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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.

 

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. 

Linking ‘omics measurements with biogeochemical cycles is a widespread challenge in microbial community ecology. Here, we propose applying genomic adaptation as ‘biosensors’ for microbial investments to overcome nutrient stress. We then integrate this genomic information with a trait-based model to predict regional shifts in the elemental composition of marine plankton communities. We evaluated this approach using metagenomic and particulate organic matter samples from the Atlantic, Indian and Pacific Oceans. We find that our genome-based trait model significantly improves our prediction of particulate C : P (carbon : phosphorus) across ocean regions. Furthermore, we detect previously unrecognized ocean areas of iron, nitrogen and phosphorus stress. In many ecosystems, it can be very challenging to quantify microbial stress. Thus, a carefully calibrated genomic approach could become a widespread tool for understanding microbial responses to environmental changes and the biogeochemical outcomes. This article is part of the theme issue ‘Conceptual challenges in microbial community ecology’. 

A key uncertainty for predicting future ocean oxygen levels is the response and feedback of organic matter respiration demand. One poorly constrained component of the respiration demand is the oxygen‐to‐carbon remineralization ratio—the respiration quotient. Currently, multiple biological hypotheses can explain variation in the respiration quotient of organic matter produced in the surface ocean. To test these hypotheses, we directly quantified the particulate respiration quotient in 715 samples along a meridional section of the Atlantic Ocean and compared to previous Pacific Ocean observations. We demonstrate significant regional shifts in the respiration quotient and a two‐basin average of 1.16. Possible diel oscillations were also observed in the respiration quotient. Basin and regional variation in the respiration quotient were positively linked to temperature, N versus P stress, and plankton size structure. These observations suggest a complex regulation of the respiration quotient with important implications for the regional coupling of carbon and oxygen cycling.

 

Climate-driven depletion of ocean oxygen strongly impacts the global cycles of carbon and nutrients as well as the survival of many animal species. One of the main uncertainties in predicting changes to marine oxygen levels is the regulation of the biological respiration demand associated with the biological pump. Derived from the Redfield ratio, the molar ratio of oxygen to organic carbon consumed during respiration (i.e., the respiration quotient,$r_{-O2:C}$) is consistently assumed constant but rarely, if ever, measured. Using a prognostic Earth system model, we show that a 0.1 increase in the respiration quotient from 1.0 leads to a 2.3% decline in global oxygen, a large expansion of low-oxygen zones, additional water column denitrification of 38 Tg N/y, and the loss of fixed nitrogen and carbon production in the ocean. We then present direct chemical measurements of$r_{-O2:C}$using a Pacific Ocean meridional transect crossing all major surface biome types. The observed$r_{-O2:C}$has a positive correlation with temperature, and regional mean values differ significantly from Redfield proportions. Finally, an independent global inverse model analysis constrained with nutrients, oxygen, and carbon concentrations supports a positive temperature dependence of$r_{-O2:C}$in exported organic matter. We provide evidence against the common assumption of a static biological link between the respiration of organic carbon and the consumption of oxygen. Furthermore, the model simulations suggest that a changing respiration quotient will impact multiple biogeochemical cycles and that future warming can lead to more intense deoxygenation than previously anticipated.

 

Detailed descriptions of microbial communities have lagged far behind physical and chemical measurements in the marine environment. Here, we present 971 globally distributed surface ocean metagenomes collected at high spatio-temporal resolution. Our low-cost metagenomic sequencing protocol produced 3.65 terabases of data, where the median number of base pairs per sample was 3.41 billion. The median distance between sampling stations was 26 km. The metagenomic libraries described here were collected as a part of a biological initiative for the Global Ocean Ship-based Hydrographic Investigations Program, or “Bio-GO-SHIP.” One of the primary aims of GO-SHIP is to produce high spatial and vertical resolution measurements of key state variables to directly quantify climate change impacts on ocean environments. By similarly collecting marine metagenomes at high spatiotemporal resolution, we expect that this dataset will help answer questions about the link between microbial communities and biogeochemical fluxes in a changing ocean.