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A majority of the world's flowering plants benefit from insect pollination. Bees in particular are known to carry large amounts of pollen, and the pollen load transported is often highly conspecific. However, there is limited knowledge about the transfer of pollen by other non‐bee flower‐visiting insect taxa.We observed and collected insects visiting flowers in an Australian alpine plant community. We identified insect body pollen loads to evaluate the relative differences among taxa using visitation and pollen transport networks. We sampled a diverse pollinator community from 39 insect families that visited 31 plant species (n = 488 individual insects).Pollen abundance and richness on insect bodies varied significantly among Diptera, Hymenoptera and Lepidoptera both among individuals and across insect families.Bees carried more pollen overall than the other three insect orders surveyed, yet dipterans were the most frequent flower visitors overall, with six dipteran families observed visiting flowers more frequently than the most frequent hymenopteran visitor (Apis mellifera L.). Apidae was also the only family in this study to carry consistently large quantities of pollen.At the order level, Diptera carried the second highest quantity of pollen but greater diversity of pollen than other insect orders. Importantly, visitation networks revealed visits to plant taxa that were not identified in pollen transport networks and vice versa.Given the missing links in both visitor observation and pollen transfer networks, we advocate combining both types of networks to provide a more accurate estimate of the full range of plant–pollinator interactions occurring within and across taxa at the community level. Understanding the variation in plant–pollinator interactions as a result of differences among taxa and between networks of flower visitors, pollen transfer is important to evaluate the level of generalisation/specialisation among plants and their pollinator partners. [ABSTRACT FROM AUTHOR]

Alpine plant–pollinator communities play an important role in the functioning of alpine ecosystems, which are highly threatened by climate change. However, we still have a poor understanding of how environmental factors and spatiotemporal variability shape these communities. Here, we investigate what drives structure and beta diversity in a plant–pollinator metacommunity from the Australian alpine region using two approaches: pollen DNA metabarcoding (MB) and observations. Individual pollinators often carry pollen from multiple plant species, and therefore we expected MB to reveal a more diverse and complex network structure. We used two gene regions (ITS2 and trnL) to identify plant species present in the pollen loads of 154 insect pollinator specimens from three alpine habitats and construct MB networks, and compared them to networks based on observations alone. We compared species and interaction turnover across space for both types of networks, and evaluated their differences for plant phylogenetic diversity and beta diversity. We found significant structural differences between the two types of networks; notably, MB networks were much less specialized but more diverse than observation networks, with MB detecting many cryptic plant species. Both approaches revealed that alpine pollination networks are very generalized, but we estimated a high spatial turnover of plant species (0.79) and interaction rewiring (0.6) as well as high plant phylogenetic diversity (0.68) driven by habitat differences based on the larger diversity of plant species and species interactions detected with MB. Overall, our findings show that habitat and microclimatic heterogeneity drives diversity and fine‐scale spatial turnover of alpine plant–pollinator networks. [ABSTRACT FROM AUTHOR]

Anthropogenic activities are triggering global changes in the environment, causing entire communities of plants, pollinators and their interactions to restructure, and ultimately leading to species declines. To understand the mechanisms behind community shifts and declines, as well as monitoring and managing impacts, a global effort must be made to characterize plant–pollinator communities in detail, across different habitat types, latitudes, elevations, and levels and types of disturbances. Generating data of this scale will only be feasible with rapid, high‐throughput methods. Pollen DNA metabarcoding provides advantages in throughput, efficiency and taxonomic resolution over traditional methods, such as microscopic pollen identification and visual observation of plant–pollinator interactions. This makes it ideal for understanding complex ecological networks and their responses to change. Pollen DNA metabarcoding is currently being applied to assess plant–pollinator interactions, survey ecosystem change and model the spatiotemporal distribution of allergenic pollen. Where samples are available from past collections, pollen DNA metabarcoding has been used to compare contemporary and past ecosystems. New avenues of research are possible with the expansion of pollen DNA metabarcoding to intraspecific identification, analysis of DNA in ancient pollen samples, and increased use of museum and herbarium specimens. Ongoing developments in sequencing technologies can accelerate progress towards these goals. Global ecological change is happening rapidly, and we anticipate that high‐throughput methods such as pollen DNA metabarcoding are critical for understanding the evolutionary and ecological processes that support biodiversity, and predicting and responding to the impacts of change. [ABSTRACT FROM AUTHOR]

Restoring degraded landscapes has primarily focused on re‐establishing native plant communities. However, little is known with respect to the diversity and distribution of most key revegetation species or the environmental and anthropogenic factors that may affect their demography and genetic structure. In this study, we investigated the genetic structure of two widespread Australian legume species (Acacia salicina and Acacia stenophylla) in the Murray–Darling Basin (MDB), a large agriculturally utilized region in Australia, and assessed the impact of landscape structure on genetic differentiation. We used AFLP genetic data and sampled a total of 28 A. salicina and 30 A. stenophylla sampling locations across southeastern Australia. We specifically evaluated the importance of four landscape features: forest cover, land cover, water stream cover, and elevation. We found that both species had high genetic diversity (mean percentage of polymorphic loci, 55.1% for A. salicina versus. 64.3% for A. stenophylla) and differentiation among local sampling locations (A. salicina: ΦPT = 0.301, 30%; A. stenophylla: ΦPT = 0.235, 23%). Population structure analysis showed that both species had high levels of structure (6 clusters each) and admixture in some sampling locations, particularly A. stenophylla. Although both species have a similar geographic range, the drivers of genetic connectivity for each species were very different. Genetic variation in A. salicina seems to be mainly driven by geographic distance, while for A. stenophylla, land cover appears to be the most important factor. This suggests that for the latter species, gene flow among populations is affected by habitat fragmentation. We conclude that these largely co‐occurring species require different management actions to maintain population connectivity. We recommend active management of A. stenophylla in the MDB to improve gene flow in the adversity of increasing disturbances (e.g., droughts) driven by climate change and anthropogenic factors. [ABSTRACT FROM AUTHOR]