The instrumental record of Antarctic sea ice in recent decades does not reveal a clear signature of warming despite observational evidence from coastal Antarctica. Here we report a significant correlation (P < 0.002) between methanesulphonic acid (MSA) concentrations from a Law Dome ice core and 22 years of satellite-derived sea ice extent (SIE) for the 80 degrees E to 140 degrees E sector. Applying this instrumental calibration to longer term MSA data (1841 to 1995 A.D.) suggests that there has been a 20% decline in SIE since about 1950. The decline is not uniform, showing large cyclical variations, with periods of about 11 years, that confuse trend detection over the relatively short satellite era.

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Despite decreasing costs, generating large-scale, well-replicated and multivariate microbial ecology investigations with sequencing remains an expensive and time-consuming option. As a result, many microbial ecology investigations continue to suffer from a lack of appropriate replication. We evaluated two fingerprinting approaches - terminal restriction fragment length polymorphism (T-RFLP) and automated ribosomal intergenic spacer analysis (ARISA) against 454 pyrosequencing, by applying them to 225 polar soil samples from East Antarctica and the high Arctic. By incorporating local and global spatial scales into the dataset, our aim was to determine whether various approaches differed in their ability and hence utility, to identify ecological patterns. Through the reduction in the 454 sequencing data to the most dominant OTUs, we revealed that a surprisingly small proportion of abundant OTUs (< 0.25%) was driving the biological patterns observed. Overall, ARISA and T-RFLP had a similar capacity as sequencing to separate samples according to distance at a local scale, and to correlate environmental variables with microbial community structure. Pyrosequencing had a greater resolution at the global scale but all methods were capable of significantly differentiating the polar sites. We conclude fingerprinting remains a legitimate approach to generating large datasets as well as a cost-effective rapid method to identify samples for elucidating taxonomic information or diversity estimates with sequencing methods.

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