Resolving the environmental drivers shaping planktonic communities is
fundamental for understanding their variability, in the present and the
future, across the ocean. More specifically, addressing the
temperature-dependence response of planktonic communities is essential as
temperature plays a key role in regulating metabolic rates and thus potentially
defining the ecosystem functioning. Here we quantified plankton metabolic
rates along the Red Sea, a uniquely oligotrophic and warm environment, and
analysed the drivers that regulate gross primary production (GPP), community
respiration (CR), and net community production (NCP). The study was conducted
on six oceanographic surveys following a north–south transect along the
Saudi Arabian coast. Our findings revealed that GPP and CR rates increased
with increasing temperature (R2=0.41 and 0.19, respectively;
p<0.001 in both cases), with a higher activation energy (Ea) for
GPP (1.20±0.17 eV) than for CR (0.73±0.17 eV). The higher Ea
for GPP than for CR resulted in a positive relationship between NCP and
temperature. This unusual relationship is likely driven by the relatively
higher nutrient availability found towards the warmer region (i.e. southern Red Sea), which favours GPP rates above the threshold that
separates autotrophic from heterotrophic communities (1.7 mmol O2 m-3 d-1) in this region. Due to the arid nature, the basin
lacks riverine and terrestrial inputs of organic carbon to subsidise a
higher metabolic response of heterotrophic communities, thus constraining CR
rates. Our study suggests that GPP increases steeply with increasing
temperature in the warm ocean when relatively high nutrient inputs are
present.
Introduction
The balance between gross primary production and community respiration,
which involves both autotrophic and heterotrophic metabolic activity
(Williams, 1993; Cullen, 2001; Ducklow and Doney, 2013), sets the
metabolic status of an ecosystem by defining the carbon available to fuel
pelagic food webs and determining whether plankton communities act as a
source or sink of CO2 (Del Giorgio et al., 1997; Williams, 1998).
Whereas gross primary production (GPP) typically satisfies the respiratory demands within the food web
across productive waters, the oligotrophic ocean often requires
allochthonous inputs of organic carbon to meet the metabolic requirements of
heterotrophic organisms (Smith and Mackenzie, 1987). Due to comparatively
higher carbon consumption relative to the production, planktonic
communities in low-productivity systems are in close metabolic balance, i.e. net community production (NCP) = 0 or GPP is equal to community
respiration (CR), or experience a net metabolic imbalance
(i.e. NCP < 0, GPP < CR) (Smith and Hollibaugh, 1993;
Duarte and Agustí, 1998; Duarte et al., 2013).
In tropical and subtropical oligotrophic regions, the high temperatures may
amplify the metabolic imbalances in plankton communities as CR tends to
increase faster than GPP (Harris et al., 2006; Regaudie-de-Gioux and
Duarte, 2012) if the allochthonous sources of organic carbon are enough to
subsidise their carbon demand. These allochthonous inputs may be delivered
from land through riverine discharge, from the atmosphere through
atmospheric deposition of dust and volatile organic carbon (Jurado et
al., 2008), or are exported from productive coastal habitats
(Duarte et al., 2013; Barrón and Duarte, 2015).
The Red Sea is a semi-enclosed highly oligotrophic basin (Acker et al.,
2008; Raitsos et al., 2013). It is known as one of the warmest tropical
seas, with maximum sea surface temperatures ranging from 33.0 to 33.9 ∘C during summer (Chaidez et al., 2017; Osman et al.,
2018), and up to 34–35 ∘C in certain parts of the basin
(Rasul et al., 2015; Garcias-Bonet and Duarte, 2017; Almahasheer et
al., 2018). Due to the prevailing arid conditions, the Red Sea experiences
large evaporation rates (nearly 2 cm yr-1 of freshwater from the
surface layers) while the lack of river runoff and low precipitation rates
make this system one of the saltiest seas on the planet (Sofianos, 2002;
Sofianos and Johns, 2015; Zarokanellos et al., 2017). Two wind patterns
govern the region: in the northern part, the wind coming from the northwest
remains relatively constant throughout the year, while in the southern area,
the Indian monsoon system regulates the wind dynamics (Sofianos, 2002;
Sofianos and Johns, 2015). During the winter monsoon the wind changes
direction, and this wind reversal along with the thermohaline forces drives
the overall circulation and favours the exchange of water with the Indian
Ocean (Sofianos, 2002; Zarokanellos et al., 2017).
