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D. Pauly and T.J. PitcherD. Pauly and T.J. PitcherD. Pauly and T.J. PitcherD. Pauly and T.J. Pitcher

Fisheries Centre, University of British Columbia,Vancouver, Canada, V6T 1Z4

AAAABSTRACTBSTRACTBSTRACTBSTRACT

The aim of the Sea Around Us Project is to quantify,in ecological and economic terms, the impact offisheries on the marine ecosystems of the NorthAtlantic, and to evaluate the costs and benefits ofvarious scenarios of mitigation, such as status quo,rebuilding of depleted resources andimplementation of closed areas. Dealing with theseissues requires a methodological package related to,but different from, that typically used in fisheriesmanagement, notably because of its ecosystem focusand the much larger temporal and spatial scales,relative to standard fisheries assessments. Thispaper summarizes the methodology deployed by theproject by introducing a suite of papers in which itsrationale and operational details are provided.

First, we review the relationships between scale andmethodology choices in marine science. Then, theprinciple modules of the Sea Around Us Projectmethodology are described as follows:

1) The North Atlantic as study area, where wereport a new ecosystem classification schemethat is compatible hierarchically with previouswork and with all statistical divisions;

2) North Atlantic fisheries catches in time andspace, where we present the project’s catch andeffort database, discuss the problems inestimating total extractions, and outlinemethods used to overcome them;

3) Fish distribution transects, where the biologyand migrations of key commercial NorthAtlantic species are used to link catches byshallow-water and offshore fisheries;

4) Bio-economic analyses of fisheries sectors,where the effect of competition between smalland large –scale fisheries is quantified using amulti-species, multi-gear yield per recruit

model and the combination of effort producinga Nash equilibrium is identified;

5) Ecosystem modeling, discussing the use ofECOPATH with ECOSIM and ECOSPACE torepresent present and past North Atlanticecosystems with their embedded fisheries, toevaluate ecosystem status, and to simulate likelyresponse to change;

6) Evaluating alternative ecosystem-basedmanagement regimes to quantify the benefits ofdifferent ecosystem-based managementscenarios;

7) Energy consumption and the ecologicalfootprint of North Atlantic fisheries, to contrastthe energy incorporated in landed fishes to thatrequired to catch them;

8) Rapid interdisciplinary appraisal of fisheriesstatus and compliance analyses using RAPFISH,to compare and characterize North Atlanticfisheries in terms of their sustainability (inecological economic technological and socialfields), analysis of their ethical status, and toscore their compliance with the FAO Code ofConduct for Responsible Fisheries, togetherwith the compliance of North Atlantic countriesvis-à-vis their internationally agreedcommitments.

9) Mapping the fate of fisheries landings from theNorth Atlantic, to identify possible pressurepoints for intervention by fish productconsumers;

We present a diagram expressing the articulation ofthe various methodological components listedabove. The synthesis to emerge from integrating theresults of these modules may contain manysurprises, both in terms of the ecological damageand economic waste presently generated by theNorth Atlantic fisheries, and in clarifying theforegone benefits that could be regained, were theseeconomic and ecological issues to be addressed.

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IIIINTRODUCTIONNTRODUCTIONNTRODUCTIONNTRODUCTION

The task of the Sea Around Us Project, funded bythe Pew Charitable Trusts, Philadelphia, andexecuted at the Fisheries Centre, University ofBritish Columbia, Vancouver, is to provide asynthesis of the impacts of fisheries on marineecosystems of the North Atlantic. More precisely,the questions to be answered are:

1. What are the total fishery catches from theecosystems? Total fishery catches includesboth reported and unreported landings anddiscards at sea.

2. What are the biological impacts of thesewithdrawals of biomass for the remainingliving components of the ecosystem?

3. What would be the likely biological andeconomic impacts of a continuation ofcurrent fishing trends (i.e., a maintenanceof the status quo)?

4. What were former states of this ecosystemlike before the expansion of large-scalecommercial fisheries?

5. How does the present-day ecosystemevaluate on a scale from ‘healthy’ to‘unhealthy’?

6. What specific policy changes andmanagement measures should beimplemented:

(a) to avoid continued worsening of thepresent situation?(b) to improve ecosystem ‘health’, asdefined in (5)?

Each of these questions, though straightforward-looking at first, leads to further questions, manyseemingly without answers. Nevertheless, theproject staff has developed a ‘methodology package’for providing the best possible answers to thesequestions. This package differs from that normallyused to assess local fish populations and localfisheries in that our methods are scalable to theentire North Atlantic basin, and indeed, eventually,to the world ocean. This package therefore,emphasizes aspects of fisheries and other marinescience that are usually given short thrift in localstudies. Conversely, we do not attempt to assess theexploitations status of exploited single-species fishpopulations. As we shall attempt to demonstrate,methods concerned with local or single-speciesstudies and those in our methodology packagesupport and complement each other.

