Introduction
Ocean carbonate chemistry is being altered in ways that may affect future
ocean ecology. The ocean absorbs carbon dioxide (CO2) from the
atmosphere which increases the concentrations of inorganic carbon and
CO2, and decreases pH in a process referred to as ocean acidification.
Surface ocean pH has decreased by 0.1 units since the beginning of the
industrial era and a further decline (0.06 to 0.32 units) is projected over
the next century (Ciais et al., 2013). Through this process, the relative
proportions of dissolved inorganic carbon species are concurrently being
altered. By 2100, bicarbonate (HCO3-), already widely available,
will increase along with CO2, which will have the largest proportional
increase from present-day levels. An increase in carbon availability may
benefit some marine producers (Koch et al., 2013). In contrast, the
concentration of carbonate ions (CO32-) needed by calcifying
organisms will decrease. Thus, ocean acidification can alter competitive
interactions which may cascade to alterations at the ecosystem level.
Seagrass meadows rank as one of the most productive ecosystems on Earth
(Duarte et al., 2010; Duarte and Chiscano, 1999). They are highly valued for
their ability to improve water quality, stabilize sediment, and provide
habitat for a diversity of organisms. Human-driven changes to the seawater
clarity and quality (e.g. eutrophication, ocean warming) are often related
to meadow decline (Jordà et al., 2012; Waycott et al., 2009). However,
these habitat-forming seagrasses are thought to benefit from ocean
acidification because they are able to use both CO2 and HCO3-
for photosynthesis but, with a higher affinity for CO2 and are often
found to be carbon-limited (Invers et al., 2001; Koch et al., 2013).
Experiments under elevated CO2 have shown an increase in seagrass
photosynthesis (Apostolaki et al., 2010; Invers et al., 1997; Jiang et al.,
2010; Ow et al., 2015; Zimmerman et al., 1997), below-ground growth
(Hall-Spencer et al., 2008; Zimmerman et al., 1997; Russell et al., 2013)
and flowering frequency (Palacios and Zimmerman, 2007). Yet the majority of
these studies were conducted in the laboratory over relatively short
durations with single taxa or small groups of taxa isolated from their
surroundings. Although studies along carbon dioxide vents allow for a whole
ecosystem approach, the high spatial and temporal variability in CO2
levels hampers the determination of a reliable dose-response relationship
(Hall-Spencer et al., 2008; Kerrison et al., 2011). To the best of our
knowledge, only Campbell and Fourqurean (2011, 2013a, 2014) have manipulated
partial pressure of carbon dioxide (pCO2) levels in a contained (ie. as
opposed to free flow CO2 bubbling) manner in situ within a Thalassia meadow to test the
response of seagrass to ocean acidification. After 6 months of exposure to
lowered pH (-0.3 from mean ambient), the seagrass had increased
non-structural carbohydrate content by 29 % in below-ground structures
(Campbell and Fourqurean 2014). This finding generally supports the
hypothesis that plant production will be stimulated from the increased
carbon availability.
Posidonia oceanica is the foundation species for mono-specific meadows in the Mediterranean
Sea where it covers up to 23 % of shallow waters (0–50 m; Pasqualini et
al., 1998) and provide services valued at
172 € m-2 yr-1
(Vassallo et al., 2013). These plants are largely dependent upon abiotic
factors as evident by its seasonal growth and physiology (Alcoverro et al.,
1995, 1998; Bay, 1984; Duarte, 1989). They have been studied under a range
of pH in the laboratory as well as along pH gradients near CO2 vents
(Invers et al., 1997, 2001, 2002; Hall-Spencer et al., 2008; Cox et
al., 2015). Around natural CO2 vents in Ischia (Italy), P. oceanica biomass was
greatest at the station nearest the CO2 source with a mean pH of
7.6 and minimum of 6.98 (on the total scale, pHT, Hall-Spencer et al., 2008). Indeed, P. oceanica has a C3
photosynthetic pathway that is hypothesized to benefit from increased carbon
availability and its photosynthesis is not saturated with respect to
dissolved inorganic carbon at natural concentrations in seawater (Invers et
al., 1997, 2001). This is evident by their enhanced productivity in the
laboratory under a pH range from 9.0 to 7.9 and has been attributed to a
less efficient use of widely available HCO3- and their reliance on
CO2 for about 50 % of carbon for photosynthesis (Invers et
al., 1997, 2001). External carbonic anhydrase acts to dehydrate
HCO3- to CO2 which enters the cell by a diffusive process
(Invers et al., 2001). Thus CO2 limitation depends upon the thickness of
the boundary layer and can also occur at high pH with slow diffusion rates
(Invers et al., 2001). However, the extent of the stimulation at pCO2
levels projected for the coming decades appears limited (Cox et al., 2015;
Invers et al., 2002). In addition, the environment and species dynamics in
meadows are complex and interactions can alter outcomes. For example, the
leaves and roots are colonized by small invertebrates and epiphytic algae
(Borowitzka et al., 2006). These associated species, many sensitive to
dissolution, compete with the plants for resources (Cebrián et al.,
1999; Martin et al., 2008; Sand-Jensen et al., 1985). A laboratory
investigation of this potential interaction under two elevated pCO2
levels (pHT 7.7 and 7.3) was performed (Cox et al.,
2015). Despite a loss of calcified photosynthetic epiphytes at pHT 7.7,
the effect on shoot productivity was limited and seagrass photosynthesis
(without epiphytes) was only stimulated at pHT of 7.3, a value unlikely
to occur in the Mediterranean Sea in the next century (Cox et al., 2015).
The long-lived plants, however, were maintained for a relatively short
duration of 6 weeks and only under the irradiance, temperature, and
nutrient conditions of February to March. From these studies it is difficult
to predict the impact of ocean acidification on P. oceanica.
Any alteration in P. oceanica productivity or abundance will likely have repercussions
to meadow function. Therefore the aim of the present study was to test the
hypothesis that Mediterranean seagrass, P. oceanica, will benefit from ocean
acidification. We tested this hypothesis in situ with a Free Ocean Carbon Dioxide
Enrichment (FOCE) system (see Gattuso et al., 2014) which consisted of two
partially open enclosures that were deployed in the Bay of Villefranche
(France) for 8 months (April–November 2014). The pH was manipulated
continuously, in one enclosure, at a -0.26 pH unit offset from ambient
between June and November. Before and during pH manipulation, macrophyte
abundance, Posidonia leaf biometrics, photosynthesis, and growth were measured and
environmental conditions were monitored.
Method
Experimental setup and system function
This study used the European FOCE (eFOCE) system, an autonomous system which
allows for the in situ manipulation of pH in benthic enclosures as an offset from
ambient pH (Gattuso et al., 2014). The system was deployed in the Bay of
Villefranche, approximately 300 m from the Laboratoire d'Océanographie
de Villefranche (NW Mediterranean Sea, France; 43∘40.73′ N,
07∘19.39′ E; Fig. 1). The eFOCE engineering design
consisted of a surface buoy and two underwater benthic enclosures (Fig. 1).
