Introduction
Before the Anthropocene, the atmospheric CO2 concentration was governed
by the surface ocean [CO2], simply because the carbon content of the
ocean is 65 times larger than that of the atmosphere (Siegenthaler and
Sarmiento, 1993). Hence, understanding the global carbon cycle and the
evolution of atmospheric pCO2 in Earth history requires knowledge of
the dynamics of the oceanic carbonate chemistry. Since the industrial
revolution, the unprecedented magnitude and rate of carbon emissions has
caused both warming and acidification of the oceans (Bijma et al., 2013;
Ciais et al., 2013; Gattuso and Hansson, 2011; Gattuso et al., 2015; Rhein et
al., 2013). As a consequence, the interest in the reconstruction of seawater
carbonate chemistry to identify ocean acidification in Earth history
experienced an impetus (Hönisch et al., 2012; Martínez-Botí et
al., 2015a).
The most promising tool for reconstructing pH is the boron isotopic
composition (δ11B) of biogenic carbonate producers such as
foraminifera and corals (Hönisch et al., 2004; Rae et al., 2011; Sanyal
et al., 2001, 1996; Spivack et al., 1993) and a growing number of studies
have thus used δ11B-based pH records to reconstruct past
atmospheric CO2 (e.g. Foster et al., 2012, 2006; Hemming et al., 1998;
Hönisch et al., 2011, 2008, 2009, 2007, 2012; Hönisch and Hemming,
2005; Martínez-Botí et al., 2015a, b; Palmer et al., 1998; Pearson
et al., 2009; Pearson and Palmer, 2000, 1999; Rae et al., 2014; Sanyal and
Bijma, 1999; Sanyal et al., 1997, 1995; Seki et al., 2010).
Reconstruction of the full oceanic carbonate chemistry requires proxies of at
least two independent parameters of the carbonate system, in addition to
temperature and salinity. However, to date, all reconstructions are based on
the analysis of δ11B of biogenic carbonates alone with assumptions
regarding a secondary parameter. In these reconstructions, total alkalinity
(AT) or [CO32-] was estimated from modern ocean
conditions or from reconstructions of the carbonate compensation depth (CCD).
Total alkalinity is a conservative parameter, meaning that AT is
linearly correlated with salinity (Dickson, 1981, 1992; Wolf-Gladrow et al.,
1999, 2007). Therefore, if it is assumed that the modern
salinity–AT relationship was constant over time, AT
can be estimated from reconstructions of salinity using sea-level records
(Foster, 2008; Hönisch et al., 2009). However, salinity and alkalinity
may be decoupled in space and time through weathering and changes in riverine
alkalinity input. In addition, reliable proxies for regional salinity
reconstructions have yet to be developed. Another approach is based on the
assumption that seawater [Ca2+] has remained proportional to
AT over time so that AT can be adjusted in a way that
the water column is exactly saturated with respect to calcite at the
lysocline (∼ 500 m above the CCD; Pearson and Palmer, 2000). Surface
AT can be estimated by assuming that increases in AT
with depth were the same as in the modern ocean. The CCD, however, is not
uniform through space and time (Van Andel, 1975), calling into question these
approaches for estimating past AT. Pearson and Palmer (2000) note
that “the CCD record for the Palaeogene Pacific Ocean is relatively poorly
constrained”.
Although δ11B has proven to be a reliable proxy for pH and one can
argue that ocean pH is the main driver of past atmospheric CO2, it is
important to remember that changes in past glacial interglacial atmospheric
pCO2 can be achieved via two end-member scenarios (e.g. Lea et al.,
1999; Sanyal and Bijma, 1999). In the first scenario, changes in carbonate
chemistry are brought about by changes in total dissolved inorganic carbon
(CT) only. This is equivalent to varying the response of the
biological pump as a reaction to variations in the nutrient content of the
surface ocean. In the second scenario, changes in carbonate chemistry are
solely controlled by addition (due to dissolution in sediments) or removal
(due to production) of calcium carbonate. The change in surface ocean
carbonate chemistry is very different in these two scenarios because the
ratio of carbonate ion increase in relation to pCO2 decrease,
depending
on surface ocean alkalinity (Lea et al., 1999). A smaller change is
associated with the drawdown of CT under conditions of unchanging
alkalinity (e.g. strengthening the biological pump without calcite
compensation). The change in surface water [CO2] is twice as much when
the same atmospheric pCO2 is reached solely via a change in
alkalinity as in the coral reef hypothesis (Lea et al., 1999). These
dependencies are nicely demonstrated in Fig. 1.1.3 of Zeebe and
Wolf-Gladrow (2001) and Fig. 1 of Foster and Rae (2016).
The real ocean operates somewhere between these end member scenarios and,
basically, depends on the relative delivery rates of calcium carbonate and
particulate organic carbon (the CaCO3 : POC “rain ratio”) and the
sensitivity of calcium carbonate preservation in deep ocean sediments. This
demonstrates that a second, pH-independent, parameter could reduce the
uncertainty in CO2 estimates. On the other hand, the propagated
uncertainty in the second parameter, reconstructed from an independent proxy
(taking into account measurement and calibration uncertainty) might not be
much lower than the margin of error that is garnered using assumptions
around, for example, total alkalinity.
