of knowledge about the ecosystem. But the percep-tion that knowledge is insufficient to apply EAM has been effectivelycontradicted (Murawski, 2007). Rather, it is more important to maxi-mize the use of available information than to emphasize areas of un-certainty (Rice, 2011). Despite the scientific facade, EAM isforemost a decision process (Walters and Martell, 2004) and thedesired status of an ecosystem is not decided in a scientific process.Yet science needs to assist that process with knowledge that helps thedecision-making. Looking more closely, successful cases of EAM aresuccessful not because of the designation of a scientific programme,but rather because of a multidisciplinary, multi-actor process integrat-ing research and management, i.e. a framework connecting scientists,managers, and stakeholders (deReynier et al., 2010). IEA is a proposedframework that has the ability to synthesize and analyse scientific in-formation in relation to specified ecosystem management objectivesand is especially suitable for engaging different stakeholder and deci-sion maker groups (Levin et al., 2009; Tallis et al., 2010; Levin et al.,2013). The main purpose of IEAs is to integrate physical, biological,and socio-economic data to evaluate trade-offs among objectivesacross different ecosystem goods and services.

ICES and the development of a framework for IEAThe ICES, as an intergovernmental organization with 20 memberstates, has the task to organize science and provide advice for the man-agement of the marine environment and associated living resources inthe North Atlantic (Rozwadowski, 2002). The advice provided is wellknown and relates to the, for example, the EU Common FisheriesPolicy (CFP) and EU Marine Strategy Framework Directive(MSFD). The ICES anticipates and is prepared for future demandsof ecosystem considerations into this advice. The new “ICESStrategy” under construction (including the Strategic, Advisory, andScience Plans) prepares for the anticipated request for specific consid-erations of ecosystem drivers and ecosystem impacts on differentocean-use sectors, as well as interactions among them. IEA will be astrong component in the new “ICES Strategy” and development ofIEAs for the European regional seas covered by ICES has been con-ducted under the auspices of Science Steering Group on RegionalSea Programmes (SSGRSP; Walther, 2011).

Ecosystem assessments within ICES started in 2006, conductedby the Regional Ecosystem Study Group for the North Sea(REGNS; ICES, 2006) based on methodology developed in theUSA and Canada (Link, 2002; Choi et al., 2005; Mollmann andDiekmann, 2012). The REGNS conducted the first assessment ofthe state and development of abiotic and biotic variables as well asnatural and human pressures in the North Sea. The template ofREGNS was then taken up by Baltic Sea scientists leading to theformation of the Working Group on Integrated Assessments of

the Baltic Sea (WGIAB; ICES, 2007), an initiative taken togetherwith the Helsinki Commission (HELCOM). Initially, the ecosystemassessments mainly assessed the impact of climate, fisheries,and eutrophication to combine the major drivers that previouslywere evaluated in isolation (Mollmann et al., 2013). Theseanalyses demonstrated pronounced climate, fisheries, andeutrophication-related structural changes for several Baltic subsys-tems (Mollmann et al., 2009; Diekmann and Mollmann, 2010;Lindegren et al., 2010). The WGIAB serves as a counterpart forthe ICES Baltic Fisheries Assessment Working Group (WGBFAS),and has over several years incrementally provided ecosystem knowl-edge for more ecosystem-based fish stock assessments and advice(Gardmark et al., 2011; Mollmann et al., 2013). The WGIAB nowdevelops tools to be applicable in future IEAs for the Baltic Sea(ICES, 2013a). The WGNARS was the first group to introduceand explore the full IEA concept developed by NOAA (USNational Oceanic and Atmospheric Administration) (Levin et al.,2009). Early on the group focused on the importance of human pres-sures and the value of indicator-based approaches. The WGNARShas now continued towards closing the IEA cycle by showing exam-ples of how to include human pressures and socio-economic aspects(ICES, 2010, 2011, 2012a) and has developed into a focal point forexploring and testing facets of IEAs in the USA and Canada.

The IEA concept has developed within ICES from a few solitaryexpert groups to a wide network under the auspice of SSGRSP. Thishas come true by a “sticky” process where existing groups help toattract scientists from different areas of expertise, geographical butalso topical, to create new regional IEA groups. Through thissticky process, knowledge and methodology developed andapplied has been transferred between regions. Today, SSGRSP iscomposed of a network of IEA groups including the Baltic Sea(WGIAB), the North Sea (WGINOSE), the Western EuropeanShelf Seas (WGEAWESS), the Norwegian Sea (WGINOR), andthe North West Atlantic Regional Sea (WGNARS) in the USA–Canada. The current and planned groups with their acronyms areshown in the schematic structure which is affectionately termedthe “Fishbone” of the SSGRSP (Figure 1). The structure alsoincludes groups that work on topical issues that interact with andcan add value to IEAs, e.g. Ecosystems economics (SGIMM), BestPractices for Large Marine Ecosystems (WGLMEBP), comparingecosystems (WGCOMEDA), and linking contaminants to IEA(WKLINCON). Eventually, it is envisaged that there will be anecosystem group for all regional seas that are covered by ICES.

The ICES IEA process is also complemented by ecosystem over-views that are being conducted or planned (WKECOVER; ICES,2013b). These overviews effectively are reports on ecosystemstatus that can be largely considered a product of the IEA process.Similar and related work is espoused in the ICES context (e.g. mod-elling, risk assessments, etc.). The salient point being that the IEAprocess can serve as a useful mechanism to collate and communicatea wide range of disparate information into packages that are usefulfor particular management issues being asked.

The future of IEA within ICESDespite the early successes of the regional groups, a common frame-work for IEA, especially in the European regional seas, is still lacking.To ensure further progress, SSGRSP initiated a series of Workshopson Benchmarking Integrated Ecosystem Assessments (WKBEMIA).In the first workshop (ICES, 2012b), progress of each regional groupwas evaluated to identify common approaches, results, and chal-lenges. The workshop adopted the NOAA IEA approach (Levin

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et al., 2009) as a framework for the SSGRSP regional groups, but alsoconsidered approaches developed and discussed by the UN Foodand Agriculture Organisation (FAO) and the ICES WorkingGroup on Ecosystem Effects of Fishing (ICES, 2013c). The region-specific application of the different methods and model require-ments for each component of the Levin et al. (2009) cycle wereidentified, and now need to be further developed by the regionalgroups. An important step will be to conduct a rigorous scopingexercise that a priori develops the extent of the EAM to be developed,i.e. which sectors, pressures, and ecosystem components need to beincluded in an IEA for a specific region. Then other components ofthe IEA cycle, i.e. indicator development, risk assessments, andmanagement strategy evaluation, can be developed (Levin et al.,2009). Plenty of data, expertise, scientific methods, and especiallymodels are available for every regional sea.

Future benchmarking workshops will continue to develop IEAmethods specific to the needs of the different regional seas.Methods will include the OSPAR Quality Status Report (QSR)approach (Knights et al., 2011), the REGNS approach (ICES,2006), Bayesian Belief Networks (BBN) (Stelzenmuller et al.,2011), and the Ocean health index (OHI; Halpern et al., 2012).These methods have often been seen as competing with IEAs, butWKBEMIA noted that instead they are in fact quite complementary.Each has strengths that can be used in aspects of IEA quantitative nu-merical processes, i.e. REGNS and BBN can be used when data areavailable, and expert judgement-based methods (OSPAR QSR andOHI) when data are sparse. The methods used should investigate

and meet the considerations in directives, e.g. the EU’s MSFDneed for Good Environmental Status indicators (EU-COM, 2008)and HELCOM Baltic Sea Action Plan (HELCOM, 2007). Theapproaches can be implemented in relation to applied directiveson ecosystem level or even on single sectors, pressures, and compo-nents when necessary, though using the common IEA framework.A future challenge will be a stronger consideration of cumulativeeffects of anthropogenic pressures. Further workshops on IEA willtherefore focus on engaging a wider science community, i.e. includ-ing other sectors (e.g. traffic, eutrophication) and socio-economics.

The first WKBEMIA workshop emphasized that IEAs will beimportant for improving the single sector, issue-based (e.g. fisheries)advice for ICES by providing ecosystem context. Results from an IEAprocess should be linked to traditional stock assessments and incre-mentally ecosystem and potentially socio-economic knowledgewould be included in existing advice and management schemesleading to an Ecosystem Approach to Fisheries Management (EAF;Rice, 2011). First steps have already been conducted for Baltic fishstock advice (Mollmann, 2013).

Implementing the EAM and IEAs still requires some rethinkingand restructuring of institutional and governance structures. ForICES, this means a closer cooperation between science and advice.Operationally, this would be performed through a closer linkageof the regional IEA groups with stock assessment and advice draftinggroups. In a longer perspective, stock assessment groups could orshould be complemented by or even developed into ecosystemassessment groups (ICES, 2012b).

Figure 1. Expert Groups under the auspice of ICES Science Steering Group on Regional Sea Programmes. Expert groups on side bones are IEAgroups; expert groups on the main bone have a more overarching and/or topical function. WGIAB, Working Group on Integrated assessments inthe Baltic Sea; WGINOSE, Working Group on Integrated Assessments of the North Sea; WGINOR, Working Group on the Integrated Assessments ofthe Norwegian Sea; WGEAWESS, Working Group on Ecosystem Assessment of Western European Shelf Seas; WGNARS, Working Group on theNorthwest Atlantic Regional Sea; WGLMEBP, Working Group on Large Marine Ecosystems Best Practices; WKLINCON, Workshop on LinkingContaminant Issues to Integrated Ecosystem Assessments; WKBEMIA, Workshop on Benchmarking Integrated Ecosystem Assessments;SGSPATIAL, Study Group on Spatial Analyses for the Baltic Sea; SGIMM, Study Group on Introducing Coupled Ecological–Economic Modellingand Risk Assessment into Management Tools; WKCOMEDA, Working Group on Comparative Analyses between European Atlantic andMediterranean marine ecosystems to move towards an Ecosystem-based Approach to Fisheries.

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ConclusionsWe think that for successfully implementing the EAM and IEAs inthe European regional seas, an international forum is requiredthat develops tailor-made EAM tools specific to the different region-al ecosystems to overcome fragmented national strategies. Webelieve that SSGRSP and its regional IEA groups provides such aforum for that, particularly with the potential to translate scienceinto management application and further the communicationbetween science advisory bodies, and managers. In a few decades,from now we may consider EAM and IEAs as common as wethink the Internet is in our society today. Yet, as noted in thecontext of developing the Internet, “The point is, that when wesucceed, we succeed because of our individual initiative, but alsobecause we do things together” (The International HeraldTribune, 22–23 September 2012, p. 14 continued on p. 16).

ReferencesChoi, J. S., Frank, K. T., Petrie, B. D., and Leggett, W. C. 2005. Integrated

assessment of large marine ecosystem: a case study of the devolutionof the Eastern Scotian Shelf, Canada. Oceanogr. Mar. Biol. Ann.Rev. 43: 47–67.

deReynier, Y. L., Levin, P. S., and Shoji, N. L. 2010. Bringing stake-holders, scientists, and managers together through an integratedecosystem assessment process. Marine Policy, 34: 534–540.

Diekmann, R., and Mollmann, C. 2010. Integrated ecosystem assess-ments of seven Baltic Sea areas covering the last three decades.ICES Cooperative Research Report 302.

EU-COM. 2008. Directive 2008/56/EC of the European Parliament andof the Council of 17 June 2008 establishing a framework for commu-nity action in the field of marine environmental policy (MarineStrategy Framework Directive: 19–40.

Gardmark, A., Nielsen, A., Floeter, J., and Mollmann, C. 2011. Depletedmarine fish stocks and ecosystem-based management: on the road torecovery, we need to be precautionary. ICES Journal of MarineScience, 68: 212–220.

Grumbine, R. E. 1994. What is ecosystem management? ConservationBiology, 8: 27–38.

Halpern, B. S., Longo, C., Hardy, D., McLeod, K. L., Samhouri, J. F.,Katona, S. K., Kleisner, K., et al. 2012. An index to assess the healthand benefits of the global ocean. Nature, 488: 615–620.

HELCOM. 2007. Baltic Sea Action Plan, HELCOM min. 101 pp.

ICES. 2006. Report of the Regional Ecosystem Study Group of the NorthSea (REGNS). ICES CM, RMC:06. 111 pp.

ICES. 2007. Report of the ICES/HELCOM Working Group onIntegrated Assessments of the Baltic Sea (WGIAB). ICES CM,BCC:04. 53 pp.

ICES. 2010. ICES WGNARS REPORT 2010 Report of the Working Groupon the Northwest Atlantic Regional Sea (WGNARS) InternationalCouncil for the Exploration of the Sea. ICES CM, SSGRSP:03. 67 pp.

ICES. 2011. ICES WGNARS REPORT 2011 Report of the WorkingGroup on the Northwest Atlantic Regional Sea (WGNARS)Halifax, Canada International Council for the Exploration of theSea. ICES CM, SSGRSP:01. 69 pp.

ICES. 2012a. ICES WGNARS REPORT 2012 Report of the WorkingGroup on the Northwest Atlantic Regional Sea (WGNARS)International Council for the Exploration of the Sea. ICES CM,SSGRSP:01. 83 pp.

ICES. 2012b. Report of the Workshop on Benchmarking IntegratedEcosystem Assessments (WKBEMIA). ICES CM, in press.

ICES. 2013a. Report of The Working Group on Integrated Assessmentsof the Baltic Sea (WGIAB). ICES CM, SSGRSP:05. 53 pp.

ICES. 2013b. Report of the Working Group on the ICES ACOM/SCICOM Workshop on Ecosystem Overviews. ACOM/SCICOM01. 130 pp.

ICES. 2013c. Report of the Working Group on the Ecosystem Effects ofFishing Activities (WGECO). ICES Document CM 2013/ACOM:25.115 pp.

Jennings, S. 2004. The ecosystem approach to fishery management: asignificant step towards sustainable use of the marine environment?Marine Ecology Progress Series, 274: 279–282.

Knights, A., Koss, R., Papadopoulou, N., Cooper, L., and Robinson, L.2011. Sustainable use of European regional seas and the role of theMarine Strategy Framework Directive. Deliverable 1, EC FP7Project (244273) “Options for Delivering Ecosystem-based MarineManagement.”

Levin, P. S., Kelble, C. R., Shuford, R. L., Ainsworth, C., deReynier, Y.,Dunsmore, R., Fogarty, M. J., et al. 2014. Guidance for implementa-tion of integrated ecosystem assessments: A US perspective. ICESJournal of Marine Science, 71: 1198–1204.

Levin, P. S., Fogarty, M. J., Murawski, S. A., and Fluharty, D. 2009.Integrated ecosystem assessments: developing the scientific basisfor ecosystem-based management of the ocean. PLoS Biology,7: e1000014.

Lindegren, M., Mollmann, C., Nielsen, A., Brander, K., MacKenzie,B. R., and Stenseth, N. C. 2010. Ecological forecasting underclimate change: the case of Baltic cod. Proceedings of the RoyalSociety B: Biological Sciences, 277: 2121–2130.

Link, J. S. 2002. What does ecosystem-based fisheries managementmean. Fisheries (Bethesda), 27: 18–21.

Lubchenco, J., Sutley, N., and Approach, A. E. 2010. Proposed U.S.Policy for Ocean, Coast, and Great Lakes Stewardship, 328:1485–1486.

McLeod, K. L., and Leslie, H. M. 2009. Ecosystem-based managementfor the oceans. Island Press, Washington, DC.

Mollmann, C., Lindegren, M., Blenckner, T., Bergstrom, L., Casini, M.,Diekmann, R., Flinkman, J., et al. 2014. Implementing ecosystem-based fisheries management: from single-species to integrated eco-system assessment and advice for Baltic Sea fish stocks. ICESJournal of Marine Science, 71: 1187–1197.

Mollmann, C., and Diekmann, R. 2012. Marine ecosystem regime shiftsinduced by climate and overfishing: a review for the Northern hemi-sphere. In Advances in Ecological Research, vol. 47, pp. 303–347.Ed. by U. Jacob, and E. O’Gorman. Academic Press, London. 510 pp.

Mollmann, C., Diekmann, R., Muller-Karulis, B., Kornilovs, G., Plikshs,M., and Axe, P. 2009. Reorganization of a large marine ecosystem dueto atmospheric and anthropogenic pressure: a discontinuous regimeshift in the Central Baltic Sea. Global Change Biology, 15:1377–1393.

Murawski, S. 2007. Ten myths concerning ecosystem approaches tomarine resource management. Marine Policy, 31: 681–690.

Rice, J. 2011. Managing fisheries well: delivering the promises of anecosystem approach. Fish and Fisheries, 12: 209–231.

Rozwadowski, H. M. 2002. The Sea Knows No Boundaries. University ofWashington Press, Seattle and London.

Stelzenmuller, V., Schulze, T., Fock, H. O., and Berkenhagen, J. 2011.Integrated modelling tools to support risk-based decision-makingin marine spatial management. Marine Ecology Progress Series,441: 197–212.

Tallis, H., Levin, P. S., Ruckelshaus, M., Lester, S. E., McLeod, K. L.,Fluharty, D. L., and Halpern, B. S. 2010. The many faces ofecosystem-based management: Making the process work today inreal places. Marine Policy, 34: 340–348.

Walters, C. J., and Martell, S. J. D. 2004. Fisheries Ecology andManagement. Princeton University Press, Princeton, NJ.

Walther, Y. 2011. SSGRSP—the square peg in a round-peg society. ICESInsight, 48: 28–32.


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Original Article

Implementing ecosystem-based fisheries management: fromsingle-species to integrated ecosystem assessment and advicefor Baltic Sea fish stocks

Christian Mollmann1*, Martin Lindegren2, Thorsten Blenckner3, Lena Bergstrom4, Michele Casini5,Rabea Diekmann1, Juha Flinkman6, Barbel Muller-Karulis7, Stefan Neuenfeldt8, Jorn O. Schmidt9,Maciej Tomczak7, Rudiger Voss9, and Anna Gardmark4

1Institute for Hydrobiology and Fisheries Science, Center for Earth System Research and Sustainability (CEN), Klima Campus, University of Hamburg,Grosse Elbstrasse 133, D-22767 Hamburg, Germany2Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA3Stockholm Resilience Centre, Stockholm University, Kraftriket 10, SE-106 91 Stockholm, Sweden4Department of Aquatic Resources, Institute of Coastal Research, Swedish University of Agricultural Sciences, Skolgatan 6, SE-742 22 Oregrund, Sweden5Department of Aquatic Resources, Institute of Marine Research, Swedish University of Agricultural Sciences, PO Box 4, SE-54330 Lysekil, Sweden6Marine Research Center, Finnish Environment Institute (SYKE), Mechelininkatu 34a, PO Box 140, FI-00251 Helsinki, Finland7Stockholm University Baltic Sea Centre, Stockholm University, SE-106 91 Stockholm, Sweden8Technical University of Denmark, National Institute of Aquatic Resources, Charlottenlund Castle, DK-2920 Charlottenlund, Denmark9Department of Economics, University of Kiel, Wilhelm-Seelig-Platz 1, 24118 Kiel, Germany

*Corresponding author: tel: +49 40 42838 6621; fax: +49 40 42838 6618; e-mail: [email protected]

Mollmann, C., Lindegren, M., Blenckner, T., Bergstrom, L., Casini, M., Diekmann, R., Flinkman, J., Muller-Karulis, B., Neuenfeldt, S., Schmidt, J. O.,Tomczak, M., Voss, R., and Gardmark, A. 2014. Implementing ecosystem-based fisheries management: from single-species to integratedecosystem assessment and advice for Baltic Sea fish stocks. – ICES Journal of Marine Science, 71: 1187–1197.

Received 10 March 2013; accepted 24 June 2013; advance access publication 24 August 2013.

Theory behind ecosystem-based management (EBM) and ecosystem-based fisheries management (EBFM) is now well developed. However,the implementation of EBFM exemplified by fisheries management in Europe is still largely based on single-species assessments and ignoresthe wider ecosystem context and impact. The reason for the lack or slow implementation of EBM and specifically EBFM is a lack of a co-herent strategy. Such a strategy is offered by recently developed integrated ecosystem assessments (IEAs), a formal synthesis tool to quan-titatively analyse information on relevant natural and socio-economic factors, in relation to specified management objectives. Here, wefocus on implementing the IEA approach for Baltic Sea fish stocks. We combine both tactical and strategic management aspects into asingle strategy that supports the present Baltic Sea fish stock advice, conducted by the International Council for the Exploration of theSea (ICES). We first review the state of the art in the development of IEA within the current management framework. We then outlineand discuss an approach that integrates fish stock advice and IEAs for the Baltic Sea. We intentionally focus on the central Baltic Seaand its three major fish stocks cod (Gadus morhua), herring (Clupea harengus), and sprat (Sprattus sprattus), but emphasize that our ap-proach may be applied to other parts and stocks of the Baltic, as well as other ocean areas.

Keywords: Baltic Sea, indicator approaches, integrated advice, integrated ecosystem assessment, strategic modelling.

#2013 International Council for the Exploration of the Sea. Published by Oxford University Press. All rights reserved.For Permissions, please email: [email protected]

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IntroductionEcosystem-based management (EBM) is now a central paradigmunderlying living marine resource policy worldwide. Contrary toconventional resource management approaches, EBM addressesthe cumulative impacts of multiple ocean uses and climate changeon multiple ecosystem components (Pikitch et al., 2004; Leslieand McLeod, 2007; Marasco et al., 2007). Hence, the goal of EBMis to find trade-offs between a diverse set of ecosystem servicesand often conflicting, management goals (McLeod and Leslie,2009). Although the theory behind EBM is well developed, its imple-mentation lacks behind (Berkes, 2012). A clear example is fisheriesmanagement in Europe that is still largely based on single-speciesassessments and ignores the wider ecosystem context and impacts.The reason for the lack or slow implementation of EBM is a lackof a coherent strategy. Such a strategy is offered by IntegratedAssessment (IA). IA is commonly defined as an interdisciplinaryprocess of combining, interpreting, and communicating knowledgefrom diverse scientific disciplines, in such a way that the whole set ofcause–effect interactions of a problem can be evaluated from a syn-optic perspective with two characteristics: (i) it should have addedvalue compared with single disciplinary assessments and (ii) itshould provide useful information to decision makers (Rotmansand Dowlatabadi, 1997; van der Sluijs, 2002).