Schematic of the system and study design (left), see text for
details;
(right) the pH (total scale) inside the enclosures and in ambient during the
week-long transition to the targeted offset (-0.25 units).
![]()
The underwater portion of eFOCE consisted of two clear, 1.7 m3 (2 m
long × 1 m width × 0.85 m tall) perspex enclosures that were open on the
bottom to partially enclose a portion of a P. oceanica meadow. They were located at
11 m depth, were placed end to end approximately 1.5 m apart and faced south.
The pH in one enclosure, referred to as the experimental enclosure, was
lowered by ∼ 0.25 units as an offset from ambient pH. The
second enclosure served as a control. A third treatment consisted of an open
fiberglass frame of the same dimensions as the enclosure footprint (2 m2).
It was placed nearby (3 m north of the experimental enclosure) and
in the same meadow. It is referred to as a reference plot and accounts for
any artifacts from the structure of the enclosures.
The surface component of eFOCE consisted of a buoy that housed solar panels,
a wind turbine and 12 V batteries that provided energy to the system. It
also housed three CO2 tanks and a peristaltic pumping system which drew
surface seawater into a 20 L container inside the buoy where pure CO2
was added and mixed until a desired pH was reached (usually between 5.5 and
5.7 pHT). A Seabird potentiometric 18-S pH sensor was used to monitor
pHT in this surface container.
The two underwater enclosures (experimental and control) were mostly
enclosed to maintain the desired pH offset, with the exception of two
openings (12 cm) on the upper, side panels. The top of the enclosure could
be removed to allow scuba divers to enter when needed. Each enclosure had 10
openings (8 cm diameter) along the bottom sides that allowed tubes to pass
through. These “injection” tubes passed through each enclosure into the
ambient environment where they were connected to a set of three underwater
brushless centrifugal pumps and a mixing tube (one for each enclosure). For
the experimental enclosure, a hose ran from the surface to depth and
connected the surface low pH container to the underwater mixing tube. A
second peristaltic pump on the buoy controlled the flow rate (up to 0.12 L min-1)
of the low-pH water through this hose while the underwater
centrifugal pumps (6.7 L min-1 each) continuously brought ambient
seawater into the mixing tube. Each mixing tube also housed a potentiometric
Seabird 18-S pH sensor that monitored pH. By sensing the pH of seawater
before it enters the enclosure, the system, via a feedback loop, could
adjust the CO2-saturated seawater pumping rate to maintain seawater
entering the experimental enclosure at the desired pH offset from ambient.
Once seawater reached the subsurface mixing tubes, it then entered the
enclosures via the injection tubes described above, where it was circulated
by another set of centrifugal pumps (4 per chamber; 6.7 L min-1 each).
Water could then exit enclosures through the two openings (12 cm diameter)
on the upper side panels. The complete renewal time of seawater in each
enclosure was ca. 1.5 h.
Field sensors and system maintenance
The environment was characterized using sensors placed inside the enclosures
and placed within 5 m from the reference plot. Sensors were connected by
cables to the surface electronic hub. The surface electronic hub
communicated 2 min averaged data by radio to the laboratory. Underwater
sensors (with their sampling frequency) included four potentiometric Seabird
18-S pH sensors (eight measures in 1 s) located inside each enclosure and in
each mixing tube, three Seabird 37 SMP-ODO CTD with SBE 63 oxygen (O2)
optodes one in each enclosure and one nearby in the ambient (one sample,
each, for salinity and temperature every 2 min, two samples for O2
every 2 min), and three LI-COR-192 PAR sensors (2000 irradiance measurements
every 5 s) also located in each enclosure and in the nearby ambient
environment.
The system required routine maintenance. Scuba divers lightly brushed the
enclosure surfaces and sensor probes at least once per week to remove
sediment and fouling. On four occasions throughout the experiment duration,
CTDs were flushed by a syringe filled with clean seawater to remove any
debris inside the sampling ports. Tubes and pumps on the buoy and subsea
were also cleaned once a week of debris and replaced when heavily fouled.
The underwater 18-S pH sensors were calibrated one to three times per month
by placing them together in the ambient environment for 45 min, followed by
collection of three, 100 mL syringes of seawater drawn directly next to the
probes. Seawater was immediately returned to the laboratory and pH
determined spectrophotometrically as described in Dickson et al. (2007).
Absorbances at peak wavelengths for purified meta-Cresol Purple (Liu et al.,
2011) were measured using an Ocean Optics© spectrophotometer model
USB2000+VIS+NIR. The pH of seawater samples was determined in triplicate
(SD < 0.008) at 22 ∘C and recomputed at in situ temperature
using the R package seacarb (function pHinsi, Gattuso et al., 2015, seacarb:
seawater carbonate chemistry with R. R package version 3.0.2). The offset
between the probe-sensed value at the time of water collection and
laboratory determined measures was used for correction. In addition, pH
sensors were refreshed every 4 to 6 weeks in a NBS buffer at pH 4 for
45 min.
Timeline
The experiment was conducted from April to November 2014. The experimental
duration can be divided into three periods: (1) the pre-acidification
period, before pH was manipulated, lasted from 5 April to 11 June; (2) the
transition period from 12 to 21 June, where pH in the experimental enclosure
was slowly lowered by no more than 0.05 units per day until an offset of
approximately -0.25 units was reached and (3) the acidified period from 22
June to 3 November during which pH in the experimental enclosure was
maintained at the targeted offset of -0.25 units. It should be noted that
the pre-acidification period began on 5 April; however, data from all
sensors were available from 15 May.
Environment characterization
All sensed data were initially screened for quality. Any obvious outliers or
missing data that resulted from system or sensor malfunction were eliminated
from the data set. The mean (±SD) pHT and median (±median
absolute deviation, MAD) diel pH changes for the two enclosures and the
ambient environment were calculated by time period and month.
Seawater samples for the determination of total alkalinity (AT) levels
in each enclosure were taken one to five times per month from May to October
(n= 11 to 12). Samples (300 mL) were filtered on GF/F membranes (47 mm)
and immediately poisoned with 100 µL of mercuric chloride (HgCl2).
