Terumbu Karang yang Terancam di Asia Tenggaraoleh , dan -
Memberikan analisis rinci dari ancaman terhadap terumbu karang di Asia Tenggara dan memberikan valuasi ekonomi pada apa yang akan hilang jika ancaman-ancaman ini -- penangkapan ikan yang merusak, penangkapan ikan yang berlebihan, polusi dari laut dan daratan, pembangunan pesisir -- terus berlanjut.
Reefs at Risk in Southeast Asia CD
The Reefs at Risk in Southeast Asia (RRSEA) Data CD contains the range of data assembled and model results developed under the RRSEA project. Included on this CD are over fifty spatial data sets reflecting physical, environmental and socioeconomic variables for Southeast Asia as well as the results of the modeling of human pressure on coral reefs for the region. The CD also provides full technical notes on the threat modeling method and the Reefs at Risk report in .PDF format.
Spatial data sets are best viewed using ESRI ArcView software, but can also be viewed using ESRI ArcExplorer, a public domain software provided on this CD.
To order a copy of this CD, contact email@example.com.
GIS Data Sets
Point Data Sets (ZIP archive, 24.7 Mb) reflecting coral reef locations classified by estimated threat. This option provides six point data sets, a polygon data set of watershed boundaries (with associated erosion estimates) and a polygon data set reflecting country boundaries. (The six threat estimates are for the individual threats - coastal development, marine-based pollution, overfishing, destructive fishing, and sediment and pollution from upland sources, in addition to integrated threat -- the Reefs at Risk threat index.) The archive also includes an ArcView project file which requires ESRI's ArcView software.
GRID Data Sets (ZIP archive, 23.1 Mb) reflecting threat estimates, and coral reef locations classified by threat estimate. This option provides 17 grid data sets, a polygon data set of watershed boundaries (with associated erosion estimates) and a polygon data set reflecting country boundaries. The grid data sets include both a threat surface (a threat estimate for all areas) and reef locations classified by the threat estimate for each of the threats considered. These are coastal development, marine-based pollution, overfishing, destructive fishing, and sediment and pollution from upland sources, in addition to integrated threat - the Reefs at Risk threat index. The archive also includes an ArcView project file which requires ESRI's ArcView software and Spatial Analyst 2.0 extension.
The Reefs at Risk model
The Reefs at Risk in Southeast Asia (RRSEA) project includes an area in Southeast Asia approximately bounded by 90 degrees E and 142 degrees E longitude, and 30 degrees N and 11 degrees S latitude. Data were integrated and the analysis performed in an equal area projection (Lambert Equal Area Azimuthal 126,6) at a 1,000 meter (1 kilometer) resolution.
Input data sets and the model method have been extensively reviewed and significantly revised based on input from project partners and at two regional workshops (the RRSEA workshop, April 2000 in Quezon City, Philippines, and the International Coral Reef Symposium (ICRS), October 2000 in Bali, Indonesia).
The model groups threats into five main categories: coastal development, marine-based pollution, overfishing, destructive fishing, and sedimentation from inland sources. Several component sources of potential degradation were identified for each threat category. For example, cities, settlements, airports, mines, and tourist resorts were identified as the primary elements contributing to degradation of coral reefs from coastal development. Once components were identified, they were then converted into a threat estimate using distance-based rules. For three threat categories – coastal development, marine-based pollution, and pollution and sedimentation from inland sources – this “raw” threat estimate was adjusted based upon an indicator of the natural vulnerability of the area to pollution and sedimentation. In addition, three “raw” threat estimates – overfishing, destructive fishing, and coastal development – were adjusted to account for the management effectiveness of the area. The adjustment factors were applied only to those threats for which the adjustments were considered relevant. The five adjusted threat estimates were then combined into an integrated estimate of threat from human activity. A 1-km resolution grid reflecting coral reef locations was overlaid with the integrated threat estimate to produce the Reefs at Risk Index - coral reefs rated by estimated threat from human activities.