IAs were initially developed during the 1970s, fuelled by scientificand public policy efforts to understand and control acid deposition inEurope and North America (van der Sluijs, 2002). Since the 1980s,they have played a role in the development of the internationalclimatepolicy leadingto,andbeingpartof, theworkof theIntergovern-menta lPanel on Climate Change (IPCC). In this context, IAs werelargely based on IA models (IAMs), computer simulation models com-biningknowledgefrommultipledisciplines,andhencesuitedtoanalyseenvironmental problems in an integrated fashion (Rotmans andDowlatabadi, 1997). Nowadays, it is widely recognized that a completeIA methodology combines IAMswith otheranalytical tools for integra-tion, such as analyses of large datasets and participatory approaches.

Early developments of IAs within the field of marine living re-source management were started in North America and based onanalyses of large datasets showing substantial changes in ecosystemstates due to climate and human impacts (Hare and Mantua, 2000;Link et al., 2002; Choi et al., 2005). Only recently, integrated ecosys-tem assessments (IEAs) have been developed as a formal synthesistool to quantitatively analyse information on relevant natural andsocio-economic factors, in relation to specified EBM objectives(Levin et al., 2009). IEAs provide a strategy to overcome the still pre-vailing single-species and single-sector approaches; they organizescience in order to inform decisions in marine EBM at multiplescales and across sectors (Levin et al., 2009; Tallis et al., 2010).

The goals and objectives of EBM and IEA need to be specified be-forehand (Jennings, 2005; Levin et al., 2009). The specified goalsthen define the focal components of the EBM and IEA approach(Kershner et al., 2011), which may range from a specific ecosystem-based fisheries management (EBFM) to a full blown cross-sectorEBM approach (Leslie and McLeod, 2007; McLeod and Leslie,2009). Although the ambitious objectives of the European Union(EU) Marine Strategy Framework Directive (MSFD) call for a fullEBM approach, fisheries management within the reformed EUCommon Fisheries Policy (CFP) still relies on the developmentand implementation of a more sector-specific EBFM approach.

Here, we focus on the process of implementing EBFM for theBaltic Sea using elements of the IEA approach. IAs and IEAs are

generally strategic in that they explore possible future trajectoriesof human and natural systems under a multitude of natural and an-thropogenic pressures (Weyant et al., 1996; Levin et al., 2009).However, present EU fisheries management requires annual stockassessment and advice. Hence, we attempt to combine both require-ments into a strategy that supports the present Baltic Sea fish stockadvice, conducted by the International Council for the Explorationof the Sea (ICES). We first review the state of the art in the develop-ment of EBFM and IA within the current management framework.We then outline an IEA-based approach that integrates fish stockadvice and IEAs for the Baltic Sea. We intentionally focus on thecentral Baltic Sea and the three major fish stocks cod (Gadusmorhua), herring (Clupea harengus), and sprat (Spratus sprattus),but emphasize that our approach may be applied to other partsand stocks of the Baltic, as well as other ocean areas.

Elements of EBM in present operational fishstock assessmentICES advice on total allowable catches (TACs) to the EU Commissionis currently based on targets of fishing mortality at maximum sus-tainable yield (FMSY) and, for Eastern Baltic cod, on an EU manage-ment plan (EC, 2007; ICES, 2012a). The analytical assessments ofBaltic fish stocks delivering the basis for the advice are conductedon a stock-by-stock basis. Extended survivor analysis or a state-space fish stock assessment model (www.stockassessment.org), bothbased on commercial catch-at-age data supplemented by fishery-independent survey indices, are applied to obtain estimates of keystock parameters, such as spawning-stock biomass (SSB), recruit-ment, and fishing mortality (F; Shepherd, 1999; ICES, 2012b).Multispecies interactions are currently only considered for themain forage fish species, namely sprat and central Baltic herring,and for cannibalism on juvenile cod. For these stocks, predationmortality by the top predator cod is derived from multispecies as-sessment models (previously multispecies virtual population ana-lysis; currently stochastic multispecies model; ICES, 2012a) andused to update the natural mortality input to the single speciesforage fish stock assessments.

As part of the assessment process, short-term forecasts (3 years)are conducted starting with the latest assessment year and using esti-mates of recruitment based on empirical spawning stock–recruit-ment relationships. Environmental data to inform these forecastsare only used for the herring stock in the Gulf of Riga (ICES,2012b). Data used are the copepod Eurytemora affinis, the mainprey for larval herring, and water temperature determining thetiming and distribution of herring spawning (Cardinale et al., 2009).Previously, the winter index of the North Atlantic Oscillation(NAO) and water temperature have been used in forecasts of spratyear-class strength (MacKenzie and Koster, 2004; ICES, 2006), butthese are no longer used due to problems with matching environ-mental time-series updates with the assessment meetings.

Multispecies modelling has a long tradition for the Baltic Sea eco-system (Sparholt, 1994; Gislason, 1999; Koster et al., 2001) but hasnever been used fully in operational fish stock assessment (asidefrom providing input to single species stock assessments, seeabove). However recently, in response to a request by the EU commis-sion, a multispecies assessment has been conducted as a pilot studytowards implementing the ecosystem approach (ICES, 2012d;STECF, 2012). The assessment was conducted using SMS thataccounts for the mortality inflicted by cod on sprat, herring, and ju-venile cod. Simulations revealed all species-specific multispecies FMSY

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to be higher than their single-species counterparts. However, particu-larly for cod and sprat, simulations show that higher fishing mortalitywill give very similar long-term yields, but result in lower SSBs and ahigher riskof stock collapse. Model results further indicate that higherF on cod will result only in a minor increase in cod yield, but in highersprat and herring yields. However, modelling of FMSY currentlyignores structural uncertainty such as variable predator–preyoverlap and density-dependent growth. Hence, ICES (2012d) andSTECF (2012) concluded that more work is needed to fully under-stand the results of the multispecies runs and their implications forthe Baltic fish stock advice and management.

Indicator approaches to IAsIntegrated trend and status assessmentsDespite efforts towards multispecies considerations, Baltic fishstock assessments are mostly single species, ignoring the larger eco-system context (Casini et al., 2011a). As a first step towards develop-ing more integrative assessments, analyses on the state anddevelopment of the various Baltic ecosystems have been conductedusing large multitrophic datasets (ICES, 2008; Mollmann et al.,2009; Diekmann and Mollmann, 2010; Lindegren et al., 2010a,2012a). These so-called integrated trend analyses (ITAs) used multi-variate statistics based on an approach developed for the NorthPacific and Atlantic, as well as the North Sea ecosystems (Hare andMantua, 2000; Link et al., 2002; Choi et al., 2005; Weijerman et al.,2005; Kenny et al., 2009; Mollmann and Diekmann, 2012).Analyses of these large datasets were conducted using dimension re-duction techniques, mainly principal component analysis (PCA; e.g.Legendre and Legendre, 1998) and methodologies to identify stepchanges in biotic and abiotic variables, such as STARS (Rodionov,2004) or chronological clustering (Legendre et al., 1985).

Here, we present a reanalysis of data from the Central Baltic Seausing 57 annual time-series (1979–2010), in two separate PCAs on28 biotic variables from phytoplankton to fish and 29 abioticvariables describing the physical conditions and anthropogenicdriving forces such as nutrient concentrations and fishing pressure(Figure 1). Connecting biotic year scores chronologically on the firstfactorial plane (PC1 vs. PC2) results in a time trajectory that showsthe regime shift during the late 1980s/early 1990s (Figure 1a). Thechange in the ecosystem is displayed by the opposition of cod andherring as well as sprat and the copepod Acartia spp., showing thestrongest loadings on PC1 (Figure 1b). According to Mollmannet al. (2009), the period between 1987 and 1992 can be interpretedas a transition period, in which a major reorganization of the ecosys-tem occurred, due to the interaction of abrupt climatic changes, un-sustainable fishing pressure and eutrophication. Our updated PCAconfirms that after 1992, abiotic conditions largely returned tovalues similar to the initial state (Figure 1c), indicating hysteresisand stabilizing feedbacks in the foodweb (Casini et al., 2009, 2010;Mollmann et al., 2009). The analysis of the major abiotic loadingsconfirmed that a temperature increase and salinity decrease weremajor drivers of the central Baltic regime shift (Figure 1d).Similar major reorganizations during the late 1980s/early 1990swere found synchronously for almost all studied Baltic ecosystems(Diekmann and Mollmann, 2010; ICES, 2012c).

Early warning indicatorsEcosystem regime shifts, like those observed in the Baltic Sea, arereported for many other marine ecosystems in the world(Mollmann and Diekmann, 2012). These large-scale

reorganizations in ecosystem structure and function bear importantsocial and economic costs and may be difficult to reverse (Schefferet al., 2001; Suding et al., 2004). Hence, management strategiesthat help prevent unwanted change are necessary, and these relyon indicators showing warning signs well before a transitionmight occur (Scheffer et al., 2009). Although the theoretical founda-tion of early warning indicators has greatly improved (Scheffer et al.,2012), the application of potential early warning indicators in realecosystems is still very limited. Lindegren et al. (2012b) applied mul-tiple early warning indicators to monitoring data of key ecosystemcomponents of the Baltic Sea, namely the zooplankton speciesPseudocalanus acuspes and Acartia spp. They demonstrated thatthe ability of the indicators to forewarn the major ecosystemregime shift in the central Baltic Sea is variable depending on theindicator time-series used. Hence, a multiple method approachfor early detection of ecosystem regime shifts is proposed that canbe useful in informing timely management actions in the face ofecosystem change (Lindegren et al., 2012b).

Indicator approach in support of single-species fishstock adviceResults and data from the above reported integrated trend and statusassessments have also been used for developing a set of ecosystemindicators that can support the assessment of the stock status of in-dividual species (Gardmark et al., 2011). Using eastern Baltic cod asa case study, they developed a set of indicators including size/agestructure of the target stock, predator, and prey levels for early life-history stages and physical oceanographic conditions. Individualindicators were evaluated for showing support for or against the as-sessment model-derived stock status and trends. Additionally, indi-vidual indicators were combined into an ecosystem-based indicatorof cod recruitment potential using fuzzy-logic networks (Jarre et al.,2008). Gardmark et al. (2011) thus show how to use ecosystem indi-cators for reducing the uncertainty in model-based estimates ofstock status and for determining more precautionary harvestcontrol rules (HCRs).

Integrated modelling approachesEcological modelsLike in many other areas, fish stock assessments for the Baltic Sea usesingle-species fisheries models as a basis for short-term tactical settingof TAC. However, to evaluate the impact of alternative managementstrategies on the state and dynamics of exploited fish populations,strategic modelling approaches are essential tools. Obviously, anexploited population does not exist in isolation, and its response toa fishing pressure emerges from the feedbacks caused by its interac-tions with other species in the foodweb, as well as from direct and in-direct effects of abiotic pressures. The essence of EBFM is to accountfor such foodweb mediated feedbacks and indirect effects (McLeodand Leslie, 2009). Hence, strategic modelling for EBFM involvesevaluating exploitation effects in the presence of species interactionsand under alternative future environments.

For the main exploited species in the central Baltic Sea, strategicmodelling for EBFM has been performed using a few approaches.Lindegren et al. (2009) developed a stochastic multivariate autore-gressive model (BALMAR) of cod, sprat, herring, and their zoo-plankton prey including the influence of fishing and climatevariables. Such a model represents statistically derived relationshipsbetween the species, and any management impact analyses usingthis model (e.g. Lindegren et al., 2010b) thus relies on the

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assumption that the species interactions (i.e. parameters) do notchange outside the estimated range obtained during the periodused for model fitting. An alternative is to represent trophic interac-tions between species in more detail as, for example, is possible withthe Ecopath with Ecosim (EwE) modelling approach (Christensenand Walters, 2004). The EwE approach has been applied to thecentral Baltic Sea foodweb (Harvey et al., 2003; Osterblom et al.,2007) and in its present form includes 22 functional groups(Niiranen et al., 2012; Tomczak et al., 2012). However, since inter-actions occur between individuals rather than populations, amore mechanistic approach towards modelling trophic interactions

is to explicitly model individual level processes, such as feeding (pre-dation), metabolism, energy allocation, and resulting growth, mor-tality, and reproduction, as done in physiologically structuredpopulation models (Metz and Diekmann, 1986; de Roos andPersson, 2001). This type of models has been developed for the inter-actions between Baltic cod, sprat, and their resources (van Leeuwenet al., 2008, 2013), and between herring, sprat, and their resources(Huss et al., 2012), to assess qualitative responses of cod, sprat,and herring to environmental changes under alternative types ofinteractions. As exemplified by these three modelling approaches,available foodweb (or multispecies) models of the central Baltic

Figure 1. Results of an ITA for the central Baltic Sea ecosystem of biotic (a and b) and abiotic (c and d) variables. (a and c) Time trajectories of PC scoreson the first factorial plane based on a normalized PCA. (b and d) Biplots showing the ten variables that were best represented on the first factorial plane(time trajectory in the background; variables and years are scaled symmetrically by square root of eigenvalues). Cod/Her/Spr, cod/herring/sprat; R,recruitment; F, fishing mortality; Ac1, Acartia spp. biomass; Chla 2,4, chlorophyll a summer concentration in Bornholm and Gotland Basin, respectively;Dino 3, dinoflagellate spring biomass in Bornholm Basin; X11psu, depth of the 11psu isohaline; T 5,6,7,8, midwater temperature in Bornholm andGotland Basin in spring and summer, respectively; Anoxic, area with anoxic bottom water; S4, deepwater salinity in the Gotland Basin.


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Sea differ greatly in fundamental assumptions on how to representecological processes. Simulated responses of exploited species andfoodwebs to fishing may therefore depend on model choice.

Biological ensemble modelling approachTo overcome the issue of model choice for impact analyses,Gardmark et al. (2013) developed a biological ensemble modellingapproach (BEMA), which can be used to assess the relative influenceof model structure on simulated species responses, as well as to for-mulate fisheries management advice robust to such uncertainty. Inthe BEMA, a set of seven ecological models (ranging from single-species to foodweb models of varying complexity) was subjected tothe same initial conditions and external forcing based on a combin-ation of exploitation and climate change scenarios to simulate theresponses of eastern Baltic cod to historically observed high fishinglevels vs. fishing at management target levels, including a numberof future climate change scenarios (Figure 2). The BEMA ensemblewas then used to: (i) identify model assumptions causing key diver-gence in simulated species responses (by contrasting ensemblesubsets), (ii) evaluate the relative importance of model structure un-certainty for overall uncertainty in simulated responses (by contrast-ing variation among models within a climate trajectory withvariation within each model among all climate trajectories), and(iii) formulate robust advice for fisheries management (by identify-ing conclusions on management effects common for the whole en-semble). Gardmark et al. (2013) demonstrated that assumptions ofspecies interactions greatly impacted simulated cod dynamics, withmodels lacking stabilizing predator–prey feedbacks showing largeinterannual fluctuations and a greater sensitivity to the underlyinguncertainty of climate forcing. Nevertheless, robust conclusionsregarding the effects of alternative fishing levels could be found,e.g. in all models, intense fishing prevented recovery and climatechange further decreased the cod population. Although the BEMA(Gardmark et al., 2013) has so far only been applied to single-speciesresponses, the approach is equally suitable to study indirect effects ofexploitation on non-target species (ICES, 2009), groups of speciesproviding particular ecosystem services, as well as indicators of envir-onmental status (ICES, 2012c) as developed for the MSFD.

Coupled ecological–economic modellingWhen formulating new fishing rules, basic economic conditions forthe relevant fishery are often not understood and therefore ignored.Coupled ecological–economic optimization models have beendeveloped and analysed for Baltic cod, herring, and sprat stocks.These models are available as single-species (Quaas et al., 2013) oras multispecies type, i.e. accounting for cod preying upon herringand sprat (Nieminen et al., 2012). These models are also able toaddress climate change impacts by using environmentally sensitivestock–recruitment functions. Changes in optimal fishing strategyunder climate change scenarios can therefore be computed (ICES,2010; Voss et al., 2011). Easily understandable, well-defined indica-tors have proven to be especially helpful to foster transfer and appli-cation of economic analyses into “real-world” fisheries management.In this context, a new ecological–economic indicator was devel-oped: the shadow interest rate, SIR (Quaas et al., 2012). The SIRextends economic concepts and considers fish stocks as naturalcapital stocks. Furthermore, the SIR, as a generic measure, allowsquantifying and comparing the economic success or failure of fish-eries management across stocks. It captures biological informationon stock productivity as well as economic information and allowsthe trade-off of management objectives to be assessed, e.g.

maximizing economic rent, employment, and biomass extraction(Quaas et al., 2012).

A future IEA strategy for Baltic fish stock adviceand managementIn the following section, we outline how the approaches and toolsdescribed above can be combined into an IEA strategy that facilitatesthe implementation of EBFM for the Baltic Sea (Figure 3). The strat-egy includes three components: (i) the transition from existingsingle-species to a multispecies stock assessment, (ii) an ecosystemassessment that integrates environmental information into thesingle-/multispecies assessment, and (iii) a strategic componentthat conducts long-term management strategy evaluation usingcoupled ecological and economic models. Hence, our strategyaccounts for both the short-term needs of annual fish stock assess-ments, conducted for most of the European fish stocks, but also thelong-term needs of future strategic EBM advice (Figure 3).

Towards multispecies stock assessmentsSingle-species assessments are to a large degree still the basis forpresent day fish stock advice. However, we envisage an increasinguse of multispecies assessment models in the future for a more real-istic assessment of multispecies MSY reference points, populationsizes relative to target levels, and TACs. Multispecies models canbe applied indirectly by providing predation mortality rates to beused in single-species models (Figure 3). This procedure is alreadycommon practice for some Baltic fish stocks but should be con-ducted on a more regular, preferably annual, basis. Multispeciesassessments may in the future replace the single-species procedures,when the implications for multispecies interactions especially forMSY calculation are sufficiently evaluated, as is recently initiated(ICES, 2013). Furthermore, additional effort is required for improv-ing multispecies assessment models, e.g. with respect to implement-ing predator–prey feedbacks and density-dependent growth(Gardmark et al., 2013) as well as the dependence of populationprocesses on environmental conditions. Equally important areimproved monitoring systems needed to account for the increaseddata requirements of multispecies models, especially with respectto data on predator diets and key functional groups affecting fishperformance, such as zooplankton. Overall, a replacement ofsingle- by multispecies assessments which account for key speciesinteractions and environmental influences would be a first steptowards integrated fish stock advice for the Baltic Sea.

The importance of ecosystem assessmentsAccounting for ecosystem effects of fishing, as well as effects of en-vironmental variability on fish stock productivity is a crucial com-ponent of EBFM (Pikitch et al., 2004). Fish stock assessmentstraditionally rely on assumptions regarding stationary (equilib-rium) dynamics of populations, communities, and the carrying cap-acity of ecosystems. However, a large body of research has shownthat abrupt changes in productivity, e.g. due to climate, mayoccur (e.g. Brander, 2007), with far reaching consequences for eco-system structure and functioning, as well as the provision of import-ant goods and services (Scheffer et al., 2001; Millennium EcosystemAssessment, 2005). The Baltic Sea, having experienced an ecosystemregime shift (Mollmann et al., 2008), including trophic cascading(Casini et al., 2008; Mollmann et al., 2009), as well as a collapse ofthe cod stock, clearly illustrates that changes in the environmentas well as foodweb interactions need to be considered for sustainablemanagement (Lindegren et al., 2009). Hence, ecosystem


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Figure 2. The BEMA (Gardmark et al., 2013) can be used to derive robust, strategic advice for EBFM. Combinations of management andenvironmental scenarios are used to force a set of ecological models of varying complexity (e.g. single species, multispecies, and foodweb models) tosimulate fish stock responses to exploitation in future environments. The performance of management strategies can then be compared across (i)ecological models, (ii) environmental scenarios, and (iii) environmental variation to identify management strategies and HCRs robust to theuncertainties of ecological processes and future conditions.


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assessments are an important component of an effective EBFM ap-proach. For the Baltic Sea, we have identified three groups of indica-tors that are needed to inform fish stock assessments (Figure 3).First, indicators of stock status and structure (“Stock” inFigure 3), other than biomass and abundance, need to be considered(Gardmark et al., 2011; Eero et al., 2012). These are also required bythe MSFD in its “Descriptor 3” (EC, 2008) and should describegrowth and recruitment of the stocks. Second, the state of theabiotic and biotic environment needs to be evaluated (“Env” inFigure 3). Gardmark et al. (2011) propose indicators for the Balticcod stock related to physical oceanographic parameters importantfor recruitment, as well as prey and predator effects on early lifestages. Similar indicators have been identified also for the otherfish stocks in the Baltic Sea (Lindegren et al., 2011; Eero et al.,2012). In addition, the PC-based holistic indicator from ITAs (seeabove) can provide important information about the ecosystem dy-namics and state in a holistic way (Link et al., 2002; Mollmann et al.,2009). Finally, early warning indicators (“EW” in Figure 3) are im-portant in providing timely detection of ecosystem change(Lindegren et al., 2012b).

A standing difficulty of using ecosystem information in an assess-ment framework is to translate ecosystem indicator informationinto decision criteria for management (Link, 2005). A first stepwould be to combine individual ecosystem indicators into an eco-system health index (EHI) (Figure 3). EHI indicates the state ofthe environment relative to its good environmental status (GES),a goal of many environmental policy drivers such as the MSFD(EC, 2008). A number of procedures is available for combining in-dividual indicators, such as fuzzy logic and various weightingschemes (Gardmark et al., 2011; Ojaveer and Eero, 2011; Halpernet al., 2012). Eventually, rules have to be defined that modify theHCR (i.e. rules for how the TAC shall be set depending on state in

relation to targets) according to the state of the EHI relative toGES. An example for a precautionary approach for Baltic cod is sug-gested by Gardmark et al. (2011).