AT was determined on triplicate 50 mL subsamples by potentiometric
titration on a Metrohm Titrando 888 titrator coupled to a glass electrode
(Metrohm, ecotrode plus) and a thermometer (pt1000). The pH electrode was
calibrated on the total scale using TRIS buffers of salinity 38,
corresponding to salinity in the Bay of Villefranche. Measurements were
carried out at 22 ∘C and AT was calculated as described by
Dickson et al. (2007). During the experiment, standards provided
by A. Dickson (batch 132) were used to check precision (standard deviation)
and accuracy (deviation from the certified value provided by Dickson); which
was 0.889 and 1.04 µmol kg-1 (n= 6), respectively. As AT
variations during the experiment were very small, average AT (mean ± SD,
experimental enclosure, n= 12, AT= 2545.5 ± 8.0 µmol kg-1;
control enclosure, n= 11, AT= 2541.7 ± 12.2 µmol kg-1)
was used to calculate all carbonate chemistry
parameters at a high frequency, together with sensed temperature, salinity
and pHT, using seacarb. To calculate carbonate chemistry of the ambient
environment at high frequency, we used an AT value of 2556 µmol kg-1
and the sensed ambient values of temperature, salinity, pHT,
using seacarb. This AT value is the mean for 2014 determined from weekly
measures of seawater collected at 1 m depth station, Point B, within the Bay
(Point B data provided by Service d'Observation Rade de Villefranche and the
Service d'Observation en Milieu Littoral). All these parameters, as well as
the O2 concentration (mean ± SD), median (±median absolute
deviation, MAD) diel O2 change and photosynthetically active radiation
(PAR, mean ± SD, mol photons m-2 d-1) were summarized by
month and by time period for the two enclosures and the reference plot
(ambient).
Shoot density and macrophyte abundance
After the enclosures had been deployed on the meadow for 4 weeks and
before the acidification period, scuba divers counted the number of shoots
within each treatment. Shoot density was determined twice by different
divers and values were averaged, except for the experimental treatment where
an observer error was made and one count was eliminated. Permanent quadrats
were then used to determine any change in shoot density through time. On 11
April, three 0.25 × 0.25 m2 permanent quadrats were haphazardly placed
inside each enclosure and in the reference plot. The number of shoots per
quadrat was then determined every 2 to 4 weeks throughout the experiment.
Percentage cover of benthic macrophytes was estimated every two to four
weeks in three to five haphazardly placed, but not overlapping, 0.5 × 0.5 m2
quadrats within each treatment. The quadrats were also divided into
four smaller squares 0.25 × 0.25 m2 to assist with estimation. Prior to
estimation, researchers practiced estimates on the same quadrat location to
inter-calibrate and limit observer bias. On some occasions, the cover and
shoot density could not be estimated in all 9 to 15 quadrat locations in 1 day. In these instances, divers returned to the treatments within 15 days (most
within 8 days) to complete sampling.
Leaf biometrics
The number of leaves per shoot, and leaf length, area, thickness and
toughness were monitored several times per month from April to November,
before and during the acidification period. On these occasions, scuba divers
used a tape measure to measure the leaf length and counted the number of
leaves per shoot for five to fifteen shoots per enclosure and plot. In
addition, approximately every four weeks from 1 August, divers collected
eight mature, six intermediate and two to four young leaves from each
enclosure and from the reference plot. To limit destructive sampling yet get
a baseline measurement, on 27 June (near the start of the acidification
period) leaves of about the same age were collected nearby. All leaves were
collected from different shoots and taken at their base above the meristem.
They were brought back to the laboratory and their length, width, and
thickness were measured with a tape measure and caliper. The width and thickness
was measured at the middle of the length of each leaf. On three occasions
(in July, September, and October), the toughness of each leaf was determined
in the middle of the leaf length with a penetrometer (see Cherrett, 1968).
For all leaf biometric parameters, data collected over several days were
pooled into one data set for a comparison by month and among treatments
(experimental, control and reference plot). Lab and field determined leaf
lengths were combined and averaged by month into a leaf length parameter
that is included graphically. The leaf area is included because it is a
frequent meadow descriptor (Pergent-Martini et al., 2005). The leaf length,
thickness and toughness were investigated for relatedness with a scatter
plot.
Fluorescence, photosynthesis, and respiration
A diving pulse amplitude modulated fluorometer (diving-PAM, Walz, Germany)
equipped with a red light emitting diode and an internal halogen lamp to
provide actinic light was used to measure the fluorescence in illuminated
and dark-adapted leaves in situ throughout the experiment. These fluorescence
values were used to produce rapid light curves (RLCs, rETR, relative electron
transport rate vs. actinic light) and dark-adapted quantum yields (Fυ/Fm).
All fluorescence and photosynthesis measures were performed on a randomly
selected secondary leaf from enclosures and reference plot. Dark-adapted
yields and RLCs were measured in situ between 10:00 and 12:00 LT (local time) over two to
three consecutive days to produce a sample size of three to ten leaves per
enclosure and reference for May (pre-acidification), July, September, and
October (acidification period for experimental enclosure). For all
fluorescence measures, the fiber optic cable was attached 8 cm above the
leaf meristem and held at a standard distance of 3 mm and at a 90∘
angle from the blade.
RLCs were produced following the procedures outlined in Cox and Smith (2015).
The actinic irradiance levels ranged up to 895 µmol photons m-2 s-1
and were applied on the leaf surface for 10 s followed by a 0.8 s
saturating pulse. Actinic range was also adjusted by month to account for
the changing abilities of plants and corrected each time for battery
decline. We determined the absorption factor (AF), used in rETR calculations,
following the methods and assumptions described in Beer and Björk (2000).
Measurements were conducted one to three times each sampled month
and monthly averages were used in calculations. Curves were fitted with the
exponential model proposed by Platt et al. (1980). Parameters derived from
the curves include (1) α, the initial slope before the onset of
saturation (µmol electrons m-2 s-1/µmol photons m-2 s-1),
(2) the relative maximum electron transport rate, rETRmax
(µmol electrons m-2 s-1) and (3) Ek, optimal irradiance
for maximal electron transport (µmol photons m-2 s-1) which is
determined by the equation Ek=rETRmax/α.
For dark-adapted quantum yield, leaves were placed in the dark for 5 min using the dark-adapter and were exposed to a 0.8 s white
saturating light pulse (saturation intensity setting of 8). Then the maximum
PSII quantum yield was calculated using the equation in Genty et al. (1989) for
dark adaption.
In addition, the photosynthesis vs. irradiance (PE) curves of experimental
and control leaf segments were produced in the laboratory using O2
evolution within a series of incubations. These incubations were performed
over two consecutive days in September and November to produce four PE curves
per enclosure each month. Leaf segments (5 cm) collected from ∼ 10 cm length leaf were collected from the enclosures in the morning and
incubated in the afternoon (13:00–19:00 LT). Immediately after
collection, leaves were stored underwater in plastic bags, and transported to
the laboratory in a dark mesh bag. Leaves were held for up to 3 h in dim
light within a temperature-controlled laboratory (20 ∘C) in
two open top cylindrical aquaria (1.5 L). Ambient water from the nearby bay
was pumped into two header tanks that fed the aquaria and allowed excess
water to overflow into a drainage basin. The pH in one header tank was
maintained at a pHT of ∼ 7.8, corresponding to pH levels
in the experimental enclosure by metered additions of pure CO2
controlled by a pH-stat system (IKS, Aquastar Aquatic Products).
