The pelagic spring bloom is essential for Arctic marine food webs, and a crucial driver of carbon transport to the ocean depths. A critical challenge is understanding its timing and magnitude, to predict its changes in coming decades. Spring bloom onset is typically light-limited, beginning when irradiance increases or during ice breakup. Here we report an acute 9-day under-ice algal bloom in nutrient-poor, freshwater-influenced water under 1-m thick sea ice. It was dominated by mixotrophic brackish water haptophytes (Chrysochromulina/ Prymnesium) that produced 5.7 g C m−2 new production. This estimate represents about half the annual pelagic production, occurring below sea ice with a large contribution from the mixotrophic algae bloom. The freshwater-influenced, nutrient-dilute and low light environment combined with mixotrophic community dominance implies that phagotrophy played a critical role in the under-ice bloom. We argue that such blooms dominated by potentially toxic mixotrophic algae might become more common and widespread in the future Arctic Ocean.

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Global deterioration of marine ecosystems, together with increasing pressure to use them, has created a demand for new, more efficient and cost-efficient monitoring tools that enable assessing changes in the status of marine ecosystems. However, demonstrating the cost-efficiency of a monitoring method is not straightforward as there are no generally applicable guidelines. Our study provides a systematic literature mapping of methods and criteria that have been proposed or used since the year 2000 to evaluate the cost-efficiency of marine monitoring methods. We aimed to investigate these methods but discovered that examples of actual cost-efficiency assessments in literature were rare, contradicting the prevalent use of the term “cost-efficiency.” We identified five different ways to compare the cost-efficiency of a marine monitoring method: (1) the cost–benefit ratio, (2) comparative studies based on an experiment, (3) comparative studies based on a literature review, (4) comparisons with other methods based on literature, and (5) subjective comparisons with other methods based on experience or intuition. Because of the observed high frequency of insufficient cost–benefit assessments, we strongly advise that more attention is paid to the coverage of both cost and efficiency parameters when evaluating the actual cost-efficiency of novel methods. Our results emphasize the need to improve the reliability and comparability of cost-efficiency assessments. We provide guidelines for future initiatives to develop a cost-efficiency assessment framework and suggestions for more unified cost-efficiency criteria.

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