Understanding Factors Considered by Fishermen in Marine Protected Area Planning and Management: Case Study of Claveria, Philippines
This empirical study is an attempt to contribute to
the understanding of what factors fishermen value or consider in Marine
Protected Area (MPA) planning and management using choice experiment.
Results showed that the fishermen in Taggat Norte consider more certain
factors such as MPA size and patrol days when evaluating MPA plans. The
attribute on expected increment in fish catch although relevant was not
accorded significance in their choice behavior. The respondents did not
seem to be willing to trade-off the benefit of an uncertain fish catch
variable with the more definite cost of increased MPA size or number of
patrol days. Policy implications include primary consideration of MPA
size when designing MPA plans and considering to some extent voluntary
fisher labor in MPA management.
Worlds coral reefs and associated invaluable resources continue to decline
owing to pollution and human pressures (Wilkinson, 2004).
Philippine marine fisheries are also characterized mainly by depleted fishery,
degraded coastal environment and critical fisheries habitats (Luna
et al., 2004). To reverse this trend, several regulatory policies
and non-regulatory management tools have been initiated and implemented in the
past decades by regional fishery management organizations, national governments
and concerned institutions. The establishment of MPAs in the Philippines, for
example, began as early as in the 1970s (Balgos, 2005)
with the aim to promote long-term conservation of and ensure sustainable income
from marine resources. Pajaro et al. (1999) listed
more than 400 community-based and local government-supported MPAs. In recent
years, the estimated number of existing and proposed MPAs is over 1300 (Aliño
et al., 2000; Campos and Aliño, 2008).
However, only 10 to 15% of this total number of MPAs in the country are effectively
managed and protected (Aliño et al., 2000;
White et al., 2002).
A major success factor in MPA sustainability as a coastal management tool is
the participation and cooperation of local stakeholders or community involvement
(Pollnac et al., 2001; White
et al., 2002; Martínez, 2008). When
the community or local stakeholders are involved in planning and decision-making
activities of an MPA, they have a sense of ownership for that MPA which increases
their likelihood of supporting it. This is the premise behind the increasing
number of small community-based marine conservation efforts in many parts of
the country. In fact, most MPAs in the country were initiated by community-level
organizations and many continue to be managed by these same organizations (Campos
and Aliño, 2008). A generalization regarding application to individual
communities, however, cannot be made because each success has its own identity
and to a limited degree, each community and local government must navigate their
own course before their program becomes sustainable (White,
This study takes the case of a quasi-MPA in Taggat Norte, Claveria, Philippinesdescribed
as government-initiated and legally backed by an ordinance, but is not currently
being protected since it still has no deployed markers and fishing and seaweed
gathering are still allowed even as it is supposed to be a no-take zone. Claveria
is located in the Northwestern part of the province and bounded on the north
by the Babuyan Channel, the most important marine fishing ground in the Cagayan
valley region in Northern Luzon, Philippines. The Taggat landing center in Claveria
is the second largest municipal landing center in the province considering the
number of fishing boats and the average landed catch especially during the peak
fishing season (Bureau of Agricultural Statistics, 2007).
Initial plans of establishing an MPA in the area were done in 1995 when a Fishery
and Aquatic Resources Development Program (FARDP) was initiated by the Bureau
of Fisheries and Aquatic Resources (BFAR) and the provincial local government
of Claveria as a strategy for its coastal resource management. Accordingly,
the program aimed to uplift the quality of life of the fisher folks through
improved fishery technology and community-based participatory activities in
order to attain sustainability and productivity without destroying the ecological
integrity of nature. In 2000, the Local Government of Claveria, through Resolution
No. 104, S-2000, enacted an ordinance providing for the development, conservation
and regulation and management of the coastal fisheries and aquatic resources
within the territorial jurisdiction of the municipality of Claveria. The ordinance
provided for the classification of municipal waters and foreshore areas for
the purpose of granting rights to fishing villages. This zoning provision also
included the establishment of the municipal marine sanctuary area and reserve
that included at least five geographically specified locations, the no-take
sanctuary of which is near lakay-lakay point in Taggat Norte, including the
Taggat Lagoon (Municipality of Claveria, 2000). The lakay-lakay
point is an elongated enormous rock formation located near the rocky cliffs
and shore on the western tip of Claveria Bay and east of Taggat Lagoon. It is
surrounded with coral reefs and seaweed beds. Other provisions of the ordinance
include: regulatory policies on the conservation and utilization of coastal
and municipal waters, creation of fishery management council, municipal licenses
and fees, registration and licensing procedures, prohibitions and restrictions
and fines and penalties.