Due to the almost negligible terrestrial inputs, the intrusion of
nutrient-rich waters from the Indian Ocean through the Bab el Mandeb Strait
(Sofianos and Johns, 2007; Raitsos et al., 2015; Kürten et al.,
2016), together with aeolian dust and aerosol deposition (Chen et al.,
2007; Engelbrecht et al., 2017), represents the primary source of nutrients
into the basin. Thus, nutrient availability in the Red Sea follows a
latitudinal pattern that is opposite to the one of salinity, but parallel to
the thermal gradient, with nutrient-richer and warmer waters towards the
southern Red Sea compared to the cooler and more oligotrophic northern Red
Sea (Sofianos, 2002; Raitsos et al., 2015).
Studies based on ocean colour data revealed that chlorophyll a (Chl a)
concentrations decline from the southern Red Sea to the northern Red Sea
(Raitsos et al., 2013; Kheireddine et al., 2017; Qurban et al., 2017) and
depict a clear seasonality. During wintertime, when the maximum exchange of
water with the Indian Ocean takes place, Chl a concentration peaks,
decreasing towards the summer period when the water column is mostly
stratified (Sofianos, 2002). Measurements of primary production also
revealed that phytoplankton photosynthetic rates follow the same south-to-north gradient as Chl a and nutrient concentration (Qurban et al., 2017;
López-Sandoval et al., 2019). However, reports regarding the metabolic
balance of the plankton communities are scarce, mostly focus on the
contribution of the autotrophic community via photosynthetic processes
(Levanon-Spanier et al., 1979; Qurban et al., 2014; Rahav et al., 2015),
or are restricted to specific regions (Tilstra et al., 2018).
Based on available evidence, we hypothesise that the high gross primary
production expected in the southern Red Sea may be counterbalanced by a
higher respiratory demand in these warm waters and that NCP might decline
towards the relatively unproductive waters of the northern Red Sea. With the
expected decrease in GPP towards the northern region, planktonic metabolism
might be driven mainly by heterotrophic communities (Duarte and Agustí,
1998; Duarte et al., 2013). However, the absence of significant
allochthonous subsidies in the basin may hamper the metabolic response of
the heterotrophic plankton communities. Hence, it remains unclear what the
metabolic balance of plankton communities is and whether a south to north
latitudinal gradient in NCP exists in the Red Sea.
Here we report the variability of plankton community metabolism (GPP, CR, and
NCP) along a latitudinal gradient in the Red Sea and examine if the
temperature dependence of planktonic metabolic rates in this basin is
consistent with those reported for the global ocean (López-Urrutia et
al., 2006; Regaudie-de-Gioux and Duarte, 2013; García-Corral et al., 2017).
We did so by conducting measurements as part of six surveys along the
south–north latitudinal gradient in the Saudi Arabian economic exclusive zone in the Red
Sea waters. Specifically, we determined plankton metabolic rates between
winter 2016 and spring 2018, thus allowing us to (1) delineate the seasonal
variability of the gross primary production and community respiration along
the Red Sea, (2) quantify changes in the metabolic balance (net community
production), and (3) test the hypothesised roles of productivity gradients and
temperature in driving NCP.
Material and methodsField sampling
We conducted six oceanographic surveys: two during autumn (October and
November 2016), two during winter (February 2016 and January 2017), one in
summer (August 2017), and one in spring (March 2018) on board the R/V
Thuwal and R/V Al Azizi. Sampling was conducted following a latitudinal transect along the
Red Sea within a region limited by coordinates 17.25 to 27.82∘ N and 34.83 to 41.39∘ E (Fig. 1). At
each station, vertical profiles of temperature and salinity were obtained
with a Sea-Bird SBE 911plus CTD profiler (Sea-Bird Electronics, Bellevue,
WA, USA), equipped with additional sensors to measure the attenuation of
photosynthetically active radiation (PAR) (Li-cor biospherical PAR
sensor), in vivo fluorescence (WetLabs ECO-FL fluorometer), and dissolved oxygen
concentration (Sea-Bird SBE 43 dissolved oxygen sensor). Water samples for
chemical and biological measurements were collected between 07:00 and 09:00
local time, using a rosette sampler equipped with 12 Teflon Niskin bottles
(12 L) that were provided with silicone O-rings and seals.
Stations sampled along the Red Sea during (a) spring 2018, (b)
summer 2018, (c) autumn 2016, and (d) winter 2016 and 2017.
Inorganic nutrients and chlorophyll a concentration
Water samples for nutrient analyses were collected in 50 mL polyethylene
bottles and kept frozen (-20 ∘C) until further processing.