After carefully removing all epiphytes, segments were individually placed
inside 60 mL biological oxygen demand (BOD) bottles submerged into a 50 L
aquarium maintained 1 to 2 ∘C to the mean monthly seawater
temperature at the time of collection (21.2 ∘C ± 0.2 SD).
BOD bottles were filled between each incubation with fresh seawater
from the respective header tank (ambient, or lowered pH) with a stirrer
below. Light was provided at a 90∘ angle to the leaf surface
by a 250 W metal-halide lamp and adjusted to nine increasing irradiance
levels (5 to 200 µmol photons m-2 s-1 measured directly at
the leaf surface). This range of irradiance is within and above irradiance
observed at the depth of collection. Plants were maintained at each
irradiance or in darkness (to measure respiration, R) for 15–30 min while
the concentration of O2 was continuously monitored with a PreSens OXY-4
O2 meter with PSt3 fiber-optic mini-sensors. After the incubations,
leaf segments were ground in a chilled room using a glass homogenizer with
90 % acetone that had been previously chilled for 12 h. The extract was
left for 24 h in darkness, centrifuged at 3000 rpm for 15 min, and the
absorbance of the supernatant measured in quartz-glass cuvette with a UV/VIS
spectrophotometer (Lambda 2, Perkin 366 Elmer). The concentrations of Chl a and
b were determined by measuring the absorbance at 647 and 664 nm and the
concentrations calculated from the equations in Jeffrey and Humphrey (1975).
Rates of changes in O2 normalized to total chlorophyll (Chl a and b)
were plotted against irradiance levels. Parameters of the PE curves were
estimated using a hyperbolic tangent model (Jassby and Platt, 1976),
assuming that R is similar in the light and dark:
Pnet=Pg max×tanh(-E/Ek)+R,
with Pnet: rate of net photosynthesis (µmol O2 (mg Chl)-1 min-1),
Pg max, rate of maximal gross photosynthesis (µmol O2
(mg Chl)-1 min-1), E, irradiance (µmol photons m-2 s-1),
Ek, irradiance at which α intersects Pg max (µmol photons m-2 s-1),
R, respiration rate.
The initial slope, α (µmol O2 (mg Chl)-1 min-1/ µmol photons m-2 s-1)
was calculated as Pg max/Ek
and Ec, the irradiance at which gross photosynthesis equals respiration
and above which plants exhibit a positive net photosynthesis, was determined
from R/α.
Growth and biomass
Leaf production and leaf plastochrone interval were determined using the
Zieman method modified by Short and Duarte (2001). Three to eight shoots in
both enclosures and in the reference plot were marked with a plastic tag
with a unique number in July, August, and September. A hypodermic needle was
used to punch a hole in the meristem region. These tagged shoots were again
located 33 to 46 days later. The distance from the puncture to the meristem was
measured and any new leaves that lacked a puncture were enumerated. Using
these methods, it was possible to calculate the number of days to produce a
new leaf (plastochrone interval) and leaf production per day for each shoot.
Leaf production incorporates the new length added to the shoot from both
the newly produced leaf (or leaves) and from the growth of older leaves.
Above-ground and below-ground biomass was determined for each enclosure and
for the reference plot at the conclusion of the study. A fourth 2 m2
area was also sampled for biomass in a nearby seagrass habitat located
approximately 6 m from the enclosures. This area was added to further
account for natural spatial variation. Three to five, 10 cm diameter cores
of 12 cm height were hammered into haphazardly selected locations within the
treatment area. They were brought back to the laboratory, stored in 5 %
formalin, and later sorted into above-ground and below-ground plant parts,
blotted dry, and weighed. A one-way ANOVA was used to test for differences
in above- and below-ground biomass when data met parametric requirements.
Pseudoreplication
Samples were collected or measured inside the plot or enclosure through
time, often both before and after the pH manipulation. Thus the replication
is equal to one for each treatment. True replication was sacrificed at the
expense of controlling pH as an offset, at the spatial scale of the plants.
Traditional inferential statistics could, therefore, not be rigorously
applied and we compare results graphically, paying careful attention to any
divergence in values between the enclosures and the reference plot.
Results
Environment characterization
The pH in the experimental enclosure was maintained at a -0.26 unit offset
from the control enclosure during the acidification period (Table 1). Values
summarized by month showed that the difference between the two enclosures
was maintained close to the targeted offset (range: -0.22 to -0.29 pH
units). Before the pH was manipulated the offset between enclosures was
smaller, -0.1 to 0.06 pH units.
A comparison of the carbonate chemistry and diel changes within the
ambient and enclosures: the mean (±standard deviation, SD) pH (on the
total scale), the maintained pH offset between experimental and control
enclosures as a difference (Diff), the partial pressure of carbon dioxide
(pCO2), and the median (Med ± median absolute deviation, MAD) diel
pH and oxygen (O2) change for each month and the period before and
during the acidification.
pHT
pCO2 (µatm)
Δ Diel pHT
Δ Diel O2 (µmol kg-1)
N
Ambient
Control
Experimental
Diff
Ambient
Control
Experimental
N
Ambient
Control
Experimental
Ambient
Control
Experimental
Months in Period
Samples
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Days
Med
MAD
Med
MAD
Med
MAD
Med
MAD
Med
MAD
Med
MAD
Before
May
11 840
8.10
0.03
8.12
0.06
8.01
0.05
-0.10
0.03
374
30
358
55
477
74
17
0.08
0.02
0.10
0.06
0.12
0.05
52.0
11.0
68.0
7.0
82.0
14.0
June
8119
8.11
0.04
8.04
0.05
8.10
0.06
0.06
0.05
369
38
443
63
378
65
11
0.10
0.03
0.15
0.04
0.16
0.02
72.0
9.0
91.0
8.0
101.0
9.0
Acidification
June
6226
8.05
0.03
8.02
0.04
7.79
0.13
-0.23
0.13
430
42
470
57
868
318
9
0.12
0.03
0.12
0.04
0.27
0.08
72.0
7.0
85.0
10.0
92.0
11.0
July
21 007
8.03
0.03
8.03
0.06
7.79
0.12
-0.24
0.11
454
46
453
81
870
254
30
0.09
0.02
0.17
0.05
0.27
0.06
60.5
14.0
95.5
18.0
100.5
18.0
August
22 682
8.00
0.03
8.04
0.07
7.81
0.12
-0.23
0.09
489
42
445
85
834
253
31
0.09
0.02
0.18
0.05
0.29
0.06
55.0
8.0
77.0
12.0
86.0
12.0
September
21 854
7.98
0.07
7.97
0.06
7.70
0.11
-0.27
0.10
521
96
536
87
1098
288
30
0.07
0.01
0.11
0.06
0.28
0.10
37.5
5.5
62.5
15.5
54.0
11.5
October
22 420
8.01
0.04
8.00
0.04
7.70
0.13
-0.29
0.14
480
52
497
64
1086
390
31
0.06
0.02
0.09
0.04
0.29
0.08
27.0
3.0
34.0
5.0
44.0
5.0
November
5377
8.02
0.03
8.02
0.02
7.80
0.15
-0.22
0.15
469
48
467
22
836
305
10
0.04
0.01
0.06
0.03
0.09
0.05
21.0
5.5
34.0
22.5
45.5
29.5
Before
24 334
8.10
0.04
8.05
0.07
8.06
0.07
0.01
0.09
380
39
434
85
426
87
34
0.09
0.02
0.14
0.06
0.16
0.07
63.5
13.0
80.5
13.5
88.0
13.0
Acidification
95 711
8.01
0.05
8.01
0.06
7.75
0.13
-0.26
0.11
483
67
482
86
971
323
132
0.08
0.02
0.14
0.06
0.28
0.14
44.0
14.5
68.5
23.5
74.0
23.0
The pHT in ambient ranged from a mean of 7.98 (±0.06 SD) in
September to 8.11 (±0.04 SD) in June (Table 1). The ambient pHT
was similar to the pHT in the control enclosure, which ranged from 7.97
(±0.07 SD) in September to 8.12 (±0.06 SD) in June. The
greatest difference between control and ambient, in monthly mean pHT
values was 0.06 units. The differences in pCO2 reflected the magnitude
of difference in pHT, as AT levels were rather constant during the
study (see method section).
