Chapter 3 Delineating Priority Areas for Marine Biodiversity Conservation in the Coral Triangle
Delineating Priority Areas for Marine Biodiversity Conservation in the Coral Triangle
Identifying priority areas for biodiversity conservation requires systematic approaches and integrated ecological and biological information. Here, multiple ecological criteria were analyzed to assess areas of biodiversity importance in the Coral Triangle region, a priority region for marine biodiversity conservation because of its high species richness and endemicity. This study used distribution data of three biogenic habitats to assess the criterion of sensitive habitat, modeled geographic distributions of 10,672 species ranges and occurrence records of 19,251 species to evaluate the criterion of species richness, distributions of 834 species of special conservation concern to examine the criterion of species of conservation concern, distributions of 373 reef fish species to assess the criterion of restricted-range species, and distribution of nesting sites and migratory route of six species of sea turtle to evaluate the criterion of areas of importance for particular life history stages. Areas of biodiversity importance were identified by superimposing each of the different criterion. Further, this study performed two tiers of multi-criteria analysis: (1) a Coral Triangle regional level analysis to identify “clustered hotspots” (i.e., groups of cells) of biodiversity significance; and (2) a site-based analysis to identify the specific sites (cells) of greatest biodiversity importance. This study found that approximately 13% of the Coral Triangle was clustered into hotspots of high biodiversity importance. These areas occurred along the southern part of the Philippines, the north-eastern part of Malaysian Sabah, central to eastern reaches of Indonesia, the eastern part of Papua New Guinea and the Solomon Islands. By comparison, the site-based analysis identified seven sites of highest biodiversity importance in the Coral Triangle include: (1) the northern tip of Sulawesi Island, (2) Ambon Island, (3) Kei Islands, (4) Raja Ampat Archipelago of Indonesian Papua, (5) the Verde Island Passage, the southern part of Negros Island, and (7) Cebu Island. This information is useful to inform participatory decision-making processes in the Coral Triangle region to identify priority areas for conservation and management.
Protected areas have been widely advocated as an effective tool for conserving and managing biodiversity (Brooks, 2010; Venter et al., 2014). Marine protected areas (MPA) benefit conservation of species and habitat (Beger et al., 2003; Williams et al., 2009; Hart et al., 2013; Péron et al., 2013), fisheries management (e.g. increased abundance, species diversity and “spill over” effect) (Russ & Alcala, 2010; Hamilton et al., 2011; Edgar et al., 2014; Smith et al., 2014), and recreational and educational opportunities (Ballantine, 2014; Costello, 2014). Coral reef cover inside Indo-Pacific MPA has shown increases up to 2% per year (Selig & Bruno, 2010), while globally, biomass of large fishes was 35% greater inside compared to outside MPAs (Edgar et al., 2014). Currently, over 12 million km2 of the world’s ocean has been designated as MPAs (Juffe-Bignoli et al., 2014), with a growth of over 360-fold in the last ten years (Klein et al., 2015). However, the proportion of MPA that actually conserve biodiversity is questionable. Around 94% of MPA are ‘take-MPA” that allow fishing within their boundaries and cannot protect all aspects of biodiversity (Costello & Ballantine, 2015). More than 83% of marine species have less than 10% of their home ranges protected within MPAs globally (Jenkins & Van Houtan, 2016). Thus, to support the MPA’s objectives in conserving biodiversity requires additional designation of larger, more effective and fully protected areas through identification of important areas for biodiversity conservation (Ricketts et al., 2005; Butchart et al., 2015).
Previously, a set of ecological and biological criteria was synthesized by Asaad et al., (2016) to aid systematic selection of areas for biodiversity conservation. Based on the review of 15 international initiatives, that reviews identified eight ecological and biological criteria required to identify suitable locations for biodiversity conservation. Four criteria identified areas that contain (1) unique and rare habitats; (2) fragile and sensitive habitats; (3) habitats important for ecological integrity; and (4) a network that is representative of all habitats. Another four criteria were based on species-specific attributes, including (5) the presence of species of conservation concern; (6) the occurrence of restricted-range species; (7) areas containing high species richness; and areas important for life-history stages of particular species. In this study, the application of these synthesized ecological criteria was explored to conduct an assessment of important areas for marine biodiversity conservation in the Coral Triangle region.
