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Contrasting patterns of foraging behaviors in Brazilian stingless bees using pollen and honey metabarcoding

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NIAID Data Ecosystem2026-05-01 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP439794
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Stingless bees are major flower visitors in the tropics, but their foraging preferences and behavior are still poorly understood. Studying stingless bee interactions with angiosperms is methodologically challenging due to the high diversity of tropical plants and inaccessibility of their flowers, especially in forests. Pollen and honey DNA metabarcoding offers an opportunity of accessing floral visitation efficiently, thus were applied in this study to answer questions regarding stingless bee floral resources spectra and foraging behavior. We chose three distantly related species of stingless bees, with different body size and social behavior: Melipona rufiventris, Scaptotrigona postica and Tetragonisca angustula. Artificial nests were set in an area of Cerrado savanna, a hotspot of biodiversity in South America, where all the three stingless bee species are natively occurring. Simultaneously, we assessed the local floristic components and phenological stage through twelve rapid botanical surveys conducted at different distances from the nests. We discovered a broad set of explored floral sources in nest pollen and honey of the three species, including some surprising records of wind-pollinated flowers and non-angiosperm taxa. Some plant families, such as Myrtaceae, Asteraceae, Euphorbiaceae, Melastomataceae and Malpighiaceae, dominated the records, indicating stingless bee preferences for abundant resources that flowers of these families provide in our study region. Honey metabarcoding indicated a more generalized exploitation of floral sources, while pollen indicated more specialization, especially in Melipona. In addition, our results reinforce the preference of stingless bees for forest trees, even if only available at long distances. Our high-resolution results, even in a hyper-diverse biome, encourage future bee-plant studies using pollen and honey metabarcoding in tropical environments.
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2023-08-11
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