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CO2concentration and iron availability determine the metabolic inventory in an Emiliania huxleyi ‐dominated phytoplankton community Summary
Ocean acidification (OA), a consequence of anthropogenic carbon dioxide (CO2) emissions, strongly impacts marine ecosystems. OA also influences iron (Fe) solubility, affecting biogeochemical and ecological processes. We investigated the interactive effects of CO2and Fe availability on the metabolome response of a natural phytoplankton community. Using mesocosms we exposed phytoplankton to ambient (390 μatm) or future CO2levels predicted for the year 2100 (900 μatm), combined with ambient (4.5 nM) or high (12 nM) dissolved iron (dFe). By integrating over the whole phytoplankton community, we assigned functional changes based on altered metabolite concentrations. Our study revealed the complexity of phytoplankton metabolism. Metabolic profiles showed three stages in response to treatments and phytoplankton dynamics. Metabolome changes were related to the plankton group contributing respective metabolites, explaining bloom decline and community succession. CO2and Fe affected metabolic profiles. Most saccharides, fatty acids, amino acids and many sterols significantly correlated with the high dFe treatment at ambient
pCO2. High CO2lowered the abundance of many metabolites irrespective of Fe. However, sugar alcohols accumulated, indicating potential stress. We demonstrate that not only altered species composition but also changes in the metabolic landscape affecting the plankton community may change as a consequence of future high‐CO2oceans.
Ice cover plays a critical role in physical, biogeochemical, and ecological processes in lakes. Despite its importance, winter limnology remains relatively understudied. Here, we provide a primer on the predominant drivers of freshwater lake ice cover and the current methodologies used to study lake ice, including in situ and remote sensing observations, physical based models, and experiments. We highlight opportunities for future research by integrating these four disciplines to address key knowledge gaps in our understanding of lake ice dynamics in changing winters. Advances in technology, data integration, and interdisciplinary collaboration will allow the field to move toward developing global forecasts of lake ice cover for small to large lakes across broad spatial and temporal scales, quantifying ice quality and ice thickness, moving from binary to continuous ice records, and determining how winter ice conditions and quality impact ecosystem processes in lakes over winter. Ultimately, integrating disciplines will improve our ability to understand the impacts of changing winters on lake ice.