The Coral Triangle (CT) Region is situated along the equator between the Indian and Pacific Oceans. This region includes the Exclusive Economic Zone of six countries (Indonesia, Malaysia, The Philippines, Papua New Guinea, Timor-Leste, and Solomon Islands) (Fig. 1.1). It is a global hotspot of marine biodiversity, and contains more than 76% of the world’s shallow-water reef-building coral species (Veron et al., 2009), 37% of the world’s reef fishes (Allen, 2008), 50% of razor clams (Saeedi et al., 2016), six out of seven of the world’s sea turtles and the largest mangrove forest in the world (Polidoro et al., 2010; Walton et al., 2014). In the socio-economic context, the marine ecosystems in this region have a gross domestic product worth $1.2 trillion per year (Asian Development Bank, 2014), and more than 120 million people benefit directly from its ecosystem goods and services (Foale et al., 2013). However, the resources within this region are being threatened by anthropogenic activities and climate change induced impacts (Hoegh-Guldberg et al., 2009; Burke et al., 2012; McLeod et al., 2012). In response, in 2007 the Coral Triangle countries declared their commitment to working collaboratively to conserve and sustainably manage their coastal and marine resources through a multilateral partnership called the Coral Triangle Initiative on Coral Reefs, Fisheries and Food Security (CTI-CFF) (CTI-CFF, 2009, 2013). One of the objectives of this initiative is to establish effective networks of MPAs, by protecting a representative range of biodiversity features (Weeks et al., 2014), encompassing the temporal and spatial scale of ecological systems (Laffoley et al., 2008) and facilitating ecological linkages between protected sites (Green et al., 2014). Currently, there are almost 2,000 MPAs within this region, covering an area of 200,881 km2 (White et al., 2014), which is less than 4% of the marine area in this region. Moreover, under-representation of ecological and biodiversity coverage, and lack of management effectiveness (Weeks et al., 2014; White et al., 2014) are among factors that prevent MPAs within this region from achieving their goals (White et al., 2014). There is thus great interest to overcome the current limitations of MPA coverage and to develop conservation priorities for the protection of biodiversity and ecosystem services in the region (Green et al., 2014; Beger et al., 2015).
Previous biodiversity conservation studies in the Coral Triangle provided insights on MPA development (Green et al., 2009; Green et al., 2014), biodiversity patterns (Hoeksema, 2007; Allen, 2008) and conservation priorities (Ambal et al., 2012; Huffard et al., 2012; Beger et al., 2015) (Table 3.1). However, those studies were limited to specific taxonomic groups, had restricted geographic scope, and/or were based on limited datasets. The framework to design MPAs proposed by Green et al. (2014) was applied at a region-wide scale but has not been used to identify MPAs at national or local scales (Walton et al., 2014). The prioritization analysis developed by Beger et al. (2015) was successful in identifying areas of high conservation value but included only limited information on species connectivity models and insufficient data on threatened species. In other studies, conservation priorities were exclusively applied at national scales, such as the identification of key biodiversity areas in the Philippines (Ambal et al., 2012), and geographic priorities for biodiversity conservation in Indonesia (Huffard et al., 2012). This study identifed areas of importance for biodiversity conservation at the regional scale for the Coral Triangle, based on a comprehensive measurement of biodiversity, encompassing a wide-variety of taxonomic groups, and pre-defined systematic ecological criteria.
This study examined the applicability of the ecological criteria recommended in Asaad et al. (2016) to delineate areas of biodiversity importance. Thus, biodiversity informatics was applied to retrieve and analyze data on habitat and species diversity, and species distributions of multiple taxonomic groups. A multi-criteria analysis were developed and two tiers of analysis were performed: (1) Regional-level analyses to identify “clustered hotspots” of biodiversity significance, and (2) Site-based analyses to identify specific sites of the highest importance for biodiversity protection. This research provides a baseline describing the intrinsic biological and ecological value of the region that benefits local communities, scientists, and decision makers in the identification of priority areas for conservation.
The study area centered on the Coral Triangle countries and their surrounding marine areas, with the bounding coordinates extending from 90E to 175E and 23N to 16S (Fig. 1.1). In the Coral Triangle other scientists have proposed different scientific and ecological boundaries for the Coral Triangle (e.g., Green & Mous, 2008; Veron et al., 2009; and reviewed in Hoeksema, 2007). Here, this study used the boundary as defined by the Coral Triangle Initiative which has declared its implementation boundary to include the full Exclusive Economic Zones (EEZs) of Indonesia, Malaysia, Papua New Guinea, the Philippines, Solomon Islands, and Timor-Leste, and includes the EEZs of two adjacent nations: Brunei Darussalam and Singapore.
