A niche comparison of Emiliania huxleyi and Gephyrocapsa oceanica and potential effects of climate change

Coccolithophore responses to changes in carbonate chemistry speciation such as CO2 and H are highly modulated by light intensity and temperature. Here we fit an analytical equation, accounting for simultaneous changes in carbonate chemistry speciation, light and temperature, to published and original data for Emiliania huxleyi, and compare the projections with those for Gephyrocapsa oceanica. Based on our analysis, the two most abundant coccolithophores in today’s oceans appear to be adapted for a similar fundamental light niche but slightly different ones for temperature and CO2, with E. huxleyi having 5 a tolerance to lower temperatures and higher CO2 levels than G. oceanica. Based on growth rates, a dominance of E. huxleyi over G. oceanica is projected below temperatures of 22◦C at current atmospheric CO2 levels. This is similar to a global surface sediment compilation of E. huxleyi and G. oceanica coccolith abundances suggesting temperature dependent dominance shifts. For a future RCP 8.5 climate change scenario (1000 μatm f CO2 and + 4.8◦C) we project a niche contraction for G. oceanica to regions of even higher temperatures. Finally, we compare satellite derived particulate inorganic carbon estimates 10 in the surface ocean with a recently proposed metric for potential coccolithophore success on the community level i.e. the temperature, light and carbonate chemistry dependent CaCO3 production potential (CCPP). Excluding the Antarctic province from the analysis we found a good correlation between CCPP and satellite derived PIC in the other regions with an R of 0.73 for Austral winter/Boreal summer and 0.85 for Austral summer/Boreal winter.


Introduction
Since the Industrial Revolution in the late 18th century, burning of fossil fuels, as well as wide scale deforestation have contributed to significant increases in atmospheric carbon dioxide, CO 2 (IPCC, 2013a).Depending upon the decisions in the next few decades, atmospheric CO 2 levels are projected to reach between 420 µatm (RCP2.6 scenario) and 985 µatm (RCP8.5 scenario) by 2100 (Caldeira and Wickett, 2005;Orr et al., 2005;IPCC, 2013a).To date approximately one third of the anthropogenic carbon emissions have been absorbed by the world's oceans (Sabine et al., 2004).As atmospheric partial pressures of CO 2 (pCO 2 ) increase, CO 2 concentrations in the surface ocean also increase, resulting in increased bicarbonate and hydrogen ions but also in decreased carbonate ion concentrations and pH (Doney et al., 2009;Schulz et al., 2009).These changes, often termed ocean carbonation and acidification, can have both positive and negative effects for different phytoplankton species and 2 ml of sample was analysed on a Marianda AIRICA system by acidification with 10% phosphoric acid to convert all DIC into CO 2 , followed by extraction with N 2 (5.0) and concomitant CO 2 analysis with an IR detector (LI-COR LI-7000 CO 2 /H 2 O analyser).Both TA and DIC measurements were calibrated against Certified Reference Materials (batches 139,141,150) following Dickson (2010).Initial DIC and TA concentrations were estimated by adding measured total particulate carbon build-up during incubations to measured final DIC, and double the particulate inorganic carbon build-up during incubations to measured final TA concentrations.Carbonate chemistry speciation for each treatment was calculated from mean TA, mean DIC, measured temperature, salinity and [PO 3−  4 ] using the program CO2SYS (Lewis et al., 1998), the dissociation constants for carbonic acid determined by Lueker et al. (2000), K S for sulphuric acid determined by Dickson et al. (1990) and K B for boric acid following Uppström (1974).

Particulate organic and inorganic carbon
Sampling started approximately two hours after the onset of the light period and lasted no longer than 3 hours.Duplicate samples for total and particulate organic carbon (TPC and POC) were filtered (-200 mbar) onto GF/F filters (Whatmann, precombusted at 500 • C for 4 hours) and stored in glass petri-dishes (pre-combusted at 500 • C for 4 hours) at -20 • C until analysis.
POC filters were placed in a desiccator above fuming (37%) HCl for 2 hours to remove all particulate inorganic carbon (PIC).
All filters were dried overnight at 60 • C, and analysed for carbon content and corresponding isotopic signature according to Sharp (1974) on an elemental analyser (Flash EA, Thermo Fisher) coupled to an isotope ratio mass spectrometer (IRMS, Delta V plus, Thermo Fisher).Particulate inorganic carbon (PIC) was calculated by subtracting measured POC from TPC.

Growth
Cell densities were measured every 3-4 days after the commencement of the experiment using a flow cytometer (Becton Dickinson FACSCalibur) on high flow settings (58 µl/minute) for two minutes per measurement.Living cells were detected by their red autofluorescence in relation to their orange fluorescence in scatter plots (FL3 vs. FL2).At some extreme CO 2 levels there was an initial lag phase and therefore growth rates were calculated from densities only during the exponential part of the growth phase.After disregarding lag phase measurements, the majority of treatments had only two to three data-points in the exponential phase.As a result, specific growth rates were calculated as: where C f represents cell densities at time of sampling, C 0 represents cell densities at the beginning of the exponential growth phase, and d is the duration of the exponential phase in days.Calcification and photosynthetic rates were calculated by multiplying cellular PIC and POC quotas with respective growth rates.

