A new study reveals that dark-pigmented microalgae, which contribute to the melting of the Greenland ice sheet, are highly efficient at nutrient uptake and growth, allowing them to rapidly colonise expanding areas of exposed ice. The findings suggest that these algae can persist and spread without the need for additional nutrient inputs, intensifying ice sheet darkening and accelerating melt rates. The results were published in the journal Nature Communications.

The utilised cutting-edge single-cell imaging techniques to examine the carbon, nitrogen, and phosphorus content of glacier ice algae. By measuring their nutrient assimilation rates, the study found that these algae store phosphorus internally and maintain exceptionally high carbon-to-nutrient ratios, indicating a survival strategy finely tuned to nutrient-poor glacier environments. 

“Our study provides crucial insights into how glacier ice algae sustain themselves in such extreme conditions,” Dr James Bradley from the Queen Mary University of London and a co-author of the paper said in a release. “They don’t require large amounts of external nutrients to grow, which means that as the ice sheet continues to melt and expose more bare ice, these algae are well-positioned to expand their coverage. This is particularly concerning because their dark pigmentation lowers the ice’s reflectivity, increasing heat absorption and accelerating melting and therefore sea-level rise.”

The melting of the Greenland Ice Sheet is the single largest contributor of freshwater to global sea-level rise. Previous research has shown that algal blooms on the ice sheet’s western margin can enhance melt rates by 10 to 13%. However, the factors controlling algal growth have remained unclear. This new study highlights how these resilient microorganisms can optimise their nutrient intake, ensuring their survival and expansion despite the nutrient-poor conditions of the ice sheet.

By revealing the self-sufficiency of these algae, the study underscores the urgent need to incorporate biological processes into climate models predicting ice sheet melt.