The boron isotope pH proxy in foraminifera has recently been reviewed by
Foster and Rae (2016) and we refer to that for further reading. Here, we will
briefly explain the boron systematics. Boron exists in seawater primarily in
the form of two species, boric acid (B(OH)3) and borate ion
(B(OH)4-; Fig. 1a). As for all weak acids, the relative abundance
between these two species is controlled by pH (Dickson, 1990; DOE, 1994). At
low pH (< 7), nearly all boron is present in the form of boric acid,
whereas at high pH (> 10), boron primarily exists as borate. Because of
the isotopic fractionation between the two aqueous species (Fig. 1b;
α4-3=RB(OH)4-/RB(OH)3), the boron isotopic
composition of each species is also pH-dependent (Hemming and Hanson, 1992;
Palmer et al., 1987; Sanyal et al., 1996, 2000). B(OH)3 is enriched in
the stable isotope 11B compared to B(OH)4-, with a constant
isotopic fractionation of 27.2 ‰ between the two boron species
(Klochko et al., 2009, 2006). Consequently, as the relative
concentration of the dissolved species changes with pH, so does their
isotopic composition. Because it is assumed that only the charged species,
borate, is incorporated into the calcite lattice (Hemming and Hanson, 1992;
Vengosh et al., 1991), the boron isotopic composition of marine carbonates
thus records the pH that prevailed when the calcium carbonate was
precipitated.
(a) Bjerrum plot showing the effect of pH on concentration of
dissolved boron species at T=25 ∘C, S=35 and [B]total 416 µmol kg-1. (b) Effect of pH on boron isotopic
composition of B(OH)4- and B(OH)3 with thermodynamic
fractionation factor (α3-4)=1.0272 (Klochko et al., 2006).
However, several studies have questioned the exclusive uptake of borate into
calcite. For instance, Uchikawa et al. (2015) used inorganic precipitation
experiments to show indirect evidence for incorporation of both
B(OH)4- and B(OH)3 into calcite. Based on first-principles
quantum mechanical tools, Balan et al. (2016) concluded that the mechanisms
of boron incorporation into calcium carbonates are probably more complex than
assumed (i.e. not just charged borate). Although not invalidating the
empirical paleo-pH proxy, their results call for a better understanding of
the fundamental mechanisms of boron incorporation in carbonates. This
demonstrates again that there is an urgent need for experiments where the
primary controls of boron incorporation are investigated.
Considering the uncertainties associated with the constraints of δ11B-based pCO2 reconstructions, it is desirable to develop proxies
for a carbonate system parameter in addition to pH. The B / Ca ratio of
planktonic foraminifera has been proposed as a proxy for estimating past
changes in [CO32-] (Foster, 2008); however, given that the
concentration of borate B(OH)4-) increases with pH and pH co-varies
with [CO32-], it is challenging, if not impossible, to identify the
parameter controlling B / Ca based on samples that have grown in natural
seawater because pH and carbonate chemistry parameters co-vary closely in
natural systems. To disentangle their effects it is necessary to deconvolve
the carbonate chemistry.
Such a study was recently carried out (Allen et al., 2012) and has shown that
the B / Ca ratio of planktonic foraminifera also decreases with
increasing total inorganic carbon (CT or [HCO3-]) at
constant pH (i.e. [B(OH)4-] was constant while [CO32-] and
[HCO3-] were increased), suggesting that borate and carbon species
compete for the inclusion in the calcite lattice. In their experiments,
they kept pH constant and varied [CO32-] but did not vary pH at
constant [CO32-], leaving the question open as to whether the B / Ca
ratio in planktonic foraminifera is only a function of the ratio between
[B(OH)4-] and CT or [HCO3-] or perhaps also
modulated by pH or [CO32-]. Kaczmarek et al. (2015b) decoupled the
carbonate chemistry both ways and showed that B / Ca in the benthic
foraminifer Amphistegina lessonii is influenced by the
ratio between [B(OH)4-] and [HCO3-], rather than by pH or
[CO32-].
Recently, Henehan et al. (2015) demonstrated a very clear and close
relationship between B / Ca and carbonate chemistry parameters (pH;
[B(OH)4-] / [HCO3-] and [B(OH)4-] / CT) in
Globigerinoides ruber from culture experiments. However, this
relationship was completely lost in the plankton tow samples and the
sediments they analysed. While they explicitly tested for a carbonate
chemistry control on B / Ca, they found a strong relationship to
[PO4-] and neither a correlation with carbonate system parameters nor
a covariation of phosphate with carbonate system parameters. They concluded
that apparently B / Ca in G. ruber is controlled by
[PO4-]. We will discuss why we believe that the primary (mechanistic)
relationship explaining B / Ca is probably still controlled by carbonate
chemistry parameters in the ambient environment of the foraminifer, but that
it may be masked in the field and decoupled from the bulk seawater carbonate
chemistry.
Here, we are specifically focussing on the primary controls of boron uptake
and conducted experiments with the planktonic foraminifer Orbulina universa and decoupled pH and [CO32-] in the same way as Kaczmarek
et al. (2015b). We show, in principle, that combined measurements of δ11Bcalcite and B / Ca on single shells of planktonic
foraminifera might be used to fully constrain the carbonate chemistry in
downcore records. However, based on recent publications (Allen et al., 2012;
Babila et al., 2014; Henehan et al., 2015; Salmon et al., 2016), it becomes
increasingly clear that in the field and downcore, B / Ca may not be a
very robust carbonate system proxy (at least in some species) as the primary
relationship can be masked by other environmental factors.