Fitting procedure
Coccolithophore metabolic rate (MR) responses of growth, calcification and photosynthetic carbon fixation to combined changes in temperature, light and carbonate chemistry speciation can be described as follows (Gafar et al., 2018).
Data from this study (Tables S1, S2) and Sett et al. (2014) were fitted to Eq. ( 2) using the non-linear regression fit procedure nlinfit in MATLAB (the Mathworks).The reason only these studies were chosen, from the multitude of E. huxleyi datasets, is because 1) they use the same strain (PML B92/11), 2) they have the same nutrient conditions and 3) they use the same carbonate chemistry manipulation methods.Nevertheless, the two chosen studies provided light (six levels) and temperature (three levels) interactions over a broad carbonate chemistry speciation range.It is noted that in both studies the carbonate chemistry system is coupled, meaning that a change in CO 2 results in a change in pH.This method reflects the changes in carbonate chemistry speciation due to ongoing ocean acidification (Bach et al., 2011(Bach et al., , 2013)).However, some studies have examined the effects of decoupled carbonate chemistry where CO 2 is changed at a constant pH.This approach is used to tease apart the independent effects of H + and CO 2 on physiological responses (see Bach et al. 2013).While Eq. ( 2) can also be used to explain responses under decoupled carbonate chemistry conditions (see Gafar et al. 2018 for details), the fit obtained here is only valid for coupled CO 2 /pH changes as no data from decoupled experiments (i.e.Bach et al. 2011) has been used.The reason for this being that Bach et al. (2011) does not contain data of temperature, light and carbonate chemistry interactions.

Temperature and light transformations
To reduce skew and to better accommodate certain features (i.e.light and temperature inhibition and limitation) both temperature and light data were transformed.Light data was square root transformed with light (I) = √ PFD, where PFD is the photon flux density (µmol photons m −2 s −1 ) of an incubation.To accommodate for known temperature inhibition below 2 • C and above 30 • C (Rhodes et al., 1995;van Rijssel and Gieskes, 2002;Helm et al., 2007;Zhang et al., 2014) at a much narrower experimental range (10-20 • C), the upper and lower limits for E. huxleyi growth were added into the equation with a general transform of T = (T t − 2) × (30 − T t ), where T t is the temperature of an incubation.To accurately express the onset of high temperature inhibition, the transform was further modified with a square root transform to give T = (T t − 2) × (30 − T t ).This transform produces reasonable results when compared to the Eppley temperature envelope curve and the Norberg model (see Gafar et al. 2018).
2.8 Physiological rate response parameter estimations to changes in carbonate chemistry, temperature and light Equation ( 2) was used to assess the combined effects of carbonate chemistry, temperature and light on growth, calcification and photosynthetic carbon fixation rates, with a focus on general physiological features, such as limitation and inhibition, as well as how much variability could be explained.For growth, photosynthetic carbon fixation and calcification rates optimum CO 2 concentrations for maximum production rates (V max ) and half saturation values were calculated at each experimental light and temperature level.K 1 2 values consisted of: sat which is the CO 2 concentration (at certain T and I) at which rates are saturated to half the maximum, and inhib, which is the CO 2 concentration (at certain T and I) at which high proton concentrations reduce physiological rates to half the maximum.Fitting results (R 2 , fit coefficients, p-values, F-values and degrees of freedom), as well as V max , K 1 2 and CO 2 optima are presented in Tables 1, 2 and 3. Species specific differences in response to changing carbonate chemistry, temperature and light were assessed by comparing the above fit to that recently produced for Gephyrocapsa oceanica (Gafar et al., 2018).

Niche comparison
To examine the potential of ongoing ocean change to influence realised niches and hence individual success, ranges for light and temperature where both Emiliania huxleyi and Gephyrocapsa oceanica might be expected to co-exist were selected (i.e.50-1000 µmol photons m −2 s −1 and 8-30 • C).E. huxleyi and G. oceanica were chosen for comparison as they are currently the only two species with response data over a range of carbonate chemistry, temperature and light conditions.Growth rates were selected as the point of comparison because they can be used as a measure of relative abundance and therefore dominance of a species, and because growth rates largely control carbon fixation rates.To assess competitive ability, and the potential realised niche, the difference in growth rates between the species was visualised using contour plots.
The effect of temperature on growth rates and hence potential dominance was then compared to phytoplankton community data from global surface sediment samples above the lysocline (McIntyre and Bé, 1967;Chen and Shieh, 1982;Roth and Coulbourn, 1982;Knappertsbusch, 1993;Andruleit and Rogalla, 2002;Boeckel et al., 2006;Fernando et al., 2007;Saavedra-Pellitero et al., 2014).As E. huxleyi and G. oceanica have similar average numbers of coccoliths per cells, 28 and 21, respectively (Samtleben and Schroder, 1992;Knappertsbusch, 1993;Baumann et al., 2000;Boeckel and Baumann, 2008;Patil et al., 2014), the abundance ratio of E. huxleyi to G. oceanica coccoliths was here assumed to be a suitable proxy for species dominance.It is noted that E. huxleyi has been found to produce excess coccoliths towards the end of blooms when inorganic nutrients become limiting for cellular growth (Balch et al., 1992;Holligan et al., 1993;Paasche, 1998), which would result in an over-estimate of E. huxleyi dominance in our study.Nevertheless, given that the coccoliths ratio varies orders of magnitude in modern marine sediments, none of our general conclusions should be affected.Temperature for each sampling site was retrieved from the NOAA 1°resolution annual temperature climatology (Boyer et al., 2013).

