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Mar Biol
DOI 10.1007/s00227-015-2644-6
ORIGINAL PAPER
Responses of three tropical seagrass species to CO2 enrichment
Y. X. Ow · C. J. Collier · S. Uthicke
Received: 2 November 2014 / Accepted: 23 February 2015
© Springer-Verlag Berlin Heidelberg 2015
serrulata and H. uninervis, but not in T. hemprichii. Despite
higher productivity with pCO2 enrichment, leaf growth rates
in C. serrulata did not increase, while those in H. uninervis
and T. hemprichii significantly increased with increasing
pCO2 levels. While seagrasses can be carbon-limited and
productivity can respond positively to CO2 enrichment, vary-
ing carbon allocation strategies amongst species suggest
differential growth response between species. Thus, future
increase in seawater CO2 concentration may lead to an over-
all increase in seagrass biomass and productivity, as well as
community changes in seagrass meadows.
Introduction
Anthropogenic carbon emissions have led to atmospheric
carbon dioxide (CO2) rising by 40 % since pre-industrial
times (Raven et al. 2005). By the end of this century,
atmospheric CO2 is predicted to double from current levels
(Meehl et al. 2007; Collins et al. 2013). The rise in oceanic
CO2 concentration that follows is projected to decrease
seawater pH by 0.3–0.4 units (Caldeira and Wickett 2003;
Feely et al. 2004). This reduction can alter the carbonate
chemistry of seawater in terms of the relative proportion
of the dissolved inorganic carbon (DIC) species. Cur-
rent concentrations of CO2 and HCO3− in seawater are 8
and 1650 µmol kg−1 seawater, respectively (Koch et al.
2013). Under the projected decrease in seawater pH, the
proportion of CO2 will have greater proportional increase
(>250 %) than the other DIC constituents (
HCO−
3
: 24 %
and
CO2−
3
: −61 %) (Koch et al. 2013). The higher concen-
tration of utilisable carbon for photosynthesis (CO2 and
HCO3−) in acidified seawater may benefit marine macro-
phytes that are limited by the DIC concentration under cur-
rent conditions (Beer et al. 2002).
Abstract Increased atmospheric carbon dioxide leads to
ocean acidification and carbon dioxide (CO2) enrichment of
seawater. Given the important ecological functions of sea-
grass meadows, understanding their responses to CO2 will
be critical for the management of coastal ecosystems. This
study examined the physiological responses of three tropical
seagrasses to a range of seawater pCO2 levels in a labora-
tory. Cymodocea serrulata, Halodule uninervis and Thalas-
sia hemprichii were exposed to four different pCO2 treat-
ments (442–1204 μatm) for 2 weeks, approximating the
range of end-of-century emission scenarios. Photosynthetic
responses were quantified using optode-based oxygen flux
measurements. Across all three species, net productivity and
energetic surplus (PG:R) significantly increased with a rise in
pCO2 (linear models, P < 0.05). Photosynthesis–irradiance
curve-derived photosynthetic parameters—maximum photo-
synthetic rates (Pmax) and efficiency (α)—also increased as
pCO2 increased (linear models, P < 0.05). The response for
productivity measures was similar across species, i.e. simi-
lar slopes in linear models. A decrease in compensation light
requirement (Ec) with increasing pCO2 was evident in C.
Communicated by K. Bischof.
Y. X. Ow (*) · C. J. Collier
College of Marine and Environmental Science, James Cook
University, Townsville, QLD 4811, Australia
e-mail: yan.ow@my.jcu.edu.au
Y. X. Ow · S. Uthicke
Australian Institute of Marine Science, PMB No 3, Townsville,
QLD 4810, Australia
C. J. Collier
Centre for Tropical Water and Aquatic Ecosystem Research
(TropWATER), James Cook University, Cairns, QLD 4870,
Australia
Mar Biol
1 3
Seagrasses can be carbon-limited at the seawater DIC
composition under current CO2 concentrations, given other
conditions, such as light, nutrient availability and water
temperature are non-limiting (Beer and Koch 1996; Thom
1996; Zimmerman et al. 1997; Invers et al. 2001). Most
seagrasses utilise the C3 metabolism for carbon fixation
(Koch et al. 2013). Elevated partial pressure of CO2 (pCO2)
can increase carboxylation rates while reducing oxygena-
tion rates of ribulose-1,5-bisphosphate carboxylase–oxy-
genase (Rubisco), the initial carboxylating enzyme in C3
plants (Bowes and Ogren 1972; Koch et al. 2013). Fur-
thermore, the predominant DIC species,
HCO−
3
, appears
to be less efficiently utilised in seagrasses—the increase
in photosynthetic rates was much higher when seagrasses
were enriched with CO2 than with
HCO−
3
(Sand-Jensen and
Gordon 1984; Durako 1993; Beer and Koch 1996; Invers
et al. 2001). Although seagrasses have been shown to pos-
sess carbon-concentrating mechanisms (CCMs) to more
efficiently utilise
HCO−
3
, whether these CCMs could effec-
tively saturate the seagrasses to meet their DIC require-
ments under natural conditions remains to be seen (Beer
et al. 2002; Koch et al. 2013). Overall, it is thought that
higher pCO2 not only increases passive diffusion of CO2
for carbon fixation, but also lowers the loss of fixed car-
bon through photorespiration (Long et al. 2004). Labora-
tory and mesocosm experiments conducted over the short
and medium term have shown an optimisation of photo-
synthetic performance, such as light requirements, pho-
tosynthetic efficiency and pigment content in response to
CO2 (Zimmerman et al. 1997; Jiang et al. 2010; Campbell
and Fourqurean 2013b). This can result in higher rates of
carbon fixation with flow-on effects to growth rate, carbo-
hydrate content, biomass and reproductive output (Zim-
merman et al. 1997; Jiang et al. 2010; Campbell and Four-
qurean 2013b). In the field, higher seagrass productivity
and biomass have been observed near natural CO2 vents,
suggesting that acidification of seawater would benefit sea-
grass meadow productivity over the long term (Hall-Spen-
cer et al. 2008; Fabricius et al. 2011; Russell et al. 2013).
Different seagrass species might vary in the manner and
extent to which they respond to CO2 enrichment. No pre-
vious studies have directly compared species responses to
CO2 enrichment, but responses to CO2 depletion indicate
that species are not affected uniformly by changing pCO2
(Invers et al. 1997; Beer et al. 2006). This makes it diffi-
cult to determine whether findings are related to species or
methodological differences. Most studies had focussed on
temperate species, such as Zostera marina (Thom 1996;
Zimmerman et al. 1997; Palacios and Zimmerman 2007),
Zostera noltii (Alexandre et al. 2012) and Posidonia oce-
anica (Invers et al. 2002). Amongst temperate species,
Invers et al. (2001) demonstrated that pCO2 enhancement
of photosynthesis was higher in Pacific species (Z. marina
and Phyllospadix torreyi) than in Mediterranean species
(P. oceanica and Cymodocea nodosa). The few studies on
tropical seagrasses yielded mixed results. For example,
Jiang et al. (2010) showed increased growth and produc-
tivity in T. hemprichii, while T. testudinum showed lit-
tle change in biomass and productivity to increased pCO2
(Durako and Sackett 1993; Campbell and Fourqurean
2013a). Hence, differential response to CO2 enrichment
might exist between and within multi-species tropical sea-
grass meadows.
