This data article is constructed using avian (bird) counts from a recently identified trail in Kenyir rainforest, East Peninsular Malaysia. Avian chirps and naked eye visual were simultaneously used to locate the birds. After visual binocular and digital image inspection, identification of avian species were carried out using reference books. Data tabulation are divided by monsoon seasons and months before interpret using Shannon and Evenness indices. The highlights like feeding guilds, nativity, iconic species and statuses in the wild are presented with the data to increase its value. Within these, a total of 457 avian individuals from 36 avian family groups were recorded from which, 25 of these avian species occur as near threatened, vulnerable, endangered and critically endangered in the wild. Having these, the tabulated data becomes a calendar for seasonal availability of avian species which considers the 1.0 km trail suitable for bird watching, scientific study and ecotourism purposes.
A study was conducted to determine the species composition, density and feeding guild of birds at Tasik Kenyir and Setiu, Terengganu between June and September 2017 using line transect method. Observations of birds at Tasik Kenyir and Setiu recorded a total of 297 individuals consisting of 26 families from 64 species. This study estimated that the diversity of birds at Tasik Kenyir (H’ = 3.6) was higher compared to Setiu (H’ = 2.9). However, the density of birds at Setiu (52.05 ± 9.09 SE individuals/ha) was higher than Tasik Kenyir (37.56 ± 10.28 SE individuals/ha). Ten feeding guilds of birds were identified in this study; insectivore, nectarivore, frugivore, omnivore, carnivore, granivore, insectivore-nectarivore, insectivore-frugivore, insectivore-granivore and frugivore-granivore. This study has provided valuable information on the bird assemblage and the understanding on the distribution of birds at Tasik Kenyir and Setiu. It is highly recommended that further studies to be conducted at both sites with more sampling efforts in order to gain a more comprehensive baseline datasets for monitoring bird population trends and turnover between habitats.
Identifying which biodiversity species are more dominant than others in any area is a very challenging task. This is because of the abundant of biodiversity species that may become the majority species in any particular region. This situation create a large dataset with a complex variables to be analysed. Moreover, the responds of organisms and environmental factors are occurred in a non-linear correlation. The effort to do so is really important in order to conserve the biodiversity of nature. To understand the complex relationships that exist between species distribution and their habitat, we analysed the interactions among bird diversity, spatial distribution and land use types at Kenyir landscape in Terengganu, Malaysia by using artificial neural network (ANN) method of self-organizing map (SOM) analysis. SOM performs an unsupervised and non-linear analysis on a complex and large dataset. It is capable to handle the non-linear correlation between organism and environmental factors because SOM identifies clusters and relationships between variables without the fixed assumptions of linearity or normality. The result suggested that SOM analysis was suited for understanding the relationships between bird species assemblages and habitat characteristics.
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