Creating community-based indicators to monitor sustainability of local fisheries

Creating community-based indicators to monitor sustainability of local fisheries

ARTICLE IN PRESS Ocean & Coastal Management 49 (2006) 237–258 Creating community-based indicators to monitor susta...

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Ocean & Coastal Management 49 (2006) 237–258

Creating community-based indicators to monitor sustainability of local fisheries Heather Boyda,, Anthony Charlesb a Biological Sciences Department, University of Calgary, Calgary, Alberta, Canada T2N 1N4 Management Science/Environmental Studies, Saint Mary’s University, Halifax, Nova Scotia, Canada B3H3C3


Abstract This paper presents a systematic process to create frameworks of indicators for monitoring sustainable development in fisheries at the local community level. Indicators are evaluated and selected through a three-stage process: first, potential indicators for general use in fisheries are identified; second, this set is refined for suitability within a specific local context; third, indicators are evaluated according to data-specific criteria. The results suggest that indicators suitable at larger geographic scales are often unsuitable, and insufficient, for use at a local scale. Conversely, many social, economic and institutional fishery indicators appear suitable for use locally, but their implementation has received insufficient attention to date. r 2006 Elsevier Ltd. All rights reserved.

1. Introduction Indicators are measures used to quantify or qualitatively describe phenomena that are not easily measured directly, but which society considers valuable to monitor over time. People have used indicators for many decades to communicate information about complex systems or phenomena in a way that is relatively simple to understand. Indicators are useful for sharing the results of technical analysis or for monitoring characteristics of systems, such as fishery systems, to inform public decisions. In particular, indicators have become very useful in monitoring ‘sustainable development’1—a complex and often Corresponding author. Tel.: +1 403 220 3551; fax: +1 403 289 9311.

E-mail addresses: [email protected] (H. Boyd), [email protected] (A. Charles). The Brundtland Report defined sustainable development as, ‘‘development that meets the needs of the present without comprising the ability of future generations to meet their own needs’’ [1]. 1

0964-5691/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.ocecoaman.2006.03.006


H. Boyd, A. Charles / Ocean & Coastal Management 49 (2006) 237–258

ambiguous concept that cannot be measured directly. Sustainable development indicators are widely used to monitor sustainability within a system, to understand whether we are meeting our current needs and whether our actions will compromise the ability of future generations to meet their needs. The FAO Technical Guidelines for Responsible Fisheries promote the use of indicators in monitoring fisheries’ contributions to sustainable development (see footnote 1). The FAO advocates a holistic approach to indicators that recognizes all dimensions of sustainability. The guidelines refer to the importance of reporting on indicators at subnational, national and regional levels. They provide guidance on how to approach the development and implementation of sustainable development indicators for marine capture fisheries. While development of indicators in fisheries has proceeded rapidly in recent years [2–8], there has been relatively little attention paid to establishing frameworks of fishery indicators applied to the local or community level. Yet there is a clear need for such indicators given the increasing focus globally on local-level co-management and community-based management in fisheries (e.g. [9–14]). Community involvement in the fishery management process can take a variety of forms, including policy input and/or participation in scientific data collection, but certainly an important aspect of managing any system is understanding the dynamics and current status of that system. Within the context of community-based management or co-management, it is reasonable to ask which components of a fishery and its related environment can and should be monitored at the local/community level. The goal of the research reported in this paper has been to explore the challenges associated with developing fisheries indicators at a local level and to identify which indicators are appropriate, and which are not, at that spatial scale. An overriding question has been to understand the circumstances in which it makes sense and is practical to monitor fishery indicators at the local level. The approach taken to explore these questions has been to: (1) develop a holistic set of indicators, representing community, ecological, institutional and socio-economic dimensions of sustainability, that could be used to monitor sustainable development in fisheries: (2) assess the suitability of each indicator for fishery application and specifically for local application: and (3) apply the resulting framework of indicators in a local-level case study, to examine the extent to which indicators can be used in practice. Each of these three stages is addressed sequentially in the following. 2. A community-level indicator development process to monitor fishery sustainability The overall process for developing a set of indicators for community-level fisheries is indicated in Fig. 1, starting at the participant identification stage, proceeding through visioning, specifying a suitable framework and sustainability characteristics, then following an iterative series of steps to develop, classify and evaluate the indicators involved. 2.1. Participants in indicator development The process of designing indicators begins with scoping for whom the indicators will be developed, and who will be part of the indicator development team. This initial stage is essential to proper indicator design and will largely influence what indicators will be

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Identify Participants

Develop a Common Vision

Develop an Indicator Framework to Reflect the Vision

Identify Relevant Characteristics of Sustainability

Develop Indicators to Reflect Characteristics of Sustainability Focus Group

Literature Review



Classify and Evaluate Indicators

Select Indicators for Community Use Fig. 1. The sustainable development indicator design process.

developed. The team takes a lead role in developing a vision of sustainable fisheries to be used in the indicator development process, defining the indicator framework to reflect the vision, scoping the desired characteristics for the indicator set, selecting and evaluating indicators from a wide range of possibilities, and finally selecting a subset of indicators that could be used in a specific context and evaluating whether those indicators are suitable for local level monitoring. The process is outlined below. 2.2. A framework for fishery sustainability The first step in developing indicators is to define an overall indicator framework within which it is possible to observe/monitor a fishery system. In dealing with any complex system such as the fishery, it is helpful to view the system in conceptually distinct


