Comparison between performance measure drivers

Table 4.4 also allowed us to compare common and distinct patterns in terms of significant explanatory factors for all the measures of success. MPA features and management actions were extremely important in predicting performance, in particular MPA size, age and no-take areas, which often interacted with one-another. Management actions emerged as important relate to MPA regulations, enforcement as well as community projects, such as alternative

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livelihoods schemes. Financial variables which emerged as important related more to sources and spending of funds, than of absolute levels of funding. Threats in inside the MPA, as well as the % of reefs at risk in the past, as use for fishing also occurred often, as was expected. Local contextual factors were minimal, compared to national contextual factors (such as level of economic development), but this may have been due to the smaller number of local contextual variables available for inclusion. In terms of the survey variables, only affiliation with an NGO was significant, for a single measure.

Those variables which were significant in the expected direction (table 4.5) were zoning, community management, American and Pacific MPAs, those with multiple aims, having a management plan, visitor pressure, fisheries management, the number of staff, the level of enforcement and the number of large scale threats. Community related variables; namely institutions associated with management, incentive initiatives and compensation also had positive effects as expected.

Those variables which were significant in the opposite direct expected included co-management, strict IUCN category, those MPAs located in Asia, level of monitoring effort, being in a LDC. Several variables also showed mixed results on MPA performance; the existence or size of the no-take area, the MPA age, number of banned activities, fishing pressure, coastal zone management and the % reefs at risk.

Variables which did not emerge as significant, but might have been expected to be included:

the proportion of the MPA which was no-take, the interaction between the no-take area size and age, as well as government or NGO management, the absolute numbers of staff or budgets, MPA aims (apart from tourism), world heritage status, staff training or technical support, conflict resolution, being part of an MPA or monitoring network, education, management effectiveness monitoring, visitor and fisher pressure and the interaction between them, proportion of jobs related to tourism or retained locally, tourist sports fishing activity, the set-up budget, percentage funding from revenues or used for community projects, respondent affiliation and data quality for coral cover estimates.

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Table 4.5 Comparison of Significant predictors of MPA performance against hypotheses from previous research. Previous research was collected which qualitatively or quantitatively assessed factors associated with MPA management effectiveness. These were used to build hypotheses in the first column about which MPA features, actions and contexts were expected to be positively (+), negatively (-) or non-linearly related (Q) to MPA performance (table 2.2). The observed relationship between these explanatory variables and the performance measures is given in the second column. The number of symbols indicates the number of times a significant relationship was demonstrated. NA denotes the fact that no relationship was detected.

Aspect Expected

Part of physical or monitoring network of MPAs + NA

Region Americas, Asia - Asia + + +

No. regulations or bans on potentially destructive

activities + ++, -

% activities detected and/or enforced + + + + +

Community involvement and/or consultation + ?

Community institutions + + +

Creating local community incentives + + + +

Environmental education and outreach programs + NA

Conflict resolution mechanisms + NA

Social and ecological research and monitoring + -

Management effectiveness evaluation + NA

Technical supervision / advice + NA

Compensation to groups suffering user costs + + +

Financial

MPA funding (absolute / per area / for active

management costs) + + + +, Q

Facilities, equipment and infrastructure + ?

% funding from user fees + / - NA

variables Respondent is part of management staff NA

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122 4.5 Discussion.

The models developed for performance (table 4.4) were able to explain at least 67% of the variation in each performance measure, which suggested many of the drivers of performance had been incorporated into this analysis. The lack of survey variables emerging as significant in the regression analyses also suggested that bias is minimal. The results showed that perceived success was linked to coral cover compared to outside the MPA, species and fisheries changes, compliance and economic benefits. Thus MPAs can be perceived as successful despite limited reduction in threats or increased coral cover improvements and conflict. Often, this is justified, as they are nevertheless improving these aspects compared to outside the MPA. Perception of achievement of aims was similar, but also incorporated temporal changes in coral cover, which makes sense in the context of habitat conservation as the predominant goals for MPAs (Francis et al., 2002; McClanahan et al., 2006). Nevertheless, the drivers of these two measures were largely different, with funding concerns important for overall success and threats and the original aim as solely important for fulfilment of aims. This suggested that both measures should be included in MPA evaluations, as they are distinct.