The modeling was done at WRI using an iterative approach with extensive input from project partners. Figure 1 provides an overview of the model. The following sections describe the modeling and data sources in detail.
Coral reef locations
The United Nations Environment Programme-World Conservation Monitoring Center (UNEP-WCMC) provided a base data set reflecting coral reefs locations for Southeast Asia. These data were revised substantially during the RRSEA project based upon input and data from project partners.
This indicator is designed to account for differences in how the physical oceanography of a reef contributes to varied responses to pollutants, such as local flushing rates and bathymetry. The model applies natural vulnerability as an adjustment factor in RRSEA’s analysis of threat from coastal development, marine-based pollution, and inland pollution and sedimentation. The natural vulnerability indicator is based upon (in order of importance) the degree of enclosure or embayment, fetch, depth of water surrounding reef, and tidal range. Each component of this layer was developed as a four-class ranked indicator, with lower numbers indicating lower vulnerability.
a) Embayments were developed at WRI using ArcWorld (ESRI, 1992) coastline (1:3 million) as the base. The four classes for the data set on embayments were defined as follows: (1) open water, (2) slightly enclosed, (3) semi-enclosed, and (4) enclosed.
b) A data layer reflecting fetch, which is defined as the distance wind blows across water, was developed at WRI with the collaboration of the University of the Philippines, Marine Science Institute (UP/MSI). ArcWorld (ESRI, 1992) coastline was used as a base. Four classes of fetch were identified: (1) areas exposed to open ocean, (2) areas open to large seas (e.g., South China Sea, Coral Sea), (3) areas open to smaller seas (e.g., Celebes Sea), and (4) areas mostly enclosed.
c) The bathymetry data set is based on 3.7-km resolution TOPEX data (Smith and Sandwell, 1997). TOPEX data were initially resampled to 1-km resolution, and a neighborhood statistic (maximum) for a 3-cell radius was taken. This manipulation results in a data set of a resolution comparable to the original data but adjusted by the maximum depth within a 4-km distance. The four depth classes are: (1) 4-10 meters, (2) 11-40 meters, (3) 41-100 meters, and 4) more than 100 meters.
d) The most complete data set reflecting tidal range for the region comes from the Land-Ocean Interaction in the Coastal Zone (LOICZ, 1998) program. Although this data set is at a coarser resolution than other data layers, regridded at 30 km, it appears to be the best available data source for the region. Tidal range data were classified in four categories reflecting decreasing mean tidal range: (1) greater than 5 meters, (2) 2-5 meters, (3) 50 cm-2 m, and (4) less than 50 cm.
A simple weighting scheme was used in which subsequent factors are given only one half the weight of the previous variable, reflecting decreasing relative importance. The four components were integrated as follows:
natural vulnerability = bays* 8 + fetch* 4 + depth* 2 + tides
The resulting index was assigned to four categories of vulnerability, as follows: (1) low (15-19), (2) medium (20-30), (3) high (31-30), and (4) very high (40-60).
Management effectiveness adjustment
Effective protection and management of coastal resources are important factors in reducing human impacts to coral reefs, increasing awareness, and promoting coral reef health. Using a UNEP-WCMC data set on marine protected areas, the project worked with its partners to improve the data set on MPAs and to develop a preliminary indicator of management effectiveness for some protected areas. The evaluation used staff size, MPA resources, and existence of a management plan as criteria. Areas were classified as having good, partially, or inadequate management effectiveness.
The adjustment for management effectiveness was applied to the analysis of threat from coastal development, overfishing, and destructive fishing. Areas classified as having good management were reduced by a full grade of threat estimate (from high to medium or medium to low, for example). Areas with partial management effectiveness were adjusted downward by one half grade (high to medium/high, for example). The half-grade adjustments are important when the threats are combined, because when cumulative threats are considered, the adjustments can result in the elevation of a threat category.