The mean O2 concentration was similar in enclosures and in the ambient
(Supplement Table S1). For example, the mean O2 concentration (±SD) before
acidification for ambient, control and experimental was 258 ± 18,
254 ± 34, and 258 ± 2 µmol kg-1, respectively. In the ambient and
in the enclosures, the O2 concentration fluctuated over the course of
the day (data not shown). After sunset, O2 concentration declined to a
night-time minimum. In the morning, the O2 began to increase to a
daily afternoon maximum; then it declined with decreasing irradiance. Over
the months of the experiment, this diel O2 change ranged from 21 to
72 µmol kg-1 in the ambient, 34 to 95 µmol kg-1 in the control
enclosure, and 34.5 to 100.5 µmol kg-1 in the experimental enclosure
(Table 1). The difference in diel change between the ambient and the
enclosures was most likely due to the amplification of a metabolic signal
inside a partially enclosed space (similar to the example of a larger
O2 fluctuation when a similar sized plant is contained in a
relatively smaller volume of water) as was evidenced by the more similar,
and greater diel change in the two enclosures. The largest difference in
median values between enclosures was 14 µmol kg-1 in May, prior to the
perturbation.
The diel pHT change in the meadow corresponded to the daily change in
O2 concentration. The natural diel pHT for this meadow was evident
from the measures in the ambient which median values show it fluctuated by
0.09 (±0.02 MAD) and 0.08 (±0.02 MAD) units per day in the
pre- and acidification period, respectively. The diel change in pHT for
the control enclosure was slightly greater but consistent in the pre- and
during acidification period (0.14 ± 0.06 MAD and 0.14 ± 0.06
MAD). In contrast, the diel pHT change for the experimental enclosure
increased from a median of 0.16 (±0.06 MAD) before pH manipulation to
0.28 (±0.14 MAD) during the acidification period.
Monthly differences were evident particularly for temperature, oxygen
concentration, and PAR (Table S1) but were similar in the ambient, control
and experimental enclosures. For example, the mean ± SD during the
acidification period for temperature in ambient, control and experimental
enclosures was 23.9 ∘C ± 0.01 (for each) and for PAR,
4.6 ± 1.9, 4.6 ± 2.0, 4.1 ± 1.7 mol photons m-2 d-1,
respectively. Temperature increased approximately by 6 ∘C from
May through August and declined by 4 ∘C until November. Oxygen concentrations and PAR fluctuated
similarly with higher values in May to August (mean monthly range: 212 to
270 µmol kg-1, 4.7 to 7.7 mol photons m-2 d-1) and decreases
in September to November (mean monthly range: 193 to 211 µmol kg-1,
1.4 to 4.4 mol photons m-2 d-1).
Shoot density and macrophyte abundance
Initial shoot densities were similar in both enclosures and reference plot
and ranged from 150 to 175 shoots m-2 (Fig. 2). There was no obvious
change in shoot number (as determined in permanent quadrates re-sampled
through time) related to the lowered pH in the experimental enclosure. For
both enclosures and the reference plot, the number of shoots (initially 6 to
27 in permanent quadrats) tended to decline with time.
Macrophyte abundance throughout the experiment;
(a) enclosures and reference plot had initially similar P. oceanica shoot density m-2 (mean ± SE). (b) mean shoot
number with time within three permanently located quadrats (0.06 m2)
per reference plot (top), control (middle) and experimental (bottom)
enclosures. (c, d, e) coverage (%) of benthic macrophytes and
unoccupied sediment or rocks (bare space) before and during the acidification
period (x axis after the dashed vertical line).
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The reference plot as well as the enclosures had a very low diversity of
benthic macrophytes as measured by estimates conducted within haphazardly
placed quadrats at each sampling interval (Fig. 2). Posidonia oceanica was the dominant
species, with a surface cover of 18 to 35 %. Peyssonnelia, a red alga, covered between 1
and 11 % of the substratum. Their abundances were similar between months
throughout the experiment. There was a slightly greater percentage of P. oceanica in the
experimental enclosure (experimental enclosure, 31.6 ± 0.6 %;
control enclosure, 27.9 ± 1.7 %; reference plot, 28.9 ± 1.3 %)
throughout the experiment duration that did not appear to be
related to the timing of the pH manipulation.
Leaf biometrics
There was no large difference in shoot height among the enclosures and
reference plot but there were large differences in shoot height between the
sampled months (Fig. 3). A similar monthly pattern in leaf length was
observed between the three treatments, for the minimum, average and maximum
leaf length. From April through August, average leaf length and average
shoot height both increased and then declined between August and September.
For example, the overall average shoot height increased from 40.6 cm in
April to 73.4 cm in August then declined to 24.8 cm in November.
Leaf biometrics (mean ± SE) before and during the
acidification period for the reference and enclosure plants. Measures through
time: average shoot height (a), leaf length (b), minimum (c) and maximum leaf
length (d), number of leaves per shoot (e), leaf area (f), leaf
thickness (g)
and leaf toughness (h) are shown. The dashed vertical line indicates when the
pH was lowered in the experimental enclosure. Additional leaves were
collected in June from the meadow and are referred to as ambient leaves.