Inorganic nutrient concentration was determined with a SEAL AA3 segmented
flow analyser (SEAL Analytical Inc., WI, USA) using standard methods
(Hansen and Koroleff, 1999). The detection limits were 0.05 µM
for nitrate, 0.01 µM for nitrite, 0.01 µM for phosphate, and 0.08 µM for silicate. For the chlorophyll a analysis, 200 mL samples were
taken at 10 discrete depths (between 5 and 200 m) and filtered through
Whatman GF/F filters. The filters were kept frozen (-20 ∘C)
until further analysis. Pigments were extracted for 24 h using 90 %
acetone and left overnight in the dark at 4 ∘C. The Chl a
concentration was estimated with the non-acidification technique using a
Trilogy fluorometer equipped with a CHL-NA module (Turner Designs, San Jose,
USA), previously calibrated with pure Chl a.
Net community metabolism, community respiration, and gross primary
production
Plankton metabolic rates were determined in vitro by measuring the changes in
dissolved oxygen concentration after 24 h light–dark bottle (Winkler)
incubations (Carpenter, 1965). This methodology, commonly used to
determine plankton metabolic rates (Williams et al., 1979; Duarte and
Agustí, 1998; Bender et al., 1999; Robinson and Williams, 1999; Ducklow
et al., 2000; Serret et al., 2001, 2009; Robinson et al., 2002; García-Martín et al., 2017), allows the diel
cycle of oxygen and carbon fluxes derived from photosynthetic mechanisms
(light-dependent reactions) and also those linked to the acquisition of
energy by both autotrophic and heterotrophic microorganisms (light- and
dark-dependent reactions)(Robinson and Williams, 2005; Williams and del
Giorgio, 2005) to be accounted for .
Water samples were collected at three different optical depths (ζ)
through the water column. One at the surface (100 %–80 % of incident PAR),
another towards the bottom of the photic layer (8 %–1 % of incident PAR),
and one intermediate sample at a depth of the chlorophyll maximum (Chl a
max). In case the Chl a max was sampled at the surface or bottom layers, the
intermediate sample was taken between 1.5 and 2.3 ζ (i.e. 22 %–10 %
of incident PAR). Seawater was collected directly from the Niskin bottles to
fill a total of 21 (100 mL) Winkler bottles. The bottles were carefully
filled using silicone tubing, and the water was allowed to overflow during the filling, taking special care to avoid the formation of air bubbles. Surface
samples were collected in 100 mL quartz bottles. From each depth, seven of
the bottles were immediately fixed with manganese sulfate (MnSO4) and
potassium hydroxide / potassium iodide solution (KI / KOH) to determine the
initial oxygen concentration while the other 14 bottles, 7 light and 7 black, were incubated on deck in surface water flow-through tanks. Due to
the difference in temperature between the surface and deep waters,
particularly during the summer and autumn surveys, we decided to include in
our analyses only those samples collected above the thermocline. Changes in
temperature and PAR in the incubation tanks were recorded with HOBO Pendant®
data loggers (Onset, Massachusetts, USA).
Before the incubation, the bottles were covered with neutral mesh to reduce
the incident PAR according to the sampled depth. At the end of the
incubation period, light and dark bottles from each depth were fixed to
determine final O2 concentrations. The oxygen concentration was measured
by automated high-precision Winkler titration with a potentiometric
end-point detection (Oudot et al., 1988) using a Mettler Toledo T50
Titration Excellence auto-titrator attached to an InMotion autosampler. NCP
was calculated as the difference in the oxygen concentration between the
light bottles after the 24 h incubation period ([O2]L-24h) and
the oxygen concentration measured before the incubation ([O2]Tzero) (i.e. NCP = ([O2] L-24h- [O2]Tzero). CR
rates (mmol O2 m-3 d-1) were calculated as the difference of
the oxygen concentration after the 24 h incubation period in the dark
bottles ([O2]D-24h) and the initial oxygen concentration
([O2]Tzero) (i.e. CR = [O2]Tzero- ([O2]D-24h). GPP (mmol O2 m-3 d-1) was calculated as the sum
of NCP and CR.
Due to the consistent relationship existing between plankton metabolism and
temperature across diverse marine regions (Regaudie-de-Gioux and Duarte,
2012; García-Corral et al., 2014), we examined how plankton metabolic
rates covariate with temperature in the Red Sea, a system whose temperature
range is higher than previously encountered in marine planktonic metabolism
research. We determined the relationship between metabolic rates and
temperature by fitting an ordinary least squares linear regression equation
to the relationship between the natural logarithm of the Chl a-specific
metabolic rates (B0) and the inverse of the absolute temperature ×k (i.e.
