| Literature DB >> 28262764 |
H L O McClelland1,2, J Bruggeman3, M Hermoso1,4, R E M Rickaby1.
Abstract
Calcite microfossils are widely used to study climate and oceanography in Earth's geological past. Coccoliths, readily preserved calcite plates produced by a group of single-celled surface-ocean dwelling algae called coccolithophores, have formed a significant fraction of marine sediments since the Late Triassic. However, unlike the shells of foraminifera, their zooplankton counterparts, coccoliths remain underused in palaeo-reconstructions. Precipitated in an intracellular chemical and isotopic microenvironment, coccolith calcite exhibits large and enigmatic departures from the isotopic composition of abiogenic calcite, known as vital effects. Here we show that the calcification to carbon fixation ratio determines whether coccolith calcite is isotopically heavier or lighter than abiogenic calcite, and that the size of the deviation is determined by the degree of carbon utilization. We discuss the theoretical potential for, and current limitations of, coccolith-based CO2 paleobarometry, that may eventually facilitate use of the ubiquitous and geologically extensive sedimentary archive.Entities:
Year: 2017 PMID: 28262764 PMCID: PMC5343501 DOI: 10.1038/ncomms14511
Source DB: PubMed Journal: Nat Commun ISSN: 2041-1723 Impact factor: 14.919
Assumptions and conclusions of significant recent works modelling carbon fluxes in single-celled phytoplankton.
| Holtz | 4 compartments (PY=pyrenoid, CP=chloroplast, CV=coccolith vesicle, CY=cytosol) | |
| Carbonate chemistry consists of | Intracellular pH gradients allow concentration of CO2 around RuBisCO without up-gradient movement of carbon. | |
| Hypothesized Ca2+/ | pHs: PY=5.0, CY=7.0, CP=8.0, CV=8.3–8.6 | |
| Hypothesized upregulation of | A net efflux of CO2 is not necessary to remove δ13C from cell | |
| Passive CO2 and | ||
| CA assumed in CP and PY but not in CY and CV | ||
| Isotope model consists of 2 compartments (CY and CP) and does not consider isotopes of calcite. | ||
| Membrane permeabilities to CO2 and | ||
| Bolton & Stoll, | 3 compartments (CP, CV and CY) | |
| Carbonate chemistry consists of | This effect is greatest in large cells. | |
| Difference in vital effects (δ13C calcite—δ13Cmedium) between small and large cells greatest at low [CO2] | ||
| Passive CO2 fluxes. | ||
| Membrane permeabilities and CA activities assumed from Hopkinson | ||
| Hopkinson | 1, 2 & 3 compartments (PY, CP, CY) | Membranes are highly permeable to CO2 (1.5 × 10−4–5.6 × 10−4 m s−1) |
| Carbonate chemistry consists of | Membranes are highly impermeable to | |
| Used 18O labelled DIC to track temporal evolution of carbonate system. | δ13C org is a function of passive diffusion of CO2, active movement of | |
| Passive CO2 fluxes. | ||
| Passive and active | ||
| Schulz | 2 compartments (CP and CY) | Carbon concentrating mechanism relies upon active (ATP driven) uptake of CO2 and |
| Carbonate chemistry consists of | Reduction in | |
| Active uptake of | ||
| Passive CO2 fluxes (membrane permeability to CO2=1.8 × 10−5 from | ||
| No efflux of HCO3 − | ||
| Cassar | 2 compartments | |
| Active and diffusive uptake of CO2 | ||
| No | ||
| Inferred fluxes based on an energy minimization approach. | ||
| Keller & Morel, | 1 compartment | Downward curvature of |
| No | ||
| Active | ||
For earlier work and the evolving appreciation of the importance of cell size, shape and growth rate see Laws et al.15 and references therein.
Figure 1Cellular compartmental configuration and fluxes as modelled.
Chemical and isotopic equilibrium is assumed in the external medium, but neither is assumed inside the cell. Labelling of fluxes and compartments follows the convention of Hopkinson et al.46 and Bolton and Stoll (ref. 2). Nomenclature is as follows: C, B refer to Carbon dioxide (CO2) and Bicarbonate () respectively. Subscripts e, i, x and v refer to compartments: external, cytosol, choroplast and coccolith vesicle respectively (NB: subscript cell refers to outer cell membrane, whilst subscript i refers to cytosol. Vi=Vcell−Vx−Vv). FΘab represents the flux of carbon species Θ, from compartment a to compartment b in units of mols−1. FΘΦa represents the rate of conversion of carbon species Θ, to carbon species Φ, in compartment a, in units of mols−1. Θa represents the concentration of carbon species, Θ, in compartment a in units of molm−3. PΘa represents the permeability of compartment a membrane to carbon species Θ in units of ms−1. Va, SAa represent the volume and surface area of compartment, a in units of m3 and m2 respectively. fa, sa represents the scale and shape factor of compartment a, for inferring Va and SAa ([Dimensionless]). See ‘Methods' section for full model derivation and parameter values.