![]()
Shoots had between 2 and 8 leaves (Fig. 3). The reference and control plants
differed slightly in leaf number per shoot (reference, 5.4 ± 0.1 vs.
control, 5.1 ± 0.1), but control and experimental plants (5.2 ± 0.2)
were highly similar indicating an absence of pH effect. Furthermore,
the number of leaves per shoot in the experimental enclosure did not
consistently increase or decrease after the pH was manipulated. Instead,
leaf number per shoot in enclosures and plot increased during months when
leaf height was lower (April, May and then October, November: 6 to 7) and
tended to be lower in June and August (4 to 5) when leaf height was
elevated.
Leaf thickness and leaf toughness increased with leaf length. However, leaf
thickness did not appear to be correlated to leaf toughness. Both parameters
varied among the enclosures and reference plot, and between months (Fig. 3).
Leaves in the experimental enclosure were slightly thicker (2.5 ± 0.1 mm)
than leaves in the control enclosure and the reference plot (2.2 ± 0.08 mm
and 2.1 ± 0.1 mm, respectively). Leaves in control enclosure
and the reference plot for the month of November had a decreased and more
variable thickness. Leaves inside the enclosures appeared to be weaker than
the leaves in the reference plot. Furthermore, leaves appeared weaker in
October compared to July and September. For example, the weakest leaf in
July could withstand 34 g of force as compared to the weakest leaf in
October which could only withstand 12 g of force. The ambient leaf samples
collected in June also had a greater mean value of toughness than the
October values from enclosures and the reference plot.
Fluorescence, photosynthesis, and respiration
The dark-adapted quantum yield obviously differed by month but not according
to pH (Fig. 4). The overall dark-adapted quantum yield ranged from 0.72 to
0.88 (n= 69). The mean values were similar in the enclosures and the
reference plot. Mean yield was 0.8, 0.789, and 0.799 for leaves measured in
the experimental, control, and reference treatments, respectively. Yield
values increased over the duration of the experiment.
The AF factor for the calculation of rETR changed with month. The determined
values (as a mean ± SD) were as follows: May: 74.5; July: 65.0;
September: 69.6 ± 1.5 (n= 3); October, 54.2 ± 0.0 (n= 2).
Photosynthetic rapid light curves (RLCs, a–d), dark-adapted quantum
yield (e), and the derived RLC parameters (f–h) measured on 2nd rank
leaves in enclosures and reference plot before (May) and during (July,
September, and October) the acidification period. Symbols represent the mean
(±SE) relative electron transport rate (rETR) at each mean
photosynthetic active radiation (PAR) value. Curved lines represent the
Jassby and Platt (1976) regression based on mean values. The dashed outline
encloses the acidification period.
![]()
The photosynthetic RLCs in Fig. 4a–d, show that the shape of the curve
changed with month. Leaves from the control and experimental enclosures have
similar rETR values that were slightly lower at elevated irradiance relative
to the leaves in the reference plot.
The initial slope (α, µmol electrons m-2 s-1/ µmol photons m-2 s-1)
ranged between 0.23 and 0.58 (n= 57). It decreased
substantially as a function of time (Table S6) from elevated values in May
(0.43 ± 0.01) and July (0.48 ± 0.01) to lower values in
September (0.31 ± 0.01) and October (0.27 ± 0.01). Overall (n= 57), rETRmax values (in µmol electrons m-2 s-1) ranged from
4.3 to 27.4 and Ek (µmol photons m-2 s-1) ranged from
12.0 to 63.6. The leaves from the reference plot had rETRmax
(12.3 ± 0.6) and Ek (33.7 ± 2.0) that were more different than
the leaves from the control (rETRmax= 10.8 ± 0.7, Ek= 29.8 ± 2.0)
and experimental (rETRmax= 12.0 ± 0.7,
Ek= 30.9 ± 0.7). However, these parameters differed by a
greater amount by month than among plants from the enclosures and the plot.
rETRmax values were substantially higher in May (22.1 ± 1.4) than
in July (10.9 ± 0.8), September (7.2 ± 0.6), and October
(7.5 ± 0.8). Overall, Ek was obviously greater in May (50.2 ± 2.2)
than in July (23.1 ± 2.6), September (24.5 ± 2.1), and
October (28.1 ± 2.5).
The parameters of the PE curves of leaves collected from the experimental
and control enclosures also did not greatly differ (Fig. 5). α,
Pg max, and R were greater for leaves measured in September than
November.
The mean total concentration of chlorophyll in leaves did not greatly differ
among enclosures. It was 0.36 ± 0.04, 0.38 ± 0.04 mg Chl cm-2
in the experimental and control enclosures, respectively. It was
greater in November than in September (0.46 ± 0.03 vs. 0.28 ± 0.04 mg Chl cm-2).
The Chl a : b ratio of leaves from the control
and experimental enclosures did not obviously differ, with an overall Chl
a : b ratio of 0.64.
Photosynthesis vs. irradiance (PE) curves produced from laboratory
incubations of P. oceanica leaf segments collected from the
enclosures after two (September, a) and four (November, b) months of
acidification. The derived parameters from the curves are shown in (c)–(g).
![]()
Growth and biomass
Leaf production and plastochrone interval of shoots in the reference plot
and in the enclosures appeared to differ (Fig. 6). Differences are most
congruent with an effect caused by the structure of enclosures and not from
the lowered pH. The shoots in the reference plot were able to produce more
leaf material than in the experimental and control enclosures. From July to
September, reference shoots grew new leaf material at a mean rate of 0.89
(±0.06) cm d-1 compared to the reference plot and control
enclosure, which both produced 0.66 (± 0.05 to 0.06) cm d-1.
Furthermore, reference shoots produced a new leaf in a fewer number of days
than shoots in the experimental and control enclosures. From August to
September, it took 11 days to produce a new leaf in the reference plot while
it took between 23 and 29 days for shoots that grew in the experimental and
control enclosures, respectively. Overall, leaf production (the growth of
all leaves per shoot) was also seasonal. It was greater per day from
September to October (1 cm d-1) than during the periods July–August
(0.5 cm d-1) and August–September (0.6 cm d-1).
At the end of the experiment, the above- and below-ground biomass was highly
variable (Fig. 6). The above- and below-ground biomass ranged from 318 to
1484 and from 348 to 1584 g FW m-2, respectively. The control and
experiment enclosures tended to have less above-ground biomass (630 and 530 g FW m-2)
than the two external plots (reference: 850 and extra ambient
plot: 870 g FW m-2).
Discussion
No overwhelming impact was observed on macrophyte abundance, P. oceanica leaf
biometrics, biomass, and photosynthesis after 4 months of elevated
pCO2. Leaf thickness may change in response to lowered pH but requires
further testing. Many of the leaf biometrics and physiology parameters
varied seasonally with the varying temperature and irradiance. Posidonia oceanica abundance
did not substantially change over 8 months as expected for a seagrass
with slow rates of colonization (Marbà and Duarte, 1998). However, under
elevated pCO2, no other benthic macrophyte or epiphyte proliferated or
decreased to alter the macro-community structure. The similarity in leaf
biometrics, photosynthesis, biomass and growth between enclosures support
the conclusion of limited stimulation for P. oceanica under future ocean acidification.