Into the future: long-term management strategyevaluationThe fish stock and ecosystem assessments described above primarilyfocus on short-term, tactical management aspects. However, envir-onmental conditions and impacts on ecosystems and their fishstocks may vary over longer time-scales, especially in the light ofexpected future climate change (MacKenzie et al., 2012; Meieret al., 2012). Hence, strategic long-term simulations are needed todefine management goals (such as FMSY) and to evaluate howrobust these goals are to future climate change (Lindegren et al.,2010a, b), to fishing effects on the ecosystem (Lassen et al., 2013),and to our ignorance of foodweb interactions in general. In add-ition, Gardmark et al. (2013) showed that a multimodel approach(i.e. BEMA) would be beneficial for developing managementgoals robust to uncertainties inherent in such simulations due tomodel structure and parameterization (Niiranen et al., 2012). Theproposed long-term management strategy evaluations will be in-strumental in developing multispecies long-term managementplans (STECF, 2012). Eventually, coupled ecological–economicalmodels can be used to evaluate the economic implications of man-agement strategies relative to environmental conditions (Voss et al.,2011; Lassen et al., 2013).

DiscussionWe have proposed a strategy that integrates the present Baltic Seasingle-species fish stock assessment and advice with elements ofIEAs. The approach focuses on (i) integrating environmental infor-mation into the short-term tactical fish stock assessment and (ii)using existing ecological and coupled ecological–economicmodels in simulations to evaluate management strategies and to an-ticipate environmental productivity changes. The strategy is largelybased on existing studies and models for the Baltic Sea and should bereadily implemented and operational.

However, although many indicators for the ecosystem assess-ment have been proposed (e.g. Gardmark et al., 2011; Eero et al.,2012), a standard set of indicators needs to be developed. Hence, in-dicator development is a crucial part of the IEA framework (Levinet al., 2009) and should comprise (i) a formal and objective indicatorselection routine, involving both scientists and stakeholders (Levinet al., 2010; Kershner et al., 2011), and (ii) an approach for determin-ing target and reference levels based on time-series and ecosystemmodelling (Samhouri et al., 2009, 2010, 2011, 2012).

After indicator selection, a further important step in our strategywould be an analysis that identifies the risk to the indicators posed byhuman activities and natural processes. Risk analyses have the goalto determine the probability that an ecosystem indicator will reachor remain in an undesirable state (Levin et al., 2009). Various tech-niques exist that use qualitative expert opinion or quantitative tech-niques such as statistical analyses and ecosystem modelling (Smithet al., 2007; Samhouri and Levin, 2012). As demonstrated here,the necessary data and modelling tools are available to employthese techniques for the Baltic Sea ecosystem to implement this im-portant step of IEA in the here proposed strategy.

The implementation of the outlined approach depends on thedevelopment of an integrated monitoring programme that routine-ly measures the selected indicators. The monitoring programmeshould combine the present fish stock surveys with environmental

Figure 3. Schematic outline for a future IEA strategy for Baltic fishstock advice and management including (1) multispecies fish stockassessments, (2) ecosystem assessments, and (3) long-termmanagement strategy evaluation: F, fishing mortality; MSY, maximumsustainable yield; TAC, total allowable catch; i, fish species, i.e. cod,herring, and sprat; stock, indicators of stock status and structure; Env,indicators on the state of the abiotic and biotic environment; EW, earlywarning indicators; EHI, ecosystem health index; GES, goodenvironmental status; BEMA, biological ensemble modelling approach;ECON, coupled ecological/economical modelling.


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monitoring, such as conducted by HELCOM (2011). At present, anumber of key indicators are insufficiently sampled, e.g. an indica-tor of GES of zooplankton in relation to fish stocks (Mollmann et al.,2008). Access to complex biological data, such as zooplankton andphytoplankton, is still difficult and reduced funding poses a seriousthreat to the important continuation of monitoring and the main-tenance of long-term time-series. Furthermore, monitoring shouldhave a wide spatial distribution at an appropriate resolution, sincerecent studies have shown important changes in the distributionsof key species such as sprat (Casini et al., 2011b) and cod (Casiniet al., 2012) which have important implications for management(Eero et al., 2012). Eventually, regular predator stomach samplingis required for conducting reliable multispecies assessments.

The utility and implementation of the proposed approach hingeson the development of management plans that can account for thetype of information that integrated fish stock advice would provide.Management plans need to include explicit rules on how TACs (andother management measures) are to be determined using informa-tion provided by, e.g. ecosystem assessments. Gardmark et al. (2011)give an example how HCRs can account for uncertainty in the advicefor Baltic cod, using among others ecosystem information. Theysuggest HCRs to be modified depending on environmental state,e.g. reflected by the EHI (Figure 3). Furthermore, harvest strategyframeworks able to deal with a broad range of information arebeing used in fisheries management in Australia using indicatorsof fishing and stock trends, combined in a hierarchical strategic ap-proach (Smith et al., 2007). The approach to long-term manage-ment strategy evaluation we propose can be instrumental insetting up these new EBM plans.

Our strategy described here implicitly demands for a resilienceapproach to ecosystem management (Folke et al., 2004; Hugheset al., 2005; Levin and Lubchenco, 2008; Fujita et al., 2012).Reducing resilience of populations, communities, and foodwebsto environmental change, through anthropogenic impacts, cancause critical transitions, i.e. regime shifts, as observed in theBaltic Sea. Implementing early warning indicators and evaluatingpotential future scenarios accounts for a precautionary approachthat ensures the health and resilience of Baltic Sea fish stocks.Furthermore, regime-based approach to EBFM can easily be imple-mented in our framework (King and McFarlane, 2006; Fu et al.,2013; Szuwalski and Punt, 2013).

The approach developed here benefits from the relative simplethree species fisheries system of the central Baltic Sea and the avail-ability of long-term datasets and modelling approaches (Casiniet al., 2011a). However, our strategy can readily be applied tomore complex fisheries ecosystems that usually have (i) fairly devel-oped multispecies fisheries models (e.g. Garrison et al., 2010;Howell and Bogstad, 2010; Kempf et al., 2010; Link et al., 2011a),(ii) long-term time-series for ecosystem assessment (Link et al.,2002; Kenny et al., 2009), and (iii) foodweb and ecosystem modelsfor strategic long-term management strategy evaluation (e.g. Linket al., 2011a, b; Kaplan et al., 2012). Naturally the higher complexityin terms of foodweb structure and related mixed fisheries in ecosys-tems such as the North Sea (Ulrich et al., 2012) makes ecosystemassessments and long-term modelling approaches more challen-ging. However, we are convinced that conducting rigorous and goal-specific indicator selection and risk assessment help overcome thesechallenges. The multimodel approach for strategic long-term simu-lations advocated here (i.e. BEMA) is less straightforward whenapplied to more than one target species (as in Gardmark et al.,2013) or multiple management goals, especially since foodweb

models able to address multisector use of ocean ecosystems arerare. Hence, multiple model sets are potentially needed to covermultiple goals, and rigouros management goal-specific selectioncriteria for model inclusion need to be developed. In general,models should be prioritized that include stabilizing predator–prey feedbacks (Gardmark et al., 2013), climate as well as anthropo-genic drivers, and that allow studying indirect exploitation effectsamong important target and non-target species.

Eventually implementing our approach requires a fundamentalchange in how fish stock assessment and advice is conducted(Casini et al., 2011a). More effort needs to be shifted from theregular single-species procedure towards implementing multispeciesand ecosystem assessments. This potentially requires a reductionin the temporal frequency of single-species assessments, allowingmore effort towards the development of ecosystem assessments.Moreover, fish stock and ecosystem assessments should be combinedinto an integrative, interdisciplinary framework. Within the ICESframework, the required integration of fish stock and ecosystemassessments is facilitated by the ICES SCICOM Steering Group onRegional Sea Programmes (SSGRSP) and currently supported bythe planned revision of the ICES science plan, which gives the devel-opment of IEA a prominent position in the organization. But IEAimplementation needs an enhanced cooperation with regional con-ventions such as HELCOM (Helsinki Commission) and OSPAR(Convention for the Protection of the marine Environment ofthe Northeast Atlantic) and related EU bodies such as STECF(Scientific, Technical, and Economic Committee for Fisheries).However, in the Baltic Sea, as well as in other areas, the data, knowl-edge, and tools for IEA and EBFM are readily available and should beapplied and implemented without further delay.

AcknowledgementsWe thank two anonymous referees and Jason Link for commentsgreatly improving the manuscript. A part of the work leading tothis paper was funded through the European Union FrameworkSeven project MYFISH (“Maximising yield of fisheries while balan-cing ecosystem, economic and social concerns”). The paper is to alarge degree the outcome of work conducted by the “ICES/HELCOM Working Group on Integrated Assessments of theBaltic Sea (WGIAB)”. We are grateful to all past and presentmembers of WGIAB for their support and input. We dedicate thearticle to the late Johan Modin, who was a supporter of WGIABfrom its start.

ReferencesBerkes, F. 2012. Implementing ecosystem-based management: evolu-

tion or revolution? Fish and Fisheries, 13: 465–476.

Brander, K. M. 2007. Global fish production and climate change.Proceedings of the National Academy of Sciences of the USA, 104:19709–19714.

Cardinale, M., Mollmann, C., Bartolino, V., Casini, M., Kornilovs, G.,Raid, T., Margonski, P., et al. 2009. Effect of environmental variabil-ity and spawner characteristics on the recruitment of Baltic herringClupea harengus populations. Marine Ecology Progress Series, 388:221–234.

Casini, M., Bartolino, V., Molinero, J. C., and Kornilovs, G. 2010.Linking fisheries, trophic interactions and climate: threshold dy-namics drive herring Clupea harengus growth in the central BalticSea. Marine Ecology Progress Series, 413: 241–252.

Casini, M., Blenckner, T., Mollmann, C., Gardmark, A., Lindegren, M.,Llope, M., Kornilovs, G., et al. 2012. Predator transitory spillover


by How

ard Brow

man on July 2, 2014


Dow

nloaded from


induces trophic cascades in ecological sinks. Proceedings of theNational Academy of Sciences of the USA, 109: 8185–8189.

Casini, M., Hjelm, J., Molinero, J. C., Lovgren, J., Cardinale, M.,Bartolino, V., Belgrano, A., et al. 2009. Trophic cascades promotethreshold-like shifts in pelagic marine ecosystems. Proceedings ofthe National Academy of Sciences of the USA, 106: 197–202.

Casini, M., Kornilovs, G., Cardinale, M., Mollmann, C., Grygiel, W.,Jonsson, P., Raid, T., et al. 2011b. Spatial and temporal density de-pendence regulates the condition of central Baltic Sea clupeids: com-pelling evidence using an extensive international acoustic survey.Population Ecology, 53: 511–523.

Casini, M., Lovgren, J., Hjelm, J., Cardinale, M., Molinero, J. C., andKornilovs, G. 2008. Multi-level trophic cascades in a heavilyexploited open marine ecosystem. Proceedings of the RoyalSociety of London, Series B, 275: 1793–1801.

Casini, M., Mollmann, C., and Osterblom, H. 2011a. Ecosystem ap-proach to fisheries in the Baltic Sea: present and potential futureapplications in assessment and management. In Ecosystem BasedManagement for Fisheries—an Evolving Perspective, pp. 9–31.Ed. by A. Belgrano, and C. Fowler. Cambridge University Press,Cambridge, UK.

Choi, J., Frank, K., Petrie, B., and Leggett, W. 2005. Integrated assess-ment of a large marine ecosystem: a case study of the devolution ofthe eastern Scotian Shelf, Canada. Oceanography and MarineBiology: an Annual Review, 43: 47–67.

Christensen, V., and Walters, C. J. 2004. Ecopath with Ecosim: methods,capabilities and limitations. Ecological Modelling, 172: 109–139.

de Roos, A. M., and Persson, L. 2001. Physiologically structuredmodels—from versatile technique to ecological theory. Oikos, 94:51–71.

Diekmann, R., and Mollmann, C. (Eds) 2010. Integrated ecosystemassessments of seven Baltic Sea areas. ICES Cooperative ResearchReport, 302. 90 pp.

Diekmann, R., Otto, S., and Mollmann, C. 2012. Towards IntegratedEcosystem Assessments (IEAs) of the Baltic Sea—investigating eco-system state and historical development. In Climate Impacts on theBaltic Sea: From Science to Policy, 1st edn. Ed. by M. Reckermann, K.Brander, B. R. MacKenzie, and A. Omstedt. Springer. 260 pp.Heidelberg, Germany.

EC (European Commission). 2007. Council Regulation (EC) No. 1098/2007 establishing a multi-annual plan for the cod stocks in the BalticSea and the fisheries exploiting those stocks, amending Regulation(ECC) No 2847/93 and repealing Regulation (EC) No 779/97.

EC (European Commission). 2008. Directive 2008/56/EC of theEuropean Parliament and of the Council of 17 June 2008 establishinga framework for community action in the field of marine environ-mental policy (Marine Strategy Framework Directive).

Eero, M., Lindegren, M., and Koster, F. W. 2012. The state and relativeimportance of drivers of fish population dynamics: an indicator-based approach. Ecological Indicatos, 15: 248–252.

Folke, C., Carpenter, S. R., Walker, B. H., Scheffer, M., Elmqvist, T.,Gunderson, L. H., and Holling, C. S. 2004. Regime shifts, resilienceand biodiversity in ecosystem management. Annual Review inEcology, Evolution and Systematics, 35: 557–581.

Fu, C., Perry, R.I., Shin, Y.-J., Schweigert, J., and Liu, H. 2013. An eco-system modelling framework for incorporating climate regimeshifts into fisheries management. Progress in Oceanography,doi:10.1016/j.pocean.2013.03.003.

Fujita, R., Moxley, J. H., DeBey, H., Van Leuvan, T., Leumer, A., Honey,K., Aguilera, S., et al. 2012. Managing for a resilient ocean. MarinePolicy, doi:10.1016/ j.marpol.2012.05.025

Gardmark, A., Nielsen, A., Floeter, J., and Mollmann, C. 2011. Depletedmarine fish stocks and ecosystem-based management: on the road torecovery, we need to be precautionary. ICES Journal of MarineScience, 68: 212–220.

Gardmark, M., Lindegren, M., Neuenfeldt, S., Blenckner, T.,Heikinheimo, O., Muller-Karulis, B., Niiranen, S., et al. 2013.

Biological ensemble modelling to evaluate potential futures ofliving marine resources. Ecological Applications, 23: 742–754.

Garrison, L. P., Link, J. S., Cieri, M., Kilduff, P., Sharov, A., Vaughan, D.,Muffley, B., et al. 2010. An expansion of the MSVPA approach forquantifying predator–prey interactions in exploited fish communi-ties. ICES Journal of Marine Science, 67: 856–870.

Gislason, H. 1999. Single and multispecies reference points for Balticfish stocks. ICES Journal of Marine Science, 56: 571–583.


Hare, S. R., and Mantua, N. J. 2000. Empirical evidence for North Pacificregime shifts in 1977 and 1989. Progress in Oceanography, 47:103–145.

Harvey, C. J., Cox, S. P., Essington, T. E., Hansson, S., and Kitchell, J. F.2003. An ecosystem model of food-web and fisheries interactions inthe Baltic Sea. ICES Journal of Marine Science, 60: 939–950.

HELCOM. 2011. HELCOM Activities 2011 Overview (Baltic SeaEnvironment Proceedings No. 132). Published by the HelsinkiCommission.

Howell, D., and Bogstad, B. 2010. A combined Gadget/FLR model formanagement strategy evaluations of the Barents Sea Fisheries.ICES Journal of Marine Science, 67: 1998–2004.

Hughes, T. P., Bellwood, D. R., Folke, C., Steneck, R. S., and Wilson, J.2005. New paradigms for supporting the resilience of marine ecosys-tems. Trends in Ecology and Evolution, 20: 380–386.

Huss, M., Gardmark, A., van Leeuwen, A., and de Roos, A. M. 2012. Size-and food-dependent growth drives patterns of competitive domin-ance along productivity gradients. Ecology, 93: 847–857.

ICES. 2006. Report of the Baltic Fisheries Assessment Working Group(WGBFAS). ICES Document CM 2006/ACFM: 24.

ICES. 2008. Report of the ICES/HELCOM Working Group onIntegrated Assessment of the Baltic Sea (WGIAB). ICES DocumentCM 2008/BCC: 4.

ICES. 2009. Report of the ICES/HELCOM Working Group onIntegrated Assessments of the Baltic Sea (WGIAB). ICES DocumentCM 2009/BCC: 2.

ICES. 2010. Workshop on including socio-economic considerationsinto the climate-recruitment framework developed for clupeids inthe Baltic Sea (WKSECRET). ICES Document CM 2010/SSGRSP: 9.

ICES. 2012a. International Council for the Exploration of the Sea.Advice 2012, Book 8.

ICES. 2012b. Report of the Baltic Fisheries Assessment Working Group(WGBFAS). ICES Document CM 2012/ACOM: 10.

ICES. 2012c. Report of the ICES/HELCOM Working Group onIntegrated Assessment of the Baltic Sea (WGIAB). ICES DocumentCM 2012/SSGRSP: 2.

ICES. 2012d. Report of the Workshop on Integrated/MultispeciesAdvice for Baltic Fisheries (WKMULTBAL). ICES Document CM2012/ACOM: 43.

ICES. 2013. Report of the Benchmark Workshop on Baltic MultispeciesAssessments (WKBALT). ICES Document CM 2013/in press.

Jarre, A., Paterson, B., Moloney, C. L., Miller, D. C. M., Field, J. G., andStarfield, A. M. 2008. Knowledge-based systems as decision supporttools in an ecosystem approach to fisheries: comparing a fuzzy-logicand a rule-based approach. Progress in Oceanography, 79: 390–400.

Jennings, S. 2005. Indicators to support an ecosystem approach to fish-eries. Fish and Fisheries, 6: 212–232.

Kaplan, I. C., Horne, P. J., and Levin, P. S. 2012. Screening CaliforniaCurrent fishery management scenarios using the Atlantisend-to-end ecosystem model. Progress in Oceanography, 102: 5–18.

Kempf, A., Dingsør, G. E., Huse, G., Vinther, M., Floeter, J., andTemming, A. 2010. The importance of predator–prey overlap: pre-dicting North Sea cod recovery with a multispecies assessmentmodel. ICES Journal of Marine Science, 67: 1989–1997.


by How

ard Brow

man on July 2, 2014


Dow

nloaded from


Kenny, A., Skjoldal, H., Engelhard, G., Kershaw, P., and Reid, J. 2009. Anintegrated approach for assessing the relative significance of humanpressures and environmental forcing on the status of large marineecosystems. Progress in Oceanography, 81: 132–148.

Kershner, J., Samhouri, J. F., James, C. A., and Levin, P. S. 2011. SelectingIndicator Portfolios for Marine Species and Food Webs: a PugetSound Case Study. PLoS One, 6: e25248. doi:10.1371/journal.-pone.0025248.

King, J. R., and McFarlane, G. A. 2006. A framework for incorporatingclimate regime shifts into the management of marine resources.Fisheries Management and Ecology, 13: 93–102.

Koster, F., Mollmann, C., Neuenfeldt, S., St. John, M., Plikshs, M., andVoss, R. 2001. Developing Baltic cod recruitment models. I. Resolvingspatial and temporal dynamics of spawning stock and recruitment forcod, herring, and sprat. Canadian Journal of Fisheries and AquaticSciences, 58: 1516–1533.

Lassen, H., Pedersen, S. A., Frost, H., and Hoff, A. 2013. Fishery manage-ment advice with ecosystem considerations. ICES Journal of MarineScience, 70: 471–479.

Legendre, P., Dallot, S., and Legendre, L. 1985. Succession of specieswithin a community: chronological clustering, with applicationsto marine and freshwater zooplankton. American Naturalist, 125:257–1298.

Legendre, P., and Legendre, L. 1998. Numerical ecology, 2nd edn.Elsevier, Amsterdam, The Netherlands.

Leslie, H. M., and McLeod, K. L. 2007. Confronting the challenges ofimplementing marine ecosystem-based management. Frontiers inEcology and the Environment, 5: 540–548.

Levin, P. S., Damon, I. A., and Samhouri, J. F. 2010. Developing mean-ingful marine ecosystem indicators in the face of a changing climate.Standford Journal of Law, Science and Policy, 2: 36–48.

Levin, P. S., Fogarty, M. J., Murawski, S. A., and Fluharty, D. 2009.Integrated ecosystem assessments: developing the scientific basisfor ecosystem-based management of the ocean. PLoS Biology, 7:e14. doi:0.1371/journal.pbio.1000014.

Levin, S. A., and Lubchenco, J. 2008. Resilience, robustness, and marineecosystem-based management. Bioscience, 58: 27–32.

Lindegren, M., Blenckner, T., and Stenseth, N. C. 2012a. Nutrient reduc-tion and climate change cause a potential shift from pelagic tobenthic pathways in a eutrophic marine ecosystem. Global ChangeBiology, 18: 3491–3503.

Lindegren, M., Dakos, V., Groger, J. P., Gardmark, A., Kornilovs, G.,Otto, S. A., and Mollmann, C. 2012b. Early detection of ecosystemregime shifts: a multiple method evaluation for management appli-cation. PLoS One, 7: e38410.

Lindegren, M., Diekmann, R., and Mollmann, C. 2010a. Regime shifts,resilience and recovery of a cod stock. Marine Ecology ProgressSeries, 402: 239–253.

Lindegren, M., Mollmann, C., Nielsen, A., Brander, K., MacKenzie, B.,and Stenseth, N. C. 2010b. Ecological forecasting under climatechange: the case of Baltic cod. Proceedings of the Royal Society ofLondon, Series B: Biological Sciences, 277: 2121–2130.

Lindegren, M., Mollmann, C., Nielsen, A., and Stenseth, N. C. 2009.Preventing the collapse of the Baltic cod stock through an ecosystem-based management approach. Proceedings of the National Academyof Sciences of the USA, 106: 14722–14727.

Lindegren, M., Ostman, O., and Gardmark, A. 2011. Interacting trophicforcing and the population dynamics of herring. Ecology, 92:1407–1413.

Link, J. S. 2005. Translating ecosystem indicators into decision criteria.ICES Journal of Marine Science, 62: 569–576.

Link, J. S., Brodziak, J., Edwards, S., Overholtz, W., Mountain, D., Jossi,J., Smith, T., et al. 2002. Marine ecosystem assessment in a fisheriesmanagement context. Canadian Journal of Fisheries and AquaticSciences, 59: 1429–1440.

Link, J. S., Gamble, R. J., and Fogarty, M. J. 2011a. An overview of theNEFSC’s ecosystem modeling enterprise for the Northeast US

Shelf Large Marine Ecosystem: towards ecosystem-based fisheriesmanagement. US Department of Commerce, Northeast FisheriesScience Center Reference Document 11-23. 89 pp.

