The diversity of ice algal communities on the Greenland Ice Sheet as revealed by oligotyping

Abstract

The Arctic is being disproportionally affected by climate change compared with other geographic locations, and is currently experiencing unprecedented melt rates. The Greenland Ice Sheet (GrIS) can be regarded as the largest supraglacial ecosystem on Earth, and ice algae are the dominant primary producers on bare ice surfaces throughout the course of a melt season. Ice-algal-derived pigments cause a darkening of the ice surface, which in turn decreases albedo and increases melt rates. The important role of ice algae in changing melt rates has only recently been recognized, and we currently know little about their community compositions and functions. Here, we present the first analysis of ice algal communities across a 100 km transect on the GrIS by high-throughput sequencing and subsequent oligotyping of the most abundant taxa. Our data reveal an extremely low algal diversity with Ancylonema nordenskiöldii and a Mesotaenium species being by far the dominant taxa at all sites. We employed an oligotyping approach and revealed a hidden diversity not detectable by conventional clustering of operational taxonomic units and taxonomic classification. Oligotypes of the dominant taxa exhibit a site-specific distribution, which may be linked to differences in temperatures and subsequently the extent of the melting. Our results help to better understand the distribution patterns of ice algal communities that play a crucial role in the GrIS ecosystem.

Glacier algae foster ice-albedo feedback in the European Alps

“…alaskana produce dark phenolic pigments to protect them from the high solar radiation 10 . This is consistent with the fact that these species are more abundant on the bare ice than Trebouxiophyceae which lack these secondary pigments 53,54 . The dark secondary pigmentation of Ancylonema nordenskioeldii and Mesotaenium berggrenii var.…”

“…The ten most abundant OTUs were assigned by BLAST 70 . A. nordenskioeldii was the most predominant alga in all the samples, but conventional clustering methods sometimes were not able to distinguish between A. nordenskioeldii and Mesotaenium species 54 . Thus, the oligotyping pipeline 71 was used on the A. nordenskioeldii sequences.…”

Algal photophysiology drives darkening and melt of the Greenland Ice Sheet

“…Of these, biologically driven albedo reduction has been proposed by both observational (7)(8)(9)(10), and modeling studies (11) to represent the single largest contributor to albedo decline in the GrIS dark zone in recent decades, matching reports from other regions of the cryosphere (12)(13)(14). Supraglacial photoautotrophic populations of the GrIS include cyanobacteria, typically associated with aggregates of inorganic particles (cryoconite) that melt down into the ice to form water-filled depressions (cryoconite holes) (15)(16)(17)(18), and heavily pigmented Zygnematophycean (Streptophyte) microalgae (hereafter glacier algae) (19) that bloom in the upper few centimeters of surface ice, which is subsequently described as dark or dirty ice (8,9,(19)(20)(21)(22)(23). Given the high abundance and large spatial coverage achieved by blooms of glacier algae during summer ablation seasons (8,9,23), glacier algal assemblages represent the most important photoautotrophic component of the GrIS supraglacial environment with regard to biological albedo effects (8,9,11).…”

Phylogenetic placement of environmental sequences using taxonomically reliable databases helps to rigorously assess dinophyte biodiversity in Bavarian lakes (Germany)

“…OTUs of studies using LSU (Elferink et al, 2017) and/or ITS sequences (Lutz, McCutcheon, McQuaid, & Benning, 2018). Concomitantly, taxa such as Peridiniella, Sphaerodinium and Tyrannodinium, of which only LSU sequences are known at present, are subsequently undetectable using dinoref (however, †Leonella and †Posoniella are also missing, although SSU reference sequences are already available).…”

“…It might be only a matter of time until this particular taxonomic confusion is corrected for future releases of the SILVA databases, as this error has been already corrected in the dinoref database (Mordret et al, 2018). The latter, in turn, relies on SSU reference sequence data only and is therefore unable to place environmental OTUs of studies using LSU (Elferink et al, 2017) and/or ITS sequences (Lutz, McCutcheon, McQuaid, & Benning, 2018). Concomitantly, taxa such as Peridiniella, Sphaerodinium and Tyrannodinium, of which only LSU sequences are known at present, are subsequently undetectable using dinoref (however, †Leonella and †Posoniella are also missing, although SSU reference sequences are already available).…”