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The oceans sequester a vast amount of carbon thus playing a central role in the global carbon cycle. Assessing how carbon cycling will be impacted by climate change requires an improved understanding of microbial dynamics, which are responsible for most carbon transformations in the oceans. Current numerical models used for predicting future states represent simplified microbial phenotypes and thus may not produce robust predictions of microbial communities. We propose reframing approaches for studying microbial trait change to allow for selection on multi-trait phenotypes. Integrating statistical approaches and trait-based models will allow for the incorporation of evolution into carbon cycle predictions.

 

Ocean microbial communities are made up of thousands of diverse taxa whose metabolic demands set the rates of both biomass production and degradation. Thus, these microscopic organisms play a critical role in ecosystem dynamics, global carbon cycling, and climate. While we have frameworks for relating phytoplankton diversity to rates of carbon fixation, our knowledge of how variations in heterotrophic microbial populations drive changes in carbon cycling is in its infancy. Here, we leverage global metagenomic datasets and metabolic models to identify a set of metabolic niches with distinct growth strategies. These groupings provide a simplifying framework for describing microbial communities in different oceanographic regions and for understanding how heterotrophic microbial populations function. This framework, predicated directly on metabolic capability rather than taxonomy, enables us to tractably link heterotrophic diversity directly to biogeochemical rates in large scale ecosystem models.

 

Phytoplankton are responsible for half of all oxygen production and drive the ocean carbon cycle. Metabolic theory predicts that increasing global temperatures will cause phytoplankton to become more heterotrophic and smaller. Here, we uncover the metabolic trade-offs between cellular space, energy, and stress management driving phytoplankton thermal acclimation and how these might be overcome through evolutionary adaptation. We show that the observed relationships between traits such as chlorophyll, lipid content, C:N, and size can be predicted on the basis of the metabolic demands of the cell, the thermal dependency of transporters, and changes in membrane lipids. We suggest that many of the observed relationships are not fixed physiological constraints but rather can be altered through adaptation. For example, the evolution of lipid metabolism can favor larger cells with higher lipid content to mitigate oxidative stress. These results have implications for rates of carbon sequestration and export in a warmer ocean.

 

Microbial community dynamics on sinking particles control the amount of carbon that reaches the deep ocean and the length of time that carbon is stored, with potentially profound impacts on Earth’s climate. A mechanistic understanding of the controls on sinking particle distributions has been hindered by limited depth- and time-resolved sampling and methods that cannot distinguish individual particles. Here, we analyze microbial communities on nearly 400 individual sinking particles in conjunction with more conventional composite particle samples to determine how particle colonization and community assembly might control carbon sequestration in the deep ocean. We observed community succession with corresponding changes in microbial metabolic potential on the larger sinking particles transporting a significant fraction of carbon to the deep sea. Microbial community richness decreased as particles aged and sank; however, richness increased with particle size and the attenuation of carbon export. This suggests that the theory of island biogeography applies to sinking marine particles. Changes in POC flux attenuation with time and microbial community composition with depth were reproduced in a mechanistic ecosystem model that reflected a range of POC labilities and microbial growth rates. Our results highlight microbial community dynamics and processes on individual sinking particles, the isolation of which is necessary to improve mechanistic models of ocean carbon uptake.

 

Marine microbes like diatoms make up the base of marine food webs and drive global nutrient cycles. Despite their key roles in ecology, biogeochemistry, and biotechnology, we have limited empirical data on how forces other than adaptation may drive diatom diversification, especially in the absence of environmental change. One key feature of diatom populations is frequent extreme reductions in population size, which can occur both in situ and ex situ as part of bloom-and-bust growth dynamics. This can drive divergence between closely related lineages, even in the absence of environmental differences. Here, we combine experimental evolution and transcriptome landscapes (t-scapes) to reveal repeated evolutionary divergence within several species of diatoms in a constant environment. We show that most of the transcriptional divergence can be captured on a reduced set of axes, and that repeatable evolution can occur along a single major axis of variation defined by core ortholog expression comprising common metabolic pathways. Previous work has associated specific transcriptional changes in gene networks with environmental factors. Here, we find that these same gene networks diverge in the absence of environmental change, suggesting these pathways may be central in generating phenotypic diversity as a result of both selective and random evolutionary forces. If this is the case, these genes and the functions they encode may represent universal axes of variation. Such axes that capture suites of interacting transcriptional changes during diversification improve our understanding of both global patterns in local adaptation and microdiversity, as well as evolutionary forces shaping algal cultivation.