Link, J. S., Gamble, R. J., and Fulton, E. A. 2011b. NEUS—Atlantis: con-struction, calibration, and application of an ecosystem model withecological interactions, physiographic conditions, and fleet behav-ior. NOAA Technical Memorandum, NMFS NE-218. NationalMarine Fisheries Service, Woods Hole, MA. 247 pp. http://www.nefsc.noaa.gov/nefsc/publications/.

MacKenzie, B., and Koster, F. 2004. Fish production and climate: sprat inthe Baltic Sea. Ecology, 85: 784–794.

MacKenzie, B. R., Meier, H. E. M., Lindegren, M., Neuenfeldt, S., Eero,M., Blenckner, T., Tomczak, T., et al. 2012. Impact of climate changeon fish population dynamics in the Baltic Sea: a dynamical downscal-ing investigation. Ambio, 41: 626–636.

Marasco, R. J., Goodman, D., Grimes, C. B., Lawson, P. W., Punt, A. E.,and Quin, T. J. 2007. Ecosystem-based fisheries management: somepractical suggestions. Canadian Journal of Fisheries and AquaticSciences, 64: 928–939.

McLeod, K. L., and Leslie, H. M. (Eds) 2009. Ecosystem-BasedManagement for the Oceans. Island Press, Washington, DC.

Meier, H. E. M., Andersson, H. C., Arheimer, B., Blenckner, T.,Chubarenko, B., Donnelly, C., Eilola, K., et al. 2012. Comparingreconstructed past variations and future projections of the BalticSea ecosystem—first results from multi-model ensemble simula-tions. Environmental Research Letters, 7: 034005.

Metz, J. A. J., and Diekmann, O. 1986. Formulating models for struc-tured populations. In The Dynamics of Physiologically StructuredPopulations (Amsterdam, 1983), Volume 68 of Lecture Notes inBiomath, pp. 78–135. Springer, Berlin.

Millennium Ecosystem Assessment. 2005. Ecosystems and HumanWellbeing: Synthesis. Island Press, Washington, DC.

Mollmann, C., and Diekmann, R. 2012. Marine ecosystem regime shiftsinduced by climate and overfishing—a review for the Northernhemisphere. Advances in Ecological Research, 47: 303–347.

Mollmann, C., Diekmann, R., Muller-Karulis, B., Kornilovs, G., Plikshs,M., and Axe, P. 2009. Reorganization of a large marine ecosystemdue to atmospheric and anthropogenic pressure: a discontinuousregime shift in the Central Baltic Sea. Global Change Biology, 15:1377–1393.

Mollmann, C., Mu?ller-Karulis, B., Kornilovs, G., and St. John, M. 2008.Effects of climate and overfishing on zooplankton dynamics and eco-system structure: regime shifts, trophic cascade, and feedback coopsin a simple ecosystem. ICES Journal of Marine Science, 65: 302–310.

Nieminen, E., Lindroos, M., and Heikinheimo, O. 2012. Optimal bioe-conomic multispecies fisheries management: a Baltic Sea case study.Marine Resource Economics, 27: 115–136.

Niiranen, S., Blenckner, T., Hjerne, O., and Tomczak, M. T. 2012.Uncertainties in a Baltic Sea food-web model reveal challenges forfuture projections. Ambio, 421: 613–625.

Ojaveer, H., and Eero, M. 2011. Methodological challenges in assessingthe environmental status of a marine ecosystem: case study of theBaltic Sea. PLoS One, 6: e19231. doi:10.1371 /journal.pone.0019231

Osterblom, H., Hansson, S., Larsson, U., Hjerne, O., Wulff, F., Elmgren,R., and Folke, C. 2007. Human-induced trophic cascades and eco-logical regime shifts in the Baltic Sea. Ecosystems, 10: 877–889.

Pikitch, E. K., Santora, C., Babcock, E. A., Bakun, A., Bonfil, R., Conover,D. O., Dayton, P., et al. 2004. Ecosystem-based fishery management.Science, 305: 346–347.

Quaas, M. F., Froese, R., Herwartz, H., Requate, T., Schmidt, J. O., andVoss, R. 2012. Fishing industry borrows from natural capital at highshadow interest rates. Ecological Economics, 82: 45–52.

Quaas, M. F., Requate, T., Ruckes, K., Skonhoft, A., Vestergaard, N., andVoss, R. 2013. Incentives for optimal management of age-structuredfish populations. Resource and Energy Economics, 35: 113–134.

Rodionov, S. N. 2004. A sequential algorithm for testing climate regimeshifts. Geophysical Research Letters, 31: L09204.


by How

ard Brow

man on July 2, 2014


Dow

nloaded from

http://www.nefsc.noaa.gov/nefsc/publications/







Rotmans, J., and Dowlatabadi, H. 1997. Integrated assessment ofclimate change: evaluation of methods and strategies. In HumanChoice and Climate Change: an International Social ScienceAssessment. Ed. by S. Rayner, and E. Malone. Battelle Press,Washington, USA.

Samhouri, J. F., Lester, S. E., Selig, E. R., Halpern, B. S., Fogarty, M. J.,Longo, C., and McLeod, K. E. 2012. Sea sick? Setting targets toassess ocean health and ecosystem services. Ecosphere, 3: 1–18.

Samhouri, J. F., and Levin, P. S. 2012. Linking land- and sea-based activ-ities to risk in coastal ecosystems. Biological Conservation, 145:118–129.

Samhouri, J. F., Levin, P. S., and Ainsworth, C. H. 2010. Identifyingthresholds for ecosystem-based management. PLoS One, 5: e8907.


Samhouri, J. F., Levin, P. S., James, A., Kershner, J., and Williams, G.2011. Using existing scientific capacity to sett argets for ecosystem-based management: a Puget Sound case study. Marine Policy, 35:508–518.

Scheffer, M., Bascompte, J., Brock, W., Brovkin, V., Carpenter, S., Dakos,V., Held, H., et al. 2009. Early-warning signals for critical transitions.Nature, 461: 53–59.

Scheffer, M., Carpenter, S., Foley, J. A., Folke, C., and Walker, B. 2001.Catastrophic shifts in ecosystems. Nature, 413: 591–596.

Scheffer, M., Carpenter, S. R., Lenton, T. M., Bascompte, J., Brock, W.,Dakos, V., van de Koppel, J., et al. 2012. Anticipating critical transi-tions. Nature, 338: 344–348.

Shepherd, J. G. 1999. Extended survivors analysis: an improved methodfor the analysis of catch-at-age data and abundance indices. ICESJournal of Marine Science, 56: 584–591.


Sparholt, H. 1994. Fish species interactions in the Baltic Sea. Dana, 10:131–162.

STECF. 2012. Scientific, Technical and Economic Committee forFisheries (STECF). Multispecies Management Plans for the Baltic(STECF-12-06).

Suding, K., Gross, K., and Houseman, G. 2004. Alternative states andpositive feedbacks in restoration ecology. Trends in Ecology andEvolution, 19: 46–53.

Szuwalski, C. S., and Punt, A. E. 2013. Fisheries management for regime-based ecosystems: a management strategy evaluation for the snowcrab fishery in the eastern Bering Sea. ICES Journal of MarineScience, 70: 955–967.

Tallis, H., Levin, P. S., Ruckelshaus, M., Lester, S. E., McLeod, K. L.,Fluharty, D. L., and Halpern, B. S. 2010. The many faces ofecosystem-based management: making the process work today inreal places. Marine Policy, 34: 340–348.

Tomczak, M. T., Niiranen, S., Hjerne, O., and Blenckner, T. 2012.Ecosystem flow dynamics in the Baltic Proper—using a multitrophicdataset as a basis for foodweb modelling. Ecological Modelling, 230:123–147.

Ulrich, C., Wilson, D. C. K., Nielsen, J. R., Bastardiea, F., Reeves, S. A.,Andersen, B. S., and Eigaard, O. R. 2012. Challenges and opportun-ities for fleet- and metier-based approaches for fisheries manage-ment under the European Common Fishery Policy. Ocean andCoastal Management, 70: 38–47.

van der Sluijs, J. P. 2002. Integrated assessment. In Encyclopedia ofGlobal Environmental Change, 4, pp. 250–253. Ed. by R. E.Munn. Wiley, Chichester.

van Leeuwen, A., De Roos, A. M., and Persson, L. 2008. How cod shapesits world. Journal of Sea Research, 60: 89–104.

van Leeuwen, A., Huss, M., Gardmark, A., Casini, M., Vitale, F., Hjelm,J., Persson, L., et al. 2013. Predators with multiple ontogenetic nicheshifts have limited potential for population growth and top-downcontrol of their prey. American Naturalist, 182: 53–66.

Voss, R., Hinrichsen, H.-H., Quaas, M. F., Schmidt, J., and Tahvonen, O.2011. Temperature change and Baltic sprat: from observations toecological-economic modeling. ICES Journal of Marine Science,68: 1244–1256.

Weijerman, M., Lindeboom, H., and Zuur, A. 2005. Regime shifts inmarine ecosystems of the North Sea and Wadden Sea. MarineEcology Progress Series, 298: 21–39.

Weyant, J., Davidson, O., Dowlatabadi, H., Edmonds, J., Grubb, M.,Richels, R., Rotmans, J., et al. 1996. Integrated assessment ofclimate change: an overview and comparison of approaches andresults. In Climate Change 1995–Economic and SocialDimensions of Climate Change. Contribution of Working GroupIII to the Second Assessment Report of the IntergovernmentalPanel on Climate Change (IPCC). Ed. by J. P. Bruce, H. Lee, and E.F. Haites. Cambridge University Press, Cambridge.



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ard Brow

man on July 2, 2014


Dow

nloaded from



Original Article

Guidance for implementation of integrated ecosystemassessments: a US perspective

Phillip S. Levin1*, Christopher R. Kelble2, Rebecca L. Shuford3, Cameron Ainsworth4,Yvonne deReynier5, Rikki Dunsmore6, Michael J. Fogarty7, Kirstin Holsman8, Evan A. Howell9,Mark E. Monaco10, Stephanie A. Oakes3, and Francisco Werner11

1National Marine Fisheries Service, Northwest Fisheries Science Center, 2725 Montlake Blvd. E., Seattle, WA 98115, USA2NOAA Office of Oceanic and Atmospheric Research, Atlantic Oceanographic and Meteorological Lab, Miami, FL, USA3National Marine Fisheries Service Office of Science and Technology, Silver Spring, MD, USA4University of South Florida, St. Petersburg, FL, USA5National Marine Fisheries Service, Northwest Regional Office, Seattle, WA, USA6NOAA National Ocean Service, National Marine Sanctuary Program, Monterey Bay National Marine Sanctuary, Monterey, CA, USA7National Marine Fisheries Service, Northeast Fisheries Science Center, Woodshole, MA, USA8Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, WA, USA9National Marine Fisheries Service, Pacific Islands Fisheries Science Center, Honolulu, HI, USA10NOAA National Ocean Service, National Centers for Coastal and Ocean Science, Silver Spring, MD, USA11National Marine Fisheries Service, Southwest Fisheries Science Center, La Jolla, CA, USA

*Corresponding author: tel: +206-860-3473; e-mail: [email protected]

Levin, P. S., Kelble, C. R., Shuford, R., Ainsworth, C., deReynier, Y., Dunsmore, R., Fogarty, M. J., Holsman, K., Howell, E., Monaco, M., Oakes, S., andWerner, F. 2014. Guidance for implementation of integrated ecosystem assessments: a US perspective. – ICES Journal of Marine Science, 71:1198–1204.

Received 11 April 2013; accepted 7 June 2013; advance access publication 4 September 2013.

Ecosystem-based management (EBM) has emerged as a basic approach for managing human activities in marine ecosystems, with the aimof recovering and conserving marine ecosystems and the services they deliver. Integrated ecosystem assessments (IEAs) further the tran-sition of EBM from principle to practice by providing an efficient, transparent means of summarizing the status of ecosystem components,screening and prioritizing potential risks, and evaluating alternative management strategies against a backdrop of environmental variability.In this paper, we draw upon lessons learned from the US National Oceanic and Atmospheric Administration’s IEA programme to outlinesteps required for IEA implementation. We provide an overview of the conceptual framework for IEAs, the practical constraints that shapethe structure of individual IEAs, and the uses and outcomes of IEAs in support of EBM.

Keywords: ecosystem-based management, ecosystem indicator, ecosystem risk, IEA, integrated ecosystem assessment, management strategyevaluation.

IntroductionThe need for a more holistic and integrated approach to the manage-ment of ocean resources is now widely appreciated in the scientificand management communities (U. S. Commission on OceanPolicy, 2004; MEA, 2005; Murawski and Matlock, 2006; Agardyet al., 2011). Ecosystem-based management (EBM) recognizes

that humans are integral components of ecosystems that interactwith all other components in diverse, complex ways. Despite theappreciation for integrated EBM, there remain few examples of suc-cessful implementation (Cowling et al., 2008). This is in part,because we need tools to make the scientific principles of EBMuseful to resource managers (Arkema et al., 2006). A preeminent

Published by Oxford University Press on behalf of the International Council for the Exploration of the Seas 2013. This work is written by USGovernment employees and is in the public domain in the US.

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need for implementing EBM is a framework to assess the status ofecosystems relative to specific management goals and objectivesand to evaluate the probable outcomes and trade-offs of alternativemanagement strategies. Integrated ecosystem assessments (IEAs)are intended to provide just such a framework (Levin et al., 2009).IEAs provide a structured approach to ecosystem assessment andevaluation that serves as an integrative counterpart to single-speciesand single-sector assessments now applied in resource manage-ment.

A number of IEA frameworks are currently being consideredacross the globe. For example, the ICES Working Group on the eco-system effects of fisheries activities, reviewed IEA approaches used inthe Northeastern Atlantic, North Sea, Canada, and the United States(ICES, 2010). These approaches differ in the degree to which pres-sures are linked to ecosystem states, the degree of integrationacross human and natural dimensions, and the regional consistencythat the frameworks promote. However, they all share a motivationto describe the status of the ecosystem relative to some desired state.Here, we focus on NOAA’s IEA framework, while acknowledgingthat IEAs are an emerging tool, which is being approached different-ly by different countries and agencies.

The basic structural elements of NOAA’s IEA framework havebeen described elsewhere (Levin et al., 2008, 2009). Since NOAAfirst published its IEA framework, the NOAA IEA programme hasgrown, and the IEA approach is now being implemented through-out the United States (www.noaa.gov/iea). In this document, webuild on the initial IEA formulation of Levin et al. (2008) anddraw upon lessons learned from NOAA’s IEA programme tooutline practical steps required for IEA implementation. Weprovide an overview of the conceptual framework for IEAs, the prac-tical constraints that shape the structure of individual IEAs, and theuses and outcomes of IEAs in support of EBM.

A stepwise process for developing an IEAIn this paper, we follow Levin et al. (2009) and define an IEA as aformal synthesis and quantitative analysis of existing informationon relevant natural and socio-economic factors in relation to speci-fied ecosystem management objectives. IEAs are a stepwise processconsisting of goal and target setting, defining indicators, analysis of

status, trends and risk, an overall assessment of ecosystem status, anevaluation of alternative management strategies, and monitoringand evaluation (Figure 1). This process is iterative, allowing forimproved understanding and management of the coupled human-natural system over time. We use this framework to organize ourdiscussion below.

Step 1: defining EBM goalsIEAs are driven by clearly defined management objectives; conse-quently, the IEA approach purposefully begins by identifying prior-ity management objectives to be addressed. This requires thatscientists, managers, and stakeholders work together to define thebroad vision and objectives of EBM, the spatial scale or scales ofinterest, and the ecosystem components and ecosystem threatsthat will be included in the effort. Below we detail each one ofthese elements.

Articulating the objectives to be addressed by the IEA processThe range of potential issues that could be addressed by an IEA isenormous, and any IEA effort must begin with transparent articula-tion of the vision and objectives of the assessment. Sainsbury andSumaila (2003) provide a useful framework for thinking about eco-system objectives. They define an ecosystem vision as a statement ofthe way “things should be”. For example, in 2005, WashingtonGovernor Christine Gregoire’s ecosystem vision for Puget Sound,USA, was that it will “forever be a thriving natural system, withclean marine and freshwaters, healthy and abundant nativespecies, natural shorelines and places for public enjoyment and avibrant economy that prospers in productive harmony with ahealthy sound.”(Puget Sound Partnership, 2006). Although suchvision statements are necessary, they are too vague to be practicallyuseful. Thus, ecosystemvisions need to be decomposed into concep-tual and operational objectives (O’Boyle and Jamieson, 2006). Aconceptual objective is a high-level statement of what is to beattained. As examples: (i) manage resources sustainable forhuman nutritional, economical, and social goals or (ii) protectrare or fragile ecosystems, habitats, and species. An operational ob-jective is an objective that has a direct and practical interpretation.Formulating effective operational objectives requires thinking

Figure 1. A stepwise process for completing an IEA. An IEA begins with a scoping process, identifies appropriate indicators and reference levels,assesses risk, and evaluates the potential of different management strategies to alter ecosystem status. Monitoring and evaluation occur throughoutthe process, and the IEA cycle is repeated in an adaptive manner.

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carefully about the specific outcomes of EBM and how success orfailure will be measured and detected.

The US National Ocean Policy provides many conceptual objec-tives that will require the development of operational objectives at na-tional and regional scales. Fortunately, NOAA and other federal andstate agencies have a long history of working with Congress and man-agementbodiestotranslate theconceptualobjectivesof legislationintooperational objectives. For example, in coastal-zone management,NOAA and the EPA provide broad guidance to the states, whichthen implement the objectives of the Coastal Zone Management Actand Clean Water Act through state-specific programmes.

Defining the spatial scale of an IEAThe spatial scale of an IEA is largely determined by the managementquestions being addressed, and thus IEAs can vary in scale andextent. As a result, a key step in IEA scoping is to determine thescale of a particular IEA as it relates to defined management objec-tives. Ecosystem boundaries are human constructs based on bio-physical and political distributions; consequently, defining thescale of an IEA is an important exercise that ideally considers bio-physical, human dimension, and management considerations. Asa consequence, there is no “correct” scale at which to conduct anIEA, but each implementation of the IEA framework will have a spe-cified scale and extent appropriate to the management objectivesdriving the assessment.

IEAs will almost certainly have to contend with ecosystem pro-cesses and human activities that extend beyond the boundaries ofan IEA. Oceanographic processes, terrestrial-based inputs, andclimate change are just a few examples of this problem. This issuecan be addressed by identifying drivers and pressures that occurwithin the IEA vs. those that emanate from outside the IEA, butmust be considered. This delineation has the benefit of definingpressures over which local management agencies have jurisdictionand the externalities that affect the system, but are outside of localcontrol.

Identifying focal ecosystem components of an IEAComponents of an ecosystem include everything: the physics,geology, chemistry, biology, and human dimensions. Focal ecosys-tem components are the major elements of an ecosystem that canbe used to organize relevant information in a limited number of dis-crete, but not necessarily independent categories. In the CaliforniaCurrent IEA, a workshop with NOAA managers was used todevelop a set of focal components that included: ecological structureand function, fisheries, protected species, habitat, and human com-munities (Levin and Schwing, 2011). Similarly, the focal compo-nents of the Kona ecosystem were identified as: coral reefs,ornamental, recreational, and commercial fisheries, open oceanand coastal aquaculture programmes, tourism, shared-use areas in-volving industry and natural resources (e.g. manta ray habitat andcommercial diving), critical cetacean habitat, and natural energy fa-cilities. The Northeast Continental Shelf IEA defined focal ecosys-tem components as ones that require management interventionsto ensure their continued viability, such as species directly or indir-ectly affected by fishing activities and other anthropogenic impacts,protected species, and human communities dependent on the eco-system for food, recreation, and other uses.

Identifying key threats to ecosystem componentsIdentification and prioritization of threats to achieving EBM objec-tives are important so that the IEA team can concentrate efforts

where they are needed most. The analytical efforts describedbelow can be useful in identifying key threats. Additionally,formal or informal discussions with partners and stakeholders canbe useful for focusing efforts.

The identification of threats during the initial stage of the IEAprocess allows regional experts an opportunity to highlight ecosys-tem components that are highly exposed to human and natural pres-sures. In essence, the identification of threats is the base from which aformal risk analysis is launched (risk analysis is discussed below).

Putting it all together: conceptualize the ecosystem and the IEADeveloping a common understanding of the context of the IEA, in-cluding the biophysical, socio-economic, and management systemsthat affect the ability to achieve the vision of the IEA is the ultimatestep in scoping an IEA. This step builds upon previous work inwhich the objectives, focal ecosystem components, and threats areidentified.

Conceptual ecosystem models have proven useful for under-standing ecosystems and can be helpful for synthesizing diverse sci-entific information. Conceptual models have a successful history inresource management (Bowen and Riley, 2003), especially whenscientists, resource managers, and stakeholders jointly developmodels in workshop settings (Svarstad et al., 2008). Collaborativemodel development assists in building consensus and helps movebeyond disagreements to a focus on how the ecosystem is structuredand functions.

Step 2: defining ecosystem indicators and reference levelsDescription of different approaches to select and evaluateecosystem indicatorsA critical step in the IEA process is to select indicators that capturethe key aspects of the focal ecosystem components identified in step1. Indicators are quantitative measures that serve as proxies for char-acterizing key attributes of biogeochemical and human systems(Heinz Center for Science and the Environment, 2008). Effectiveindicators serve as the measures of the many ecosystem servicesthat concern policy-makers and stakeholders (Link, 2005) and areone of the primary contact points between policy and science.

Hundreds if not thousands of indicators have been proposed foruse in EBM (e.g. Kershner et al., 2011; James et al., 2012). Rice andRochet (2005), Methratta and Link (2006), and Shin and Shannon(2010) outline valuable frameworks for sorting through volumin-ous lists and building a portfolio of informative indicators forEBM. These authors argue that indicators should be directly observ-able and based on well-defined theory while also being understand-able to the general public, cost effective to measure, supported byhistorical time-series, sensitive, and responsive to changes in ecosys-tem state (and management efforts), and responsive to propertiesthey are intended to measure. Levin et al. (2011) adapted these fra-meworks by soliciting and organizing expert judgement from thescientific community. Then, building on Rice and Rochet (2005),a team of scientists representing different agencies and areas of ex-pertise worked through proposed indicators and determined howwell they met criteria related to public awareness, cost effectiveness,theoretical foundation, measurability, and availability of historicaldata (Levin et al., 2011). This type of screening process is a necessaryfirst step, but it cannot rigorously evaluate key indicator traits suchas sensitivity, responsiveness, or specificity. Similar screening pro-cesses have been adopted in other regions (Link et al., 2002;Ecosystem Assessment Program, 2009; Shin et al., 2012).