1/kT), where k is the Boltzmann's constant (8.617734×10-5 eV K-1)
(Gillooly et al., 2001; Brown et al., 2004):
LnB0=-Ea(1/kT)+C.
In these so-called Arrhenius plots, the slope of this relationship
represents the average activation energy (Ea= negative slope), characterising the
extent of thermal dependence of metabolic processes.
Statistical analyses
Statistical analyses and figures were done using the statistical and machine
learning toolbox in MATLAB version R2018b (Mathworks Inc, Natick, MA, USA)
and with the R statistical computing package using RStudio 1.1419. Pearson
correlation tests were used (corrplot function in R) to determine the
relationship between environmental variables (temperature, nitrate + nitrite (NOx), phosphate, and silicate concentration) and their latitudinal
distribution, and to determine the relationship between volumetric
measurements of GPP, CR, NCP, and environmental variables (temperature, NOx
concentration, Chl a, and latitude). We used ordinary least squares (OLS)
simple regression models (fitlm function in MATLAB) to describe the
potential relationships between different planktonic metabolic rates and
between metabolic rates and environmental variables, and to predict the
response of the Chl a-normalised GPP (and CR) to temperature (Arrhenius
plots described in Sect. 2.3). To test if the activation energies
(obtained from the Arrhenius plots) were significantly different, we
performed an analysis of covariance (ANCOVA) by using the aoctool in MATLAB.
The variability of planktonic metabolic rates between cruises was
statistically analysed using non-parametric Kruskal–Wallis tests. Mean
values and their standard error (SE) are reported throughout the
text.
ResultsLatitudinal variability of physicochemical properties and Chl a
concentration
Hydrographic (temperature and salinity) and chemical variables (nutrient
concentrations) depicted a marked latitudinal gradient typical of the Red
Sea. At the southern-most area, sea surface temperature (SST) fluctuated
between 28 ∘C (winter–spring) and 32 ∘C
(summer), while at the far-northern sampling site SST ranged between 23 ∘C (winter) and 27–28 ∘C (summer–autumn)
(Fig. 2). Overall, all macronutrients observed a significant inverse
correlation with latitude (Pearson correlation coefficients r<-0.4, p<0.05) (Fig. 3). Nitrite + nitrate (NOx) decreased from
6.1±0.9µM in the southern region to 2.9±0.3µM towards the northern Red Sea, while on average, phosphate concentration
ranged from 0.5±0.01µM in the south of the Red Sea to 0.1±0.01µM towards the northern stations (data not shown).
Phytoplankton biomass (measured as Chl a concentration) also decreased
significantly towards the north of the Red Sea (Pearson's correlation, r=-0.4, p<0.001, and n= 77) (Table 1). We found the highest
autotrophic biomass during the autumn and winter cruises. During this
period, surface Chl a ranged from 0.6 to 0.8 mg m-3 in the southern
region and ranged from 0.2 to 0.3 mg m-3 in the north (Fig. 2). In general, our
results confirm that all variables correlated significantly with latitude,
highlighting the prevalence of the south–north gradient in temperature,
salinity, nutrient availability, and chlorophyll a concentration across the
Red Sea.
Overall seasonal and latitudinal variability of surface (a)
temperature (SST), (b) salinity, and (c) chlorophyll a concentration
(Chl a) measured during spring 2018, summer 2017, autumn 2016, and
winter 2016 and 2017 cruises along the Red Sea (∼100 % of
incident photosynthetically active radiation, PAR).
Pearson correlations between environmental variables (temperature
and the concentrations of nitrate + nitrite [NOx], phosphate, and silicate)
and their latitudinal distribution measured at selected depths: (a) the
first optical depth (from the surface down to 37 % of incident PAR) and
(b) at the bottom of the photic layer (between 1 % and 0.1 % of incident PAR
values). The size of the squares is the magnitude, and the colour indicates the
direction (green for positive correlations and purple for negative
correlations). The value of the correlation coefficient (r) is shown in the
colour bar below the graphs. Non-significant correlations are denoted with a
“×”.
