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Social multi-criteria evaluation as a decision support tool for integrated coastalzone management

Eneko Garmendia a,b,*, Gonzalo Gamboa b, Javier Franco c, Joxe Mikel Garmendia c, Pedro Liria c,Marta Olazabal d,e

a Environmental Economics Unit, Institute for Public Economics, University of the Basque Country, Spainb Institute for Environmental Sciences and Technologies (ICTA), Universitat Autonoma de Barcelona, 08193 Bellaterra, SpaincAZTI-Tecnalia, Marine Research Division, Herrera Kaia e Portualdea z/g, 20110-Pasaia, Spaind LABEIN-Tecnalia, Urban and Industrial Environment Unit, Parque Tecnológico de Bizkaia, 48160 Derio, SpaineDepartment of Land Economy, University of Cambridge, CB3 9EP, United Kingdom

a r t i c l e i n f o

Article history:Available online 21 May 2010

a b s t r a c t

Traditional top-down and technocratic approaches seem to be insufficient to tackle the many conflictsrelated to the sustainable use of natural resources. At the same time, reductionist and mono-disciplinaryapproaches lack the capacity to capture the complex interactions within evolving socio-ecologicalsystems. Coastal zone management is an area that provides a clear example of such difficulties. In thispaper we explore the scope of a participatory integrated assessment process, known as Social Multi-Criteria Evaluation (SMCE), in the context of Integrated Coastal Zone Management (ICZM). Througha two-year collaborative research process, between an interdisciplinary group of researchers anda diverse group of stakeholders in the Urdaibai Estuary (a Biosphere Reserve in the Basque Country,Northern Spain), we show that improving the integration of diverse expertise and values can lead,through a mutual learning process, to the definition of relevant policy options and sound decisions in theface of complexity, value conflict and unavoidable uncertainty.

� 2010 Elsevier Ltd. All rights reserved.

1. Introduction

In the past, the failure of research to account for the full spec-trum of natural system functions and human system complexityhas often hindered its ability to produce realistic results that lead toinformed policies [1]. In coastal areas this situation has beenexacerbated by inappropriate managerial interventions [2]. Hardengineering solutions and command and control approaches,which neglected the diversity of social actors and the multiplescales of complex socio-ecological issues, have been shown to beinsufficient for solvingmany contemporary issues related to coastalzone management. Global trends show a decline in the quality ofthese regions due to habitat loss, decline in water quality, collapseof fisheries or loss of biodiversity [3,4].

In recent years, increasing attention has been given to theinclusion of participatory approaches in natural resource manage-ment and policy making [5e14] and ICZM has also shifted to a moredeliberate role worldwide [15e19]. Claims for the active and

sustained involvement of different stakeholders and citizens inhow coastal resources are allocated and conflicts mediated comefrom different strands [2,3,9,20e27]. Nevertheless, efforts in thisdirection still need further attention. In this paper we will try toaddress the following key questions:

(i) How do we make operational the claim for more inclusiveapproaches in ICZM?

(ii) Aiming to provide better management options for our coastalsystems, how could we enhance participatory approachescapable of integrating a wide range of scientists, coming fromdifferent disciplines, with a broader public and stakeholders,with different values and interests, in a collaborative andinclusive partnership?

(iii) How could we deal with fuzzy, uncertain and often incompleteinformation about the complex socio-ecological systems (SES)that surround us [28]?

Ourunderstandingof hownatural and social systems interact, overlong timeperiodsandalongthespatial scale,needstobesubstantiatedby democratic mechanisms that can deal with the inherent problemsof continuous change, irreversibility, uncertainty and multiple legiti-mate standpoints of the systems [5]. In this context it is difficult tofind

* Corresponding author. Environmental Economics Unit, Institute for PublicEconomics, University of the Basque Country, Spain. Tel.: þ34 946017103; fax: þ34946017100.

E-mail address: [email protected] (E. Garmendia).

Contents lists available at ScienceDirect

Ocean & Coastal Management

journal homepage: www.elsevier .com/locate/ocecoaman

0964-5691/$ e see front matter � 2010 Elsevier Ltd. All rights reserved.doi:10.1016/j.ocecoaman.2010.05.001

Ocean & Coastal Management 53 (2010) 385e403


any alternative to what has been defined by Funtowicz and Ravetz[29e31] as an extended community of peers. When facts are uncer-tain, values in dispute, stakes high and decisions urgent, scientistscannot provide any useful input without interacting with the rest ofsociety, and the rest of society can hardly make any sound decisionwithout considering the best scientific knowledge (see also [32e35]).

From this it seems obvious that in addition to the inclusion ofvarious scientific disciplines, collaboration should be enhancedbetween all relevant stakeholders representing the diversity ofvalues in society [36]. Local actors, citizens and other collectivestraditionally excluded from decision-making can contributesubstantially in this sense [37,38], as “non-experts” may see prob-lems, issues and solutions that experts miss [39]. In other words,the process of policy design requires a more collaborative interplaybetween decision-makers, scientists and other actors [40e44], andparticipatory approaches constitute a promising framework forpursuing this collective effort [45e47].

Among other holistic approaches, Multi-Criteria Evaluation(MCE) techniques have been shown to be particularly appropriatefor integration with participatory approaches in the search for newstrategies that foster sustainability in many issues characterized bydeep complexities and unavoidable conflicts [10,48e55]. Thisapproach allows one to take into account controversial, multidi-mensional and uncertain effects of decisions [56], in a systematicand structured way [57]. In the end, management plans are aboveall hypotheses that require “reflection before action” [44], andpublic and stakeholder participation supported by integratedassessment tools, like the one presented in this paper, can initiatesocial learning processes that enrich this reflexive process in thelight of complexity and unavoidable uncertainty [47,58,59].

With this study we explore the potential of a participatoryintegrated assessment process developed under the Social Multi-Criteria Evaluation framework (SMCE), in the context of coastal zonemanagement, through a real case study carried out in the BiosphereReserve of Urdaibai (Basque Country, Northern Spain). The rest ofthe paper is organized as follows. Section 2 presents briefly themethodological framework. Section 3 introduces the case study.Section 4 describes the whole participatory integrated assessmentprocess that has been developed to analyse different managementoptions for the study area. Section 5 shows the results obtained fromthis process. Finally, Section 6 discusses the potential of this meth-odology in the context of ICZM and gives some general conclusions.

2. Methodological framework: Social Multi-CriteriaEvaluation (SMCE)

MCE is a means of simplifying and structuring complex deci-sion-making problems that can involve many stakeholders,a diversity of possible outcomes and many, sometimes intangible,criteria bywhich to assess the outcomes [53]. The origins of MCE liein the fields of mathematics and operational research but in recentyears it has been increasingly applied in the context of naturalresource management and other sustainability related issues.

When first developed, MCE was characterized by the method-ological principle of multi-criteria decision-making (MCDM). Theobjective was to elicit clear preferences from a (mythical) decisionmaker and then to solve a well-structured problem by means ofa mathematical algorithm. Progressively, ideas about proceduralrationality1 [60] and the constructive or creative approach developed

by Roy2 [61] have lead to the development of the methodologicalframework of Multi-criteria Decision Aid (MCDA). With time, moreand more authors emphasize the need to include, public partici-pation in MCDA [48,51,53] fostering the emergence of ParticipatoryMulti-criteria Evaluation (PMCE). Social multi-criteria evaluation(SMCE) was born in this context and emphasizes transparency. Themain idea is that results of an evaluation exercise depends on theway a given policy problem is structured; thus, the assumptions,ethical positions, interests and values have to bemade clear. Withinthis framework SMCE public participation is a necessary condition,but not a sufficient one, mathematical aggregation conventions playan important role, i.e. to assure that the ranking of alternatives areconsistent with the information and the assumptions used [51].SMCE also includes:

� Consideration of the socio-cultural context in which the rela-tionship decision-makers/analysts is embedded;

� Combination of participatory methods (qualitative andquantitative);

� The use of a cyclic and dynamic evaluation procedure, in whichthe research teamand the involved social actors experimentwitha learning process (that may lead to a change in preferences).

Within this framework the application of participatoryapproaches must account for the:

� Potential influence of powerful stakeholders in discussiongroups;

� Lack of representation of qualitative participatory approaches(focus groups and in-depth interviews, among others);

� Inclusion of non-organized groups as part of the social actors;� Ethics e public participation and scientific outcomes do notentail de-responsibility of decision-makers.

People transform their positions and opinions with regard to anissue by interacting with other agents, exchanging information andreflecting on their underlying values and assumptions. In thisregard, authentic deliberation would require non-coercivecommunication so as to induce reflection upon preferences [62].

There are hundreds of mathematical algorithms to solve multi-criteria analysis problems [63] and each of them has advantagesand disadvantages depending on the context in which we want touse them [64]. The mathematical algorithm must yield outcomesconsistent with the information and assumptions used: theiraxiomatization should be complete and clear. Also, they should beas simple as possible in order to assure transparency in a socialcontext [51].

In this case, given the complexity of coastal ecosystems, thesurrounding uncertainty and the presence of high degrees ofconflict among the stakeholders involved we have chosen the so-called SMCE framework. As we have seen above, this novelapproach combines multi-criteria algorithmic (mathematical)methods with participatory approaches in its various stages andwas explicitly designed for dealing with complex and uncertainissues in the context of sustainability [65]. The theoretical foun-dation of this framework can be found in Post-Normal Science andComplex System Theory and rests on the idea of weak compara-bility of values, which states that irreducible value conflict isunavoidable but can be made compatible with rational choice by

1 According to Simon, one can distinguish between substantive and proceduralrationality. The former is independent of the way a decision is made and refersexclusively to the results of the choice. The last refers to the process in whicha decision is made.

2 According to Roy, finding a final solution in a decision problem is lessa discovery than a creation, in which the actors taking part in the decision processeither shape, argue and/or transform their preferences, arriving at a decision thatmeets their goals.

E. Garmendia et al. / Ocean & Coastal Management 53 (2010) 385e403386


employing practical judgments [51,56,66]. Renewable energypolicies [67], regional planning [68], risk assessment [69] or watermanagement [70] are but some areas to which this particularframework has been applied.

The main characteristics that make SMCE suitable for ICZM ingeneral and this case study in particular, can be summarized asfollows:

- inter/multi-disciplinary (with respect to the research team);- participatory (with respect to all stakeholders involved);- transparent (since all criteria are presented in their originalform and avoid reductionist assumptions);

- allows the inclusion of qualitative information in fuzzy oruncertain evaluation problems;

- adaptive and dynamic in a way that allows a continuouslearning process while capturing the emergent properties ofthe coevolving socio-ecological system.

3. Study area: Urdaibai estuary

Urdaibai is located in the south-eastern corner of the Bay ofBiscay, in the Basque Country (Fig. 1). It covers an area of 220 km2

with around 45,000 inhabitants, most of them concentrated in thetowns of Gernika and Bermeo. It has 22municipalities, 11 of whichlie wholly within its borders. To the north its border is the coast,where capes Matxitxako and Ogoño protect the entrance to theestuary and the island of Izaro stands guard. The rest of its bordersfollow thewatershed of the River Okawhich is 12 km inwidth and20 in. length. The territory is characterized by a hydrographic basinof small creeks thatmerge in a great saltmarsh surrounded by highsheer cliffs. The surrounding countryside is occupied by meadowland, oak groves, leafywoods and, especially, by plantations of fast-growing conifers (mainly Pinus radiata).

The central area of this region is the Urdaibai Estuary (UE),which is also referred to as the Oka, Mundaka or Gernika Estuary. Itis 12 km long and around 1 km at its maximum width [71]. Thisarea represents in all its complexity a clear example of the multipleinterests that coexist in the coastal zones and the difficulties weface in managing them. The estuary was used for food provision byits prehistoric inhabitants and nowadays we can still find variousremnants of the prehistoric, Roman and Middle Ages eras. Sincethen this area has been in a constant co-evolution with the humanactivities that modify it. Despite the major industrial developmentof the district throughout the 20th century, the estuary has main-tained its rural character and nowadays it encompasses the largestcoastal wetlands and the best preserved estuary in the BasqueCountry.