Before we present the various elements of thismethodology package, we shall briefly contrast two

views of (marine) sciences, and provide reason why,given the present, much depleted state of NorthAtlantic fish populations, and the ruinous state ofthe fisheries depending thereon, we have chosen toidentify with one of these views.

Two views of (marine) sciencesTwo views of (marine) sciencesTwo views of (marine) sciencesTwo views of (marine) sciences

Our reading of the history of science in general, andmarine science in particular suggests two basic waythat advances are made:

1. Through what, for lack of a better term, weshall call Smart New Tricks (SNT), or

2. Through assimilation of large sets of pre-existing data, and, based thereon, throughthe creation of New Mental Maps (NMM).

Examples of SNT in fisheries were the invention ofVirtual Population Analysis (usually attributed toGulland, 1965), or of Bayesian risk analysis(reviewed by Punt and Hilborn 1997). SNT usuallyresolve one problem (often one that was not evenperceived as such), and do this in a new way that isoften regarded as ‘neat’ or ‘elegant’. On the negativeside, we should add that SNT can also be seen as‘techno-fixes’, resolving the technological aspect of aproblem but usually leaving wide open theunderlying process that generated the problem. Inthe case of the two examples above, the problemswere how to estimate fishing mortality, and how topresent management options to politicians,respectively. Their downside as techno-fixes wasthat the former quickly bred a misplaced confidencein its outputs (see Walters and Maguire 1996,Pitcher and Hart 1982), whilst the latter, eventhough labelling them as such, provided ultra-riskyoptions to industry and politicians (Mace 2000),decision-takers who, by the nature of theirprofessions, tend to prefer risky options to saferones.

The alternative to the SNT, the NMM cansometimes build on one or several small SNT. Theimportant feature of the NMM, however, is that itinvolves the assimilation (or meta-analysis) of large(sometimes enormous) data sets. Our best exampleis the realization by U.S. Navy Commander MathewF. Maury, in the mid-1800s, that marinerscollectively held in their head enough informationon currents and winds (e.g., in the North Atlantic),to generate maps which would improve navigation,i.e., shorten the route between Europe and theAmericas (Maury 1963).

Maury thus promised cooperating mariners copiesof his planned maps, should they agree tocontribute their individual knowledge on most

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favorable routes. These data (and depth soundingshe also gathered) enabled him not only to produce,after lots of painstaking work, the best navigationmaps then in existence (‘applied’ science), but alsoto be the first to perceive the existence of mid-Atlantic ridge (‘basic’ science). Moreover, single-handedly created the mode of interactions betweenmariners and naval offices that still prevails, andwhich has enabled the emergence of modernphysical oceanography as a discipline wherein dataare shared. Hence the existence and collaboration,even during the coldest years of the Cold War, ofData Center A (in Washington, D.C.) and B (inMoscow). This, incidentally, is also the reason whyoceanographic data can be used to verify theoccurrence of global changes: the data are availablesince the late 19th Century.

Which brings us to marine biology and fisheries.Here, like Maury since the end of the 19th Century,we inherit a mountain of data on the variousorganisms, from phyto-plankton (net samples, C14

measurements, satellite oceanography) andzooplankton (Hensen nets samples, Hardy samplerstime series), trawl and benthic surveys, catch timeseries, landing and price data, etc. – an enormous,ever-growing data set. Yet we are very often told byfisheries scientists and others that there are “nodata” upon which to make inferences about the stateof North Atlantic ecosystems, and on remedialactions regarding their depletion, and on the futureof the commercial species therein. We are told thatwhat we need is ‘new, better data’, or indeed that weshould hope for a SNT to somehow resolve theproblem(s) that led to the mountain of data beingaccumulated in the first place.

Yet major NMM are based on assimilation ofexisting data, even in areas with which all arefamiliar. Thus, for example, it is relatively wellknown that the report which convinced the USauthorities, and the US public, and later others inother parts of the world, that cigarettes are bad forsmokers did not present a SNT. Rather, it was meta-analysis of a large number of small studies, eachperhaps not very convincing by itself, but jointlyproviding incontrovertible evidence. Further, morerecent meta-analyses added the effects of second-hand smoke, now leading to widespread restraintson smoking in enclosed spaces, both public andprivate. What changed here is the position ofcigarettes in peoples’ mental maps.

In a similar way, Rachel Carson’s Silent Springassimilated into a coherent whole a large number ofpreviously unconnected observations, and thiscreated a NMM wherein the location of DDT andother pesticides was radically different from itprevious position (Lear 1997).