Variability of plankton metabolism measured along the Red Sea
Analogous to the environmental variability, planktonic metabolism followed
the same significant north–south decreasing pattern with latitude (Fig. 4). The inverse correlation of GPP rates with latitude was highly
significant (Pearson correlation coefficient r=-0.6, p<0.001,
n= 77) (Table 1), as found for autotrophic biomass, thus explaining the
strong correlation observed between GPP and Chl a concentration (Pearson
correlation coefficient r= 0.7, n= 77) (Table 1). GPP rates decreased
on average by 79 %, from 4.1±0.5 mmol O2 m-3 d-1 (≈49.2 mgC m-3 d-1, assuming the photosynthetic
quotient (PQ) = 1) at the southernmost station of the Red Sea to 0.9±0.1 (≈ 10 mgC m-3 d-1; PQ = 1) at the northern
site, while CR decreased on average by 73 %, from 3±0.4 mmol
O2 m-3 d-1 (≈36 mgC m-3 d-1, assuming the
respiratory quotient (RQ) = 1) in the south to 0.8±0.1 in the north
(≈9.6 mgC m-3 d-1; RQ = 1) (Fig. 4). We did not find
any significant correlation between NOx availability and GPP (Pearson
correlation coefficient, p>0.05, n= 56), CR (Pearson
correlation coefficient, r= 0. 2, p>0.05), or NCP rates
(Pearson correlation coefficient, r=-0.2, p>0.05, n= 56)
(Table 1); however, all metabolic rates were positively correlated with
temperature (Table 1).
Ordinary least squares linear regression between gross primary
production (GPP), planktonic community respiration (CR), and net community
production rates (NCP) with (a, b, c) chlorophyll a concentration (Chl a),
(d, e, f) temperature, and (g, h, i) latitude. The solid red line is the
linear least square fit, while the shaded grey area represents the 95 %
confidence intervals. The coefficient of determination and the statistical
significance are indicated for each regression.
Pearson correlation matrix between volumetric gross primary
production (GPP), planktonic community respiration (CR), and net community
production (NCP) with environmental variables (temperature; latitude;
nitrite + nitrate, NOx; chlorophyll a concentration, Chl a). Bold numbers
indicate significant relationships and the significance levels are indicated
by *p<0.05, **p<0.01, and ***p<0.001.
The highest GPP and CR rates measured along the Red Sea came from data
collected during the autumn and winter cruises, when GPP and CR rates
reached values above 6 and 4 mmol O2 m-3 d-1, respectively
(Fig. 5), and when the mean values were the highest (GPPautumn-winter=2.9±0.3–2.3±0.3 mmol O2 m-3 d-1;
CRautumn-winter=2.5±0.3–2±0.2) (Fig. 5).
However, despite the overall variability between autumn–winter and
spring–summer seasons, when all data are considered together, planktonic GPP and CR
rates were not significantly different between seasons (Kruskal–Wallis H test: χ2=6.83, p= 0.08; χ2=4.14, p= 0.25, respectively). Furthermore, the balance between planktonic autotrophic
production (GPP) and respiratory losses (due to the heterotrophic and
autotrophic metabolism, CR) (i.e. NCP rates) revealed that NCP rates also
decreased towards the northern region (by 94 %). From 1.1±0.3 mmol
O2 m-3 d-1 at the southern stations to 0.1±0.1 mmol
O2 m-3 d-1 above 26∘ N (Fig. 4). The
average NCP measured during our cruises was 0.3±0.1 mmol O2 m-3 d-1 (Fig. 5), which indicates an overall prevalence of
autotrophic communities (Fig. 5). However, a closer look at our data
revealed the mean NCP rate in spring was -0.3±0.2 mmol O2 m-3 d-1 (Fig. 5), while during summer, NCP rates in the northern
region ranged from -0.6 to -0.1 mmol O2 m-3 d-1, which
provides evidence that planktonic metabolism was governed by heterotrophic
communities during both spring and summer in the northern region.
Seasonal variability of (a) gross primary production (GPP), (b)
community respiration (CR), and (c) net community production (NCP) measured
along the Red Sea. Boxplots indicate the 95 % confidence intervals (in
lighter colour) with ±1 SD (dark shaded). The central horizontal
white lines in the box mark the mean value for each season. The red dashed
lines represent the overall mean while the red dotted line in (c) defines
the limit between autotrophic and heterotrophic communities (NCP = 0).
Values inside the doughnut plots (c) indicate the percentage of heterotrophy
(NCP < 0) for each season.
When we evaluated the relationship of GPP with CR and NCP, the analysis
showed that both CR and NCP increased significantly with GPP (R2=0.62 and 0.49, respectively; p<0.001) (Fig. 6). From the
functional relationships between GPP with CR and NCP, we calculated the
threshold of GPP for metabolic equilibrium for the region. By solving for
GPP = CR and for NCP = 0 (from the relationship describing NCP as a
function of GPP), and by using the slope and intercept shown in Fig. 6a
and b, we determined that the GPP threshold that separates autotrophic from
heterotrophic planktonic communities in the Red Sea is 1.7 mmol O2 m-3 d-1 (range 1.2–1.9 mmol O2 m-3 d-1).
