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Abstract The proportion of major elements in marine organic matter links cellular processes to global nutrient, oxygen and carbon cycles. Differences in the C:N:P ratios of organic matter have been observed between ocean biomes, but these patterns have yet to be quantified from the underlying small-scale physiological and ecological processes. Here we use an ecosystem model that includes adaptive resource allocation within and between ecologically distinct plankton size classes to attribute the causes of global patterns in the C:N:P ratios. We find that patterns of N:C variation are largely driven by common physiological adjustment strategies across all phytoplankton, while patterns of N:P are driven by ecological selection for taxonomic groups with different phosphorus storage capacities. Although N:C varies widely due to cellular adjustment to light and nutrients, its latitudinal gradient is modest because of depth-dependent trade-offs between nutrient and light availability. Strong latitudinal variation in N:P reflects an ecological balance favouring small plankton with lower P storage capacity in the subtropics, and larger eukaryotes with a higher cellular P storage capacity in nutrient-rich high latitudes. A weaker N:P difference between southern and northern hemispheres, and between the Atlantic and Pacific oceans, reflects differences in phosphate available for cellular storage. Despite simulating only two phytoplankton size classes, the emergent global variability of elemental ratios resembles that of all measured species, suggesting that the range of growth conditions and ecological selection sustain the observed diversity of stoichiometry among phytoplankton. 

Phytoplankton exhibit diverse physiological responses to temperature which influence their fitness in the environment and consequently alter their community structure. Here, we explored the sensitivity of phytoplankton community structure to thermal response parameterization in a modelled marine phytoplankton community. Using published empirical data, we evaluated the maximum thermal growth rates (μ_max) and temperature coefficients (Q₁₀; the rate at which growth scales with temperature) of six key Phytoplankton Functional Types (PFTs): coccolithophores, cyanobacteria, diatoms, diazotrophs, dinoflagellates, and green algae. Following three well‐documented methods, PFTs were either assumed to have (1) the sameμ_maxand the sameQ₁₀(as in to Eppley, 1972), (2) a uniqueμ_maxbut the sameQ₁₀(similar to Kremer et al., 2017), or (3) a uniqueμ_maxand a uniqueQ₁₀(following Anderson et al., 2021). These trait values were then implemented within the Massachusetts Institute of Technology biogeochemistry and ecosystem model (called Darwin) for each PFT under a control and climate change scenario. Our results suggest that applying aμ_maxandQ₁₀universally across PFTs (as in Eppley, 1972) leads to unrealistic phytoplankton communities, which lack diatoms globally. Additionally, we find that accounting for differences in theQ₁₀between PFTs can significantly impact each PFT's competitive ability, especially at high latitudes, leading to altered modeled phytoplankton community structures in our control and climate change simulations. This then impacts estimates of biogeochemical processes, with, for example, estimates of export production varying by ~10% in the Southern Ocean depending on the parameterization. Our results indicate that the diversity of thermal response traits in phytoplankton not only shape community composition in the historical and future, warmer ocean, but that these traits have significant feedbacks on global biogeochemical cycles.

 

Phago-mixotrophy, the combination of photoautotrophy and phagotrophy in mixoplankton, organisms that can combine both trophic strategies, have gained increasing attention over the past decade. It is now recognized that a substantial number of protistan plankton species engage in phago-mixotrophy to obtain nutrients for growth and reproduction under a range of environmental conditions. Unfortunately, our current understanding of mixoplankton in aquatic systems significantly lags behind our understanding of zooplankton and phytoplankton, limiting our ability to fully comprehend the role of mixoplankton (and phago-mixotrophy) in the plankton food web and biogeochemical cycling. Here, we put forward five research directions that we believe will lead to major advancement in the field: (i) evolution: understanding mixotrophy in the context of the evolutionary transition from phagotrophy to photoautotrophy; (ii) traits and trade-offs: identifying the key traits and trade-offs constraining mixotrophic metabolisms; (iii) biogeography: large-scale patterns of mixoplankton distribution; (iv) biogeochemistry and trophic transfer: understanding mixoplankton as conduits of nutrients and energy; and (v) in situ methods: improving the identification of in situ mixoplankton and their phago-mixotrophic activity.

 

Remote sensing observations from satellites and global biogeochemical models have combined to revolutionize the study of ocean biogeochemical cycling, but comparing the two data streams to each other and across time remains challenging due to the strong spatial-temporal structuring of the ocean. Here, we show that the Wasserstein distance provides a powerful metric for harnessing these structured datasets for better marine ecosystem and climate predictions. The Wasserstein distance complements commonly used point-wise difference methods such as the root-mean-squared error, by quantifying differences in terms of spatial displacement in addition to magnitude. As a test case, we consider chlorophyll (a key indicator of phytoplankton biomass) in the northeast Pacific Ocean, obtained from model simulations, in situ measurements, and satellite observations. We focus on two main applications: (i) comparing model predictions with satellite observations, and (ii) temporal evolution of chlorophyll both seasonally and over longer time frames. The Wasserstein distance successfully isolates temporal and depth variability and quantifies shifts in biogeochemical province boundaries. It also exposes relevant temporal trends in satellite chlorophyll consistent with climate change predictions. Our study shows that optimal transport vectors underlying the Wasserstein distance provide a novel visualization tool for testing models and better understanding temporal dynamics in the ocean. 

