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The sawtooth-patterned glacial-interglacial cycles in the Earth’s atmospheric temperature are a well-known, though poorly understood phenomenon. Pinpointing the relevant mechanisms behind these cycles will not only provide insights into past climate dynamics, but also help predict possible future responses of the Earth system to changing CO2 levels. Previous work on this phenomenon suggests that the most important underlying mechanisms are interactions between marine biological production, ocean circulation, temperature and dust. So far, interaction directions (i.e., what causes what) have remained elusive. In this paper, we apply Convergent Cross-Mapping (CCM) to analyze paleoclimatic and paleoceanographic records to elucidate which mechanisms proposed in the literature play an important role in glacial-interglacial cycles, and to test the directionality of interactions. We find causal links between ocean ventilation, biological productivity, benthic δ18O and dust, consistent with some but not all of the mechanisms proposed in the literature. Most importantly, we find evidence for a potential feedback loop from ocean ventilation to biological productivity to climate back to ocean ventilation. Here, we propose the hypothesis that this feedback loop of connected mechanisms could be the main driver for the glacial-interglacial cycles.

Ice core measurements have revealed a highly asymmetric cycle in Antarctic temperature and atmospheric CO2 over the last 800 kyr. Both CO 2 and temperature decrease over 100 kyr going into a glacial period and then rise steeply over less than 10 kyr at the end of a glacial period. There does not yet exist wide agreement about the causes of this cycle or about the origin of its shape. Here we explore the possibility that an ecologically driven oscillator plays a role in the dynamics. A conceptual model describing the interaction between calcifying plankton and ocean alkalinity shows interesting features: (i) It generates an oscillation in atmospheric CO 2 with the characteristic asymmetric shape observed in the ice core record, (ii) the system can transform a sinusoidal Milankovitch forcing into a sawtooth-shaped output, and (iii) there are spikes of enhanced calcifier productivity at the glacial-interglacial transitions, consistent with several sedimentary records. This suggests that ecological processes might play an active role in the observed glacial-interglacial cycles.

We present a model of the growth rate and elemental stoichiometry of phytoplankton as a function of resource allocation between and within broad macromolecular pools under a variety of resource supply conditions. The model is based on four, empirically-supported, cornerstone assumptions: that there is a saturating relationship between light and photosynthesis, a linear relationship between RNA/protein and growth rate, a linear relationship between biosynthetic proteins and growth rate, and a constant macromolecular composition of the light-harvesting machinery. We combine these assumptions with statements of conservation of carbon, nitrogen, phosphorus, and energy. The model can be solved algebraically for steady state conditions and constrained with data on elemental stoichiometry from published laboratory chemostat studies. It interprets the relationships between macromolecular and elemental stoichiometry and also provides quantitative predictions of the maximum growth rate at given light intensity and nutrient supply rates. The model is compatible with data sets from several laboratory studies characterizing both prokaryotic and eukaryotic phytoplankton from marine and freshwater environments. It is conceptually simple, yet mechanistic and quantitative. Here, the model is constrained only by elemental stoichiometry, but makes predictions about allocation to measurable macromolecular pools, which could be tested in the laboratory.

Biogeochemical cycles in the ocean are strongly affected by the elemental stoichiometry (C:N:P) of phytoplankton, which largely reflects their macromolecular content. A greater understanding of how this macromolecular content varies among phytoplankton taxa and with resource limitation may strengthen physiological and biogeochemical modeling efforts. We determined the macromolecular basis (protein, carbohydrate, lipid, nucleic acids, pigments) of C:N:P in diatoms and prasinophytes, two globally important phytoplankton taxa, in response to N starvation. Despite their differing cell sizes and evolutionary histories, the relative decline in protein during N starvation was similar in all four species studied and largely determined variations in N content. The accumulation of carbohydrate and lipid dominated the increase in C content and C:N in all species during N starvation, but these processes differed greatly between diatoms and prasinophytes. Diatoms displayed far greater accumulation of carbohydrate with N starvation, possibly due to their greater cell size and storage capacity, resulting in larger increases in C content and C:N. In contrast, the prasinophytes had smaller increases in C and C:N that were largely driven by lipid accumulation. Variation in C:P and N:P was species-specific and mainly determined by residual P pools, which likely represent intracellular storage of inorganic P and accounted for the majority of cellular P in all species throughout N starvation. Our findings indicate that carbohydrate and lipid accumulation may play a key role in determining the environmental and taxonomic variability in phytoplankton C:N. This quantitative assessment of macromolecular and elemental content spanning several marine phytoplankton species can be used to develop physiological models for ecological and biogeochemical applications., Gordon and Betty Moore Foundation (Grant GBMF3378)