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Efforts in the Gulf of Mexico, Northeastern US, and CaliforniaCurrent are using ecosystem models to evaluate the diagnostic qual-ities of indicators (Fulton et al., 2005; Samhouri et al., 2009; Levinand Schwing, 2011). These models are used to simulate varyinglevels and different types of perturbations to the ecosystem.The performance of each indicator in tracking perturbationsor ecosystem structure and function can be assessed using avariety of statistical techniques (e.g. time-series analysis, cross-correlations, etc.).

As with all phases of the IEA, indicators need to be regularlyupdated and revisited as more information becomes available, as en-vironmental conditions change, and as new threats emerge. Finally,because indicators are a key point of connectivity between scienceand policy, it is important to generate portfolios of indicators thatare not only scientifically rigorous but are also understandableand salient to stakeholders (Levin et al., 2010).

Science to inform the establishment of ecosystem managementreference levelsEstablishing a set of indicator values that reflect progress towardsspecific management objectives is critical for successful EBM.Such reference levels provide context for evaluating performanceand progress towards EBM goals. Reference levels can be diverseand include both ecosystem state variables of interest (e.g. habitatarea, measures of diversity, etc.) as well as metrics of ecosystem pres-sures (e.g. shoreline development, nutrient, or contaminant input).These levels can be drawn from the underlying properties of thenatural and human systems or they can be designated as part ofthe process of setting management goals. Establishing a referencelevel is informed by science, but ultimately reference levels are setto achieve a desired policy outcome.

For an IEA, reference levels serve a variety of purposes. The mostobvious is the role they play in the establishment of targets for restor-ing and protecting the ecosystem (Sainsbury et al., 2000; Bottrillet al., 2008). A reference target is the level of an ecosystem indicatorthat represents the desired state of the ecosystem. A reference limit,on the other hand, is the attribute level that marks an ecosystem stateto be avoided (Samhouri et al., 2011). In fisheries management, forinstance, “optimum yield” is a reference target and “overfished” is areference limit. Because some ecosystem indicators respond slowlyto management action or natural drivers, there is a need for bench-marks or intermediate indicator values that demonstrate progresstowards those levels.

Ecosystem-based reference levels are needed to refine the limitsof acceptable resource use, plan for future climate- and human-induced changes to ecosystem services, and inform conservationand recovery plans for sensitive species and habitats. Scientific ana-lysis can contribute to the setting of reference levels in several ways.For example, perturbations to ecosystem models have been used toexplore non-linearities between pressures and ecosystem state (e.g.Samhouri et al., 2010). To complement these modelling approaches,statistical models may prove useful for investigating the relationshipbetween ecosystem state variables and natural and anthropogenicpressures. No matter what approaches are used, the goal of thisstep is to identify thresholds and inflection points that mayprovide a basis for the identification of reference levels.Importantly, as we noted at the beginning of this section, the iden-tification of reference levels is a societal choice and the role of IEAs isto inform that choice.

Step 3: risk analysis—impacts of natural perturbationsand human activities on ecosystem statusDescription of different approaches for conducting risk analysisOnce ecosystem indicators and reference levels are selected, the nextIEA step evaluates the risk to the indicators posed by human activ-ities and natural processes. The goal of these risk analyses is to quali-tatively or quantitatively determine the likelihood that an ecosystemindicator will reach or remain in an undesirable state (i.e. breach areference limit). Ecosystem modelling and analysis are importantin determining incremental improvements in ecosystem indicatorsin response to changes in human-induced pressures. Risk analysismust explicitly consider the inevitable uncertainties involved inunderstanding and quantifying ecosystem dynamics and their posi-tive and negative impacts on social systems.

Risk analysis must include pressures that occur on land (e.g.coastal development, agriculture, changing river flows, etc.), inthe air (e.g. weather, climate), and in the ocean itself (e.g. shipping,naval exercises, fishing, energy extraction, and physical and chem-ical conditions; Halpern et al., 2009). Thus, an ecosystem risk ana-lysis ideally requires an understanding of the distribution andintensity of land-, air-, and sea-based pressures, as well as theirimpacts on ecosystem components. Additionally, because the cu-mulative effect of multiple stressors may not simply equal the sumof the individual stressors’ effects, risk analysis should consider cu-mulative impacts (Crain et al., 2008; Ban et al., 2010; Kaplan et al.,2012).

There are a number of approaches to risk assessment; however,most forms of risk assessment can be used within the ecologicalrisk assessment framework described by Hobday et al. (2011).Briefly, this is a hierarchical approach that moves from qualitativebut comprehensive analyses (level 1) to a less comprehensive, semi-quantitative analysis (level 2) and to a focused, fully quantitativeanalysis (level 3).

A level 1 analysis for each pressure qualitatively scores eachhuman activity or natural perturbation for its impact on the focalecosystem components of the IEA. Those pressures receiving ahigh impact score move onto level 2 analyses. As part of theongoing engagement process described above, scientists and man-agers need to define what levels of impact score constitute “high”or “low” for this process. Thus, a level 1 analysis separates outthose activity-component pairs that warrant further investigationfrom those that are given the all clear.

A level 2 analysis considers the exposure of an ecosystem compo-nent to a pressure and the sensitivity of the component to that pres-sure. This framework has proven useful for conductingsemi-quantitative risk analysis in ecosystem-based fisheries man-agement (Stobutzki et al., 2002; Hobday et al., 2006, 2011; Patricket al., 2010) and has been useful for IEAs, as well (e.g. Samhouriand Levin, 2012). In this approach, risk to an indicator can bedefined as the Euclidean distance of the indicator from the originin a space defined by exposure and sensitivity to particular humanactivities. Exposure can be estimated as a function of spatial andtemporal overlap of activities, and sensitivity can be estimated bythe degree to which life-history attributes or behaviour affects anindicator’s ability to resist or recover from exposure to a human ac-tivities. If this level 2 analysis determines the impact of an activity ona species or other ecological component is high and there are noplanned management interventions to remove it, the reasons aredocumented and the assessment moves to level 3.


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The level 3 analysis takes a quantitative approach such as is usedin stock assessments and population viability analyses. A number ofmodelling approaches lend themselves to level 3 analyses, but all aredependent on the amount and quality of the available data. Whatmodel is used in a level 3 analysis depends on the nature of thedata and other available information.

Step 4: evaluation of management strategies for protectionor restoration of ecosystem statusApproaches for evaluating management strategiesThe next step in the IEA process uses simulation and analytical orconceptual modelling to evaluate the potential of different manage-ment strategies to influence the status of natural and human systemindicators and to achieve our stated ecosystem objectives.

Scenario analysis generates the multiple alternative descriptionsof potential outcomes, including processes of change, thresholds,and uncertainties (Alcamo, 2008). Scenarios explore alternative per-spectives about underlying system processes and can illuminate keyissues, by using a consistent set of assumptions about the systemstate to broaden perspectives (Raskin, 2005; Refsgaard et al.,2007). They generate alternative, internally consistent, logicaldescriptions of the future. Scenarios can be qualitative, in which“storylines” are developed, or quantitative, in which the outcomesof numerical models are explored (Refsgaard et al., 2007).

Formal management strategy evaluation (MSE) is a modellingapproach that can be used to analyse posited scenarios. MSE iswidely used in the management of protected species (e.g. marinemammals) and fisheries and is beginning to see use in the EBM(Sainsbury et al., 2000; Fulton et al., 2007). By evaluating a rangeof management scenarios using multiple performance indicators(and potentially multiple operating models), formal MSE can beused to test the utility of modifying indicators, managementtargets, assessments, monitoring plans, management strategies,and decision rules. Importantly, the objective of MSE is not optimal-ity. Rather, MSE is used to screen out poorly performing manage-ment strategies, identify trade-offs among objectives, anddistinguish approaches robust to various types of uncertainty.Increasingly, MSEs are being used to evaluate interactionsbetween separate management tactics and interactions betweenmanagement, ecosystem processes, and large-scale drivers likeclimate change. For example, recent applications have attemptedto the minimize risk of uncertainty on target and bycatch species(e.g. Stram and Ianelli, 2009), ESA at-risk species, critical habitats,and human communities under various short- and long-termclimate scenarios (Hollowed et al., 2009)

MSE incorporates a number of important features (Sainsburyet al., 2000) that make it an ideal supporting process for IEAs. (i)Simulations are performed in the operating model on themanaged system as a whole. For management towards ecologicalobjectives, we require the explicit representation of the ecologicalsystem; similarly, for economic objectives, we require explicitecological-economic linkages. (ii) Performance metrics are evalu-ated quantitatively in a simulation framework utilizing the indica-tors developed earlier in the IEA process. (iii) A variety of modelsor submodels may be used in the evaluation process; thus, scenariosmay explore alternative hypotheses on ecosystem functioning ormay use a consistent set of assumptions about the system state to il-luminate key issues and broaden perspectives (Raskin, 2005;Refsgaard et al., 2007). (iv) The MSE process allows ample

opportunity for stakeholder involvement (e.g. workshops) and isgreatly strengthened by discussion regarding management strategiesto be evaluated, target species to include, incorporation of long-term monitoring data, comparison of model outcomes (includingsocio-economic impacts), and discussion of management trade-offs. (v) The MSE process often identifies data and knowledgegaps, which in turn can be used to inform future research.

Step 5: monitoring and evaluationMonitoring and evaluation of chosen indicators and managementstrategies is an integral part of the IEA process. Monitoring andevaluation is necessary to determine whether management strat-egies improve ecosystem services and sustainability and quantifiesthe trade-offs that have occurred since implementation of the man-agement strategy.

MonitoringAt its core, monitoring is straightforward; it is the collection ofbiotic, abiotic, and human dimension data. In the context of IEAs,monitoring is the systematic collection of data to reliably answerclearly articulated management questions (Katz, 2013). For IEAindicators, monitoring must directly address the operational objec-tives developed as part of the IEA process. While apparently simple,monitoring is costly and subject to the changing priorities offunding agencies. Thus, successful monitoring depends on develop-ing efficient sampling programmes that allow a cost-effective deter-mination of the state of the ecosystem and the effectiveness ofmanagement actions.

In general, there are two types of monitoring that are particularlyimportant to IEAs. Trend monitoring is a systematic series of obser-vations over time to detecting change in the state of an ecosystemcomponent (MacDonald et al., 1991). Typically, the observationsare not taken with the aim of evaluating management actions, al-though such data may prove useful in this context as well. Trendmonitoring focuses on the indicators of ecosystem state developedin step 2 of the IEA. Effectiveness monitoring is used to evaluatewhether specific management actions had the desired effect.Effectiveness monitoring focuses on changes in threats identifiedin the scoping phase of the IEA and links threat reduction tochanges in the status of key ecosystem components. Thus, effective-ness monitoring requires the observations of threats as well as theecosystem component(s) targeted by the management action.

Katz (2013) notes that the key elements of monitoring are deter-mining “what, where, (and sometimes) how” to measure the system.He also notes that in the best cases, a monitoring programme alsoconfronts the issue of how well one wants to know the answer.Successfully addressing these elements defines the indicators(what and how) and the sampling design (where, when, and howwell). Importantly, monitoring includes not only the measurementsof the biophysical environment but also includes social and eco-nomic systems (McLeod and Leslie, 2009).

EvaluationEvaluation of ecosystem status involves using data generated fromtrend monitoring to assess the condition or status of particular eco-system components (Stem et al., 2005). In contrast to status evalu-ation, evaluations for measuring management effectiveness arenecessarily linked to discrete management actions and obviouslyare directly linked to effectiveness monitoring. Stem et al. (2005)


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describe two types of effectiveness evaluations. Impact evaluationsare generally one-time assessments frequently performed at the con-clusion of a management project. The goal of impact evaluations isto determine how well a particular project performed. A secondform of effectiveness evaluation is adaptive management—an itera-tive process that integrates the design of management strategies andmonitoring to systematically evaluate management actions(Walters, 1986). Successful IEAs will evaluate the effectiveness ofmanagement actions and provide information to managers sothey can adjust actions, as needed.

ConclusionsAfter decades of struggle over what EBM means, whether it is pos-sible, and if it is needed, we have arrived at a time when comprehen-sive EBM is emerging and is supporting efforts to recover andconserve marine ecosystems (e.g. Lubchenco and Sutley, 2010). Tofurther the transition of EBM from principles to practice, we mustdevelop approaches that provide an efficient, transparent meansof summarizing the status of ecosystem components, screeningand prioritizing potential risks, and evaluating alternative manage-ment strategies against a backdrop of environmental variability.IEAs provide a means to do just this. Importantly, while thescience of IEAs is progressing, Samhouri et al. (in review) notethat operationalizing IEAs in management will require additionalwork and provide insight into how this might be facilitated.

In this paper, we opted out of producing an IEA “cookbook” withsimple recipes for accomplishing each IEA step. Ecosystems, includ-ing their associated institutions, are too variable for such a prescrip-tive treatment. Instead, we provide a cookbook without recipes (cf.Haller, 1976), with the goal of providing basic guidance that can betailored to the specific management needs, scientific capacity, andgovernance structures in any region. Like all science-managementprocesses, we expect that as IEAs propagate and the scientific andmanagement communities gain experience with them, a collectionof best IEA practices will emerge. Currently, however, we lookforward to a period of creativity and innovation that will rapidlyadvance the rigor and utility of this try.

ReferencesAgardy, M., Davis, J., Sherwood, K., and Vestergaard, O. 2011. Taking

steps toward marine and coastal ecosystem-based management-anintroductory guide. UNEP Regional Seas Reports and Studies, 189.68 pp.

Alcamo, J. 2008. Environmental Futures: the Practice of EnvironmentalScenario Analysis. Elsevier, Amsterdam.

Arkema, K. K., Abramson, S. C., and Dewsbury, B. M. 2006. Marineecosystem-based management: from characterization to implemen-tation. Frontiers in Ecology and the Environment, 4: 525–532.

Ban, N. C., Alidina, H. M., and Ardron, J. A. 2010. Cumulative impactmapping: advances, relevance and limitations to marine manage-ment and conservation, using Canada’s Pacific waters as a casestudy. Marine Policy, 34: 876–886.

Bottrill, M. C., Joseph, L. N., Carwardine, J., Bode, M., Cook, C., Game,E. T., Grantham, H., et al. 2008. Is conservation triage just smart de-cision making? Trends in Ecology and Evolution, 23: 649–654.

Bowen, R. E., and Riley, C. 2003. Socio-economic indicators and inte-grated coastal management. Ocean and Coastal Management, 46:299–312.

Cowling, R. M., Egoh, B., Knight, A. T., O’Farrell, P. J., Reyers, B.,Rouget, M., Roux, D. J., et al. 2008. An operational model for main-streaming ecosystem services for implementation. Proceedings ofthe National Academy of Sciences of the USA, 105: 9483–9488.

Crain, C. M., Kroeker, K., and Halpern, B. S. 2008. Interactive and cu-mulative effects of multiple human stressors in marine systems.Ecology Letters, 11: 1304–1315.

Ecosystem Assessment Program. 2009. Ecosystem Status Report for theNortheast U.S. Continental Shelf Large Marine Ecosystem. USDepartment of Commerce, Northeast Fisheries Science CenterReference Document, 09-11. 34 p.


Fulton, E. A., Smith, A. D. M., and Smith, D. C. 2007. Alternative man-agement strategies for Southeast Australian CommonwealthFisheries: Stage 2: Quantitative management strategy evaluation.Commonwealth Scientific and Industrial Research Organisation(CSIRO), Hobart, Tasmania, Australia.

Haller, J. 1976. The Blue Strawberry Cookbook: Cooking (Brilliantly)Without Recipes. Harvard Commons Press, Cambridge, MA.

Halpern, B. S., Kappel, C. V., Selkoe, K. A., Micheli, F., Ebert, C. M.,Kontgis, C., Crain, C. M., et al. 2009. Mapping cumulative humanimpacts to California Current marine ecosystems. ConservationLetters, 2: 138–148.

Heinz Center for Science and the Environment. 2008. The State of theNation’s Ecosystems 2008: Measuring the Lands, Waters, andLiving Resources of the United States. Island Press, Washington DC.

Hobday, A. J., Smith, A., Webb, H., Daley, R., Wayte, S., Bulman, C.,Dowdney, J., et al. 2006. Ecological Risk Assessment for the Effectsof Fishing: Methodology. Report R04/1072 for the AustralianFisheries Management Authority, Canberra.

Hobday, A. J., Smith, A. D. M., Stobutzki, I. C., Bulman, C., Daley, R.,Dambacher, J. M., Deng, R. A., et al. 2011. Ecological risk assessmentfor the effects of fishing. Fisheries Research, 108: 372–384.

Hollowed, A. B., Bond, N. A., Wilderbuer, T. K., Stockhausen, W. T.,A’mar, Z. T., Beamish, R. J., Overland, J. E., et al. 2009. A frameworkfor modelling fish and shellfish responses to future climate change.ICES Journal of Marine Science, 66: 1584–1594.

ICES. 2010. Report of the Working Group on Ecosystem Effects ofFishing Activities (WGECO), 7–14 April 2010, Copenhagen,Denmark. ICES Document CM 2010/ACOM: 23.

James, C. A., Kershner, J., Samhouri, J., O’Neill, S., and Levin, P. S. 2012.A methodology for evaluating and ranking water quantity indicatorsin support of ecosystem-based management. EnvironmentalManagement, 2012: 1–17.

Kaplan, I. C., Gray, I. A., and Levin, P. S. 2012. Cumulative impacts offisheries in the California Current. Fish and Fisheries, in press.

Katz, S. L. 2013. Monitoring endangered species. In Extinction. Ed. by N.MacLeod, D. Archibald, and P. S. Levin. Gale Publishing,Farmington Hills, MI.

Kershner, J., Samhouri, J. F., James, C. A., and Levin, P. S. 2011. Selectingindicator portfolios for marine species and food webs: a Puget Soundcase study. PLoS One, 6: e25248.

Levin, P. S., Damon, M., and Samhouri, J. F. 2010. Developing meaning-ful marine ecosystem indicators in the face of a changing climate.Stanford Journal of Law Science and Policy, 2: 37–48.

Levin, P. S., Fogarty, M., Matlock, G., and Ernst, M. 2008. Integratedecosystem assessments. US Department of Commerce. NOAATechnical Memorandum, NMFS-NWFSC 92. 20 pp.

Levin, P. S., Fogarty, M. J., Murawski, S. A., and Fluharty, D. 2009.Integrated ecosystem assessments: developing the scientific basisfor ecosystem-based management of the ocean. PLoS Biology, 7:e1000014 doi:1000010.1001371/journal.pbio.1000014.

Levin, P. S., James, C. A., Kershner, J., O’Neill, S., Francis, T. B.,Samhouri, J. F., Harvey, C. J., et al. 2011. The Puget SoundEcosystem: what is our desired outcome and how do we measureprogress along the way? Accessed from pugetsoundscienceupdate.-com. Puget Sound Partnership, Tacoma, WA.

Levin, P. S., and Schwing, F. 2011. Technical background for an IEA ofthe California Current: ecosystem health, salmon, groundfish and


by How

ard Brow

man on July 2, 2014


Dow

nloaded from


green sturgeon. NOAA Technical Memorandum, NMFS-NWFSC-109.330 pp.

Link, J. S. 2005. Translating ecosystem indicators into decision criteria.ICES Journal of Marine Science, 62: 569.

Link, J. S., Brodziak, J. K. T., Edwards, S. F., Overholtz, W. J., Mountain,D., Jossi, J. W., Smith, T. D., et al. 2002. Marine ecosystem assessmentin a fisheries management context. Canadian Journal of Fisheriesand Aquatic Sciences, 59: 1429–1440.

Lubchenco, J., and Sutley, N. 2010. Proposed U.S. Policy for Ocean,Coast, and Great Lakes Stewardship. Science, 328: 1485–1486.

MacDonald, L. H., Smart, A. W., and Wissmar, R. C. 1991. Monitoringguidelines to evaluate effects of forestry activities on streams in thePacific Northwest and Alaska. Region 10, US EPA. https://digitallibwashingtonedu/dspace/handle/1773/17068.

McLeod, K., and Leslie, H. 2009. Ecosystem-Based Management for theOceans. Cambridge University Press.


Millennium Ecosystem Assessment (MEA). 2005. Ecosystems andHuman Well-being: Synthesis. Island Press.

Murawski, S., and Matlock, G. 2006. Ecosystem science capabilitiesrequired to support NOAA’s mission in the year 2020. NOAATechnical Memorandum, NMFS-F/SPO-74, Silver Spring, MD.

O’Boyle, R., and Jamieson, G. 2006. Observations on the implementa-tion of ecosystem-based management: experiences on Canada’seast and west coasts. Fisheries Research, 79: 1–12.

Patrick, W. S., Spencer, P., Link, J., Cope, J., Field, J., Kobayashi, D.,Lawson, P., et al. 2010. Using productivity and susceptibility indicesto assess the vulnerability of United States fish stocks to overfishing.Fishery Bulletin, 108: 305–322.

Puget Sound Partnership. 2006. Sound health, sound future: protectingand restoring Puget Sound. Olympia, Washington.

Raskin, P. D. 2005. Global scenarios: background review for theMillennium Ecosystem Assessment. Ecosystems, 8: 133–142.

Refsgaard, J. C., van der Sluijs, J. P., Hojberg, A. L., and Vanrolleghem,P. A. 2007. Uncertainty in the environmental modelling process - Aframework and guidance. Environmental Modelling and Software,22: 1543–1556.

Rice, J. C., and Rochet, M. J. 2005. A framework for selecting a suite ofindicators for fisheries management. ICES Journal of MarineScience, 62: 516–527.

Sainsbury, K., and Sumaila, R. 2003. Incorporating ecosystem objectiveis into management of sustainable marine fisheries, including bestpractice reference points and use of marine protected areas. InResponsible Fisheries in the Marine Ecosystems. Ed. by M.Sinclair, and G. Valdimarsson. FAO, Rome.

