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Data from: Metabarcoding reveals diet diversity in an ungulate community in Thailand - MaRDI portal

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Data from: Metabarcoding reveals diet diversity in an ungulate community in Thailand (Q6693129)

From MaRDI portal





Dataset published at Zenodo repository.
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Data from: Metabarcoding reveals diet diversity in an ungulate community in Thailand
Dataset published at Zenodo repository.

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    Asian dry forests contain diverse and abundant large herbivore communities whose diet breadth is largely unstudied. We examined the diet composition of eight ungulate species in a dry tropical forest using metabarcoding to determine if the diet separation of the diverse community was structured and if and obvious attributes (i.e. body size, phylogeny or ecology) can explain the structure. We collected fecal samples from the ungulates in Huai Kha Khaeng Wildlife Sanctuary in the western forest complex of Thailand. The fecal collections occurred around a Large Forest Tree Plot (ForestGeo) where all woody species were codified within a genetic barcode library and used in this study. This DNA library was supplemented with samples from forb and grass species known to be consumed by ungulates in the region. Of 333 plant species tested, at least 92 were found within the fecal samples of the ungulates tested. Over half of the identified species were not previously identified by experts as forage species. All ungulate species showed a strong consumption of grasses and forbs. The pattern of forage consumption by these species did not consistently cluster according to obvious paradigms of body size or taxonomy, with significant differences found in diet selection of two similar-sized bovids (guar and banteng), and with the diet of sambar being more similar to bovids than to the other deer species in the community. We conclude Asian ungulate communities do differentiate in their forage consumption  and that metabarcoding techniques should allow for testing of diet shifts in response to seasonal rains and fires which dominate the phenology of Asian dry forests.
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    21 October 2019
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