Global calcium carbonate production potential
While our fit equation has previously explained variability in lab experiments quite well (Gafar et al., 2018), natural systems are much more complex, with the interactions of dozens of variables including temperature, light, nutrients, predation and competition all influencing productivity (Behrenfeld, 2014).As such we wanted to examine how our, relatively simple, equation projections of productivity compared to coccolithophorid productivity patterns observed in natural systems.Productivity can be defined in a few ways, traditionally, changes in cellular calcification rates, in response to ocean change, have been used as indicator for the potential success of coccolithophores in the future ocean.However, the exponential nature of phytoplankton growth amplifies even small differences in cellular growth rates, when applied on the community level.For instance, a phytoplankton bloom occurring over one week at a growth rate of 1.0 d −1 and a starting cell density of 50 cells ml −1 would lead to a peak density of about 55,000 cells ml −1 .This is in stark contrast to conditions where growth is only 10% lower as peak cell densities, and hence biomass and PIC standing stock, will only be half.
Recently, a new metric was proposed, the CaCO 3 production potential (CCPP) which 1) should be a better representation of potential coccolithophore success on the community level and 2) can be tested against modern observations of surface ocean CaCO 3 distribution.CCPP is defined as the amount of CaCO 3 produced within a week by a coccolithophore community (with a set starting cell count) for a certain environmental condition, calculated from Eq. (2) derived growth rates and inorganic carbon quotas.Inorganic carbon quotas are calculated as the quotient of calcification and growth rates.As CCPP is calculated from calcification and growth rates, it accounts for the individual effects of temperature, light and carbonate chemistry on growth rates and on carbon production.It was for these reasons that CCPP was the metric chosen for comparison.
Provided values for temperature, light, substrate (CO 2 + HCO − 3 ) and hydrogen ion concentrations (H) for the surface mixed layer, coccolithophore CaCO 3 production potential can be projected for the world oceans.CCPP can then be cautiously evaluated against and compared to satellite derived global particulate inorganic carbon concentration estimates (PIC s ).As inorganic nutrients are a critical factor influencing phytoplankton abundance, and especially bloom formation, in the ocean (Browning et al., 2017) nitrate concentrations were also included in the analysis (for details see below).As a result, climatological datasets consisted of, World Ocean Atlas 2013 v2 (WOA) nitrate concentrations at 1°resolution (Boyer et al., 2013); SeaWiFS mixed layer depth (MLD 2°resolution) from de Boyer Montégut et al. (2004) Hydrogen ion concentrations were calculated as 10 −pH , CO 2 , after conversion of pCO 2 to f CO 2 as described in CO2SYS (Lewis et al., 1998), as [f CO 2 ]*K0 (with K0 being the temperature and salinity dependent Henry's constant), HCO − 3 as ), and substrate (S) as the sum of CO 2 and HCO − 3 concentrations.Mean mixed layer nitrate concentrations were calculated by determining concentrations for each depth and averaging from surface to the mixed layer depth for each grid cell.Mean mixed layer irradiance was calculated in one meter depth increments for each grid cell as where I is the average PAR (µmol photons m −2 s −1 ), k d is the attenuation coefficient (m −1 ), MLD denotes the mixed layer depth in meters, and I 0 is the incident PAR at the surface (µmol photons m −2 s −1 ).
Global coverage of oceanic nutrient concentrations are often limited to only a few macro-nutrients (nitrate, silicate, phosphate).However, concentrations of these nutrients are often strongly correlated (e.g.phosphate and nitrate in Boyer et al. 2013).
To ensure there was sufficient nutrients to support the level of production estimated by CCPP, we opted to use a single nutrient, i.e. nitrate, in combination with a simple scaling metric.First it was assumed that CaCO 3 is produced with a PIC:PON ratio of 6.625 for E. huxleyi and 13.25 for G. oceanica (based on Redfield proportions and PIC:POC ratios of one and two respectively).Hence, maximum CaCO 3 production potential (CCPP max ) in a grid cell would be 6.625 and 13.25 times the nitrate concentration for E. huxleyi and G. oceanica respectively.If estimated CCPP for a cell exceeded CCPP max , and therefore the nitrate required to produce that much PIC, then it was replaced with the CCPP max value.If CCPP was less than C max then no further changes were applied.
To ensure that mean global CCPP and mean global PIC s would be of the same magnitude, starting cell counts for CCPP calculations were set at 1 ml −1 for E. huxleyi alone, 0.25 ml −1 for G. oceanica alone and 0.25 ml −1 for each species when combined.To allow comparison, CCPP and PIC s were both converted to units of µmol PIC L −1 .All data were then averaged for Austral summer/Boreal winter (December-February) and Austral winter/Boreal summer (June-August).Austral summer/Boreal winter and Austral winter/Boreal summer were chosen as they provide prominent differences between minimum and maximum PIC, while spring and autumn do not.A direct comparison between PIC s and CCPP was achieved by splitting

Responses to changing carbonate chemistry: CO 2 and H +
All rates had a similar optimum curve response to the broad changes in carbonate chemistry speciation (Figure 1) regardless of temperature and light intensities.Growth, calcification and photosynthetic carbon fixation rates required similar CO 2 concentrations to stimulate rates to half the maximum, K 1 2 CO 2 sat (Table 2, Table 3).Optimum CO 2 concentrations for calcification were slightly lower than for photosynthesis or growth (Table 2, Table 3).At CO 2 concentrations beyond the optimum, a much higher sensitivity to increasing [H + ], i.e.K 1 2 CO 2 inhib was observed for calcification than for photosynthesis or growth rates (Tables 2, 3 and Figures 1, 2).