Unexpectedly, the relationship between increased employment and number of jobs was negative. This was likely to be because changes in employment are not the same as the number of jobs available, but this could also suggest that these measures are inaccurate. It is also possible that since it was not defined, respondents could have interpreted the necessary link between the MPA and the jobs differently, limiting the usefulness of this metric. Further clarification of metrics which are more prone to individual interpretation is recommended in future research using expert knowledge. Also trends, as were often employed in this analysis are easier to evaluate than more detailed metrics such as number of jobs.

Only one of the correlations between performance measures other than overall success and aim achievement was above 0.5. This points to the fact that MPAs that perform well in some areas do not often perform well in others (Christie, 2004; Pomeroy et al., 2007). This validates the approach of not using a composite indicator of success (Hudina, 2006; Holtzman et al., 2008), and suggests that trade-offs need to be made in terms of prioritising management aims (Hicks et al., 2009). However, results suggested that MPAs that have achieved fisheries and endangered species improvements also often increased local economic welfare. In addition, MPAs with reduced threats and destructive activities were often able to achieve better habitat improvements (Allison et al., 1998; Burke et al., 1998; Wilkinson, 2006).

The previous chapter identified age, having a no-take area, region and to a lesser extent size as having significant effects on many outcomes for this sample of MPAs, using bi-variate

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analyses. The conclusion of the importance of no-take areas in increasing MPA performance remains here, despite other significant variables having demonstrated importance.

Furthermore, some of the impacts of no-take areas were also likely to be absorbed by the number of zones, as any MPA with a no-take area has at least two zones and the mean number of zones is only 2.1. The number of threats inside the MPA had an important impact on half the performance indicators. Whilst larger MPAs had more threats, those with larger no-take areas had fewer, so this makes a case for having a relatively large proportion of an MPA as no-take. Conflict resolution was an activity that had a significant relationship to reduced conflict when bi-variate analyses were used (chapter 3), but did not emerge as significant here when other contextual and management variables are included.

MPA age was significant in three of the eight regressions, and has positive, negative and non-linear links to these outcomes (Claudet & Pelletier, 2004; Leverington et al., 2008). Thus age has a complex effect on MPA performance, and different impacts of different facets of performance (Syms & Carr, 2001). Other aspects of MPA features, including governance and size, appeared to be important in determining benefits. MPA size had also relatively limited effects on a small number of measures, but larger MPAs performed better each time and size interacts with age. In the previous chapter, regions emerged as having a strong impact on performance, however this was less true here, once other variables had been taken into account. This validated using regressions to look at the combinations of many aspects on MPA performance. No-take areas were demonstrated to have important impacts on performance. However, much of their impact could be masked by the number of zones, which was also significant.

Only Asia emerged in three regressions as having out-performed other regions, which is surprising, given the high level of coral damage and the destructive uses that had occurred there, which have meant that 37% of corals are effectively dead and 47% of the remaining corals are at high risk (Wilkinson, 2004) and that Asian MPAs have more threats within their boundaries (chapter 3). However, since this research emphasises additionality (through comparison with counterfactuals), it is exactly the MPAs that outperformed their surroundings that would emerge most succesful, as has been stressed by other authors e.g. (Salafsky et al., 2001).

This research enabled us to infer which factors seemed to be important in determining MPA performance and could help to increase resilience of coral reef habitat in the context of future stressors. Community managed areas were more successful at reducing conflict, but in general, no specific governance type was associated with improved outcomes. This is because the best

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management body at a given site is likely to depend on the context, including the institutional capacity, the nature of threats and local values and norms (Christie & White, 2007). Similarly, MPA aims seemed to have no bearing on their performance, apart from those established to increase tourism. This meant that MPAs cannot necessarily be relied on to achieve conservation goals (Allison et al., 1998).

Management actions which were carried out at an MPA have a great deal of influence over outcomes, even in newly established MPAs. MPAs which detected and punished illegal activities produced better outcomes. Increasing enforcement was linked to decreased threats, which in turn was linked to improved habitat quality. Regulations for a large number of activities helped to improve certain outcomes. Since many of these were established in management plans or in the IUCN designation, these variables may be related. Benefits to community members, in terms of projects that increase community welfare, that provide alternative sources of income other than fishing and which compensate those who lose out as a result of MPAs, emerged as an extremely important determinant of MPA performance, as have been emphasized by other terrestrial research and to a lesser extent MPAs (Leverington et al., 2008; Mascia, 2004; Pollnac et al., 2001a; Pomeroy et al., 2007; Tupper et al., 2008a).

