Mapping the distribution of display trees for conservation of firefly habitat – a case study of the mangrove tree Sonneratia caseolaris in Selangor, Malaysia

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H. Khali Aziz, O. Hamdan, F. Mohd Azahari, I. Azhan Shah, H. Mohd Nasir, N. Samsu Annuar

Abstract

The total mangrove forest area in Selangor is about 22,530 ha with about 18,088 ha located in forest reserves and the remaining in state-owned land. Diversity of flora in the mangrove forest is low compared to other inland forest types, and for Selangor it was reported that there have been only 18 mangrove tree species recorded to date. One of the species is Sonneratia caseolaris, locally known as berembang. Many mangrove creatures depend directly or indirectly on S. caseolaris. This mangrove tree species is known to have an association with fireflies along the Selangor River – it is a favoured display tree of the firefly Pteroptyx tener. Sonneratia caseolaris normally grows naturally along river banks and can grow in zero salinity water. As such, it can be found further upstream of the river mouth. Being among the first trees to grow on upstream tidal mudflats, Sonneratia stabilise the riverbanks and coasts, providing more favourable ground for other types of trees and plants. It was reported that the natural regeneration of Sonneratia is so successful that planting is usually not needed. However, due to development activities, many mangrove areas have been converted to other land uses. Detailed mapping of important mangrove species including Sonneratia is, therefore, necessary. Knowing the extent and distribution of Sonneratia and other trees important to the firefly will be useful in planning conservation of its habitat. This paper presents findings from a study to develop a firefly habitat mapping technique using remote sensing data for the Selangor River. SPOT data with a 5 m resolution acquired in 2008 was used to map the distribution of the trees. The spectral signature of Sonneratia was also analysed using a spectroradiometer which can be used to differentiate the tree leaves signature in order to facilitate the image classification process and mapping of tree distribution.

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