Responses to temperature
The effect of temperature on rates was dependent upon CO 2 , with the greatest effect observed at optimum CO 2 concentrations (Figure 1).Increasing temperature increased growth rates up to twofold, photosynthetic rates up to 43% and calcification rates up to 52% (Figure 1, Table 2) under optimal CO 2 concentrations.CO 2 half saturation concentrations (K 1 2 CO 2 sat) were insensitive to temperature (Table 2), while CO 2 concentrations for both optimal growth and for inhibition of rates to half the maximum (K 1 2 CO 2 inhib) decreased with increasing temperature for all rates (Table 2).

Responses to light
Light intensities affected all physiological rates, with the greatest effect generally being observed at CO 2 concentrations at or above the optimum (Figure 2).Between 50 and 1200 µmol photons m −2 s −1 , calcification rates doubled, photosynthetic rates tripled and growth rates increased around 36% (Figure 2, Table 3).Both optimum CO 2 and CO 2 concentrations at which rates were half saturated (K 1 2 CO 2 sat) increased slightly with increasing light intensity (Table 3).CO 2 concentrations required to inhibit rates to half of maximum (K 1 2 CO 2 inhib) for calcification and photosynthesis increased with increasing light intensity, while those for growth increased from 50-150 µmol photons m −2 s −1 before decreasing with further increases in light (Table 3).which they then declined again.This pattern in growth, photosynthetic carbon fixation and calcification rates has been observed previously for several coccolithophore species (Sett et al., 2014;Bach et al., 2015).The availability of substrate (CO 2 and HCO − 3 ) was suggested as the factor influencing the increase in rates on the left side of the optimum, while the proton concentration ([H + ]) was the factor most likely driving declines to the right side of the optimum (Bach et al., 2011(Bach et al., , 2015)).
Of the two species, E. huxleyi has a higher CO 2 optimum than G. oceanica (Tables 2 and 3, Gafar et al. 2018) for all rates and under most conditions.This could suggest that E. huxleyi has a slightly higher substrate requirement than G. oceanica.
However, considering that G. oceanica has both a larger cell size and higher carbon quotas per cell the opposite would be expected (Sett et al., 2014;Bach et al., 2015).An explanation for achieving maximum rates only at higher CO 2 concentrations in E. huxleyi, in comparison to G. oceanica despite a lower inorganic carbon demand, might be a less efficient or capable carbon uptake/ concentrating mechanism.Alternatively, a decreased sensitivity to high [H + ] in E. huxleyi, in comparison to G. oceanica (see below), would lead to a shift in the optimum towards higher CO 2 as well and might be a more likely explanation.
Of the three rates, calcification in E. huxleyi had both the lowest CO 2 requirement and the highest sensitivity to increasing [H + ] (Tables 3 and 2).This is a pattern previously observed for G. oceanica under varying temperature and light conditions (Gafar et al. 2018, See also Table S3).As evidenced by higher K 1 oceanica depending on temperature) (Tables 2, 3, S3, Gafar et al. 2018).This also supports earlier results in a model analysis by Bach et al. (2015) where E. huxleyi reacted less sensitively to higher CO 2 (and [H + ]) than G. oceanica.
A lower sensitivity of rates to changes in carbonate chemistry speciation, in particular calcification rates, could be explained by the lower degree of calcification in E. huxleyi (PIC:POC ratios 0.24-1.38)when compared to G. oceanica (PIC:POC ratios 0.82-2.17)(Sett et al., 2014).Higher rates of calcification result in greater production of intracellular H + (Ca 2+ + HCO − 3 CaCO 3 + H + ), potentially decreasing [CO 2− 3 ] in the coccolith producing vesicle and hence the CaCO 3 saturation state (Bach et al., 2015).Furthermore, increased [H + ] has been found to result in declines in [HCO − 3 ] uptake, the primary carbon source for calcification (Kottmeier et al., 2016).

Responses to temperature
Temperature was observed to have few modulating effects on CO 2 responses in E. huxleyi.Changes in temperature produced little (<11 µmol kg −1 ) change in CO 2 optima and substrate saturation (K 1 2 CO 2 sat) levels, at least within the measured range (Figure 1, Table 2).Similar results were observed for G. oceanica (Gafar et al., 2018).This indicates that while overall rates change, carbon uptake mechanisms appear to scale to maintain internal substrate concentrations and thus cellular requirements regardless of temperature conditions.In contrast, the inhibition of rates by rising [H + ] i.e.K 1 2 CO 2 inhib was more sensitive to temperature.The CO 2 concentration at which rates were reduced to half the maximum increased with decreasing temperatures (Table 2).These results were also observed for G. oceanica which had a lower sensitivity to increasing [H + ] at the lowest tested temperature (Gafar et al., 2018).This also agrees with De Bodt et al. ( 2010) in which a greater decline in calcification rate was observed with increasing CO 2 at 18 • C than at 13 • C.These results indicate that, at least some, coccolithophores may be less sensitive to high CO 2 levels at lower temperatures.As a result, both G. oceanica and E. huxleyi may become more vulnerable to the negative effects of ocean acidification as ocean temperatures increase due to climate change.