In terms of financial aspects, absolute funding was not significant, although funding per km² managed is for two of the performance measures. Spending and funding sources were more important than absolute levels of funding. MPAs that did not return funds to government and those spending on active management have most success. The percentage of funding was not significant, neither was spending on community projects, although these were related to community projects featured in management variables.

Variables which seemed to be only marginally significant, but may have been expected to be more significant included education (Browning et al., 2006; Christie & White, 2007; Mascia, 2000; Tupper et al., 2008a) and frequent research and monitoring (Kelleher, 1996; Leverington et al., 2008; Lundquist, 2005; Mascia, 2000; Tupper et al., 2008a). In addition, this research suggested that less effort and emphasis should be put on several aspects of MPAs commonly thought to be critical for success; the set-up budget, management effectiveness monitoring, monitoring and inclusion in networks, partnering with international organisations, staff training, low fishing pressure and low or high levels of tourist visitation. This is not to say however that these will not have beneficial effects at some MPAs, as these are process-type activities that are not expected to directly impact performance, but are nevertheless valuable.

Contextual factors did also affect MPA outcomes. These included the level of local use for subsistence fishing which was positively correlated with performance, but the importance in

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terms of commercial fishing had the opposite relationship. Active fisheries management beyond designation of a no-take area and coastal zone management will also improve MPA performance. A higher GDP in the MPA‟s host country is related to, improved overall success, although there is more opportunity to improve local levels of wealth for MPAs in developing countries. Overall, it was the interaction of contextual factors, MPA features and management that determined performance, yet the most importance must be placed on endogenous factors. This is encouraging, as these are factors that management can affect, given appropriate financial and technical resources.

The approach of using expert opinion to gather information on a range of performance indicators was cost effective, but also dependent on the level of knowledge of the respondent.

However, most respondents familiar with a site are expected to know whether conflict has significantly increased, decreased or stayed the same. This means that this method is also limited to information that is commonly known about MPAs and excludes finer scale information about habitat and fisheries effects, which necessitate expensive on-site research.

Other potential problems with this analysis which need to be considered include the difficulty of teasing apart causation and correlation e.g. number of staff and decreasing coral cover over time. Many variables are also likely to show endogenity, however, this would be expected to be more problematic in a time-series analysis. The research would have been strengthened by a greater sample size and a greater number of responses for each MPA to help validate responses.

Factors that were not able to thought to be accurately assessed using expert surveys, but might be expected to have an impact on performance include factors related to the choice of locations where the MPA was situated, border demarcation, the level of stakeholder consultation, historical rates of use and visitation, the level of participation of local communities in management, management infrastructure, perceived equity of costs and benefits generated by the MPA, the level of technical assistance and success of community and development projects.

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126 4.6 Recommendations.

This research has important implications for MPA establishment and management. MPAs with multiple goals are unlikely to fulfil all of these goals simultaneously. MPAs need to be established that have features that are likely to produce the main aim of that MPA. MPAs work most effectively when combined with coastal zone management and active fisheries management. They should be as large as possible, with at least two zones (one being a no-take area). However, no-take areas should not be established without community consultation.

Benefits cannot be expected to materialise straight away and stake-holders should be warned of this. This is especially true for threat reduction and coral cover changes and aim achievement. MPAs should be able to keep monies raised on site for active management costs. Funding should be targeted to both enforcement and projects that benefit community members, especially where opportunity costs have been severe.

Future research should be undertaken, which uses the 13 performance measures here, on a larger scale. A five point scale could be used for perceived temporal changes in outcomes, instead of a three point scale, to increase the quality of information. This would enable more information as to the magnitude of effects of various inputs. Validation could be achieved by using at least 5 responses for each MPA (from respondents with different affiliations). These performance measures, which focus on changes over time and spatial comparisons should be regularly assessed at MPAs, using data from monitoring, as a tool for adaptive management over time and to help demonstrate efficacy to donors or to highlight areas of concern. Further research is needed to explore the temporal aspects of MPA performance as well as research to understand the causes of conflict, which was a common problem at these MPAs.

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