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Zapata et al-2019-Journal of Phycology

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J. Phycol. *, ***–*** (2019)
© 2019 Phycological Society of America
DOI: 10.1111/jpy.12900
NON-RANDOM DISTRIBUTION AND ECOPHYSIOLOGICAL DIFFERENTIATION OF
PYROPIA SPECIES (BANGIALES, RHODOPHYTA) THROUGH ENVIRONMENTAL
GRADIENTS1
Javier Zapata
Departamento de Ecologıa y Biodiversidad, Facultad de Ciencias de la Vida, Universidad Andres Bello, Rep
ublica 440, Santiago, Chile
Centro de Investigaci
on e Innovaci
on para el Cambio Climatico (CiiCC), Facultad de Ciencias, Universidad Santo Tomas, Ej
ercito
146, Santiago, Chile
Andr
e s Meynard
Departamento de Ecologıa y Biodiversidad, Facultad de Ciencias de la Vida, Universidad Andres Bello, Rep
ublica 440, Santiago, Chile
Centro de Investigaci
on Marina Quintay (CIMARQ), Facultad de Ciencias de la Vida, Universidad Andres Bello, Quintay, Chile
Center of Applied Ecology & Sustainability (CAPES), Santiago, Chile
Crist
o bal Anguita
Departamento de Ecologıa y Biodiversidad, Facultad de Ciencias de la Vida, Universidad Andres Bello, Rep
ublica 440, Santiago, Chile
Camila Espinoza, Paula Alvear
Departamento de Ecologıa y Biodiversidad, Facultad de Ciencias de la Vida, Universidad Andres Bello, Rep
ublica 440, Santiago, Chile
Centro de Investigaci
on Marina Quintay (CIMARQ), Facultad de Ciencias de la Vida, Universidad Andres Bello, Quintay, Chile
Manoj Kumar
Climate Change Cluster (C3), University of Technology Sydney, Sydney, NSW, Australia
and Loretto Contreras-Porcia
Departamento de Ecologıa y Biodiversidad, Facultad de Ciencias de la Vida, Universidad Andres Bello, Rep
ublica 440, Santiago, Chile
Centro de Investigaci
on Marina Quintay (CIMARQ), Facultad de Ciencias de la Vida, Universidad Andres Bello, Quintay, Chile
Center of Applied Ecology & Sustainability (CAPES), Santiago, Chile
distribution, GM dominating almost exclusively on
rocky walls (where lowest PAR and T values but
maximum RH were registered). Conversely, Pyropia
orbicularis and Pyropia variabilis LM were found in high
abundance on flat rocky platforms in summer, LM and
GM also dominating flat rocky platforms in winter and
spring. LPX and catalase activity did not differed among
species in summer, while in winter activity and
transcription of cat were higher in P. orbicularis than
P. variabilis. Results suggest that tolerance to
environmental stresses such as temperature could
regulate the occurrence of P. variabilis GM on rocky
walls; conversely, abundances of P. variabilis and
P. orbicularis on flat rocky platforms would be also
regulated by other abiotic and/or biotic factors.
Recently 18 Bangiales seaweed species were reported
for the Chilean coast, including Pyropia orbicularis and
Pyropia variabilis (large [LM] and green [GM]
morphotypes). Porphyra/Pyropia spp. occur mainly in
the upper intertidal where desiccation stress is triggered
by tidal fluctuations. However, the influence of
environmental and ecophysiological variables and
seasonal
differences
on
Porphyra/Pyropia
(microhabitats) intertidal distributions is unknown.
Accordingly, we determined (i) the effect of
environmental variables (temperature [T], relative
humidity [RH], and photosynthetically active radiation
[PAR]) and season on distribution, and (ii) physiological
(cellular activity and lipid peroxidation [LPX]) and
molecular responses (antioxidant enzymes expression
at biochemical and transcript level) to desiccation stress
in both Pyropia species and morphotypes (common
garden experiment, on flat rocky platforms).
Multivariate analyses of coverage and abundance in
relation to environmental variables revealed a
significant effect of temperature on P. variabilis GM
1
2
Key index words: ecophysiology; environmental stress;
intertidal distribution; Pyropia
Abbreviations: CAT, catalase; GM, green morphotype;
LM, large morphotype; LPX, lipid peroxidation; MTT,
(3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium
bromide; PRX, peroxiredoxine; RH, relative humidity
Received 25 September 2018. Accepted 19 June 2019.
Author for correspondence: e-mail lorettocontreras@unab.cl.
1
2
J A V I E R Z A PA T A E T A L .
The red algal order Bangiales (Rhodophyta) is the
oldest taxonomically defined eukaryotic group,
whose ancient origin is supported by the finding of
the filamentous Bangia-like fossil Bangiomorpha pubescens dated to nearly 1.2 billion years (Butterfield
2000). This order is comprised of approximately 15
genera (Sutherland et al. 2011), the most conspicuous being Bangia, Porphyra, and Pyropia (Sutherland
et al. 2011, Sanchez et al. 2014). Of these, the genus
Pyropia is comprised by at least 75 known taxa.