Responses to light
The sensitivity of all rates in E. huxleyi to changing carbonate chemistry, in particular increasing [H + ], was clearly modulated by light intensity (Figure 2), agreeing with earlier findings (Zondervan et al., 2002;Feng et al., 2008;Gao et al., 2009;Rokitta and Rost, 2012;Zhang et al., 2015).CO 2 half-saturation (K 1 2 CO 2 sat) for all rates were insensitive to increasing light intensities (Table S3).This agrees with results for G. oceanica which also displayed little change in CO 2 half-saturation concentrations with increasing light (Table S3).Increasing light intensity induced increases in CO 2 optima in all rates, however these changes were small (<10 µmol kg −1 ) for calcification and growth rates.This contrasts with G. oceanica for which a distinct decrease in optimal CO 2 concentrations for growth rates with increasing light intensities was observed (Table S3).However, G. oceanica projections are based on a dataset with only three CO 2 concentrations (∼16, 31, 45 µmol kg −1 ).As such, it is difficult to determine how robust the estimates of CO 2 optima and half-saturation requirements may be for this species (Zhang et al., 2015).
In E. huxleyi the relationship between H + sensitivity and light intensity was the same for the three rates.Calcification and photosynthetic carbon fixation and growth rates were most sensitive to H + at the lowest (50 µmol photons m −2 s −1 ) and growth rates were also slightly more sensitive at the highest (1200 µmol photons m −2 s −1 ) light intensities (Table 3).This result is in part due to an underestimation of growth rates by the fitting equation under high CO 2 conditions at 50 µmol photons m −2 s −1 light (Figure 2).However, it may be that sub-optimal light intensities add additional stress to the cells resulting in them having less resources with which to handle the stress of increasing high [H + ].Hence rates are lower, but also appear more sensitive to changing carbonate chemistry.These findings agree with findings by Rokitta and Rost (2012) where a diploid E. huxleyi strain became insensitive to the effects of rising CO 2 (380 vs. 1000 µatm) when light intensities were increased from 50 to 300 µmol photons m −2 s −1 .However, this differs to G. oceanica which, with rising light intensities, had no change in sensitivity for calcification rates, a decrease in sensitivity for photosynthesis and an increase in sensitivity for growth rates (Table S3).
Again, although this could be indicative for species specific differences in sensitivity, it may also be a result of the low number of CO 2 treatments used in the light data of G. oceanica (see Zhang et al. 2015).In the future ocean CO 2 , temperature and light availability are all expected to change (Rost and Riebesell, 2004;IPCC, 2013b).Levels of f CO 2 are expected to reach as high as 985 µatm by the end of the century with concomitant rise in global ocean temperature of up to 4.8 • C (RCP8.5 scenario IPCC 2013a, b).Light intensities in the surface ocean are also expected to increase as a result of mixed layer depth shoaling (Rost and Riebesell, 2004).By calculating and comparing growth rates for E. huxleyi and G. oceanica over a range of environmental conditions, it is possible to differentiate between the fundamental (physiological) niche of a species and its potentially realised niche when in competition with others.For this purpose, light, temperature and CO 2 ranges were restricted to those where both species would be expected to co-occur, i.e. 20-1000 µmol photons m −2 s −1 , 8-30 • C and 25-4000 µatm, respectively.The calculated difference in growth rates in response to CO 2 and temperature does not significantly change with light intensity (Figure 3 and 4).It should be noted, however, that light intensity might modify observed growth rate differences for other strains of the same species than used here as they can possess different sensitivities and requirements (i.e.Langer et al. 2009;Müller et al. 2015).

Fundamental niche
Experimentally, E. huxleyi has been found to grow in a range of ∼6 to 2500 µmol photons m −2 s −1 with high light resulting in no inhibition of maximum rates in some strains, and up to 20% reduction in others (Balch et al., 1992;van Bleijswijk et al., 1994;Nielsen, 1995;Nanninga and Tyrrell, 1996;van Rijssel and Gieskes, 2002).In contrast, G. oceanica is more sensitive in a similar experimental range of ∼6-2400 µmol photons m −2 s −1 with maximum rates inhibited by up to 38% at high light intensities (Larsen, 2012).Light intensities below 6 µmol photons m −2 s −1 for E. huxleyi and G. oceanica resulted in no growth for both species (van Bleijswijk et al., 1994;van Rijssel and Gieskes, 2002;Larsen, 2012).So, while G. oceanica is more sensitive to high light, the potential upper light limit for growth in both species is beyond naturally occurring maxima.Within this light range both species show a similar increase in projected absolute growth rates of 0-1.57(d −1 ) for E. huxleyi and 0-1.51 (d −1 ) for G. oceanica (based on figure 4).
E. huxleyi has been successfully cultured at pCO 2 levels between ∼20-5600 µatm, while G. oceanica has been successfully cultured at pCO 2 levels of ∼20-3400 µatm (Sett et al., 2014).Again, the upper tolerance limit for growth in both is not known and well above what is expected for most ocean systems.Responses in projected growth rates with rising CO 2 differ between the two species with G. oceanica rates dropping to 50% of maximum at f CO 2 levels above ∼1760 µatm while E. huxleyi drops to 50% of maximum at ∼5950 µatm.In terms of temperature E. huxleyi has a broader niche of 3-29 • C in comparison to G. oceanica at 10-32 • C. Within this temperature niche both species again show a similar change in absolute growth rates of 0-1.40 (d −1 ) for G. oceanica and 0-1.43 (d −1 ) for E. huxleyi (based on figure 5).
It should be noted however, that although niche ranges and maximum rates are similar for both species, different requirements (K 1 2 sat) and sensitivities (K 1 2 inhib) will lead to different actual rates at a specific environmental condition.This becomes ev- ident when examining the temperature, light and CO 2 niches to find a combination of conditions at which growth rate for each species is at its maximum.For E. huxleyi maximum growth rates of 1.62 (d −1 ) are projected at ∼970 µmol photons m −2 s −1 light, ∼640 µatm CO 2 and 20.2 • C. In contrast, the conditions for optimal growth rates of 1.52 (d −1 ) for G. oceanica are achieved at ∼500 µmol photons m −2 s −1 light, ∼430 µatm CO 2 and 24.4 • C. Differences in sensitivity and therefore performance under certain conditions will influence the potentially realised niche of the species.For example, E. huxleyi is projected to reach higher growth rates than G. oceanica under a broader range of temperature, light and CO 2 conditions (Figures 3, 4 and 5), indicating that this species may be more of a generalist.