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Ecological Sustainability

Institutional Sustainability

Socio-economic Sustainability

Community Sustainability

Fig. 2. The sustainability triangle (modified from Charles [15, p. 205]).

components, and where possible, to observe each component of the system in turn. It is critical to recognize throughout the process that in reality, all these components of the system interact, and that changes to one aspect of the system will influence sustainability of the other aspects of the system. The framework used here for monitoring sustainability of the fishery system reflects a holistic vision of fisheries management and is based on four components of fishery sustainability—community, ecological, institutional and socio-economic sustainability—as proposed by Charles [15–17]. See Fig. 2 for a graphical description—note that in the figure, institutional sustainability is represented in the core of the triangle because institutions provide the instruments through which fishery systems are translated into sustainable fishery systems, and thus impact on all the other three sustainability components. Note as well that in contrast to the more common ecological–economic–social framework of sustainable development components, the framework here has the advantage of explicitly recognizing the importance of communities and institutions, and in particular of being directly applicable to the community level. Within this model, the indicator framework recognizes that humans are an integral component of fishery systems. Fisheries management is the management of human interactions with fish, particularly although not exclusively through fishing. Numerous factors influence decisions to fish and these motivating factors ultimately influence the number of fish that are taken from the ocean. Good management requires an understanding of the dynamics and current status of the fishery, including the factors that influence fishers as well as ecological factors that affect the fish. Motivating factors on the human side are reflected in the sets of socio-economic, community and institutional indicators. The sustainable fisheries framework was used to systematically identify the characteristics of fishery systems that can be expected to impact sustainability and then to develop indicators to monitor the status of each characteristic. 2.3. Characteristics of fishery sustainability Within a given framework of sustainability indicators, there is a need to determine precisely what fisheries characteristics are to be considered as influencing sustainability.

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Table 1 Characteristics of fishery sustainability Fishery system Community sustainability Characteristics:  Demography  Access to knowledge  Contribution of marginal groups to decision making  Traditions and culture  Access for people dependent on local fishing  Cooperation/ cohesion  Dispute resolution mechanisms  Resilience

Ecological sustainability

Institutional sustainability



 Biodiversity  Change in area or quality

 Adequacy of


of habitat Area and quality of fished versus unfished areas Carrying capacity Direct effects of fishing gear on ecosystems Resilience Direct effects of fishing gear on non-target species Indirect effects of fishing on trophic and community structure Catch structure Exploitation rate Target species abundance Reproductive potential/ impairment Fish waste Resource waste


management resources Recognition of ICZM Integrated approach to management in fisheries Participation and transparency Locally appropriate Dynamic management with a long-term vision Research Conflict and cooperation

Socio-economic sustainability Characteristics: Harvest Harvest value Product value Export value Profitability Income Employment Harvesting and processing capacity  Effort  Use of public funds  Market incentives  Indebtedness  Protein  Health and safety  Resilience  Natural capital  Distribution


The set of relevant characteristics of fishery sustainability identified here, as shown in Table 1, are characteristics used internationally and nationally, as well as those recognized in peer-reviewed publications listing principles of sustainable marine fisheries. While there is a rapidly growing array of documentation on the subject internationally, the primary sources of sustainability principles used here included the FAO Code of Conduct for Responsible Fisheries, the Canadian Code of Conduct for Responsible Fishing Operations: Consensus Code, and the Marine Stewardship Council Principles and Criteria for Sustainable Fishing [18,19]. Note that the process has a flexibility that allows for any extent of adjustment to the list of characteristics to fit particular situations. The selected characteristics were incorporated into the framework under the most relevant sustainability component, although since the framework is conceptual and the four aspects are interrelated, some characteristics could be legitimately included under more than one of the framework’s four sustainability components. 2.4. Indicator selection: initial compilation Given a set of characteristics of fishery sustainability as above, multiple indicators must be selected, suitable to monitor each of the characteristics of interest. Indicator development is a cyclical process, involving compilation of information from other


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experiences (e.g., through a literature review), evaluation by the community indicator development team, consultations with appropriate experts, and use of focus groups where needed, as follows:

First, compilation of information must be carried out, from other indicator development experiences and from theoretical studies, to provide an initial set of indicator possibilities and basic guidance on indicator choices. Indicators to be considered for inclusion in the indicator system must be reasonably closely associated with one of the characteristics of fishery sustainability developed in the previous stage. This step might well involve a review of the literature, within which a wealth of indicators has been proposed (e.g. [20,21,5,6,2]). Indicators that need to be included in this broad compilation include: (a) indicators that have been used specifically for fisheries monitoring, (b) those used to monitor other natural resources, and (c) those used in managing sustainability projects in general. The ‘macro’ set of possible indicators thereby produced must then be evaluated by the ‘indicator development team’—which at a community level could be a multi-faceted set of community members, possibly supplemented by outside ‘experts’ or consultants. At this step, there is an opportunity to modify/adapt indicators previously used in other situations—e.g., where it is necessary to increase either their quality or their relevance to a specific characteristic of fishery sustainability—and to develop original new indicators, in instances where the broad survey located no existing indicators that reflected a given selected characteristic of fishery sustainability. In conjunction with the indicator development team’s evaluation process, there can be useful consultations with experts from diverse disciplines, so as to examine the indicators identified and developed in the above steps of the process. In this phase of the cycle, indicators can be modified or rejected, and, as above, new indicators may be developed in the consultations. The experts’ feedback can assist in assessing (a) the scientific validity of the indicators and (b) the appropriateness of each indicator relative to the corresponding characteristic of fishery sustainability. Also in conjunction with the evaluation process, focus groups can supplement individual expert input by providing an interactive forum to examine the indicators with respect to scientific validity and relevance to the intended characteristic of sustainability. Focus groups will generally be multidisciplinary groups representing a range of experience in fisheries, in sustainable development indicators, and in relevant disciplines.