Sainsbury, K. J., Punt, A. E., and Smith, A. D. M. 2000. Design of oper-ational management strategies for achieving fishery ecosystem objec-tives. ICES Journal of Marine Science, 57: 731–741.

Samhouri, J. F., Haupt, A., Levin, P. S., Link, J., and Shuford, R. Inreview. Lessons learned from developing integrated ecosystemassessments to inform marine ecosystem-based management inthe U.S. ICES Journal of Marine Science.

Samhouri, J. F., and Levin, P. S. 2012. Linking land-and sea-based activ-ities to risk in coastal ecosystems. Biological Conservation, 145:118–129.

Samhouri, J. F., Levin, P. S., and Ainsworth, C. H. 2010. Identifyingthresholds for ecosystem-based management. PLoS One, 5: e8907.doi:10.1371/journal.pone.0008907

Samhouri, J. F., Levin, P. S., Andrew James, C., Kershner, J., andWilliams, G. 2011. Using existing scientific capacity to set targetsfor ecosystem-based management: a Puget Sound case study.Marine Policy, 35: 508–518.


Shin, Y. J., Bundy, A., Shannon, L. J., Blanchard, J. L., Chuenpagdee, R.,Coll, M., Knight, B., et al. 2012. Global in scope and regionally rich:an IndiSeas workshop helps shape the future of marine ecosystemindicators. Reviews in Fish Biology and Fisheries, pp. 1–11.

Shin, Y. J., and Shannon, L. J. 2010. Using indicators for evaluating,comparing, and communicating the ecological status of exploitedmarine ecosystems. 1. The IndiSeas project. ICES Journal ofMarine Science, 67: 686–691.

Stem, C., Margoluis, R., Salafsky, N., and Brown, M. 2005. Monitoringand evaluation in conservation: a review of trends and approaches.Conservation Biology, 19: 295–309.

Stobutzki, I., Miller, M., and Brewer, D. 2002. Sustainability of fisherybycatch: a process for assessing highly diverse and numerousbycatch. Environmental Conservation, 28: 167–181.

Stram, D., and Ianelli, J. 2009. Eastern Bering Sea pollock trawl fisheries:variation in salmon bycatch over time and space. American FisheriesSociety Symposium, 70: 827–850.

Svarstad, H., Petersen, L. K., Rothman, D., Siepel, H., and Watzold, F.2008. Discursive biases of the environmental research frameworkDPSIR. Land Use Policy, 25: 116–125.

U. S. Commission on Ocean Policy. 2004. An ocean blueprint for the21st century. Final Report to the Present and Congress.

Walters, C. J. 1986. Adaptive Management of Natural Resources.Mac-Millan, New York.

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Original Article

Lessons learned from developing integrated ecosystemassessments to inform marine ecosystem-based managementin the USA

Jameal F. Samhouri1*, Alison J. Haupt2, Phillip S. Levin1, Jason S. Link3, and Rebecca Shuford4

1Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and AtmosphericAdministration, 2725 Montlake Boulevard East, Seattle, WA 98112, USA2West Coast Governors Alliance, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and AtmosphericAdministration, 2725 Montlake Boulevard East, Seattle, WA 98112, USA3National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 166 Water St., Woods Hole, MA 02543, USA4Marine Ecosystems Division, Office of Science and Technology, National Marine Fisheries Service, National Oceanic and Atmospheric Administration,Silver Spring, MD 20910, USA

*Corresponding author: e-mail: [email protected]

Samhouri, J. F., Haupt, A. J., Levin, P. S., Link, J. S., and Shuford, R. 2014. Lessons learned from developing integrated ecosystem assessments to informmarine ecosystem-based management in the USA. – ICES Journal of Marine Science, 71: 1205–1215.

Received 2 May 2013; accepted 1 August 2013; advance access publication 7 September 2013.

Borne out of a collective movement towards ecosystem-based management (EBM), multispecies and multi-sector scientific assessments ofthe ocean are emerging around the world. In the USA, integrated ecosystem assessments (IEAs) were formally defined 5 years ago to serve asa scientific foundation for marine EBM. As outlined by the US National Oceanic Atmospheric Administration in 2008, an IEA is a cyclicalprocess consisting of setting goals and targets, defining indicators, analysing status, trends, and risk, and evaluating alternative potentialfuture management and environmental scenarios to enhance information needed for effective EBM. These steps should be hierarchical,iterative, non-prescriptive about technical implementation, and adaptable to existing information for any ecosystem. Despite thesestrengths and some initial successes, IEAs and EBM have yet to be fully realized in the USA. We propose eight tenets that can beadopted by scientists, policy-makers, and managers to enhance the use of IEAs in implementing EBM. These tenets include (i) engagewith stakeholders, managers, and policy-makers early, often, and continually; (ii) conduct rigorous human dimensions research; (iii) rec-ognize the importance of transparently selecting indicators; (iv) set ecosystem targets to create a system of EBM accountability; (v) establisha formal mechanism(s) for the review of IEA science; (vi) serve current management needs, but not at the expense of more integrative oceanmanagement; (vii) provide a venue for EBM decision-making that takes full advantage of IEA products; and (viii) embrace realistic expecta-tions about IEA science and its implementation. These tenets are framed in a way that builds on domestic and international experienceswith ocean management. With patience, persistence, political will, funding, and augmented capacity, IEAs will provide a general approachfor allowing progressive science to lead conventional ocean management to new waters.

Keywords: ecosystem-based management, indicator, integrated ecosystem assessment, marine policy, risk, sustainable marine management andconservation.

IntroductionPeople are unquestionably dependent upon the services that marineecosystems provide (Guerry et al., 2012). In turn, ocean conditions

are affected by people’s actions and influences (Halpern et al.,2012). Marine resources face a well known and growing list of pres-sures and demands—from long-standing activities like fisheries and

Published by Oxford University Press on behalf of the International Council for the Exploration of the Seas 2013. This work is written by(a) US Government employee(s) and is in the public domain in the US.

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extraction of fossil fuels, to newer uses such as wind and wave energy(Halpern et al., 2008). Because of existing governance structures,ocean managers have historically tackled the most pressing activities,and addressed them one-by-one (Kareiva and Marvier, 2011).

However, in the face of emerging uses and increasing demandsfrom existing activities, this reactive, sectoralized approach toocean management has been called into question (Levin andLubchenco, 2008). Protected areas, for instance, may achievesome conservation objectives within their boundaries, butwithout coordinated management outside of their boundaries, dis-placed fishing effort may result in the degradation of an ecosystem asa whole (Hilborn et al., 2006; Jennings, 2009). Similarly, reductionsin chemical pollution and improvements in water quality have facili-tated the recovery of endangered coastal species such as the baldeagle, but recovery of eagles has led to the decline of some otherseabird species and overall diversity (Hipfner et al., 2012). Asthese examples illustrate, well intentioned but segmented manage-ment has the potential to interfere with other ecosystem goals andperhaps even degrade the overall state of marine environments.

A potential solution is a more systematic, integrated approachknown as ecosystem-based management (EBM; McLeod and Leslie,2009). The transition to EBM will not be easy, fast, or simple. It islikely to be gradual and iterative, building on existing single speciesand single-sector governance where possible and characterized bytrial-and-error learning where such building is not possible. The evo-lution of comprehensive management is likely to benefit from inte-grated science—a rarity in many regions. In the USA, the NationalOceanicandAtmospheric Administration (NOAA) has been develop-ing the integrated ecosystem assessment (IEA) as a means to conductand deliver integrated, cross-sectoral science to support EBM (Levinet al., 2009). IEAs transparently identify socio-economic and bio-physical attributes that maintain ecosystem structure and function,assess human activities and their interdependence with the naturalecosystem, and evaluate management alternatives that will maintainor improve the coupled social-ecological system (Figure 1).

While IEAs are a major step forward for developing the science tosupport EBM (Foley et al., 2013), both in the USA and around theworld (Smith et al., 2007; European Commission, 2008;Katsanevakis et al., 2011; ICES, 2011, 2013a, b, c, Mollmann, inpress), widespread confusion exists about what, exactly, defines anIEA, and how to use an IEA so that it informs on-the-wateractions. A companion paper by Levin et al. (this volume) and previ-ous descriptions (Levin et al., 2008, 2009) delineate one perspectiveof what an IEA is. In this article, we explore the question of how suchIEAs can be used in US ocean management now (through severalproposed tenets), discuss reasonable expectations of IEAs in thecontext of implementation of EBM, and offer some suggestionsabout what needs to happen next to make better use of them. Ourperspective on these topics is based on our collective experienceattempting to inform EBM via IEAs in the USA, largely learningby trial and error, while doing our best as scientists to create asolid technical basis from which to conduct EBM. We hope thismini-review of what has worked well, what has not worked well,and what may work well in the USAwill be of interest to those devel-oping integrated scientific assessments, and trying to avoid potentialimpediments to their use, for ocean management around the world.

Brief history of IEAs in the USAHigh-profile reports by the US Oceans Commission (USCOP, 2004)and the Pew Oceans Commission (POC, 2003) stressed the import-ance of incorporating ecosystem principles into US ocean and

coastal resource management. Indeed, the premise of EBM is nowcodified in the US National Ocean Policy (Obama, 2010; USNOC,2013). In response to recommendations of these reports suggestingthe need for technical information to support EBM decisions,NOAA’s Science Advisory Board commissioned an external

Figure 1. Conceptual schematic describing the cyclical, iterativenature of IEAs at the US NOAA. This figure is an update of thecharacterization of the approach depicted in Levin et al. (2009). DefineEBM goals and targets: the IEA process involves manager engagement toidentify critical ecosystem management goals and targets to beaddressed through and informed by the IEA approach. The rest of theprocess is driven by these defined objectives, which can be informed byavailable scientific syntheses during the development of the first IEA inany region. Engagement is continual throughout the entire IEA process.Develop indicators: indicators represent key components in anecosystem and allow change to be measured. They provide the basis toassess the status and trends in the condition of the ecosystem or of anelement within the system. Indicators are essential to all subsequentsteps in the IEA approach. Assess ecosystem: ecosystem indicator dataare assessed together to evaluate overall ecosystem status and trendsrelative to ecosystem management goals and targets. Individualindicators are assessed to determine the underlying cause for theobserved ecosystem status and trends. Analyse uncertainty and risk:ecosystem analyses and models evaluate risk to the indicators (and thusthe ecosystem) posed by human activities and natural processes. Thesemethods incorporate the degree of uncertainty in each indicator’sresponse to pressures. This determines incremental improvements ordeclines in ecosystem indicators in response to changes in drivers andpressures and to predict the potential that an indicator will reach orremain in an undesirable state. Evaluate strategies: managementstrategy evaluation (MSE) is useful to help resource managers considertrade-offs and potential for success in reaching targets. It relies onecosystem modelling and empirical analysis to evaluate the potentialfor different management strategies to influence the status of naturaland human system indicators and to achieve stated ecosystemobjectives. Taking, monitoring, and assessing action: Based on the MSE,an action is selected and implemented. Monitoring of indicators isimportant to determine if the action is successful; if yes, the status,trends, and risk to the indicators continue to be analysed forincremental change. Otherwise as part of adaptive management, theoutcomes need to be assessed and evaluated to refine goals, targets,and/or indicators.

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review of NOAA’s ecosystem research. The resulting report(Fluharty et al., 2006) recommended that NOAA prioritize the pro-duction of IEAs, although the report did not precisely define an IEA.As a result, NOAA developed the US IEA framework (Levin et al.,2009) as a cyclical process consisting of setting goals and targets, de-fining indicators, analysing status, trends, and risk, and evaluatingalternative potential future management and environmental scen-arios (Figure 1). The NOAA approach is a direct descendant ofapproaches advocated by Caddy (1999), Sainsbury et al. (2000),and Smith et al. (2007), but it is related to decades of EBM thinkingaround the globe (reviewed by Rosenberg et al., 2009; also seeEuropean Commission, 2008; Katsanevakis et al., 2011; ICES,2011, 2013a, b, c; Mollmann, in press).

Underpinning the distinct IEA steps (Figure 1) are four integra-tive ideas. First, an IEA is hierarchical: all indicators, status assess-ments, risk analyses, and scenario evaluations must map back tothe established ecosystem management goals. Second, IEAs mustbe considered an iterative process. This idea complicates an other-wise hierarchical structure during the development of the first IEAfor a region. The process of setting ecosystem management goalsfor the first time can definitely benefit from synthesis of scientific in-formation that allows a description of what is possible from a multi-sector perspective. For example, in what has emerged as a nationalexample of EBM implementation, a synthetic scientific report wasproduced in Puget Sound, WA (Ruckelshaus and McClure, 2007),before the delineation of ecosystem goals by the regional manage-ment agency. Indeed, the first IEA for any region, and any majorchanges to ecosystem management goals, requires an iterative dia-logue between scientists and those charged with setting goals.Third, the IEA is not prescriptive about analytical approaches.There are a variety of qualitative and quantitative tools that can beused to conduct an IEA, and the appropriate tool depends on theparticulars of data availability, scientific capacity, and ecosystemgoals. Thus, because it is not prescriptive, an IEA can be implemen-ted now, over a range of spatial and temporal scales, for a variety ofecosystem objectives (Tallis et al., 2010). Fourth, an IEA is funda-mentally cross-sectoral. That is, IEAs address drivers, pressures,and impacts on ecosystem services that cross ecosystems, habitats,species, and human activities and institutions. Thus, ecosystemassessments that address a single sector (e.g. fisheries) cannot beconsidered truly integrated (Levin et al., 2009).

IEAs are currently under development throughout the USA in aphased implementation strategy (Table 1). NOAA selected theCalifornia Current for the first full IEA development, and workbegan in 2009. There is also formal IEA work being conducted inthe Gulf of Mexico, the US Northeast Shelf, Alaska, and thePacific Islands. Although IEAs were introduced only 5 years ago asan approach to enable marine EBM (Levin et al., 2008), there arealready examples that illustrate how they can and will be used.

A key success of the US IEA programme has been the adoption ofa standard conceptual framework that facilitates customized imple-mentation. While IEA products are best tailored to regional goalsand institutions, the existence of a common, cyclical approach(Figure 1) has provided for national consistency while enablingand encouraging regional flexibility. It is already clear that this pro-gramme design eases internal and external communication andenhances the potential for regional comparisons.

Perhaps as a result of national consistency and regional flexibil-ity, the “clientele” for IEAs is substantial and growing. The primaryIEA clients include (i) new decision-making entities that haveemerged to address increasingly diverse ocean uses in a

comprehensive fashion (e.g. regional planning bodies and regionalocean partnerships); and (ii) marine resource managers who arerequired by law to incorporate ecosystem considerations into theirdecisions but need tools to do so in a useful way.

As an example, in 2008, the West Coast Governors Alliance(WCGA) created the WCGA IEA Action Coordination Team toaddress the following issue (their Action 3.2): Assess physical, biologic-al, chemical, and socio-economic factors in ecosystem health across theWest Coast to establish standards and indicators for ocean health. TheWCGA IEA team created a plan to divide the dynamic and heteroge-neous California Current Large Marine Ecosystem into six subregionsto allow for local customization. For example, the Oregon Coastsub-IEA may focus on interactions of fisheries and renewable oceanenergy projects, whereas the Southern California sub-IEA may bemore concerned with water quality issues that can lead to frequentbeach closures in popular recreation areas.

Although IEAs are a nascent enterprise in the USA, there has beenample opportunity for growth and progress. While no region in theUSA can yet boast a fully mature IEA, the IEA approach must none-theless look forward to ensure that it is actually used to facilitateEBM. Below we identify eight key tenets (Table 2) that we haveextracted from the US experience, with the objective of improvingthe implementation and practice of IEAs. These tenets are by nomeans unique to the USA. Indeed, they build on best practices pro-posed elsewhere (e.g. UNEP and IOC-UNESCO, 2009) but arefocused on areas in which emphasis is needed to see IEAs implemen-ted in the USA: transparency, accountability, assurance of scientificrigor, and forging effective links between IEA science and oceanpolicy. It is our hope that clear articulation of these tenets willhelp scientists, managers, and policy-makers avoid potential pitfallsas ocean management transitions from its historical focus on singlespecies and single sectors to the one that is ecosystem-based.

Key tenets of IEA implementation and practice1. Engage with stakeholders, managers, and policy-makersearly, often, and continuallyGood communication underlies almost all successful applicationsof science to management and policy (Olson, 2009; Baron, 2010).The success of IEAs depends fundamentally on the scientist–manager–stakeholder dialogue in which scoping sessions serve tosupport the policy-making process that leads to the establishmentof a shared vision of the current and future desired states of their eco-system. This dialogue provides an opportunity for scientists toevaluate realistic alternative approaches for management toachieve desired states. Interactions between scientists, managers,and stakeholders must not be limited to a one-time event, butshould be maintained to adapt scientific products, managementstrategies, and ecosystem goals over time (Watson, 2005; Fletcher,2007; UNEP and IOC-UNESCO, 2009; deReynier et al., 2010).

There are a number of means that IEA teams can use to engage thelarger EBM community. In countries like the USA, these includepresenting IEA science in person or via webinars, developing webcontent, engaging in social media, producing web-based videos(http://www.noaa.gov/iea/multimedia/index.html), and conven-ing workshops, among others. Critically, effective communicationmust consider the technical and scientific knowledge of each user.Sophisticated data analyses and mathematical models that are alarge part of IEAs may not be accessible to all users (cf. Gleasonet al., 2010). Such hesitancy can be assuaged by communicating ina way that is tailored to specific interests and the knowledge base

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of each audience. For some groups, using marine spatial planningas an entre to the utility of IEAs may be useful, while for others, itmay be better to explain an IEA as an extension of standard stockassessments that includes such considerations as multispecies and

trophic relationships as well as environmental conditions. Thebottom line is that one size will not fit all, and that meeting audi-ences where they are will be crucial in engaging the diverse consti-tuents of IEAs.

Table 1. Snapshot examples of regional implementation of IEAs in the USA, as described on regional IEA websites accessible at http://www.noaa.gov/iea/.

Region Select examples of implementation progressKey managementtopics Current clientele

Alaska Complex † Annual ecosystem considerations chapter provided toNPFMC

† Ecosystem indicator selection process throughmultistakeholder workshops

† Use of multiple ecosystem models to develop and testindicators

† Development of metrics to represent condition ofecosystems; help establish reference points andcomparisons across ecosystems (part of Risk Assessment)

† Fisheries

† Climate

† Energy

† North Pacific FisheriesManagement Council

† Arctic Research Commission

† North Pacific Marine ScienceOrganization (PICES)

† Bureau of Ocean EnergyManagement

California Current † Two IEA reports, including all steps within IEA process(2011, 2013)

† Ecosystem considerations report delivered to PFMC (2011)

† Integration of IEA science into management discussions(e.g. Sanctuaries, Puget Sound, Sacramento River)

† IEA “toolkit” for CC

† Next steps: habitats, highly migratory species

† Climate

† Fisheries

† Energy

† Pacific Fisheries ManagementCouncil

† West Coast National MarineSanctuaries

† West Coast Governors Alliance

† North Pacific Marine ScienceOrganization (PICES)

Gulf of Mexico † Demonstration project with GMFMC SEDAR process toprovide ecosystem considerations

† Development of ensemble set of ecosystem models

† Ecosystem Assessment Management Report for 4estuarine ecosystems

† Development of digital trophic database and Data Atlas

† Next: Ecosystem Status report for 2013

† Commercial andRecreational Fishing

† Energy

† Population

† Recreation andTourism

† Shipping

† Gulf of Mexico FisheriesManagement Council

† Gulf of Mexico Alliance

† National Marine Sanctuaries

Northeast US Shelf † Development of multispecies and ecosystem models

† Indicator development using DPSIR

† Development of spatial tools for EBFM

† Semi-annual production of Ecosystem Advisory report

† Biannual Ecosystem Status report

† Fisheries

† Wind energy

† Protected species

† Climate

† Recreation andTourism

† Shipping

† New England and Mid-AtlanticFisheries Management Councils

† Northeast Regional OceanCouncil

† Mid-Atlantic Regional Council onthe Ocean

† North Atlantic FisheriesOrganization

† International Council forExploration of the Seas

Pacific Islands † Studies on effects of ocean circulation on larval retention

† Development of “reef” and “coastal” ecosystem model tounderstand energy flows and interactions

† Studies on human dimensions in ecosystem functions inKona Coast (incl. indicator development, identification ofdrivers and pressures, communication and networkingwith managers)

† Hawaiian Islands Humpback Whale National MarineSanctuary plan review

† Cetacean habitat modelling

† Kona IEA research cruises

† Shared use resources

† Aquaculture

† Climate change andKona Sentinel Site

† Fisheries andaquarium fishcollection

† Western Pacific Regional FisheriesManagement Council

† The Kohala Center

† Hawaii Division of AquaticResources

† Pacific Islands and Hawaii OceanObserving Systems

† National Marine Sanctuaries

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The Puget Sound Partnership (PSP) provides one model of en-gagement for IEAs. The PSP was established by the Governor ofWashington state, USA, in 2005 to protect and restore the PugetSound ecosystem. The PSP worked with the general public, diversestakeholders, a science working group, and regional managers andpolicy-makers to craft an “Action Agenda” to achieve this goal. TheAction Agenda was developed using a community-based approachthat made use of a number of public forums and that promoted exten-sive public and scientific input. These included workshops, experttopic meetings, and local meetings with the general public. In all,1600 people attended workshops, 75 presentations were given tocommunity and business groups, and some 12 300 public commentswere received (PSP, 2009). This level of engagement has been centralto the success of the PSP in obtaining funding to support restorationefforts$—$230 million has been spent annually on Puget SoundRestoration since the creation of the Action Agenda (http://www.kitsapsun.com/news/2012/oct/27/little-progress-reported-in-puget-sound-health/#axzz2RtAGFF1l).

2. Conduct rigorous human dimensions researchThe notion that humans are integral to marine ecosystems is nowcommonplace (McLeod and Leslie, 2009). However, thereremains a surprising asymmetry in the attention researchersdevote to natural vs. human systems when it comes to marineEBM (cf. Kittinger et al., 2012). We contend that for EBM, anabsence of rigorous investigations on the human dimensions of eco-systems is akin to ignoring basic elements of ecosystems such as up-welling, plankton productivity, and fish population dynamics.

