Gene sequences of the lichen Cetraria aculeata

Lichens are symbioses between fungi (mycobionts) and photoautotrophic green algae or cyanobacteria (photobionts). Many lichens occupy large distributional ranges covering several climatic zones. So far, little is known about the large-scale phylogeography of lichen photobionts and their role in shaping the distributional ranges of lichens. We studied south polar, temperate and north polar populations of the widely distributed fruticose lichen Cetraria aculeata. Based on the DNA sequences from three loci for each symbiont, we compared the genetic structure of mycobionts and photobionts. Phylogenetic reconstructions and Bayesian clustering methods divided the mycobiont and photobiont data sets into three groups. An AMOVA shows that the genetic variance of the photobiont is best explained by differentiation between temperate and polar regions and that of the mycobiont by an interaction of climatic and geographical factors. By partialling out the relative contribution of climate, geography and codispersal, we found that the most relevant factors shaping the genetic structure of the photobiont are climate and a history of codispersal. Mycobionts in the temperate region are consistently associated with a specific photobiont lineage. We therefore conclude that a photobiont switch in the past enabled C. aculeata to colonize temperate as well as polar habitats. Rare photobiont switches may increase the geographical range and ecological niche of lichen mycobionts by associating them with locally adapted photobionts in climatically different regions and, together with isolation by distance, may lead to genetic isolation between populations and thus drive the evolution of lichens.

Environmental variables and multivariate seabed classification maps via k means clustering of Potter Cove, Antarctica, link to input and result files in GeoTIFF format

This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.