Differences in carbon utilisation and allocation strate-
gies exist amongst tropical seagrass species (Hemminga
and Duarte 2000; Uku et al. 2005). Species-specific differ-
ences in DIC uptake mechanisms would result in varying
abilities amongst species to utilise the extra DIC (Invers
et al. 2001; Uku et al. 2005; Campbell and Fourqurean
2013b). Species-specific carbon allocation strategies could
affect how responses to CO2 enrichment manifest at the
plant scale. For example, in species that invest a greater
proportion of biomass to belowground tissue, such as Hal-
odule uninervis and Thalassia hemprichii, there would be a
higher metabolic demand on aboveground tissue for photo-
synthetic carbon fixation (Terrados et al. 1999; Hemminga
and Duarte 2000; Tanaka and Nakaoka 2007). Increased
availability of CO2 in seawater could allow for increasing
photosynthetic capacity (e.g. more chlorophyll pigments,
enhanced shoot growth) and/or increased storage of car-
bohydrates to support respiratory demands (Zimmerman
et al. 1997; Jiang et al. 2010). In addition, small-bodied
ephemeral species, such as Halodule uninervis, exhibit
short turnover of leaves, while bigger and more persistent
species such as Cymodocea serrulata and Thalassia hemp-
richii have longer shoot plastochrone intervals (Hemminga
and Duarte 2000). Turnover rates of assimilated carbon
could influence carbon demand (Arp 1991; Hemminga
and Duarte 2000). Thus, various measures of productivity,
such as tissue growth rates, carbohydrates storage or shoot
production could vary amongst co-occurring species in
response to CO2 over different timescales.
Productivity of seagrass meadows is central to their
ecological functions as a food source, including for meg-
afauna such as dugongs and turtles, in bio-sequestration
(“blue carbon”), and substrate stabilisation (Duarte and
Chiscano 1999; Gacia and Duarte 2001; Fourqurean et al.
2012; Vafeiadou et al. 2013). Understanding how produc-
tivity responses to CO2 enrichment vary amongst species
is vital for predicting future ecological change. In the pre-
sent study, we quantified the photosynthetic and growth
responses of three tropical seagrass species to increasing
pCO2 levels, bracketing the range of different end-of-cen-
tury emission scenarios as predicted by IPCC (2013). This
allows for the quantification of the response to pCO2 lev-
els in seagrass productivity and growth. The three species
Mar Biol
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examined, Halodule uninervis, Cymodocea serrulata and
Thalassia hemprichii, are common seagrasses found in the
tropical Indo-Pacific region with contrasting growth strat-
egies, ranging from rapid growth in H. uninervis to slow
growth in C. serrulata and T. hemprichii (Hemminga and
Duarte 2000). It was hypothesised that pCO2 enrichment
would increase photosynthetic and growth rates, but rate of
responses may vary between species due to varying carbon
uptake and allocation strategies (Campbell and Fourqurean
2013b).
Materials and methods
Experimental species
Seagrasses were collected two to four weeks prior to the
start of the experiment. Seagrass species Cymodocea ser-
rulata and Halodule uninervis were collected from the
intertidal meadow at Cockle Bay, Magnetic Island, North-
ern Great Barrier Reef (19°10.88′S, 146°50.63′E) in March
2013. Average daily and average maximum photosyn-
thetically active radiations (PAR) at this site are 385 and
961 μmol m−2 s−1, respectively (Collier, unpublished).
Intact plugs of H. uninervis and sediment were collected
with a trowel and placed into a plastic pot lined with a plas-
tic bag. The bag was pulled up and secured over the sea-
grass to prevent moisture loss during transport. C. serrulata
was collected by excavating intact shoots with connected
horizontal rhizomes from the sediment before placing into
seawater-filled containers for transport to aquaria. Thalas-
sia hemprichii was collected from Green Island in the
Northern Great Barrier Reef (16°45.37′S, 145°58.19′E),
using a similar method to C. serrulata. At this site, aver-
age daily PAR was 344 μmol m−2 s−1 and average maxi-
mum PAR was 841 μmol m−2 s−1, respectively (Collier C,
unpublished). Average water temperatures at Cockle Bay
(2005–2012) and Green Island (2003–2012) were 26.2 and
26.6 °C, respectively (McKenzie et al. 2014). Seagrasses
were planted into orchid pots lined with a pool filter sock,
in a mud and sand (roughly 20:80) mixture, within 2 days
of collection. For acclimation, all species were kept in an
outdoor flow-through aquarium prior to the experiment,
under average light levels of 350 μmol m−2 s−1, average
seawater temperature of 25 °C and salinity at 35 ppt.
Experimental set-up
Seagrasses were exposed to four different seawater pCO2
concentrations in a flow-through system for two weeks
(Table 1). The experiment was conducted in an indoor
flow-through aquarium system at the Australian Institute of
Marine Sciences, Townsville. Sixteen glass aquaria with four
Table 1 Measured and calculated parameters, and average nutrient concentrations for control and three enriched pCO2 treatments
Water samples for DIC and nutrients (in duplicates) were taken every 5 days from each tank. Results were pooled and averaged over sampling times and tanks for each treatment (n = 4). Stand-
ard errors are given in brackets
pCO2
treatment
Measured parameters Calculated parameters Nutrient concentrations
pH range
(NBS scale)
Temp (°C) DIC
(μmol kg−1
SW)
TA
(μmol kg−1
SW)
pH (NBS
scale)
pCO2
(μatm)
HCO3−
(μmol kg−1
SW)
CO32−
(μmol kg−1
SW)
CO2
(μmol kg−1
SW)
NH4+ (µmol
L−1)
PO43− (µmol
L−1)
NO3− (µmol
L−1)
High 7.69–7.85 23.9 (0.2) 2146 (7) 2296 (3) 7.76 (0.02) 1204 (59) 2024 (4) 86.2 (4.0) 35.3 (1.8) 0.217 (0.02) 0.206 (0.05) 0.968 (0.70)
Intermediate 7.81–7.98 24.0 (0.2) 2120 (10) 2290 (2) 7.89 (0.02) 884 (52) 1980 (7) 113.4 (6.2) 25.9 (1.5) 0.210 (0.03) 0.167 (0.04) 0.700 (0.50)
Low 7.91–8.01 23.7 (0.2) 2084 (7) 2289 (2) 7.98 (0.01) 694 (20) 1930 (7) 133.2 (3.4) 20.5 (0.6) 0.223 (0.03) 0.211 (0.06) 0.914 (0.61)
Control 8.12–8.16 23.7 (0.2) 2012 (8) 2281 (1) 8.14 (0.01) 442 (6) 1814 (6) 184.5 (2.6) 13.0 (0.2) 0.210 (0.03) 0.184 (0.03) 0.923 (0.64)
Mar Biol
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replicates for each treatment (working volume 18 l) were
supplied with fresh filtered seawater from four header tanks.
Each aquarium contained all three species. Two sub-replicate
pots of each species were placed in each aquarium. pH lev-
els in the header tanks were monitored, as a proxy to con-
trol for CO2 input, with eight potentiometric sensors (±0.01
pH unit) calibrated on the NBS scale. The sensors are con-
nected to a feedback control system that regulates pH lev-
els via a CO2 gas injection system (AquaMedic, Germany).
Pumps and diffusers installed in mixing tanks and experi-
mental aquaria ensured thorough mixing of CO2. Additional
pH readings were taken regularly with a hand held pH probe
(pH probe: Eutech, USA; console: Oakton, USA) and com-
pared to Tris seawater standards (Batch 10, Supplied by A.
Dixon, Scripps Institute of Oceanography). Water tempera-
ture remained constant throughout the experiment around
24 °C (Table 1). Water samples, taken every 5 days, were
analysed for dissolved inorganic carbon (DIC) and total
alkalinity (AT) concentrations using a Vindta 3C analyser.
Carbonate system parameters (Table 1) were calculated by
measured values of AT, DIC, temperature and salinity by
USGS CO2calc software (Robbins et al. 2010). Illumination
was provided with LED lamps (Aqua Illumination) mounted
about 40 cm above the aquaria, providing 400 μmol m−2 s−1
of light set on a 12-h light/dark photoperiod. Duplicate water
samples collected from each individual aquaria every 5 days
were filtered (0.45 μm pore size) before they were analysed
for dissolved inorganic nitrogen and phosphorus concentra-
tion according to Ryle et al. (1981).