3.1. Environmental characteristics and main morphologicalelements

Like many other estuaries on the Cantabrian Coast, the UrdaibaiEstuary and its surroundings include a great variety of habitats andenvironments: cliffs, rocky shores, sand dunes and sand beaches inthe outermost area; intertidal sand banks, muddy banks and lowand intermediate marshes in the middle reaches; and highmarshes, freshwater habitats and riverine woods in the inner areas.This estuary also hosts several habitats and species of Europeanimportance according to the Birds and Habitats Directive. Of specialrelevance is that the area represents an important refuge for birds,mainly during the migration and winter seasons and both asa resting and feeding area. Many bird species included in the BirdsDirective are regular visitors to this estuary, like the EurasianSpoonbill (Platalea leucorodia), the Osprey (Pandion haliaetus) andmany waders.

The estuary can be seen to function as a tidal inlet, in terms of itssediment dynamics. The effect of river flow is relatively low,compared with the tidal prism volume, which represents almost allof the water flow in the estuary mouth [72]. Tidal inlets are one ofthe most dynamic elements of the littoral sediment budget. Somestudies have shown that the characteristics of the main morpho-logical elements of a tidal inlet depend upon the tidal prism, inletgeometry, shoreline configuration, offshore bathymetry, waveclimate, littoral drift, sediment characteristics and freshwaterrunoff [73e77].

The main morphological elements of the UE and their dynamicsare described below, in order to create a conceptual model of theevolution of the system and facilitate the construction and valua-tion of different management options for the area.

According to the dominancy of different dynamics in themorphology and sediment transport we can describe threedifferent parts of the estuary, with different morphologicalelements in each one.

(i) The offshore sand reservoir: this is the lower part of thebeach profile and in the UE is laterally confined by rockycontours (Izaro Island to the east and Matxitxako Cape to thewest). Completely wave dominated and without contact withother offshore sand banks or inputs due to coastal sedimentdrift.

(ii) The estuary mouth: this is the most dynamic area and wavedynamics and tide-dynamics are balanced. In this zone we canidentify the following morphological elements:- Ebb tidal delta. Known locally as the “Mundaka Sandbar” it isformed as the result of equilibrium between the tidal action(tidal outflow) and wave activity. The morphology of theMundaka Sandbar, in turn, is in response to the shorelineconfiguration (high-angle half-delta) [72].

- Main channel: tidal action dominates and its cross-sectionalarea is directly related to the tidal prism. The channel is alsoconditioned by wave action that tends to accumulate sand,constricting its section.

- Dynamic beach profile: this includes the breaking zone andthe intertidal beach. It is almost completely wave dominatedand its evolution is related to mean wave climate.

- Supratidal beach: this is a reservoir of sand modelled bywind action creating sand dunes. Its form is also condi-tioned by extreme storms on its north face and themeandering erosion of the main channel on the southernpart.

(iii) The inner part of the estuary: tidal action and river floware themain dynamics in this area. Wave action can have someimpact (especially infragravity waves in extreme storms) but itdecreases rapidly towards the inner part. In this part alsodifferent morphological elements can be described:- Flood deltas: these are created by the diffraction of the fluxduring the flood and modelled by the meandering erosiveaction of the main channel. Wave activity still has some effectmaking the sand banks (flood deltas) migrate inland.

- Main channel: tidal action on each point is proportional tothe tidal flow. Thus the dominance of the river outflowincreases as wemove from the estuary mouth to the inside ofthe estuary. There is still some wave activity, especially inrelation to the displacement of the sand banks andmorphology of the channel.

- Secondary channels: the dynamics are very similar to thesedescribed in the main channel but with no influence of wavedynamics.

- Mud flats: dynamics are really slow in this part. Freshwaterrunoff and some tidal action are the main factors.

E. Garmendia et al. / Ocean & Coastal Management 53 (2010) 385e403 387


3.2. A turning point: the creation of the Biosphere Reserve and thenew legal framework

In 1984, considering its natural and cultural values, this areawasaccepted as part of the World Network of Biosphere Reserves byUNESCO (Man and Biosphere Programme) and later, the BasqueCountry Parliament adopted the Urdaibai Biosphere ReserveProtection and Planning Act, Law 5/1989, with the aim of:

“.protecting the integrity and promoting the recovery of theland, flora, fauna, landscape, water and atmosphere, and inshort, of the whole ecosystem on the basis of its natural,scientific, educational, cultural, recreational and socio-economicinterest” (article 1).

In 1992 this area was also included on the Ramsar Convention’sList of Wetlands of International Importance; in 1994 it joined thenetwork of Special Protection Areas (SPAs) for Birds, which entailedautomatic inclusion in the Natura 2000 network of European pro-tected natural areas; finally in 2006, the Urdaibai littoral zones andmarshes were declared a Site of Community Importance (Natura2000 Network).

3.3. Management problems and related conflicts

Nowadays within this area, like in many other Cantabrian andMediterranean coastal zones, a wide range of interests coexist, e.g.tourism, agriculture, fishing, industry, recreational activities orconservation. Nevertheless this coexistence is not always an easytask and managing the system in a sustainable manner entailsa great challenge.

The estuary encompasses a highly dynamic and complex system,and the human activities within this system are closely inter-connected. Due to this complexity, compatibility among variousinterests is not always possible. Managers have to make trade-offs toappease the diverse interests and competing values. In the case ofUrdaibai, fishers claim access to selfish and consider any restriction infavour of conservation measures an infringement on their rights,which are previous to the creation of the Biosphere Reserve. Bird-watchers, environmental guides and others dependent on theecological values of the estuary underscore the legal status of theestuary as a special protected area and report illegal fishing andnavigation as a great threat to these habitats. Surfers depend on theconfiguration of the Mundaka sandbar to guarantee proper waves.

Fig. 1. Map of the study area showing, on the left, the main locations cited in the text and, in the photograph on the right, the main habitats of the estuary.



They reject anyconservationmeasures, like the creation of the dune inthemouth of the estuary, that could alter the dynamics of the channeland modify the configuration of the bar. Tourism also depends onrecreational activities, e.g., kayaking or kite surfing, in the inner part ofthe estuary, which also creates tension between sport practitionersand conservation measures. These are just some examples, but in thelast decades many other conflicts have arisen in the area due to thepresence of confronted interest and perspectives.

The last serious episode took place in 2003 when a shipyardlocated in the middle of the estuary dredged over 300,000 m3 ofsand andmud to facilitate the launching of its boats. The disposal ofthe dredged material in the outer estuary modified its hydrody-namics and subsequently the morphological features of the system,affecting a number of activities like surfing, fishing and birdwatching, and causing social alarm. The intervention in the bottomof the channel was not a new issue, and has been the focus of manycontroversies. In the 1970s for instance, under Franco’s dictatorship,the pressures suffered by the estuary led to the creation of some ofthepioneering conservationandecologist associations in theBasqueCountry. Nevertheless, this time, due to a combination of severalfactors, especially the impact onMundaka’swave (the longest left inEurope and host of the World Cup) and the role of the mass media,the concern about the future of the estuary reached unprecedentedlevels. Many local, regional and also international collectivesshowed their concern about the future of the area, leading toa turning point in the current management regime (Fig. 2).

In summary, the emergence of new social values and needs hasshifted the management system in the estuary. Between the 16thcentury and the beginning of the 19th century, increasing demandfor agricultural land due to demographic pressure diminishedwetland areas and created polders. In the last part of the 19th

century and the beginning of the 20th century, a large channel andrailway along the estuary were built to serve the local economy,shifting management and greatly influencing the dynamics of theestuary. Between the 1960s and the late 1990s, abandoned agricul-tural land reverted tomarshland, and dredging activities shaped theestuary. Finally, the creation of the Biosphere Reserve in 1989 andthe subsequent legal protectionof theestuaryas a conservationzonehave conditioned the future of the area. The law now requires thesustainable management of the estuary (see Section 3.2).

In this context, in 2007 a diverse group of researchers3 togetherwith local, regional and national stakeholders4 concerned about thesituation in the area, created a collaborative research process with theaim of analysing sustainable management options for the UrdaibaiEstuary from a holistic perspective and considering the activeinvolvementof adiversegroupof stakeholders. In the followingsectionwe describe in more detail the whole participatory integrated processthathasbeendevelopedwith thispurposeunder theSMCEframework.

4. The participatory integrated assessment process under theSMCE framework

In operational terms, the application of a social multi-criteriaframework, in a participatory context, involves the following mainsteps [51]:

Fig. 2. Multiple uses in the estuary: (a) Polders constructed in the past due to demographic pressure and land demand; they are currently threatened by invasive species in due toabandonment of agricultural activity; (b) shipyard in the middle of the estuary; (c) Mundaka’s wave and surfers in the river mouth of the estuary, (d) Recovered dunes in the outerpart of the estuary.

3 Composed of: marine scientists, biologists, sociologists, economists, engineers,lawyers, chemists, ecologists and geologists.

4 Among others this group included representatives from: the Basque govern-ment, Spanish environmental ministry, industry and labour unions, mayors, citi-zens, NGOs, birdwatchers, fishers and surfers.



1. Identification of relevant social actors by means of institutionalanalysis, individual interviewswithkeyagents, focusgroups, etc.;

2. Problem definition, which follows a similar procedure as thatoutlined above;

3. Creation of alternativese policy optionse and the definition ofevaluation criteria. This process must be a collective creationresulting from a dialogue between the scientists and the socialactors. Criteria are indicators that assess to what extent thedifferent social actors’ objectives are achieved by eachalternative;

4. Valuation of criteria in a multi-criteria impact matrix. Thematrix synthesizes the scores of all criteria for all alternatives.Each criterion score represents the performance of each alter-native according to each criterion;

5. Assessment of social actors’ preferences and values, mainlythrough in-depth interviews and focus groups;

6. Selection of the multi-criteria evaluation method and applica-tion of the model through a mathematical aggregation proce-dure. In order to obtain a final ranking of the availablealternatives, the criterion scores must be aggregated by meansof a mathematical algorithm. Many multi-criteria models havebeen formulated since the 1960s, each one with advantagesand disadvantages. In each case, the most appropriate modelmust be chosen by weighing the pros and cons of each;

7. Social analysis and discussion of the results to check therobustness of the analysis. Results are exposed to public debateand validation. This step also entails a sensitivity analysis inwhich some of the assumptions or parameters included in themodel are given a different value, to test whether the finalranking of alternatives changes and the results are robust. Thisstep is very important due to the unavoidable degree ofuncertainty that characterizes most real-world decision-making processes (Fig. 3).

In summary, the above mentioned steps can be divided intothree general phases:

(i) approach to the situation under study, in order to identify thesocial actors involved, understand the socio-environmentaldynamics of the system and define the problem;

(ii) representation of the problem at hand: that is, the definition ofthe decision space and the evaluation criteria;

(iii) evaluation, in which the set of alternatives forming the deci-sion space are assessed in social and technical terms.

In the following sections each phase as it was carried out in thisstudy is described in more detail.

4.1. First phase: approaching

In this case, this phase included the following steps for devel-oping a wider understanding of the issue at hand and identifyingthe relevant actors and their stakes:

(i) Institutional analysis by means of:- A detailed review of the historical uses of the river basin[78e81]

- Mapping the multiple uses/interests in the area and theplausible conflicts among them

- Identifying the relevant stakeholders and their positions withregard to the current situation in the estuary

- A detailed revision of the existing legislation, and otherhistorical documents such as newspaper articles andminutesof the city council sessions to better understand past conflict(Section 3.3).

