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Identifying potential dam site using the forest diversity assessment in Bengoh Catchment, Sarawak, Malaysia


Met, Les (2016) Identifying potential dam site using the forest diversity assessment in Bengoh Catchment, Sarawak, Malaysia. Doctoral thesis, Universiti Putra Malaysia.


Dams are built to provide water for irrigated agriculture, domestic or industrial use, flood control, irrigation, navigation, sedimentation control, hydropower and to support economic development. Despite the benefits provided by the dams to humankind, dam developments leads to the irreversible loss of species populations and ecosystem. As forest diversity assessment constitutes the major component in the ecological evaluation, it is paramount for the ecological evaluation of dam projects to be strengthened and emphasized so as to provide criteria and information that can be used to support decision making by the relevance authorities with regard to natural conservation. The study focuses on four specific objectives, that is, measuring the species diversity of plants vegetation, developing the land-cover map and ecosystem map of Bengoh Catchment, determining the rarity and viability value of plants vegetation in four different types of forest vegetation and assessing the ecosystem-loss impact score and ecosystem fragmentation impact score using the rarity and viability value based on fragmentation impact map for the ranking of potential dam site. The approach begins with the mapping of the land cover and ecosystem of Bengoh Catchment where the dam projects have been proposed. The classification of forest was performed using the information generated from the data collected during the field work and also from the digitise topographic maps. The species diversity of the forest ecosystem were calculated using the diversity index expression. The identification of the potential dam site was done by accessing ecosystem loss impact score and ecosystem fragmentation impact score using the rarity and viability value. A total of 148 species and 72 families were recorded within the four different types of forest ecosystem. Out of 148 species, 22 trees species were recorded at primary forests, 72 species were recorded at the old secondary forest, 37 species were recorded at young secondary forest and 17 were recorded at agroforestry. The diversity index indicates the species richness, species diversity and evenness in all four major forest ecosystems were relatively high. The rarity value of all the four types of ecosystem was relatively high; indicating that the species in the ecosystem were distributed equitably and reflecting the commonness of the species. The viability value of the entire four ecosystems is relatively low indicating that the species are prone to extinction. The impact analysis carried out in this study which generates the ecosystem-loss impact scores and ecosystem-fragmentation impact scores of the proposed dam site and gives a clear picture on which alternative to be considered as one of the most appropriate site for the proposed dam project. Based on the analysis of the impact score of the five alternatives, alternative 4 is the best-performing with the overall impact score 0.663 with respect to the ecosystem-loss and the ecosystem-fragmentation impact. Thus, Alternative 4 appears to be the most appropriate site for the dam project. The approach to this work paths the way to alleviate the impact of dam development on the displacement of ecosystem and to develop methods of evaluating the long-term impact, as well as the viability of populations and ecosystems.

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Additional Metadata

Item Type: Thesis (Doctoral)
Subject: Forest biodiversity - Malaysia
Subject: Biodiversity conservation - Malaysia
Subject: Forest management - Malaysia
Call Number: FPAS 2017 12
Chairman Supervisor: Associate Professor Latifah Abd Manaf, PhD
Divisions: Faculty of Environmental Studies
Depositing User: Nabilah Mustapa
Date Deposited: 20 Aug 2019 00:50
Last Modified: 20 Aug 2019 00:50
URI: http://psasir.upm.edu.my/id/eprint/70633
Statistic Details: View Download Statistic

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