Methods
Collection and culturing
Living specimens of O. universa were collected daily using a 57 cm
diameter WP2 plankton net (200 µm mesh size), between July and
September 2012 at Point B, Villefranche-sur-Mer, France (43.41∘ N,
7.19∘ E), and maintained until gametogenesis in laboratory cultures
at the Laboratoire d'Oceanographie de Villefranche. Established procedures
for maintaining planktonic foraminifera in laboratory culture were used
(Bemis et al., 1998; Bijma et al., 1998; Spero and Lea, 1993). Briefly,
specimens were identified, the diameters measured with a light microscope, and they were then transferred
to 0.2 µm-filtered seawater, whose carbonate chemistry was
accurately determined and subsequently modified. Specimens were maintained
individually in air-tight 100 mL acid-washed SCHOTT
DURAN® bottles that were sealed without an
air space and placed upside down into thermostated water baths maintained at
a temperature of 23 ∘C (±0.2 ∘C). Light was provided by
four 39 W fluorescent tubes (JBL Solar Ultra Marin Day), with reflectors
(at a distance of ca. 15 cm from the water surface), with a 12:12 h L:D
photoperiod. The average irradiance, measured with a LI-193 sensor (LiCOR) in
the culture jars was about 290 µmol photons m-2 s-1.
The foraminifers were fed a one-day-old brine shrimp Artemia
nauplius every second day until gametogenesis. The brine shrimp were hatched
in modified seawater from the same batch as used for culturing the
foraminifera. Just prior to feeding, hatched nauplii were transferred once
again to fresh medium from the same batch. After feeding, culture jars were
topped up with medium from the same batch to prevent the formation of a
headspace. Empty shells were collected within 24 h after successful
gametogenesis, rinsed in deionized water and archived in covered micro-paleo-slides for later analysis. Prior to analysis, specimens were harvested,
bleached in NaOCl (active chlorine: 4.6 %) for 6 h, rinsed four times
using deionized water, and dried for 12 h at 50 ∘C. Approximately
35 tests were grown for each experimental treatment. Culture water samples
were collected at the start and end of the experiments to verify the boron
concentration, its isotopic composition and the carbonate system parameters.
Average properties of the manipulated seawater culture medium from
four
samples (two from the start of the incubation and two from the end of the
incubation).
pHT
CT
AT
pCO2
CO32-
HCO3-
T
S
δ11B
(µmol kg-1)
(µmol kg-1)
(µatm)
(µmol kg-1)
(µmol kg-1)
(∘C)
(‰)
8.05 ± 0.02
2235.9
2566.8 ± 11
431.8
238.7
1981
23 ± 0.7
38 ± 0.6
5.35 ± 0.53
8.05 ± 0.05
2671.5
3050 ± 27
516.5
285.6
2370.6
23 ± 0.7
38 ± 1.02
4.98 ± 0.85
8.05 ± 0.03
4985.4
5594.3 ± 38
1103.7
533.9
4424.2
23 ± 0.7
38 ± 0.5
4.20 ± 1.03
7.9 ± 0.02
3809.2
4153.2 ± 154
1061
296.6
3478.4
23 ± 0.7
38 ± 0.3
4.11 ± 0.94
7.7 ± 0.03
5119.8
5361.8 ± 23
2335.1
257.8
4791.6
23 ± 0.7
38 ± 0.9
4.69 ± 2.4
Modified seawater chemistry
The objective of these experiments was to decouple seawater pH and
[CO32-] and create treatments with a constant pH and varying
carbonate ion concentration and treatments with a constant carbonate ion
concentration but varying pH. To decouple the effects of pHT and
[CO32-], seawater carbonate chemistry was modified by manipulating
pHT, using NaOH and HCl, and dissolved inorganic carbon
(CT) by adding gravimetrically carbonate and bicarbonate or
bubbling with CO2. Calculations were made using csys_vari.m (Zeebe et
al., 2001) with carbonic acid dissociation constants of Mehrbach et al.
(1973). Temperature (23 ∘C) and salinity (38.0) were kept constant
(Table 1).
To enable single-shell analysis by LA-MC-ICP-MS, the boron concentration was
increased to 10 times the concentration of natural seawater by adding boric
acid to the culture water (see Sanyal et al., 2001, 2000). The pHT
and CT were then modified via titration with boron-free NaOH (1N)
and HCl (1N) to bring the experimental pH to desired levels of
7.70 ± 0.03, 7.90 ± 0.02, and 8.05 ± 0.05.
Culture water samples collected at the start and at the end of each
experiment showed that pH remained nearly constant throughout each
experiment. The boron isotopic composition of each culture treatment is
provided in Table 1. The pH of the culture solutions was measured using a
Metrohm, 826 mobile pH meter with a glass electrode (Metrohm, electrode plus)
calibrated to the total scale using TRIS and 2-aminopyridine buffer solutions
(Dickson et al., 2007) adjusted to a salinity of 38.0. Total alkalinity
(AT) samples (150 mL) were filtered on GF/F and measured
potentiometrically using a Metrohm Tritando 80 titrator and a Metrohm,
electrode plus glass electrode (Dickson et al., 2007). 60 mL samples were
also taken at the start and end of incubations and poisoned with
10 µL of saturated HgCl2 pending determination of dissolved
inorganic carbon (CT). Samples were measured using an AIRICA
(Marianda, Kiel) fitted with a Licor 6262 infrared gas analyser. All
parameters of the carbonate system were calculated from AT and
pHT (Hoppe et al., 2012) using the R package seacarb (Lavigne and
Gattuso, 2013).
Culture water analysis
Boron isotopic composition of the culture media were analysed by means of a
Thermo® Element XR, a single collector,
sector field, high-resolution inductively coupled plasma mass spectrometer,
fitted with a high-sensitivity interface pump (Jet pump) as described in
Misra et al. (2014). Boron isotopic composition is reported as per mil
(‰) deviation from NIST SRM 951a
(11B / 10B = 4.04362 ± 0.00137) (Catanzaro et al., 1970)
where:
δ11Bsample(‰)=11/10Bsample11/10BNISTSRM951a-1×1000.