Potentially realised niche
Temperature and CO 2 both have substantial effects on the potentially realised niche, of E. huxleyi and G. oceanica (Figures 4   and 5).In contrast, light intensity has very little effect (Figure 3).E. huxleyi appears able to exceed growth rates of G. oceanica at temperatures below 22 • C under most CO 2 and light conditions (Figures 4 and 5).A similar difference in temperature preferences has also been observed in New Zealand isolates of Gephyrocapsa oceanica and Emiliania huxleyi with G. oceanica and E. huxleyi growing between 10-25 • C and 5-25 • C at optimum temperatures of 22 • C and 20 • C, respectively (Rhodes et al., 1995).While these results are based on single strain laboratory experiments, there is evidence that such differences in temperature sensitivity may also hold true in the modern ocean.For example, data gathered from multiple phytoplankton monitoring cruises indicate that while both species are found at higher temperatures, G. oceanica largely vanishes from the assemblage at and Bé, 1967;Eynaud et al., 1999;Hagino et al., 2005).However, phytoplankton monitoring cruises can be seasonally biased and represent a single point in time.
Another way to relate our niche comparison to today's oceans is through surface sediments.Surface sediment samples represent an integrated signal of the composition of a phytoplankton community over time and can therefore be a more suitable proxy of species dominance in a certain location.Global surface sediment data on G oceanica and E. huxleyi coccolith abundance indicates that the dominance of these two species is influenced by temperature, particularly in the Pacific Ocean (Figure 6).Globally the data suggests that dominance switches from E. huxleyi to G. oceanica at temperatures above 25 • C which is similar to our projections.It is noted, however, that in the Atlantic Ocean there appears to be a warm water E. huxleyi strain outcompeting G. oceanica at temperatures above 25 degrees.While both species have a similar upper limit to their fundamental thermal niche (i.e.Rhodes et al. 1995), it would appear that the higher minimum temperature of G. oceanica, combined with its greater tolerance for high temperatures, restricts its realised niche to the upper end of the temperature range (Figures 4 and 6).
CO 2 level also influences the relative growth rates of E. huxleyi and G. oceanica.Under current day levels of ∼400 µatm, E. huxleyi would dominate at temperatures up to 22 • C (Figure 5).However, at higher and lower CO 2 levels, E. huxleyi begins to outgrow G. oceanica at progressively higher temperatures.At extreme CO 2 levels of 25 and 4000 µatm G. oceanica is only projected to reach higher growth rates than E. huxleyi at temperatures above 29 • C (Figure 5).This is also supported by Rhodes et al. (1995) and Bach et al. (2015) which suggest that G. oceanica begin to be inhibited at lower CO 2 (higher H + ) Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-88Manuscript under review for journal Biogeosciences Discussion started: 1 March 2018 c Author(s) 2018.CC BY 4.0 License.than E. huxleyi.So, while growth rates in both species are negatively affected by increasing [H + ], G. oceanica is more sensitive so its rates decrease relative to E. huxleyi for the same change in f CO 2 .However, this sensitivity is partially mitigated by increasing temperatures.For example, under RCP scenario 8.5 temperature and CO 2 levels are expected to increase up to 4.8 • C and 985 µatm, respectively.Under higher temperature conditions alone G. oceanica would be able to outgrow E. huxleyi under a broader range of CO 2 conditions (Figure 5).Meanwhile, under higher CO 2 conditions alone the thermal niche of G.
oceanica would decrease with this species being dominated by E. huxleyi at temperatures up to 26 • C. The combined effect of rising temperature and CO 2 allows G. oceanica to outgrow E. huxleyi under a broader range of CO 2 conditions but a narrower temperature range.As a result, G. oceanica' s niche would be expected to decrease under future ocean conditions.
This comparison only considers E. huxleyi and G. oceanica.However, coccolithophore communities can be made up of dozens of species (McIntyre and Bé, 1967;Winter and Siesser, 1994), all of which are likely to have different preferences for and sensitivities to changes in f CO 2 , temperature and light.Shifts in plankton community structure, as a result of different species and group preferences, in response to environmental change have already been observed in the past (Beaugrand et al., 2013;Rivero-Calle et al., 2015), while simulations also suggest shifts in plankton community under future climate conditions (Dutkiewicz et al., 2015).Species and composition shifts in the coccolithophore communities are likely to alter ocean biogeochemistry with implications for ocean-atmosphere CO 2 partitioning.