Photosynthetic response
Photosynthetic rates and respiration of the second young-
est leaf (rank 2) of a haphazardly chosen shoot from each
pot were measured using optical oxygen sensors (“optode”,
PreSens, Sensor spots-Pst3) and a PreSens Oxy 4 four-
channel fibre-optic oxygen meter after two weeks. While
the authors acknowledge that seagrasses could be sensi-
tive to physical manipulations such as removing leaves
(Schwarz et al. 2000), care was taken to reduce the impact
on leaves such as using the whole leaf and gently rub-
bing epiphytes off with fingers instead of scrapping with a
blade. Small transparent acrylic chambers (200 mL) were
set in an array of four (i.e. four separate chambers allowing
four parallel measures) and incubated at 25 °C water tem-
perature using a flow-through water system connected to
a water bath (Lauda, Ecoline RE 106). Stirrer bars placed
within the chambers provided even stirring. The leaves
were held upright in the chamber to mimic natural orien-
tation. Oxygen consumption (dark respiration) was meas-
ured over a 20-min period in the dark. Photosynthetic rates
were then measured on the same leaf over a series of light
steps (10, 30, 70, 110, 220, 400, 510 μmol m−2 s−1) (Aqua
Illumination LED), with each light step lasting 20 min.
Seawater within the chambers was replaced with fresh
media every two to three steps. Oxygen concentration data
in the chambers were logged every 5 s, and respiration and
production rates were calculated by fitting a linear regres-
sion. Rates were normalised to the dry weight of the leaf.
Leaves were dried at 60 °C for 48 h before weighing. Ini-
tial periods of incubation (~5 min) prior to stabilisation of
photosynthetic rates were omitted from regressions. Each
optode was calibrated according to Collier et al. (2011).
Net productivity (NP) was taken to be the photosynthetic
rate measured at 400 μmol m−2 s−1, which was the experi-
mental light level. Energetic surplus (PG:R) was calculated
as the ratio of gross productivity (sum of net photosynthetic
rate and dark respiration rate) to dark respiration rate (Zim-
merman et al. 1997). To determine photosynthetic parame-
ters, photosynthesis versus irradiance (P–E) data plots were
fitted to the adapted hyperbolic tangent model equation of
(Jassby and Platt 1976):
where Pmax is the maximal photosynthetic rate (mg
O2 g−1 DW h−1), E is irradiance (μmol m−2 s−1), and α
described photosynthetic efficiency via the gradient of the
curve at limiting irradiances (mg O2 μmol−1). Saturating
irradiance (Ek) is the light level at which photosynthesis
initially reaches the maximum rate, and compensation irra-
diance (Ec) is the light level when photosynthetic rate is
equal to respiration rate.
Determination of growth rates
Growth was measured following Short and Duarte (2001).
All shoots from each pot were marked at the top of the
sheath with a needle at the start of the experiment. At the
end of the experiment, the shoots were harvested. The
length of new tissue growth was excised, dried at 60 °C for
48 h and weighed for determination of weight of new leaf
growth. Leaf tissue growth was normalised to the above-
ground biomass of its respective pot to derive relative leaf
growth rates (RGR).
Specific leaf area (SLA) was calculated from biomass
and areal measurements of leaves. Specific leaf area refers
to the total leaf area normalised by the total biomass of the
leaves and could be used to infer whole-plant changes in
leaf biomass and area in response to pCO2 enrichment (Chi-
ariello et al. 1989). Leaves were separated from shoots and
placed on a flat surface. Areal measurement of leaves was
then carried out by capturing a clear image of all the leaves
and analysing with CPCe software (version 3.6) (Kohler
and Gill 2006). Finally, the leaves were dried at 60 °C for
48 h and weighed to obtain biomass measurements.
P
=Pmax ×tanh
αPmax
E
Mar Biol
1 3
Chlorophyll content
A young mature leaf (rank 2) from each pot was collected
and stored immediately at −20 °C at the end of the experi-
ment. To determine chlorophyll concentration, a 10- to
15-mm section of leaf was cut from the middle of a fully
mature leaf and the width of the leaf segment was meas-
ured using a pair of callipers. The leaves were blotted dry
and weighed before they were ground in a chilled mortar.
Depending on the species and the weight of the leaf seg-
ment, 5–6 mL of cold (4 °C) 90 % acetone was added to
extract chlorophyll from the sample. The solution was gen-
tly shaken, left in the dark to extract for 24 h at 4 °C and
then centrifuged at 2680 g for 4 min to settle the pellet. The
extract was measured for chlorophyll concentration accord-
ing to Granger and Izumi (2002).
Non-structural carbohydrate (NSC) content
Roots and rhizomes were dried at 60 °C for 48 h, before
being finely ground in a bead beater (Daintree Scientific).
Four replicate samples per treatment and species were sent
to the Agriculture and Food Sciences laboratory in Univer-
sity of Queensland for non-structural carbohydrate content
analysis. Briefly, soluble carbohydrates were extracted
twice with 80 % ethanol at 80 °C for 10 min from 200 mg
of ground plant material. Extracts were then passed through
a de-colourising column to remove phenolic compounds.
After acid hydrolysis, the amount of soluble carbohy-
drates was assayed with ferricyanide reagent and absorb-
ance measured on a UV–Vis spectrophotometer at 420 nm
(McCleary and Codd 1991).
Starch content was analysed according to Karkalas
(1985). Residue from the soluble carbohydrate extraction
was solubilised in boiling water. After cooling to room
temperature, samples underwent enzyme digestion where
amylase and amyloglucosidase were added. After incuba-
tion, the concentration of glucose is measured using a com-
mercially available glucose oxidase/peroxidase (GOPOD)
testing reagent (Megazyme). Absorbance was then meas-
ured at 510 nm.
Total non-structural carbohydrate (NSC) content, which
was the sum of the amount of soluble carbohydrate and
starch content, was expressed as milligrams dry weight−1
of tissue.
Statistical analyses
All statistical analyses were carried out with R software (R
Development Core Team 2011). Changes in photosynthetic
and growth responses were tested using linear models with
average pCO2 levels for each treatment as explanatory
variable. Data from sub-replicate pots from each tank were
averaged for the analysis. Assumptions of homogeneity of
variances and normality were checked using box plots and
residual plots. To satisfy the assumptions, photosynthetic
efficiency (α) and compensation irradiance (Ec) for T. hem-
prichii were square-root-transformed prior to analysis. One
data point was identified as an outlier (>2 SD from mean of
remaining replicates) in each of the PG:R and α dataset and
was subsequently removed. To examine species differences
in productivity and growth responses to increasing pCO2,
confidence intervals (CI) of the slopes (degree of response
per 100 µatm rise in pCO2) from linear models were calcu-
lated and compared.
Results
Experimental parameters
Water temperature (23.7–24.0 °C) and salinity (35 ppt)
in the experimental tanks were near-constant through-
out the experiment (Table 1). Carbonate system param-
eters of the enriched pCO2 treatments remained well
within the target range (control pCO2 = 442 ± 6 μatm;
low pCO2 = 694 ± 20 μatm; intermediate
pCO2 = 884 ± 52 μatm; high pCO2 = 1204 ± 59 μatm)
(Table 1). Inorganic nutrient concentrations were similar
between tanks and averaged to an ammonium concentration
of 0.22 ± 0.01 μM, nitrate concentration of 0.88 ± 0.3 μM
and phosphate concentration of 0.19 ± 0.02 μM.
Photosynthetic performance
Carbon dioxide enrichment increased seagrass net productiv-
ity (NP). Under the chosen light level (400 μmol m−2 s−1),
NP significantly increased with increasing pCO2 levels for
all species (Fig. 1; Table 2). Across species, the increase
in NP ranged from 0.757 to 1.040 mg O2 g−1 DW h−1 for
every 100 µatm increase in pCO2; however, no species dif-
ference in the slope was detected (based on overlapping
confidence intervals) (Table 2).
Energetic surplus, or gross photosynthetic to respiration
ratios (PG:R), significantly increased with increasing pCO2
for all three species (Fig. 1; Table 2). No distinct differ-
ences in the slopes (0.32–0.47 units as pCO2 increased by
100 µatm, Table 2) indicated that PG:R responses in the dif-
ferent species were similar.
