Explore the vast range of titles available.

Understanding the causes of the  ~90 ppmv atmospheric CO 2 swings between glacial and interglacial climates is an important open challenge in paleoclimate research. Although the regularity of the glacial-interglacial cycles hints at a single driving mechanism, Earth System models require many independent physical and biological processes to explain the full observed CO 2 signal. Here we show that biologically sequestered carbon in the ocean can explain an atmospheric CO 2 change of 75 ± 40 ppmv, based on a mass balance calculation using published carbon isotopic measurements. An analysis of the carbon isotopic signatures of different water masses indicates similar regenerated carbon inventories at the Last Glacial Maximum and during the Holocene, requiring that the change in carbon storage was dominated by disequilibrium. We attribute the inferred change in carbon disequilibrium to expansion of sea-ice or change in the overturning circulation. Atmospheric CO2 was  ~ 90 ppmv lower at the Last Glacial Maximum (LGM) than during the Holocene. Based on a carbon isotope budget, this study infers that at the LGM biological production pumped carbon into the deep ocean and sea ice kept it there.

Statistically derived species distribution models (SDMs) are increasingly used to predict ecological changes on a warming planet. For Prochlorococcus , the most abundant phytoplankton, an established statistical prediction conflicts with dynamical models as they predict large, opposite, changes in abundance. We probe the SDM at various spatial-temporal scales, showing that light and temperature fail to explain both temporal fluctuations and sharp spatial transitions. Strong correlations between changes in temperature and population emerge only at very large spatial scales, as transects pass through transitions between regions of high and low abundance. Furthermore, a two-state model based on a temperature threshold matches the original SDM in the surface ocean. We conclude that the original SDM has little power to predict changes when Prochlorococcus is already abundant, which resolves the conflict with dynamical models. Our conclusion suggests that SDMs should prove efficacy across multiple spatial-temporal scales before being trusted in a changing ocean. This work explains how the spatial structuring of populations, focusing on the globally dominant phytoplankton Prochlorococcus , can lead to erroneous statistical predictions for changes in plankton abundance as the ocean warms. Conflicting predictions of dynamical and statistical models for this biogeochemically critical species are resolved.

Significance Oceanic dissolved organic carbon (DOC) contains as much carbon as Earth’s atmosphere, yet its cycling timescales and composition remain poorly constrained. We use serial oxidation experiments to measure the quantitative distribution of carbon isotopes inside the DOC reservoir, allowing us to estimate both its cycling timescales and source distribution. We find that a large portion of deep water DOC has a modern radiocarbon age and a fast turnover time supported by particle dissolution. In addition, stable carbon isotopes allow for diverse sources of carbon, besides microbial production, to quantitatively feed this reservoir. Our work suggests a DOC cycle that is far more intricate, and potentially variable on shorter timescales, than previously envisioned. Marine dissolved organic carbon (DOC) is a large (660 Pg C) reactive carbon reservoir that mediates the oceanic microbial food web and interacts with climate on both short and long timescales. Carbon isotopic content provides information on the DOC source via δ ¹³C and age via Δ ¹⁴C. Bulk isotope measurements suggest a microbially sourced DOC reservoir with two distinct components of differing radiocarbon age. However, such measurements cannot determine internal dynamics and fluxes. Here we analyze serial oxidation experiments to quantify the isotopic diversity of DOC at an oligotrophic site in the central Pacific Ocean. Our results show diversity in both stable and radio isotopes at all depths, confirming DOC cycling hidden within bulk analyses. We confirm the presence of isotopically enriched, modern DOC cocycling with an isotopically depleted older fraction in the upper ocean. However, our results show that up to 30% of the deep DOC reservoir is modern and supported by a 1 Pg/y carbon flux, which is 10 times higher than inferred from bulk isotope measurements. Isotopically depleted material turns over at an apparent time scale of 30,000 y, which is far slower than indicated by bulk isotope measurements. These results are consistent with global DOC measurements and explain both the fluctuations in deep DOC concentration and the anomalous radiocarbon values of DOC in the Southern Ocean. Collectively these results provide an unprecedented view of the ways in which DOC moves through the marine carbon cycle.