As noted above, this phase of indicator development is cyclical/iterative in that indicators can be continually revised to reflect new insights gained from the literature, advice from experts, insights from the focus groups, etc. 2.5. Classification of indicators The initial stages of this indicator development process involve an implicit classification of indicators into categories given by the sustainability components that constitute the framework described earlier (ecological, socio-economic, community and institutional components), so that each component is represented by some sub-set of the indicators. In developing an indicator set, this form of classification of each indicator into one of a

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certain small set of categories allows the organizing of indicators according to a certain perspective (i.e. the ‘type’ of indicator) and helps identify whether the set of indicators as a whole, fully addresses all sustainable development considerations viewed as important. The value of classification is especially important when indicators will be monitored and used to support management. More specifically, classification schemes are useful in understanding indicators and the systems they are designed to monitor, in at least five ways:


Classifying indicators provides an opportunity during the design process to focus on the intent and potential contribution of each indicator. Classifying indicators demonstrates that it is often difficult to identify which actions affect sustainability, thereby identifying gaps in our understanding of fishery systems. Classifying indicators can make it easier to identify cross-linkages between indicators in community, ecological, institutional and socio-economic aspects of sustainability. Classifying indicators can make it easier to identify parts of the fishery system for which new indicators would be useful. For indicators belonging to more than one class, classification identifies the perspective from which the indicator has been interpreted.

As a classification scheme, the four components (ecological, socio-economic, community and institutional) may not always lead to clear-cut results since each indicator may not fall into one and only one category—a given indicator of sustainability can reflect more than one component of sustainability at a time, and indicators are also linked with one another [22]. However, this classification scheme is useful from a practical perspective, in that (1) society often studies these components of sustainability separately and this scheme provides an incentive to identify needs in each area and (2) the organizational structure itself helps demonstrate the relationships between the four components of fisheries sustainability through indicators that are relevant to more than one of these components. Classification can therefore emphasize the interactions and similarities between the four aspects of fishery sustainability. At this step in indicator development, it can be useful to guide the process using additional classification schemes. One important approach classifies indicators according to the ways in which they characterize system interactions affecting fishery sustainability. This includes the popular pressure-state-response scheme, and a scheme similar to that described by Duinker [23], classifying indicators according to context, action or condition/ response functions. An effort to apply the latter scheme is described in the case study later in the paper. 2.6. Indicator selection: general and context-specific evaluation To this point in the indicator development process, a framework has been determined within which to develop the set of sustainability indicators, the sustainability characteristics of interest have been identified, and a ‘phase 1’ comprehensive collection of indicators has been compiled. The next stage of the process refines the set of indicators, introducing quality control through a process of indicator evaluation and selection of a manageable indicator suite applicable at the community level (by analyzing suitability for local level monitoring).


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As management tools, the practicality and utility of a set of indicators requires meeting a number of objectives:


A minimum standard of general indicator quality, as determined through a process of evaluation against the criteria of indicator quality. Inclusion of a broad range of indicators representing the characteristics of sustainability built into the indicator framework. A manageable number of indicators for continued monitoring.

Evaluation is an important step in the indicator design process because it helps to identify indicators’ strengths and weaknesses, enabling a more accurate interpretation of results. This can be accomplished by compiling a list of evaluation criteria from various sources (e.g. [21–26]) and using these criteria to determine the quality of the sustainability indicators developed in previous stages. The compiled evaluation criteria can be organized into three groups (Table 2): 1. General indicator quality criteria, capable for use in evaluating indicators regardless of the specific application of the indicators. 2. Context-specific ‘relational’ criteria for evaluating indicator quality, used specifically to evaluate each indicator in relation to the system characteristic it is designed to monitor. 3. Data-specific criteria—used to evaluate the quality of indicator data. Table 2 Criteria of indicator quality General indicator quality criteria  Relevant  Qualified by reference values  Sensitive  Predictable  Measurable  Expressed in a way that makes sense  Simple/understandable  Easily interpreted  Timely  Integrative (across all aspects of sustainable development) Context-specific criteria  Influential to policy and decision-making  Theoretically appropriate in spatial scale  Practical Data-specific criteria  Appropriate in temporal scale  Scientifically valid  Accurate and precise  Adequately documented  Current  Directly measurable  Acceptable in scale quality  Consistent in scope, quality, currency, scale, sampling methods

