Identification of important plant areas using GIS-based multi-criteria decision-making in Peninsular Malaysia

The Important Plant Areas (IPAs) framework developed by Plantlife International in the early 2000s aims to protect wild plants and fungi and contributes to the fifth target of the CBD Global Strategy for Plant Conservation (GSPC). In addition, national implementation contributes to the sixth target of the Malaysian National Policy on Biological Diversity 2016-2025. IPA initiative focused on plant conservation through three key criteria, i.e., presence of threatened species, exceptional botanical richness, and threatened habitats. These criteria were developed for global implementation, hence a likelihood of unsuited use of the criteria and thresholds in Malaysia. A review of studies revealed that the IPA criteria were strict for implementation and the method used for IPA identification was varied and uncertain in determining the criterion weights. The preferred method used in IPA was the scoring method because of its simplicity, ease of use, and comprehensibility. However, the scoring method suffered from judgment uncertainty, the influence of the weighted score on each criterion was not understood, and the limited ability to complement biodiversity-related parameters. Herbarium databases were widely used in IPA identification; however, the database was associated with the biasness towards collections efforts, resulting inaccurate population counts, which would inadvertently classify areas with massive collection data as species-rich areas. IPA identification is divided into two phases. First, identification of all potential IPAs and second, decision-making in selecting the final IPAs. This study moulded a preliminary solution in the first phase in the state of Perak to address issues of criterion weights, judgement uncertainty and biases in herbarium collections by proposing three complementarity techniques, namely multi-criteria decision-making - analytical hierarchy process (MCDM-AHP), species distribution modelling (SDM) and GIS-based multi-criteria decision-making (GIS-MCDM). The MCDM-AHP technique was used to solve criterion weights and judgment uncertainty issues. Collection bias in the herbarium database was reduced using SDM utilising the Maximum Entropy (MaxEnt) to identify the Dipterocarpaceae species richness areas in Perak. GIS-MCDM, which combined MCDM-AHP and SDM to acquire information for decision-making, was used to identify the IPAs. As a result, on the weights and judgment uncertainty issues, threatened habitats were given the highest weight, followed by threatened species, endemism, and botanical richness. The results of species modelling revealed that 65% of the dipterocarp species richness areas were in the centre and south Perak and the remaining 35% were found in northern areas. IPA weights and indexes were incorporated into the GIS-MCDM environment, and as a result, eight dipterocarp IPAs were identified in the state of Perak. Six were in the protected areas, while two IPAs were outside of the protected areas. This study has improved the existing method for site-based plant conservation by providing a smaller-scale map of IPAs with more significant detailed information related to threatened species, botanical richness, threatened habitats, and endemic species. GIS-MCDM used in this study enhanced the IPAs identification technique by incorporating GIS-based decision-making, species modelling, and spatial analysis. This enabled stakeholder to analyse spatial data, maps, charts, and reports in graphical formats for decision-making.

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