(ii) Interviews with the relevant stakeholders to complement thebroad picture obtained from the institutional analysis, andimprove our understanding of the main socio-ecologicalaspects of the area. With this aim, starting with a few contactsin the local administration, social and ecological movementsand the regional government, through a “snowball” technique,during the spring of 2007 we performed more than 20 semi-structured in-depth interviews with a diverse group ofstakeholders.

It is worth noting that key informants are not meant to be“representative” of members of an organization or community, inthe way that statistical sampling is. Instead, key informants arepeople who are privy to the events being studied and able toprovide the researcher with reliable information about the orga-nization or community to which they pertain and the knowledgethat comes from their experience in these settings [8].

(iii) An open meeting (>20 participants) with a diverse group ofstakeholders (identified by means of the institutional analysisand the interviews) and the research team. This workshopserved to define the issue at hand and complete the full list ofrelevant stakeholders. In this meeting the research team gaveaccount of the multiple uses and interests that were identifiedin the estuary and the conflicts around them. After an intensediscussion and a quick presentation of the SMCE framework, allthe counterparts agreed to follow up a collaborative researchprocess to assess different management options for the UE.

During this phase, all parties acknowledged the need for urgentresponses to get out of the current “trap”, and walk in the directionof sustainability as recognized in the foundation of the BiosphereReserve. Nevertheless, it was remarkable that the interpretation ofsustainability entails a great diversity, and no consensus orcommon understanding exists with regard to the possiblemanagement options for the area. Conflict of interest, diversity ofperspectives and mistrust among participants is often a commonfeature at the beginning of this type of process and this casewas notan exception. Many participants showed scepticism about thescope of working together with groups whose interests conflictedwith their own.

Fig. 3. Social Multi-Criteria Evaluation (SMCE) framework used in this study (adaptedfrom Roca et al. [69].



4.2. Second phase: representing

4.2.1. Creation of alternativesOnce the problem had been defined and the relevant stake-

holders identified, the second phase of the SMCE consists in thedefinition of alternatives or policy options to confront these witha set of criteria. In our case alternatives represent managementoptions for the Urdaibai Estuary (UE).

Dredging activities, disposal sites and the ecological threats tothe estuary arose during the participatory process as the key factorsto define different philosophies of action together with compen-sation mechanism for those affected by the management plan. Onthis basis a preliminary proposal was constructed by the researchteam and external group of experts, followingMassam’s suggestion[82] which includes: (a) the status quo or business as usual situa-tion, (b) an ideal best plan, (c) a hypothetical worst plan and (d)a compromise solution or minimum satisfaction.

To avoid biases from the research team and the selected group ofconsulted experts this set of management options was exposed tothe revision of thewider public, in a second participatory workshop(>25 participants) that served to redefine a preliminary proposal.Table 1 summarizes the resulting set of alternatives and sub-alternatives emerged from this interactive process (Table 1).

4.2.2. Definition of evaluation criteriaTogether with the construction of alternatives, in a multi-

criteria framework we need to define the diversity of interests andrelevant issues in a set of criteria that will constitute the basis forour assessment. These criteria are a technical translation of socialactors’ needs and expectations operated by the research team andshould cover the multiple dimensions of the issue at hand. There is

no consensus in determining the number of criteria that should beconsidered in this type of evaluation, but usually this is limited toa maximum of 7e12 [83,84]. In this sense, Bouyssou [83] states thatfor reasons related to the cognitive limitations of the human mindand to the necessity of gathering inter-criteria information, it is notadvisable to include more than a dozen of criteria when imple-menting aggregation procedures.

The identification and selection of criteria starts with personalinterviews, but a joint discussion among participants with differentperspectives makes possible the emergence of new ideas, whileallowing participants to reflect on their own underlying values andassumptions. In this sense public participation, which includesdeliberation and inclusion [85], has been demonstrated to beappropriate to initiating social learning processes that reflectcollective needs and understanding [47,86e88].

The second workshop, organized after the approaching phase,had the aim of defining the relevant set of criteria. The 15 partici-pants were organized into several groups in order to facilitate theirparticipation and involvement. They were asked to discuss anddefine the main criteria needed to guide the UE in the future.

The workshop was structured as follows:

(i) Brief presentation of the objectives of the workshop(ii) Joint reflection about the future of the region(iii) Discussion in focus groups of around eight people, about the

relevant aspects to be considered for the sustainablemanagement of the estuary

(iv) A final joint discussion among all the working groups

In this typeofworkshop it isdesirable to combinebig settingswithsmall groups inorder tooffereverybodythechance toparticipate, and

Table 1Summary of alternatives or management options.

Scenario Alternatives Sub-alternatives

Nonedredging

A1 Do nothing: leave the system on its own but without any type of intervention.No active conservation measures, no dredging activities, no compensation measures.A2 Compensation: do not allow dredging and compensate the affected parties(mainly shipyard workers) due to constraints on their activities.A3 Conservation: do not allow dredging and direct all the public resources intoconservation measures for the estuary. Eradication of invasive species, recoveryplans for damaged areas, creation of guard and maintenance services in theestuary and removing the illegal boats.

Max dredging B Satisfy demands from industry (shipyard) with a maximum dredgingalong the channel (200,000e300,000 m3) anddisposal of dredged material in.

B1. Both sides of the main channelB2. Intertidal zoneB3. Emerged areaB4. Submerged area

Min dredging C Compromise: minimum dredging according to the “systems limit”(20,000e30,000 m3 to guarantee navigability for small boats) andconservationa measures. Disposal of dredged material in.

C1. Both sides of the main channelC2. Intertidal zoneC3. Emerged areaC4. Submerged area

a In this case the conservation measures will be less than in scenario A3 considering that part of the public budget would be assigned for a minimum dredging.

Table 2Profile of working groups.

Working groups

Society and welfare Environment and biodiversity Economic dynamism

Environmental guide Citizen Surfers AssociationShipyard worker Zain Dezagun Urdaibai (Environmental NGO) Shipyard DirectorTrade union representative Representative of recreational boats Mayor of Gautegiz-ArteagaFishers association representative Head of dune recovery program Mayor of MuruetaEkologia tailerra (NGO) Chemist expert in marine pollution working in the area Regional Development Agency

Mayor of Mundaka

Assistance from the research teamEngineer and Sociologist Biologist and Marine Scientist Economist and Environmental

Science



avoid potential lobbying strategies (i.e. some interests, like those offishers or surfers, were over-represented compared to others). On theotherhand, oftenpower relationscan intimidate the free interventionof some participants (e.g. between the owner of a business and hisemployees, politicians and civil servants, etc.) which also makes itdesirable splitting them in different settings. It is worth noticing thatthe groups should be homogeneous with regard to their participantsand that heterogeneity can be reach by a diversity of groups. In thiscase participants were distributed in three groups and discussed thecurrent and future situation of the estuary from the followingperspectives: (1) society and welfare; (2) environment and biodi-versity; (3) economic dynamism. Table 2 summarizes the composi-tion of each working group.

With a similar rationale, collecting different points of viewthrough anonymous questionnaires and personal interviews is alsoessential within the participatory process [33,68,70,89], anda second round of personal interviews was carried out with rele-vant actors that did not have the opportunity to participate in theworkshops (Head of the Biosphere Reserve, Basque EnvironmentalMinistry, Head of Coastal Affairs, Head of Harbours and Ministry ofTransport, Mayor of Busturia, among others). In this case inter-viewees were also asked to express their needs, preferences anddesires with regard to the UE, and to define relevant criteria for theevaluation phase.

These qualitative [participatory] techniques can be criticized fortheir lack of statistical meaning, but they give the participant andthe analyst the time to deliberate, i.e. to think and create relevantknowledge for policy making, which is necessary when facingsituations with multiple and uncertain outcomes [68].

From this interactive process we identified the list of criteriathat is summarized below. (Table 3)

4.2.3. Valuation of criteria: feeding the impact matrixHaving defined the relevant criteria and constructed the alter-

natives, the next step in an SMCE process consists of feeding theimpact matrix in which each alternative is confronted with eachcriterion. This serves to assess the performance of each alternativeaccording to its impact on the selected criteria (see Table 3).

The construction of the criteria (indicators) in the framework ofthe decision aid depends more on the art and the experience of theanalyst than on “science” [83]. In the case of a SMCE process (inwhich theparticipationof divers’disciplinesplayanactive role) eachdiscipline has its job, although an interdisciplinary discussion aboutmethodologies and assumptions e a space in which constructivecritique is possible e is an essential part of the valuation process.

Briefly the valuation process to feed the impact matrix entails:

1. Selection of the indicators to assess the performance of thealternatives. Criteria represent certain objectives or relevantissues present in society and the indicators measure the degreeof fulfilment of these;

2. Choice of the temporal and spatial scale inwhich the indicatorsare valued;

3. Collection of information and data needed for the valuation ofthe criteria; There can be several indicators to measure theperformance of one criterion;

4. Evaluation of criterion scores.

The valuation process is not an easy task. When measuring theimpact of a given policy, the interpretation of indicators might becontroversial. What may be beneficial for some, may be harmful forothers, and vice versa. For example, an increase in the number ofcars sold might be good for the economy but bad for the quality of

Table 3Evaluation criteria.

Criteria Needs and expectations Criteria scores

Socio-economicaldimension

Employment - Enhance local employment and avoid people’s displacement toother areas

- Support local economic activities- Improve the quality of life- Guarantee job stability- Coherence with local reality e local identity maintenance

Number of jobs and their stabilityUnit: people employed in thenext 10 yearsDirection: maximize

Local incomes - Increase municipality’s income- Avoid becoming a residential area- Promote local business- Equitable development among municipalities

Local income and its distributionUnit: qualitativeDirection: maximize

Compatibility betweensocio-ecological activities

- Avoid collapsing activities- Minimize impact on fishing, surfing, industry, conservation, tourism,navigation

- Foster a balance between development, education and conservation

Number and degree ofcompatible activitiesUnit: indexDirection: maximize

Cost of implementation - Keep industrial competitiveness and warranty, economic viability- Consider administrative budget constraints- Take in to account opportunity cost

Cost of implementationUnit: VDirection: minimize

Socio-ecologicaldimension

Environmental disturbance - Keep the environment quiet- Avoid massive affluence and foster quality tourism- Limit navigation- Enhance non invasive cultural and economic activities- Conserve the environmental quality of the area

Unit: qualitativeDirection: minimize

Impact on habitat and fauna - Reduce impact over the different ecosystems: marshes, reedbeds,sand banks, etc.

- Avoid impact on fauna: birds, shellfish, benthonic communities- Diminish the impact of toxic sediments, in ground and water.- Avoid invasive species proliferation in abandoned agricultural land

Unit: synthetic indexDirection: maximize

Reversibility - Not jeopardize the potential of the area for the future- Respect the dynamics of the river- Recover the original channel- Consider the long term and the time to get back to equilibrium

Time to get back to equilibriumUnit: qualitativeDirection: minimize

Uncertainty - Reduce the degree of uncertainty of management options- Acknowledge the uncertain and complex response of the system- Adopt a precautionary approach

Degree of uncertaintyUnit: qualitativeDirection: minimize



the air. Similarly, the presence of endemic species might be seen asa treasure for environmentalists, but a menace for others who seetheir activity threatened by the presence of such species. For thesereasons, it is important to recall that before fulfilling the impactmatrix and obtaining the values of indicators to assess criteria, thenarrative that guides the evaluation (discourses, objectives, values,etc.) must first be defined. Neglecting this preliminary work cancreate ambivalence and confusion in the valuation process,undermining the legitimacy of the result.

In addition, data are often sparse, knowledge of processeslimited, and management actions change the system beingmanaged, making inevitable the presence of surprise and change[90]. In these cases, the ability to incorporate and manage differentdata sources in a modelling process becomes essential. It isimpossible to be certain about the consequences of any environ-mental management decision [91] and qualitative approachesbecome essential for including the best available information[92,93]. This avoids excessive assumptions and forecasting of data,increasing the transparency of the decision-making process [68].