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Indicators rarely rate well against all criteria [27], but acceptable indicators will rate favorably against many of the criteria. The procedure proposed here involves three steps within this stage of the process. First, criteria of general indicator quality are used to evaluate and filter the indicators, the idea being that indicators which are not generally desirable (because they have certain inherent flaws) will not be desirable specifically at a local level. Second, the indicators passing the test of general indicator quality are evaluated on the context-specific criteria. Third, those suitable on both general and context-sensitive grounds are examined in terms of dataspecific criteria to eventually reach a conclusion about suitability for local level monitoring. 2.6.1. Evaluation: general indicator quality The set of criteria assessing general indicator quality provide an effective framework for an initial evaluation of basic indicator quality in a consistent manner. The process involves evaluating all indicators against each criterion of general indicator quality, as listed in Table 2, in order to identify the indicators’ strengths and weaknesses in relation to each of these criteria. It is worth noting that because the general quality criteria represent basic characteristics of indicator quality, they are likely to be implicitly considered during indicator design—i.e. the choice of indicators to keep in the pool for potential application at each step will draw on these general quality criteria—and thus it will not be surprising to find that once this evaluation stage is reached, many of the indicators will rate positively in relation to these criteria. In particular, experience to date (see associated references) suggests that certain characteristics are of greatest importance in shaping the development of the indicators:


Relevance [21–24,26,28,29]. Reference values [21,23,24,26,30,31]. Sensitivity [21,23,25,26,29,32]. Measurability [23–26]. Sensible expression [26]. Simplicity/understandability [21–23,25,26,29–31]. Ease of interpretation [4,6,22,26,31]. Timeliness [4,6,22].

There are other, less obvious criteria of general indicator quality, including predictability [21,23,24,29,32] and integration of several aspects of sustainability [21,22,32]. However, these criteria may be less critical to general indicator quality, because (a) while indicators that are not predictable cannot be used for modeling purposes, they do have value in retrospective analysis and (b) most indicators integrate multiple aspects of sustainable development if interpreted accordingly. Used alone, these two criteria do not provide a sufficient basis for ranking indicators according to quality. A crucial matter in developing an indicator framework lies in balancing the manageability of the set of indicators (particularly in regard to the overall number of indicators) and the breadth in the range of indicators. The best approach to accomplish this balancing depends on the level of resources available for monitoring and the extent to which monitoring data is available through other sources.


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The first step in selecting indicators is to eliminate those identified as unmeasurable through the previous evaluation process. Indicators were considered unmeasurable if there was no known or accepted technique for measuring them. Practical monitoring concerns, such as cost or expertise, were not considered at this point. The next step involves selection of indicators on the basis of their ability to reflect how their respective characteristics of sustainability affect the sustainability of fishery systems— the goal being to select the most relevant indicators for each characteristic. This is a subjective assessment in identifying the capacity of indicators to monitor fisheries sustainability, drawing on theoretical considerations compiled from existing experiences and literature, as well as expert consultations and focus groups at the indicator design phase. The indicators selected are those that best reflect each characteristic within the indicator framework, and any redundant indicators are eliminated. After completion of this step, the indicator set that has been obtained is ready for analysis with respect to context-sensitive and data-sensitive criteria. 2.6.2. Evaluation: suitability for context-specific monitoring The next stage of sustainability indicator development is to evaluate indicators from the perspective of their suitability for application in a specific local context. This also involves identifying the commonalities and differences among useful local level indicators. The approach proposed here focuses on examining and evaluating the indicators in terms of applicability in a particular community-level situation. A step-by-step process is used, with indicator suitability evaluated sequentially using three context-specific criteria: 1. Influence in policy decision-making. 2. Appropriateness in spatial scale. 3. Practicality. These steps are described in sequence below. Influence in policy decision-making. The first of the context-specific criteria of indicator quality, influence in policy decision-making, refers to the potential for indicators to assess policy effectiveness and identify options for policy change (e.g. [21]). This criterion helps to evaluate whether indicators provide information that could influence decisions positively, notably toward improved sustainability. This criterion can best be applied to evaluate whether indicators have the potential to impact on policy change (i.e. for some possible management options) rather than whether they could impact on policy change under the present political and management systems. Political priorities and management approaches are subject to change, and indicators that may not influence policy today may have influence as policies and management approaches change. The evaluation, therefore, considers the spatial scale of management, but is not limited to evaluating indicators in relation to the current form of management. The power of this criterion in selecting or rejecting indicators depends on how ‘‘policy decision-making’’ is defined. The term can include both management policy decisions and personal-level decisions because, at the community level, both can influence the sustainability of fisheries development. This criterion of indicator quality may in fact be the most important of all those considered, since it defines the potential usefulness of an indicator in addressing the real

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issues at hand. Therefore, this criterion provides a crucial reference point from which to evaluate indicators in specific real-world cases. However, it is important to recognize that there can be wide variations in the definitions of ‘potential to impact policy change’ and ‘policy decision-making’. Clearly, the narrower the definition, the greater the number of indicators that will be rejected based on this criterion—hence it is crucial to find a definition within which desirable indicators from a policy standpoint are not lost. Furthermore, this variability means that while the criterion is important for use in specific situations, it does not provide a basis for ranking indicators in general (and for this reason, it was not utilized in the case study analysis to be presented later in this paper). Appropriateness in spatial scale. The second step in the proposed process is the consideration of each indicator’s appropriateness to the community spatial scale [23,33,34]. Spatial scale is an important consideration in monitoring indicators. In particular, regular disturbances can be misinterpreted as anomalies if the scale is too fine but significant disturbances can be masked and overlooked if the scale is too coarse [33,34]. Spatial scale is considered (theoretically) appropriate for a given indicator if the system component that the indicator would monitor can be both observed and managed at that scale. For a specific community, indicators can be considered ‘highly appropriate’ at the spatial scale of the community if the indicators can be observed and managed within the community. Indicators are considered useable (observable and potentially manageable) at the scale of the fishing community if they monitor components of the fishery system that do not extend beyond:


The human membership of the fishing community (community indicators). The physical fishing grounds of the fishing community (ecological indicators). The institutions unique to the fishing community (institutional indicators). The socio-economic characteristics unique to the fishing community (socio-economic indicators).