The Convention of Biological Diversity (CBD)requires that all the countries of the world makeinventories of their biodiversity, and take measuresto protect it. Where does small country X get aglobal reference list of the plants and animals thathave so far been described (and of which the speciesin country X must be a subset)? Such a list still doesnot exist, despite the straightforward nature of thescience that would be required (just as for Maury’smaps).

In the late 1980s, work on a large database intendedto provide a rigorous nomenclature andclassification for all the fishes in the world, and keyfacts for each of these 25,000 species. Ten yearslater, the job is largely done (see www.fishbase.org):the countries of the developing world now thus havea tool that enables them to get started on meetingtheir obligations vis-à-vis the CBD, at leastconcerning the fishes (presently, the Internetversion of FishBase gets over half a million visits permonth, several orders of magnitude more than forany comparable product). Moreover, the databasethus created, in a collaborative mode resemblingMaury’s, has many elements serving as model forSpecies 2000, which aims at producing a list of allorganisms so far described (seewww.species2000.org).

An excellent example of a meta-analysis is the seriesof contributions by R.A. Myers and collaborators onthe stock-recruitment relationships of fishes, basedon their vast compilation of time series of publishedstock and recruitment time series. This workrecently culminated in Myers et al. (1999) and hasthe potential to produce massive changes in themental maps of fisheries biologists. Myers’ studyshows conclusively that the common feature ofstock-recruitment relationships across species (anarrow range of slopes near the origin, indicative ofa narrow range of reproductive potentials ofindividual female fish) was not seen previouslybecause nobody bothered to standardize, over alarge number of cases, the scales of plots ofrecruitment versus parent stocks. Rather, earlierauthors emphasized the ‘uncertain’, even ‘chaotic’nature of stock-recruitment relationships, entirelymissing what turns out to be highly predictablerelationships. It is as if Maury had complainedabout the ‘complex’ nature of mariners’ knowledge,rather than assemble his maps.

These items are examples of NMM, major pieces ofwork that make available to practitioners tools thatassimilate much of the work previously done in agiven area. In each case data was already availablein principle, but was not assimilated within arigorous framework. So we can ask: why are there

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not more of these collaborative exercises in marinebiology and fisheries, given their potential impact?

One reason might be that, in the context ofgovernment-funded research, such work can bedone only after a consensus has emerged about theresearch to be conducted, the idea being that suchNMM should emerge from the bottom up. Theproblem here is the tendency for collective andcommittee-led research to reduce new sets of ideas,‘visions‘ as it were, to a least common denominator:voluminously documented research proposalsfavoring safe science over risky new approaches.

The methodology package we have assembled toanswer the questions above, related to the impactsof fisheries on the ecosystems of the North Atlantic,thus reflect our vision, not yet widely shared, thatsuch questions can be tackled at basin-wide scales.The methodology is devoted to assimilating, inrigorous, quantitative terms, a large amount ofprevious work and to involving multiplecollaborative arrangements. However, we shallmaintain standards such that coherent productsemerge.

Such approach, from the top down is, we believe,the only way products can emerge which are usefulat scales above that at which marine and fisheriesbiologists typically operate, usually that defined bythe boat of a university research station, or by thecommercial vessels used in a fishery under study.

The North Atlantic as Study AreaThe North Atlantic as Study AreaThe North Atlantic as Study AreaThe North Atlantic as Study Area

As defined by the Sea Around Us Project, the NorthAtlantic includes all marine waters North of Miami,Florida in the West and North of Cape Bojador,Morocco in the East. This area is identified in Fig. 1,which also identifies the Biogeochemical Provinces(BGCP), which are compatible with the LargeMarine Ecosystems (Sherman and Duda 1999) ofthe North Atlantic (see below). These articulate, atdifferent levels, the ecosystem classification adoptedby the project (see Pauly et al. 2000). Note that thisdefinition excludes the Mediterranean from thescope of the project. Moreover, for variouspragmatic reasons, we also exclude the Balticproper, though not its connections with the NorthSea, the Kattegat and Skagerrak. Except for aSouthern border a bit further south, and theomission of the Baltic, our definition of the NorthAtlantic thus overlaps with the area jointly coveredby FAO areas 21 (Eastern North Atlantic) and 27(Western North Atlantic), themselves largelyoverlapping with the area for which ICES, andNAFO, respectively, are responsible.The questions posed of the Sea Around Us Project,referring to the ecosystem impact of fisheries,

require that we identify the ecosystems of the NorthAtlantic. In the spirit of the foregoing, whichemphasizes the need to assimilate large amount ofpre-existing data, we have adopted, for the SeaAround Us Project, the large Marine Ecosystem(LME) concept and definitions developed in the last15 years by K. Sherman and co-workers, andrecently summarized in Sherman and Duda (1999).