The establishment of the MPA in this area was initiated with the aim of protecting the marine habitats from over exploitation, at the same time take advantage of the natural beauty of the marine environment and promote this remote area for tourism. Eight years after the enactment of the ordinance, the policy provisions on registration of fishermen, licensing of fishing vessels and gears, organization of municipal fishery management council and apprehension of the use of illegal fishing gears and fishing or taking of endangered species continue to be implemented although not perfectly complied with. The setting of demarcation marks of the MPA and the prohibition of fishing activities within the designated marine sanctuary, however, is not being enforced yet.
The main purpose of this study is to contribute to the understanding of what factors in MPA management matter to fishermen in the area when considering MPA plans. Results will inform and provide some insights on the fishermens value of MPA and their preferences on the MPA design and management.
MATERIALS AND METHODS
Understanding preferences through choice experiments: Choice Experiment
(CE) is a choice modeling approach under the wide umbrella of conjoint analysis
techniques. It is based around the idea that any good or services can be described
in terms of its attributes, or characteristics and the levels that these take
(Bateman et al., 2002). In a CE, respondents are
presented with a series of alternatives and asked to choose their most preferred
with the status quo baseline usually included in the choice set (Bateman
et al., 2002). In environmental applications, CE involves respondents
being asked to select their preferred alternative from a range of potential
resource management policies described in terms of a set of attributes (Benett,
2004). A review of the method and applications of conjoint analysis for
environmental evaluation done by Alriksson and Oberg (2008)
observed that choice experiments seem to have a comparatively stronger position
in environmental studies than elsewhere. CE has been recently widely applied
for non-market valuation of environmental goods and services (Adamowicz
et al., 1998; Blamey et al., 1999;
Rolfe et al., 2000; Birol
et al., 2006). Wattage et al. (2005) applying
CE to evaluate the importance of fisheries management objectives concluded that
CE is a useful approach for evaluating management alternatives and programs
in the field of fisheries. Hearne and Salinas (2002)
used CE to study tourist preferences for ecotourism development and concluded
that CE is a feasible mechanism to analyze user preferences for the management
of protected areas in developing countries. Wallmo and Edwards
(2008) used CE to estimate the non-market values of marine protected areas
in the Northeast Region of the US and found that roughly half of the respondents
saw reserve size as a normal economic good with positive, but diminishing marginal
For this empirical study, we use CE to understand the attributes relevant to
small-scale artisanal fishermen when presented with MPA plans. Results can be
used to inform policy decision makers on the factors that matter to fishermen
and the values fishermen put on MPAs or marine sanctuaries. The basic strength
of CE technique is its being able to provide information on which attributes
are significant determinants of the values people place on non-market goods
and the implied ranking of these attributes (Bateman et
Attributes and levels used for MPA plans
|aApproximate size from lakay-lakay point based
on geographical coordinates
Attributes, experimental design and survey questionnaire: Fishermen
respondents were presented with a series of alternative MPA plans (choice sets)
described using a common set of attributes, namely: the range or size of MPA,
the expected increment in average fish catch and the volunteer patrol days per
year, with varying levels (Table 1). These three attributes
were selected based on field observation and discussion with key informants
and fishermen in Taggat Norte. The levels were determined based on the status
quo or the present MPA plan level and discussion with key informants in the
village. Final levels were set following the analysis of the survey questionnaire
pre-test and pilot surveys. The change from current condition to the proposed
level was included in the visual presentation of each alternative so that the
respondent is clear on the difference between the plans.
With three attributes and three levels for each attribute, a full factorial
design would generate 27 possible plan combinations. It would, however, be difficult
for fishermen respondents to choose from 27 set of alternatives. Respondents
should not be asked to undertake tasks that are too difficult or complex because
they might not perform them reliably and/or might resort to shortcuts or haphazard
answers (Bateman et al., 2002). Thus, nine plans
of expanding MPA were generated using orthogonal array method. This full set
of nine alternatives was further blocked into three subsets, with each subset
containing three different plans, hence three questionnaire versions. Based
on random assignment, each fisherman was presented with three alternative plans
and an option not to choose any of the plans. Figure 1 shows
a sample plan included in the choice set.
