Discovering factors that influence the success of community-based marine protected areas in the Visayas, Philippines

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Abstract

Community-based marine protected areas have become a popular coastal resources management method advocated in many projects and programs. While many case studies have been written about factors contributing to project success, few empirical studies using quantitative methods have been employed. A study was conducted of 45 community-based marine protected areas in Philippines. Several success measures were developed and analyzed in relation to a number of independent variables categorized as contextual or project intervention factors. Correlations between individual factors and the dependent variables are discussed. Stepwise multiple regression was used to determine the most important predictors of success. These included: population size of the community, a perceived crisis in terms of reduced fish populations, successful alternative income projects, high levels of participation in community decision making, continuing advice from the implementing organization and inputs from local government. The implications of these results for policy makers and project managers are discussed.

Introduction

Marine protected areas (MPAs) are widely advocated as a means for managing coastal resources [1]. Their use is proliferating around the world, and they are being touted as the most efficient tool for the management of over exploited coastal resources in developing, tropical countries. The Philippines is an extreme example where government policy, international aid, universities, and non-governmental organizations (NGOs) have resulted in the establishment of over 400 MPAs [2], [3]. What is frightening is the fact that while there is clear evidence that MPAs are an effective tool for conserving and improving coastal resources, there are relatively reliable estimates indicating that only some 20–25 percent of the over 400 MPAs in the Philippines are successful [2]. This is a disturbing scenario because such a high failure rate can result in rejection of the community-based MPA (CB-MPA) concept just as a similarly high failure rate of fishers’ cooperatives resulted in their rejection as a tool for fishery development in the 1970s and 1980s [4].

In order to forestall the untimely rejection of this important tool for coastal resource management we need to increase the success rate. The best way to do this is to determine factors resulting in observed successes and failures of CB-MPAs. Towards this end, case studies have been written and examined (e.g. [1], [5]), published literature has been reviewed (e.g. [6]) and experts have been convened for focus group discussions (e.g. [2]). While such endeavors may give us some insights into factors influencing the success of CB-MPAs, the results are influenced by the fact that information presented is not comparable across the various sites; e.g., we do not know if a certain factor is absent or simply not reported. Additionally, especially with regard to case studies, information is frequently site specific and heavily influenced by the personalities involved in the establishment of the CB-MPA.

Nevertheless, factors uncovered by the foregoing techniques are frequently the result of intimate knowledge of specific projects or sets of projects and are very real for the sites involved. The problem is that the decision-maker frequently needs information that can be used to apply to a situation where a number of CB-MPAs are planned. In such a case, the need is to develop strategies and tactics that will maximize the chances of success. In other words, the decision-maker would like to know that if procedures “A”, “B” and “C” are carried out, the probability of success is “X”. And that if “C” is not carried out, the probability will reduce to “Y” or if “A”, “B”, “C” and “D” are carried out, the probability of success will increase to “Z”. In order to develop this type of information we need an analysis of comparable data collected across a range of sites where probabilities associated with the various factors said to impact success of CB-MPAs can be estimated. Examples of such cross-site studies, at varying levels of precision, include Salafsky et al. [7] who identify factors influencing success of enterprise strategies for conservation, World Bank [8] who identify factors impacting local level management, and Pollnac et al. [9] who examine variables influencing success of fishers’ cooperatives. What we wish to present here is a modest start in this direction for identifying and evaluating factors influencing the success of CB-MPAs.

There are many aspects of “success”, and rather than simply focussing on one, a multi-component approach to success is used in this study. The most obvious measure of success for a CB-MPA involves an improvement in the resource; e.g., measurable increases in the quality and quantity of flora and fauna, including corals where included. Community members’ perception of the MPA's impact on the resource is also an important indicator. It is these perceptions that will influence their behavior regarding the CB-MPA. Another indicator of success is the establishment and maintenance of a set of features inherent to a functioning CB-MPA, such as marker buoys, community signboards, a management plan, a management committee, etc. Degree of adherence to the rules associated with the MPA is also an indicator of success. Finally, since a CB-MPA involves empowering community members to manage their own resources, the degree to which this empowerment is realized is a component of success. We contend that a successful CB-MPA will manifest relatively high levels of all five of the aforementioned success indicators.

The above mentioned focus group meetings of experts [2], literature reviews [6], [10], case studies [1], as well as meetings and workshops (among the most recent being WRI [11]) have identified numerous factors that appear to be related to the success of CB-MPAs. Since most of the cited literature is readily available, there is no point listing the factors here, only to repeat them in the methods and analysis sections of the paper. Instead, the general classification of factors will be outlined. For purposes of the analysis presented here, factors influencing success of CB-MPAs are classified into two broad categories: contextual and project. Contextual factors include social, cultural, political, and economic aspects of the lowest levels of political organization (usually the village and the town where it is located) directly responsible for the CB-MPA. Project factors include aspects of project implementation (e.g., strategies and tactics) and post-implementation activities. The paper will examine how these factors individually and in combination impact the various components of success of CB-MPAs.

Section snippets

Sample

It was decided to conduct the analysis within one nation as a means of controlling for aspects of national legislation and policies which could impact establishment and sustainability of CB-MPAs. A cross-national study would only further complicate an already complicated analytical problem. The Philippines was selected since the nation has had more experience and a larger number of CB-MPAs than any other country. The CB-MPAs in the Philippines also manifest a wide range of levels of success,

Discussion

As a first step in the discussion, it is necessary to provide some examples that will help in understanding the implications of all the preceding, number-filled tables. Correlations tell us about the strength of the relationship between two variables. The test of significance tells us the probability that the observed correlation differs from 0.00, or no relationship. A probability statement, such as “p<0.05”, indicates that there is <1 chance in 20 (or 5 percent) that the observed value is

Conclusions

Overall, the analyses indicate that six factors appear to be the most important of those involved in the overall success of the CB-MPAs in our sample (all the independent variables that appear in Table 12):

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    Population size (relatively small).

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    A perceived crisis in terms of reduced fish populations before the MPA project is started.

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    Successful alternative income projects.

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    A relatively high level of community participation in decision making (high on the democracy scale).

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    Continuing advice from the

Acknowledgments

The authors would like to acknowledge the assistance of our field assistants Bruna Abrenica, Rhodora Bande, Pablin Cadiz, Eliza Dadole, Wendell Galon, Wednesday Gaudon, Prisilla Latoreno, and Perpetua Papa. Their expertise and sense of humor resulted in both a pleasant and productive period of data collection in the Visayas. Thanks also go to Dr. Paciencia Milan, President of the Visayas State College of Agriculture, Baybay and Dr. Hilconida Calumpong, Director of the Silliman University Marine

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