This decision was facilitated by the discovery thatthe LMEs so far defined can be easily mapped onto,and re-expressed as components of coastalBiogeochemical Provinces (BCGP), the larger

Figure 1.Figure 1.Figure 1.Figure 1. (A) ( top) Map of North Atlantic showing thatSea Around Us Project area (southern boundary is thickhorizontal line) overlaps four major FAO statisticalareas. (B) (bottom) The nine major biogeochemicalprovinces in the Sea Around Us Project area.ARCT=Atlantic Arctic Province (in two regions); NECS= Northeast Atlantic Shelves Province; SARC = AtlanticSubarctic Province; NADR = North Atlantic DriftProvince; NASE = North Atlantic Subtropical GyralProvince (East); NASW = North Atlantic SubtropicalGyral Province (West); GFST = Gulf Stream Province;CHSB = Chesapeake Bay Province; MEDI =Mediterranean. For further details of how these zonesare conflated with Sherman’s Large Marine Ecosystems,ICES and NAFO management areas, and USA andCanadian statistical zones, using a half-degree squareSea Around Us database, see Pauly et al. (2000).

A

B

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ecosystem units proposed by Longhurst (1995,1998) to provide a stratification of the world ocean.

Indeed, this redefinition of LME provides the lowerrungs of a hierarchy ranging from ‘biomes’, i.e.,large, circum-terrestrial entities with similar climate(Polar; Westerlies; Trades; and Coastal Boundary)to 56 BGCP and about 80 LME (see Pauly et al.2000). Moreover, the LME themselves can befurther subdivided, especially for modelingpurposes (see Pauly et al. 2000 and Christensen andWalters 2000).

This structure for ecosystem classification,proposed as a consensus of several research groupsworking on this type of issue (Pauly et al. 2000),appears well suited for the stratification required forbasin-level estimates of various states and rates andto address the issue of variability of scalesemphasized by Levin (1990). Moreover, using thisscheme, fisheries may be mapped onto theecological entities, the ecosystems, that generate thefish caught, and not the artificial boundaries ofcountries, EEZs, and jurisdictions, our next topic.

NNNNORTH ORTH ORTH ORTH AAAATLANTIC TLANTIC TLANTIC TLANTIC FFFFISHERIES ISHERIES ISHERIES ISHERIES CCCCATCHES IN ATCHES IN ATCHES IN ATCHES IN TTTTIME ANDIME ANDIME ANDIME AND

SSSSPACEPACEPACEPACE

Accurate time series of fisheries catches, hereunderstood as all animals killed by fishing gears,and not only those that are landed, are at the heartof the Sea Around Us Project. However, contrary towhat may be believed, assembling such time seriesfor the North Atlantic is not a matter of setting up anew program for sampling primary data in thecountries bordering the North Atlantic. Rather, it islargely a matter of identifying, for each of thesecountries, those elements (if any) that prevent theirofficial catch statistics from reflecting the trueeffects of fishing gears.In many cases, even landings are incompletebecause the data collecting entity is not mandated tocollect data from certain types of gear (often small-scale gear, or sport fishers), notwithstanding thepotential impacts of a large number of such gear.

In other cases, obvious sources of biases, notablymassive discarding of by-catch are not considered incompiling catch statistics. This also applies to illegalcatches, even when, as occur in some fisheries, allthose involved – including government scientists -know of their existence, and even their magnitude.

Watson et al. (2000) review these and relatedissues, and thereby present the database structureand methodology we shall use to obtain, for theNorth Atlantic, figures that will better reflect truecatches (i.e., all withdrawals) than those presentlyavailable, illustrated by an example of cooperation

with a government agency. Moreover, Pitcher andWatson (2000) explore this issue further, byestimating percentage in each category ofunreported catches, following in time the changes inlegal instruments, including the Law of the Sea, thatprovide disincentives to accurate reporting. Theanalysis is presented such that it can be easilyrefined by further work.

However, even the first round of estimates resultingfrom these considerations should contribute tomaking our catch figures more realistic. Thiscontrasts with the assumption of zero in thosecategories, the common default position of publicagencies, and one that is neither useful noracceptable to the public itself.

We are well aware that the data set thus assembledwill remain fragmentary and incomplete, and thatfar better data sets will exist on local scales. At theLME and basin-wide scale, however, we expect thatour data set will be the most accurate, in that allsources of fishing mortality will be accounted for.

Pauly et al. (2000) present the method by which theglobal FAO fisheries catch data set will be re-expressed on a global LME map. The keycomponent of the method proposed therein is that itwill proceed ‘by subtraction’, i.e., by first assigningfishes with clear affinities to depth ranges, habitattypes and/or certain LME, e.g. the anchovetaEngraulis ringens to the inshore part of theHumboldt Current LME, or the neritic fishesreported for Bangladesh to the shelf component ofthe Bay of Bengal LME, etc., each time subtractingthe assigned fish groups from the database. Severalrounds of subtraction will lead to small amounts ofunallocated landings, pertaining mainly to fishlanded in countries with distant water fleets (orproviding flags of convenience to such fleets).Assigning the residual landings to the LME wherethese fleets are known to occur (see Bonfil et al.1999 and references therein), in proportion to thecatches per half-degree square previously allocated,will be sufficient for a first-pass allocation,especially since misallocations should generatevisible patterns in the maps thus generated.