The information yielded in this process is represented ina multi-criteria impact matrix (Table 4) which allows:

1. Structuring of all the information in a simplified way;2. Reflection of the diversity of impacts according to different

type of information, i.e. fuzzy, crisp, ordinal or qualitative;3. Comparison of each alternative according to their strengths

and weaknesses in an illustrative manner;4. Analysis of criteria (objectives, values) supporting choices.

In the following lines we present briefly the scoring procedurewe follow to fulfil this impact matrix.

4.2.3.1. Employment. This criterion assesses the number of jobscreated (or eliminated) in the area under each management option.In order to take into consideration the duration of the jobs (i.e. theirseasonality and/or temporality) we have decided to use people peryear as the unit of measurement. Among others we have assessedpotential impacts on the workers of the shipyard; environmentalguides; staff at the bird watching centre and at hostels (Table 5).

4.2.3.2. Local income. This criterion evaluates the income derivedfor eachmanagement proposal and its distribution. The evaluationsare in qualitative terms due to the lack of reliable quantitative dataand the uncertainty involved in this sort of calculation. To obtainthe scores of these criteria we take into account the followingconsiderations:

A1: this does not include any initiative to promote economicactivity and in contrast the lack of conservation measures tomediate the present environmental problems, mainly propa-gation of invasive species, would affect current economicactivities such as providing environmental guides or benefitingfrom tourism. Therefore it gets the worst score in both sub-criteria.A2: the difference with respect to option A1 is that thismanagement option considers compensation mechanisms forthe shipyard, due to a ban on dredging, which increases thepossibility of gradually adapting its current. This would avoidhigher losses for the shipyard activities but would only benefitthe municipality of Murueta.A3: in this case all the municipalities would benefit from the fitout works to restore the area. In addition other municipalitieswould obtain incomes coming from the regulated moors.Moderate incomes and high distribution were assigned to thisoption. Ta

ble

4Im

pactmatrixforaltern

ativeman

agem

entop

tion

sin

theUrdaiba

iEstuary.

Criteria

Units

Dir

Alternatives

A1

A2

A3

B1

B2

B3

B4

C1

C2

C3

C4

Employm

ent

Peop

le/yea

rMax

031

.541

.897

.77

97.77

97.77

97.77

79.11

83.11

76.86

83.11

Localinco

mes

Ordinal

Max

5�4�

2�3�

3�3�

3�1�

1�1�

1�

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ofactivities

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1�8�

7�7�

6�5�

3�4�

2�

Costof

implemen

tation

VMin

02.44

2.33

06.18

6.62

44.92

5.81

94.92

5.81

94.92

5.81

94.92

5.81

95.32

5.34

75.32

5.34

75.32

5.34

75.32

5.34

7En

vironmen

tal

disturban

ceOrdinal

Min

3�1�

3�4�

4�4�

4�2�

2�2�

2�

Impacton

hab

itat

andfauna

Synthetic

index

Min

1327

1327

1455

1064

1200

1193

1202

1203

1311

1303

1289

Stab

ility

Ordinal

Max

3�3�

7�9�

8�6�

5�4�

4�4�

2�

Uncertainty

Qualitative

Min

Mod

erate

Mod

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Low

VeryHigh

VeryHigh

VeryHigh

VeryHigh

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High

High

High



B1, B2, B3, B4 are equal in terms of income and include incomescoming from motor vehicle taxes, business taxes and propertytaxes derived from the shipyard which would account for 8000V to 10,000V per year (moderate). The distribution is low as theonly council to benefit would be Murueta and other councilswould suffer decline in their incomes due to the impact ofdredging activities on surfing, fishing or tourism.C1, C2, C3, C4 are also equal in these terms. These managementoptions are similar to A3 but in addition to the conservationmeasures included in A3 they consider a “minimum dredging”that would make possible the navigation of small boats andcertain activities of the shipyard within the limits of thesurrounding system. That means that the industrial activitywould have to readjust to the construction of boats that requiredless depth in the channel. All in all these alternatives obtain highincomes and moderate distribution.

To aggregate the scores of both sub-criteria, we use the NAIADE(Novel Approach to Imprecise Decision Environment) method (seeSection 4.3.1.), which gives us an ordinal raking of alternatives bymeans of fuzzy set comparison among the sub-criteria (Table 6).

4.2.3.3. Compatibility between socio-ecological activities. To esti-mate the score of these criteria, first we identified the main uses inthe UE (first column) and then based on the existing informationand a consultation process, we defined the degree of compatibilityfor each activity within each scenario as the set of sub-criteria. Thedegree of compatibility goes from Very Low (VL) to Low (L),Moderate (M), High (H) or Very High (VH).

In this way, we carry out a multi-criteria evaluation of themanagement options based on the following set of sub-criteria:

(a) Compatibility with shell fishing(b) Compatibility with industry(c) Compatibility with conservation(d) Compatibility with surfing,(e) Compatibility with tourism(f) Compatibility with navigation.

In order to assign values to these sub-criteria we consider thefollowing factors:

� An intensification of dredging would increase the hydraulicpotential of the channel and could be responsible for the siltingup of secondary channels, altering oxygen supply and nutrientfluxes, and affecting the flora, fauna and habitats and, conse-quently, economic activities such as fishing and shell fishing[94,95]. The deposition of the sediments would also affect theconfiguration of Mundaka’s sandbar and thus the surfing andtourism associated with this [96,97].

� Massive dredging activities would also affect safety in naviga-tion due to sudden changes of currents.

� Conservation interests would be affected by dredging andbenefited by habitat recovery plans, the creation of guardservices or eradication of invasive species.

� Industrial activity in the UE depends on the shipyard andwhether or not to dredge is the determining factor in this sense.

Aggregating the impacts on these sub-criteria by means ofNAIADE, we obtain the ranking presented in Table 7.

4.2.3.4. Cost of implementation. The costs are estimated in eurosand include the cost of all the interventions considered in eachalternative for the following 10 years (Table 8).

A1 does not include any intervention and therefore does notimply any cost.A2 considers compensations for the shipyard workers due torestriction of their activities and according to the current labourlegislation the compensation framework that has been consid-ered would cost around 2,442,330 V.A3 includes: (a) conservation and recovery plans for around 160ha of the estuary and transferring the cost of similar plans in thearea the cost of this actuation would be around 1,961,624 V;eradication of invasive species (78 ha completely affected and100 ha partially), 2,560,000 V; maintenance service to conservethe environmental value of the estuary, 990,000 V and guardservice, 675,000 V.B1, B2, B3 and B4 include the cost of maximum dredging,3,500,000 V and the removal of polluted material derived fromthe dredging activity, 1,425,819 V. This cost has been reachedtaking into account the cost of similar actuations in the past.C1, C2, C3 and C4 include: conservation measures in 138 ha,1,657,024 V; eradication of invasive species in 78 ha completelyaffected, 1,560,000 V; maintenance service, 990,000 V andguard service 675,000 V.

4.2.3.5. Environmental disturbance. Several studies show that giventhe limited human resources available in the Reserve to fulfil theexisting legal restrictions, the estuary is the focus of many unde-sirable practices that disturb the environment of the area [98]. Weunderstand as a perturbation those incidents that alter the calmenvironment of the area, like the noise or the inflow of people inareas of high sensitivity that negatively affect the presence of manyspecies.

Table 5Impact on employment (unit: people per year).a

Jobs A1 A2 A3 B1 B2 B3 B4 C1 C2 C3 C4

Benefited 0 0 26.3 0 0 0 0 19.3 19.3 19.3 19.3Damaged 127.5 96 112 29.7 29.72 29.727 29.72 67.6 63.6 69.9 63.6Rescaled 0 31.5 41.8 97.77 97.77 97.77 97.77 79.11 83.11 76.86 83.11

a The results have been rescaled, to facilitate the interpretation, comparing all alternatives with the non-intervention scenario, A1.

Table 6Impact on income

Income A1 A2 A3 B1;B2;B3;B4 C1;C2;C3;C4

Amount 0 Low Moderate Moderate HighDistribution 0 Low Moderate Low ModerateOrdinal Rank 5 4 2 3 1

Table 7Compatibility among socio-economic activities.

Activities A1 A2 A3 B1 B2 B3 B4 C1 C2 C3 C4

Shell fishing H H H VL VL VL L L L L MIndustry N L N M H H H L L L LConservation VL VL H VL VL VL VL L M M MSurfing H H H VL VL VL VL L L VL VLTourism VL VL H VL VL VL VL M M M MNavigation L L L VL VL VL L VL M M HOrdinal ranking 5 4 1 8 7 7 6 5 3 4 2



Therefore, in this case we consider the following sub-criteria inorder to assess the environmental disturbance.

(a) Noise(b) Frequency (due to dredging and navigation)(c) Perturbations: massive tourism and trekking, uncontrolled

navigation with boats, kayaks etc., the presence of dogs inforbidden areas.

These sub-criteria have been evaluated in qualitative termsaccording to the level of activity expected in each managementoption. It follows the aggregation of the sub-criteria by means ofNAIADE, which gives the following results (Table 9).

4.2.3.6. Impact on habitat and fauna. This criterion is evaluatedaccording to the following index:

IHFjX

jðwB � VHBþwH � VHHþwR � VHRÞji � AHBi

where IHFj is the Impact on Habitat and Fauna index of themanagement option j, and i represents the different habitats withinthe estuary (i.e. cliff, sub-tidal rock, intertidal rock, intertidal sandand mud, beach, supra littoral rock, intertidal sand, intertidal mud,dune vegetation, estuarine water, marsh, freshwater habitats,riverine wood, artificial habitats and areas for future restoration).

Each habitat type is evaluated based on three components:

� VHB is the value of the habitat as a breeding, resting or feedingarea both for passing and for sedentary birds [99];

� VHH is general habitat value, keeping in mind the presence ofspecies or areas of high value, the biodiversity and the singu-larity and rarity in the area [100];

� VHR is the potential of the habitat regarding exploitableresources, mainly fishing and shell fishing [101].

For each scenario andhabitat, each sub-criterionwas scored from0 to 2 (0 for low value; 1 for intermediate value; 2 for high value).

In this case, each sub-criterion is also weighted according to itsrelative importance. To attach these values we take into accountthat the Urdaibai Estuary is especially important for its variety ofestuarine habitats, holding species of high ecological value. Thearea is also of relevance for wintering and migratory birds. Finally,

some exploitable resources (e.g. shellfish) have considerable socialimportance, although in economic terms their contribution is notso significant. Along these lines we considered that VHH is moreimportant than the value of the habitat as a breeding, resting orfeeding area, and VHB is considered more relevant than VHRtaking into account its international importance for migratorybirds. With this in mind we consider the following weights:wH>wB>wR, where wH¼ 3, wB¼ 2 and wR¼ 1. Finally, eachhabitat i is also weighted according its side, multiplying the sumof weighted sub-criteria by the corresponding area in eachscenario.

This global sumprovides uswith aqualitativehierarchy, orderingthe scenarios frommore valuable to less valuable in terms of impacton habitat and fauna. The results are presented in Table 10.

In this assessment, it is generally observed that the magnitudeof the impact will depend mainly on the dredged volume, thelocation of the disposal area of dredged sediments and the resto-ration works that would be undertaken.

4.2.3.7. Stability. We approach the issue of stability by assessing inqualitative terms the time that the system would require to getback to a stable situation. In order to do so we have integrated twovariables: morphodynamic and ecological stability. This criterionhas been widely ignored in the past although it encompassesa standard element of sustainability [102].