Beyond simple definitions of EBM (McLeod et al., 2005), thereare a number of reasons why social science is fundamental. First,EBM is predicated on managing the actions of people based ontheir needs, and understanding people and their motivations is fun-damental to the achievement of ecosystem goals (Pollnac et al., 2010;Gutierrez et al., 2011). Second, understanding and addressing trade-offs is a central EBM pursuit; consequently, identifying how and whycultures value different ecosystem services derived from marinesystems is a basic necessity of EBM. Additionally, includinghuman dimensions of ecosystems can enhance the implementationof EBM by quantifying impacts on livelihoods and communities, in-creasing buy-in, reducing conflict (Evans and Klinger, 2008), andhelping to develop alternatives that address concerns of thoseaffected by ecosystem changes (Turner et al., 2008).

The ways in which human dimensions research could be incor-porated into IEAs are as varied as the academic disciplines thatstudy humans in marine ecosystems (e.g. history, political science,geography, anthropology, sociology, economics, psychology, etc.).

We offer three illustrative examples below that underscore the im-portance of including such work in IEAs.

Cultural keystone speciesClearly, in evaluating trade-offs among management options, it iscritical to know if a particular species holds importance beyondits monetary value or ecological role. For example, the red algaPorphyra abbottiae has been dubbed a “cultural keystone species”for the role it plays in indigenous cultures in the NorthernCalifornia Current (Turner, 2003). Porphyra is highly valued forits nutritional content, as a gift and trade item, and for its medicinalproperties (Garibaldi and Turner, 2004). As the term cultural key-stone species suggests, small changes in the availability ofPorphyra can have disproportionate impacts on the cultures thatdepend on it. Elders believe declines in gathering this alga willlead to a substantial loss of knowledge and tradition (Garibaldiand Turner, 2004). Thus, ignoring the cultural role species likePorphyra play in human communities will miss fundamental attri-butes of the social-ecological system.

Ecosystem service modellingMarine ecosystems produce goods and services that sustain humanlife, and increasingly, modern conservation science is focused onprotecting ecosystems for the benefit of humanity (Kareiva andMarvier, 2011). Process-based ecosystem service models that quan-titatively link change in marine ecosystems to change in human well-being will substantially enhance our ability to analyse the status andforecast the future of coupled social-ecological systems (Guerryet al., 2012). They offer a productive avenue for quantifyingimpacts of EBM strategies on livelihoods and communities. Thesemodels cannot be developed, refined, and put to use for manage-ment planning without deep interdisciplinary collaborationbetween economists, social scientists, and natural scientists.

Many examples of fruitful ecosystem service modelling effortsexist around the USA (Barbier et al., 2011; Tallis et al., 2013;White et al., 2012b). Perhaps the area ripest for further developmentis related to services provided by coastal habitats (e.g. saltmarshes,coral reefs, mangroves, oyster beds, barrier islands, etc.). Thevalue of coastal habitats can be enormous—in many areas, theyprovide a large variety of benefits to people, including coastaldefence from storms, aesthetic value, climate change mitigationvia carbon storage and sequestration, and more. For instance, arecent analysis examined how natural habitats across the entireUSA modify hazards due to sea-level rise, suggesting that thenumber of people, poor families, elderly, and total value of residen-tial property most exposed to hazards can be reduced by half if exist-ing coastal habitats remain fully intact (Arkema et al., 2013). Thisstudy underscored just one of the important functions natural habi-tats play in the coupled social-ecological system. The developmentof models that adequately capture the layered complexity of ecosys-tem services provided by coastal habitats will require significant in-tellectual consideration and resources, but are central to thedevelopment of socially resonant IEAs.

Behavioural science as a source of insightA deficiency of standard economic models is that they assumepeople make decisions rationally (Amir et al., 2005). The evidenceacross a wide range of examples suggests, however, that humansact in predictably irrational ways (Ariely, 2009). For example,Johnson and Goldstein (2003) showed that organ donation ratesacross several European countries were highly predictable based

Table 2. Tenets for IEA implementation and practice.

1. Engage with stakeholders, managers, and policy-makers early, often,and continually

2. Conduct rigorous human dimensions research3. Recognize the importance of transparently selecting indicators4. Set ecosystem targets to create a system of EBM accountability5. Establish a formal mechanism(s) for the review of IEA science6. Serve current management needs, but not at the expense of more

integrative ocean management7. Provide a venue for EBM decision-making that takes full advantage of

IEA products8. Embrace realistic expectations about IEA science and its

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on default options: participation rates were much higher in coun-tries where citizens “opted in” to donor programmes by defaultthan in countries where the default option was to “opt out”.

People may be motivated to action based on similarly subtle differ-ences in choices about how to report and deliver IEA science. For in-stance, Levin et al. (2010) showed that in some cases, indicators withequivalent ecological information content have widely varying socialresonance. Similarly, Beaudreau et al. (2011) demonstrated thatalternative views of biodiversity can lead to radically different percep-tions of risk to ecosystem components. Moreover, recognition ofboundaries of acceptable ecosystem conditions for different oceanusers and stakeholders can help define the “safe” operating spacefor EBM decisions (Rockstrom et al., 2009). Successful implementa-tion of EBM will require people to support management actions, andin some cases, to take actions as individuals (e.g. voting, clean upefforts, compliance with regulations, etc.). Social science can facilitatean understanding of people’s motivations for supporting or opposingsuch actions. Insights from behavioural science can help guide thedevelopment of socially meaningful IEA products most likely togarner public support for, and participation in, EBM implementation(cf. Thaler and Sunstein, 2003).

3. Recognize the importance of transparently selectingindicatorsThe development of a performance evaluation system is basic togood management of businesses, environmental issues, humanhealth, and more (Otley, 1999; Link, 2005; Rice and Rochet, 2005;Manski, 2013). Indicators are the basic building block for a perform-ance management system: they provide a means to track progresstowards management goals. At first glance, indicator selectionmay seem like a straightforward process. IEAs require indicatorsthat capture key ecosystem and socio-economic states and processes(Levin et al., 2009), and a number of frameworks exist to rigorouslydetermine an indicator set (e.g. Methratta and Link, 2006; Shin et al.,2010a, b; Kershner et al., 2011; James et al., 2012).

In practice, deriving a set of indicators is more challenging thansimply determining proxies for key ecosystem components or pro-cesses. This difficulty emerges from the truism that IEAs requiresome indicators, but not too many (cf. Lægreid et al., 2006). IEAsrequire that the performance characteristics of the indicators areunderstood and that the status and trends and current values relativeto EBM targets can be interpreted correctly (Rice and Rochet, 2005).Using too few indicators limits the scope for adequately assessing theecosystem, but too many indicators reveal a lack of prioritization ofgoals and objectives (Aucoin and Jarvis, 2005; Fulton et al., 2005;Methratta and Link, 2006). The fact that there is a limit on thenumber of indicators means that choices must be made, and notall potential indicators can be used.

The key to whittling down a potentially infinite list of candidateindicators is a transparent selection process. Transparency canavoid, or at least reveal, institutional and personal biases, helpingto create an indicator portfolio that meets the needs of EBM bybeing scientifically, politically, and socially meaningful. Formalevaluation of indicators following one of many indicator-screeningframeworks (see references above) ensures the transparency of indi-cator selection. Final selections can be made based on additionalinput from complementary public engagement efforts and conven-tional political processes. Indicators that are reported regularly canrepresent a subset of those that are tracked for the purposes of eco-system status assessment, providing a hedge in the event of ecologic-al surprises and evolving management goals. This recipe, if executed

properly, will generate a transparent and inclusive indicator set thattruly allows for monitoring and measuring of progress towards eco-system goals. Further, it can be used to generate a subset of standardindicators that will facilitate comparisons among IEA regions.

An example of culling these indicators, as developed in an IEAcontext, comes from the Northeast US shelf ecosystem where over300 indicators have been documented (Link and Brodziak, 2002).After an iterative selection process conducted to winnow thisnumber down (Link, 2005; Methratta and Link, 2006), many con-sultations among scientists, and several stakeholder workshops,the number of indicators routinely reported (http://www.nefsc.noaa.gov/publications/crd/crd1207/crd1207.pdf) is �30–50(EcoAP, 2009, 2012). These ecological, economic, and social indica-tors are intended to represent aspects of the marine social-ecologicalenvironment that affect and are affected by human use of the ecosys-tem. This much more concise list allows for multiple uses of the in-formation in many contexts, regular updates (every 2–3 years), andthe examination of novel hypotheses and processes related toobserved patterns. An even smaller subset of indicators is reportedmore frequently to track trends in ecosystem dynamics andprovide alerts in the event of major shifts (http://www.nefsc.noaa.gov/ecosys/advisory/current/advisory.html).

4. Set ecosystem targets to create a system of EBMaccountabilityAlone, a transparently selected, ecologically defensible, politicallyacceptable set of ecosystem indicators is of limited value for EBM.To guide effective management, indicators must be associatedwith targets, or values of the indicators equated with successfulachievement of management goals (Samhouri et al., 2011, 2012).We distinguish between targets and other reference points such asecosystem thresholds, in that targets need not be defined objectivelythrough analysis of biophysical or socio-economic data. Rather,targets should reflect desired ecosystem states, as articulatedthrough people’s stated or revealed preferences for alternative eco-system conditions. Active monitoring of indicators in relation tosuch targets can be used to instigate, cease, or adapt EBM actions.

However, generating consensus on target values for indicators atthe ecosystem level is no small task, for at least two reasons. First,perceptions of ecosystem status are just that: a personal, subjectiveassessment that is very likely to differ from stakeholder to stakehold-er depending on how s/he uses and values marine ecosystems (e.g.Loring, 2013). Thus, it is realistic to expect target setting to be a pol-itical activity, informed by scientific information. Such is the case inmany familiar single-sector management examples (e.g. targets forprotected areas, fisheries harvest guidelines, water quality, etc.). Yetmeans of objectively determining ecosystem thresholds in relationto environmental and anthropogenic pressures show somepromise of at least identifying regions where target levels are aptto be most effective (Samhouri et al., 2010; McClanahan et al.,2011; Large et al., 2013). The actual control rules used will stillneed to be specified, but many other disciplines (e.g. ecotoxicology,water quality, species-focused fisheries management) have usedsimilar non-linearities to support the establishment of these targetlevels. A related idea advocated by Rockstrom et al. (2009), amongothers, is to define nature’s safe operating space, or boundaries,via objective analysis. Policy-makers can use this information to de-lineate targets within or outside of the natural system boundaries.

The second challenge in defining target values at the ecosystemlevel is that they force trade-offs to the fore. It is relatively easy todevelop ambitious targets for individual indicators. However,


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achievement of individual targets is complicated by interrelation-ships among ecosystem components. Improvements towards onetarget may impede or enhance progress towards another(Samhouri et al., 2011; Fay et al., 2013). Thus, it is critical for IEAscience to outline how establishment of alternative targets for indi-vidual indicators influences the full suite of indicators related toEBM goals (for a related discussion on an ecosystem approach tofisheries, see Rice, 2005).

There are many, non-mutually exclusive ways for IEA teams toillustrate the inter-relations of different target sets. For example,simulation models can describe what is ecologically and socio-economically feasible for the full ecosystem, given a set of targetsfor a particular subset of indicators (e.g. Kaplan and Leonard,2012; Fay et al., 2013). For example, Kaplan and Leonard (2012) illu-strated the direct, indirect, and induced effects of management strat-egies with alternative groundfish targets for the broader ecologicalcommunities of which groundfish are a part and for fisherysectors, industry suppliers, and household spending patterns.Scenarios such as these can be developed into survey instruments,designed to solicit thresholds of acceptability for different ecosystemstates. Similar approaches are commonly used to evaluate normativebeliefs associated with wildlife management actions (Zinn et al.,1998) and outdoor recreational activities (Vaske et al., 1993).With an understanding of what is acceptable across the full ecosys-tem, targets for individual indicators can be deduced. Just as im-portant, these approaches can identify ecosystem states that arecategorically non-desirable by all stakeholders or those that are tech-nically infeasible to achieve.

By specifying indicator targets, IEAs have the potential to create asystem of EBM accountability. Given such a system, it is up to policy-makers to decide on a course of management action that most ap-propriately reflects stakeholder desires for the ecosystem.

5. Establish a formal mechanism(s) for the reviewof IEA scienceA basic step in seeing IEA science used to inform EBM implementa-tion is likely to involve the development and institutionalization of amechanism(s) for peer review. Ideally, managers, stakeholders, andscientists will work with policy-makers to develop a template forthe review of IEA science. Key elements of a review process mayinclude committees tasked with external, independent review ofIEA scientific products, opportunity for public comment, and aclear commitment to ensure the best available science is used toinform management decisions. In the USA, federal fisheries manage-ment practices provide a useful analogue, as they are conducted in ahighly reviewed context. National Standard 2 of the Magnuson-Stevens Sustainable Fisheries Act requires documentation that astock assessment has used best available science. A significantprocess to review information relied upon and produced by stockassessments has thus developed.

The success of the precedent set by US species-focused fisheriesmanagement is encouraging, although from our perspective, theprecise format of an IEA review process is less important than ensur-ing that it occurs. The expectations from an IEA, whatever they maybe, should be specified in a formal terms of reference to clarify sci-entific deliverables and their intended uses. The review processcould lead to standardized outputs tailored for use by EBM decisionmakers. For example, the terms of reference may state that IEAs mustinclude a minimum of five management strategy evaluations asso-ciated with corresponding risk levels for stakeholder-designatedecosystem goals. We urge caution with any type of standardization,

however, as it should not be applied in a way that impedes innov-ation and adaptability. While we do not intend to be prescriptiveregarding what standardized products or the review mechanism(s)should look like, we do feel that the development of these processes isessential to guaranteeing rigor in IEAs and for more effective use ofIEA science in EBM implementation.

6. Serve current management needs, but not at the expenseof more integrative ocean managementIEAs were borne out of the need to provide integrative science toinform comprehensive, ecosystem-based ocean management.While genuine EBM must operate across different ocean usesectors, in the USA, it is clear that this vision is constrained by exist-ing governance structures and is more of an aspiration than thecurrent reality (Rosenberg and Sandifer, 2009). The current realitybears more of a resemblance to many individual actors operatingin a common space and using common pool resources (Crowderet al., 2006), without much accommodation for the joint socialvalue of their decisions (White et al., 2012a). There are some exam-ples available, however, suggesting that accounting for the jointsocial value of single-sector management decisions can lead toimproved outcomes (Hannesson et al., 2009; Allnutt et al., 2012;Levi et al., 2012). The contrast between aspiration and realitycreates a tension between meeting single-sector ocean managementneeds today and making directed progress towards true, cross-sectoral EBM.

In the near-term, as EBM and IEAs gain trust, traction, andmomentum, it is imperative that IEA products support currentnational ocean resource mandates as they are prescribed now. IfIEA products do not provide information relevant to singlesector and single species marine management decisions (e.g. fish-eries, protected species, marine sanctuaries, etc.), then the IEA en-terprise will not be viewed (by some) as useful. However, thisexistential risk need not be a major concern. Because they are syn-thetic “scientific warehouses”, IEAs can be leveraged to augmentsingle-sector management. For instance, IEAs summarize infor-mation about climatic conditions, species abundance, andhuman activities in the ocean, and these data can be packagedto inform the emerging needs of ecosystem-based fisheries man-agement. In fact, “ecosystem considerations” reports and fisheriesecosystems reports that place individual stocks at the centre of theecosystem, and describe climate, prey availability, predator abun-dance, and non-fisheries stressors, have already been requestedand delivered to several Regional Fisheries ManagementCouncils across the USA (e.g. Levin and Wells, 2011; EcoAP,2012; Zador, 2012). Similarly, within National MarineSanctuaries, habitat risk assessments can be used to informspatial planning decisions regarding species of concern such ascorals and sponges (Samhouri et al., 2012).

The easier path forward is to repackage existing scientific pro-ducts and market them as IEAs. However, in the longer term, ifIEAs focus exclusively on the scientific needs of individual oceanuse sectors, they will fail to fulfil the goals of EBM. While potentiallyuseful, a report describing ecosystem considerations for an individ-ual species or an individual sector is not an IEA. Such reports willhelp to justify the existence of an IEA programme in today’s oceanmanagement spheres, but will not help to realize EBM. Individualsectors aim to maximize utility based on their independent goalsfor marine ecosystems (White et al., 2012a), yet at some point, acomprehensive evaluation of resulting trade-offs is needed. Totruly blaze a new trail for a sustainable ocean future, IEA science is


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better served by striving for the anticipatory development of toolsthat can assist in actualizing better, more efficient marine EBM.Only by integrating biophysical and socio-economic informationacross an ecosystem can an IEA—and by extension EBM—help toshape a new reality characterized by coordinated and sustainableocean uses.

7. Provide a venue for EBM decision-making that takesfull advantage of IEA productsAn IEA is in many ways widely marketable; it is designed to providescientific information that can inform more sustainable, efficient,and compatible ocean uses across multiple sectors. Perhaps mostimportantly, an IEA strives to clarify the varied outcomes of alterna-tive management scenarios, by drawing connections between landand sea, nearshore and offshore, fisheries and water quality,energy extraction and coastal recreation, and whale watching andshipping, just to note a few possible contrasts. However, althoughIEAs create a broader perspective for decision makers, more integra-tive ocean management will not just happen.

As is true on the international stage (Gjerde et al., 2008), chal-lenges to coherent management and regulation in the USA representboth a policy implementation gap and a governance gap (Hildreth,2008). Governance processes have been exploring ways for effectivecoordination of cross-sector decision-making ever since the Law ofthe Sea came into force, and many hurdles remain (Rice, 2011).Nonetheless, in the long term, we believe that EBM will requirethe creation of a venue for making decisions about ecosystems, incontrast to decisions about individual species, individual issues,or individual sectors.

Getting there will not be easy. In the USA, IEAs do not yet foldneatly into any one existing governance structure, and the creationof a new one is an enormously complex undertaking. Such adecision-making body would need to be charged with maintaininga cross-sectoral focus, possibly by way of an inter-sectoral set of con-stituent members. The US National Ocean Policy recognizes the im-portance of Regional Ocean Partnerships (ROPs) that haveidentified priorities relevant to their specific regions, and couldprovide a preliminary venue for the delivery of IEA science. TheROPs may serve as an initial template, and could work to leverageexisting legal mandates and apply them within existing single-sectormanagement frameworks, while remaining cognizant of the cross-sectoral trade-offs that deserve consideration.

The formation of such a venue is a step that will facilitate dia-logue, the adjudication of compatible vs. incompatible ocean uses,and the coordination of management decisions. Ideally, it couldserve a facilitative role by tracking actions taken within individualsectors and providing a forum to negotiate trade-offs that influencethe joint social value of an ecosystem with respect to stakeholder-determined goals (White et al., 2012a). Even with due diligence byscientists to see IEAs used in management, EBM is unlikely tobecome a reality without the creation of a group charged with main-taining a broad perspective to coordinate trade-offs across individ-ual ocean-use sectors.

8. Embrace realistic expectations about IEA scienceand its implementationHistorically, there is a time-lag between the development of thescience for a new environmental management approach and theadoption of this information into policy and management. For in-stance, in the USA, extinction risk is one of the main criteria evalu-ated in determining whether a species should be listed under the

Endangered Species Act (ESA) of 1973. Population viability analysisis considered one of the best quantitative methods for evaluating ex-tinction risk, yet it remains infrequently used in endangered speciesrecovery planning (Morris et al., 2002). This reality is natural,expected, and to a limited extent even desirable—unfamiliar scien-tific products require time for vetting and shaping to practical appli-cations. However, lack of familiarity should not be an excuse for alack of reliance on best available science in guiding managementdecisions.

Given the lag time often associated with new management strat-egies, EBM and IEAs could take a generation or more to establish astrong foothold across all sectors of US ocean management. Theapplication of stock assessment science in US fisheries managementprovides a useful corollary. In his book, Smith (1994) elegantlytracked the development of the theory and associated scientificunderpinnings of fish stock recruitment and production dynamics,largely in the middle of last century. He noted that it was at least adecade, or more, before such information was used as the basis forsetting reference points and harvest control rules to manage livingmarine resources. It has taken even longer for the full suite of govern-ance structures and review venues to evolve into something even re-motely familiar to what we now observe in the USA with NationalStandards, Regional Fisheries ManagementCouncils, and related ma-chinery to conduct fishery management. A similar evolution is to beexpected for IEAs as they begin to support EBM.

IEA science is young and necessary, but not sufficient for makingEBM happen. The National Ocean Policy, the National Environ-mental Policy Act, the National Coastal Zone Management Act,and other statutes do provide inroads for implementing facets ofEBM (Keiter, 1998; Abbott and Marchant, 2010; Fox et al., 2013).However, it could be argued that the readiness of IEA products pre-cedes the preparedness of legal and management structures to usethe information. Happily, there are several examples from acrossthe world, suggesting that even complex, international policy-makingorganizations are capable of adapting quickly to new scientific devel-opments and including them in their processes (e.g. IUCN extinctionrisk assessments have used “quantitative population models” since1994; in 1992, Rio Agenda 21 created a policy framework for precau-tionary fisheries management based on stock–recruitment product-ivity dynamics, etc.). Our observation is that these efforts tend to beparticularly effective when top-down actions to implement policyand management are coupled to bottom-up efforts to develop therelevant science.

The future of IEAs for ocean managementin the USA and beyondTo date, IEAs are most useful as syntheses of information and for in-fluencing the way scientists, managers, and policy-makers thinkabout ocean issues. IEAs take the conceptually appealing idea ofEBM, and provide some structure around which to consider theotherwise overwhelming task of identifying, evaluating, and devel-oping management strategies for multiple ecosystem componentsand sectors. These characteristics make them a next-generationtool for ocean and coastal management. Those involved with devel-oping IEAs in the USA are learning by doing, improvising as they go,and subsequently trying to improve the implementation of EBM.The eight tenets introduced in this article (Table 2) representlessons we have learned along the way that may enhance theuptake of integrated scientific assessments in the USA and beyond.


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IEAs face the tall order of meeting managers where theyare today,while at the same time remaining sufficiently visionary that they canshow managers where they could be tomorrow. IEA scientists will bechallenged to remain nimble and responsive to sectoral needs, and atthe same time steadfast and persistent in the pursuit of the largergoal of EBM. In the short term, we expect that the most efficientway forward is to tailor IEAs, so that they are clear where andhow cross-sectoral, coordinated management can increase theprobability of attaining ecosystem goals relative to single-sector,siloed decision-making (White et al., 2012a). If successful, IEAswill lead managers and policy-makers to create the infrastructurecapable of ingesting and applying principles of ecosystem scienceto foster sustainable ocean uses in the future.

