Priority Reef Areas in the Pacific Coast of the ...

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... permits ranking of various sites in order of their importance as potential MPA. ... prominently in rankings of species richness for many taxa. (Roberts et al. 2002). .... the reserve selection software WORLDMAP) performed best but cautioned ...
PHILIPP AGRIC SCIENTIST Vol. 94 No. 4, 384-400 December 2011

ISSN 0031-7454

Priority Reef Areas in the Pacific Coast of the Philippines for Marine Protected Area Deployment Wilfredo Y, Licuanan1,*, Marianne Lorelei S. Medina1, Katrina S. Luzon2, Maricar S. Samson1, Cleto L. Nañola, Jr.3, Rene N. Rollon4 and Michael Y. Roleda1,5 1

Biology Department and Br. Alfred Shields FSC Marine Station, De La Salle University, 2401 Taft Avenue, Manila 1004, Philippines 2 The Marine Science Institute, University of the Philippines, Diliman, Quezon City 1101, Philippines 3 College of Science and Mathematics, University of the Philippines Mindanao, Brgy. Mintal, Tugbok District, Davao City 8022, Philippines 4 Institute of Environmental Science and Meteorology, College of Science, University of the Philippines, Diliman, Quezon City 1101, Philippines 5 Present address: Department of Botany, University of Otago, P. O. Box 56, Dunedin 9054, New Zealand * Author of correspondence; e-mail: [email protected] The present paper seeks to provide a scientific basis for the establishment of marine protected areas (MPA) through an integrated and objective analysis of biodiversity survey data, which permits ranking of various sites in order of their importance as potential MPA. The approach proposed here involves the determination of biodiversity values for each of the four taxonomic groups (corals, reef fishes, seagrasses and seaweeds) and an assessment of the levels of risk for each of the survey sites to human degradation and natural disturbance. The biodiversity and risk scores were then combined into one MPA priority score using a conversion table. Five of the 17 geographic units (mostly small islands) stand out as high priority sites for conservation: Biri in Northern Samar; Ticao and Palaguigue Islands in Masbate; Pujada Bay, Davao Oriental; Homonhon and Suluan Islands, Eastern Samar; and Laoang, Northern Samar. The approach described here provides a framework by which an objective, repeatable prioritization of conservation value of various areas could be undertaken. Although the final measures are not absolute, it allows one to make explicit the assumptions made about the characters and measures used in prioritization and assign relative weights to various species, taxonomic groups and data sets, thereby reducing the impact of an observer’s subjectivity.

Key Words: marine protected area, Pacific Seaboard Research and Development Program, Philippine Pacific coast Abbreviations: DENR – Department of Environment and Natural Resources, GU – geographic unit, MPA – marine protected area, PSRDP – Pacific Seaboard Research and Development Program, UP-MSI – University of the Philippines-Marine Science Institute, WRI – World Resources Institute

INTRODUCTION Marine Biodiversity in the Philippines A remarkable wealth of species is found in the Philippines, the largest contributor to the high biodiversity of the Indo-Pacific center (Carpenter and Springer 2005). The country‘s coastal areas figure prominently in rankings of species richness for many taxa (Roberts et al. 2002). Over 460 of the world‘s 794 coral species are found in the Philippines (Licuanan and Capili 2004; Veron and Fenner 2000). The country has the second largest reef area in Southeast Asia (Burke et al. 2002) and the third largest in the world (Burke et al. 2011), making up 5% of the world‘s coral reef coverage 384

(McManus 2002). In addition, the country has around 44 mangrove species out of a global total of 70 (Spalding et al. 2010; Polidoro et al. 2010), and 16 of the world‘s 50 seagrass species (Sudara et al. 1994). These figures will likely increase as local waters are better studied. For instance, in the Sulu Sea, 21 new species of coral were collected in a 2-wk period, whereas it normally takes a year to collect that number of new species worldwide (Veron and Fenner 2000). Coral reefs and reef fisheries are important sources of income and protein for the country (Gomez 1997; Alcala 2001; UP-MSI et al. 2002). For example, the reefs found in Sumilon and Apo Islands, and Bolinao, Pangasinan, respectively, supply 125 and 350 of the 200 The Philippine Agricultural Scientist Vol. 94 No.4 (December 2011)

Priority Reef Areas in the Pacific Coast of the Philippines

Wilfredo Y. Licuanan et al.