In morphodynamic terms, there is no impact in the first twoalternatives (A1, A2) and assuming that currently the estuary is innatural equilibrium we assign them the optimum value. The third

alternative (A3) includes a modification that could affect thedynamics of the system, with an increase in the intertidal area ofthe estuary and therefore in the tidal prism. However as: (a) theexpected increase in the tidal prism does not exceed 10% (withinthe range of natural variability); (b) the interventionwill take placeprogressively over a range of 10 years, giving enough time for thesystem to adapt; and (c) in any case the proposed modificationswould enhance the stability of the main morphologic elements andtherefore the equilibrium of the system, this alternative is alsoconsidered as optimal.

B1, B2, B3, and B4 get the worst scores. All of them implicateimportant sediment movements (similar to the volume of the mainmorphological elements) over a very short period of time.

Despite the fact that alternatives C1eC4 represent an instanta-neous and important movement of sediment within the estuary,they can be compared with the natural oscillation (in volume) ofthemainmorphological elements due to cyclic natural variability inthe hydrodynamics (tides and wave climate). Therefore, thesealternatives obtain intermediate values.

The final score of each alternative also takes into account theintensity of the main dynamics in the affected area. Very intensedynamics would implicate a higher probability of reaching animportant disequilibrium state over a very short period of time,while slow dynamics let the system to absorb the changes. On theother hand, if the dynamics are too low the changes can becomeirreversible.

In ecological stability terms the best option is A3, because it doesnot touch any of the sensitive areas and it proposes actions to

Table 8Total cost of implementation.

Cost A1 A2 A3 B1; B2;B3; B4

C1; C2;C3; C4

Cost of implementation (V) 0 2442.330 6186.624 4925.819 5325.347

Table 9Environmental disturbance.

Env. disturbance A1 A2 A3 B1;B2;B3;B4 C1;C2;C3;C4

Level of noise Moderate Moderate Low High ModerateFrequency of noise Moderate Moderate Low Moderate ModerateOther perturbations High High Low High LowOrdinal Ranking 3 1 3 4 2

Table 10Impact on habitat and fauna.

A1 A2 A3 B1 B2 B3 B4 C1 C2 C3 C4

Impact on habitat and fauna (IHF)a 1327 1327 1455 1064 1200 1193 1202 1203 1311 1303 1289Ordinal ranking 2 2 1 10 8 9 7 6 3 4 5

a The final values have been re-scaled dividing the final scores by 100,000 for each of the management options.



restore the equilibrium in those areas covered by invasive speciesor sequestrated to the marsh. Then, in alternatives C the amount ofmaterial removed is small enough to let the system recover quiterapidly, and it also has the recovery plan to eradicate invasivespecies. A1 and A2 get medium scores due to propagation ofinvasive species. The rest obtain the worst scores, due to theamount of the removed and deposited materials and for the lack ofmeasures to deal with exotic species.

Finally the (ordinal) criterion score for each alternative isobtained by aggregating those sub-criteria by means of NAIADE(Table 11).

4.2.3.8. Uncertainty. The corresponding qualitative scores havebeen obtained as a result of an intense dialogue among the localstakeholders (fishers, surfers, etc.) and an interdisciplinary group ofresearchers that addressed the following sources of uncertaintywith regard to the different management options5:

(a) Although in recent years there has been a considerable prog-ress in monitoring the dynamics of this system [96], theresponse of the estuary in the presence of major alterations isstill enigmatic. We do not know with certainty the morpho-logical response of the system due to changes in the sedimentdistribution or changes in the tidal prism.

(b) In ecological terms, material removal might pollute the envi-ronment due to the presence of polluted sediments but itsimpact is uncertain [103]. In our study area these factors havenot been studied consistently but the presence of heavy metalsis recognized by many studies [104e107].

(c) The presence and potential propagation of invasive speciesconstitutes another source of uncertainty in our study, as itdepends on many uncontrollable factors (changes in temper-ature, sea level rises, etc.).

According to all these factors those scenarios that imply moresediment removal obtain the worst scores and among those alter-natives that do not consider any dredging activity, discrimination isdone considering the presence or not of measures to deal withinvasive species (Table 12).

We want to remark that other sources of uncertainty associatedwith the rest of the criteria have been addressed using qualitativeand ordinal evaluations, combining the scientific knowledge of theresearch team and the knowledge of those participants involved inthe evaluation process.

4.3. Third phase: evaluating

4.3.1. Selection of the multi-criteria method and application of themathematical aggregation algorithm

Once the impact matrix has been completed (i.e., informationstructured in a multi-criteria way), one can analyze the informationcontained in it and/or aggregate the criterion scores by means ofa mathematical algorithm in order to yield a set of orderings ofalternatives (i.e., rankings). As mentioned above, there arehundreds of mathematical algorithms to solve multi-criteria anal-ysis problems and the desirable properties in the context ofsustainability issues have been already discussed elsewhere.

According to Munda [51,65,108] the multi-criteria aggregationmethod should:

� Be as simple as possible to guarantee transparency among thecounterparts;

� Be non-compensatory. Very good performances in somecriteria can offset bad performances in other criteria and a non-compensatory method doesn’t allow such a counterbalancebetween very good and bad performances;

� Use methods that include indifference and preference thresh-olds, which imply considering the intensity of preferences6;

� Use of weights as importance coefficients. Note that the mix ofintensity of preference and weights7 leads to compensationand trade-off between criteria, and therefore in these cases toavoid compensability we have to consider weights with ordinalcriterion scores.

In this study, we applied the NAIADE method, developed in theJoint Research Centre of the European Commission by GiuseppeMunda [109], to aggregate the evaluation criteria and to obtaina ranking of alternatives. The main advantage of NAIADE is itsability to deal with mixed information (i.e., qualitative and quan-titative simultaneously).8 Another advantage is that it alsoconsiders intensity of preferences in the aggregation procedure andallows the analyst to manage the degree of compensation betweencriteria (from non-compensatory to completely compensatory).Unfortunately, NAIADE does not use weights and, therefore, theprioritization of dimensions (socio-economic, socio-ecological, etc.)depends on the number of criteria within each dimension. In ourcase, to reach a balance between dimensions, we use the samenumber of criteria in each dimension.

In operational terms, NAIADE is an outranking method andconsequently its aggregation procedure works as follows:

(1) Pair-wise comparison of alternatives by means of preferencerelationships. Indifference and preference thresholds have tobe defined for this task;

(2) Calculation of preference intensity indexes, which indicate howmuch better or worse one alternative is in respect to another.NAIADE calculates the number of criteria in favour of one

Table 12Degree of uncertainty.

A1 A2 A3 B1; B2; B3; B4 C1; C2; C3; C4

Uncertainty Moderate Moderate Low Very high HighOrdinal ranking 2 2 1 4 3

Table 11Impact on stability.

Stability A1 A2 A3 B1 B2 B3 B4 C1 C2 C3 C4

Morphodynamic VH VH VH M L L L H H H HEcological M M VH VL VL L M L M M HOrdinal Ranking 3 3 1 7 9 8 6 5 4 4 2

VH, very high; H, high; M, moderate; L, low; VL, very low.

5 Note that other sources of uncertainty are already addressed in the way that hasbeen adopted to estimate the impact of each criterion.

6 The indifference threshold is the maximum difference between the criterionscores of two alternatives that makes no difference between them (under thatcriterion). The preference threshold is the minimum difference between theperformances of two alternatives in one criterion that makes one option preferableto another.

7 On the one hand, weights as importance coefficients reflect the relativeimportance e given by the decision-maker, the analyst or the social actore of onecriterion in relation to the others. On the other hand, weights as trade-off reflect thesubstitution rate among criteria.

8 For a detailed review of other methods able to deal with this type of infor-mation see Gomiero and Giampietro [90].



alternative with respect to another and the intensity ofpreference;

(3) Aggregation of preference intensity indexes and calculation oftwo indexes. One index indicates how one alternative is betterthan all other alternatives, and the other indicates how thealternative is worse than all other alternatives;

(4) Obtaining the ranking of alternatives, based on the comparisonof the two indexes calculated in the previous step.

It is important to highlight that several factors influence therankings of alternatives, e.g., the quality of the information and dataused, and the criteria or indicators chosen for the evaluation or thecriteria aggregation method (mathematical model). In other words,the result of the multi-criteria analysis will depend on the structureof the problem. Public participation plays a key role in qualitycontrol for: (i) the definition of the problem; (ii) the informationused in the assessment; and (iii) the calculation of criterion scores.

5. Results

5.1. Ranking of alternatives

In this case, by applying the NAIADE method we obtain thefollowing results according to the different degrees of preference(first column) and the degree of rejection (second column) of eachalternative. That is, the ranking in the first column (left) is basedupon the number of criteria in favour of an alternative. The secondranking from left to right is based upon the number of criteriaagainst the alternatives. The third ranking from left corresponds tothe intersections of the previous ones.

Alternative A3, which involves the biggest number of conser-vation measures and different mechanisms for the complementa-tion of the existing law, gets the best score togetherwith alternativeC4 (minimum dredging, deposition of the sediments in the sub-tidal north part of the estuary accompanied by conservationmeasures). The former obtains the first position among all alter-natives with regard to compatibility, impact on habitat and fauna,reversibility and disturbance, and second in terms of income andemployment. It gets the worst scores in terms of cost andemployment. The latter, although it does not get the first position,shows a good average performance in most criteria and is notpunished with a bad score in any particular one.

In second place are options A2 and C2. C3, A1 and C1 obtainmiddle values and in the worst position are all the alternatives thatconsider the maximum dredging: B4 and B2 followed by B1 and B3respectively. The bad performance of these alternatives is due to theimpact they have on habitat and fauna, as well as socio-economicactivities, and the great uncertainty and disequilibrium that theyimply for the system. Their positive aspect is confined to job crea-tion. A lowamount of income and a high cost of implementation areother common characteristics of these latter alternatives.

One characteristic of outrankingmethods like NAIADE (based onpair-wise comparison) is the possibility of rank reversal, meaningthat despite the fact that one alternative is better than anotheraccording to most of the criteria; their position in the final rankingcould be reversed or equal.9 Therefore, it is sometimes necessary toreview the results of the pair-wise comparisons (e.g., when two ormore alternatives are sociably acceptable and obtain a similarposition in the ranking).

To clarify this point, in Fig. 5 we illustrate the pair-wisecomparison of alternatives A3 and C4, which obtain both the firstposition in the ranking. The (brown) bar graphs on the right showthedegree of credibility that one alternative (in this case A3) ismuchbetter (�), better (>), almost equal (¼w), equal (¼), worse (<) and/or much worse (�) than the other alternative (in this case C4). Thehorizontal red line in the graph indicates the degree of credibilitydetermined by the preference thresholds (see Section 4.3.1).

As we can see in Fig. 5, A3 is much better than C4 under criteriaC6 and C8 (brown bars in the upper-right graphic of Fig. 4). Also, A3is better than C4 under the same criteria (second bar graph fromabove). Both alternatives are almost equal under criteria C3 and C7,and are equal under criterion C3. A3 is much worse (and worse)than C4 in criterion C1.

These are the results obtained from a more technical perspec-tive, but as we have already remarked, considering differentstakeholders’ perspectives and potential conflicts is an essentialpart of public policies related to complex socio-ecological systems.For this reason, in addition to integrated assessment processes thatcan capture the complexity of the issue at hand from multipleperspectives, it is useful to perform a conflict analysis.

5.2. Conflict analysis: searching compromise solutions

This analysis highlights plausible conflicts among the differentstakeholders. By mapping winners and losers and making explicitthe trade-off between different interests, this analysis provides richinformation in the search for compromise solutions. In sustain-ability policy related issues, distributional issues are a key questionwhen it comes to reaching a sound decision. In this sense, for thesustainable management of natural resources in general andcoastal zones in particular, participatory approaches appear to be ofkey importance. These processes can help to address conflictingareas, build bridges between confronted interests and achieve theco-evolution of stakeholder preferences. In this case to structurethe dialogue between the affected parties and help in the search forshared goals and compromise solutions, we developed an ad hocanalysis of potential coalitions by means of an eclectic approachthat uses concepts coming from land use planning, fuzzy clusteranalysis and social choice [65,110,111].