The deep-ocean carbonate ion concentration impacts the fraction of the marine calcium carbonate production that is buried in sediments. This gives rise to the carbonate compensation feedback, which is thought to restore the deep-ocean carbonate ion concentration on multimillennial timescales. We formulate an analytical framework to investigate the impact of carbonate compensation under various changes in the carbon cycle relevant for anthropogenic change and glacial cycles. Using this framework, we show that carbonate compensation amplifies by 15–20% changes in atmospheric CO[subscript 2] resulting from a redistribution of carbon between the atmosphere and ocean (e.g., due to changes in temperature, salinity, or nutrient utilization). A counterintuitive result emerges when the impact of organic matter burial in the ocean is examined. The organic matter burial first leads to a slight decrease in atmospheric CO[subscript 2] and an increase in the deep-ocean carbonate ion concentration. Subsequently, enhanced calcium carbonate burial leads to outgassing of carbon from the ocean to the atmosphere, which is quantified by our framework. Results from simulations with a multibox model including the minor acids and bases important for the ocean-atmosphere exchange of carbon are consistent with our analytical predictions. We discuss the potential role of carbonate compensation in glacial-interglacial cycles as an example of how our theoretical framework may be applied., Gordon and Betty Moore Foundation (Grant 3778), National Science Foundation (U.S.) (OCE-1536515), Simons Foundation (SCOPE Award 329108)

We develop and extend a theoretical framework to analyze the impacts of changes in temperature and alkalinity on the ocean-atmosphere carbon partitioning. When investigating the impact of temperature, we assume that there is no change in the global ocean alkalinity. This idealized situation is probably most relevant on intermediate timescales of hundreds to thousands of years. Our results show that atmospheric pCO₂ depends approximately exponentially on the average ocean temperature, since the chemical equilibria involved have an exponential (Arrhenius-type) dependence. The dependence of pCO₂ on alkalinity is more complicated, and our theory suggests several regimes. The current ocean-atmosphere system appears to have an exponential dependence of pCO₂ on global mean ocean alkalinity, but at slightly higher alkalinities, the dependence becomes a power law. We perform experiments with a numerical physical-biogeochemical model to test the validity of our analytical theory in a more complex, ocean-like system: in general, the numerical results support the analytical inferences.

Numerical studies have indicated that the steady-state ocean-atmosphere partitioning of carbon will change profoundly as emissions continue. In particular, the globally averaged Revelle buffer factor will first increase and then decrease at higher emissions. Furthermore, atmospheric carbon will initially grow exponentially with emission size, after which it will depend linearly on emissions at higher emission totals. In this article, we explain this behavior by means of an analytical theory based on simple carbonate chemistry. A cornerstone of the theory is a newly defined dimensionless factor, O. We show that the qualitative changes are connected with different regimes in ocean chemistry: if the air-sea partitioning of carbon is determined by the carbonate ion, then the Revelle factor increases with emissions, whereas the buffer factor decreases with emission size, when dissolved carbon dioxide determines the partitioning. Currently, the ocean carbonate chemistry is dominated by the carbonate ion response, but at high total emissions, the response of dissolved carbon dioxide takes on this role.