The effects of ocean acidification and increased temperature on physiology
of six strains of the polar diatom
The Arctic Ocean is currently experiencing fast environmental changes, such
as warming and sea ice loss, as well as sea ice and ecosystem structure
changes due to natural and anthropogenic factors (Arrigo, 2014; Nicolaus
et al., 2012; Turner and Overland, 2009). According to some models, the
average sea surface temperature (SST) in some areas of the global ocean will
increase by 1–4
Next to rapid changes in the ocean surface temperature and their
consequences on the marine ecosystem, ocean acidification is expected to
occur relatively fast in the Arctic environment. The major reasons are its
unique features, such as cold and relatively fresh surface waters which
promote high CO
To date, experimental data on phytoplankton tolerance to decreasing pH and
rising SST are scarce and mostly only available for phytoplankton from
temperate coastal waters. Berge et al. (2010) investigated the tolerance
of eight temperate phytoplankton species from four groups (dinoflagellates,
cryptophytes, diatoms, prymnesiophytes) to lowered pH, and showed that
marine phytoplankton was, in general, resistant to climate change in terms
of ocean acidification. Similarly, Nielsen et al. (2011) reported that
the investigated coastal plankton communities from temperate regions were
unaffected by projected 21st century changes in pH and free CO
Experimental data on combined effects of elevated temperatures and decreased
pH on the growth of phytoplankton from polar waters remain limited and
poorly understood (Slagstad et al., 2011). Most
studies investigating climate effects on phytoplankton use only one strain
as representative of a species despite it being well documented that species
are genetically and physiologically diverse. Therefore, conclusions based on
single strains could potentially be misguiding. The aim of the present study
was to simulate pH and temperature changes from present to probable future
levels, to be able to evaluate their potential impact on the growth of the
polar diatom species
Water samples were collected from Disko Bay (69
The experiments were carried out at three different temperatures, 1, 5,
and 8
For acclimation, each of the six strains was grown in L1 medium, based on
0.2
The experimental flasks (65 mL) were inoculated with a cell concentration of
1000 cells mL
Temperature and pH were measured using a WTW pH 340i pH-metre with a SenTix 41 electrode, with a sensor detection limit of 0.01. The pH electrode was calibrated weekly (2 point calibration) using Sentron buffers of pH 7.0 and 10.0 dilutions.
The concentration of dissolved inorganic carbon (DIC) in fresh media (all
four pH treatments) was measured in triplicate. Measurements were done using
an infrared gas analyzer (IRGA) and a bicarbonate standard solution
(2 mmol L
Samples (3
Assuming exponential growth of the cells, the maximum growth rates were
calculated from the logarithmic curves of cell growths (logarithmic
cumulative cell concentrations versus days) using the equation
The maximum growth rate for a given strain and pH treatment at a specific
temperature was calculated employing linear regression for the steepest part
of the growth curve. Linear regression was carried out for each replica of
the strain at a given treatment, and the mean of maximum growth rates of the
three replicates at a given treatment was taken as the maximum growth rate
for that combination of strain and treatment. The temperature coefficients,
All six
All analyses were performed using IBM SPSS Statistics (version 22). Differences between the treatments were tested using three-way ANOVA with temperature and pH as fixed factors, and strain as a random factor. A statistically significant three-way interaction was followed up with simple two-way interactions at all levels, applying a Bonferroni adjustment, and simple main effects for fixed factors pH and temperature. The normal distribution of data was tested using a Shapiro-Wilk test and homogeneity of variances using Levene's test. The level of significance used was 0.05.
All strains, cultivated at all combinations of three different temperatures
and four different pH treatments, grew exponentially as a function of time,
with an acclimation period of three days (Fig. S1 in the Supplement). The
differences in growth rates within and among the strains were tested using
three-way ANOVA, and a significant interaction among temperature, pH and
strain on growth rate was found (
A general positive effect of increased temperature on the growth rates was
observed at all four different pH treatments (Fig. 1). Comparisons of the
maximum growth rates among the three different temperatures showed highest
growth rates at 8
The mean maximum growth rates (d
The mean maximum growth rates (d
The
Strain D10A12 showed the overall highest growth rates at the highest
temperature (8
A general negative effect of increased acidification at three different temperatures on the growth rates was observed (Fig. 2).
At 5
Overall we found a decrease in growth rates from pH 8.0 to pH 7.1 at 5
At 1
For all three strains grown at 1
At 8
In the three strains grown at 8
Temperature and pH in the experimental treatments fluctuated minimally
around the designated values (< 0.6
The average temperatures
The sequences of ITS1, 5.8S and ITS2 of all six strains were identical to
each other and also identical to strain Real9 of
Future marine phytoplankton will not be exposed solely to a decrease in pH but also to other concurrent changes such as increased SST, which is why it
is important to consider cumulative effects of multiple climate stressors
(e.g. present study; Schlüter et al., 2014; Xu et al., 2014). This
study showed a statistically significant interaction among pH, temperature
and strain on the growth of all
The variation in the growth rates within a single species suggests variation
in evolutionary potential within species (Beaufort et al., 2011; Langer
et al., 2009), which is why it is important to take intra-specific diversity
into account when trying to understand the physiology and evolution of
natural populations (Collins et al., 2014). This study showed that
different strains of
In contrast, if one parameter is examined at a time, a general positive effect of increased temperature (see Sect. 4.1.2), and a general negative effect of increased acidification (see Sect. 4.1.3) is found. However, one has to take into consideration that the largest variability was found among the strains (the random factor). Some strains showed better performance than others when cultivated in the same conditions, indicating that these strains may display high resilience to the changes in pH and temperature predicted for the 21st century (e.g. present study; Kremp et al., 2012; Langer et al., 2009). Climate change may therefore lead to alterations in strain composition, with the strains exhibiting high phenotypic plasticity, in terms of temperature and pH tolerance, dominating the population. To our knowledge, this is the first study reporting the intra-specific variability of a phytoplankton species from the polar environments in response to elevated temperatures and ocean acidification.
A change of temperature had significant effects on
The noteworthy variability in strain-specific responses, with growth rates
varying up to
Acidification results in both decreasing pH and increasing CO
The present study found a general negative effect of increasing
acidification on
To date, studies on phytoplankton responses to ocean acidification have
mainly been focused on temperate or tropical regions, and only a few studies
have been carried out in polar regions (e.g. present study; McMinn et
al., 2014; Thoisen et al., 2015; Torstensson et al., 2012). However,
increased
Long-term adaptation to environmental parameters of
We thank the Arctic station in Qeqertarsuaq, Greenland, for providing excellent research facilities and data on ocean temperature, and help in any way. Funding was provided by the Carlsberg Foundation (2012_01_0556), a grant DFF – 1323-00258 from the Danish Research Council to N. Lundholm, and a grant Ad futura (11010-306) from Slovene Human Resources Development and Scholarship Fund to M. Pančić. Edited by: C. Robinson