Boron isotope analyses were made following a Sample–Standard Bracketing
(SSB) technique. NIST 951a was used as the standard and samples were
concentration-matched, typically at 5 %, with the standard and were
analysed in quintuplicate. The accuracy and precision of the analytical
method was assessed by comparing 11B measurements of seawater (from the
Atlantic Ocean) and secondary boron standards (AE 120, 121, 122) with
published (accepted) results. Our estimates of δ11BSW of
39.8 ± 0.4 ‰ (2 SE, n=30) are independent of sample size
and are in agreement with published values of 39.6 ± 0.04 ‰ (2 SE, n=28)
(Foster et al., 2010) and 39.5 ± 0.6 ‰ (2 SD) (Spivack and Edmond,
1987). Moreover, our δ11B estimates of SRM AE-120
(-20.2 ± 0.5 ‰, 2 SE, n=33), SRM AE-121
(19.8 ± 0.4 ‰, 2 SE, n=16), SRM AE-122
(39.6 ± 0.5 ‰, 2 SE, n=16) are identical, within
analytical uncertainty, to accepted values (Vogl and Rosner, 2012).
Information about sample preparation for analysis can be found in the
Supplement provided in Kaczmarek et al. (2015a).
Analysis of O. universa
For simultaneous determination of the B isotopic composition and its
concentration, a Fiber Optics Spectrometer (Maya2000 Pro, Ocean Optics) was
connected to the torch of a Thermo Finnigan Neptune multiple-collector
inductively coupled plasma mass spectrometer (MC-ICP-MS) at the Leibniz
University of Hannover. Laser ablation on reference material and samples was
performed by an in-house-built UV-femtosecond laser ablation system based on
a regenerative one-box femtosecond laser (Solstice Newport/Spectra Physics).
A detailed description of the method used for the simultaneous determination
of B concentration and δ11B of O. universa can be found in
Kaczmarek et al. (2015a). A summary of the procedure is given below.
Simultaneous determination of B concentration and δ11B
The B intensity of a reference material corresponds to its known B
concentration. Based on this relationship, the unknown B concentration of a
sample can be calculated. However, our measurements of the reference material
(NIST SRM 610) and samples were not performed at the same laser repetition
rate: hence, their B ratios are not proportional. Because Ca concentrations
in the reference material and in the sample are known (NIST SRM 610:
8.45 %, CaCO3: 40 %) a correction for different laser repetition
rates was realized by the analysis of calcium using the optical spectrometer.
More information on this procedure is provided by Longerich et al. (1996).
Calcium analysis
The Maya2000 Pro is a high-sensitivity fiber optical spectrometer. It has a
measuring range between 250 and 460 nm with a resolution of 0.11 nm covering
the first order emission lines of Mg II, Ca II, Sr II, Ba II and Li II. It is equipped with a back-thinned 2-D
FFT-CCD detector, and a grating with a groove density of 1200 lines mm-1. The
optical fiber used is 2 m long (attenuation of the photon flux is
length-dependent), connecting the spectrometer with the coupling lens at the
end of the plasma torch of the MC-ICP-MS (Thermo Finnigan Neptune). Ca II ion
lines were measured at a wavelength of 393.48 and 396.86 nm. At these
wavelengths the Ca spectrum shows no detectable interferences for the matrices
used. The acquisition parameters were set to acquire 220 cycles per analysis
with an integration time of 1 s for each cycle. For the first 40 cycles,
only background (BG) signal was detected prior to measuring the sample. The
BG signal detected at the start of the analysis was later used for correcting
sample measurements by subtracting BG intensity from the intensity of the
reference and the sample material.
Boron isotope analysis – 194 nm femtosecond laser ablation
The in-house-built laser ablation system is based on a 100 femtosecond
Ti-sapphire regenerative amplifier system operating at a fundamental
wavelength of 777 nm in the infrared spectrum. Subsequent harmonic
generations produce the wavelengths 389 nm in the second, 259 nm in the
third and 194 nm in the fourth harmonic. The pulse energies measured with a
pyroelectric sensor (Molectron, USA) are 3.2 mJ pulse-1 at 777 nm,
0.7 mJ pulse-1 at 259 nm, and 0.085 mJ pulse-1 at 194 nm.
After the fourth harmonic generation stage, the 194 nm beam is steered by
eight dichronic mirrors into an 8 × objective (NewWave Research, USA)
and focussed onto the outside of the sample. Spot size was set to
50 µm for the reference material and the samples. Within this spot,
an energy density of ∼ 2 J cm-2 is maintained. Reference
material measurements were performed in raster mode
(100 µm × 100 µm) at 10 Hz and samples were
ablated at 8–50 Hz depending on B concentration.
It should be noted that the fs laser ablation process is fundamentally
different from ns laser ablation. When the pulse length is shorter than 1 ps
(Hergenröder et al., 2006), the laser energy can be deposited into the
material before it can thermally equilibrate. Femtosecond ablation also
provides smaller aerosol particle sizes. Due to the short pulse length, fs
laser ablation shows no detectable matrix dependency (e.g. Chmeleff et al.,
2008; Horn et al., 2006; Kaczmarek et al., 2015a; Lazarov and Horn, 2015;
Oeser et al., 2014; Schuessler and von Blanckenburg, 2014), i.e. it does not
require a matrix-matched standard and therefore permits the use of NIST SRM
610 (a glass) as a reference for carbonates. As boron concentrations differ
between sample and standard, and different matrices require more or less
energy for ablation, the repetition rate was chosen such that the signal of
sample and standard at the ion counters was comparable. This is important for
normalization of the sample to the known δ11B of the standard and
also accounts for the imprecision of the determined detector dead time.
