Background and aims. Among the numerous pantropical species of the yam genus, Dioscorea, only a small group occurs in the Mediterranean basin, including two narrow Pyrenean endemics (Borderea clade), and two Mediterranean-wide species (D. communis and D. orientalis, Tamus clade). However, several currently unrecognized species and infraspecific taxa have been described in the Tamus clade due to significant morphological variation associated with D. communis. Our overarching aim was to investigate taxon delimitation in the Tamus clade using an integrative approach combining phylogenomic, spatial and morphological data.Methods. We analysed 76 herbarium samples using Hyb-Seq genomic capture to sequence 260 low-copy nuclear genes and plastomes, together with morphometric and environmental modelling approaches.Key results. Phylogenomic reconstructions confirmed that the two previously accepted species of the Tamus clade, D. communis and D. orientalis, are monophyletic and form sister clades. Three subclades showing distinctive geographic patters were identified within D. communis. These subclades were also identifiable from morphometric and climatic data, and introgression patterns were inferred between subclades in the eastern part of the distribution of D. communis. Conclusions. We propose a taxonomy that maintains D. orientalis, endemic to the eastern Mediterranean region, and splits D. communis sensu lato into three species: D. edulis, endemic to Macaronesia (Canary Islands and Madeira); D. cretica, endemic to the eastern Mediterranean region; and D. communis sensu stricto, widespread across western and central Europe. Introgression inferred between D. communis s.s. and D. cretica is likely to be explained by their relatively recent speciation at the end of the Miocene, disjunct isolation in eastern and western Mediterranean glacial refugia and a subsequent westward recolonization of D. communis s.s. Our study shows that the use of integrated genomic, spatial and morphological approaches allows a more robust definition of species boundaries and the identification of species that previous systematic studies failed to uncover.

Automatic pollen image identification using neural networks increases accuracy for hay fever forecasts

Environmental DNA (eDNA) is used for monitoring the occurrence of freshwater organisms. Various studies show a relation between the amount of eDNA detected and target organism abundance, thus providing a potential proxy for reconstructing population densities. However, environmental factors such as water temperature and microbial activity are known to affect the amount of eDNA present as well In this study, we use controlled aquarium experiments using Gammarus pulex L. (Amphipoda) to investigate the relationship between the amount of detectable eDNA through time, pH, and levels of organic material. We found eDNA to degrade faster when organic material was added to the aquarium water, but that pH had no significant effect. We infer that eDNA contained inside cells and mitochondria is extra resilient against degradation, though this may not reflect actual presence of target species. These results indicate that, although estimation of population density might be possible using eDNA, measured eDNA concentration could, in the future, be corrected for local environmental conditions in order to ensure accurate comparisons.