Survey approach and data collection: Most of the fishermen using the
Claveria bay and adjacent fishing grounds and who were involved in the earlier
meetings about the MPA, are from Taggat Norte, Claveria so it was chosen to
be the case study area. The 2006 village census indicated around 280 households,
95 of which have family members engaged in fishing activity. After confirming
with the village chairman and other key informants and based on the list of
fishermen from the municipal fishery technician, the total number of confirmed
household residents was 238 and around 100 fishing households in Taggat Norte.
Not including those covered in the pre-test and pilot surveys, we randomly sampled
50% of the fishing households. The total number of valid questionnaires used
in the analysis was 48. Using face to face interview technique, each respondent
was presented an introductory explanation and a choice set consisting of three
alternatives. The respondent was then asked to choose one most preferred alternative.
The survey was conducted in May, 2008.
Econometric model: The model used in the study is a case of discrete
choice-unordered with more than two categories. Unordered-choice models can
be motivated by random utility model (Greene, 2003). Accordingly,
for the ith respondent faced with J choices, we assume the utility of choice
j is of the Eq. 1 form:
where, Vij is the deterministic or observable component of utility
and eij is the error component or the unobservable components influencing
the choice. If the respondent chose plan j, then it is implied that the utility
of choosing plan j (Uij) is higher than the utility of other plans
(Uik). The probability that a respondent i will choose the alternative
j from the set of J choices is Eq. 2:
For this study, we specified the deterministic component of utility (V
j) to be of the Eq. 3 form:
Vj = b0 + b1 MPA4j
+ b2 MPA6j + b3 FISH20j + b4 FISH30j
+ b5 PATR15j + b6 PATR20j
where, the dependent variable in this model is a variable that takes a value
of 1 for the chosen alternative and zero for the alternatives not chosen. Independent
variables, on the other hand, consist of six dummy variables representing the
attributes of the alternatives: MPA4j and MPA6j which take a value of 1 if the
MPA is expanded offshore by 400 and 600 m more than the current state, respectively
and zero otherwise; FISH20j and FISH30j take a value of 1 if the expected fish
harvest increases more than the current state by 20 and 30%, respectively and
zero otherwise; PATR15j and PATR20j take a value of 1 if the patrol days per
year are 15 days and 20 days, respectively and zero otherwise. The corresponding
bs of the independent variables are the parameter estimates.
Since, there are three levels for each of the attribute dummy variables, the minimum condition (that is, 200 m from offshore, 10% expected increase in fish catch and 10 patrol days per year) was set as the reference or base level from which the other levels are compared with. This corresponds to the constant term b0 in the parameter estimates.
Under the assumptions of independently and identically distributed Type I extreme
value error terms; that when no alternative plan is chosen, the current utility
Uos deterministic utility Vo is 0 and the difference
between e0 and ej follows a logistic distribution, then
the choice probability for plan j can be estimated as multinomial logit model
(McFadden, 1973) which can be expressed as:
RESULTS AND DISCUSSION
Table 2 shows estimated coefficients for the multinomial logit model. Initial analysis showed that the coefficients of the independent variables: MPA4 and MPA6 were both statistically significant at 1% level and PATR20 was statistically significant at 5% level. On the MPA size, with the coefficient for the MPA size at 200 meters normalized to 0, the estimated significant negative coefficients -2.371 for MPA4 and -1.818 for MPA6 indicate that other factors constant, fishermen would less likely prefer 400 and 600 m MPA relative to the 200 m. In other words, fishermen in the study site would significantly prefer smaller size MPA. As it is expected that the coefficient of MPA6 would be slightly smaller than MPA4 and the coefficients showed otherwise, we tested whether the two coefficients are statistically different from each other and found that they are not statistically different. This implies that per respondent evaluation, the difference between 400 or 600 m is not important (or almost the same in a sense) relative with the other factors such as fish catch and patrol days. Hence, we re-estimated the model considering the same coefficient for MPA4 and MPA6 for use in the choice probability analysis.