Here, the terminology of “Coral Triangle Region” refers to the area covered by the bounding geographical coordinates of the study area, while the term “Coral Triangle Countries” refers to the six countries (i.e., Indonesia, Malaysia, The Philippines, Papua New Guinea, Timor-Leste, and Solomon Islands) that are the signatories of the Coral Triangle Initiatives Declarations. The analysis was extended to the periphery of the Coral Triangle countries to have a comprehensive measurement of biodiversity in the region.
This study explored the application of five ecological criteria recommended by Asaad et al. (2016) for which data were readily available. The distribution data for three biogenic habitats (coral reefs, seagrass meadows, and mangrove forests) were used to assess the criterion of sensitive habitat, collated from global summary reports for each habitat type (Table 3.2). All of these habitat datasets were referenced to a geographic coordinate system of WGS84 (World Geodetic Survey 1984) and a standardized metadata system developed by UNEP-WCMC (Weatherdon et al., 2015).
A modelled geographic species ranges extracted from AquaMaps (Kaschner et al., 2016) was used to assess the criterion of potential species richness (Table 3.2). AquaMaps generates a prediction of relative probabilities of species range at a resolution of half-degree cells. Each cell contains a probability value ranging from 0 and 1, representing the relative suitability of that cell for the specified species. In this analysis, a species was assumed as present in cells where their probability of occurrence values was greater than 0.5. In addition, species point occurrence records from the Ocean Biogeographic Information System (OBIS) (OBIS, 2015) (Table 3.2) were used to complement the AquaMaps species range data (Supplementary Table S3.1). The taxonomic differences between datasets were resolved because OBIS uses the World Register of Marine Species (WoRMS) database (Horton et al., 2016) for species nomenclature and classification. Species names in AquaMaps are also regularly synchronized with the WoRMS database.
To assess the criterion of the occurrence of species of conservation concern, occurrence records of five classes (i.e., bony fishes, anthozoans, elasmobranchs, mammals, and molluscs) were extracted from OBIS (OBIS, 2015) and FishBase (Froese Pauly, 2016) (Table 3.2). These taxa were selected to represent a diversity of threatened taxa and excluded seabirds from our analysis, as most are migratory or wide-ranging. Species were included as conservation concern as recognised by IUCN Red List categories (IUCN, 2015), CITES (UNEP-WCMC, 2015) and national directives of the Coral Triangle countries. A species was assigned as a species of conservation concern if it was categorized as either (1) Critically Endangered (CR), Endangered (EN) or Vulnerable (VU) according to the IUCN Red List of Threatened Species; or (2) listed in Appendix 1 or Appendix 2 of CITES as species that need a greater level of protection from over-harvesting; or (3) classified as threatened or protected based on national regulations. Appendix I of CITES includes species that are threatened with extinction, and Appendix II includes species that, although currently not threatened with extinction, may become so without trade controls. For the national regulations, we used the list of protected species enacted by the governments of Indonesia (Government Regulation, 1999), Malaysia (Fisheries Act, 1985; Fisheries Regulation, 1999), and the Philippines (Republic Act, 2001) (Table S3.2). The assessment using different scales of conservation concern (global to national) was designed to account for a large number of species that may be vulnerable to human activities.
The criterion of restricted-range species was assessed using the distributions of 373 reef fishes (comprising 150 genera and 47 families) that are each endemic to the Coral Triangle (Table 3.2). These data were extracted from a dataset of nearly 4,000 species of Indo-Pacific reef fishes (Allen, 2008; Allen & Erdmann, 2013). Here, restricted-range is defined as a reef fish species with a spatial distribution of less than 5 million km2 and whose known range is only within the Coral Triangle. For consistency, throughout the rest of this paper, these Coral Triangle restricted-range reef fishes will be referred to simply as “restricted-range reef fishes”. We also note that these datasets define reef fishes as fish species that live on shallow water coral reefs and associated substrata (i.e., sand or rubble patches, seagrass beds, etc.) less than 60 m deep (Table S3.3).