The first step to performing this analysis consists of theconstruction of the equity matrix (Table 13). In this table we mapthe preferences of each interest group with regard to eachalternative.

Fig. 4. Ranking of alternatives.

9 Outranking methods works as a soccer league, in which each team play withthe rest of the participants. The final position of a team depends on the results ofthe games between this team with the rest of the teams and the results of all othergames.



Fig. 5. Pair-wise comparison of alternative A3 and C4.

Table 13Social impact matrix.

Social actors Al A2 A3 B1 B2 B3 B4 C1 C2 C3 C4

Bird watchers Good Good Very good Extremelybad

Extremelybad

Extremelybad

Extremelybad

Bad Moderate Bad More lessbad

Fishers Good Good Very good Extremelybad

Extremelybad

Extremelybad

Very bad Extremelybad

Extremelybad

Very bad More Lessbad

Surfers Good Good Very good Extremelybad

Extremelybad

Extremelybad

Extremelybad

Very bad Very bad Very bad Bad

Busturia Council Very bad Very bad Perfect Extremelybad

Very bad Moderate Good Extremelybad

Bad Good Perfect

Murueta Council. Extremelybad

Extremelybad

More lessbad

More lessgood

Good Very good Perfect Bad Bad Bad Bad

Recreational boats More lessgood

More lessgood

Good Extremelybad

Extremelybad

Very bad Perfect Very bad Extremelybad

Extremelybad

Perfect

Shipyard workers Very bad Very good Very bad More lessgood

More lessgood

Mora lessgood

Very good Moderate Moderate Moderate Moderate

Head CoastalManagement

Good Very good Perfect Extremelybad

Very bad Very bad Very bad Bad Bad Bad Bad

Env. Ministry (ReserveDirector)

More lessbad

Good Vary good Extremelybad

Extremelybad

Extremelybad

Extremelybad

Bad Bad Bad Bad

Dune Recovery Good Good Perfect Extremelybad

Very bad Very bad Very bad Bad Bad Moderate Moderate

Environmental Guides More lessgood

Very good Perfect Extremelybad

Extremelybad

Extremelybad

Extremelybad

Extremelybad

Bad Very Bad More lessbad

Arteaga Council Moderate Moderate Vary good Extremelybad

Extremelybad

Very bad Very bad Bad Moderate Bad Moderate

Ekologia Tailerra (NGO) Bad Very good Perfect Extremelybad

Extremelybad

Extremelybad

Extremelybad

Extremelybad

Extremelybad

Extremelybad

Extremelybad

Shipyard Owners Extremelybad

Moderate Extremelybad

More lessgood

More lessgood

Good Perfect Bad Bad Bad Bad

Head Harbors Good Good Good Extremelybad

Extremelybad

Extremelybad

Extremelybad

Moderate Moderate Moderate Moderate



In order to do so, we asked each of the identified interest groupsabout their preferences regarding each management option, basedon qualitative terms: extremely good, very good, good, more or lessgood, moderate, more or less bad, bad, very bad to extremely bad.10

Then, through a sequence of mathematical reductions, we usedNAIADE to build a dendogram of coalition formation. Fig. 6 showsthe potential coalitions and the degree of credibility of theiroccurrence (the number on the left in Fig. 6).

For instance, there is aquitehighdegreeof credibility (0.775) thatsurfers (G3), environmentalists (G11) and Head of Coastal Manage-ment (G8) will form a coalition, given the fact that a stable systemserves the interest of each of these groups. Environmentalistswouldview as negative any destabilization of the system that could affecthabitats and damage the environmental properties of the estuary;surfers desire stability because anychanges to theMundaka sandbarcould alter surfing possibilities; and managers prefer to avoid thepotential conflicts and social tensions that disruption could cause (ashas happened in the past). Surprisingly, the diverse interest groupsthatwere in opposition at the beginning of the participatory processhad acknowledged their common interests by the end. An interac-tive process that allowed better understanding of the complexdynamics in the estuary helped to create a common space andpossibilities for compromise solutions. Comments like thefollowing, by a Mundaka surfer, are one example of those we heardseveral times during the last phase of the process:

“We saw fishermen and birdwatchers as enemies, and now weknow that we share a lot of interest. We should row in the samedirection” (Personal communication with surfer).

In the other hand, other coalitions have less degree of credibilityand are unlikely to form, according to the results of our study. Forexample, there is a very low probability (0.360) that shipyardworkers (G7), shipyard owners (G14) andMurueta Council (G5) willform a coalition with other stakeholders. These three interestgroups depend on industrial activity in the estuary to satisfy theirneeds: industry provides employment for shipyard workers; itguarantees the viability of the enterprise; and it provides incomethrough taxes for the Murueta Council. However other social actorssee their interests threatened by the shipyard. The rejection ofindustrial activity by the other interest groups was remarkable

during the participatory process. The assessments also elucidatedthe incompatibility between current shipyard activity and otheruser group interests. Adapting the shipyard to work with smallerboats, which do not require as deep canals as do the current ships, isthe only foreseeable way to make multiple interests compatible.However, this seems rather improbable due to the high competi-tion in international markets, where European shipyards faceserious difficulties to compete with Asian constructors. Reducingthe shipyards’ potential market to small boats could threaten itseconomic viability.

In any case, it is worth noting that to reach this type ofconclusions it is relevant to validate the information gathered inthis questionnaire with the information that is collected in theprevious interviews in the institutional analysis and during thewhole process. A quality check control confronting different sour-ces of information can help to identify and minimize the presenceof strategic behaviour and draw a more realistic picture.

From here, we can also obtain the ranking of alternativesaccording to the different coalitions, and look for possible conflictsof interest and their sources. The image below shows the ranking ofthe coalitions derived from the coalition dendrogram with a coin-cidence degree of 0.696 (quite high). (Table 14)

In overall from these results (Fig. 6 and Table 14) it is observedthat the coalition formed by Environmental NGO (G13), Head ofBiosphere Reserve-Basque Environmental Ministry (G9), guides(G11), surfers (G3), Head of Coastal Affairs e Spanish Environ-mental Ministry (G8), birdwatchers (G1), dune recovery supporters(G10) and the Fisheries Association (G2), prefers managementoption A3, whichwas also the best option according to the technicalanalysis (see section 5.1). This is also the best option for the Head ofHarbours e Basque Ministry of Transport (G15), Arteaga (G12) andBusturia Council (G4), which have a different ranking of alterna-tives but agree on the first option. This option would be rejected bythe owners of the shipyard (G14), its employees (G7) and MuruetaCouncil (G5), because it implies restrictions on their activities andlosses in the employment and income derived from it. For repre-sentatives of recreational boats alternative A3 is the second-bestoption after a minimum dredging option. In any case from thisanalysis we could state that all management options that considermaximum dredging would be vetoed by the vast majority ofstakeholders, regardless of the deposition site. In the middle wefind alternatives A2 and C4 followed by C2 and C3. These alterna-tives, although not among the preferred ones for themajority of the

Fig. 6. Coalition formation dendrogram.

10 NAIADE uses this scale by default.



identified groups, are not rejected by anyone and might encompassa compromise solution or a second-best option.

5.3. Sensitivity analysis

Sensitivity analysis is an important feature of this type of eval-uation to check the robustness of the results [112].

The objectives of sensitivity analysis are (at least) threefold:

� To deal with uncertainties in data, assumptions and calcula-tions, among other things, and check their influence on theresults.

� To check the influence of changing model’s parameters in theresults;

� To check the influence of different prioritizations of criteria(i.e., weights) in the results.

In this case, we have dealt with uncertainties in the evaluationprocess (data, assumptions and calculations) by using qualitative,ordinal and fuzzy evaluations. Since NAIADE does not use weights,we have carried out the sensitivity analysis by changing parametersof the model: in this case, we have changed the degree ofcompensation between criteria.

Our results show that the ranking is quite stable when changingthe degree of compensation in the evaluation. Alternative A3remains in the first position, followed by C4, A2 and C2. The worstpositions are for those alternatives that contemplate a maximumdredging to satisfy the needs of industry B1, B2, B3 and B4respectively.

6. Discussion and conclusions

This paper explores the potential of Social Multi-Criteria Eval-uation, in the context of Integrated Coastal Zone Management.Starting from a real conflict in a coastal zone that pertains toa Biosphere Reserve, this paper shows how to structure, ina systematic way, complex and uncertain issues characterized byhigh degrees of conflict, by means of a well grounded analytical

framework such as MCE. This analytical method has been appliedwith the support of participatory approaches that integratea diverse group of scientists with different knowledge and a diversegroup of stakeholders that represent the multiple interests andvalues in the society. The Biosphere Reserve of the Urdaibai Estuaryin northern Spain has been used as a pilot case study to validate thisapproach in the context of ICZM.

Like in many other coastal systems, in this case, most of theprevious research has been focused on mono-disciplinary and top-downapproaches thatneglected themultidimensional anddynamicnature of this complex socio-ecological system. As a consequence,despite the huge amount of financial and human resources investedin the past, policy makers and natural resources managers have notbeen able to tackle the continuous deterioration of the area.

In these areas the institutional aspects, environmental dynamics,socio-economic processes and cultural values are coevolving overtime and their management faces conflicts, uncertainty andsurprises, making it necessary to abandon the expectation to finda global steady state. Decision-making in coastal systems requiresa shift to an adaptive and evolutionary approach, trying to capturethe complexity of the system frommultiple perspectives.

According to GESAMP (Group of Experts on the ScientificAspects of Marine Environmental Protection), ICZM is: “a contin-uous and dynamic process that unites government and thecommunity, science and management, sectoral and public interestsin preparing and implementing an integrated plan for the protec-tion and development of coastal ecosystems and resources” [3]. Assuch this process requires flexible approaches capable of inte-grating the best knowledge in an inclusive manner, and SMCEencompasses a promising framework to foster this shift.

Any adaptation which enhances a specific optimization processof an individual subsystem could fail to enhance the resilience e

the capacity to buffer perturbations e of the whole system [57] andpolicies for sustainable development cannot rely on the notion ofoptimal solutions based on a single measurement; the most likelybeing of course economic efficiency [102]. Instead collaborativelearning processes that consider the multiple aspects of the issue athand appear to be of central importance for social-ecological

Table 14Coalition rankings at 0.696 coincidence degree.



systems to build resilience [113]. From this perspective, an adaptivemanagement approach treats policies as hypotheses, andmanagement as an experiment from which managers can learn,accepting uncertainty and expecting surprises [114]. Under thisview it is also acknowledged that flexible social networks andorganizations that proceed through learning-by-doing are betteradapted for long-term survival than are rigid social systems thathave set prescriptions for resource use [115].

Following these statements and foreseeing practical applicationto a real case, in this paper, we hypothesize that for a shift towardan integrated coastal zone management, efforts should draw ona broader set of knowledge domains that are represented in a singlediscipline and guarantee the inclusion of a wider public in a deci-sion-making process. With this case study we have shown how tomake operational this claim in the real world. Through a two-yearcollaborative research process, between an interdisciplinary groupof researchers and a diverse group of stakeholders, we show thatimproving the integration of diverse expertise and values can lead,through a mutual learning process, to the definition of relevantpolicy options and sound decisions in the face of great complexities,value conflict and unavoidable uncertainty.

In this sense the scope of the SMCE process presented here goesbeyond the search for an optimum solution and it follows the ideaof procedural rationality which is emphasized in the quality of thedecision-making process itself [60,116,117]. It encompassesa mutual learning routine among scientists and non-scientists thatbesides improving the knowledge of the system, open ups thepossibility to reframe the issue at hand in an adaptive mannerwhile creating opportunities for a shared understanding, jointaction and the search for compromise solutions. Note that here theemphasis is on compromise and not on forcing consensus, sinceignoring the negotiation dimension of participatory approachesmight erode their legitimacy and effectiveness as a learning processto solve complex socio-ecological issues [118].

