Marine phytoplankton growth at high latitudes is extensively limited by iron availability. Icebergs are a vector transporting the bioessential micronutrient iron into polar oceans. Therefore, increasing iceberg fluxes due to global warming have the potential to increase marine productivity and carbon export, creating a negative climate feedback. However, the magnitude of the iceberg iron flux, the subsequent fertilization effect and the resultant carbon export have not been quantified. Using a global analysis of iceberg samples, we reveal that iceberg iron concentrations vary over 6 orders of magnitude. Our results demonstrate that, whilst icebergs are the largest source of iron to the polar oceans, the heterogeneous iron distribution within ice moderates iron delivery to offshore waters and likely also affects the subsequent ocean iron enrichment. Future marine productivity may therefore be not only sensitive to increasing total iceberg fluxes, but also to changing iceberg properties, internal sediment distribution and melt dynamics.

Practical experiments drive important scientific discoveries in biology, but theory‐based research studies also contribute novel—sometimes paradigm‐changing—findings. Here, we appraise the roles of theory‐based approaches focusing on the experiment‐dominated wet‐biology research areas of microbial growth and survival, cell physiology, host–pathogen interactions, and competitive or symbiotic interactions. Additional examples relate to analyses of genome‐sequence data, climate change and planetary health, habitability, and astrobiology. We assess the importance of thought at each step of the research process; the roles of natural philosophy, and inconsistencies in logic and language, as drivers of scientific progress; the value of thought experiments; the use and limitations of artificial intelligence technologies, including their potential for interdisciplinary and transdisciplinary research; and other instances when theory is the most‐direct and most‐scientifically robust route to scientific novelty including the development of techniques for practical experimentation or fieldwork. We highlight the intrinsic need for human engagement in scientific innovation, an issue pertinent to the ongoing controversy over papers authored using/authored by artificial intelligence (such as the large language model/chatbot ChatGPT). Other issues discussed are the way in which aspects of language can bias thinking towards the spatial rather than the temporal (and how this biased thinking can lead to skewed scientific terminology); receptivity to research that is non‐mainstream; and the importance of theory‐based science in education and epistemology. Whereas we briefly highlight classic works (those by Oakes Ames, Francis H.C. Crick and James D. Watson, Charles R. Darwin, Albert Einstein, James E. Lovelock, Lynn Margulis, Gilbert Ryle, Erwin R.J.A. Schrödinger, Alan M. Turing, and others), the focus is on microbiology studies that are more‐recent, discussing these in the context of the scientific process and the types of scientific novelty that they represent. These include several studies carried out during the 2020 to 2022 lockdowns of the COVID‐19 pandemic when access to research laboratories was disallowed (or limited). We interviewed the authors of some of the featured microbiology‐related papers and—although we ourselves are involved in laboratory experiments and practical fieldwork—also drew from our own research experiences showing that such studies can not only produce new scientific findings but can also transcend barriers between disciplines, act counter to scientific reductionism, integrate biological data across different timescales and levels of complexity, and circumvent constraints imposed by practical techniques. In relation to urgent research needs, we believe that climate change and other global challenges may require approaches beyond the experiment.

Here, we present radiative forcing (RF) estimates by snow algae in the Antarctic Peninsula (AP) region from multi-year measurements of solar radiation and ground-based hyperspectral characterization of red and green snow algae collected during a brief field expedition in austral summer 2018. Our analysis includes pigment content from samples at three bloom sites. Algal biomass in the snow and albedo reduction are well-correlated across the visible spectrum. Relative to clean snow, visibly green patches reduce snow albedo by ∼40 % and red patches by ∼20 %. However, red communities absorb considerably more light per milligram of pigment compared to green communities, particularly in green wavelengths. Based on our study results, it should be possible to differentiate red and green algae using Sentinel-2 bands in blue, green and red wavelengths. Instantaneous RF averages were double for green (180 W m⁻²) vs. red communities (88 W m⁻²), with a maximum of 228 W m⁻². Based on multi-year solar radiation measurements at Palmer Station, this translated to a mean daily RF of ∼26 W m⁻² (green) and ∼13 W m⁻² (red) during peak growing season – on par with midlatitude dust attributions capable of advancing snowmelt. This results in ∼2522 m³ of snow melted by green-colored algae and ∼1218 m³ of snow melted by red-colored algae annually over the summer, suggesting snow algae play a significant role in snowmelt in the AP regions where they occur. We suggest impacts of RF by snow algae on snowmelt be accounted for in future estimates of Antarctic ice-free expansion in the AP region.

Seasonal dynamics of ocean prokaryotic communities in the free-living fraction have been widely described, but less is known about the seasonality of prokaryotes inhabiting marine particles. We describe the seasonality of bacterial communities in the particulate matter continuum by sampling monthly over two years in a temperate oligotrophic coastal ecosystem and using a serial filtration (including six size-fractions spanning from 0.2 to 200 μm). We observed that bacterial communities in the particulate matter continuum had annual changes following harmonic seasonal oscillations, where alpha, beta, and gamma diversity increased during the warm period and decreased during the cold period. Communities in each size-fraction changed gradually over time, being the communities in larger size-fractions the ones with stronger annual changes. Annual community changes were driven mainly by day length and sea surface temperature, and each size-fraction was additionally affected by other variables (e.g., smaller size-fractions by dissolved PO₄ and larger size-fractions by turbidity). While some taxonomic groups mantained their preference for a given size fraction during most of the year, others varied their distribution into different size fractions over time, as e.g., SAR11, which increased its presence in particles during the cold period. Our results indicate that the size-fractionation scheme provides novel seasonal patterns that are not possible to unveil by analyzing only free-living bacteria, and that help to better understand the temporal dynamics of prokaryotes.