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Recent studies have demonstrated regional differences in marine ecosystem C:N:P with implications for carbon and nutrient cycles. Due to strong co-variance, temperature and nutrient stress explain variability in C:N:P equally well. A reductionistic approach can link changes in individual environmental drivers with changes in biochemical traits and cell C:N:P. Thus, we quantified effects of temperature and nutrient stress on Synechococcus chemistry using laboratory chemostats, chemical analyses, and data-independent acquisition mass spectrometry proteomics. Nutrient supply accounted for most C:N:Pcell variability and induced tradeoffs between nutrient acquisition and ribosomal proteins. High temperature prompted heat-shock, whereas thermal effects via the “translation-compensation hypothesis” were only seen under P-stress. A Nonparametric Bayesian Local Clustering algorithm suggested that changes in lipopolysaccharides, peptidoglycans, and C-rich compatible solutes may also contribute to C:N:P regulation. Physiological responses match field-based trends in ecosystem stoichiometry and suggest a hierarchical environmental regulation of current and future ocean C:N:P.

 

Key Points Simulated Prochlorococcus , Synechococcus , and pico‐eukaryotes contribute ∼60% of marine net primary productivity (NPP) Pico‐phytoplankton cycling contributes half of the marine export production, approaching parity with their contribution to NPP Pico‐eukaryotes and diatoms with elevated C:P stoichiometry enhance carbon export at poleward flanks of western boundary currents 

Prochlorococcus is the most numerically abundant photosynthetic organism in the surface ocean. The Prochlorococcus high-light and warm-water adapted ecotype (HLII) is comprised of extensive microdiversity, but specific functional differences between microdiverse sub-clades remain elusive. Here we characterized both functional and phylogenetic diversity within the HLII ecotype using Bio-GO-SHIP metagenomes. We found widespread variation in gene frequency connected to local environmental conditions. Metagenome-assembled marker genes and genomes revealed a globally distributed novel HLII haplotype defined by adaptation to chronically low P conditions (HLII-P). Environmental correlation analysis revealed different factors were driving gene abundances verses phylogenetic differences. An analysis of cultured HLII genomes and metagenome-assembled genomes revealed a subclade within HLII, which corresponded to the novel HLII-P haplotype. This work represents the first global assessment of the HLII ecotype’s phylogeography and corresponding functional differences. These findings together expand our understanding of how microdiversity structures functional differences and reveals the importance of nutrients as drivers of microdiversity in Prochlorococcus.

 

The elemental ratios of carbon, nitrogen, and phosphorus (C:N:P) within organic matter play a key role in coupling biogeochemical cycles in the global ocean. At the cellular level, these ratios are controlled by physiological responses to the environment. But linking these cellular‐level processes to global biogeochemical cycles remains challenging. We present a novel model framework that combines knowledge of phytoplankton cellular functioning with global scale hydrographic data, to assess the role of variable carbon‐to‐phosphorus ratios (R_C:P) on the distribution of export production. We implement a trait‐based mechanistic model of phytoplankton growth into a global biogeochemical inverse model to predict global patterns of phytoplankton physiology and stoichiometry that are consistent with both biological growth mechanisms and hydrographic carbon and nutrient observations. We compare this model to empirical parameterizations relatingR_C:Pto temperature or phosphate concentration. We find that the way the model represents variable stoichiometry affects the magnitude and spatial pattern of carbon export, with globally integrated fluxes varying by up to 10% (1.3 Pg C yr⁻¹) across models. Despite these differences, all models exhibit strong consistency with observed dissolved inorganic carbon and phosphate concentrations (R² > 0.9), underscoring the challenge of selecting the most accurate model structure. We also find that the choice of parameterization impacts the capacity of changingR_C:Pto buffer predicted export declines. Our novel framework offers a pathway by which additional biological information might be used to reduce the structural uncertainty in model representations of phytoplankton stoichiometry, potentially improving our capacity to project future changes.

 

Historically, our understanding of bacterial ecology in the Indian Ocean has been limited to regional studies that place emphasis on community structure and function within oxygen‐minimum zones. Thus, bacterial community dynamics across the wider Indian Ocean are largely undescribed. As part of Bio‐GO‐SHIP, we sequenced the 16S rRNA gene from 465 samples collected on sections I07N and I09N. We found that (1) there were 23 distinct bioregions within the Indian Ocean, (2) the southeastern gyre had the largest gradient in bacterial alpha‐diversity, (3) the Indian Ocean surface microbiome was primarily composed of a core set of taxa, and (4) bioregions were characterized by transitions in physical and geochemical conditions. Overall, we showed that bacterial community structure spatially delineated the surface Indian Ocean and that these microbially defined regions were reflective of subtle ocean physical and geochemical gradients. Therefore, incorporating metrics of in situ microbial communities into marine ecological regions traditionally defined by remote sensing will improve our ability to delineate warm, oligotrophic regions.