Global calcium carbonate production potential
The CaCO 3 production potential (CCPP) is based on cellular CaCO 3 quotas and growth rates calculated for a given set of temperature, light and carbonate chemistry conditions (see section 2.10).Here we test how this measure for productivity compares to estimated surface ocean CaCO 3 content observed by satellite imaging (PIC s ).At this point it is important to remember that CCPP does not account for top-down controls such as grazing or viral attack (Holligan et al., 1993;Wilson et al., 2002;Behrenfeld, 2014), and bottom-up controls such as competition for macro or micro-nutrients (Zondervan, 2007;Browning et al., 2017).Thus, a potential for high CaCO 3 production is not necessarily realised when exposed to different top-down and bottom up pressures.
Calculated CCPP of E. huxleyi alone (Figure 7) for the global ocean visually reproduces the mid-latitude production belts, however at lower latitudes than satellite PIC estimates.This agrees with the NEMO and OCCAM models of coccolithophore dominance (Sinha et al., 2010) and the chlorophyll a NASA Ocean Biogeochemical Model (NOBM) model for the Southern hemisphere and central North Atlantic provinces (Gregg and Casey, 2007).CCPP also estimates seasonal changes with higher productivity during summer in both hemispheres (see figure 7A and D vs. B and E).This pattern is driven mainly by temperature, which influences the latitudinal location of the bands, and light intensity, which influences whether the northern or southern band of productivity is stronger in a season.Nutrients are an essential, and in the ocean often limiting, requirement for biological productivity (Kattner et al., 2004;Browning et al., 2017).As such it would be expected that nutrients should also be strongly influencing seasonal patterns of PIC production.However, with the starting cell concentrations for the CCPP (2017) (growth rates at or close to zero which equates to low to zero CCPP) and Sinha et al. (2010) (high nutrients resulting in coccolithophores being dominated by diatoms).For the Southern Ocean, it has been suggested that satellite PIC concentrations in subantarctic waters are overestimated by a factor of 2-3 while those in Antarctic waters may be even more so (Holligan et al., 2010;Balch et al., 2011;Trull et al., 2018).The fact that three other global estimates, based on different sets of environmental parameters, all estimate very little productivity in the Southern Ocean seems to support this theory.However, there are also specifically cold adapted strains of Emiliania huxleyi found at high latitudes which at least partially could explain discrepancies between the mentioned model projections and satellite derived PIC concentrations (see also below).
In Austral winter/Boreal summer CCPP (for E. huxleyi) and satellite PIC estimates closely match (R 2 =0.73 F=26.78 p<0.01) with low PIC in the South and central South provinces, very low PIC in the equatorial, North Indian and Antarctic provinces and higher PIC in the North central Pacific, North Pacific and North Atlantic provinces (Figure 8A).In Austral summer/Boreal winter CCPP (for E. huxleyi) and satellite PIC estimates in individual ocean provinces are also generally of overall good agreement (R 2 =0.85 F=50.01 p<0.01).Both CCPP and satellite PIC estimates for Austral summer/Boreal winter are low in all equatorial and North ocean provinces with slightly higher CCPP and satellite PIC production for the North central provinces and higher production in the South and South central provinces (Figure 8B).
Despite having similar PIC patterns, overall PIC estimates can differ significantly between CCPP and PIC s in some provinces.
These provinces can be divided into two groups characterized by either greater or lesser PIC estimates than those observed by satellite (Figure 8).The mid-latitude provinces of central South and central North Pacific and Atlantic and central South Indic in the summer season belong to the former, with higher CCPP than PIC s .Recently, low phytoplankton biomass in these subtropical gyre systems have been hypothesized to be the result of strong grazing pressure despite high cellular growth rates (Behrenfeld, 2014), lending an explanation of why CCPP is higher than satellite PIC standing stocks.The lower PIC standing stocks estimated from the satellite could also be the result of other phytoplankton functional groups, such as diatoms, taking a comparatively bigger nutrient share (Iglesias-Rodríguez et al., 2002) thereby leaving less for PIC production by coccolithophores.
In contrast, in Austral summer/Boreal winter in the Antarctic and Austral winter/Boreal summer in the North Pacific, CCPP is smaller than satellite PIC estimates (Figure 8).E. huxleyi, which our projections are based off, has been found to dominate assemblages in polar areas, particularly in the southern hemisphere (Okada and Honjo, 1973;Gravalosa et al., 2008;Mohan et al., 2008;Charalampopoulou, 2011).The strains of E. huxleyi found here are special cold-adapted ones which can survive at temperatures as low as -1.7 • C in the Antarctic (Cubillos et al., 2007) and -0.9 • C in the Arctic (Charalampopoulou, 2011)).
As our CCPP is based on a temperate coccolithophore strain, lacking the cold adapted ones, our projections underestimate coccolithophore productivity in these areas.Additionally, differences in CCPP and satellite PIC in the Southern Ocean may also be connected to satellite overestimation of PIC at high southern latitudes (see above).
Comparing satellite PIC and CCPP in different oceanic provinces (Figure S1) E. huxleyi alone provided the greatest agreement between both.The addition of G. oceanica to CCPP calculations negatively affected correlations with satellite PIC.This Table 1.Fit coefficients (k1 to k6), R 2 , F-values, degrees of freedom and p-values obtained for calcification (pg C cell −1 d −1 ), photosynthetic carbon fixation (pg C cell −1 d −1 ) and growth rates (d −1 ) from Eq. ( 2) fitted to data from this study and Sett et al. (2014).For calcification and photosynthetic carbon fixation rates the unit for v = pg C cell −1 day −1 while for growth rates the unit for v = day −1 .