Figure 2Model output.
Model output across the experimental range of CO2, with empirical data superimposed. The black horizontal dashed line shows the expected composition of abiogenic calcite. Universal constants used to generate model output are constrained by the points outlined in bold, here re-sampled 1,000 times from distributions defined by the associated analytical uncertainties. The data from this study also include additional G. oceanica data (calcite only; green filled circles) and organic carbon isotopic compositions for C. pelagicus from samples from a previous study9. See Supplementary Data 1 for values. Additional literature data are from dilute batch experiments manipulated by varying DIC9 (calcite carbon isotopic compositions only: C. leptoporus—dark blue upwards triangles; C. pelagicus—blue squares; E. huxleyi—yellow downwards triangles; and P. placolithoides—orange diamonds), and by varying pH (ref. 75; E. huxleyi—organic carbon isotopic compositions only: small yellow filled circles). Further data are superimposed in Supplementary Fig. 3. Data points are all the average of two replicates, with the ends of bars representing the value of each replicate. Solid lines and shaded envelopes represent respectively the mean and standard deviation of isotopic compositions predicted by the model for the 1,000 repeated calibrations. Values for compartmental pH are taken from published measurements33. Different species are represented by a representative set of parameters, which for ease of illustration are held constant with varying [CO2]. Representative values are taken from across a range of sources in the literature and from our own unpublished data (cell radius, division rate, PIC:POC are as follows: E. huxleyi – 2.3 μm, 1 day−1, 0.5; G. oceanica - 3.5 μm, 1 day−1, 1.1; C. pelagicus – 8 μm, 0.9 day−1, 1.2; C. leptoporus – 6 μm, 0.65 day−1, 2.2; and P. placolithoides – 7 μm, 0.8 day−1, 0.3). Strong co-variance between cell size or growth rate with CO2 would not be well represented in this projection. Note: for the pH manipulated model output uptake is enhanced at low CO2, manifest as a more rapid isotopic enrichment at low CO2 (steep yellow model curve). All species curves are a similar shape controlled by a number of trade-offs, and with the point of inflexion and maximum δ13Ccalcite determined by varying combinations of cell size, PIC:POC and growth rate. There are some regions of parameter space that are theoretically possible, but may not be observed in reality due to poor growing conditions. Regions of model space not populated by data should be treated as hypothetical.
Figure 3Effect of cellular utilization and PIC:POC on isotopes.
Summary of model output—isotopic compositions as a function of PIC:POC and of the utilization parameter, τ. τ approximates utilization, and is a dimensionless linear function of growth rate, cell size [DIC], as defined in equation (1). (a) Calcite carbon isotopic compositions depend strongly on PIC:POC—if PIC:POC is high, calcite becomes isotopically light as utilization increases, if PIC:POC is low, calcite becomes isotopically heavy as utilization increases. (b) The carbon isotopic composition of organic matter is largely independent of PIC:POC, and is a strong function of the utilization parameter.
Figure 4Summary of causes of vital effects.
Summary of causes of carbon isotope vital effects in coccolith calcite. (a) Coccolithophore cell with isotopically depleted POC produced in the chloroplast and isotopically enriched PIC produced in the coccolith vesicle. (b) Schematic representation of the effect of three dominant processes affecting the isotopic composition of calcite (δ13Ccalcite). (c) Net result of carbon isotopic vital effects in coccolith calcite. At low τ (that is, high CO2, low cell size or low growth rate), the flux of carbon into the cell far exceeds intracellular processes, and all species plateau at the same value (I). The value of this plateau is heavier than that of the carbon entering the cell due to intracellular interconversion of carbon species and preferential loss of light carbon dioxide. Low PIC:POC: for a cell of low PIC:POC, as τ increases (I–II), the flux of isotopically heavy carbon leaving the chloroplast (depleted in light carbon by carbon fixation catalysed by RuBisCO) influences the isotopic composition of the coccolith vesicle. As τ increases further (II–III), the flux of carbon from the chloroplast, although isotopically increasingly heavy, tends towards zero, and Rayleigh-type fractionation within the coccolith vesicle itself (which removes isotopically heavy carbon) takes over, driving the pool to light values. High PIC:POC: For a cell of high PIC:POC, as τ increases (I–IV) the Rayleigh-type fractionation due to calcite precipitation drives the isotopic composition of the coccolith vesicle to light values. The effect of heavy carbon leaking from the chloroplast is obscured. Across all cells of all PIC:POC values, the trends in vital effects are moderated by the biological up-regulation of HCO3− transport proteins, which increases overall permeability to carbon and increases the and isotopic composition of carbon entering the cell with increasing τ, and which dampens the Rayleigh fractionation-type effects when τ is high.