Rocky intertidal organisms living between the lowand high-tide water lines are exposed to terrestrial
and marine conditions, with the upper range limits
determined mostly by physiological tolerances to
abiotic factors, and lower range limits being regulated mainly by biological interactions (Stephenson
and Stephenson 1949, 1972, Connell 1961a, Menge
1976). Other trophic (e.g., herbivory by fissurellid
[Fissurellidae], limpets and fishes), negative nontrophic interactions (mainly competition for space),
and meso-scale oceanographic processes (e.g.,
upwelling and downwelling) have been also suggested to modulate local dynamics of seaweed populations in coastal communities (e.g., Aguilera 2011,
K
efi et al. 2015, Broitman et al. 2001, respectively).
Species belonging to the Porphyra/Pyropia, our focus
group in this study, are distributed in temperate,
polar, and tropical water bodies (Guiry and Guiry
2019), where most inhabit the upper intertidal
rocky zone. Within this zone, several environmental
variables including air, temperature (T), relative
humidity (RH), ultraviolet/photosynthetically active
radiation (UV/PAR), salinity, nutrient availability,
and desiccation, among others, regulate their local
population abundance and persistence (Zaneveld
1969, Davison and Pearson 1996, Ji and Tanaka
2002, L
opez-Cristoffanini et al. 2013). All of these
environmental stresses would have similar impacts
through exerting a substantial pressure on osmotic
balance of seaweed cells and affecting various physiological functions at the cellular level (Kumar et al.
2014). In intertidal seaweeds, desiccation results in
decreased intracellular water levels during air exposure, in turn leading to physiological alterations primarily through reactive oxygen species (ROS)
generation, which is a common alteration to different types of stresses. Nonetheless, in the desiccation
stress-tolerant species Pyropia orbicularis (Ramırez
et al. 2014), which inhabits the upper intertidal
zone along much of the Chilean coast, various desiccation tolerance mechanisms activated during low
tide result in rapid physiological recovery during
rehydration (Kim et al. 2008, Gao et al. 2011, Contreras-Porcia et al. 2012, Flores-Molina et al. 2014). In
this alga, ABA overproduction during desiccation
was found to induce activation of antioxidant
enzymes (including catalase [CAT], thioredoxin
[TRX] and peroxiredoxin [PRX]), concomitant
with low lipid peroxidation and high cell viability
(Contreras-Porcia et al. 2012, Ramırez et al. 2014,
Guajardo et al. 2016). Additionally, L
opez-Cristoffanini et al. (2015), Contreras-Porcia et al. (2017),
and Fierro et al. (2017) reported the disassembly of
actin filaments and activation of ABC-transporters
both at the protein and transcriptional levels to
eliminate toxic compounds (methylglyoxal), as a tolerance mechanism to desiccation stress in Pyropia
orbicularis.
New species of the Porphyra/Pyropia complex has
been recently described globally, and other were reassigned to the appropriate genus, based on wide sampling and molecular analyses (e.g., Sutherland et al.
2011, Mateo-Cid et al. 2012, Nelson 2013, Verges et al.
2013, Niwa et al. 2014, Sanchez et al. 2014, Lindstrom
et al. 2015, Guillemin et al. 2016). The reassignment
of species between the Porphyra and Pyropia genera
brings with it changes to the ecological knowledge of
this complex. As a result, there is a need to determine
specific distribution patterns within the intertidal
zone, where a gradient of environmental variations
exists on small spatial and temporal scales (Davison
and Pearson 1996), and could result in “functional
niche” differentiation, congeneric species performing
optimally at different points along a resource or environmental gradient. In this context, previous studies
in brown and red algae (e.g., Billard et al. 2010, Tronholm et al. 2010, Couceiro et al. 2015, Muangmai
et al. 2016) have revealed differences in micro-niches
partitioning between related but cryptic species of
macroalgae. For example, three brown kelp (genetic)
entities of the genus Fucus vesiculosus and spiralis complex were found inhabiting different tidal positions of
the intertidal along the coasts of Northwest France
and Northern Portugal, showing differential physiological tolerances to desiccation/heat stress exposure (Billard et al. 2010, Zardi et al. 2011). The study of
Muangmai et al. (2016; along the coastline of Wellington, New Zealand) revealed the co-occurrence of
three genetic entities for the (red alga) morphospecies Bostrychia intricata, within distinct algal patches
and different intertidal habitats, wherein their distribution was strongly associated with tidal position and
wave exposure. The first one, cryptic species N4, was
found at a higher tidal position, generally in wave-protected areas, than the other two (N2 and N5); the second one (N2) was the more abundant and was more
frequently detected in wave exposed areas than N4
and N5; and cryptic species N5 was the less abundant
and had an overlapping but more restricted (locally
and across shores of Moa Point) distribution than N2
in relation to tidal position.
Recently, molecular analysis by Guillemin et al.