Most previous publications on boron isotopes have used “wet chemistry” for
which NIST SRM 951 is a perfect standard. We have also used this standard for
the analysis of the culture waters. The foraminiferal shells, however, were
referenced against NIST SRM 610. As shown by several studies (Fietzke et al.,
2010; Kasemann et al., 2001; Le Roux et al., 2004), both standards are,
within analytical uncertainty, isotopically equal. Hence, for comparison
between δ11B of O. universa and δ11B of
B(OH)4-, the isotopic difference between the two standards can be
neglected and it does not make a difference if values are reported vs. one
or the other standard.
Boron isotope analysis – acquisition parameters
All measurements are carried out in low mass resolution (Δm/m=350
where m is the mass of the ion of interest and Δm is the mass
difference between its 5 and 95 % peak height). Compact discrete dynode
multipliers (CDDs, Thermo) are attached to Faraday cups at the low site on L4
and the high site on H4. The low-resolution mode is sufficient to resolve
potential interferences from doubly charged ions due to the intrinsic high
resolution in the low mass region. Possible interferences are the clusters of
40Ar4+ or 20Ne2+, which are well resolved to the
background level. The instrument was tuned prior to each analytical session
for optimal peak shape. Instrumental operating conditions are reported in
Table 2. All measurements were performed at plateau voltage of the CDDs,
which was checked prior to every analytical session. Before the beginning of
sample analysis, measurements of NIST SRM 610 were continued until
instrumental drift (due to warm-up) was less than 200 ppm over a bracketing
sequence duration of twelve minutes. Boron signal intensities of NIST SRM 610
and samples were matched within 10 % in signal intensity by adapting the
laser repetition rate. The acquisition parameters in static mode for analysis
of NIST SRM 610 and samples were set to acquire 200 cycles of 1 s
integrations each. During the first 40 cycles the background signal was
acquired, whereas the remaining cycles represent the sum of the background and
the reference material, or the background and the sample signals. A complete
measurement consisting of 200 cycles of a single reference material or sample
took 4 min before the next sample was introduced. For analysis we adopted
the standard sample bracketing procedure and the B isotopic composition is
reported using the delta notation:
Instrumental operating conditions for the MC-ICP-MS and LA.
Cool Gas [L min-1]:
14.6
Aux Gas [L min-1]:
1.2
Sample Gas [L min-1]:
1.5
Add Gas [L min-1]:
0.4
Operation Power [W]:
1269
X Pos [mm]:
1.5
Y Pos [mm]:
-1.7
Z Pos [mm]:
-2.5
Wavelengh [nm]
194
Pulse energy [J cm-2]
2
Pulse width [fs]
∼ 200
Spot size [µm]
50
δ11Bsample(‰)=11B/10Bsample11B/10BNIST610-1+11B/10BNIST610+1/2-1×1000,
where NIST 610 - 1 and NIST 610 + 1 refer to the analysis of the
reference material before and after the sample. The uncertainty of the
samples was calculated according to:
2SEδ11Bsample(‰)=SE11/10BNIST-12+SE11/10Bsample2+SE11/10BNIST+12×2×1000,
where 11/10B ratios represent mean values of the reference material and
the sample calculated from one measurement (based on
160 cycles) and SE represents the standard error of the 11/10B ratios.
Due to the natural inhomogeneity of the samples, the analytical uncertainty
is represented best by repeated measurements of the homogenous reference
material given by:
δ11BNIST610(‰)=11/10B011/10B-1+11/10B+1/2-1×1000,
where the measurements of the (11/10B)-1 and (11/10B)+1
ratios of NIST 610 were performed before and after the measurement of
(11/10B)0, respectively. For the determination of the analytical
uncertainty and external reproducibility, all measurements of NIST 610
performed between each sample measurement were taken into account. On
average, the analytical uncertainty and external reproducibility is
0.66 ‰.
Conversion of δ11BO.universa to natural
seawater
Due to the additional B addition to our culture media the δ11Bseawater shifted from 37.63 (Mediterranean) to, on average,
4.66 ‰ (Table 1). Therefore, the δ11BO.universa shifted accordingly. In order to compare
our O. universa data to published values (Fig. 3a), the measured
δ11B from each experiment was normalized to natural seawater using
the following (Zeebe and Wolf-Gladrow, 2001):
δ11Bc=αsw-msw×δ11Bm+ε,
where ε is (αsw-msw-1) × 1000,
δ11Bc represents the converted δ11B for the
measured value (δ11Bm),
αsw-msw is the
fractionation factor expressing the difference between the natural seawater
and manipulated seawater:
αsw-msw=δ11Bsw+103/δ11Bmsw+103.
Statistics
Lamtool (a modified Excel spreadsheet, initially programmed by Jan Kosler,
University of Bergen, Norway) was used for analysis and background correction
of the δ11B data. All other statistics were carried out using R (R
Core Team, 2008). Error bars represent ±2σ errors, correlations
were calculated by linear regression. The procedures for data evaluation,
background correction and uncertainty calculations for boron concentration
and isotopes are extensively described in Kaczmarek et al. (2015a).