 

Establishing links between microbial diversity and environmental processes requires resolving the high degree of functional variation among closely related lineages or ecotypes. Here, we implement and validate an improved metagenomic approach that estimates the spatial biogeography and environmental regulation of ecotype-specific replication patterns (RObs) across ocean regions. A total of 719 metagenomes were analyzed from meridional Bio-GO-SHIP sections in the Atlantic and Indian Ocean. Accounting for sequencing bias and anchoring replication estimates in genome structure were critical for identifying physiologically relevant biological signals. For example, ecotypes within the dominant marine cyanobacteria Prochlorococcus exhibited distinct diel cycles in RObs that peaked between 19:00–22:00. Additionally, both Prochlorococcus ecotypes and ecotypes within the highly abundant heterotroph Pelagibacter (SAR11) demonstrated systematic biogeographies in RObs that differed from spatial patterns in relative abundance. Finally, RObs was significantly regulated by nutrient stress and temperature, and explained by differences in the genomic potential for nutrient transport, energy production, cell wall structure, and replication. Our results suggest that our new approach to estimating replication is reflective of gross population growth. Moreover, this work reveals that the interaction between adaptation and environmental change drives systematic variability in replication patterns across ocean basins that is ecotype-specific, adding an activity-based dimension to our understanding of microbial niche space.

 

Oceanic nutrient cycles are coupled, yet carbon-nitrogen-phosphorus (C:N:P) stoichiometry in marine ecosystems is variable through space and time, with no clear consensus on the controls on variability. Here, we analyze hydrographic, plankton genomic diversity, and particulate organic matter data from 1970 stations sampled during a global ocean observation program (Bio-GO-SHIP) to investigate the biogeography of surface ocean particulate organic matter stoichiometry. We find latitudinal variability in C:N:P stoichiometry, with surface temperature and macronutrient availability as strong predictors of stoichiometry at high latitudes. Genomic observations indicated community nutrient stress and suggested that nutrient supply rate and nitrogen-versus-phosphorus stress are predictive of hemispheric and regional variations in stoichiometry. Our data-derived statistical model suggests that C:P and N:P ratios will increase at high latitudes in the future, however, changes at low latitudes are uncertain. Our findings suggest systematic regulation of elemental stoichiometry among ocean ecosystems, but that future changes remain highly uncertain.

 

Abstract Concentrations and elemental stoichiometry of suspended particulate organic carbon, nitrogen, phosphorus, and oxygen demand for respiration (C:N:P:−O 2 ) play a vital role in characterizing and quantifying marine elemental cycles. Here, we present Version 2 of the Global Ocean Particulate Organic Phosphorus, Carbon, Oxygen for Respiration, and Nitrogen (GO-POPCORN) dataset. Version 1 is a previously published dataset of particulate organic matter from 70 different studies between 1971 and 2010, while Version 2 is comprised of data collected from recent cruises between 2011 and 2020. The combined GO-POPCORN dataset contains 2673 paired surface POC/N/P measurements from 70°S to 73°N across all major ocean basins at high spatial resolution. Version 2 also includes 965 measurements of oxygen demand for organic carbon respiration. This new dataset can help validate and calibrate the next generation of global ocean biogeochemical models with flexible elemental stoichiometry. We expect that incorporating variable C:N:P:-O 2 into models will help improve our estimates of key ocean biogeochemical fluxes such as carbon export, nitrogen fixation, and organic matter remineralization. 

Climate warming likely drives ocean deoxygenation, but models still cannot fully explain observed declines in oxygen. One unconstrained parameter is the oxygen demand per carbon respired for complete remineralization of organic matter (i.e., the total respiration quotient,r_Σ‐O2:C). Here, we tested ifr_Σ‐O2:Cdeclined with depth by quantifying suspended concentrations of particulate organic carbon (POC), particulate organic nitrogen (PON), particulate organic phosphorus (POP), particulate chemical oxygen demand (PCOD), and total oxygen demand (Σ‐O₂ = PCOD + 2PON) down to a depth of 1,000 m in the Sargasso Sea. The respiration quotient (r_‐O2:C = PCOD:POC) and total respiration quotient (r_Σ‐O2:C = Σ‐O₂:POC) declined with depth in the euphotic zone, but increased vertically in the disphotic zone. C:N andr_Σ‐O2:Nchanged with depth, but surface values were similar to values at 1,000 m. C:P, N:P, andr_Σ‐O2:Pmostly decreased with depth. We hypothesize thatr_Σ‐O2:Cis linked to multiple environmental factors that change with depth, such as phytoplankton community structure and the preferential production/removal of biomolecules. Using a global model, we show that the global distribution of dissolved oxygen is equally sensitive tor_‐O2:Cvarying between surface biomes versus vertically during remineralization. Additionally, adjusting the model'sr_‐O2:Cwith depth to match our observations resulted in less dissolved oxygen throughout the upper ocean. Most of this loss occurred in the tropical Pacific thermocline, where oxygen models underestimate deoxygenation the most. This study aims to improve our understanding of biological oxygen demand as warming‐induced deoxygenation continues.