Photosynthetic rates in all three species exhibited typical
P–E (PAR) response curves. Photosynthetic rates increased
linearly (initial slope, α) with light under limiting irradi-
ances, before levelling off at the maximum photosynthetic
rate (Pmax) past saturating irradiance (Ek). Photosynthesis–
irradiance (P–E) curves demonstrated a good fit (R2 > 0.85;
P < 0.05) to the adapted hyperbolic tangent model.
Mar Biol
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Increasing pCO2 levels significantly increased maximum
photosynthetic rates (Pmax) for all three species (Table 2;
Fig. 2). Maximal photosynthetic rates (Pmax) increased by
0.677–0.929 mg O2 g−1 DW h−1 for every 100 µatm rise in
seawater pCO2. Photosynthetic efficiency (α) significantly
increased with pCO2 levels across all species (Table 2;
Fig. 2). Photosynthetic efficiency increased by 0.004–0.013
with every 100 µatm rise in pCO2 level across all species.
Saturating irradiance (Ek) was not significantly altered
by the pCO2 treatments (Table 2; Fig. 2). Increasing pCO2
enrichment reduced compensation irradiance (Ec) for C.
serrulata and H. uninervis (Table 2; Fig. 2); however, in
T. hemprichii, Ec was not affected by pCO2 enrichment
(Table 2; Fig. 2).
Overall, most photosynthetic parameters responded sig-
nificantly to pCO2 increase. Although some variation exists
in the slopes, overlapping CIs indicated that species differ-
ences were non-significant (Table 2).
Plant-scale responses (leaf growth and rhizome
carbohydrates)
Leaf growth responses to pCO2 enrichment differed
between species. C. serrulata did not show differences in
growth rates with increasing pCO2 levels (Fig. 3; Table 2).
By contrast, growth rates increased with pCO2 enrichment
for H. uninveris (Fig. 3; Table 2) and T. hemprichii (Fig. 3;
Table 2). Slopes for relative leaf growth rates (RGR) were
about 0.001 units for every 100 µatm increase in pCO2 for
both species.
For plant-scale response to pCO2, amongst the three
species only T. hemprichii displayed an increase in spe-
cific leaf area (SLA; leaf area per unit dry weight) with
increasing pCO2 (Table 2). No significant effects of pCO2
on chlorophyll content were detected for all three spe-
cies at the end of the experiment (Table 2). Starch con-
tent in C. serrulata rhizomes decreased as pCO2 levels
increased from 442 to 1204 µatm (Table 2). There were no
significant changes for starch content in H. uninervis and
T. hemprichii rhizomes with pCO2 enrichment (Table 2).
Neither NSC nor soluble carbohydrate content showed
significant changes with pCO2 enrichment for all three
species (Table 2).
Discussion
Under predicted future scenarios of ocean acidification,
marine macrophytes on coral reefs could be amongst the
“winners”, because growth and survival will be enhanced
400 600 800 1000 1200
2
4
6
8
10
12
400600 800 1000 1200 400600 800 1000 1200
C. serrulata H. uninervisT. hemprichii
Energetic surplus (P :R)
G
Net Productivity
(mg O g DW h )
-1
-1
2
pCO
2
y = 8.669 + 0.008 x
P = 0.001
y = 6.560 + 0.010 x
P < 0.001
y = 9.755 + 0.009 x
P = 0.004
y = 4.194 + 0.004 x
P = 0.015
y = 3.988 + 0.003 x
P = 0.002
y = 3.434 + 0.005 x
P = 0.014
5
10
15
20
25
Fig. 1 Linear model fits (dotted lines indicate 95 % confidence intervals) for net productivity and energetic surplus (PG:R) of C. serrulata, H.
uninervis and T. hemprichii in response to pCO2 enrichment. N = 4
Mar Biol
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by higher CO2 availability (Fabricius et al. 2011; Koch
et al. 2013). The present study supports this hypothesis
as all three species benefitted from higher rates of photo-
synthesis (i.e. Pmax increased) and adjusted photosynthetic
kinetics in response to pCO2 enrichment of coastal seawa-
ter. Enhanced photosynthetic responses and growth rates
were observed after two weeks of exposure to enriched
pCO2. Although photosynthetic responses were very similar
Table 2 Linear models for all response variables measured
All parameters were analysed with pCO2 treatments as explanatory variable and tanks as replicates (n = 4). Slopes (pCO2) and 95 % confidence
intervals (CI) are expressed per 100 µatm pCO2. * P < 0.05; ** P < 0.01; *** P < 0.001. Parameters: NP—net productivity, PG:R—gross photo-
synthesis to respiration ratio, Pmax—maximum photosynthetic rate, α—photosynthetic efficiency, Ek—saturating irradiance, Ec—compensation
irradiance, RGR—relative growth rate, SLA—specific leaf area, chl a—chlorophyll a, chl b—chlorophyll b, NSC—total non-structural carbohy-
drates. α and Ec have been square-root-transformed for T. hemprichii
Species Parameter Intercept PCO295 % CI R2F (1,14) P
C. serrulata NP 8.669 0.757 (0.352, 1.162) 0.502 16.094 0.001**
PG:R3.434 0.474 (0.111, 0.838) 0.313 7.845 0.014*
Pmax 9.532 0.677 (0.291, 1.062) 0.468 14.179 0.002**
α0.052 0.006 (0.002, 0.010) 0.427 12.190 0.004**
Ek198.834 −4.748 (−11.141, 1.646) 0.093 2.537 0.134
Ec48.540 −2.557 (−4.588, −0.525) 0.295 7.288 0.017*
RGR 0.030 −2.811 × 10−5(−4.455 × 10−4, 3.893 × 10−4) 0.070 0.021 0.887
SLA 405.793 −0.346 (−5.883, 5.190) 0.070 0.018 0.895
chl a 0.795 −0.004 (−0.038, 0.031) 0.068 0.049 0.828
chl b 0.404 −0.004 (−0.020, 0.013) 0.055 0.216 0.649
NSC 10.450 0.026 (−0.844, 0.895) 0.071 0.004 0.951
Sol carbs 10.020 0.049 (−0.823, 0.922) 0.070 0.015 0.906
Starch 0.424 −0.023 (−0.041, −0.004) 0.277 6.741 0.021*
H. uninervis NP 9.755 0.867 (0.318, 1.416) 0.411 11.459 0.004**
PG:R3.988 0.322 (0.140, 0.505) 0.471 14.328 0.002**
Pmax 9.866 0.857 (0.314, 1.401) 0.410 11.434 0.004**
α0.090 0.004 (0.001, 0.008) 0.276 6.337 0.026*
Ek110.927 2.866 (−2.296, 8.028) 0.027 1.418 0.254
Ec37.282 −1.413 (−2.513, −0.312) 0.305 7.572 0.016*
RGR 0.018 0.001 (7.240 × 10−4, 1.890 × 10−3) 0.596 23.128 0.000***
SLA 450.908 1.094 (−5.010, 7.199) 0.060 0.148 0.706
chl a 1.558 −0.009 (−0.081, 0.062) 0.065 0.080 0.782
chl b 0.776 −0.005 (−0.050, 0.041) 0.068 0.047 0.831
NSC 17.196 −0.077 (−0.796, 0.641) 0.067 0.054 0.820
Sol carbs 2.469 0.050 (−0.122, 0.223) 0.042 0.390 0.542
Starch 14.726 −0.128 (−0.751, 0.495) 0.057 0.194 0.667
T. hemprichii NP 6.560 1.040 (0.746, 1.334) 0.791 57.586 0.000***
PG:R4.194 0.410 (0.094, 0.730) 0.309 7.712 0.015*
Pmax 7.720 0.929 (0.691, 1.168) 0.822 70.109 0.000***
Sqrt α0.215 0.013 (0.006, 0.019) 0.518 17.134 0.001**
Ek177.312 −2.548 (−8.231, 3.135) 0.005 0.925 0.353
Sqrt Ec6.67 −0.191 (−0.387, 0.004) 0.237 4.448 0.054
RGR 0.025 0.001 (7.277 × 10−4, 2.114 × 10−3) 0.550 19.330 0.001***
SLA 333.021 6.169 (1.158, 11.182) 0.285 6.971 0.019*
chl a 0.934 −0.013 (−0.040, 0.014) 0.007 1.110 0.310
chl b 0.453 −0.008 (−0.022, 0.006) 0.028 1.430 0.252
NSC 7.477 0.624 (−0.230, 1.478) 0.089 2.457 0.139
Sol carbs 1.894 0.227 (−0.241, 0.696) 0.005 1.082 0.316
Starch 5.574 0.398 (−0.221, 1.016) 0.057 1.900 0.190
Mar Biol
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5
10
15
20
25
Pmax (mg O g DW h )
-1
2-1
0.05
0.10
0.15
0.20
Photosynthetic efficiency
100
150
200
250
Ek ( mol PAR m s )
-2 -1
µ
Ec ( mol PAR m s
)
-2 -1
µ
0
20
40
60
C. serrulata
pCO2
H. uninervis
400 600 800 1000 1200 400 600 800 1000 1200 400 600 800 1000 1200
T. hemprichii
y = 9.532 + 0.007x
P = 0.002
y = 0.052 + 5.919*10 x
P = 0.004
-5
y = 198.834 - 0.047x
P = 0.134
y = 48.540 - 0.026x
P = 0.017
y = 37.282 - 0.014x
P = 0.016
y = 110.927 + 0.029x
P = 0.254
y = 0.090 + 4.407*10 x
P = 0.026
-5
y = 9.866 + 0.009x
P = 0.004
y = 7.720 + 0.009x
P < 0.001
y = 0.036 + 8.387*10 x
P = 0.001
-5
y = 177.312 - 0.025x
P = 0.352
y = 41.747 - 0.019x
P = 0.053
Fig. 2 Parameters derived from P–E curves. Top row—maximal pho-
tosynthetic rates (Pmax); second row—photosynthetic efficiency (α);
third row—saturating irradiance (Ek); bottom row—compensation
irradiance (Ec). Data were fitted with linear models (dotted lines 95 %
confidence intervals). N = 4
Mar Biol
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between species, magnitude of plant-scale responses was
species specific.