Indicators that can provide useful information at the scale of the fishing community, but which would be more useful if applied at a larger spatial scale, can be rated as ‘medium’ in relation to spatial scale appropriateness. Indicators that do not meet the requirements for a high rating in appropriateness at the scale of the particular community, and do not fit the ‘medium’ scenario, are given a low rating. Of these, indicators that are only appropriate at a larger spatial scale (and indicators rated as of medium appropriateness) can be classified as context indicators (cf. Section 3.2). These can usefully inform community level management decisions but, in most cases, it would be inappropriate to assign the responsibility for monitoring these indicators to the local community level. Practicality. The third step in context-sensitive evaluation involves each indicator’s practicality [4,6,23,28,29,31,32]. Practicality is a valuable criterion for evaluating whether the benefits from use of an indicator justify the time and financial resources required to include it as part of the indicator project (e.g. [4,31]). Given the limited resources available for indicator projects, it is necessary to determine whether a specific community can fulfill responsibilities for designing, monitoring, interpreting and


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reporting on the indicator. Indicators are considered practical if there are sufficient time and financial resources available within the community for these tasks. The proposed process places indicators which received high or medium ratings with respect to scale appropriateness into five categories of practicality—high, potential, low, ‘alternate scale’, and unknown. On the other hand, indicators which receive low ratings on scale appropriateness are classified into just two categories, either low practicality or ‘alternate scale’. Each of these categories is described below. Indicators are rated as highly practical at the fishing community level if the community can take responsibility for ensuring that the indicators are properly designed, monitored, interpreted and reported. Indicators receive a high practicality rating if the indicator information was available at the time of the study or in the past, is soon to become available, or requires a simple calculation based on data available at the scale of the specific fishing community. Indicators do not meet the criteria for a high practicality rating if there is insufficient experiential evidence to demonstrate that they are practical for a local fishing community. These will typically include novel indicators developed specifically in the indicator development process, and indicators that are not currently monitored at the local community scale. A number of these indicators are rated as having ‘potential’ practicality, depending in part on the design of collection methods (e.g., surveys). Indicators are given this rating if a similar indicator, or an indicator requiring a similar data collection method, has been implemented either at a similar spatial scale or at a larger spatial scale if costly primary data collection is not required. A ‘low’ practicality rating is assigned to indicators if the method for collecting primary data is not practical or if the data itself is not practical to obtain. Methods are considered impractical if they are complex to the extent that they have not yet been successfully undertaken and no potentially successful method is apparent. Primary data collection is considered to be impractical if it requires specialized equipment that is not available to fishing communities or if the information is confidential. Indicators with a low rating are rejected at this point and not evaluated further. Numerous indicators are not practical at the local community scale, for the above reasons, but would receive a high practicality rating at a larger scale. These are referred to here as ‘alternate scale’ indicators. For these, it is useful to identify within the process the scale at which monitoring would be practical. These indicators, which include those that are theoretically appropriate at the community level as well as those that are not, can be considered contextual in nature, i.e. providing information on the context within which a community-level fishery is operating. Finally, an indicator may be rated as unknown with respect to practicality. Such an indicator may be practical, but for this to be the case, it requires a complementary input that cannot be ascertained to be present. For example, there may be a need for significant participation or cooperation from particular individuals or organizations for successful monitoring, and thus the practicality will depend in this case on the willingness of particular individuals to assist in the indicator’s monitoring. 2.6.3. Evaluation: data-specific criteria If an indicator rates satisfactorily with regard to general quality criteria and contextsensitive criteria, the process proceeds to examine data-specific criteria. A range of dataspecific quality criteria were listed in Table 1 above: (1) appropriate in temporal scale,

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(2) scientifically valid, (3) accurate and precise, (4) adequately documented, (5) current, (6) directly measurable, (7) acceptable in scale quality, (8) consistent in scope, quality, currency, scale, sampling methods. Where possible, each indicator must be evaluated against these criteria of data quality to help determine whether they are high-quality indicators. Whether this can be accomplished depends on the level of development or utilization of the indicator in the specific situation at hand, or at least the level of knowledge about it, if it has not yet been applied. Also of interest is an indicator of data availability, to ascertain the extent to which monitoring already occurs—this is an aspect considered in the case study below. 2.6.4. Summary of indicator evaluation and selection process The stepwise decision process proposed to assess context- and data-sensitive criteria, as described above, is shown in Fig. 3. The assumption in the figure is that the indicators being addressed are those considered to have sufficient ‘general indicator quality’. Then the flowchart indicates first examining the context-specific criterion influence in policy decisionmaking (reflecting its crucial importance for choosing indicators within specific situations) followed by appropriateness in scale and practicality, then matters of data availability (and potentially data quality as well). 3. Case study The process for community-level sustainability indicator development proposed in this paper was implemented and tested based on a specific case study of a Canadian community-level fishery. However, the analysis was done in an artificial manner in that, rather than an actual community-based implementation, this paper’s first author served as a one-person ‘indicator development team’ and the second author, together with others, comprised the focus group. This enabled us to undertake an initial examination and assessment of the process itself. 3.1. Initial steps As described earlier, the process began with a set of four steps to develop an initial indicator set: 1. An ongoing literature review provided the foundation for the first round of selecting a ‘macro’ set of indicators. 2. An initial evaluation of the set of possible indicators, in this case by the one-person ‘research team’, led to modification of previously used indicators and development of original indicators. Indicators drawn from the literature review were modified in instances where it was necessary to increase either their quality as an indicator, or their relevance to a specific characteristic of fishery sustainability. Original indicators were created in instances where there were no existing indicators that reflected a given selected characteristic of fisheries sustainability. 3. Consultations were held individually with experts from diverse disciplines including fisheries biology and ecology, sociology, economics, community studies and resource management. Through consultations, we examined the indicators that had been identified and developed in the above first two steps of the process. In this phase of the