In the North Pacific Subtropical Gyre (NPSG), an annual pulse of sinking organic carbon is observed at 4000 m between July and August, driven by large diatoms found in association with nitrogen fixing, heterocystous, cyanobacteria: Diatom–Diazotroph Associations (DDAs). Here we ask what drives the bloom of DDAs and present a simplified trait-based model of subtropical phototroph populations driven by observed, monthly averaged, environmental characteristics. The ratio of resource supply rates favors nitrogen fixation year round. The relative fitness of DDA traits is most competitive in early summer when the mixed layer is shallow, solar irradiance is high, and phosphorus and iron are relatively abundant. Later in the season, as light intensity drops and phosphorus is depleted, the traits of small unicellular diazotrophs become more competitive. The competitive transition happens in August, at the time when the DDA export event occurs. This seasonal dynamic is maintained when embedded in a more complex, global-scale, ecological model, and provides predictions for the extent of the North Pacific DDA bloom. The model provides a parsimonious and testable hypothesis for the stimulation of DDA blooms.

Photosynthesis fuels primary production at the base of marine food webs. Yet, in many surface ocean ecosystems, diel-driven primary production is tightly coupled to daily loss. This tight coupling raises the question: which top-down drivers predominate in maintaining persistently stable picocyanobacterial populations over longer time scales? Motivated by high-frequency surface water measurements taken in the North Pacific Subtropical Gyre (NPSG), we developed multitrophic models to investigate bottom-up and top-down mechanisms underlying the balanced control of Prochlorococcus populations. We find that incorporating photosynthetic growth with viral- and predator-induced mortality is sufficient to recapitulate daily oscillations of Prochlorococcus abundances with baseline community abundances. In doing so, we infer that grazers in this environment function as the predominant top-down factor despite high standing viral particle densities. The model-data fits also reveal the ecological relevance of light-dependent viral traits and non-canonical factors to cellular loss. Finally, we leverage sensitivity analyses to demonstrate how variation in life history traits across distinct oceanic contexts, including variation in viral adsorption and grazer clearance rates, can transform the quantitative and even qualitative importance of top-down controls in shaping Prochlorococcus population dynamics. This study shows that a multitrophic community model jointly recapitulates diel rhythms in abundances of Prochlorococcus picocyanobacteria, as well as viral infection, viral abundances and grazer abundances. Model-data integration implies that grazing predominantly controls Prochlorococcus abundances in surface waters of the North Pacific Subtropical Gyre, despite high viral densities.

Diatom–diazotroph associations (DDAs) are symbioses where trichome-forming cyanobacteria support the host diatom with fixed nitrogen through dinitrogen (N2) fixation. It is inferred that the growth of the trichomes is also supported by the host, but the support mechanism has not been fully quantified. Here, we develop a coarse-grained, cellular model of the symbiosis between Hemiaulus and Richelia (one of the major DDAs), which shows that carbon (C) transfer from the diatom enables a faster growth and N2 fixation rate by the trichomes. The model predicts that the rate of N2 fixation is 5.5 times that of the hypothetical case without nitrogen (N) transfer to the host diatom. The model estimates that 25% of fixed C from the host diatom is transferred to the symbiotic trichomes to support the high rate of N2 fixation. In turn, 82% of N fixed by the trichomes ends up in the host. Modeled C fixation from the vegetative cells in the trichomes supports only one-third of their total C needs. Even if we ignore the C cost for N2 fixation and for N transfer to the host, the total C cost of the trichomes is higher than the C supply by their own photosynthesis. Having more trichomes in a single host diatom decreases the demand for N2 fixation per trichome and thus decreases their cost of C. However, even with five trichomes, which is about the highest observed for Hemiaulus and Richelia symbiosis, the model still predicts a significant C transfer from the diatom host. These results help quantitatively explain the observed high rates of growth and N2 fixation in symbiotic trichomes relative to other aquatic diazotrophs.