However, due to tradeoffs related to experimental design, there were
limitations to our conclusions.
Growth as P. oceanica leaf production (a) and leaf
plastochrone interval (b) during the acidification period. After 4 months of
acidification, biomass (above-ground, c; below-ground, d) was determined from
replicate cores collected from enclosures and the reference plot. A fourth
nearby ambient area was additionally sampled to better account for spatial
variation.
![]()
Thickness and toughness are two structural factors related to mechanical
strain (Harder et al., 2006; Littler and Littler, 1980; Padilla, 1985) and
both traits were altered. Flexibility and strength are needed in
environments with strong wave forces (de los Santos et al., 2013). In
Cymodocea nodosa, another Mediterranean seagrass, leaf cross-sectional area varies with
hydrodynamical forces (de los Santos et al., 2013). Therefore, observed
differences in leaf toughness for plants maintained in the enclosures
support the notion that mechanical abrasion was less than in ambient. This
finding is an artifact of the structure that could not be avoided. In P. oceanica,
thickness changes along the leaf axis and leaves are thinner with depth
(Colombo et al., 1983). Given that the experiment was conducted at the same
depth and leaves were measured at their center, it is interesting to note
that leaf thickness was greatest for the shoots collected from the
experimental enclosure and that this effect was driven by measures in
November. An increase in seagrass leaf thickness would be an opposing effect
to those observed for the upright calcified alga, Acetabularia acetabulum, which lost skeletal
support under ocean acidification conditions (Newcomb et al., 2015). There
are several possible interpretations of these results. First, leaves at the
lower pH may have increased their carbon content as observed for
below-ground plant structure of the seagrass Thalassia testudinum under elevated pCO2
(Campbell and Fourqurean, 2013a). Secondly, lowered pH could result in a
delay of leaf shedding. Plants from the experimental enclosure had a
tendency towards relatively greater leaf length and maintenance of number of
leaves in November. A prolonged leaf life-span could allow plants to
scavenge nutrients from senescing leaves to maintain C / N ratio (Gobert et
al., 2002). However, photosynthesis measures were not elevated by the
lowered pH and thus there would be no need for increased nutrients.
Additionally, increased pCO2 and high light increased leaf shedding for
the seagrass Amphibolis antarctica (Burnell et al., 2014). The response was linked to
proliferation of filamentous epiphytes, which did not occur in this study.
Alternately, increased leaf thickness could be the result of chance. The
plausible relationship warrants further investigation in field experiments
with prolonged duration and increased replication.
If indeed leaf thickness increases with ocean acidification, it is unclear
how this would impact herbivore feeding. The main herbivores, the fish,
Sarpa salpa, and the sea urchin Paracentrotus lividus, feed preferentially on the adult and thicker leaves
(Peirano et al., 2001). These herbivores were prevented from grazing in
enclosures. Arnold et al. (2012) have reported increased rates of fish
grazing on the plant at a proximity of a CO2 vent, presumably due to the
significant decreases in the production of phenolics. To date, very few
studies have focused on plant-herbivore interactions under elevated
pCO2 levels (Asnaghi et al., 2013; Campbell and Fourqurean, 2014; Poore
et al., 2013) and as plant-herbivore interactions were not the focus of this
study, it is not known how this would have impacted the results.
To our knowledge, this is the first in situ study to repeatedly and over several
months (6) measure P. oceanica fluorescence to find that the second rank leaves showed a
typical seasonal pattern of plant acclimation (Boardman, 1977). Leaves were
more sun-adapted (relatively higher rETRmax and Ek) in periods with
elevated irradiance and more shade-adapted when irradiance and photoperiod
were reduced. The relatively lowered Fυ/Fm in May and July
compared to October indicates a down-regulation of PSII activity (Campbell
et al., 2003; Henley, 1993) that corresponds with elevated irradiance in
warmer months. Findings are in agreement with Figueroa (2002) where ETR and
Ek were higher in September than in February. Although there have been
some concerns on the ability of fluorescence techniques to indicate seagrass
carbon stimulation (see Cox et al. (2015); Jiang et al., 2010), P. oceanica productivity
as a function of increasing irradiance was in agreement with fluorescence
results.
The results of the present study add to the growing evidence that the pH
change predicted over the next century may result in limited production
stimulation for P. oceanica. The relationship between pH and P. oceanica photosynthesis was
established over a wide range of pHT from 9.0 to 7.9 (scale unknown,
Invers et al., 1997), or with more extreme low levels (6.98 pHT,
Hall-Spencer et al., 2008; 7.5 scale unknown, Invers et al., 2002). Within
the range of 7.9 to 9.0, the slope of the pH-photosynthesis relationship was
significant but, the two variables were moderately related (Invers et al.,
1997). Along CO2 vents, there was no indication of photosynthetic
stimulation at stations with a pH range of 6.98 to 8.17 but, shoot density
was 30 % greater than nearby areas at the lowest mean pH station
(Hall-Spencer et al., 2008). In a laboratory incubation of P. oceanica shoots with
their attached epiphytes, at a similar pHT as this study
(∼ 7.7–7.8), there was also a limited stimulation of
productivity (Cox et al., 2015). Similarly, modeled outcomes from laboratory
studies of leaf segments by Invers et al. (1997, 2001) predicted that
elevating pCO2 by the amount used in this experiment would increase
productivity by only 10 %. This first in situ experiment confirms previous
results obtained on isolated plants or leaf segments in the laboratory and
is interpreted as in agreement with observations at CO2 vents.
Posidonia oceanica has a shoot lifespan estimated up to 50 years (Gobert et al., 2006). In
carbon budgets it is thought that there is asynchrony between fixation
(photosynthesis) and use (respiration or growth), which is balanced by the
storage of carbohydrate reserves (Alcoverro et al., 2001). Because of this
asynchronicity, the photosynthetic benefit of CO2 may translate into
the following season or year as it did for the seagrass Zostera marina (Palacios and
Zimmerman, 2007). In the present study, there was no indication of increased
productivity as gauged by RLCs, PE curves, and measures of leaf chlorophyll.
Therefore, there is no available evidence that carbon availability translated
into increased carbon storage as occurred for T. testudinum under elevated pCO2
(Campbell and Fourqurean, 2013a). Carbohydrates can be translocated to other
ramets (Marbà et al., 2002) which can lessen observed effects but, in
this case, enclosure area captured the 20 cm maximum translocation distance
detected by Marbà and Duarte (1998) and edges severed (designed to
penetrate ∼ 8 cm) several outside to inside shoot connections.
