Phylogenetic Support for Glacier Algae Metacommunities Linked through Atmospheric Transport

Abstract:

Biological darkening of glacier and ice sheet surfaces lowers ice albedo, enhances ice melting, and generates a positive feedback in which algal growth enhances habitability by further accelerating surface meltwater production. Morphologically similar taxa of algae are known to colonize the surfaces of ice sheets and glaciers globally (i.e., Ancylonema nordenskioeldii, Mesotaenium berggrenii, and Cylindrocystis brebissoni), but few data have been available to examine relatedness between the populations documented at geographically distant locations. The most common species of glacier algae have cells with major axis diameters >10 μm, placing fundamental constraints on their transport distances and residency time in the atmosphere. In this study, supraglacial ecosystems of the Matanuska Glacier (Alaska) were sampled during the summer of 2014 and 2015, and DNA extracted from the microbes was sequenced to analyze community composition and generate metagenomic assembled genomes. Reconstruction of full length (1700-1800 bp) 18S rRNA genes from metagenomic data were compared to those available for common glacier algae, and the sequences obtained from the Alaskan glacier samples have >99 % similarity to those of a A. nordenskioeldii species from Svalbard. The high identities in their 18S rRNA genes are consistent with morphological similarities that have been found in A. nordenskioeldii and other glacier algae in the polar regions, implicating intercontinental atmospheric transport as their means of dispersal. Since glacier algae are well adapted to high levels of visible and UV irradiance and belong to a class containing various desiccation resistant species, they may also be well suited for survival under the conditions associated with atmospheric transport. To further evaluate their biogeographical relationships and potential for long distance dissemination, we discuss new results based on higher resolution phylogenetic markers (e.g., rbcL) and particle dispersion modeling that lend insight for explaining glacier algae distribution patterns and biogeography.