Pollen DNA metabarcoding reveals high diversity of alpine plant-pollinator networks

Dr Francisco Encinas-viso1, Dr Jessica Bovill1, Mr Jaime  Florez2, Dr Bryan Lessard2, Mr James  Lumbers2, Dr Juanita Rodriguez-Arrieta2, Dr Alexander Schmidt-Lebuhn1, Dr Andreas Zwick2, Dr Liz Milla1

1Centre of Australian National Biodiversity Research, CSIRO, Canberra, Australia, 2Australian National Insect Collection, CSIRO, Canberra, Australia

Abstract:

Animal pollination is a crucial ecosystem service to maintain food security and ecosystem functioning. Recently, DNA metabarcoding have been used to reveal hidden interactions and the complexity of plant-pollination networks. However, we still have a poor understanding of the structure of genetic-based pollination networks and how they differed from flower-visitor observation networks. Here we analyse the structure and diversity of a plant-pollinator metacommunity from the Australian alpine region using two approaches: pollen DNA metabarcoding (MB) and flower-visitor observations. We analysed and compared species and interaction turnover across space of both type of networks. Additionally, we evaluated differences of plant phylogenetic diversity and phylogenetic beta diversity from both approaches. We used two gene regions (ITS2 and trnL) to identify plant species present in pollen loads of 180 insect pollinators from three alpine habitats. We found significant structure differences between both type of networks, notably MB networks were much less specialised but more diverse than observation networks. We also found that MB networks were able to detect higher spatial turnover of plant species and interaction rewiring than observation networks as well as showing higher phylogenetic diversity than observation networks. Overall, our findings show that pollen DNA metabarcoding is a powerful approach to reveal hidden interactions, diversity (taxonomic and phylogenetic) and beta diversity of plant-pollinator metacommunities.


Biography:

Francisco is an evolutionary ecologist with expertise in genomics, ecological modelling, evolutionary biology and conservation ecology. His research interests are focused on the development of biomonitoring tools using eDNA data to monitor ecosystem changes and pollination service.

Date

Mar 21 - 23 2022
Expired!