In the case of fish catch, we also normalized to zero the 10% expected increase
and compared it with the expected fish catch increase at 20% (FISH20) and 30%
of the Multinomial Logit Model, Taggat Norte, 2008
|Summary statistics; No. of respondents = 48; Log likelihood
at zero = -56.5361; Log likelihood at convergence = -52.0862; McFaddens
Pseudo R2 = 0.0787; **, ***Significant at 5 and 1%, respectively
probabilities of accepting MPA plan
|*Based on the constant coefficient
Both did not yield significant coefficients implying that the respondents
evaluations of plans with 10, 20 or 30% expected increase in fish catch did
not differ significantly.
The coefficient of 10 patrol days level was also normalized to zero and used as reference for PATR15 and PATR20. The negative coefficient for PATR15 was not significant compared with the reference 10 patrol days suggesting that the decrease in fishermens utility for patrolling 15 days per year is not significantly different with patrolling for 10 days. However, PATR20 had a significant negative coefficient signifying that fishermen have significantly lower preference for any plan that would require them 20 patrol days per year, compared with 10 patrol days.
Table 3 shows the results of choice probability analysis (probability of agreement with proposed plans calculated by using estimated coefficients). As shown, the variables MPA4, MPA6 and PATR20 had statistically significant coefficients with reference to the minimum combination (MPA size expanded by 200 m and 10 days patrol). A plan, in which MPA will be expanded offshore to 200 m more than the current range, the expected fish catch will increase by 10% more than current average catch and the patrol days will be 10 days per year (case 1 in the table or constant in this model), for example, had a 0.62 probability of acceptance, that is, 62% of the fishermen are predicted to agree with the plan. Fishermen will unlikely prefer any plan of expanding the size of the sanctuary to 400 or 600 m, as shown by the 0.17 probability value. The forecasted choice probability values suggest that any plan with an MPA expansion of only 200 m would be selected by majority of the respondents.
In addition, the choice probability by fishermen will decrease to 0.20 if 20 patrol days will be served in a year (case 4). This result suggests that any plan for fishermen patrolling would be more acceptable if it is within 15 days in a year. Finally, the probability of a plan of increasing the MPA size by 400 or 600 m and at the same time requiring 20 patrol days being preferred is almost nil (cases 5 and 6).
The abovementioned results confirmed that fishermen in the area are not entirely unwilling to support any plans of MPA establishment. The results, however, indicate that relative to the other factors, the MPA size is an overwhelmingly important factor to fishermen in the area. Lesser MPA size is much preferred as this would mean lesser reduction in fishing ground and thus perceived lower cost to them (The context of the study is that the marine sanctuary is a year-round no-take zone which is what is currently in the ordinance). Fishermen consider more the size of MPA even relative to any expected increase in fish catch. Some respondents mentioned during the face to face interviews that a 400 or 600 m would already imply that the sea basin in the remaining available fishing ground comprise mostly of sand and less coral reef and fewer fish can be caught. The longer range of MPA would also imply that they will be obliged to go farther to fish which will require more fishing effort despite the promise of increased average fish catch in the long-run.
The importance of size as a factor was also emphasized in Wallmo
and Edwards (2008) in studying value of ecological reserves and analyzing
trade-offs between reserve size and allowable uses. They suggested that smaller
reserves with liberal uses may provide considerably more value than larger no-take
No statistically significant difference was found among the 10, 20 and 30%
expected increment in fish catch. A possible explanation for this is that fishermen
consider the attribute on fish catch an uncertain feature relative to the certainty
of MPA size and patrol day factors. Particularly on the short-run, an immediate
increase in fish catch is less tangible compared with the reduced fishing ground
and number of patrol days. Much scientific evidence is available on the ecological
and biological positive impact of marine no-take zones, but some bio-economic
exercises also present some uncertainties and conditionality particularly on
the net economic benefits of MPAs. Alban et al. (2008)
presented some literature review. The size of the no-take sanctuary relative
to the total fishing ground in the area, for example, is crucial in the rehabilitating
habitat and increasing fish productivity impacts of MPAs (Soliman
et al., 2002). Thus, despite the awareness of fishermen on the conceptual
rationality of the benefits from MPA in improving fish stock and ecosystem conservation
and the study context explained during the survey of the attainability of increased
fish catch through MPA establishment, there is still much uncertainty attached
to fish catch, for example, natural conditions such as weather, or occurrence
of typhoon and other human-related factors that may explain the reservations
fishermen may have on banking on expected fish catch. With socio-economic gain
as the primary motivation of local communities to participate in resources management
(Meñez, 2002), this reservation may explain the
result of the choice behavior.