The full utility of IEAs in ocean management will not be apparentovernight. We have spent centuries studying the parts and onlyrecent decades in more formally developing the science to informmanagement of the whole (Jackson, 2011). IEAs are science fortomorrow’s oceans, and we urge patience as it matures, and withit, the readiness of ocean managers to use it. The eight tenets out-lined above summarize our perspective on how to carry IEAsfrom the realm of interesting scientific products to the realm ofuseful EBM tools. Common to all of them is a need for patience, per-sistence, political will, funding, and augmented scientific capacity(especially human dimensions capacity). It will also take innov-ation, engagement, and open dialogue to see ecosystem scienceimplemented into effective, ecosystem-based ocean management,but we assert that it can be done using IEAs.

AcknowledgementsThis article was inspired by dialogue at a national IEA programmemeeting in September 2012. We thank all participants of thatmeeting, participants in the National NOAA IEA programme, andIEA partner NOAA ESRL in Boulder, CO, USA, for hosting themeeting. Jake Rice and an anonymous reviewer provided commentsthat vastly improved the article.

ReferencesAbbott, K. W., and Marchant, G. E. 2010. Institutionalizing sustainabil-

ity across the federal government. Sustainability, 2: 1924–1942.

Allnutt, T. F., McClanahan, T. R., Andrefouet, S., Baker, M., Lagabrielle,E., McClennen, C., Rakotomanjaka, A. J. M., et al. 2012. Comparisonof marine spatial planning methods in Madagascar demonstratesvalue of alternative approaches. PLoS ONE, 7: 28–969.

Amir, O., Ariely, D., Cooke, A., Dunning, D., Epley, N., Gneezy, U.,Koszegi, B., et al. 2005. Psychology, behavioral economics, andpublic policy. Marketing Letters, 16: 443–454.

Ariely, D. 2009. Predictably Irrational, Revised and Expanded Edition:the Hidden Forces That Shape Our Decisions. HarperCollinsPublishers, New York, USA.

Arkema, K. K., Guannel, G., Verutes, G., Wood, S. A., Guerry, A.,Ruckelshaus, M., and Kareiva, P. et al. 2013. Coastal habitats shieldpeople and property from sea-level rise and storms. NatureClimate Change, advance online publication. http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate1944.html(last accessed 29 July 2013).

Aucoin, P., and Jarvis, M. D. 2005. Modernizing government account-ability: a framework for reform. Canada School of Public Service,Canada.

Barbier, E. B., Hacker, S. D., Kennedy, C., Koch, E. W., Stier, A. C., andSilliman, B. R. 2011. The value of estuarine and coastal ecosystemservices. Ecological Monographs, 81: 169–193.

Baron, N. 2010. Escape from the Ivory Tower: A Guide to Making YourScience Matter. Island Press, Washington, DC. 272 pp.

Beaudreau, A. H., Levin, P. S., and Norman, K. C. 2011. Using folk tax-onomies to understand stakeholder perceptions for species conser-vation. Conservation Letters, 4: 451–463.

Caddy, J. F. 1999. Fisheries management in the twenty-first century: willnew paradigms apply? Reviews in Fish Biology and Fisheries, 9:1–43.

Crowder, L. B., Osherenko, G., Young, O. R., Airame, S., Norse, E. A.,Baron, N., Day, J. C., et al. 2006. SUSTAINABILITY: resolving mis-matches in US ocean governance. Science, 313: 617–618.

deReynier, Y. L., Levin, P. S., and Shoji, N. L. 2010. Bringing stake-holders, scientists, and managers together through an integratedecosystem assessment process. Marine Policy, 34: 534–540.

Ecosystem Assessment Program. 2009. Ecosystem status report for theNortheast US Continental Shelf Large Marine Ecosystem. NortheastFisheries Science Center Reference Document, 09-11. 34 pp.

Ecosystem Assessment Program. 2012. Ecosystem status report forthe Northeast US Continental Shelf Large Marine Ecosystem—2011. Northeast Fisheries Science Center Reference Document,12-07. 32 pp.

European Commission. 2008. Directive 2008/56/EC of the EuropeanParliament and of the Council of 17 June 2008 establishing a frame-work for Community actions in the field of marine environmentalpolicy (Marine Strategy Framework Directive). Official Journal ofthe European Communities, L164/19 25.06.2008.

Evans, K. E., and Klinger, T. 2008. Obstacles to bottom-up implementa-tion of marine ecosystem management. Conservation Biology, 22:1135–1143.

Fay, G., Large, S. I., Link, J. S., and Gamble, R. J. 2013. Testing systemicfishing responses with ecological indicators: an MSE approach.Ecological Modelling, 265: 45–55.

Fletcher, S. 2007. Converting science to policy through stakeholder in-volvement: an analysis of the European Marine Strategy Directive.Marine Pollution Bulletin, 54: 1881–1886.

Fluharty, D., Abbott, M., Davis, R., Donahue, M., Madsen, S., Quinn, T.,and Rice, J. 2006. Evolving an ecosystem approach to science andmanagement throught NOAA and its partners. Available fromwww.sab.noaa.gov/reports/eETT_Final_1006.pdf (last accessed 14March 2013).

Foley, M. M., Armsby, M. H., Prahler, E. E., Caldwell, M. R., Erickson,A. L., Kittinger, J. N., Crowder, L. B., et al. in press. Improvingocean management through the use of ecological principles and inte-grated ecosystem assessments. Bioscience, 63: 619–631.

Fox, E., Miller-Henson, M., Ugoretz, J., Weber, M., Gleason, M., Kirlin,J., Caldwell, M., et al. 2013. Enabling conditions to support marineprotected area network planning: Califronia’s Marine LifeProtection Act Initiative as a case study. Ocean and CoastalManagement, 74: 14–23.


Garibaldi, A., and Turner, N. 2004. Cultural keystone species: implica-tions for ecological conservation and restoration. Ecology andSociety, 9: 1.

Gjerde, K., Dotinga, H., Hart, S., Molenaar, E., Rayfuse, R., and Warner,R. 2008. Regulatory and Governance Gaps in the InternationalRegime for the Conservation and Sustainable Use of MarineBiodiversity in Areas beyond National Jurisdiction. IUCN, Gland,Switzerland. 70 pp.

Gleason, M., McCreary, S., Miller-Henson, M., Ugoretz, J., Fox, E.,Merrifield, M., McClintock, W., et al. 2010. Science-based andstakeholder-driven marine protected area network planning: a suc-cessful case study from north central California. Ocean & CoastalManagement, 53: 52–68.

Guerry, A. D., Ruckelshaus, M. H., Arkema, K. K., Bernhardt, J. R.,Guannel, G., Kim, C-K., Marsik, M., et al. 2012. Modeling benefitsfrom nature: using ecosystem services to inform coastal and


by How

ard Brow

man on July 2, 2014


Dow

nloaded from

http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate1944.html






www.sab.noaa.gov/reports/eETT_Final_1006.pdf






marine spatial planning. International Journal of BiodiversityScience, Ecosystem Services & Management, 8: 107–121.

Gutierrez, N. L., Hilborn, R., and Defeo, O. 2011. Leadership, socialcapital and incentives promote successful fisheries. Nature,advance online publication. http://dx.doi.org/10.1038/nature09689 http://www.nature.com/nature/journal/vaop/ncurrent/abs/nature09689.html#supplementary-information.


Halpern, B. S., Walbridge, S., Selkoe, K. A., Kappel, C. V., Micheli, F.,D’Agrosa, C., Bruno, J. F., et al. 2008. A global map of humanimpact on marine ecosystems. Science, 319: 948–952.

Hannesson, R., Herrick, S., Jr, and Field, J. 2009. Ecological and eco-nomic considerations in the conservation and management of thePacific sardine (Sardinops sagax). Canadian Journal of Fisheriesand Aquatic Sciences, 66: 859–868.

Hilborn, R., Micheli, F., and De Leo, G. A. 2006. Integrating marine pro-tected areas with catch regulation. Canadian Journal of Fisheries andAquatic Sciences, 63: 642–649.

Hildreth, R. G. 2008. Place-based ocean management: emerging US lawand practice. Ocean & Coastal Management, 51: 659–670.

Hipfner, J. M., Blight, L. K., Lowe, R. W., Wilhelm, S. I., Roberston, G. J.,Barrett, R. T., Anker-Nilssen, T., et al. 2012. Unintended conse-quences: how the recovery of sea eagle Haliaeetus spp. populationsin the northern hemisphere is affecting seabirds. MarineOrnithology, 40: 39–52.

ICES. 2011. Report of the Working Group on Ecosystem Assessment ofWestern European Shelf Seas (WGEAWESS). 3–6 May 2011,Nantes, France. 175 pp.

ICES. 2013a. Report of the Working Group on Integrated Assessmentsof the North Sea (WGINOSE). 11–15 February 2013, Lisbon,Portugal. 76 pp.

ICES. 2013b. Report of the Working Group on the ICES ACOM/SCICOM Workshop on Ecosystem Overviews (WKECOVER).7–11 January 2013, ICES HQ, Copenhagen, Denmark.

ICES. 2013c. Report of the Workshop on Benchmarking IntegratedEcosystem Assessments (WKBEMIA). 27–29 November 2012,ICES Headquarters, Copenhagen, Denmark. 27 pp.

Jackson, J. B. C. 2011. Ecological extinction and evolution in the bravenew ocean. Proceedings of the National Academy of Sciences ofthe United States of America, 105: 11458–11465.

James, C. A., Kershner, J., Samhouri, J. F., O’Neill, S., and Levin, P. S.2012. A methodology for evaluating and ranking water quantityindicators in support of ecosystem-based management. Environ-mental Management, 49: 703–719.

Jennings, S. 2009. The role of marine protected areas in environmentalmanagement. ICES Journal of Marine Science, 66: 16–21.

Johnson, E. J., and Goldstein, D. 2003. Do Defaults Save Lives? Science,302: 1338–1339.

Kaplan, I. C., and Leonard, J. 2012. From krill to convenience stores:forecasting the economic and ecological effects of fisheries. MarinePolicy, 36: 947–954.

Kareiva, P., and Marvier, M. A. 2011. Conservation Science. Roberts andCompany, Greenwood Village, CO.

Katsanevakis, S., Stelzenmuller, V., South, A., Sørensen, T. K., Jones,P. J. S., Kerr, S., Badalamenti, F., et al. 2011. Ecosystem-basedmarine spatial management: review of concepts, policies, tools,and critical issues. Ocean & Coastal Management, 54: 807–820.

Keiter, R. B. 1998. Ecosystems and the law: toward an integrated ap-proach. Ecological Applications, 8: 332–341.

Kershner, J., Samhouri, J. F., James, C. A., and Levin, P. S. 2011. Selectingindicator portfolios for marine species and food webs: a Puget Soundcase study. PLoS ONE, 6: e25–248.

Kittinger, J. N., Finkbeiner, E. M., Glazier, E. W., and Crowder, L. B.2012. Human dimensions of coral reef social-ecological systems.Ecology and Society, 17: 17.

Lægreid, P., Roness, P. G., and Rubecksen, K. 2006. Performance man-agement in practice: the Norwegian Way. Financial Accountability &Management, 22: 251–270.

Large, S. I., Fay, G., Friedland, K. D., and Link, J. S. 2013. Defining trendsand thresholds in responses of ecological indicators to fishing andenvironmental pressures. ICES Journal of Marine Science, 70:757–767.

Levi, T., Darimont, C. T., MacDuffee, M., Mangel, M., Paquet, P., andWilmers, C. C. 2012. Using grizzly bears to assess harvest-ecosystemtradeoffs in salmon fisheries. PLoS Biology, 10: e1001303.

Levin, P. S., Damon, M., and Samhouri, J. F. 2010. Developing meaning-ful marine ecosystem indicators in the face of a changing climate.Stanford Journal of Law, Science, & Policy, 1: 36–48.

Levin, P. S., Fogarty, M. J., Matlock, G. C., and Ernst, M. 2008. Integratedecosystem assessments. US Dept.of Commerce, NOAATech.Memo.,NMFS-NWFSC-92. 20 pp.

Levin, P. S., Fogarty, M. J., Murawski, S. A., and Fluharty, D. 2009.Integrated ecosystem assessments: developing the scientific basisfor ecosystem-based management of the ocean. PLoS Biology, 7:e14. doi:10.1371/journal.pbio.1000014

Levin, P. S., and Wells, B. 2011. Discussion document: development ofan annual report on conditions in the California Current ecosystem.http://www.pcouncil.org.

Levin, S. A., and Lubchenco, J. 2008. Resilience, robustness, and marineecosystem-based management. BioScience, 58: 27–32.

Loring, P. A. 2013. Alternative perspectives on the sustainability ofAlaska’s commercial fisheries. Conservation Biology, 27: 55–63.

Link, J. S. 2005. Translation of ecosystem indicators into decision cri-teria. ICES Journal of Marine Science, 62: 569–576.

Link, J., and Brodziak, J. (Eds.). 2002. Report on the status of the NE USContinental Shelf Ecosystem. NEFSC Ecosystem Status WorkingGroup. Northeast Fisheries Science Center Ref. Doc. 02-11. 245 pp.

Manski, C. F. 2013. Diagnostic testing and treatment under ambiguity:using decision analysis to inform clinical practice. Proceedings of theNational Academy of Sciences of the United States of America, 110:2064–2069.

McClanahan, T. R., Graham, N. A. J., MacNeil, M. A., Muthiga, N. A.,Cinner, J. E., Bruggemann, J. H., and Wilson, S. K. 2011. Criticalthresholds and tangible targets for ecosystem-based managementof coral reef fisheries. Proceedings of the National Academy ofSciences of the United States of America, 108: 17230–17233.

McLeod, K. L., Lubchenco, J., Palumbi, S. R., and Rosenberg, A. A. 2005.Scientific consensus statement on marine ecosystem-based manage-ment. Signed by 221 academic scientists and policy experts with rele-vant expertise and published by the Communication Partnership forScience and the Sea at http://compassonline.org/?q=EBM.

McLeod, K. L., and Leslie, H. 2009. Ecosystem-based Management forthe Oceans. Island Press, Washington, DC.


Mollmann, C. In press. Implementing ecosystem-based fisheries man-agement—from single-species to integrated ecosystem assessmentand advice for Baltic Sea fish stocks. ICES Journal of Marine Science.

Morris, W. F., Bloch, P. L., Hudgens, B. R., Moyle, L. C., andStinchcombe, J. R. 2002. Population viability analysis in endangeredspecies recovery plans: past use and future improvements. EcologicalApplications, 12: 708–712.

Obama, B. 2010. Executive Order 13547. Stewardship of the ocean, ourcoasts, and the Great Lakes. Executive Order 13547.

Olson, R. 2009. Don’t Be Such a Scientist: Talking Substance in an Age ofStyle. Island Press, Washington, DC.

Otley, D. 1999. Performance management: a framework for manage-ment control systems research. Management Accounting Research,10: 363–382.

POC. 2003. America’s living ocean: charting a course for sea change. Areport to the nation. Pew Trusts, Washington, DC.


by How

ard Brow

man on July 2, 2014


Dow

nloaded from

http://dx.doi.org/10.1038/nature09689







http://www.nature.com/nature/journal/vaop/ncurrent/abs/nature09689.html#supplementary-information







http://www.pcouncil.org





http://compassonline.org/?q=EBM




Pollnac, R., Christie, P., Cinner, J. E., Dalton, T., Daw, T. M., Forrester,G. E., Graham, N. A. J., et al. 2010. Marine reserves as linkedsocial-ecological systems. Proceedings of the National Academy ofSciences of the United States of America, 107: 18262–18265.

PSP. 2009. Public Involvement and outreach summary. Puget SoundPartnership. http://psp.wa.gov/aa_action_agenda.php.

Rice, J. 2005. Will an ecosystem approach mitigate the factors of unsus-tainability? In International Workshop on the Implementation ofthe International Fisheries Instruments and Factors of Unsustain-ability and Overexploitation in Fisheries. Siem Reap, Cambodia,13–16 September 2004. Ed. by J. Swan, and D. Greboval. FAO,Rome, Italy. http://www.fao.org/docrep/009/a0312e/A0312E12.htm#ch2.10.

Rice, J. C. 2011. Achieving coherent policies for conservation and sus-tainable use of marine ecosystems. Conservation Biology, 25:1065–1068.

Rice, J. C., and Rochet, M. J. 2005. A framework for selecting a suite ofindicators for fisheries management. ICES Journal of MarineScience, 62: 516–527.

Rockstrom, J., Steffen, W., Noone, K., Persson, A., Chapin, F. S. I.,Lambin, E., Lenton, T. M., et al. 2009. Planetary boundaries: explor-ing the safe operating space for humanity. Ecology and Society, 14.http://www.ecologyandsociety.org/vol14/iss2/art32/.

Rosenberg, A. A., Mooney-Seus, M. L., Kiessling, I., Mogensen, C. B.,O’Boyle, R., and Peacey, J. 2009. Lessons from national-level imple-mentation across the world. In Ecosystem-Based Management forthe Oceans, pp. 294–313. Ed. by K. McLeod, and H. Leslie. IslandPress, Washington, DC.

Rosenberg, A. A., and Sandifer, P. A. 2009. What do managers need? InEcosystem-based management for the oceans, pp. 13–30. Ed. byK. McLeod and H. Leslie. Island Press, Washington, DC.

Ruckelshaus, M., and McClure, M. 2007. Sound science: synthesizingecological and socioeconomic information about the PugetSound ecosystem. US Dept. of Commerce, National Oceanic andAtmospheric Administration (NMFS), Northwest FisheriesScience Center, Seattle, WA, USA. 93 pp.

Sainsbury, K. J., Punt, A. E., and Smith, A. D. M. 2000. Design of oper-ational management strategies for achieving fishery ecosystem objec-tives. ICES Journal of Marine Science, 57: 731–741.

Samhouri, J. F. 2012. Risk assessment for ecological integrity. InIntegrated Ecosystem Assessment of the California Current. Ed. byP. S. Levin, and B. Wells. U.S. Dept. of Commerce, NMFS-NWFSC, Seattle.

Samhouri, J. F., Lester, S. E., Selig, E. R., Halpern, B. S., Fogarty, M. J.,Longo, C., and McLeod, K. L. 2012. Sea sick? Setting targets toassess ocean health and ecosystem services. Ecosphere, 3: art41.

Samhouri, J. F., Levin, P. S., and Ainsworth, C. H. 2010. Identifyingthresholds for ecosystem-based management. PLoS ONE, 5: e8907.

Samhouri, J. F., Levin, P. S., James, C. A., Kershner, J., and Williams, G.2011. Using existing scientific capacity to set targets for ecosystem-based management: a Puget Sound case study. Marine Policy, 35:508–518.

Shin, Y-J., Bundy, A., Shannon, L. J., Simier, M., Coll, M., Fulton, E. A.,Link, J. S., et al. 2010a. Can simple be useful and reliable? Using eco-logical indicators for representing and comparing the states ofmarine ecosystems. ICES Journal of Marine Science, 67: 717–731.

Shin, Y-J., Shannon, L. J., Bundy, A., Coll, M., Aydin, K., Bez, N.,Blanchard, J. L., et al. 2010b. Using indicators for evaluating, com-paring, and communicating the ecological status of exploitedmarine ecosystems. 2. Setting the scene. ICES Journal of MarineScience, 67: 692–716.


Smith, T. D. 1994. Scaling Fisheries: The Science of Measuring theEffects of Fishing, 1855–1955. Cambridge University Press,New York.

Tallis, H. M., Levin, P. S., Ruckelshaus, M., Lester, S. E., McLeod, K. L.,Fluharty, D. L., and Halpern, B. S. 2010. The many faces ofecosystem-based management: making the process work today inreal places. Marine Policy, 34: 340–348.

Tallis, H.T., Ricketts, T., Guerry, A.D., Wood, S. A., Sharp, R., Nelson, E.,Ennaanay, D., et al. 2013. InVEST 2.5.5 User’s Guide. The NaturalCapital Project, Stanford.

Thaler, R. H., and Sunstein, C. R. 2003. Libertarian paternalism.American Economic Review, 93: 175–179.

Turner, N. J. 2003. The ethnobotany of edible seaweed (Porphyra abbot-tae and related species; Rhodophyta: Bangiales) and its use by FirstNations on the Pacific Coast of Canada. Canadian Journal ofBotany, 81: 283–293.

Turner, N. J., Gregory, R., Brooks, C., Failing, L., and Satterfield, T. 2008.From invisibility to transparency: identifying the implications.Ecology and Society, 13: 7.

UNEP and IOC-UNESCO. 2009. An Assessment of Assessments,Findings of the Group of Experts. Start-up Phase of a RegularProcess for Global Reporting and Assessment of the State of theMarine Environment Including Socio-economic Aspects.

USCOP. 2004. An ocean blueprint for the twenty-first century. UnitedStates Commission on Ocean Policy, Washington, DC.

USNOC. 2013. National ocean policy implementation plan. UnitedStates National Ocean Council, Washington, DC.

Vaske, J., Donnelly, M., and Shelby, B. 1993. Establishing managementstandards: selected examples of the normative approach.Environmental Management, 17: 629–643.

Watson, R. T. 2005. Turning science into policy: challenges and experi-ences from the science–policy interface. Philosophical Transactionsof the Royal Society B: Biological Sciences, 360: 471–477.

White, C., Costello, C., Kendall, B. E., and Brown, C. J. 2012a. The valueof coordinated management of interacting ecosystem services.Ecology Letters, 15: 509–519.

White, C., Halpern, B. S., and Kappel, C. V. 2012b. Ecosystem servicetradeoff analysis reveals the value of marine spatial planning for mul-tiple ocean uses. Proceedings of the National Academy of Sciences ofthe United States of America, 109: 4696–4701.

Zador, S. (Ed.). 2012. Ecosystem Considerations 2012. North PacificFisheries Management Council, Anchorage, AK. 230 pp.

Zinn, H. C., Manfredo, M. J., Vaske, J. J., and Wittmann, K. 1998. Usingnormative beliefs to determine the acceptability of wildlife manage-ment actions. Society & Natural Resources, 11: 649–662.

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