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Sustainable Development Fishery Indicators Passing General Indicator Quality Criteria Influential in Policy Decision-making


Not Influential

Appropriateness in Scale Rejected

High, Medium



Alternate Scale




High, Potential, or Unknown


Alternate Scale




Data Availability





Fig. 3. Context-specific evaluation and selection.

cycle, indicators were often modified or rejected. We also developed new indicator ideas during the consultations. The experts’ feedback was most valuable in assessing (a) the scientific validity of the indicators and (b) the appropriateness of the indicator relative to the corresponding characteristic of fisheries sustainability. 4. The fourth step in the indicator development process involved a multidisciplinary focus group representing a range of experience in fishery management, economics, policy, and sociology, and in formulating local level sustainable development indicators. The focus group provided a forum to examine each indicator in detail with respect again to its scientific validity and relevance to the intended characteristic of sustainability. The focus group was sufficiently large to bring a variety of perspectives and experiences to the task, yet small enough to have efficient and productive discussion and commentary

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regarding the indicators and their suitability as indicators of sustainable development in marine capture fisheries. As noted above, this phase of indicator development is cyclical/iterative in that: (a) the literature review was ongoing throughout the indicator development process, (b) expert consultations took place over the full course of the indicator development, and (c) there were numerous focus group meetings. Indicators were continually revised to reflect advice from experts, insights from the focus group, or new insights gained from the literature. The indicator and fisheries literature also provided background for indicator evaluation, and, together, these provided a basis for meaningful discussions with experts. The focus group played a valuable role in examining indicators in detail and in exploring and comparing the merits and demerits of each indicator. 3.2. Applying an indicator classification scheme The case study examined the utility of selecting indicators to meet the dual goals of having sufficient indicators for each of the sustainability components, and fitting within a ‘‘context—action—condition/response’’ classification scheme [23]. The specific terms involved in this scheme are defined as follows:

Context refers to phenomena that cannot be directly manipulated through management. Context indicators are relevant to sustainability because they describe the uncontrollable characteristics that can directly affect, in this case, fisheries. For example, water temperature is a context indicator in fisheries; it affects migration and local abundance of fish stocks, but it is not directly affected by management actions. Action indicators describe human actions, or inaction, that influence the system in question. Examples of action indicators might be those describing harvest levels, which directly reflects the level of impact on the fish stocks, and those of public participation in management, since public participation will influence the decisions made within the fisheries management system. Condition or response indicators describe the system’s current state or its reactions to human influence. A condition/response indicator in fisheries could be the cost of shellfish site closures resulting from contamination.

The context, action and condition/response classifications frame each indicator to allow results of indicator monitoring to be more easily interpreted and to facilitate insights into relationships between context, actions and conditions/responses in fishery systems. For example, the extent of conservation initiatives (a community indicator) is classified as an action indicator in its relationship to the condition/response indicator of biomass (an ecological indicator). Ideally, each condition/response indicator within a sustainability indicator set should be accompanied by both action and context indicators that are known to be associated with the condition/response indicator. This trio of indicators would make it possible to study some potential reasons for the observed conditions and responses, and to make prudent management decisions in relation to them. Initially, the plan in this case study was to select trios of condition/response and associated context and action indicators whenever possible. However, indicators were not


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selected on this basis for three reasons. First, higher priority was placed on creating a suite of indicators that included at least one from each characteristic of sustainability (the classification scheme used in designing the indicators). Given this constraint, and the need for a manageable-sized suite of indicators, it was apparent that selecting three or more indicators for each characteristic would have created an indicator set of impractical size. Second, developing or identifying all three indicator types for each characteristic of sustainability was not always possible due to limitations in our understanding of fishery systems. Third, the value of context–action–condition/response classification schemes is in monitoring interactions among system components. The scope of this work did not extend to implementation of a monitoring process that would be used to examine system interactions. Thus, classifying indicators through the context–action–condition/response classification scheme did not assist in selecting indicators in our case study, but as noted above, viewing indicators through the ‘lens’ of this scheme provided useful insights into the nature of the fishery. 3.3. General-level evaluation The evaluation step involved assessing general indicator quality for each of the potential indicators in terms of each criterion of general indicator quality. A simple ‘good’/‘poor’ rating system was used to rate the indicators. This rating system was chosen over more detailed systems (e.g., a 1–5 rating scheme) because without precise and identifiable increments between each rating in the scale, it is not possible to ensure that (a) increments within the measurement scale for each criterion are consistent with each other and (b) indicators will be rated for the same criterion in a consistent manner. The evaluation process provided an opportunity to reflect on which qualities each indicator possesses and also the extent to which each indicator possesses those qualities. Certain characteristics, implicitly considered desirable qualities for indicators within the focus group, the expert consultations and the team evaluation process, shaped the development of the indicators (see Section 2.6.1 above):


Relevance Reference values Sensitivity Measurability Sensible expression Simplicity/understandability Ease of interpretation Timeliness

Indicators had more variable ratings in relation to less obvious criteria of general indicator quality, including predictability and integration of several aspects of sustainability. As noted earlier, these criteria may also be less critical to general indicator quality. Of the key criteria noted above, the evaluation of each indicator’s strengths and weaknesses demonstrated that two of the 10 criteria are essential to general indicator quality, and must be satisfied for an indicator to be useful:


Relevance (to the priority issues). Measurability.

