Intensive pasture management alters the composition and structure of plant-pollinator interactions in Sibiu, Romania.

Background: Land management change towards intensive grazing has been shown to alter plant and pollinator communities and the structure of plant-pollinator interactions in different ways across the world. Land-use intensification in Eastern Europe is shifting highly diverse, traditionally managed hay meadows towards intensive pastures, but few studies have examined how this influences plant-pollinator networks. We hypothesized that the effects of intensive grazing on networks will depend on how plant communities and their floral traits change. Methods: We investigated plant and pollinator diversity and composition and the structure of plant-pollinator interactions near Sibiu, Romania at sites that were traditionally managed as hay meadows or intensive pastures. We quantified the identity and abundance of flowering plants, and used transect walks to observe pollinator genera interacting with flowering plant species. We evaluated the effects of management on diversity, composition and several indices of network structure. Results: Pollinator but not plant diversity declined in pastures and both plant and pollinator taxonomic composition shifted. Functional diversity and composition remained unchanged, with rather specialized flowers having been found to dominate in both hay meadows and pastures. Apis mellifera was found to be the most abundant pollinator. Its foraging preferences played a crucial role in shaping plant-pollinator network structure. Apis mellifera thus preferred the highly abundant Dorycnium herbaceum in hay meadows, leading to hay meadows networks with lower Shannon diversity and interaction evenness. In pastures, however, it preferred less abundant and more generalized flower resources. With pollinators being overall less abundant and more generalized in pastures, we found that niche overlap between plants was higher. Discussion: With both hay meadows and pastures being dominated by plant species with similar floral traits, shifts in pollinator preferences seem to have driven the observed changes in plant-pollinator interaction networks. We thus conclude that the effects of grazing on pollinators and their interactions are likely to depend on the traits of plant species present in different management types as well as on the effects of grazing on plant community composition. We thereby highlight the need for better understanding how floral abundance shapes pollinator visitation rates and how floral traits may influence this relationship.

Pollen analysis using multispectral imaging flow cytometry and deep learning.

Pollen identification and quantification are crucial but challenging tasks in addressing a variety of evolutionary and ecological questions (pollination, paleobotany), but also for other fields of research (e.g. allergology, honey analysis or forensics). Researchers are exploring alternative methods to automate these tasks but, for several reasons, manual microscopy is still the gold standard. In this study, we present a new method for pollen analysis using multispectral imaging flow cytometry in combination with deep learning. We demonstrate that our method allows fast measurement while delivering high accuracy pollen identification. A dataset of 426 876 images depicting pollen from 35 plant species was used to train a convolutional neural network classifier. We found the best-performing classifier to yield a species-averaged accuracy of 96%. Even species that are difficult to differentiate using microscopy could be clearly separated. Our approach also allows a detailed determination of morphological pollen traits, such as size, symmetry or structure. Our phylogenetic analyses suggest phylogenetic conservatism in some of these traits. Given a comprehensive pollen reference database, we provide a powerful tool to be used in any pollen study with a need for rapid and accurate species identification, pollen grain quantification and trait extraction of recent pollen.

Sexual Deception in the Eucera-Pollinated Ophrys leochroma: A Chemical Intermediate between Wasp- and Andrena-Pollinated Species.

Ophrys flowers mimic sex pheromones of attractive females of their pollinators and attract males, which attempt to copulate with the flower and thereby pollinate it. Virgin females and orchid flowers are known to use the same chemical compounds in order to attract males. The composition of the sex pheromone and its floral analogue, however, vary between pollinator genera. Wasp-pollinated Ophrys species attract their pollinators by using polar hydroxy acids, whereas Andrena-pollinated species use a mixture of non-polar hydrocarbons. The phylogeny of Ophrys shows that its evolution was marked by episodes of rapid diversification coinciding with shifts to different pollinator groups: from wasps to Eucera and consequently to Andrena and other bees. To gain further insights, we studied pollinator attraction in O. leochroma in the context of intra- and inter-generic pollinator shifts, radiation, and diversification in the genus Ophrys. Our model species, O. leochroma, is pollinated by Eucera kullenbergi males and lies in the phylogeny between the wasp and Andrena-pollinated species; therefore, it is a remarkable point to understand pollinator shifts. We collected surface extracts of attractive E. kullenbergi females and labellum extracts of O. leochroma and analyzed them by using gas chromatography with electroantennographic detection (GC-EAD) and gas chromatography coupled with mass spectrometry (GC-MS). We also performed field bioassays. Our results show that O. leochroma mimics the sex pheromone of its pollinator's female by using aldehydes, alcohols, fatty acids, and non-polar compounds (hydrocarbons). Therefore, in terms of the chemistry of pollinator attraction, Eucera-pollinated Ophrys species might represent an intermediate stage between wasp- and Andrena-pollinated orchid species.