The most productive period for above-ground growth occurred from April to
August; a pattern consistent with increased growth induced from the greater
availability of both light and nutrients in early spring and increased
storage in July to August (Alcoverro et al., 1995, 1998, 2001; Bay, 1984;
Duarte, 1989; Ott, 1980). Therefore it is possible that if the experiment
were initiated earlier, in a period more conducive for biomass production,
or prolonged to capture any lagging effects the outcome may have been
different. Only two of six studies support a pulsed seasonal-pH interaction
that could result in long-term gains yet, these were found at pH < 7.7
(see Hall-Spencer et al., (2008); Invers et al., 2002).
We caution that conclusions should not be applied to other seagrasses and
that outcomes may vary with differences in community composition and
environment. Presumably due to differences in their evolutionary past, some
species are comparatively more responsive to lowered pH (Campbell and
Fourqurean, 2013b; Invers et al., 2001; Koch et al., 2013). Posidonia oceanica is less
sensitive to pCO2 and can rely heavily on bicarbonate compared to two
other Pacific seagrass species (Invers et al., 2001). In addition, at
CO2 seeps in Papua New Guinea, two seagrass species (Cymodocea serrulata and Halophila ovalis) occur in
mixed stands and while both species had increased productivity along the
lowered pH gradient, it was only C. serrulata with dense below-ground biomass that had
increased abundance (Russell et al., 2013); demonstrating that outcomes may
be species specific, related to the plant physiology and structure, and vary
with competition. Biological communities and environmental conditions are
variable both within (e.g. depth) and among meadows (Hemminga and Duarte,
2000). For example, epiphyte coverage and thus level of competition were
reported to be greater along control stations at Ischia, Italy (Martin et
al., 2008) than in our study site, however, differences in methodology
prevent direct coverage comparisons. Nutrient concentration can also alter
the response of seagrass to CO2 additions (Burnell et al., 2014;
Martínez-Crego et al., 2014). Clearly our understanding of meadow
dynamics under ocean acidification conditions could benefit from repeated
in situ studies that address issues such as species differences, more prolonged
durations, herbivore–plant interactions, and temporal and spatial effects.
Performing this experiment in situ, over several months, is an advancement for
understanding the response of P. oceanica to ocean acidification. The eFOCE design has
advantages to other mesocosm systems such as its large size which allows for
measuring processes at the scale of a meadow, its ability to monitor the
environment in real-time, and its ability to maintain pH as an offset.
Though replicated enclosures would have been preferred and are recommended
for future use, their implementation was not feasible at this stage.
However, several steps were taken to eliminate possible erroneous
conclusions including the following: (1) the environment was continuously monitored to
ensure comparisons were valid; (2) repeated measurements were made at the
same location through time both before and after acidification; (3) comparisons
from the pH manipulated enclosure were made to at least two
different spatial locations, and (4) results obtained in laboratory and
natural experiments were compared and are in general agreement. The duration
of this study was longer than any previous pH perturbation carried out on
P. oceanica and it was performed in the most natural conditions possible. This study
addresses a need for manipulative experiments done in situ for longer durations to
make best predictions of future marine ecology (see Gattuso et al., 2014).
Our findings have implications for the function of future meadows.
Seagrasses through their metabolic activity alter the chemical properties of
the meadow. In daylight, seagrasses draw down the available dissolved
inorganic carbon and at night their respiration has the opposite effect
(Hendriks et al., 2014a). The daily change in pH has been shown to be up to
0.24 pH units and to be related to the density and length of leaves
(Hendriks et al., 2014a). In the current study, the decline in leaf length
and 3 ∘C difference in temperature likely contributed to the
decline of ambient pHT from 8.10 to 8.01 from May to November. Hendriks
et al. (2014b) has suggested that (1) organisms within the meadow may not be
as vulnerable to ocean acidification because they are adapted to large diel
pH changes; (2) the productivity of Posidonia during the day may buffer the impacts of
ocean acidification, particularly for calcifiers by providing a daily window
of maximum calcium carbonate saturation where calcification can be more
efficient, and (3) ocean acidification could stimulate seagrass productivity
and thus increase buffering capacity, which was not supported by the results
of this present study. Considering the two previous proposed hypotheses, the
median diel pH variation for the meadow in this study was ∼ 0.1
and also appeared to be driven by plant metabolism. However, the median
diel pH range in the experimental enclosure was two to three times larger
than the control (0.09 to 0.29 pH units) and exhibited greater variability;
a finding that would be missed in typical experiments which lower pH and
maintain it at a constant future level(s). The variation in diel pH cannot
solely be explained by O2 fluxes. The increased diel pH fluctuation
could largely be the result of the reduced buffering capacity of seawater at
lowered pH (Shaw et al., 2013). The lowered and larger diel pH variation and
lack of productivity stimulation casts doubt on the adaptability of
organisms to future pH change and the ability of a P. oceanica meadow to serve as a
future refuge.
Ocean acidification is not occurring in isolation, warming has been
predicted to result in a complete extinction of P. oceanica meadows by the year 2049
(Jordà et al., 2012). The speculation that increased CO2
availability would enhance seagrass production and help to alleviate thermal
stress (Zimmerman et al., 2015) was not supported. Jordà et al. (2012)
also draw attention to the continuing decline of P. oceanica meadows from 1990 despite
the increase in CO2 as a demonstration of the limited capacity of ocean
acidification to buffer seagrass vulnerability to disturbances. It confirms
observations after an explosive episode at a CO2 vent which resulted in
an extreme lowering of pH (4.7 to 5.4) and elevated temperatures (28–30 ∘C,
3 to 5 ∘C above ambient). Along this vent, P. oceanica
experienced a decrease in growth that persisted for 3 years (Vizzini et
al., 2010). The extreme nature of the vent activity, confounding biological
differences found at vent sites (e.g. Vizzini et al., 2013), and the
possible change in physiology under combined stressors make it difficult to
predict future meadow ecology. It underscores the need to investigate
stressors concurrently and in situ. The FOCE systems are tools that can be used to
investigate these types of impacts.
Summary, caveats, and perspectives
Any benefit from ocean acidification, over the next century, on Posidonia physiology
and growth appears minimal. This conclusion is supported by the similarity
of measures between enclosures and in context of results from other studies.
We have cautioned that the eFOCE study, like all studies, has limitations.
There may be small gains in plant productivity which are masked by an
enclosure effect or difficult to identify without replication or more
prolonged duration. We recommend that future in situ manipulative efforts use FOCE
systems to control pH as an offset, as we did, and increase replication. The
field of ocean acidification and future seagrass ecology could benefit from
further in situ experiments that focus on combined stressors, extended experiment
duration, and differences which occur over varying spatial and temporal
scales (eg. within a season promoting above-ground biomass).