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In this case study, a large initial indicator set of 80–100 indicators was reasonable because the scope of the research did not include primary data collection. With this target, it was feasible to select approximately two indicators to represent each characteristic of sustainability within the indicator framework. The indicator set resulting from the general-level evaluation includes 86 indicators out of the original overall set of 169. Together, the 86 indicators cover 44 of the 47 sustainability characteristics of marine capture fisheries. 3.4. Context-specific evaluation: indicator suitability for local level monitoring The 86 indicators determined at the general evaluation stage were examined with respect to their suitability in the fishing community case study. The approach was taken of examining indicator suitability using the two context-specific criteria of indicator quality: appropriateness in spatial scale and practicality. (For reasons noted earlier, indicators were not evaluated in relation to their influence in policy decision-making, the third criterion of context-specific indicator quality.) Appropriateness in spatial scale: Indicators were rated as highly appropriate at the spatial scale of the case-study fishing community if they satisfied conditions described earlier, or a low rating otherwise, except for three of the indicators evaluated, which were of some use at the scale of the community but would be more useful if applied at a larger spatial scale— these received a medium rating. Practicality: After evaluating each indicator with respect to appropriateness at the spatial scale of the case-study fishing community, the 86 selected indicators were rated according to practicality, i.e. high, potential, low and unknown practicality. Most indicators were rated in practicality as high or ‘potential’, but eight indicators evaluated through this case study were given low ratings, and three were rated as unknown with respect to their practicality. 3.5. Data-specific evaluation Indicators were also evaluated according to the criterion, data availability. Ideally, indicators would be evaluated against the criteria of data quality (Table 2) to help determine whether they are high-quality indicators, but data quality was not evaluated in this case because data was available for few indicators within the suite that was developed. In this study, data availability was used to ascertain the extent to which monitoring already occurs. Available data included data that was collected specifically at the community level or at a larger geographic scale that included the case-study community. 3.6. Results The results of the evaluations of the 86 indicators (Table 3) show that most of the indicators within the indicator suite are suitable—i.e. both (1) theoretically appropriate in spatial scale and (2) practical—for monitoring the sustainability of fisheries at the local community level. However, despite their suitability, data is currently collected for few of these indicators at the local level. Useable indicators are identified as those that are: (1) theoretically appropriate, (2) practical, and (3) have data available at the local level. Only 14 of the 86 indicators

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Table 3 Proportion of indicators within each sustainability component that received a positive evaluation in relation to the three criteria evaluating context-specific indicator quality

Community sustainability Ecological sustainability Institutional sustainability Socio-economic sustainability Total

Theoretical appropriateness


Data availability

Useable indicators

17/18 11/25 12/17 24/26 64/86

16/18 8/25 11/17 15/26 51/86

5/18 15/25 2/17 9/26 30/86

4/18 4/25 1/17 5/26 14/86

Useable indicators are those acceptable in terms of all the three criteria.

evaluated could be considered useable (Table 3). Most community and institutional indicators were evaluated as both theoretically appropriate and either practical or potentially practical but few had been monitored to date. These are identified as developable indicators (Fig. 3) because they are not immediately useable but could likely be developed. Many socio-economic indicators were also developable, but another group of socio-economic indicators were rejected due to confidentiality challenges associated with economic data. Ecological indicators were primarily contextual; they were evaluated as more appropriate at a larger spatial scale. 4. Conclusions This paper has presented a systematic process for use by communities that seek to develop and monitor a set of local-level, community-relevant sustainable development indicators as part of their involvement in fishery management. This process built on an initial synthesis of indicator development approaches in the literature, to derive a decision support system for choosing a set of fishery indicators. The process (illustrated in Figs. 1 and 3, and Table 2) involves three sequential categories of indicator evaluation criteria which together provide a filtering process that can be used in evaluating the quality of indicators:


General quality criteria that will apply to a specific indicator in all contexts, regardless of the scale of application or the sector involved. It is therefore possible to discuss indicator quality in relation to these generic criteria across sectors and geographic scales. Context-specific criteria must be used in relation to a specific context. Indicators that are suitable in one sector or a specific community may not be suitable in other contexts. Data quality criteria can only be fully evaluated after indicators have been selected and monitored. It is often possible to improve data quality for a given indicator by modifying data gathering methods.