Physiological responses to pCO2 enrichment
Carbon dioxide enrichment increased net productivity (NP)
and energetic surplus (PG:R) in all three species tested. The
increase in NP and PG:R was quantified as 0.757–1.040 and
0.322–0.474 units per 100 μatm pCO2, respectively. This
response is consistent with previous findings that photosyn-
thetic rates increase with pCO2 in seagrasses (Thom 1996;
Zimmerman et al. 1997; Invers et al. 2002; Alexandre et al.
2012). Having greater energetic surplus could indicate
flow-on effects to plant-scale responses, such as growth and
shoot production (Invers et al. 2002; Palacios and Zimmer-
man 2007). Energetic status can affect growth, response to
physical disturbances such as grazing (Eklöf et al. 2009),
abundance and spatial distribution (Dennison et al. 1993;
Zimmerman et al. 1997), and even reproductive output
(Palacios and Zimmerman 2007).
Maximum photosynthetic rates (Pmax) and efficiency (α)
in all species were raised at higher pCO2 levels although
chlorophyll content was not affected. Photoacclimation
had been reported for several temperate and tropical sea-
grass species (Invers et al. 1997; Zimmerman et al. 1997;
Jiang et al. 2010; Alexandre et al. 2012), but this is the first
study to compare short-term responses to CO2 enrichment
amongst three tropical species in one experiment. In gen-
eral, P–E curves did not show differences between species
in their photosynthetic response to CO2 enrichment. The
responses over the range of pCO2 in photosynthetic param-
eters were similar between species (similar slope, as shown
by overlapping confidence intervals). Maximum relative
electron transport rate (rETRmax) could increase with CO2
enrichment (Jiang et al. 2010). While comparisons between
quantum efficiency and O2 production need to be viewed
with caution (Beer et al. 2001), these findings indicate that
there was a stronger response of Pmax in the present study
using respirometry per 100 µatm rise in pCO2 (7.86 %
increase at 1204 µatm for 2 weeks) compared with rETRmax
(3.37 % increase in rETRmax at ~807 µatm (pH 7.75) for
3 weeks, Jiang et al. 2010). Temperate species increased
Pmax with pCO2 enrichment too, but showed much more
variable response rates per 100 µatm pCO2 (Zostera marina
0.59 % increase per 100 µatm pCO2 for 3 weeks, Zim-
merman et al. 1997; Zostera noltii 9.64 % increase per
100 µatm pCO2 for 5 months, Alexandre et al. 2012).
Overall, our study concurs that seagrasses can raise
productivity from pCO2 enrichment, at least in the short
term (2 weeks exposure). The response of net productiv-
ity and PG:R to increasing pCO2 followed a linear trend,
indicating that any future change in pCO2 could have an
effect on seagrass productivity. In numerous studies on
terrestrial plants, the initial stimulation of photosynthe-
sis and growth in elevated CO2 can decline over time, as
Rubisco is down-regulated, carbohydrates accumulate and
nitrogen content decreases (Stitt and Krapp 1999). Obser-
vations of high seagrass abundance at CO2 seep sites indi-
cate seagrass productivity might continually benefit from
pCO2 enrichment over the long term (decades) (Fabricius
et al. 2011). However, interaction from other co-occurring
influences, such as the lowered competition from photo-
synthetic calcifiers or intrinsic genetic capacity to respond
within the population, should be taken into account too.
Whether such longer term acclimatory responses to pCO2
enrichment would manifest in tropical seagrasses remains
unknown. Furthermore, the capacity of seagrasses to
respond to increasing pCO2 is likely to depend on other
limiting factors such as nutrient or light availability (Invers
et al. 1997).
0.020
0.025
0.030
0.035
0.040
0.045
pCO
C. serrulata H. uninervis
Relativegrowthrate(mgmgDWd
)
-1-1
y = 0.030 - 2.911*10 x
P = 0.887
-7 y = 0.018 + 1.307*10 x
P < 0.001
-5
400 600 800 1000 1200
400 600 800 1000 1200 400 600 800 1000 1200
T. hemprichii
y = 0.025 + 1.421*10 x
P < 0.001
-5
2
Fig. 3 Linear model fits (dotted lines indicate 95 % confidence intervals) for relative growth rates of C. serrulata, H. uninervis and T. hemp-
richii in response to pCO2 enrichment (mgDW mg−1DW day−1). N = 4
Mar Biol
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Light availability is often the primary limiting factor
for seagrass productivity. Exposure to low light conditions
(such as high turbidity and high epiphyte loads) is a com-
mon factor causing seagrass loss (Waycott et al. 2009; Col-
lier et al. 2012). Here, a lowering in the light requirement
to meet respiratory demands (Ec) and an increase in light
efficiency (α) were observed with increasing pCO2. This
could imply that a lower amount of light energy would be
required to meet metabolic balances (Schwarz et al. 2000;
Long et al. 2004). Therefore, CO2 enrichment could poten-
tially increase the tolerance of seagrasses to conditions of
low light, for example during flood plume events. In con-
trast, there was no change in the light level required to
reach maximum photosynthetic rates (Ek). pCO2 enrich-
ment increased Ek in Z. marina (Zimmerman et al. 1997),
Z. noltii (Alexandre et al. 2012) and T. hemprichii (Jiang
et al. 2010). An increase in Pmax without a simultaneous
rise in light requirement might be explained by the strong
upregulation of photosynthetic efficiency (α). pCO2 enrich-
ment can affect light requirements, and this could be impor-
tant for how seagrasses will respond to changing environ-
mental conditions—including water quality—in the future.