For the North Atlantic, this crude approach can bereplaced by one in which the catch reported byspecies, from distinct ICES or NAFO sub areas isassigned to the half-degree squares in each area as afunction of the mean depth of each square, and theobserved depth distributions in the species inquestion, as plotted on the ‘depth transects’presented below (see also Zeller and Pauly 2000).Here again, misallocations should generate visiblepatterns in the maps thus generated, and thus leadto improvements of the allocation rules.

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FISH DISTRIBUTION TRANSECTSFISH DISTRIBUTION TRANSECTSFISH DISTRIBUTION TRANSECTSFISH DISTRIBUTION TRANSECTS

As mentioned above, the Sea Around Us Project willnot attempt to perform assessments of single-species fisheries, and not generally question suchassessments as performed by various colleagues.

However, we do require connecting our work withkey aspect of the distribution of major commercialspecies, for two reasons:

1) These distributions can help assign catches toareas (see above); and

2) The depth and distance from the coast of majorpopulation components determines theirrelative vulnerability to coastal (often small-scale) and offshore (often large-scale) gear andhence the existence and intensity of interactionsand (potential) conflicts between these differentfisheries.

The format we have developed for these transectfulfils these requirements by integrating the keyinformation on the distribution and migration offish in a single graph (see Zeller and Pauly 2000).Using such a graph, catches of both small- andlarge- scale fisheries, both inshore and offshore, canbe partitioned and their impacts evaluated.

Bio-economic analyses of fisheries: small vs. largeBio-economic analyses of fisheries: small vs. largeBio-economic analyses of fisheries: small vs. largeBio-economic analyses of fisheries: small vs. large

Few, if any studies have quantified the economicrent lost from competition between the large- andsmall-scale sectors of a fishery. Here we havechosen an approach with three important keyfeatures:

1) Easily scalable from local fisheries to theentire North Atlantic;

2) Provides management alternatives byemphasizing, where possible, thesubstitutability of large by small scalefisheries (and vice versa);

3) Should lead to a reliable estimate ofeconomic losses (waste) due to excesscapacity and non-cooperative behaviorbetween different elements of the fisheriessector (see Nash 1951, 1953).

This approach uses a multispecies, multifleet yield-per-recruit analysis to estimate, based on thepresent, calculated recruitment ( = influx of youngfishes and invertebrates to the fishing grounds), thefeatures of a ‘small scale’ and a ‘large-scale’ fleetwhich maximize the gross value of the catches of

both fleets. These features are the level of effortrelative to present, and the selection curves of eachgear relative to each species. Then, under theassumptions that the present fisheries are at or neartheir bioeconomic equilibrium point (where totalcosts equal gross total returns; Gordon 1954), andthat fishing mortality scales linearly to fishing cost,we identify the equilibrium point at whichmaximum net returns can be obtained if the fleetsadjusted their fishing mortality such that their jointnet benefit is maximized (Munro 1979; Sumaila1997).

The difference from between these optional returnsand the Nash Frontier to the present position of thefleet allows the loss (=economic waste) due to non-cooperation and mismanagement. Finally, wepartition benefits by sector and identify the Nashbargaining solution (Nash (1953) associated withthe equilibrium point (Binmore 1982). Thisprocedure can be applied successively to a largesample of representative North Atlantic fisheries,thus yielding, by addition, an overall estimate ofeconomic losses, and, more importantly of theeconomic gains that would result from improvedmanagement (Ruttan et al. 2000). We expect thesenumbers to be very large, especially when scaled upto our reference area, through the ratio of the sumof all catches in the sample fisheries to the totalNorth Atlantic catches.

The Achilles’ heel of this approach is, of course, theassumption that for each fishery, relativerecruitment, as obtained by dividing yield perrecruit into average catches, will remain constantwhile fishing mortality varies. We note, however,that the approach we propose will tend to associatethe Nash equilibrium with levels of fishing mortalitylower than those commonly presently occurring inreal fisheries (which tend to suffer from growthoverfishing). This implies that recruitment would beassumed to remain constant over a small range of F-values only.

Moreover, the proposed method will treat eachfishery independently from the others, usingdistinct mixes of species, each with their own sets ofrelative recruitment, and growth and selectionparameters. Thus, given the Central Limit Theorem,our global estimate of economic loss will tend to beaccurate, even if the estimates for certain fisheriesare not.