The sequence of evaluation and selection that serves to filter indicators based on contextspecific quality was shown in Fig. 3. The value of the evaluation process is that indicators will be more easily interpreted and more useful if their strengths and weaknesses are well

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understood. Indicators are meant to represent reality—typically they are imperfect in doing so, and indeed if serious flaws are identified, indicators can be rejected. The criteria provide consistent guidance for ensuring indicator quality. Communities can use the process of indicator design, classification and selection outlined in this paper as a guide in customizing their sets of fishery indicators. Indeed, the specific framework of indicators developed through this research may provide a starting point for communities wishing to undertake the process of developing local level indicators of their own. The particular indicators chosen, and even details of the process, will depend on specific realities of the fishery and community involved. Communities can choose to follow all three steps of the filtering process; alternatively, they can draw on previous work in this area [35] to identify indicators meeting general quality standards and continue the evaluation within their local context through steps two and three of the filtering process. While the results of the case study in this research cannot necessarily be extended to other situations, certain interesting outcomes have arisen that deserve broad consideration: (1) Of the various indicators identified in the study, the ecological indicators are the most commonly monitored, and thus the most likely to be available to inform management decisions. (2) On the other hand, most ecological indicators were neither appropriate nor practical for local level monitoring, and are typically not monitored at the scale of local communities due to the lack of fit between ecological boundaries (for the fish stocks) and political boundaries (of fishing communities). (3) A high proportion of the community, institutional and socio-economic indicators developed in this research are both appropriate and practical for local level monitoring. (4) On the other hand, only a small proportion of those community, institutional and socio-economic indicators are currently monitored and available for the case-study community. These results indicate a major potential problem in local-level fishery indicator development. On the one hand, the apparent emphasis on monitoring ecological aspects of fisheries, and at larger scales than that of the community, reflects a tradition of biological data collection and analysis in fisheries, together with scale/boundary issues (the typical scale chosen to analyze fish stocks, for example) and financial aspects (even if feasible, it would be costly to gather, let alone manage, stock assessment and ecological data for each fishing community). There is, however, scope for appropriate ecological indicators at the local level in suitable circumstances. At the same time, these results suggest that there is a clear opportunity for increased monitoring of community, institutional and socio-economic indicators of fisheries sustainability. Does the fact that this is not carried out much at present reflect a low value in monitoring such indicators? On the contrary, recent research suggests that, at least in some fishing communities, community and policy indicators are considered more important than ecological indicators [3]. Indeed, in the increasingly common environment of co-management and community-based management, fishing communities need to maintain and enhance fishery sustainability—including that of fish stocks as well as that of the human activities and benefits associated with the exploitation of a healthy fish stock. To do so, to understand and manage in such situations, certainly requires monitoring of the human impacts on fisheries. Gathering this information as part of the


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community-based management process will require commitment from the fishing communities themselves—it must be driven by communities that acknowledge this information as valuable to managing their fisheries. This demonstrated need for local-level indicators highlights the importance of overcoming a key factor identified in this research—that from a rather extensive list of theoretically interesting indicators, few may be immediately useable. Many of the indicators identified or designed in this research would satisfy most criteria of general and context-specific indicator quality, but data required to implement them is currently not collected. These were identified as ‘‘developable’’ indicators. The data could be collected through custom surveys or, potentially, through custom extractions or analysis of existing data sets, notably from governmental statistical sources. A primary barrier for a community to acquire this information on a consistent basis would be limited resources, and this in turn suggests the need for governmental support. In any case, we have seen that indicator selection and development is a complex process that deserves attention and rigor, since the value of fishery monitoring depends very much on the quality of the indicators selected. The process developed in this paper will hopefully provide a systematic approach to support these needs, so fishing communities, fishery participants and local-level managers can improve the monitoring and management of their local fisheries. Acknowledgments Boyd acknowledges financial support through the Dalhousie Faculty of Graduate Studies and the SRES Thesis Research Award. Charles acknowledges financial support from the Natural Sciences and Engineering Research Council of Canada, the Social Sciences and Humanities Research Council of Canada, and the Pew Fellows Program in Marine Conservation. The authors thank Peter Duinker and Richard Apostle for many helpful ideas and insights in the course of this research. References [1] WCED. Our common future. World conference on environment and development. Oxford: Oxford University Press; 1987. p. 43. [2] Jamieson G, O’Boyle R, Arbour J, Cobb D, Courtenay S, Gregory R, et al. Proceedings of the workshop on objectives and indicators for ecosystem-based management. Canadian Science Advisory Secretariat (CSAS) Proceedings Series 2001/09, Sidney, BC, 2001. [3] Adrianto L, Matsuda Y, Sakuma Y. Assessing local sustainability of fisheries system: a multi-criteria participatory approach with the case of Yoron Island, Kagoshima prefecture. Japan. Marine Policy 2005;29:9–23. [4] Garcia SM, Staples DJ, Chesson J. The FAO guidelines for the development and use of indicators for sustainable development of marine capture fisheries and an Australian example of their application. Ocean and Coastal Management 2000;43(7):537–56. [5] Chesson J, Clayton H. A framework for assessing fisheries with respect to ecologically sustainable development. Canberra: Bureau of Rural Sciences, Fisheries Resources Branch; 1998. [6] Garcia SM, Staples DJ. Indicators for sustainable development of marine capture fisheries FAO technical guidelines for responsible fisheries (8). Rome: FAO; 1999. [7] Belfiore S. The growth of integrated coastal management and the role of indicators in integrated coastal management: introduction to the special issue. Ocean and Coastal Management 2003;46(3–4):225–34. [8] Garcia SM, Staples DJ. Sustainability indicators in marine capture fisheries: introduction to the special issue. Marine and Freshwater Research 2000;51(5):381–4.

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