Seagrasses can utilise the predominant
HCO−
3
in seawa-
ter via carbon-concentrating mechanisms (CCMs), some-
what alleviating the problem of carbon limitation at higher
pH (Durako 1993; Bjork et al. 1997; Uku et al. 2005;
Campbell and Fourqurean 2013b). In favourable conditions
where other factors are non-limiting, CCMs might cause
some seagrasses to be carbon-saturated (Schwarz et al.
2000; Beer et al. 2002). Such mechanisms were thought
to be less efficient in Thalassia (T. hemprichii and T. tes-
tudinum), rendering this genus less capable of utilising
HCO−
3
than other species (Uku et al. 2005; Campbell and
Fourqurean 2013b). Hence, an increase in CO2 availabil-
ity would be important in raising productivity for Thalas-
sia. Cymodocea and Halodule reportedly possess CCMs
that allow them to utilise
HCO−
3
under ambient conditions
(Schwarz et al. 2000; Uku et al. 2005). Both species were
able to increase photosynthetic rates under enriched pCO2
conditions, where the relative increase in CO2 was much
greater than that in
HCO−
3
(Koch et al. 2013). Both species
have been observed to become more dominant and have
increased biomass around highly enriched volcanic CO2
seeps (Takahashi et al. under review). All the three species
tested responded at similar rates in terms of net productiv-
ity. It appears that regardless of whether the species possess
CCMs or not, CO2 enrichment can increase photosynthetic
rates for different species to a similar extent.
Sinks for carbon: plant-scale responses
As a result of increased photosynthetic rates and relatively
stable dark respiration rates, energetic surplus (PG:R)
was increased at higher pCO2 for all species. The rate of
increase with pCO2 levels in PG:R was similar between the
three species. There are a number of possible sinks for this
additional fixed C. In this short-term study, we measured
growth and storage carbohydrates in rhizomes, but other
sinks, such as biomass or sexual reproduction, exist.
Response in leaf growth rates to pCO2 enrichment dif-
fered between species. Growth of H. uninervis and T.
hemprichii responded strongly, but not in C. serrulata.
Specifically, relative growth rate (RGR) increased signifi-
cantly, and in T. hemprichii, an increase in leaf area rela-
tive to leaf biomass (SLA) was also observed. Leaf growth
response appeared to vary amongst the limited number of
studies on tropical seagrass. While Campbell and Four-
qurean (2013a) found no differences in leaf growth rates
with pCO2 enrichment in T. testudinum, Jiang et al. (2010)
showed a 2.63 % rate increase in leaf growth (per 100 µatm
pCO2) at pH 7.76 after 3 weeks of exposure in T. hemp-
richii. This is about half of the 5.62 % rate of increase in
leaf growth observed in T. hemprichii here. The effect of
CO2 enrichment on growth rate can be influenced by the
tissue nutrient requirement of the species and other pre-
vailing environmental conditions (Zimmerman et al. 1997;
Palacios and Zimmerman 2007; Jiang et al. 2010; Alexan-
dre et al. 2012; Campbell and Fourqurean 2013a). Under
nutrient limitation, seagrasses could direct the fixed carbon
towards carbon-rich tissues such as belowground tissues,
instead of investing in nitrogen-rich tissue such as leaves
(Poorter et al. 1996; Stitt and Krapp 1999). C. serrulata,
which has a higher proportion of its biomass existing as
shoots and leaves (Hemminga and Duarte 2000), might
have required a simultaneous increase in nitrogen availabil-
ity in order to assimilate the carbon into its leaves. Temper-
ature strongly influences carbon and nitrogen metabolism
(Touchette and Burkholder 2007) and could also affect the
growth response of seagrasses to pCO2 (Atkin et al. 2005;
Collier et al. 2011). Whether these, and other, environmen-
tal parameters affected the differences in growth response
amongst species warrants further investigation.
Sink strength, or carbon demand, could modulate
growth response in seagrasses to CO2 enrichment, similar
to that in terrestrial C3 species (Arp 1991; Poorter et al.
1996). Increased energetic surplus from pCO2 enrichment
indicates extra assimilated carbon available for storage,
growth and metabolism. While little change in NSC con-
tent was observed in the present study, seagrasses do pos-
sess a number of alternative “carbon sinks”, with the size
of carbon demand for each sink dependent on species-spe-
cific growth strategy (Doust 1981; Hemminga and Duarte
2000) (described further below). For example, the shorter
time taken for shoot initiation for H. uninervis (average
7.9 days), compared to C. serrulata (average 21.2 days) and
T. hemprichii (average 38.5 days), meant a faster turnover of
Mar Biol
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aboveground biomass for H. uninervis (Duarte 1991; Marba
and Duarte 1998). Therefore, H. uninervis might have a
strong carbon demand in leaf growth. The relatively greater
proportion of belowground biomass in H. uninervis and T.
hemprichii suggests higher storage potential and metabolic
demand (Duarte 1991; Marba and Duarte 1998). In these
species, more carbon could be directed to belowground
biomass, and/or leaf area could be expanded to increase
photosynthetic rates. Extra carbon could also be directed
to increased shoot production and flowering, as observed
in Z. marina after 1 year of CO2 enrichment (Palacios and
Zimmerman 2007). Essentially, the extra carbon assimilated
could be directed to a single “sink”, such as the growth of
new leaves, or it could be spread amongst various metabolic
functions and storage organs. The latter makes distinguish-
ing the fate of the extra carbon complicated, especially for
short-term experiments such as this study.
In general, our results imply that the availability of
higher pCO2 might alter future interspecific competition
amongst co-occurring species. With deteriorating water
quality, i.e. low light and high nutrients, species that are
able to readily assimilate and mobilise carbon resources
with the extra CO2 might outcompete other species. Under
optimal growth conditions, species that are able to rapidly
utilise the extra CO2 to occupy more “space”, i.e. either
upwards on vertical stems or via horizontal rhizomes, could
potentially increase their abundance and distribution.
Seagrasses as “winners”?
The ability of marine macro-autotrophs to utilise the greater
CO2 availability suggests that they will thrive under future
scenarios of climate change (Koch et al. 2013). This pre-
sent study has built evidence to support this, with increased
growth, productivity and biomass from pCO2 enrichment
(Zimmerman et al. 1997; Invers et al. 2002; Palacios and
Zimmerman 2007; Jiang et al. 2010; Campbell and Four-
qurean 2013a). This study has also quantified the change
in physiological parameters with respect to CO2 enrich-
ment. Surveys at natural CO2 seeps further attest to this,
where greater seagrass cover, shoot density, root biomass
and productivity were reported at low pH/high CO2 sites
when compared to adjacent high pH/low CO2 sites (Hall-
Spencer et al. 2008; Fabricius et al. 2011; Russell et al.
2013; Takahashi et al. under review). For calcifying marine
autotrophs, such as hard corals, foraminifera and coralline
algae, ocean acidification lowers calcification and growth
rates and increases rates of bio-erosion (Kuffner et al. 2007;
de Putron et al. 2010; Fabricius et al. 2011; Doo et al. 2014;
James et al. 2014), and calcifying organisms might be out-
competed (Russell et al. 2011; Short et al. 2014). A shift
in the ecological diversity and functions in coastal habitats
might result.
This study demonstrated that tropical seagrasses can
increase their photosynthetic rates, adjust photosynthetic
performance and increase growth rates in response to CO2
enrichment. Varying plant-scale responses to CO2 enrich-
ment between species might affect interspecies competi-
tion, especially in mixed species meadows (Takahashi et al.
under review). Under CO2 enrichment scenarios, carbon
utilisation and allocation traits between seagrass species
come into consideration, such as carbon uptake mecha-
nisms, the ability to assimilate additional carbon and the
response time of rhizome and shoot elongation to DIC
enrichment (Hall-Spencer et al. 2008; Russell et al. 2013;
Takahashi et al. under review). Furthermore, environmen-
tal conditions such as light and nutrients, which result from
water quality changes, could limit species response to CO2
enrichment in the long term. Changes in species compo-
sition and diversity in tropical seagrass meadows could
potentially impact the functional diversity offered by these
productive ecosystems. Interspecific variation amongst sea-
grasses in response to ocean acidification, over different
temporal scales, deserves further examination.
