Distribution of subterranean termite mounds in oil palm plantation of FELDA Kemahang, Tanah Merah, Kelantan

Oil palm act as an essential export-oriented crop in Malaysia. However, they prone to the infestation of endemic insect pests including termite. Moreover, the lack of insect studies compromising in the oil palm plantation. Hence, this study purposely (i) to identify subterranean termites by the distribution of their nest in an oil palm plantation and (ii) to compare the distribution pattern between genera of the subterranean mound in oil palm plantation. The distribution of subterranean mound was investigated in oil palm plantation of FELDA Kemahang, Tanah Merah, Kelantan with three sampling sites covering three estates, FELDA Kemahang 1, 2 and 3. The location of each identified mounds within 50 m X 50 m quadrat was geotagged using GPS. Ten termites from each colony have been collected and preserved in 70% ethanol for species identification. Then, mounds recorded were illustrated using maps generated by ArcGIS 10.3 and spatial patterns were analysed using the nearest-neighbour technique. From the obtained results, there were four genera of subterranean mounds distributed in oil palm plantation of FELDA Kemahang, Tanah Merah, Kelantan. The most abundance genus was Odontotermes spp. with 28%, then followed by Globitermes sp., Maerotermes spp. and Microtermes spp. with 26%, 23% and 23% respectively. Macrotermes spp. were found to be distributed randomly to regularly patterns while Microtermes spp. were recorded in aggregated to random pattern. Odontotermes spp. arranged in random to regular pattern and Globitermes sp. in regular to highly aggregated pattern. Termite distribution patterns vary regionally, and various environmental factors, such as vegetation type, habitat disturbance and habitat fragmentation. In oil palm plantation, the spatial arrangements of oil palm planting and the different management practices giving the impact towards the patterns. Besides, surrounding parameter such as soil pH, moisture and temperature could also be additional factors. In addition, since the nearest-neighbour method cannot identify some types of distribution, thus future study could use Morisita's index to analyse the pattern.