Summarizing, the whole participatory integrated assessmentframework developed within this case study was shown to be

� dynamic in a way that included continuous feedback loopsamong all the counterparts and was open to a continuousprocess of reframing the issue at hand

� able to allow inclusion and deliberation among different actorswith different states in the assessment of alternativemanagement options

� integrated with respect to scientific disciplines but also withdiverse types of knowledge that were neglected to date

Notwithstanding, this pathway is not safe from difficulties.Building trust among different stakeholders, reframing our mono-disciplinary perspectives, becoming aware of the continuouschanges in our complex and interconnected socio-ecologicalsystems or the search for a common language among a diversegroup of social actors (including the scientific team) are only a fewof the main challenges we have faced in this process.

Other difficulties may emerge in the future if our choice is toshift ICZM towards a more holistic and inclusive partnership. Timefor reflection, open dialogue among all the counterparts and hugedoses of creativity are some necessary ingredients for this prom-ising scientific and socio-political journey.

Acknowledgements

We would like to acknowledge comments on a preliminaryversion of this paper presented at the Berlin Conference on theHuman Dimension of Global Environmental Change, 2008. Wewould also like to thank all participants who were involved in the

case study workshops for taking the time and for their contribu-tions. Assistance by Karmele Herranz and Arantzazu Urzelai is alsogratefully acknowledged. This study has been partially supportedby the ETORTEK program financed by the Basque Governmentthrough the project EKO-LURRALDEA (Sustainable SpatialManagement) and a Basque Government Research Group Grant(GIC07/56-IT-383-07).

References

[1] Hanna S, Folke C, Maler K- G. Rights to nature: ecological, economic, cultural,and political principles of institutions for the environment. Island Press; 1996.

[2] Barker A. Capacity building for sustainability: towards community devel-opment in coastal Scotland. Journal of Environmental Management 2005;75(1):11e9.

[3] Olsen S, Tobey J, Kerr M. A common framework for learning from ICMexperience. Ocean & Coastal Management 1997;37(2):155e74.

[4] Halpern BS, Walbridge S, Selkoe KA, Kappel CV, Micheli F, D’Agrosa C, et al. Aglobal map of human impact on marine ecosystems. Science 2008;319(5865):948e52.

[5] van den Hove S. Participatory approaches to environmental policy-making:the European Commission climate policy process as a case study. EcologicalEconomics 2000;33(3):457e72.

[6] Spash CL. Broadening democracy in environmental policy processes. Envi-ronment and Planning C-Government and Policy 2001;19(4):475e81.

[7] Leach WD, Pelkey NW, Sabatier PA. Stakeholder partnerships as collaborativepolicy making: evaluation criteria applied to watershed management inCalifornia and Washington. Journal of Policy Analysis and Management2002;21(4):645e70.

[8] Koontz TM. We finished the plan, so now what? Impacts of collaborativestakeholder participation on land use policy. Policy Studies Journal 2005;33(3):459e81.

[9] Videira N, Antunes P, Santos R, Gamito S. Participatory modelling in envi-ronmental decision-making: the Ría Formosa Natural Park case study. Jour-nal of Environmental Assessment Policy and Management 2003;5(3):421e47.

[10] Hermans LM. Exploring the promise of actor analysis for environmentalpolicy analysis: lessons from four cases in water resources management.Ecology and Society 2008;13(1).

[11] Pahl-Wostl C, Sendzimir J, Jeffrey P, Aerts J, Berkamp G, Cross K. Managingchange toward adaptive water management through social learning. Ecologyand Society 2007;12(2).

[12] Pahl-Wostl C, Craps M, Dewulf A, Mostert E, Tabara D, Taillieu T. Sociallearning and water resources management. Ecology and Society 2007;12(2).

[13] Pahl-Wostl C, Mostert E, Tabara D. The growing importance of social learningin water resources management and sustainability science. Ecology andSociety 2008;13(1).

[14] Fernandez-Gimenez ME, Ballard HL, Sturtevant VE. Adaptive managementand social learning in collaborative and community-based monitoring:a study of five community-based forestry organizations in the western USA.Ecology and Society 2008;13(2).

[15] Bowen RE, Riley C. Socio-economic indicators and integrated coastalmanagement. Ocean & Coastal Management 2003;46(3e4):299e312.

[16] Cicin-Sain B, Knecht R. Integrated coastal and ocean management: conceptsand practices. Island Press; 1998.

[17] White AT, Christie P, D’Agnes H, Lowry K, Milne N. Designing ICM projectsfor sustainability: lessons from the Philippines and Indonesia. Ocean &Coastal Management 2005;48(3e6):271e96.

[18] Christie P. Is integrated coastal management sustainable? Ocean & CoastalManagement 2005;48(3e6):208e32.

[19] Christie P, Lowry K, White AT, Oracion EG, Sievanen L, Pomeroy RS, et al. Keyfindings from a multidisciplinary examination of integrated coastalmanagement process sustainability. Ocean & Coastal Management 2005;48(3e6):468e83.

[20] GESAMP (Joint Group of Experts on the Scientific Aspects of Marine Environ-mental Protection). The contributions of science to integrated coastalmanagement. Food and Agriculture Organization of the United Nations; 1996.

[21] Saengsupavanich C, Chonwattana S, Naimsampao T. Coastal erosion throughintegrated management: a case of southern Thailand. Ocean & CoastalManagement 2009;52(6):307e16.

[22] Buanes A, Jentoft S, Runar Karlsen G, Maurstad A, Søreng S. In whoseinterest? An exploratory analysis of stakeholders in Norwegian coastal zoneplanning. Ocean & Coastal Management 2004;47(5e6):207e23.

[23] Buanes A, Jentoft S, Maurstad A, Søreng SU, Runar Karlsen G. Stakeholderparticipation in Norwegian coastal zone planning. Ocean & CoastalManagement 2005;48(9e10):658e69.

[24] Edwards SD, Jones PJS, Nowell DE. Participation in coastal zone managementinitiatives: a review and analysis of examples from the UK. Ocean & CoastalManagement 1997;36(1e3):143e65.

[25] Hegarty A. Start with what the people know: a community based approachto integrated coastal zone management. Ocean & Coastal Management1997;36(1e3):167e203.



[26] Davos CA. Sustaining co-operation for coastal sustainability. Journal ofEnvironmental Management 1998;52(4):379e87.

[27] Fletcher S. Stakeholder representation and the democratic basis of coastalpartnerships in the UK. Marine Policy 2003;27(3):229e40.

[28] Berkes F, Colding J, Folke C, editors. Navigating social-ecological systems:building resilience for complexity and change. Cambridge: CambridgeUniversity Press; 2003.

[29] Funtowicz SO, Ravetz JR. Uncertainty and quality in science for policy.Springer; 1990.

[30] Ravetz J, Funtowicz S. Post-Normal Science - an insight now maturing.Futures 1999;31(7):641e6.

[31] Funtowicz SO, Ravetz JR. Science for the post-normal age. Futures 1993;25(7):739e55.

[32] Smith G. Deliberative democracy and the environment. Routledge; 2003.[33] Guimaraes-Pereira A, Tognetti S, Guedes-Vaz S. Interfaces between science

and society. Greenleaf Publishing; 2006.[34] O’Connor M. Pathways for environmental evaluation: a walk in the

(Hanging) Gardens of Babylon. Ecological Economics 2000;34(2):175e93.[35] Kasemir B, Gardner M, Jäeger J, Jaeger C, editors. Public participation in

sustainability science. Cambridge, UK: Cambridge University Press; 2003.[36] Costanza R, Jorgensen SE, editors. Understanding and solving environmental

problems in the 21st century: toward a new, integrated hard problemscience. Oxford, UK: Elsevier Science; 2002.

[37] Gowdy J, Ohara S. Weak sustainability and viable technologies. EcologicalEconomics 1997;22(3):239e47.

[38] De Marchi B, Ravetz J. Participatory approaches to environmental policy. In:Spash C, Carter C, editors. Concerted action environmental valuation inEurope. Policy research brief no. 10; 2001.

[39] Isaacson P. Pollution regulation and public sensibility. Environmental ImpactAssessment Review 1986;6:229e32.

[40] Holling CS, editor. Adaptive environmental assessment and management.London: John Wiley & Sons; 1978.

[41] Rogers K. Managing science/management partnerships: a challenge ofadaptive management. Conservation Ecology [online] 1998;2(2):R1.

[42] van den Hove S. A rationale for science-policy interfaces. Futures 2007;39(7):807e26.

[43] Lee KN. Compass and gyroscope: integrating science and politics for theenvironment. Island Press; 1993.

[44] Baskerville GL. Advocacy, science, policy, and life in the real world. Conser-vation Ecology [online] 1997;1(1):9.

[45] Fiorino DJ. Citizen participation and environmental risk: a survey of institu-tional mechanisms. Science Technology &Human Values 1990;15(2):226e43.

[46] Laird FN. Participatory analysis, democracy, and technological decision-making. Science Technology & Human Values 1993;18(3):341e61.

[47] Webler T, Kastenholz H, Renn O. Public participation in impact assessment:a social learning perspective. Environmental Impact Assessment Review1995;15:443e63.

[48] Banville C, Landry M, Martel JM, Boulaire C. A stakeholder approach toMCDA. Systems Research and Behavioral Science 1998;15(1):15e32.

[49] Stagl S. Multicriteria evaluation and public participation: the case of UKenergy policy. Land Use Policy 2006;23(1):53e62.

[50] Stirling A. Analysis, participation and power: justification and closure inparticipatory multi-criteria analysis. Land Use Policy 2006;23(1):95e107.

[51] Munda G. Social multi-criteria evaluation: methodological foundations andoperational consequences. European Journal of Operational Research2004;158(3):662e77.

[52] Proctor W. MCDA and stakeholder participation e valuing forest resources.In: Getzner M, Spash C, Stagl S, editors. Alternatives for environmentalvaluation. Routledge; 2004. p. 134e58.

[53] Proctor W, Drechsler M. Deliverative multicriteria evaluation. Environmentaland Planning C: Government and Policy 2006;24:169e90.

[54] Messner F, Zwirner O, Karkuschke M. Participation in multi-criteria decisionsupport for the resolution of a water allocation problem in the Spree Riverbasin. Land Use Policy 2006;23(1):63e75.

[55] Holland A, O’Connor M, O’Neill J. Costing environmental damage: a criticalsurvey of current theory and practice and recommendations for policyimplementation. European Parliament STOA; 1996.

[56] Martinez-Alier J, Munda G, O’Neill J. Weak comparability of values as a foun-dation for ecological economics. Ecological Economics 1998;26(3):277e86.

[57] Rammel C, Stagl S, Wilfing H. Managing complex adaptive systems e a co-evolutionary perspective on natural resource management. EcologicalEconomics 2007;63(1):9e21.

[58] Schusler TM, Decker DJ, Pfeffer MJ. Social learning for collaborative naturalresource management. Society & Natural Resources 2003;16(4):309e26.

[59] Brugnach M, Dewulf A, Pahl-Wostl C, Taillieu T. Toward a relational conceptof uncertainty: about knowing too little, knowing too differently, andaccepting not to know. Ecology and Society 2008;13(2).

[60] Simon HE. From substantive to procedural rationality. In: Latsis JS, editor.Methods and appraisal in economics. Cambridge, UK: Cambridge UniversityPress; 1976.

[61] Roy B. Méthodologie multicritere d’ aide à la decision. Economica; 1985.[62] Dryzek JS. Deliverative democracy and beyond. liberals, critics, contestations.

