Aim The aim of this study was to resolve the phylogenetic placement of island taxa, reconstruct ancestral origins and resolve competing hypotheses of dispersal patterns and biogeographical histories for oceanic island endemic taxa within subgenus Plantago (Plantaginaceae). Location Juan Fernández Islands, the Auckland Islands, Lord Howe Island, New Amsterdam Island, New Zealand, Tasmania, Falkland Islands, Rapa Iti and the Hawaiian Islands. Taxon Island endemics within Plantago (Plantaginaceae), a globally distributed taxonomic group comprising approximately 250 species. Methods We use Bayesian phylogenetic and divergence time analyses and historical biogeographical analysis of molecular sequence data to infer the ancestral origins of the oceanic island species in Plantago . Results Taxa within subgenus Plantago form clades based on geographic proximities and challenge previous phylogenetic relationships and classification based on morphology. We infer that biogeographic histories of oceanic island taxa from multiple islands were shaped by dispersal at different scales and possibly by different types of birds. The highly remote Hawaiian Islands and Rapa Iti were colonized from North American taxa in a pattern corresponding to known migration routes of large marine birds, rather than from New Zealand as previously hypothesized. The island endemics of Juan Fernández, the Falkland Islands, Lord Howe, Auckland Islands and New Zealand are found to have sources in the nearest continental areas. The analyses confirm recent speciation within subgenus Plantago – which is particularly heightened in island lineages in Hawaii and Rapa Iti – but show slightly older divergence times than previous molecular dating studies. Main conclusions Using molecular data to infer ancestral ranges for plants with uncertain taxonomic relationships can greatly improve our understanding of biogeographical histories and help elucidate origins, dispersal modes and routes in widespread lineages with complex distribution patterns such as Plantago . We improve understanding of important floristic exchange areas between continents and islands as a result of long‐distance dispersal. We infer that a combination of both stepping stone dispersal and extreme long‐distance dispersal can shape insular floras, and that multiple floristic areas can be the sources of closely related island taxa. However, despite the successful dispersal of Plantago , radiation in island archipelagos is generally limited suggesting specific traits may limit diversification.

Plants produce a multitude of metabolites that contribute to their fitness and survival and play a role in local adaptation to environmental conditions. The effects of environmental variation are particularly well studied within the genus Plantago; however, previous studies have largely focused on targeting specific metabolites. Studies exploring metabolome‐wide changes are lacking, and the effects of natural environmental variation and herbivory on the metabolomes of plants growing in situ remain unknown. An untargeted metabolomic approach using ultra‐high‐performance liquid chromatography–mass spectrometry, coupled with variation partitioning, general linear mixed modeling, and network analysis was used to detect differences in metabolic phenotypes of Plantago major in fifteen natural populations across Denmark. Geographic region, distance, habitat type, phenological stage, soil parameters, light levels, and leaf area were investigated for their relative contributions to explaining differences in foliar metabolomes. Herbivory effects were further investigated by comparing metabolomes from damaged and undamaged leaves from each plant. Geographic region explained the greatest number of significant metabolic differences. Soil pH had the second largest effect, followed by habitat and leaf area, while phenological stage had no effect. No evidence of the induction of metabolic features was found between leaves damaged by herbivores compared to undamaged leaves on the same plant. Differences in metabolic phenotypes explained by geographic factors are attributed to genotypic variation and/or unmeasured environmental factors that differ at the regional level in Denmark. A small number of specialized features in the metabolome may be involved in facilitating the success of a widespread species such as Plantago major into such wide range of environmental conditions, although overall resilience in the metabolome was found in response to environmental parameters tested. Untargeted metabolomic approaches have great potential to improve our understanding of how specialized plant metabolites respond to environmental change and assist in adaptation to local conditions.

Phenology has emerged as a key metric to measure how species respond to changes in climate. Innovative means have been developed to extend the temporal and spatial range of phenological data by obtaining data from herbarium specimens, citizen science programs, and biodiversity data repositories. These different data types have seldom been compared for their effectiveness in detecting environmental impacts on phenology. To address this, we compare three separate phenology datasets from Denmark: (i) herbarium specimen data spanning 145 years, (ii) data collected from a citizen science phenology program over a single year observing first flowering, and (iii) data derived from incidental biodiversity observations in iNaturalist over a single year. Each dataset includes flowering day of year observed for three common spring-flowering plant species: Allium ursinum (ramsons), Aesculus hippocastanum (horse chestnut), and Sambucus nigra (black elderberry). The incidental iNaturalist dataset provided the most extensive geographic coverage across Denmark and the largest sample size and recorded peak flowering in a way comparable to herbarium specimens. The directed citizen science dataset recorded much earlier flowering dates because the program objective was to report the first flowering, and so was less compared to the other two datasets. Herbarium data demonstrated the strongest effect of spring temperature on flowering in Denmark, possibly because it was the only dataset measuring temporal variation in phenology, while the other datasets measured spatial variation. Herbarium data predicted the mean flowering day of year recorded in our iNaturalist dataset for all three species. Combining herbarium data with iNaturalist data provides an even more effective method for detecting climatic effects on phenology. Phenology observations from directed and incidental citizen science initiatives will increase in value for climate change research in the coming years with the addition of data capturing the inter-annual variation in phenology.