Browsing by Subject "Environmental sciences"

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Biomonitoring via DNA metabarcoding and light microscopy of bee pollen in rainforest transformation landscapes of Sumatra
(2022) Carneiro de Melo Moura, Carina; Setyaningsih, Christina A.; Li, Kevin; Merk, Miryam Sarah; Schulze, Sonja; Raffiudin, Rika; Grass, Ingo; Behling, Hermann; Tscharntke, Teja; Westphal, Catrin; Gailing, Oliver; Carneiro de Melo Moura, Carina; Department of Forest Genetics and Forest Tree Breeding, University of Göttingen, Göttingen, Germany; Setyaningsih, Christina A.; Department of Palynology and Climate Dynamics, Albrecht-von-Haller-Institute for Plant Sciences, University of Göttingen, Göttingen, Germany; Li, Kevin; Agroecology, Department of Crop Sciences, University of Göttingen, Göttingen, Germany; Merk, Miryam Sarah; Statistics and Econometrics, University of Göttingen, Göttingen, Germany; Schulze, Sonja; Agroecology, Department of Crop Sciences, University of Göttingen, Göttingen, Germany; Raffiudin, Rika; Department of Biology, IPB University ID, Bogor, Indonesia; Grass, Ingo; Department of Ecology of Tropical Agricultural Systems, University of Hohenheim, Stuttgart, Germany; Behling, Hermann; Department of Palynology and Climate Dynamics, Albrecht-von-Haller-Institute for Plant Sciences, University of Göttingen, Göttingen, Germany; Tscharntke, Teja; Agroecology, Department of Crop Sciences, University of Göttingen, Göttingen, Germany; Westphal, Catrin; Functional Agrobiodiversity, Department of Crop Sciences, University of Göttingen, Göttingen, Germany; Gailing, Oliver; Centre of Biodiversity and Sustainable Land Use, University of Göttingen, Göttingen, Germany
Background: Intense conversion of tropical forests into agricultural systems contributes to habitat loss and the decline of ecosystem functions. Plant-pollinator interactions buffer the process of forest fragmentation, ensuring gene flow across isolated patches of forests by pollen transfer. In this study, we identified the composition of pollen grains stored in pot-pollen of stingless bees, Tetragonula laeviceps , via dual-locus DNA metabarcoding (ITS2 and rbcL ) and light microscopy, and compared the taxonomic coverage of pollen sampled in distinct land-use systems categorized in four levels of management intensity (forest, shrub, rubber, and oil palm) for landscape characterization. Results: Plant composition differed significantly between DNA metabarcoding and light microscopy. The overlap in the plant families identified via light microscopy and DNA metabarcoding techniques was low and ranged from 22.6 to 27.8%. Taxonomic assignments showed a dominance of pollen from bee-pollinated plants, including oil-bearing crops such as the introduced species Elaeis guineensis (Arecaceae) as one of the predominant taxa in the pollen samples across all four land-use types. Native plant families Moraceae, Euphorbiaceae, and Cannabaceae appeared in high proportion in the analyzed pollen material. One-way ANOVA (p > 0.05), PERMANOVA (R² values range from 0.14003 to 0.17684, for all tests p-value > 0.5), and NMDS (stress values ranging from 0.1515 to 0.1859) indicated a lack of differentiation between the species composition and diversity of pollen type in the four distinct land-use types, supporting the influx of pollen from adjacent areas. Conclusions: Stingless bees collected pollen from a variety of agricultural crops, weeds, and wild plants. Plant composition detected at the family level from the pollen samples likely reflects the plant composition at the landscape level rather than the plot level. In our study, the plant diversity in pollen from colonies installed in land-use systems with distinct levels of forest transformation was highly homogeneous, reflecting a large influx of pollen transported by stingless bees through distinct land-use types. Dual-locus approach applied in metabarcoding studies and visual pollen identification showed great differences in the detection of the plant community, therefore a combination of both methods is recommended for performing biodiversity assessments via pollen identification.