Finally, the factor on patrol days, like MPA size, is also more certain variable
and can be set definitely. The use of time of fishermen is entirely their own
decision and the number of patrol days maybe definitely set. Committing to 10
or 15 patrol days in a year or around one day per month, for example, is a clearly
decidable factor for fishermen. The results presented also imply that fishermen
are not unwilling to contribute effort in patrolling the MPA. A potential commitment
of 10 or 15 patrol days in a year or around one day per month for one year for
each fisherman can be a significant contribution in managing the MPA. Further,
if we take the willingness to contribute labor as an indicator of willingness
to pay for the MPA such as the approach taken by Muranaka
and Terawaki (2005) and Casey (2003), then the analysis
of the choice probability presented here may mean that fishermen have a positive
willingness to pay for the MPA but up to a certain limit.
Findings of the study contained in this paper point to the conclusion that fishermens choice behavior consider more certain factors such as MPA size and patrol days when considering MPAs. The attribute on expected increased fish catch, although it is an important consideration to them considering that fishing is their major source of income and livelihood, is an uncertain attribute and was not accorded much significance in their choice behavior. Based on the hypothetical plans, the respondents did not seem to be willing to trade-off the benefit of an uncertain increase in fish catch with the more certain cost of increased MPA size or number of patrol days. Some policy implications of the results are (1) that the size of MPA must be a prime factor that should be discussed with stakeholders when designing and establishing MPA plans and management options especially no-take zones, (2) that efforts to identify the potential losers in the MPA establishment and how to compensate them B for example, alternative or supplementary income sources for displaced artisanal fishers must be made clear in the planning and development of an MPA and (3) that fishers to a certain extent may be willing to contribute voluntary labor for MPA management. Information drive and educational campaigns showing first hand evidence on the value of MPAs in habitat improvement and conservation and eventually productivity enhancement will also be helpful.
For further research, investigation considering socioeconomic and biological factors would contribute to better understanding of choice behavior and MPA design and planning. In addition, particularly for the fishermen in the study area, direct elicitation of monetary values might be deemed unrealistic considering the cash constraints faced by artisanal fishermen. Designing the CE to extend analysis for valuing marine protected area in monetary terms via willingness to contribute labor is set for further study.
Adamowicz, W.P., P. Boxall, M. Williams and J. Louviere, 1998. Stated preference approaches for measuring passive use values choice experiments and contingent valuation. Am. J. Agric. Econ., 80: 64-75.
Alban, F., G. Appere and J. Boncoeur, 2008. Economic Analysis of Marine Protected areas a Literature Review. EMPAFISH Project, London.
Aliño, P.M., H. Arceo and A.J.N. Palomar, 2000. Uychiaoco Challenges and opportunities for community participation for the management of marine protected areas (MPAs) in the Philippines. Proceedings of the 9th ICRS, Oct. 23-27, Bali, Indonesia.
Alriksson, S. and T. Oberg, 2008. Conjoint analysis for environmental valuation a review of methods and applications. Environ. Sci. Pollut. Res., 15: 244-257.
Balgos, M.C., 2005. Integrated coastal management and marine protected areas in the Philippines concurrent developments. Ocean. Coast. Manage., 48: 972-995.
Bateman, I.J., R.T. Carson, B. Day, M. Hanemman and N. Hanley et al., 2002. Economic Valuation with Stated Preference Techniques a Manual. Edward Elgar Publ Ltd., UK., pp: 248-295.
Benett, J., 2004. Estimating the Value of Coral Reef Management Options. In: Economic Valuation and Policy Priorities for Sustainable Management of Coral Reefs, Ahmed, M., C.K. Chong and H. Cesar (Eds.). WorldFish Center, Penang, Malaysia, pp: 41-49.
Birol, E., M. Smale and Á. Gyovai, 2006. Using a choice experiment to estimate farmers` valuation of agrobiodiversity on hungarian small farms. Environ. Resour. Econ., 34: 439-469.
Blamey, R., J. Gordon and R. Chapman, 1999. Choice modeling assessing the environmental values of water supply options. Aust. J. Agric. Resour. Econ., 43: 337-357.
Direct Link |
Bureau of Agricultural Statistics (BAS), 2007. Number of boats landing by landing center, by Municipality. Region 2, Philippines, 2007.