Acknowledgments We thank Martina De Freitas Prazeres, Niko-
las Vogel and Michelle Liddy for assistance with the set-up and run-
ning of the experiment. Miwa Takahashi and Lucas Langois provided
assistance in the field. The work was supported by funding from the
Australian Government’s National Environmental Research Program
and the Great Barrier Reef Foundation (Project title: Investigating the
effects of seagrass productivity on pH at local scales).
References
Alexandre A, Silva J, Buapet P, Bjork M, Santos R (2012) Effects of
CO2 enrichment on photosynthesis, growth, and nitrogen metabo-
lism of the seagrass Zostera noltii. Ecol Evol 2:2620–2630
Arp WJ (1991) Effects of source-sink relations on photosynthetic
acclimation to elevated CO2. Plant Cell Environ 14:869–875
Atkin OK, Bruhn D, Hurry VM, Tjoelker MG (2005) The hot and
the cold: unravelling the variable response of plant respiration to
temperature. Funct Plant Biol 32:87–105
Beer S, Koch E (1996) Photosynthesis of marine macroalgae and sea-
grasses in globally changing CO2 environments. Mar Ecol Prog
Ser 141:199–204
Beer S, Bjork M, Gademann R, Ralph P (2001) Measurements
of photosynthetic rates in seagrasses. In: Short FT, Coles RC
(eds) Global seagrass research methods. Elsevier Science B.V.,
Amsterdam, pp 183–198
Beer S, Bjork M, Hellblom F, Axelsson L (2002) Inorganic carbon
utilisation in marine angiosperms (seagrasses). Funct Plant Biol
29:349–354
Beer S, Mtolera M, Lyimo T, Bjork M (2006) The photosynthetic per-
formance of the tropical seagrass Halophila ovalis in the upper
intertidal. Aqua Bot 84:367–371
Bjork M, Weil A, Semesi S, Beer S (1997) Photosynthetic utilisation
of inorganic carbon by seagrasses from Zanzibar, East Africa.
Mar Biol 129:363–366
Bowes G, Ogren WL (1972) Oxygen inhibition and other properties
of soybean ribulose 1,5-diphosphate carboxylase. J Biol Chem
247:2171–2176
Mar Biol
1 3
Caldeira K, Wickett ME (2003) Anthropogenic carbon and ocean pH.
Nature 425:365
Campbell JE, Fourqurean JW (2013a) Effects of in situ CO2 enrich-
ment on the structural and chemical characteristics of the sea-
grass Thalassia testudinum. Mar Biol 160:1465–1475
Campbell JE, Fourqurean JW (2013b) Mechanisms of bicarbonate use
influence the photosynthetic carbon dioxide sensitivity of tropical
seagrasses. Limnol Oceanogr 58:839–848
Chiariello NR, Mooney HA, Williams K (1989) Growth, carbon alloca-
tion and cost of plant tissues. In: Percy RW, Ehleringer J, Mooney
HA, Rundel PW (eds) Plant physiology ecology: field methods and
instrumentation. Chapman and Hall, New York, p 457
Collier CJ, Uthicke S, Waycott M (2011) Thermal tolerance of two
seagrass species at contrasting light levels: implications for
future distribution in the Great Barrier Reef. Limnol Oceanogr
56:2200–2210
Collier CJ, Waycott M, McKenzie LJ (2012) Light thresholds derived
from seagrass loss in the coastal zone of the northern Great Bar-
rier Reef, Australia. Ecol Indic 23:211–219
Collins M, Knutti R, Arblaster J, Dufresne JL, Fichefet T, Friedling-
stein P, Gao X, Gutowski WJ, Johns T, Krinner G, Shongwe M,
Tebaldi C, Weaver AJ, Wehner M (2013) Long-term Climate
change: projections, commitments and irreversibility. In: Stocker
TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nau-
els A, Xia Y, Bex V, Midgley PM (eds) Climate change 2013: the
physical science basis Contribution of Working Group I to the
Fifth Assessment Report of the Intergovernmental Panel on Cli-
mate Change. Cambridge University Press, Cambridge
de Putron SJ, McCorkle DC, Cohen AI, Dillon AB (2010) The impact
of seawater saturation state and bicarbonate ion concentration on
calcification by new recruits of two Atlantic corals. Coral Reefs
30:321–328
Dennison WC, Orth RJ, Moore KA, Court Stevenson J, Carter V, Kol-
lar S, Bergstrom PW, Batiuk RA (1993) Assessing water quality
with submersed aquatic vegetation. Bioscience 43:86–94
Development Core Team R (2011) R: a language and environment for
statistical computing. R Foundation for Statistical Computing,
Vienna
Doo SS, Fujita K, Byrne M, Uthicke S (2014) Fate of calcifying tropi-
cal symbiont-bearing large benthic foraminifera: living sands in a
changing ocean. Biol Bull 226:169–186
Doust LL (1981) Population dynamics and local specialization in a
clonal perennial (Ranunculus repens). J Ecol 69:743–755
Duarte CM (1991) Allometric scaling of seagrass form and productiv-
ity. Mar Ecol Prog Ser 77:289–300
Duarte CM, Chiscano CL (1999) Seagrass biomass and production: a
reassessment. Aqua Bot 65:159–174
Durako MJ (1993) Photosynthetic utilization of CO2(aq) and HCO3− in
Thalassia testudinum (Hydrocharitaceae). Mar Biol 115:373–380
Durako MJ, Sackett WM (1993) Effects of CO2 (aq) on the carbon iso-
topic composition of the seagrass Thalassia testudinum Banks ex
Konig (Hydrocharitaceae). J Expt Mar Biol Ecol 169:167–180
Eklöf JS, McMahon K, Lavery PS (2009) Effects of multiple dis-
turbances in seagrass meadows: shading decreases resilience to
grazing. Mar Freshw Res 60:1317–1327
Fabricius KE, Langdon C, Uthicke S, Humphrey C, Noonan S, Death
G, Okazaki R, Muehllehner N, Glas MS, Logh JM (2011) Losers
and winners in coral reefs acclimatized to elevated carbon diox-
ide concentrations. Nat Clim Change 1:165–169
Feely RA, Sabine CL, Lee K, Berelson W, Kleypas J, Fabry VJ, Mil-
lero FJ (2004) Impact of Anthropogenic CO2 on the CaCO3 sys-
tem in the oceans. Science 305:362–366
Fourqurean JW, Duarte CM, Kennedy H, Marba N, Holmer M, Mateo
MA, Apostolaki ET, Kendrick GA, Krause-Jensen D, McGlath-
ery KJ, Serrano O (2012) Seagrass ecosystems as a globally sig-
nificant carbon stock. Nat Geosci 5:505–509
Gacia E, Duarte CM (2001) Sediment retention by a Mediterranean
Posidonia oceanica meadow: the balance between deposition and
resuspension. Estuar Coast Shelf Sci 52:505–514
Granger S, Izumi H (2002) Water quality measuement methods for
seagrass habitats. Elsevier Science, Amsterdam
Hall-Spencer JM, Rodolfa-Metalpa R, Martin S, Ransome E, Fine
M, Turner SM, Rowley SJ, Tedesco D, Buia MC (2008) Volcanic
carbon dioxide vents show ecosystem effects of ocean acidifica-
tion. Nature 454:96–99
Hemminga MA, Duarte CM (2000) Seagrass ecology. Cambridge
University Press, Cambridge
Invers O, Romero J, Perez M (1997) Effects of pH on seagrass photo-
synthesis: a laboratory and field assessment. Aqua Bot 59:185–194
Invers O, Zimmerman RC, Alberte RS, Perez M, Romero J (2001)
Inorganic carbon sources for seagrass photosynthesis: an experi-
mental evaluation of bicarbonate use in species inhabiting tem-
perate waters. J Exp Mar Biol Ecol 365:203–217
Invers O, Tomas F, Perez M, Romero J (2002) Potential effect of
increased global CO2 availability on the depth distribution of the
seagrass Posidonia oceanica (L.) Delile: a tentative assessment
using a carbon balance model. B Mar Sci 71:1191–1198
IPCC (2013) Climate change 2013: The physical science basis. Con-
tribution of Working Group I to the Fifth Assessment Report of
the Intergovernmental Panel on Climate Change. Cambridge Uni-
versity Press, Cambridge
James RK, Hepburn CD, Cornwall CE, McGraw CM, Hurd CL
(2014) Growth responses of an early successional assemblage of
coralline algae and benthic diatoms to ocean acidification. Mar
Biol 161:1687–1696
Jassby AD, Platt T (1976) Mathematical formulation of the relation-
ship between photosynthesis and light for phytoplankton. Limnol
Oceanogr 21:540–547
Jiang ZJ, Huang X, Zhang J (2010) Effects of CO2 enrichment on
photosynthesis, growth and biochemical composition of sea-
grass Thalassia hemprichii (Ehrenb.) Aschers. J Integr Plant Biol
52:904–913
Karkalas J (1985) An improved enzymic method for the determination
of native and modified starch. J Sci Food Agric 36:1019–1027
Koch M, Bowes G, Ross C, Zhang XH (2013) Climate change and
ocean acidification effects on seagrasses and marine macroalgae.