and 500+ species of fish recorded in these areas‘ reefs to local markets (Alcala 2001; McManus et al. 1992). Of the 195 seaweed species collected in the Philippine Pacific coast, 81 species (42%) are considered as commercially important (Trono 2004). Unfortunately, as the Philippines is a biodiversity ―hotspot,‖ it is also highly threatened (Roberts et al. 2002; Conservation International 2011) both by natural occurrences and manmade interventions (Burke et al. 2002, 2011). Generally, Philippine reefs are in a poor state, with only about 4% in excellent condition (i.e., with coral cover exceeding 75%; see Licuanan and Gomez 2002). Recent data analyzed from the Pacific coast of the country revealed that there were no ―excellent‖ reefs in the area, and that coral cover exceeded 50% in only 3 of 105 reef sites surveyed. In one of these sites, not a single living coral was seen.

enhancement of fisheries (e.g., siganids in seagrass meadows), and ease of enforcement (Weeks et al. 2009; Hansen et al. 2011). These deployments increase the chances of failure when the limited technical basis for the MPA design, coupled with high expectations from the local populace, lead to a false sense of accomplishment and widespread disenchantment when the MPA fails to make a substantial impact on fish catch. Criteria for potential MPA site selection clearly need to be refined and adapted to local situations (Allison et al. 1998). This condition is especially true for biodiversity conservation since species distributions are poorly known within the country and the costs of collating existing habitat health information are substantial, hindering the use of algorithms such as Marxan (Hansen et al. 2011). The procedure outlined in this paper is an effort to develop a locally relevant and useful tool.

Marine Protected Areas Protection of marine biodiversity and sustainable fisheries are inexorably linked to coastal habitats in the Philippines and are a consequence of the wide variety of marine species exploited in the country, coupled with the complex interrelations among them and their habitats typical of tropical systems. Efforts to arrest the decline of habitat quality, biodiversity and fisheries yields have thus focused on the establishment of marine protected areas (also known as marine fishery reserves, fish sanctuaries and fishery replenishment areas, among others) in the country (Aliño et al. 2002). These efforts have been spurred by the studies and interventions in central Philippines of Alcala and his co-workers who have demonstrated that restricting access to 25% of the reef can double the fish catch in the remaining parts as long as nondestructive fishing gears are used (Alcala 1988, 2001). Currently, the Philippine Fisheries Code of 1998 (Republic Act 8550) recommends that each coastal municipality set aside 15% of its coastal waters as MPAs. Implementation of RA 8550 has led to numerous efforts and successes at the community (often municipal) level despite the ―opportunistic‖ nature of their selection and design, relying more on stakeholder discussions based on practical considerations such as ease of enforcement and maximizing fish population recovery (Hansen et al. 2011). This is because scientific experts and detailed biophysical information in most areas are in short supply (see Hansen et al. 2011). Efforts such as those of the Philippine Coral Reef Information Network (PhilReefs) and the MPA Support Network (MSN) currently seek to provide the means (data and information, assessment tools, etc.) to rationalize, coordinate and scale up MPA deployments around the country (Lowry et al. 2009). Most community-driven MPA deployments in the Philippines have a very small area, often involving single habitats (often the reef edge) and focusing only on the

MPA Selection Criteria In terms of biodiversity, criteria for site prioritization of protected areas include measures of organismal abundance and rarity, species richness, habitat health and representativeness (Salm and Clark 1984; Magurran 1988; Price 2002; Roberts et al. 2003) and connectivity (Grantham et al. 2003; Shanks et al. 2003). In relation to these criteria, various indices have been proposed for measuring biodiversity, including different diversity measures that consider species richness and/or relative abundances of organisms both in alpha (within habitat) and beta (turnover between habitats) sense (see Magurran 1988). These indices differ in how they weigh rare species (i.e., those occurring in small numbers and or in few of the samples only). Sampling intensity is critical since undersampling of species (e.g., cryptic ones) may make them appear to be rarer than they actually are (Ellingsen 2001; Beger et al. 2003). Also, designation of ―rare‖ taxa is often subjective because ―…the exercise lacks repeatability among observers and assemblages‖ (Goodsell and Connell 2002). Beger et al. (2003) compared the use of hotspots (sites richest in all species or rarest species), maximum complementarity (of rare species and of all species) and random selection methods in using coral and fish biodiversity for selecting marine conservation areas. They found that complementarity based methods (using the reserve selection software WORLDMAP) performed best but cautioned that differences in distribution and response to environmental gradients among the taxa considered will affect the efficacy of selection procedures. Hansen et al. (2011) used the reserve selection software Marxan to evaluate the conservation value of 30 central Philippine MPAs that were set up mainly on the basis of local community preference. They found that the latter ―opportunistic‖ approach performed better than random selection but not as well as a

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