Ordinary least square linear regression between (a) planktonic
community respiration and (b) net community production (NCP) with gross
primary production (GPP) rates measured along the Red Sea. The ordinary
least square regression parameters (slope and intercept) and the statistical
significance of each regression are indicated. The solid red line represents
the linear least square fit and the shaded grey area represents the 95 %
confidence interval.
Metabolic rates and temperature
Due to the pervasive influence of temperature in regulating metabolic rates,
we further explored the temperature dependence of GPP and CR by analysing
the relationship between chlorophyll a-specific metabolic rates and
temperature. Our analysis revealed that both GPP and CR tended to increase
with temperature albeit with different activation energies, i.e. Ea was
significantly higher for GPP (1.20±0.17 eV) than for CR rates (0.73±0.17 eV) (ANCOVA, F= 3.96, p= 0.04) (Fig. 7). We also tested
whether the temperature-dependence response was consistent between cruises
(Fig. 8). Our results indicated a relatively higher activation energy for
GPP during the summer cruise (2.31±0.75 eV) and for CR in spring
(2.60±0.85 eV). However, the observed differences in the activation
energies for GPP were not significantly different between seasons (ANCOVA, F= 0.38, p= 0.8).
Arrhenius plots indicating temperature dependence of planktonic
metabolic rates plotted as the relationship between the natural logarithm of
(a) chlorophyll a-normalised gross primary production and (b)
chlorophyll a-normalised planktonic community respiration with temperature as
a function of 1/kT (lower axis), where k is the Boltzmann's constant (8.2×10-5 eV K-1), and T denotes the absolute temperature (K). The
corresponding temperatures in degree Celsius are shown in the upper axis for
each graph. The solid red line is the linear least square fit and the shaded
grey area represents the 95 % confidence interval. Ea represents the
activation energy (Ea= negative slope).
Arrhenius plots indicating the seasonal temperature dependence of
planktonic metabolic rates plotted as the relationship between the natural
logarithm of (a) chlorophyll a-normalised gross primary production and (b)
planktonic community respiration with temperature as a function of 1/kT
(lower axis), where k is the Boltzmann's constant (8.2×10-5 eV K-1), and T denotes the absolute temperature (K). Each line represents
the linear least square fit. Ea represents the activation energy
(Ea= negative slope).
DiscussionVariability of plankton community metabolic rates along the Red Sea
Our results demonstrate that planktonic metabolic rates are markedly
different between the southern and northern regimes of the Red Sea, with a
northward increase in the overall mean GPP and CR by factors of 5 and 4,
respectively (i.e. an absolute increase in GPP rates of 3.2 mmol O2
m-3 d-1≈38.4 mgC m-3 d-1, while absolute CR
rates increased by 2.2 mmol O2 m-3 d-1≈26.4 mgC m-3 d-1). Although, sensu stricto, the overall balance between autotrophic
metabolism and planktonic community respiration (i.e. NCP) indicated a
prevalence of autotrophic communities during our samplings along the Red
Sea. Heterotrophic communities prevailed during the spring, and in the
northern stations during the summer, which highlights the shift in the
trophic conditions in the basin. Consistent with these findings, our data
revealed that the GPP threshold that separated autotrophic from
heterotrophic communities in the Red Sea (1.7 mmol O2 m-3 d-1) is similar to that reported across oceanic communities elsewhere
(Duarte and Agustí, 1998; Duarte and Regaudie-de-Gioux, 2009),
agreeing with the oligotrophic characteristics that govern the basin at
certain periods or locations. The latitudinal differences depicted in our
results mirror the increasing north–south pattern in Chl a concentration and
photosynthetic carbon fixation rates previously reported for the Red Sea
(Acker et al., 2008; Raitsos et al., 2013; Qurban et al., 2014;
Kheireddine et al., 2017), which are supported by the presence of
different planktonic communities (Al-aidaroos et al., 2016; Pearman et
al., 2016; Robitzch et al., 2016; Kheireddine et al., 2017; Kottuparambil
and Agusti, 2018).