results into major ocean biogeographical provinces following Gregg and Casey 2007 with the single change of adjusting the Antarctic and the north ocean regions to start at 45°as in Longhurst 2007 rather than 40°(Figure S1).For each major province, the total amount of PIC s and CCPP for all comparable grid cells were calculated for Austral summer/Boreal winter and Austral winter/Boreal summer.For comparison, values for each basin and season were then converted into percentages of annual global (global summer plus global winter) PIC s or CCPP production.Agreement between the satellite and CCPP estimates was then assessed using a linear correlation.Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-88Manuscript under review for journal Biogeosciences Discussion started: 1 March 2018 c Author(s) 2018.CC BY 4.0 License.
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-88Manuscript under review for journal Biogeosciences Discussion started: 1 March 2018 c Author(s) 2018.CC BY 4.0 License.calculations chosen here, there was sufficient nitrate to support the projected production in most ocean regions (Figure 7C and F).High temperatures drove relatively low productivity in the equatorial regions in agreement with satellite PIC.Similar low levels of coccolithophores are estimated in Sinha et al. (2010) in the equatorial Pacific and Atlantic with the mixed phytoplankton functional group dominating with or without coccolithophores due to low iron and moderate phosphate concentrations and in Gregg and Casey (2007) for the equatorial Indian and Atlantic provinces.CCPP underestimates production at cold high latitudes, in particular in the Southern Ocean, when compared to the satellite.Similar low levels of coccolithophores have been projected in the Southern Ocean in Gregg and Casey (2007) (very low coccolithophore chlorophyll a), Krumhardt et al.
is counter-intuitive as one would expect increasing correlation of CCPP with satellite PIC as more species are used for the projection of the former.Indeed, estimates based on a combination of E. huxleyi and G. oceanica in Austral summer/Boreal winter were similar to those for E. huxleyi alone.However, in Austral winter/Boreal summer estimates based on a combination of E. huxleyi and G. oceanica resulted in much lower agreement between CCPP and satellite PIC when compared to E. huxleyi alone.This difference is driven by greatly increased CCPP estimates in the central North Pacific and Atlantic, combined with greatly decreased CCPP estimates in the North Pacific and Atlantic, relative to the E. huxleyi alone fit.Being a warm adapted species including G. oceanica would result in more productivity in the sub-tropical zones.However, these zones are also regions of potentially significant top-down control (see above for details).Meanwhile the North Pacific and Atlantic are likely dominated by cold-adapted species (see above for details), so including the warm-adapted G. oceanica in CCPP calculations would further reduce estimates in these regions.As a result, the inclusion of G. oceanica does not assist in making global estimates of coccolithophore PIC production.5 ConclusionsOur analysis of the projected combination of increased temperature and CO 2 on potential success, in terms of growth rates, suggests that E. huxleyi will benefit over G. oceanica.Due to a greater sensitivity to CO 2 , G. oceanica's niche will likely contract to regions of higher temperature under future ocean conditions.In general, changes in community composition can influence community level carbon production and sequestration by coccolithophores.Such changes could have significant implications for climate feedback mechanisms, one being the effects on the relative strength of the organic and inorganic carbon pumps, especially in coccolithophore dominated ecosystems.Temperature and light were found to be important factors driving projections of CaCO 3 production potential (CCPP) on a global scale.Comparison of satellite derived inorganic carbon versus estimated inorganic carbon suggests that E. huxleyi CCPP is a good proxy for coccolithophore community production in most biogeographical provinces.However, results indicate that data on the responses of polar species and strains, to environmental change, may be required to improve estimates in the high-latitudes, while the effects of top-down controls might be needed to improve estimates in the mid-latitudes.Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-88Manuscript under review for journal Biogeosciences Discussion started: 1 March 2018 c Author(s) 2018.CC BY 4.0 License.Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-88Manuscript under review for journal Biogeosciences Discussion started: 1 March 2018 c Author(s) 2018.CC BY 4.0 License.

Figure 7 .
Figure 7. Austral summer/Boreal winter (A) and Austral winter/Boreal summer (D) satellite measured particulate inorganic carbon.Austral summer/Boreal winter (B) and Austral winter/Boreal summer (E) CCPP estimates accounting for carbonate chemistry (substrate and hydrogen ion concentrations), light intensity and temperature.Note the strong bands of CCPP at the mid-latitudes.Austral summer/Boreal winter (C) and Austral winter/Boreal summer (F) CCPP estimates accounting for carbonate chemistry (substrate and hydrogen ion concentrations), light intensity and temperature and nitrate concentrations (nutrient proxy).

Figure 8 .
Figure 8. Satellite derived particulate inorganic carbon (black bars) and CCPP (white bars) estimates for major ocean biogeographical provinces (see figure S1 for details) as percentages of total production in (A) Austral winter/Boreal summer and (B) Austral summer/Boreal winter.