In contrast to “wet chemical” analysis, laser ablation (LA) records the
inhomogeneous boron distribution (“boron banding”, see Branson et al., 2015)
within a specimen and individual shell analysis captures inter-specimen
differences. Sadekov et al. (2016) demonstrated that the variability in both
B / Ca and δ11B recurs in each chamber and, therefore,
represents real data of high quality. This is supported by the fact that the
values of the averaged laser data are very close to wet chemical analyses
where multiple specimens are dissolved and the intra- and inter-variability
is “averaged” before the analysis. The intra-specimen δ11B
variability in Cibicidoides wuellerstorfi is up to ca. 10 ‰
(Sadekov et al., 2016), while the inter-specimen δ11B variability
of Amphistegina lessonii from the same treatment is ca.
6 ‰ (Kaczmarek et al., 2015b). Histograms of single-foram
δ11B measurements from each of our pH treatments (Fig. S1 in the Supplement)
show that the LA data is normally distributed (p values from
Shapiro–Wilk tests are all higher than 0.05). This is confirmed by the box
plots (Fig. S1) where the average and median values are very
close to each other. The relatively large standard errors of laser ablation
analyses are representative of true inter-specimen variability and largely
unrelated to analytical errors. Therefore, the relatively large standard
errors do not present a limitation for how much can be interpreted from the
data. The major difference between LA and “wet chemistry” data is that the
latter method averages individual variability before analysis by measuring
multiple dissolved shells in one go, while LA captures individual
variability (which is large and real as argued above) and averages
afterwards.
B / Ca ratios plotted against (a) [CT],
(b) [B(OH)4-] / [CT] ratio, (c) [CO2],
(d) [B(OH)4-] / [CO2], (e) [CO32-],
(f) [B(OH)4-] / [CO32-], (g) [HCO3-],
(h) [B(OH)4-] / [HCO3-], error bars represent standard error.
One could further argue that the uncertainty stemming from the analysis of
culture water δ11B should also be propagated when plotting in
“normal δ11Bsw” space (Table S4 in the Supplement). The
propagated error is, of course, large as it includes the individual δ11B variability of the foraminifers. It is important to acknowledge that
this variability represents true data, which is largely unrelated to
analytical uncertainty. We added a calcite vs. borate δ11B cross-plot
(Fig. 4) to avoid the conversion into the seawater scale and making the error
propagation obsolete. However, as not all studies report the parameters
required for the calculation of δ11B of borate, we plotted for
comparison in “normal δ11Bsw” space (Fig. 3a) but did
not propagate the error related to the analysis of culture water
δ11B.
Discussion
B / Ca
Foster (2008) showed that the partition coefficient KD for the B / Ca ratio
is influenced by [CO32-] (and temperature). Although complicating the
application as a proxy related to [B(OH)4-] / [HCO3-], he
also demonstrated that B / Ca in combination with δ11B can be
used to fully constrain the carbonate system in downcore records.
Nonetheless, he identified [CO32-] as having a major (secondary)
control on B / Ca in samples of foraminifera from down-core samples and
core tops. A similar conclusion was reached by Allen et al. (2011) for
O. universa. These authors demonstrated a trend of decreasing
B / Ca with increasing pH and [CO32-]; however, due to the
co-variations of the carbonate system in natural seawater, it is difficult to
identify the differential effects of the individual parameters. Allen and
Hönisch (2012) conclude that the relationships between KD and
seawater parameters can sometimes be driven by the denominator of the
empirical boron partition coefficient
([B(OH)4-] / [HCO3-]), and not by B / Ca of seawater
itself. Reconstructions based on such B / Ca-independent relationships
are susceptible to being driven by other environmental parameters. They
conclude that application of the empirical boron partition coefficient should
be avoided until more is known about the relative influences of different
chemical species on boron incorporation.
Experimentally decoupling pHT from other parameters of the
carbonate system using modified seawater media allowed us to decouple the
relationships and identify the controlling carbon species. Our results
demonstrate that the amount of boron incorporated into O. universa
calcite is a function of CT (Fig. 2a). As CT increases,
B / Ca decreases, suggesting that B(OH)4-competes with carbon
species for inclusion in the calcite lattice. When B / Ca ratios are
plotted against [CO2], the relationship is similar to that of
CT; however, only < 1 % of CT is in the form of
CO2 so this species is unlikely to have a major control on boron
incorporation. The remaining > 99 % is ∼ 10 % CO32-
and ∼ 90 % HCO3- (Zeebe and Wolf-Gladrow, 2001). Due to
the strong correlation of the B / Ca ratio and
[B(OH)4-] / [CT], one could argue that foraminifera
utilize both HCO3- and CO32- as substrate for calcification
and, therefore, that CT is the factor controlling the B / Ca
ratios. However, because [HCO3-] and [CO32-] in our
treatments increase and decrease with decreasing pHT, respectively
(Table 1), we can distinguish between bicarbonate and carbonate ion control
over the B / Ca ratio.
At constant pHT, the relationship between B / Ca and
[CO32-] (Fig. 2e) supports the hypothesis of competition between
CO32- and B(OH)4-. However, when [CO32-] is held
constant and pHT is decreased, B / Ca significantly decreases
despite the fact that [CO32-] remains more or less constant (Fig. 2e,
Table 1). If the same relationships are examined for B / Ca and
[HCO3-] a strong correlation between [HCO3-] and B / Ca
is observed for both the absolute concentration of HCO3- (Fig. 2g)
and also for the ratio of [B(OH)4-] / [HCO3-] with no
effect of changing pHT (Fig. 2h). The close correlation between
[CO32-] and B / Ca at constant pHT can be explained by
the corresponding increases in [HCO3-] in these treatments (Table 1).