The lower productivity of the northern section of the Red Sea explains the
dominance of heterotrophic communities therein. Still, sustaining
heterotrophy in oligotrophic regions requires an allochthonous source of
organic matter (Duarte et al., 2011, 2013). The arid nature of the northern
Red Sea, with the watershed consisting mostly of deserts, leads to the
absence of rivers and significant organic carbon inputs to the sea. Dust
inputs are important, however, and whereas they have shown no effect on
primary production (Torfstein and Kienast, 2018), they are a source of
organic carbon (Jurado et al., 2009) that can partially supply the organic
matter required to sustain heterotrophic communities. Moreover, the Red Sea
supports highly productive coral reefs, mangrove forests, seagrass meadows,
and algal communities in its extensive shallow coastal areas (Rasul
et al., 2015; Almahasheer et al., 2016), which may export significant
organic carbon to the pelagic compartment, thereby helping to sustain
heterotrophic plankton communities in the northern Red Sea.
Temperature and metabolic balance in the Red Sea
Temperature is a master variable that regulates many components of ocean
dynamics, such as vertical stratification and most aspects of organismal
biology, from setting boundaries in the distribution of organisms
(Clarke, 1996) to controlling biochemical reactions that constrain the
energy for metabolic processes (Gillooly et al., 2001). Hence,
temperature is likely a significant driver of metabolic processes in the Red
Sea, one of the warmest tropical marine ecosystems (Raitsos et al., 2011;
Chaidez et al., 2017). Indeed, our results showed a positive response of
planktonic metabolism to temperature. Moreover, the functional relationships
between metabolic rates with temperature suggested that both GPP and CR were
positively enhanced with increasing temperature but at a different pace.
The metabolic theory of ecology (MTE) relates the metabolic rate of an
organism with its mass and temperature. This theory hypothesises that
individual metabolic rates relate to temperature with a relatively constant
activation energy (Ea∼0.63 eV) for a wide range of taxa, from
unicellular organisms to plants and animals (Gillooly et al., 2001;
Brown et al., 2004). For aerobic respiration, Ea values vary between 0.41
and 0.74 eV at temperatures between 0 and 40 ∘C (Gillooly
et al., 2005), while for photosynthetic processes the predicted Ea is
lower, ∼0.32 eV (Allen et al., 2005). From a thorough compilation
of data obtained for a wide range of marine systems (from polar to
subtropical and tropical oceanic regions), Regaudie-de-Gioux and Duarte (2012) found that overall, the activation energies for photosynthetic
production (GPP) varied between 0.29 and 0.32 eV, and for respiratory processes
(CR) between 0.65 and 0.66 eV.
The Ea for GPP (1.20±0.17 eV) obtained for the Red Sea was higher
than the overall value predicted by the MTE, while the Ea values for CR were
below those for GPP (0.72±0.17 eV) unlike those observed elsewhere in open
oceanic waters (Regaudie-de-Gioux and Duarte, 2011; García-Corral et al.,
2017). Furthermore, these Ea values imply that GPP rates increased faster
(5.1-fold) than CR rates (2.7-fold), in the Red Sea's thermal range
(22–32.5 ∘C). These findings differ with the expected
double increase in heterotrophic respiration (regarding photosynthetic
processes) with temperature (Harris et al., 2006) but are closer to the
results obtained by García-Corral et al. (2017), who recently
reported Ea values for GPP of 0.86 , 1.48, and 1.07 eV for the Atlantic, Indian, and
Pacific oceans, respectively, while the Ea values for CR found in the Atlantic, Indian,
and the Pacific oceans were 0.77, 0.57, and 0.82 eV, respectively.
The apparent contradiction between our findings and the general patterns
predicted by the MTE is, however, not surprising. In their model, Allen et
al. (2005) predict the activation energy of photosynthesis per chloroplast
(for temperatures between 0 and 30 ∘C) using the temperature-dependence parameters obtained by Bernacchi et al. (2001) for RuBisCO
carboxylation rates in one species (tobacco leaves). Although the
temperature range selected by Allen et al. (2005) comprises the optimum
temperatures of growth rates for a wide range of functional groups of marine
primary producers (Chen, 2015; Thomas et al., 2016), the
temperature observed in the Red Sea exceeded this range. Due to the fast
generation times of microbes (Collins, 2010), we can expect that
photosynthetic planktonic communities are acclimated or even locally adapted
to the thermal conditions they experience. So by favouring certain
photosynthetic or thermal traits, they can enhance their metabolism and
growth to the ambient temperature, up to their thermal optimum
(Galmés et al., 2015; Thomas et al., 2016). Therefore, it is likely
that the acclimation or local adaptation (in the long term) of
photosynthetic traits in Red Sea plankton optimises the metabolic response
at the high temperatures reached, resulting in a steeper response to
temperature than predicted by the MTE. Moreover, as the trait responses
to temperature vary among phylogenetic groups (Galmés et al., 2015, 2016; Thomas et al., 2016), we anticipated a certain
degree of discrepancy if we characterise the photosynthetic response (GPP)
of planktonic communities by considering only one trait (i.e. RuBisCO
carboxylation) of one species.