Another aspect of our comparative bioeconomicstudies of small-scale vs. large-scale fisheries is thatthey should provide a framework for evaluatinggovernment policies which purport to benefitemployment, or other social goods: small-scale andlarge-scale fisheries often sharply differ in the

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employment opportunities or other social benefitsthey provide (see section below on RAPFISH; andAlder et al. 2000).

EEEECOSYSTEM MODELLINGCOSYSTEM MODELLINGCOSYSTEM MODELLINGCOSYSTEM MODELLING

Embedding the fisheries that generate the catchesand economic returns discussed above intoecosystems will be achieved by constructing at leastone ECOPATH model for each of the LME in theNorth Atlantic. The rationale for ECOPATH asmodeling tool is that it is the only approach so fardemonstrated to be widely applicable for modelingmarine ecosystems, notwithstanding a commonmisunderstanding as to the ready availability ofalternative approaches. Christensen and Walters(2000) review ECOPATH as used in the context of theSea Around Us Project, with emphasis on this andother misunderstandings regarding the capabilitiesand limits of the approach it embodies.

Presently, ECOPATH models exist for numerous partsof the world (see Pauly et al., 2000). However, only20 of these represent ecosystems of the NorthAtlantic basin, hence precluding simple raising ofbiomass flows from ecosystem to basin scales. Thus,a stratification scheme is required, based on thegeographic structure outlined above, which can beused to scale models from the sampling area of thefield data used to parameterize the models to thewider area that is assumed represented by thesesame models.

LMEs are seen here as providing the key level forecosystem model construction. For each LME, anECOPATH model will be constructed to describe theecosystem resources and their utilization, and toensure that the total fisheries catch of each LME isused as output constraint (just as their primaryproduction will be used as input constraint). Inaddition, the stratification scheme used must besuch that it can straightforwardly accommodate anynumber of additional ECOPATH models for eachLME. This can be done so as to simultaneouslyaddress the issue of parameter uncertainty, asdescribed in Pauly et al. (2000).

The LME ECOPATH models require information onabundance, production and consumption rates anddiets for all ecosystem groupings. Such informationcan be obtained from the following sources:

• Abundance, production and consumptionrates, and diets of marine mammals areavailable from the Sea Around Us Projectdatabase for all (117) species of marinemammals and on a seasonal basis;

• Fishery catches: available from the spatiallystructured catch database generated as

described above (see also Watson et al.2000), and covering all species groups;

• Occurrence, biology and ecology of marinefishes: available from FishBase(www.fishbase.org) at LME level for theNorth Atlantic, as a result of cooperationbetween the Sea Around Us Project andFishBase projects.

• For marine invertebrates: only limitedinformation (beyond the catches in the FAOdatabase) is available from electronicdatabases, but a variety of publicationsprovide extensive information. Productionrates can be estimated from the well-founded empirical relationships of Brey(1999), now included in ECOPATH;

• Primary production estimates:establishment of a global database aimed atsupplying fine grid level satellite basedestimates of primary production ispresently underway through a cooperationbetween the Space Applications Institute,EC Joint Research Centre, Ispra, Italy, andseveral members of the Sea Around UsProject.

The LME-level ECOPATH models will serve as thebackbone for addressing issues related to fisheriesimpacts, to derive indices related to ecosystemhealth (Rapport et al. 1998a; 1998b; Costanza andMageau. 1999), to evaluate, using ECOSIM andECOSPACE (Walters et al. 1997, 1999; Walters andChristensen 2000), the likely effects of changes infishing patterns, including setting up of marineprotected areas, and to estimate the expectedeconomic benefits of such interventions.

Moreover, these LME-level ECOPATH models,representing the present states of the systems inquestion, will also serve as templates for models ofselected areas (notably the Gulf of Maine,Newfoundland and the North Sea) forreconstructions representing these systems prior tothe onset of large scale mechanized fisheries, andthe ensuing resource depletion. Thus, LME-levelECOPATH models of past ecosystems will provide thebasis for estimating the benefits that would obtainfrom rebuilding strategies, as required to addressQuestion 6 in the Introduction (see also Figure 5).The next section provides more details on this issue.

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Evaluating alternative ecosystem-basedEvaluating alternative ecosystem-basedEvaluating alternative ecosystem-basedEvaluating alternative ecosystem-basedmanagement regimesmanagement regimesmanagement regimesmanagement regimes

To complement the analysis of small- and large-scale fisheries as outlined above, leading to anestimate of potential economic gains from improvedmanagement, we will simulate the results of variousmanagement regimes, and evaluate their results inthe framework of fisheries economics, extended tomake it applicable to ecosystem analysis.