Figure 5Concept for interpretation of sedimentary data.
(a) Once calibrated, the model provides values of isotopic compositions of organic matter and of calcite (δ13Corg and δ13Ccalcite respectively) as outputs, given a number of input parameters (δ13CDIC, r, μ, [CO2] and PIC:POC). δ13CDIC can be estimated from foraminifera. r, μ and [CO2] form a single compound variable for each size fraction (semi-transparent ovals), τ (equation (1)), which cannot be deconvolved without additional evidence. The model can be inverted and used to iteratively search parameter space for the values of τ and PIC:POC that minimize the misfit between model-predicted and measured isotopic compositions. r can be estimated from coccolith size. Boxes without a division denote a shared variable between measured isotopic compositions. O is only weakly dependent on PIC:POC so to a first approximation, τ may be estimated from O alone (as shown by shaded box). The assumption included in [CO2] concerns the ambient concentration of , but the model output is highly insensitive to this assumption. (b–d) Model output describing theoretical carbon isotopic compositions of inorganic (b) and organic (c) material relative to δ13CDIC, and δ13Ccalcite—δ13Corg (d) over a range of PIC:POC and τ. The double headed arrows point to the difference between a cell with a PIC:POC typical of E. huxleyi (left) and a typical C. pelagicus (right); the number of δ13Ccalcite contours crossed decreases with decreasing τ.
Parameters from the model, their definitions, derivation and units.
| | External CO2 and | Measured [DIC] and pH | Independent variable | mol m−3 |
| | δ13C of external CO2 & | Calculated from | Independent variable | ‰PDB |
| | Average carbon fixation rate | Division rate, mol C org per cell | Measured variable | mol s−1 |
| | Average calcification rate | Division rate, mol calcite per cell | Measured variable | mol s−1 |
| PIC:POC | Particulate inorganic to particulate organic carbon ratio of biomass | Measured variable | Molar ratio | |
| TCR | Total carbon assimilation rate | Measured variable | mol s−1 | |
| δ | δ13C of organic material | Measured directly | Measured variable | ‰PDB |
| δ | δ13C of calcite | Measured directly | Measured variable | ‰PDB |
| | Cell radius | Measured directly | Measured variable | m |
| | Cell surface area and volume | Functions of | Measured variable | m2&m3 |
| Rho | Cellular organic carbon density | This study, consistent with Reinfelder | 20 × 10−15 | mol m−3 |
| | Carbon isotopic fractionation during calcification | Zeebe and Wolf-Gladrow | +1 (from | ‰PDB |
| Kinetic carbon isotopic fractionation factors | Zeebe and Wolf-Gladrow | −13, −22, −11, −20, −1, −10 | ‰PDB | |
| | Kinetic rate constants | Calculated from Zeebe and Wolf-Gladrow | T and S dependent. | various—dependent on reaction |
| | Ion product of water | Calculated from (ref. | T and S dependent. | mol2 m−6 |
| | 1st acidity constant of carbonic acid | Calculated from Lueker | T and S dependent. | mol m−3 |
| | Specific activity of CA for hydration reaction | Inferred from bovine erythrocyte CA | 2.7 × 107 | M−1 s−1 |
| | pH in compartments i, x & v. | ref. | 7.0, 7.9 & 7.1. | free scale |
| | Scale factor for compartments x & v | TEM images | 1.1 & 0.6 | dimensionless |
| | Shape factor for compartments x & y | TEM images | 6 & 4 | dimensionless |
| | Effective carbon isotopic fractionation during C-fixation by Rubisco | Fitted parameter | −14.3 | ‰PDB |
| | Cell membrane permeability to CO2 | Fitted parameter | 9.3 × 10−4 | ms−1 |
| | Cell membrane permeability to HCO3− | Fitted parameter | 7.8 × 10−8, 5.1 × 10−6 | ms−1 |
| | Effective concentration ratio of the coported ion at the cell membrane | Fitted parameter | 2.7 | ratio |
| [CA]i, [CA]x, [CA]v | [CA] in compartments i, x & v. | Inferred | 0.1–1 | mol m−3 |
See supplementary information for values for measured parameters generated in this study.