Sea turtles nesting habitat and migratory routes were used as indicators of important areas for sea turtles. Six sea turtle species inhabit the Coral Triangle: green, leatherback, loggerhead, hawksbill, olive Ridley and flatback turtles. A total of 2,055 point occurrence records of sea turtles were retrieved from OBIS (OBIS, 2015) and Indonesian sea turtle datasets (MoF-MoMAF, 2010) (Table 3.2). Over 16% of the records were turtle nesting sites (Fig. S3.5).
Datasets of 16 environmental variables were extracted from the Global Marine Environment Datasets (GMED) (Basher et al., 2014), i.e., depth, slope, land distance, temperature, surface current, salinity, wind speed, tide, primary productivity, photosynthetically active radiation (PAR), chlorophyll-a, pH, dissolved oxygen, nitrate, silicate, and calcite. These environmental layers were in an ASCII format at a spatial resolution of 5-arc min (0.083° grid cells, c. 9 km2 at the equator) (Table S3.5).
Areas of biodiversity importance were identified by superimposing each of the different information layers (Malczewski, 2006; Greene et al., 2011; Bottero et al.,2013). This study explored the application of the ecological criteria and two tiers of multi-criteria analysis: a Coral Triangle regional level analysis to identify “clustered hotspots” (i.e., groups of cells) of biodiversity significance, and a site-based analysis to identify the specific sites (cells) of greatest biodiversity importance. An individual “site” was defined as a single half-degree cell.
All datasets were clipped to the Coral Triangle region using a grid approach of half-degree cells (0.5°) using the c-squares geocodes system developed by Rees (2003). C-squares divide the world’s surface to a grid square to enable simple spatial queries. Using this approach, all of the datasets were presented and mapped in a regular shape of a grid square. The Coral Triangle region comprised 13,360 cells, where each cell covered an area of ~55 x 55 km. All of the spatial analyses were performed using ArcGIS ver. 10.5 (ESRI, 2016a). For the biogenic habitat coverage, we classified and scored the cells based on the total number of habitats that fell within each cell, i.e., 1, 2, or 3.
Species richness was determined based on (i) species ranges derived from modelled geographic distributions; and (ii) species occurrence records. For the species ranges, richness was based on the number of predicted species in each cell. Within the study area, the number of species per 0.5° cells ranged from 0 to 5,509. Thus, we classified the cells into five equal interval classes based on the total number of species that fell within each cell, i.e., Class 1 (1 – 1,101 species); Class 2 (1,102 – 2,203 species); Class 3 (2,204 – 3,305 species); Class 4 (3,306 – 4,407 species); and Class 5 (4,408 – 5,509 species). An equal interval classification was chosen to allow an unbiased comparison across criteria.
For the species occurrence records, ES50 (estimated species in random 50 samples) were calculated based on Hulbert’s index of expected species richness (Hurlbert, 1971) and Hulbert’s standard errors (Heck et al., 1975) using the Vegan package in R v3.2.2 (R Core Team, 2016). The Hurlbert index were used rather than simple species richness indices or the number of species present in a designated area, as it is based on a rarefaction technique (Sanders, 1968) that allows for comparison of species numbers between communities and is less dependent on sample size (Boyle et al., 1990; Reiss & Kröncke, 2005). Then, the cells were classified into five equal interval classes, i.e., Class 1 (ES50 1 – 10); Class 2 (11 – 20); Class 3 (21 – 30); Class 4 (31 – 40); and Class 5 (41-50).
Table of Contents
Table of Contents
List of Figures
List of Tables
List of Appendices
1. Thesis Overview
1.1. General Introduction
1.2. The status of marine biodiversity in the Coral Triangle
1.3. Important knowledge gaps
1.4. Thesis objective and structure .
2. Ecological Criteria to Identify Areas for Biodiversity Conservation
2.2. Initiatives to identify conservation areas
2.3 Ecological and biological criteria
2.4. Biodiversity variables
3. Delineating Priority Areas for Marine Biodiversity Conservation in the Coral Triangle
4. Designating Spatial Priorities for Marine Biodiversity Conservation in the Coral Triangle
4.2. Materials and Methods
5. Digital map of the Coral Triangle: An Online Atlas Marine Biodiversity Conservation
5.2. Methods (Web Map Design)
6. General Discussion
6.1. Summary and Conclusions.
6.2. Future Directions
GET THE COMPLETE PROJECT
Prioritization of Marine Biodiversity Conservation in the Coral Triangle