Prochlorococcus is both the smallest and numerically most abundant photosynthesizing organism on the planet. While thriving in the warm oligotrophic gyres, Prochlorococcus concentrations drop rapidly in higher-latitude regions. Transect data from the North Pacific show the collapse occurring at a wide range of temperatures and latitudes (temperature is often hypothesized to cause this shift), suggesting an ecological mechanism may be at play. An often used size-based theory of phytoplankton community structure that has been incorporated into computational models correctly predicts the dominance of Prochlorococcus in the gyres, and the relative dominance of larger cells at high latitudes. However, both theory and computational models fail to explain the poleward collapse. When heterotrophic bacteria and predators that prey nonspecifically on both Prochlorococcus and bacteria are included in the theoretical framework, the collapse of Prochlorococcus occurs with increasing nutrient supplies. The poleward collapse of Prochlorococcus populations then naturally emerges when this mechanism of “shared predation” is implemented in a complex global ecosystem model. Additionally, the theory correctly predicts trends in both the abundance and mean size of the heterotrophic bacteria. These results suggest that ecological controls need to be considered to understand the biogeography of Prochlorococcus and predict its changes under future ocean conditions. Indirect interactions within a microbial network can be essential in setting community structure.

In the North Pacific Ocean, nutrient rich surface waters flow south from the subpolar gyre through a transitional region and into the subtropics. Along the way, nutrients are used, recycled, and exported, leading to lower biomass and a commensurate change in ecosystem structure moving southward. We focus on the region between the two gyres (the Transition Zone) using a coupled biophysical ocean model, remote sensing, floats, and cruise data to explore the nature of the physical, biogeochemical, and ecological fields in this region. Nonlinear interactions between biological processes and the meridional gradient in nutrient supply lead to sharp shifts across this zone. These transitions between a southern region with more uniform biological and biogeochemical properties and steep meridional gradients to the north are diagnosed from extrema in the first derivative of the properties with latitude. Some transitions like that for chlorophyll a (the transition zone chlorophyll front [TZCF]) experience large seasonal excursions while the location of the transitions in other properties moves very little. The seasonal shifts are not caused by changes in the horizontal flow field, but rather by the interaction of seasonal, depth related, forcing with the mean latitudinal gradients. Focusing on the TZCF as a case study, we express its phase velocity in terms of vertical nutrient flux and internal ecosystem processes, demonstrating their nearly equal influence on its motion. This framework of propagating biogeochemical transitions can be systematically expanded to better understand the processes that structure ecosystems and biogeochemistry in the North Pacific and beyond.

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.

Global biogeochemical ocean models are invaluable tools to examine how physical, chemical, and biological processes interact in the ocean. Satellite-derived ocean color properties, on the other hand, provide observations of the surface ocean, with unprecedented coverage and resolution. Advances in our understanding of marine ecosystems and biogeochemistry are strengthened by the combined use of these resources, together with sparse in situ data. Recent modeling advances allow the simulation of the spectral properties of phytoplankton and remote sensing reflectances, bringing model outputs closer to the kind of data that ocean color satellites can provide. However, comparisons between model outputs and analogous satellite products (e.g., chlorophyll a) remain problematic. Most evaluations are based on point-by-point comparisons in space and time, where spuriously large errors can occur from small spatial and temporal mismatches, whereas global statistics provide no information on how well a model resolves processes at regional scales. Here, we employ a unique suite of methodologies, the Probability Density Functions to Evaluate Models (PDFEM), which generate a robust comparison of these resources. The probability density functions of physical and biological properties of Longhurst's provinces are compared to evaluate how well a model resolves related processes. Differences in the distributions of chlorophyll a concentration (mg m-3) provide information on matches and mismatches between models and observations. In particular, mismatches help isolate regional sources of discrepancy, which can lead to improving both simulations and satellite algorithms. Furthermore, the use of radiative transfer in the model to mimic remotely sensed products facilitates model–observation comparisons of optical properties of the ocean.