Ocean chlorophyll time series exhibit temporal variability on a range of timescales due to environmental change, ecological interactions, dispersal, and other factors. The differences in chlorophyll temporal variability observed at stationary locations (Eulerian perspective) or following water parcels (Lagrangian perspective) are poorly understood. Here we contrasted the temporal variability of ocean chlorophyll in these two observational perspectives, using global drifter trajectories and satellite chlorophyll to generate matched pairs of Eulerian‐Lagrangian time series. We found that for most ocean locations, chlorophyll variances measured in Eulerian and Lagrangian perspectives are not statistically different. In high latitude areas, the two perspectives may capture similar variability due to the large spatial scale of chlorophyll patches. In localized regions of the ocean, however, chlorophyll variability measured in these two perspectives may significantly differ. For example, in some western boundary currents, temporal chlorophyll variability in the Lagrangian perspective was greater than in the Eulerian perspective. In these cases, the observing platform travels rapidly across strong environmental gradients and constrained by the shelf topography, potentially leading to greater Lagrangian variability in chlorophyll. In contrast, we found that Eulerian chlorophyll variability exceeded Lagrangian variability in some key upwelling zones and boundary current extensions. In these cases, variability in the nutrient supply may generate intermittent chlorophyll anomalies in the Eulerian perspective, while the Lagrangian perspective sees the transport of such anomalies off‐shore. These findings aid with the interpretation of chlorophyll time series from different sampling methodologies, inform observational network design, and guide validation of marine ecosystem models.

 

Rising ocean temperatures affect marine microbial ecosystems directly, since metabolic rates (e.g., photosynthesis, respiration) are temperature‐dependent, but temperature also has indirect effects mediated through changes to the physical environment. Empirical observations of the long‐term trends in biomass and productivity measure the integrated response of these two kinds of effects, making the independent components difficult to disentangle. We used a combination of modeling approaches to isolate the direct effects of rising temperatures on microbial metabolism and explored the consequences for food web dynamics and global biogeochemistry. We evaluated the effects of temperature sensitivity in two cases: first, assuming that all metabolic processes have the same temperature sensitivity, or, alternatively, that heterotrophic processes have higher temperature sensitivity than autotrophic processes. Microbial ecosystems at higher temperatures are characterized by increased productivity but decreased biomass stocks as a result of transient, high export events that reduce nutrient availability in the surface ocean. Trophic dynamics also mediate community structure shifts resulting in increased heterotroph to autotroph ratios at higher temperatures. These ecosystem thermal responses are magnified when the temperature sensitivity of heterotrophs is higher than that of autotrophs. These results provide important context for understanding the combined food web response to direct and indirect temperature effects and inform the construction and interpretation of Earth systems models used in climate projections.

 

Light, essential for photosynthesis, is present in two periodic cycles in nature: seasonal and diel. Although seasonality of light is typically resolved in ocean biogeochemical–ecosystem models because of its significance for seasonal succession and biogeography of phytoplankton, the diel light cycle is generally not resolved. The goal of this study is to demonstrate the impact of diel light cycles on phytoplankton competition and biogeography in the global ocean.

Global ocean.

Phytoplankton.

We use a three‐dimensional global ocean model and compare simulations of high temporal resolution with and without diel light cycles. The model simulates 15 phytoplankton types with different cell sizes, encompassing two broad ecological strategies: small cells with high nutrient affinity (gleaners) and larger cells with high maximal growth rate (opportunists). Both are grazed by zooplankton and limited by nitrogen, phosphorus and iron.

Simulations show that diel cycles of light induce diel cycles in limiting nutrients in the global ocean. Diel nutrient cycles are associated with higher concentrations of limiting nutrients, by 100% at low latitudes (−40° to 40°), a process that increases the relative abundance of opportunists over gleaners. Size classes with the highest maximal growth rates from both gleaner and opportunist groups are favoured by diel light cycles. This mechanism weakens as latitude increases, because the effects of the seasonal cycle dominate over those of the diel cycle.

Understanding the mechanisms that govern phytoplankton biogeography is crucial for predicting ocean ecosystem functioning and biogeochemical cycles. We show that the diel light cycle has a significant impact on phytoplankton competition and biogeography, indicating the need for understanding the role of diel processes in shaping macroecological patterns in the global ocean.