However, we must bear in mind that the metabolic response of individuals is
not only temperature dependent, and that resource supply also plays an
essential role (Brown et al., 2004; Allen and Gillooly, 2009). Our
results provide evidence that the increased response of planktonic metabolism
towards warmer temperatures was mostly confined to the southern half of the
Red Sea, which receives the direct inflow of the enriched Intermediate Water
coming from the Gulf of Aden during the winter monsoon (Raitsos et al.,
2015; Wafar et al., 2016). Recent findings have demonstrated that
mass-specific carbon fixation rates of phytoplankton communities can be
enhanced with increasing temperature when nutrients are not limiting their
growth (Marañón et al., 2014, 2018).
Therefore, it is likely that the intertwined effect of both the warmer
temperatures and the higher nutrient availability towards the south of the
Red Sea are key drivers regulating the metabolic response of planktonic
communities. Thus, unlike the global ocean, where nutrient concentration is
inversely correlated with temperature (e.g. Agawin et al., 2000), in the
Red Sea nutrient concentration and temperature are positively correlated.
This anomaly may explain the steep increase in Ea for GPP, as primary
producers in the warmer region are being supported by the inflow of
nutrient-enriched waters from the Indian Ocean.
The elevated Ea for GPP compared to CR in Red Sea plankton is also an
anomaly, likely associated with the lack of allochthonous nutrient supply
due to the absence of rivers and vegetation in the arid watershed of the Red
Sea. The warm oligotrophic ocean is characterised by plankton communities
that are in metabolic balance or net metabolically imbalanced (Duarte and
Agusti, 2008; Duarte et al., 2013). In contrast, the warm southern Red Sea
tends to support autotrophic metabolism, sustained by the input of
nutrient-enriched waters while low allochthonous carbon inputs may constrain
CR. As a result, NCP tends to increase, rather than decrease with increasing
temperature (Regaudie-de-Gioux and Duarte, 2011; García-Corral et al., 2017).
These patterns in plankton metabolism in the oligotrophic and warm Red Sea
deviate from those characterising the subtropical and tropical gyres of the
open ocean, but it provides an opportunity to explore the mechanistic basis
for patterns in plankton metabolism with temperature, which would otherwise
remain obscured by the underlying prevalent negative relationship with
nutrient concentrations.
Conclusions
Our results show that plankton metabolism in the Red Sea presents a
remarkably different pattern compared to other warm and oligotrophic marine
systems (e.g. the subtropical and tropical gyres). In this region,
autotrophic plankton communities prevailed and are supported by relatively
high GPP rates, which are above the threshold separating heterotrophic
low-productivity communities from autotrophic ones. Metabolically balanced
or net heterotrophic plankton communities dominated in the northern Red Sea,
whereas autotrophic communities were predominant in the south supported by
nutrient inputs from the Gulf of Aden. Elevated temperatures contributed to
the enhanced metabolic activity of planktonic organisms due to the increase
in kinetic energy (favouring enzymatic reactions) with temperature. Plankton
communities in the Red Sea, however, displayed activation energies for GPP
that were higher than those for CR, resulting in a positive relationship
between NCP and temperature. Those findings represent anomalies in the
relationship between metabolic rates and temperature compared to the warm,
oligotrophic open ocean. These anomalies are likely related to the higher
nutrient supply from nutrient-rich Indian Ocean waters in the warm southern
Red Sea, suggesting that GPP can respond strongly to the temperature in the
warm ocean when supported by high nutrient inputs, relative to those in the
subtropical gyres.
Data availability
The authors declare that the data supporting the findings are available
within the article and from the authors upon request.
Author contributions
DCLS, CMD, and SA designed the study; KR and PCdA obtained the data and
provided technical support; DCLS analysed the data; DCLS wrote
the article with substantial contributions from CMD and SA. All authors
discussed the results and commented on the article.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
The authors thank the editor and the reviewers for their thorough revision
and constructive comments that helped to greatly improve the paper.
Financial support
This research has been supported by the King Abdullah University of Science and Technology (grant nos. BAS/1/1071-01-01 assigned to CMD, BAS/1/1072-01-01 assigned to SA, and FCC/1/1973-21-01 assigned to RSRC).
Review statement
This paper was edited by Stefano Ciavatta and reviewed by two anonymous referees.
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