In agreement with our results, the study of Allen et al. (2012) investigated
the effects of decoupling pH and the carbonate system on B / Ca and
suggest that B(OH)4- competes with carbon species for inclusion in
the calcite lattice in three planktonic species Globigerinoides sacculifer, Globigerinoides ruber, and Orbulina universa.
Although analysis of planktonic foraminifera from core tops revealed a good
correlation between B / Ca and [B(OH)4-] / [HCO3-] it
does not rule out a possible correlation with
B(OH)4- / CO32- and/or B(OH)4- / CT
(Yu et al., 2007).
A recent study by Kaczmarek et al. (2015b) shows the same competition between
B(OH)4- and HCO3- in the benthic species A. lessonii
cultured in a pH-[CO32-] decoupled seawater. The observation that
B / Ca is driven by B(OH)4- / HCO3- and not related
to CO32- only becomes visible at higher pH (8.6) when
[B(OH)4-] is sufficiently high (see Fig. 6 and Table S1 in Kaczmarek
et al., 2015b). Below pH 8.6, foraminiferal B / Ca also correlates with
B(OH)4- / CO32-.
The finding that B(OH)4- / HCO3- controls boron incorporation
in O. universa calcite is also in agreement with the hypotheses of
Hemming and Hanson (1992) who suggested that only B(OH)4- is
incorporated into marine carbonates with the partition coefficient defined
below:
KD=[B/Ca]solid[B(OH)4-/HCO3-]seawater.
To summarize, based on our study, we can eliminate a control by
[CO32-] but cannot exclude [B(OH)4- / CO32-]. By
comparison to the B / Ca control in the benthic foraminifer A. lessonii (Kaczmarek et al., 2015b), we assume B / Ca in planktonic
foraminifera is also a function of [B(OH)4- / HCO3-].
Boron isotopic fractionation (δ11B)
As the various species of inorganic carbon and pHT are tightly
linked, it is still to be experimentally demonstrated, beyond doubt, whether
only pHT and/or the concentration of one or several carbonate
species might have an effect on δ11B. The results for treatments
with varying pHT and constant carbonate ion concentration displayed
the same relationship as those from the calibration curve for O. universa produced by Sanyal et al. (1996) but the absolute values for a
given pHT are lower by approximately 1 to 2 ‰ when
compared to the values corrected to the fractionation factor suggested by
Klochko et al. (2006; Zeebe et al., 2008). The effects of the unnaturally
high CT and AT values in the treatments cannot be
discounted as the cause of this difference, as δ11B values
increased with increasing [CO32-]. The δ11B values for
O. universa found in this study match closely with the
δ11B values of borate ion in artificial seawater given by Klochko
et al. (2006). This is probably caused by the suppression of the vital
effects imposed by O. universa. Theoretical considerations
demonstrate that at 10 × boron concentration compared to natural
seawater, vital effects are suppressed and the isotopic value of biogenic
calcite approaches the value of borate (Zeebe, 2003). This was confirmed by
the comparison of the boron isotopic values of O. universa grown at
low and high light (Hönisch et al., 2003) and supports the notion that
borate is, indeed, the species being taken up. There is a trend of varying
[CO32-] on δ11B of samples grown at the same pH but, most
importantly, in light of the results obtained for the B / Ca ratio, there
is no effect of [HCO3-] (Fig. 3c).
Proxy implications
A sound understanding of the effects of past carbon perturbations becomes
increasingly urgent in an age where anthropogenic activities are producing
such rapid changes in global climate (Bijma et al., 2013; Knoll and Fischer,
2011). The usefulness of biogeochemical proxies to reconstruct
paleo-oceanographic conditions is well established for many environmental
parameters (Wefer et al., 1999) but uncertainties remain for proxies related
to pH and the carbonate system (Allen and Hönisch, 2012; Hönisch et
al., 2007; Katz et al., 2010; Pagani et al., 2005). This study confirms the
robustness of δ11B as an independent pH proxy and supports the
growing body of evidence that B / Ca in planktonic foraminiferal calcite is
mechanistically controlled by [HCO32-] (Yu et al., 2007), thereby
allowing researchers to fully constrain the carbonate system in combination
with δ11B.
δ11B of borate vs. that of calcite. δ11Bborate was calculated using the fractionation factor of
11-10KB=1.0272 (Klochko et al., 2006) at T=23 ∘C
and S=38. Error bars for δ11Bforam represent ±2σ errors, and for δ11Bborate the translated
uncertainty of pH measurements (Table 3).
Based on our results and other culture studies, it becomes clear that despite
strong biological effects on the ambient carbonate chemistry (Köhler-Rink
and Kühl, 2001, 2000; Rink et al., 1998; Wolf-Gladrow et al., 1999; Zeebe et
al., 2008), the boron isotopic composition and the B / Ca are faithful
predictors of seawater pH and bicarbonate ion concentration, respectively.
Our results provide strong evidence that [HCO3-] is the primary
control of the B / Ca ratio. The correlation of the B / Ca ratio to
[HCO3-] rather than to [CO32-] might have some implications
for existing paleo-carbonate chemistry reconstructions based on this proxy
such as the study by Foster (2008) and that of Yu et al. (2014), since it
seems reasonable to assume that the same relationship probably holds for
benthic foraminifers as for planktonics.
A wide range of [HCO3-] was necessary to facilitate de-coupling the
carbonate system from pHT. The high [HCO3-] in some of
these treatments are unrealistic for natural seawater systems and more
environmentally-relevant values should be used for future calibration
experiments. The proxy should, therefore, be ground-truthed using water
column and core top samples.