Campos, W. and P.M. Aliño, 2008. Recent advances in the management of marine protected areas in the Philippines. Kuroshio. Sci., 2: 29-34.
Casey, J., 2003. The value of forest conservation: Willingness-to-Work (WTW) to protect local forest resources in Calakmul, Campeche, Mexico. Problemas del Desarrollo: Revista Latinoamericana de Economía, 34: 125-142.
Direct Link |
Greene, W.H., 2003. Econometric Analysis. 5th Edn., Prentice Hall, New Jersey.
Hearne, R.R. and Z.M. Salinas, 2002. The use of choice experiments in the analysis of tourist preferences for ecotourism development in costa rica. J. Environ. Manage., 65: 153-163.
Luna, C.Z., G.T. Silvestre, M.F. Carreon, A.T. White and S.J. Green, 2004. Sustaining Philippine marine fisheries beyond turbulent seas a synopsis of key management issues and opportunities. Turbulent Seas the Status of Philippine Marine Fisheries. Coastal Resource Management Project, Cebu City, Philippines, pp: 345-358.
Martínez, R.E.R., 2008. Community involvement in marine protected areas the case of Puerto Morelos reef Mexico. J. Environ. Manage., 88: 1151-1160.
McFadden, D., 1973. Conditional Logit Analysis of Qualitative Choice Behavior. In: Frontiers in Econometrics, Zarembka, P. (Ed.). Academic Press, New York, pp: 105-142.
Meñez, M.A.J, 2002. Myths and realities of participation in philippine cbcrm lessons from an analysis of who participates in what. Proceedings of the 9th Conference of the International Association for the Study of Common Property, Jun. 17-21, Victoria Falls, Zimbabwe,
Municipality of Claveria, 2000. Resolution No. 104, S-2000. Ordinance seeking to enact coastal, fisheries and aquatic resources code. Claveria, Cagayan, 2000.
Muranaka, T. and H. Terawaki, 2005. Socioeconomic evaluation of the management of hilly areas using the stated preference approach the wtp and wtw of residents in the kannon-no-mori area in okunaka, nakamachi, hyogo prefecture. Human Geography, 57: 27-46.
Pajaro, M.F., B. Olano, S. Juan and C. Nozawa, 1999. In ventory of marine protected areas in the Philippines. Proceedings of the Workshop on Marine Protected Areas in the Philippines. Dec. 15-16. Marine Science Institute, UP Diliman, Quezon City.
Pollnac, R.B., B.R. Crawford and M.L. Gorospe, 2001. Discovering factors that influence the success of community based marine protected areas in the Visayas Philippines. Ocean. Coast. Manage., 44: 683-710.
Direct Link |
Rolfe, J., J. Bennett and L. Louviere, 2000. Choice modeling and its potential application to tropical rainforest preservation. Ecol. Econ., 35: 289-302.
Shinbo, T., C.C. Launio and Y. Morooka, 2009. Economic valuation of the Marine Protected Area (MPA) of San Miguel Island in the Bicol Region the Philippines. Proceedings of the Annual Scientific Conference of Japanese Agricultural Economics Society, Mar. 28-30 (In Japanese).
Soliman, V., R. Dioneda, A. Mendoza and N. Dullesco, 2002. Critical issues for rational management of the fisheries of lagonoy gulf bicol region Philippines. Bicol. Univ. Res. Dev. J., 15: 40-49.
Wallmo, K. and E. Edwards, 2008. Estimating non-market values of marine protected areas a latent class modeling approach. Marine. Resour. Econ., 23: 301-323.
Wattage, P., S. Mardle and S. Pascoe, 2005. Evaluation of the importance of fisheries management objectives using choice experiments. Ecol. Econ., 55: 85-95.
White, A.T., 2007. Status of coastal and marine resources implications for fisheries management and poverty in Southeast Asia. Proceedings of the International Conference on Fisheries and Poverty, Apr. 10-11, Makati city, Philippines.
White, A.T., A. Salamanca and C.A. Courtney, 2002. Experience with marine protected area planning and management in the Philippines. Coast. Manage., 30: 1-26.
Wilkinson, C., 2004. Status of coral reefs of the world. Global Coral Reef Monitoring Network and Reef and Rainforest Research Centre, Townsville, Queensland, Australia.