This work summarizes ice algal studies, presented as biomass and species temporal and spatial distribution, during 11 cruises conducted between 1986 and 2012. The majority of the biomass was found as loosely attached sub-ice algal layers, and sampling required diving. A maximum of 40 mg chlorophyll m⁻² and 15.4 × 10⁹ cells m⁻² was measured in May. The species diversity was separated in zones based on ice thickness, with the highest biodiversity in the medium-thick ice of 30–80 cm. Nitzschia frigida was the most common species. There was a significant positive relationship between the dominance of this species and ice thickness, and it dominated completely in thick ice. Other common species, such as N. promare and Fossulaphycus arcticus reacted oppositely, by becoming less dominant in thick ice, but the positive correlation between total cell numbers and number of these three species indicated that they would most likely dominate in most populations. Melosira arctica was found several times below medium-thick annual ice. Algae occurred from top to bottom in the ice floes and in infiltration layers, but in very low numbers inside the ice. The bipolar dinoflagellates Polarella glacialis inhabited the ice, both as vegetative cells and cysts. The algal layers detached from the ice and sank in late spring when melting started. The cells in the sediments form an important food source for benthic animals throughout the year. Fjord populations survive the winter on the bottom and probably form next year’s ice algal inoculum. A few ‘over-summer’ populations found in sheltered locations might provide supplementary food for ice amphipods in late summer. The future faith of the ice flora is discussed in view of a warmer climate, with increased melting of the Arctic ice cover.

Despite the exclusion of the Southern Ocean from assessments of progress towards achieving the Convention on Biological Diversity (CBD) Strategic Plan, the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) has taken on the mantle of progressing efforts to achieve it. Within the CBD, Aichi Target 11 represents an agreed commitment to protect 10% of the global coastal and marine environment. Adopting an ethos of presenting the best available scientific evidence to support policy makers, CCAMLR has progressed this by designating two Marine Protected Areas in the Southern Ocean, with three others under consideration. The region of Antarctica known as Dronning Maud Land (DML; 20°W to 40°E) and the Atlantic sector of the Southern Ocean that abuts it conveniently spans one region under consideration for spatial protection. To facilitate both an open and transparent process to provide the vest available scientific evidence for policy makers to formulate management options, we review the body of physical, geochemical and biological knowledge of the marine environment of this region. The level of scientific knowledge throughout the seascape abutting DML is polarized, with a clear lack of data in its eastern part which is presumably related to differing levels of research effort dedicated by national Antarctic programmes in the region. The lack of basic data on fundamental aspects of the physical, geological and biological nature of eastern DML make predictions of future trends difficult to impossible, with implications for the provision of management advice including spatial management. Finally, by highlighting key knowledge gaps across the scientific disciplines our review also serves to provide guidance to future research across this important region.

Ecosystems are subjected to increasing exposure to multiple anthropogenic drivers. This has led to the development of national and international accounting systems describing the condition of ecosystems, often based on few, highly aggregated indicators. Such accounting systems would benefit from a stronger theoretical and empirical underpinning of ecosystem dynamics. Operational tools for ecosystem management require understanding of natural ecosystem dynamics, consideration of uncertainty at all levels, means for quantifying driver-response relationships behind observed and anticipated future trajectories of change, and an efficient and transparent synthesis to inform knowledge-driven decision processes. There is hence a gap between highly aggregated indicator-based accounting tools and the need for explicit understanding and assessment of the links between multiple drivers and ecosystem condition as a foundation for informed and adaptive ecosystem management. We describe here an approach termed PAEC (Panel-based Assessment of Ecosystem Condition) for combining quantitative and qualitative elements of evidence and uncertainties into an integrated assessment of ecosystem condition at spatial scales relevant to management and monitoring. The PAEC protocol is founded on explicit predictions, termed phenomena, of how components of ecosystem structure and functions are changing as a result of acting drivers. The protocol tests these predictions with observations and combines these tests to assess the change in the condition of the ecosystem as a whole. PAEC includes explicit, quantitative or qualitative, assessments of uncertainty at different levels and integrates these in the final assessment. As proofs-of-concept we summarize the application of the PAEC protocol to a marine and a terrestrial ecosystem in Norway.