Recently, Henehan et al. (2015) showed that B / Ca in G. ruber
collected with a plankton net was perfectly correlated to [PO43-] and
not to any carbonate chemistry parameter, despite the fact that their culture
study demonstrated a highly significant relationship between B / Ca and
for example [B(OH)4-] / [HCO3-]. Based on plankton tow, sediment trap
and core-top data, they concluded that, apparently, B / Ca in G. ruber is controlled by [PO43-]. However, it should be noted that
foraminifera, and especially symbionts bearing planktonic foraminifers, never
experience the bulk ocean carbonate chemistry (e.g. micro-electrode study by
Rink et al., 1998, and the modelling study by Wolf-Gladrow et al., 1999).
They only experience their ambient carbonate chemistry as modulated by their
own life processes, symbiont photosynthesis and respiration (so called
“vital effects”). Existing calibrations and field relationships are
therefore purely empirical and not mechanistic and the ambient carbonate
chemistry of the foraminifer and the bulk seawater chemistry can be
decoupled. We note that, of all symbionts bearing planktonic foraminifera,
G. ruber is probably the most “autotropic” (Bijma et al., 1992).
Although we cannot prove it, we assume that symbiont photosynthetic rates are
higher at elevated [PO43-] (limiting nutrient) and therefore that
ambient pH would be higher. Hence, even if the correlation between B / Ca
and seawater carbonate chemistry is lost, the correlation with ambient pH (or
[CO32-], [HCO3-]) may still hold up. At this point, there is
no obvious direct link between [PO43-] and B / Ca and we believe
that, mechanistically, it can be explained by increased photosynthesis and/or
higher calcification rates. Kaczmarek et al. (2016) show that boron
partitioning in inorganic precipitation experiments increases with increasing
growth rate, and early work by the pioneers of foraminiferal biology and
calcification (e.g. Bé et al., 1982; Bé, 1965; Caron et al., 1982;
Hemleben et al., 1987; Jørgensen et al., 1985; Spero and Parker, 1985)
clearly demonstrated the huge impact of symbionts on foraminiferal shell
growth. Interestingly, Babila et al. (2014) state: “The seasonal cycle of
B / Ca in G. ruber white was more strongly correlated with light
intensity than with temperature. Both observations suggest that the presence
of symbionts in G. ruber and seasonal variability in their
photosynthetic activity act to modify the internal pH during calcification,
by up to 0.2 units relative to ambient seawater.” This supports our line of
argumentation above.
In another recent paper on B / Ca, Salmon et al. (2016) write: “We
provide the first evidence for a strong positive relationship between area
density (test thickness) and B / Ca, and reveal that this is consistent
in all species studied, suggesting a likely role for calcification in
controlling boron partitioning into foraminiferal calcite.” Their conclusion
also supports our reasoning, that, mechanistically, increased photosynthesis
may lead to higher calcification rates. Remarkably, Salmon et al. (2016) show
that B / Ca of the non-symbiont-bearing species (Globigerina bulloides and Globigerina inflata) and even the symbiont-bearing
species G. sacculifer are related to [CO32-] and
[B(OH)4- / HCO3-]. In our view, those results demonstrate
the primary control by carbonate chemistry parameters not masked by symbiont
photosynthesis. One could even argue that there is a positive trend for
O. universa but that the natural range of [CO32-]
variability (or borate/bicarbonate) is small (ca.
20 µmol kg-1 in the depth range 30 to 50 m) in comparison to
the decoupling we carried out in controlled culture experiments.
Interestingly, Henehan et al. (2016) propose a field calibration for
O. universa that is very close to δ11B of borate,
suggesting that their “vital effects” are muted in the real ocean,
especially the symbiont impact of raising the calibration curve above
δ11B of borate. This is supported by the observation of Hemleben
and Bijma (1994) that O. universa occupies a subsurface maximum (in
the Red Sea) between 20 and 60 m (Hemleben and Bijma, 1994, Fig. 5) and could
explain why B / Ca in this species is not (completely) masked by symbiont
photosynthesis (Salmon et al., 2016).
Our final conclusion is that, although controlled laboratory studies are the
only means to clarify the mechanisms of proxy incorporation, field studies
are required to determine to what extent vital effects determine species-specific offsets from the target parameters. For instance, the light level
used in the culture experiments of Sanyal et al. (2001) was
∼ 380 µmol photons m-2 s-1, providing a photon
flux for maximum photosynthetic rates (Pmax) of the symbionts (Spero
and DeNiro, 1987; Spero and Parker, 1985; Spero and Williams, 1988).
Consequently, the impact of photosynthesis on the G. sacculifer
calibration of Sanyal et al. (2001) is fully expressed. However, in the real
ocean this species may experience lower irradiance, shifting the calibration
curve more towards the borate values. In our study, the average irradiance in
the culture jars was about 290 µmol photons m-2 s-1,
which is well below Pmax of the symbionts and apparently closer to the
irradiance conditions of their natural depth habitat. Therefore, the impact
of photosynthesis is muted (Hönisch et al., 2003; Zeebe, 2003) and our
laboratory calibration closer to the field calibration of (Henehan et al.,
2016).
Laboratory experiments are usually carried out with foraminifera selected as
model organisms for ease of availability and ability to be maintained in
culture but, generally, state nothing about their suitability for paleo-studies. Field studies are much better to identify which species are best
suited for down-core reconstructions. We agree with Henehan et al. (2015)
that G. ruber is not a good choice for B / Ca as its primary
relationship to carbonate chemistry parameters is, apparently, not very
robust. However, other symbiont-bearing species, non-symbiotic planktonic
foraminifera and deep-sea benthic foraminifera, may still be a viable option to use
B / Ca for carbonate chemistry reconstructions.