The extended theory is then applied to explore anumber of questions including (i) to what extent isit worth society’s while to restore currentecosystems to their past states? (ii) What is theoptimal approach path to the past ecosystem? Is itoptimal to invest (disinvest) rapidly in restoring theecosystem, or should investment (disinvestment)proceed more slowly?

ECOPATH and ECOSIM models will form theecological basis for our analysis, while ecologicaleconomics valuation techniques will help determinethe economically feasible restoration plans andpaths (see Munro and Sumaila 2000).

Mapping the fate of fisheries landings from theMapping the fate of fisheries landings from theMapping the fate of fisheries landings from theMapping the fate of fisheries landings from theNorth AtlanticNorth AtlanticNorth AtlanticNorth Atlantic

The validity of the analyses described abovedepends on the markets presently existing for fishproducts, and their likely evolution. We proposetherefore, that a spreadsheet-based framework canhelp track the flow of fish landings within the NorthAtlantic region (details in Sumaila et al. 2000).

Starting with the total fish landings from the watersof each major fishing nation within the NorthAtlantic region, a map can be developed showinghow these landings flow into the major productforms under which they are marketed, i.e., fresh,frozen, salted and smoked. In addition, the portionof the product forms are consumed in the domesticversus the export market can be determined.Finally, the results derived can be used to identifythe sectors or product forms which capture most ofthe economic benefits from the fishes of the NorthAtlantic.

Energy consumption and ecological footprint of theEnergy consumption and ecological footprint of theEnergy consumption and ecological footprint of theEnergy consumption and ecological footprint of theNorth Atlantic fisheriesNorth Atlantic fisheriesNorth Atlantic fisheriesNorth Atlantic fisheries

One way to express the overcapitalization of NorthAtlantic fisheries (i.e., the excess of catchingcapacity) is to relate the energy dissipated ingenerating present landings to the energy containedin the landings.

This appears more straightforward than estimatingfleet ‘capacity’, which is not only hard to measure,but even hard to define. Energy expenditures, onthe other hand are easily defined, and can beestimated reasonably well from the size of thevessels, which relates strongly to that of theirengines, and hence to their fuel consumption.

Hence our choice of Horsepower∙days as measure ofeffort, a choice having the further advantage ofallowing comparisons between otherwise widelydifferent boat/fishing gear combination (seeWatson et al. 2000).

The estimation of energy consumption by thefishing fleets of the North Atlantic, and the relatedestimation of their ecological footprint(Wackernagel and Rees 1996), are presented byTydmer (2000), who provides details, as well, onthe required distinction between variable energycosts (associated with running vessels) and fixedcosts, associated with the construction and eventualretirements of the vessels comprising a fleet.We anticipate that the aggregate energy costs offishing, in the North Atlantic, will be very high,relative to the energy (and commercial value) of thelandings, the difference being met by varioussubsides.

RRRRAPFISHAPFISHAPFISHAPFISH and compliance analyses and compliance analyses and compliance analyses and compliance analyses

Evaluations in the Sea Around Us Project employ anew multi-disciplinary, rapid appraisal technique,called RAPFISH, that focuses on the comparativesustainability of fisheries (Pitcher and Preikshot1998; Pitcher et al. 1998a; Pitcher et al. 1998b;Preikshot and Pauly 1998; Preikshot et al. 1998;Pitcher and Preikshot, in press). RAPFISH can beperformed even when the rigorous survey data thatenables conventional stock assessment are notavailable, as is the case for many North Atlanticfisheries.

As such, RAPFISH is a typical SNT, a smart new trickas defined above. It is however, suitable for the SeaAround Us Project because it allows us to quantifyaspects of fisheries thought before to beunquantifiable, and thus allows for comparisons.Moreover, the method can be applied at all scalesrelevant to the Sea Around Us Project, from thefisheries of a small bay of gulf, to those of countries,or of the entire North Atlantic. As well, RAPFISH canbe used to compare gears, and thus to contribute itsunique perspective to the comparisons betweensmall- and large-scale fisheries mentioned above.

Assessment and Mitigation of Fisheries Impacts

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In RAPFISH analyses, sets of attributes, chosen toreflect sustainability within each discipline, arescored on a ranked or binary scale. Where data aresparse or uncertain, scores may be refined whenbetter information becomes available. Ordinationsof sets of attributes are performed using multi-dimensional scaling followed by scaling androtation. The leverage of each attribute on theresults can be estimated with a step-wise procedure.The ordinations are anchored by fixed referencepoints that simulate the best (= ‘good’) and worst(‘bad’) possible fisheries using extremes of theattribute scores, while other anchors secure theordination in a second axis normal to the first.Significant differences are defined by Monte Carlosimulation of errors attached to the original scores.Raw plots of the results show fisheries status inrelation to ‘bad’ and ‘good’.