 

Marine microbes form the base of ocean food webs and drive ocean biogeochemical cycling. Yet little is known about the ability of microbial populations to adapt as they are advected through changing conditions. Here, we investigated the interplay between physical and biological timescales using a model of adaptation and an eddy-resolving ocean circulation climate model. Two criteria were identified that relate the timing and nature of adaptation to the ratio of physical to biological timescales. Genetic adaptation was impeded in highly variable regimes by nongenetic modifications but was promoted in more stable environments. An evolutionary trade-off emerged where greater short-term nongenetic transgenerational effects (low-γ strategy) enabled rapid responses to environmental fluctuations but delayed genetic adaptation, while fewer short-term transgenerational effects (high-γ strategy) allowed faster genetic adaptation but inhibited short-term responses. Our results demonstrate that the selective pressures for organisms within a single water mass vary based on differences in generation timescales resulting in different evolutionary strategies being favored. Organisms that experience more variable environments should favor a low-γ strategy. Furthermore, faster cell division rates should be a key factor in genetic adaptation in a changing ocean. Understanding and quantifying the relationship between evolutionary and physical timescales is critical for robust predictions of future microbial dynamics. 

Primary productivity in the nutrient-poor subtropical ocean gyres depends on new nitrogen inputs from nitrogen fixers that convert inert dinitrogen gas into bioavailable forms. Temperature and iron (Fe) availability constrain marine nitrogen fixation, and both are changing due to anthropogenic ocean warming. We examined the physiological responses of the globally important marine nitrogen fixer, Crocosphaera watsonii across its full thermal range as a function of iron availability. At the lower end of its thermal range, from 22 to 27°C, Crocosphaera growth, nitrogen fixation, and Nitrogen-specific Iron Use Efficiencies (N-IUEs, mol N fixed hour –1 mol Fe –1 ) increased with temperature. At an optimal growth temperature of 27°C, N-IUEs were 66% higher under iron-limited conditions than iron-replete conditions, indicating that low-iron availability increases metabolic efficiency. However, Crocosphaera growth and function decrease from 27 to 32°C, temperatures that are predicted for an increasing fraction of tropical oceans in the future. Altogether, this suggests that Crocosphaera are well adapted to iron-limited, warm waters, within prescribed limits. A model incorporating these results under the IPCC RCP 8.5 warming scenario predicts that Crocosphaera N-IUEs could increase by a net 47% by 2100, particularly in higher-latitude waters. These results contrast with published responses of another dominant nitrogen fixer ( Trichodesmium ), with predicted N-IUEs that increase most in low-latitude, tropical waters. These models project that differing responses of Crocosphaera and Trichodesmium N-IUEs to future warming of iron-limited oceans could enhance their current contributions to global marine nitrogen fixation with rates increasing by ∼91 and ∼22%, respectively, thereby shifting their relative importance to marine new production and also intensifying their regional divergence. Thus, interactive temperature and iron effects may profoundly transform existing paradigms of nitrogen biogeochemistry and primary productivity in open ocean regimes. 

Ocean phytoplankton play a critical role in the global carbon cycle, contributing ∼50% of global photosynthesis. As planktonic organisms, phytoplankton encounter significant environmental variability as they are advected throughout the ocean. How this variability impacts phytoplankton growth rates and population dynamics remains unclear. Here, we systematically investigated the impact of different rates and magnitudes of sea surface temperature (SST) variability on phytoplankton community growth rates using surface drifter observations from the Southern Ocean (>30°S) and a phenotype‐based ecosystem model. Short‐term SST variability (<7 days) had a minimal impact on phytoplankton community growth rates. Moderate SST changes of 3–4°C over 7–45 days produced a large time lag between the temperature change and the biological response. The impact of SST variability on community growth rates was nonlinear and a function of the rate and magnitude of change. Additionally, the nature of variability generated in a Lagrangian reference frame (following trajectories of surface water parcels) was larger than that within an Eulerian reference frame (fixed point), which initiated different phytoplankton responses between the two reference frames. Finally, we found that these dynamics were not captured by the Eppley growth model commonly used in global biogeochemical models and resulted in an overestimation of community growth rates, particularly in dynamic, strong frontal regions of the Southern Ocean. This work demonstrates that the timescale for environmental selection (community replacement) is a critical factor in determining community composition and takes a first step towards including the impact of variability and biological response times into biogeochemical models.