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 dimorphism modifies habitat-associated divergence: Evidence from beach and creek breeding sockeye salmon.

Studies of parallel or convergent evolution (the repeated, independent evolution of similar traits in similar habitats) rarely explicitly quantify the extent of parallelism (i.e. variation in the direction and/or magnitude of divergence) between the sexes; instead, they often investigate both sexes together or exclude one sex. However, differences in male and female patterns of divergence could contribute to overall variation in the extent of parallelism among ecotype pairs, especially in sexually dimorphic traits. Failing to properly attribute such variation could lead to underestimates of the importance of environmental variation in shaping phenotypes. We investigate the extent of parallelism in the body shape of male and female beach and creek spawning sockeye salmon (Oncorhynchus nerka) from two lake systems in western Alaska that were colonized independently after the last ice age. Although both sexes showed some degree of parallelism, patterns of beach-creek body shape divergence vary between the sexes and between lake systems. Phenotypic change vector analyses revealed highly parallel aspects of divergence between males from different lake systems (males from beaches had deeper bodies than males from creeks) but weaker parallelism in females and high parallelism between the sexes in one lake system but not the other. Body shape also had population-specific components, which were mostly, but not entirely, explained by environmental variation in the form of creek depth. Our results highlight the importance of explicitly considering the extent of parallelism between the sexes and environmental variation among sites within habitat types.

Intensive grazing alters the diversity, composition and structure of plant-pollinator interaction networks in Central European grasslands.

Complex socio-economic, political and demographic factors have driven the increased conversion of Europe's semi-natural grasslands to intensive pastures. This trend is particularly strong in some of the most biodiverse regions of the continent, such as Central and Eastern Europe. Intensive grazing is known to decrease species diversity and alter the composition of plant and insect communities. Comparatively little is known, however, about how intensive grazing influences plant functional traits related to pollination and the structure of plant-pollinator interactions. In traditional hay meadows and intensive pastures in Central Europe, we contrasted the taxonomic and functional group diversity and composition, the structure of plant-pollinator interactions and the roles of individual species in networks. We found mostly lower taxonomic and functional diversity of plants and insects in intensive pastures, as well as strong compositional differences among the two grassland management types. Intensive pastures were dominated by a single plant with a specialized flower structure that is only accessible to a few pollinator groups. As a result, intensive pastures have lower diversity and specificity of interactions, higher amount of resource overlap, more uniform interaction strength and lower network modularity. These findings stand in contrast to studies in which plants with more generalized flower traits dominated pastures. Our results thus highlight the importance of the functional traits of dominant species in mediating the consequences of intensive pasture management on plant-pollinator networks. These findings could further contribute to strategies aimed at mitigating the impact of intensive grazing on plant and pollinator communities.

A systematic approach to evaluate the influence of environmental conditions on eDNA detection success in aquatic ecosystems.

The use of environmental DNA (eDNA) to determine the presence and distribution of aquatic organisms has become an important tool to monitor and investigate freshwater communities. The successful application of this method in the field, however, is dependent on the effectiveness of positive DNA verification, which is influenced by site-specific environmental parameters. Factors affecting eDNA concentrations in aquatic ecosystems include flow conditions, and the presence of substances that possess DNA-binding properties or inhibitory effects. In this study we investigated the influence of different environmental parameters on the detection success of eDNA using the invasive goby Neogobius melanostomus. In a standardized laboratory setup, different conditions of flow, sediment-properties, and fish density were compared, as well as different potential natural inhibitors such as algae, humic substances, and suspended sediment particles. The presence of sediment was mainly responsible for lower eDNA detection in the water samples, regardless of flow-through or standing water conditions and a delayed release of eDNA was detected in the presence of sediment. Humic substances had the highest inhibitory effect on eDNA detection followed by algae and siliceous sediment particles. The results of our study highlight that a successful application of eDNA methods in field surveys strongly depends on site-specific conditions, such as water flow conditions, sediment composition, and suspended particles. All these factors should be carefully considered when sampling, analyzing, and interpreting eDNA detection results.