Glob Change Biol 19:103–132
Kohler KE, Gill SM (2006) Coral Point Count with Excel extensions
(CPCe): a Visual Basic program for the determination of coral
and substrate coverage using random point count methodology.
Comput Geosci 32:1259–1269
Kuffner IB, Andersson AJ, Jokiel PL, Rodgers KS, Mackenzie FT
(2007) Decreased abundance of crustose coralline algae due to
ocean acidification. Nat Geosci 1:114–117
Long SP, Ainsworth EA, Rogers A, Ort DR (2004) Rising atmos-
pheric carbon dioxide: plants FACE the future. Annu Rev Plant
Biol 55:591–628
Marba N, Duarte CM (1998) Rhizone elongation and seagrass clonal
growth. Mar Ecol Prog Ser 174:269–280
McCleary BV, Codd R (1991) Measurement of (1→3), (1→4)-ß-D-
Glucan in barley and oats: a streamlined enzymic procedure. J
Sci Food Agric 55:303–312
McKenzie LJ, Collier CJ, Waycott M (2014) Reef Rescue Marine
Monitoring Program—Inshore Seagrass, Annual report for the
sampling period 1st July 2–11 = 31st May 2012. James Cook
University, Cairns
Meehl GA, Stocker TF, Collins WD, Friedlingstein P, Gaye T, Greg-
ory JM, Kitoh A, Knutti R, Murphy JM, Noda A, Raper SCB,
Watterson IG, Weaver AJ, Zhao ZC (2007) Global climate pro-
jections. In: Solomon SD, Qin D, Manning M, Chen Z, Marquis
M, Averyt KB, Tignor M, Miller HL (eds) IPCC, 2007: Cli-
mate Change (2007) The physical science basis contribution of
Mar Biol
1 3
Working Group I to the Fourth Assessment Report of the Inter-
governmental Panel on Climate Change Cambridge University
Press, Cambridge, pp 747–845
Palacios SL, Zimmerman RC (2007) Response of eelgrass Zostera
marina to CO2 enrichment: possible impacts of climate change
and potential for remediation of coastal habitats. Mar Ecol Prog
Ser 344:1–13
Poorter H, Roumet C, Campbell BD (1996) Interspecific variation
in the growth response of plants to elevated CO2: a search for
functional types. In: Korner C, Bazzaz FA (eds) Carbon dioxide,
populations and communities. Academic Press, California, pp
375–412
Raven JA, Caldeira K, Elderfield H, Hoegh-Guldberg O, Liss P,
Riebesell U, Shepherd J, Turkey C, Watson A, Heap R, Banes
R, Quinn R (2005) Ocean acidification due to increasing atmos-
pheric carbon dioxide. The Clyvedon Press Ltd, Cardiff
Robbins LL, Hansen ME, Kleypas JA, Meylan SC (2010) CO2 calc—
a user-friendly seawater carbon calculator for windows, Mac OS
X, and iOS (iPhone) open-file report 2010. Geological Survey
U.S, Reston
Russell BD, Passarelli CA, Connell SD (2011) Forecasted CO2 modi-
fies the influence of light in shaping subtidal habitat. J Phycol
47:744–752
Russell BD, Connell SD, Uthicke S, Muehllehner N, Fabricius K,
Hall-Spencer J (2013) Future seagrass beds: can increased
productivity lead to increased carbon storage? Mar Poll Bull
73:463–469
Ryle VD, Mueller HR, Gentien P, Science AIoM (1981) Automated
analysis of nutrients in tropical sea waters. Australian Institute of
Marine Science
Sand-Jensen K, Gordon DM (1984) Differential ability of marine and
freshwater macrophytes to utilize HCO3− and CO2. Mar Biol
80:247–253
Schwarz AM, Bjork M, Buluda T, Mtolera M, Beer S (2000) Photo-
synthetic utilisation of carbon and light by two tropical seagrass
species as measured in situ. Mar Biol 137:755–761
Short FT, Duarte CM (2001) Methods for the measurement of sea-
grass growth and production. In: Short FT, Coles RC (eds) Global
Seagrass research methods. Elsevier Science B.V., Amsterdam,
pp 155–182
Short J, Kendrick GA, Falter J, McCulloch MT (2014) Interactions
between filamentous turf algae and coralline algae are modified
under ocean acidification. J Exp Mar Biol Ecol 456:70–77
Stitt M, Krapp A (1999) The interaction between elevated carbon
dioxide and nitrogen nutrition: the physiological and molecular
background. Plant Cell Environ 22:583–621
Takahashi M, Noonan S, Fabricius K, Collier CJ (under review) The
effects of long term in situ CO2 enrichment on tropical seagrass
communities: implications for ocean acidification
Tanaka Y, Nakaoka M (2007) Interspecific variation in photosynthe-
sis and respiration balance of three seagrasses in relation to light
availability. Mar Ecol Prog Ser 350:63–70
Terrados J, Borum J, Duarte CM, Fortes MD, Kamp-Nielsen L,
Agawin NSR, Kenworthy WJ (1999) Nutrient and mass alloca-
tion of South-east Asian seagrasses. Aqua Bot 63:203–217
Thom RM (1996) CO2-enrichment effects on eelgrass (Zostera
marina L.) and bull kelp (Nereocystis luetkeana (Mert.) P. & R.).
Water Air Soil Poll 88:383–391
Touchette BW, Burkholder JM (2007) Carbon and nitrogen metabo-
lism in the seagrass, Zostera marina L.: environmental control of
enzymes involved in carbon allocation and nitrogen assimilation.
J Exp Mar Biol Ecol 350:216–233
Uku J, Beer S, Bjork M (2005) Buffer sensitivity of photosyn-
thetic carbon utilisation in eight tropical seagrasses. Mar Biol
147:1085–1090
Vafeiadou A, Materatski P, Adao H, De Troch M, Moens T (2013)
Food sources of macrobenthos in an estuarine seagrass habitat
(Zostera noltii) as revealed by dual stable isotope signatures. Mar
Biol 160:2517–2523
Waycott M, Duarte CM, Carruthers TJB, Orth RJ, Dennison WC,
Olyamik S, Calladine A, Fourqurean JW, Heck JKL, Hughes
AR, Kendrick GA, Kenworthy WJ, Short FT, Williams SL (2009)
Accelerating loss of seagrasses across the globe threatens coastal
ecosystems. Proc Nat Acad Sci 106:12377–12381
Zimmerman RC, Kohrs DG, Stellar DL, Alberte RS (1997) Impacts
of CO2 enrichment on productivity and light requirements of eel-
grass. Plant Physiol 115:599–607