Oxford University Press; 2000.[63] Figueira J, Greco S, Ehrgott M, editors. Multiple-criteria decision analysis.

State of the art surveys. New York: Springer; 2005.

[64] Montis A, De Toro P, Droste-Franke B, Omann I, Stagl S. Assessing the qualityof different MCDA methods. In: Getzner M, Spash C, Stagl S, editors. Alter-natives for environmental valuation. Routledge; 2004. p. 99e133.

[65] Munda G. Social multi-criteria evaluation for sustainable economy. Springer;2008.

[66] O’Neill J. Ecology, policy and politics. Routlege; 1993.[67] Gamboa G, Munda G. The problem of windfarm location: A social multi-

criteria evaluation framework. Energy Policy 2007;35(3):1564e83.[68] Gamboa G. Social multi-criteria evaluation of different development

scenarios of the Aysen region, Chile. Ecological Economics 2006;59(1):157e70.

[69] Roca E, Gamboa G, Tàbara JD. Assessing the multidimensionality of coastalerosion risks. Public participation and Multicriteria Analysis (MCA) ina Mediterranean Coastal system. Risk Analysis 2008;28(2):399e412.

[70] De Marchi B, Funtowicz SO, Lo Cascio S, Munda G. Combining participativeand institutional approaches with multicriteria evaluation. An empiricalstudy for water issues in Troina, Sicily. Ecological Economics 2000;34(2):267e82.

[71] Orive E, Santiago J, Villate F. Variabilidad de algunos parámetros físicos ybiológicos en la ría de Mundaka Cuadernos de area de ciencias mariñas,Seminario Estudios Galegos; 1984.

[72] Liria P, Garel E, Uriarte A, Collins MB. Effects of dredging operations on thehydrodynamics of an ebb tidal delta: Oka Estuary, Northern Spain. ContinetalShelf Research 2009;29(16):1983e94.

[73] Walton TL, Adams WD. Capacity of inlet outer bars to store sand. in:Proceedings of the 15th international conference on coastal engineering,New York; 1976. p. 1919e37.

[74] Marino JN, Mehta AJ. Inlet ebb shoals related to coastal parameters. NewYork, USA: Coastal Sediments; 1987. 1608e1623.

[75] Marino JN, Mehta AJ. Sediment trapping at Florida’s east coast inlets. In:Aubrey DaWL, editor. Hydrodynamics and sediment dynamics of tidal inlets.New York: Springer Verlag; 1988. p. 284e96.

[76] FitzGerald DM. Shoreline erosional-depositional processes associated withtidal inlets. In: Aubrey DG, Weishar L, editors. Hydrodynamics and sedimentdynamics of tidal inlets. New York: Springer-Verlag Inc.; 1988. p. 186e225.

[77] Gao S, Collins M. Tidal inlet equilibrium, in relation to cross-sectional areaand sediment transport patterns. Estuarine, Coastal and Shelf Science1994;38(2):157e72.

[78] Pallares J, Fernández Alonso L. Interrelación ser humano-entorno como ejeconductor para el aprovechamiento pedagógico del sector orientar de lacuenca de Urdaibai; 1992.

[79] Edeso Fito JM, Meaza Rodríguez G, Merino Gonzalez A, Ormaetxea Arenaza O.In: Amelia Gómez Villar JMGR, Vadillo José Arnáez, editors. Cambios en ladinámica geomorfológicas y sus repercusiones en los suelos y en la vegetaciónnatural a consecuencia de explotación forestal intensiva: El caso de la cabeceradel Maper-Sollube (Ría de Gernika e Urdaibai, Vizcaya). III Reunión de geo-morfología, Logroño: Geomorfología en España; 1994. p. 441e56.

[80] Meaza Rodríguez G, Cadiñanos Aguirre JA. Valoración de la vegetación. In:Meaza G, editor. Metodología y práctica de la Biogeografía. Barcelona:Ediciones del Serbal; 2000. p. 201e72.

[81] Juaristi Linacero J, Gogeascoechea A. Aprovechamientos históricos y priva-tización de las marismas del Urdaibai, vol. 20. Lurralde: Investigación yespacio; 1997. 169e189.

[82] Massam B. Multi-criteria decision-making techniques in planning. In:Diamond D, McLoughlin J, editors. Progress in planning. Oxford: PergamonPress; 1988. p. 1e84.

[83] Bouyssou D. Building criteria: a prerequisite for MCDA. In: Bana e Costa CA,editor. Readings in multiple criteria decision aid. Berlin, Heidelberg, NewYork: Springer; 1990. p. 58e80.

[84] Yoon K, Hwang C. Multiple attribute decision making: an introduction. Sage;1995.

[85] Bloomfield D, Collins K, Fry C, Munton R. Deliberation and inclusion: vehiclesfor increasing trust in UK public governance? Environment and Planning C:Government and Policy 2001;19:501e13.

[86] Pahl-Wostl C, Hare M. Processes of social learning in integrated resourcesmanagement. Journal of Community & Applied Social Psychology 2004;14(3):193e206.

[87] Tabara JD, Pahl-Wostl C. Sustainability learning in natural resource use andmanagement. Ecology and Society 2007;12(2).

[88] Pahl-Wostl C. Towards sustainability in the water sector e the importance ofhuman actors and processes of social learning. Aquatic Sciences 2002;64(4):394e411.

[89] Corral Quintana SA. Una metodología integrada de exploración y com-prensión de los procesos de elaboración de políticas públicas Departamentode Economía. Doctoral Thesis, Universidad de la Laguna; 2000.

[90] Walters CJ, Holling CS. Large-scale management experiments and learningby doing. Ecology 1990;71(6):2060e8.

[91] Henriksen HJ, Barlebo HC. Reflections on the use of Bayesian belief networksfor adaptive management. Journal of Environmental Management 2008;88(4):1025e36.

[92] Munda G, Nijkamp P, Rietveld P. Qualitative multicriteria evaluation forenvironmental management. Ecological Economics 1994;10(2):97e112.

[93] Gomiero T, Giampietro M. Graphic tools for data representation in integratedanalysis of farming systems. International Journal of Global EnvironmentalIssues 2005;5(3/4):264e301.



[94] Wilber DH, Brostoff W, Clarke DG, Ray GL. Sedimentation: potential bio-logical effects from dredging operations in estuarine and marine environ-ments DOER technical notes collection. Vicksburg: U.S. Army EngineerResearch and Development Center; 2005. 14.

[95] Dauvin JC. The main characteristics, problems, and prospects for WesternEuropean coastal seas. Marine Pollution Bulletin 2008;57(1e5):22e40.

[96] Cearreta A, Monge-Ganuzas MEI. Seguimiento morfodinámico de la desem-bocadura del estuario de Oka (Mundaka-Ibarrangelu, Reserva de la Biosferade Urdaibai): 2005e2006. Basque Government; 2006. 131.

[97] Murphy M. The impact of Surfing on the local economy of Mundaka, Spain.Marine Resource Management, Oregon State University; 2008.

[98] del Villar J, Garaita R, Prieto A. La Espátula en la Reserva de la Biosfera deUrdaibai: diez años de seguimiento. Gobierno Vasco: Departamento deMedio Ambiente y Ordenación del Territorio; 2007.

[99] García Plazaola JI. Estudio de la avifauna acuática de la Ría de Urdaibai:análisis crítico, unpublished; 1999. p. 134.

[100] Meaza Rodríguez G, Cadiñanos Aguirre JA. Valoración de la vegetación. In:Meaza G, editor. Metodología y práctica de la Biogeografía. Barcelona:Ediciones del Serbal; 2000. p. 201e72.

[101] Bald J. Estado de los recursos de almeja y berberecho en los estuarios deMundaka, Plentzia y Txingudi (1998e2007). Pesca y Alimentación delGobierno Vasco: Informe inédito para la Dirección de Pesca y Acuicultura delDepartamento de Agricultura; 2007. 79.

[102] Rammel C, van den Bergh J. Evolutionary policies for sustainable develop-ment: adaptive flexibility and risk minimising. Ecological Economics2003;47(2e3):121e33.

[103] Canellas-Bolta S, Strand R, Killie B. Management of environmental uncer-tainty in maintenance dredging of polluted harbours in Norway. WaterScience and Technology 2005;52(6):93e8.

[104] Irabien MJ, Velasco F. Heavy metals in Oka river sediments (UrdaibaiNational Biosphere Reserve, northern Spain): lithogenic and anthropogeniceffects. Environmental Geology 1999;37(1e2):54e63.

[105] Bartolome L, Tueros I, Cortazar E, Raposo JC, Sanz J, Zuloaga O, et al. Distri-bution of trace organic contaminants and total mercury in sediments fromthe Bilbao and Urdaibai Estuaries (Bay of Biscay). Marine Pollution Bulletin2006;52(9):1111e7.

[106] Ruiz de la Rosa JM, Saiz Salinas JI. Bioavailability of heavy metals in twoestuaries of the Basque Country. In: Sorbe JC, Jouanneau JM, editors. Actes duIII colloque international. Bordeaux: Oceanographie Biologique du Golfe deGascogne; 1993. p. 111e6.

[107] Saiz Salinas JI. Bioindicators of metallic pollution in sediments: applicationsto estuaries in N. Atlantic Spain. In: Dyer KR, Orth RJ, editors. Changes influxes in estuaries: implications from science to management. Fredensborg:Olsen and Olsen; 1994.

[108] Janssen R, Munda G. Multi-criteria evaluation for quantitative, qualitativeand fuzzy evaluation problems. In: van der Bergh JCJB, editor. Handbook ofenvironmental and resource economics. Cheltenham/Northhampton, MA:Edward Elgar; 1999. p. 837e52.

[109] JRC-EC. NAIADE manual & tutorial e version 1.0.ENG. Institute for Systems,Informatics and Safety, Joint Research Centre e EC, ISPRA SITE; 1996.

[110] Munda G. Multicriteria evaluation in a fuzzy environment, Theory andapplications in ecological economics. Contributions to economics series.Physica-Verlag; 1995.

[111] Munda G. A conflict analysis approach for illuminating distributional issuesin sustainability policy. European Journal of Operational Research 2009;194(1):307e22.

[112] Saltelli A, Chan K, Scott EM, editors. Sensitivity analysis. West Sussex,England: John Wiley and Sons, Ltd.; 2000.

[113] Folke C, Carpenter S, Elmqvist T, Gunderson L, Holling CS, Walker B. Resil-ience and sustainable development: building adaptive capacity in a world oftransformations. AMBIO: A Journal of the Human Environment 2002;31(5):437e40.

[114] Gunderson LH, Holling CS, Light SS, editors. Barriers and bridges to the renewalof ecosystems and institutions. NewYork, NY: Columbia University Press; 1995.

[115] Folke C, Carpenter S, Elmqvist T, Gunderson L, Holling C, Walker B, BengtssonJ, Berkes F, Colding J, Kjell Danell, Malin Falkenmark, Line Gordon, RogerKasperson, Nils Kautsky, Ann Kinzig, Simon Levin, Karl-Göran Mäler, FredrikMoberg, Leif Ohlsson, Per Olsson, Elinor Ostrom, Walter Reid, Johan Rock-ström, Savenije H, Svedin U. Resilience and sustainable development:building adaptive capacity in a world of transformations; 2002.

[116] Froger G, Munda G. Methodology for decision support: procedural rationalityand multicriteria decision aid, Cahiers du C3E. France: University of Paris I;1994. 94-20.

[117] O’Connor M, Fauxcheux S, Forger G, Funtowicz S, Munda G. Emergentcomplexity and procedural rationality: post-normal science for sustain-ability. In: Costanza OSaJM-A R, editor. Getting down to earth e practicalapplications of ecological economics. Washington, D.C.: Island Press; 1996.

[118] van den Hove S. Between consensus and compromise: acknowledging thenegotiation dimension in participatory approaches. Land Use Policy 2006;23(1):10e7.


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