Separate RAPFISH ordinations are performed inevaluation fields (disciplines) that express status interms of ecological, economic, social, technologicaland ethical (Pitcher and Power 2000) sustainability:a further field evaluates compliance with the FAOCode of Conduct for Responsible Fisheries (Pitcher1999). Status results may be combined in ahierarchical way in ‘kite diagrams’ (see Figure 2) tofacilitate comparison of fisheries by gear type,country, ecosystem or size category, and data maybe constructed to represent the outcomes ofalternative policies (Alder et al. 2000).

At this stage in the SAU project, we present a paperreporting preliminary RAPFISH analyses of fisheriesin two major North Atlantic areas, the Gulf of Maineand the North Sea (Alder et al. 2000). By the end ofthe SAU project all major fisheries will be coveredby RAPFISH evaluations. This will allowexamination, for each country, of fisheriescompliance with the FAO Code of Conduct forResponsible Fisheries. Compliance scored in thisway will be also be evaluated using a matrixexpressing international fisheries conventions towhich each country in the North Atlantic issignatory.

Figure 2Figure 2Figure 2Figure 2. Diagram illustrating how RAPFISH

evaluation fields for different modalities ofsustainability can be considered together as scoreson the axes of a kite diagram. Boxes represent theattributes used to ordinate fisheries within eachevaluation field. Connections, arrows and kite apicesrepresent a score between 0% and 10% from eachfield. The outer rim of the kite is equivalent to 100%scores ( = ‘good’) in each field, while the centre of thekite represents scores of 0% ( = ‘bad’). Six evaluationfields are illustrated here, one of which, for the Codeof Conduct, is comprised hierarchically of a five-fieldRAPFISH.

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CCCCONCLUSIONSONCLUSIONSONCLUSIONSONCLUSIONS

The relationships among the various elements of theSea Around Us Project are summarized in Figure 5.We anticipate that the synthesis to emerge fromintegrating the results of these modules will containmany surprises, both in terms of the ecological

damage and economic waste presently generated bythe North Atlantic fisheries, and the benefits thatcould be gained, were these economic and ecologicalissues addressed.

CCCCATCHATCHATCHATCH/E/E/E/EFFORTFFORTFFORTFFORT D D D DATABASEATABASEATABASEATABASE

Comprehensive time seriesaccounting for small-scale

catches, discards, unreported catch etc.,

by area

EEEECOPATHCOPATHCOPATHCOPATH MODELSMODELSMODELSMODELS

One model per area,incorporating current data & understanding

of each ecosystem

RRRRAPFISHAPFISHAPFISHAPFISH A A A ANALYSISNALYSISNALYSISNALYSIS

Status of fisheries interms of ecological, economic,

technological, social and ethical sustainability

MMMMAPSAPSAPSAPS

Ecosystem definitions

and properties

FFFFISHISHISHISHBBBBASEASEASEASE

Spp. by ecosystems )(subcontract

TTTTRANSECTSRANSECTSRANSECTSRANSECTS

Depth distributionof key spp.

TTTTOTALOTALOTALOTALEEEEXTRACTIONSXTRACTIONSXTRACTIONSXTRACTIONS

By species and

ecosystem

EEEECOSYSTEMCOSYSTEMCOSYSTEMCOSYSTEMHHHHEALTHEALTHEALTHEALTH

FFFFISHERIESISHERIESISHERIESISHERIESIIIINTERACTIONNTERACTIONNTERACTIONNTERACTIONSSSS

losses from

competition between small- and large-

scale fisheries

FFFFISHINGISHINGISHINGISHINGEEEEFFORFFORFFORFFORTTTT

Energy consumption

and ecological footprint of fleets

PPPPASTASTASTAST E E E ECOYSTEMCOYSTEMCOYSTEMCOYSTEMSSSS

Models of past, reconstructed

ecosystems

MMMMARKETARKETARKETARKETSSSS

Market pathways, profits and

subsidies

CCCCOMPLIANCOMPLIANCOMPLIANCOMPLIANCEEEE

with treaties and the FAO Code of

Conduct for Responsible

Fisheries

EEEEVALUATIOVALUATIOVALUATIOVALUATIONNNN

Benefits from ecosystem-based

management

Figure 3. Figure 3. Figure 3. Figure 3. Conceptual diagram illustrating the relationships of the various methodological elements of the SeaAround Us Project.

Assessment and Mitigation of Fisheries Impacts

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AAAACKNOWLEDGMENTSCKNOWLEDGMENTSCKNOWLEDGMENTSCKNOWLEDGMENTS

The Sea Around Us Project is supported by theEnvironment Program of The Pew CharitableTrusts. We would particularly like to thank Dr.Joshua Reichert, for his support of the ideas whichled to the development of this project. Also, wethank Drs Reg Watson, Rashid Sumaila, and DirkZeller for detailed comments on the draft of thiscontribution.

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