(2016) identified eighteen bladed Bangiales along
the Chilean coast (genetic species). Later, Meynard
et al. (2019) confirmed genetically and morphologically, and with a wider sampling within contrasting
intertidal habitat types, the existence of a new Pyropia
species in central Chile (26° S–32° S), namely Pyropia
variabilis (a sister species of Pyropia orbicularis;
Fig. 1A). This study also established that P. variabilis
I N TE R T I D A L D I S T R I B U T I O N O F P YR OP I A S P E C I E S B Y E N V I R O N ME N T A L S T R E S S
3
FIG. 1. Habit of the foliose
gametophyte sampled from the
intertidal zone in Maitencillo
beach, Valparaıso, Chile (scale
bar = 5 cm). Pyropia orbicularis
(A) and Pyropia variabilis; green
morphotype
(B)
and
long
morphotype (C).
and P. orbicularis are dominant in the upper intertidal at Maitencillo Beach, a contact zone where these
two species have overlapping distributions (Guillemin et al. 2016). Pyropia variabilis would show two
morphotypes, namely a green morphotype (GM) and
a large morphotype (LM; Fig. 1, B and C), occurring
in discrete tidal habitats. The green morphotype,
P. variabilis GM, is notable for its characteristic olivaceous green color and is dominant on (vertical)
rocky walls of the upper intertidal (Meynard et al.
2019, Fig. 1B). The large morphotype, P. variabilis
LM, has a central large frond (and frequently shorter
ones extending from the same disc) and occurs
mainly on (horizontal) flat rocky platforms of the
upper intertidal zone (just aside of rocky walls), just
as P. orbicularis (Meynard et al. 2019, Fig. 1C). These
authors suggest that these two morphs of P. variabilis
probably result from ecophysiological plasticity, or
alternatively, correspond to instraspecific genetic differentiation (which could be revealed using highly variable genetic markers, such as microsatellites) and
adaptation, to deal with microniches characterized by
contrasting environmental conditions. Therefore,
these findings highlight the importance of recognizing
the ecological and ecophysiological characteristics of
Pyropia species, which influence the specific intertidal
microniches that they are able to occupy, both locally
and regionally.
In this context, the objectives of the present study
were i) to determine the distribution of Pyropia species (P. orbicularis and P. variabilis LM and GM)
along different intertidal habitats at Maitencillo
Beach (a representative locality of central Chile) over
a yearly cycle; (ii) assess if the distribution of these
two sister Pyropia species (mentioned above) is associated with the intensity of diverse intertidal environmental variables (i.e., PAR, T and RH); and (iii)
provide physiological and molecular evidence for different tolerances to desiccation stress between Pyropia species and morphotypes, by assessing the level of
oxidized biomolecules, cellular activity, and enzymatic activity both at biochemical and transcriptional
level. The results of this study obtained will provide
new insights on the ecological microhabitat distribution of these seaweeds along the rocky intertidal
zone, and to some extent will help to understand the
process of their evolutionary divergence (or their
acclimation capacity) at the level of these microniches or microhabitats.
MATERIALS AND METHODS
Study zone analyses were performed on samples collected
from the intertidal zone of central Chile, in the Valparaıso
Region at Maitencillo (31°290 S; 71°260 W), which is located
180 km north of Santiago. Quantitative sampling was performed monthly over a period of 12 months (six during fallwinter and six during spring-summer). Samples were collected
along three transects (10–15 m long and 1–4 m depth) perpendicular to the coast. Transects were separated from one
another by 25–30 m, and each transect included the upper,
middle, lower, and vertical rocky walls of intertidal zones.
Spatial distribution of Pyropia orbicularis and P. variabilis (LM
and GM) along the rocky intertidal zone. Exact distribution patterns were identified for Pyropia variabilis morphotypes and
P. orbicularis, going from the upper (depth from 0 to 2 m) to
4
J A V I E R Z A PA T A E T A L .
the lower (depth from 2 to 4 m) intertidal zone where the Lessonia spicata belt can be found (Ramırez et al. 2018). Furthermore, seasonal variations in coverage were recorded through
the point intercept method over 10–15 reticulated 0.25 m2
quadrants per transect and intertidal zone. In the rocky walls
zone, three quadrants with a checkered layout were used.
Determining physical environmental factors (PAR, T, and RH)
intensity associated with the distribution of Pyropia orbicularis and
P. variabilis (LM and GM). In association with spatial distribution, ambient temperature (T; °C), photosynthetic active
radiation (PAR; lmol photons m2 s1), and relative
humidity (RH; %) were recorded for each monthly sampling
in the intertidal zone over the 12-month experimental period. Measurements of T and RH were recorded with installed
data loggers (iButtonâ Hygrochron Temperature/Humidity
Logger; Maxim Integrated, San Jose, CA, USA), while PAR
light intensity was measured using a quantometer with a separate sensor (Apogeeâ, model MQ-200; Santa Monica, CA,
USA). These parameters were registered during low tide.
Comparative in situ analysis of desiccation tolerance responses
between Pyropia orbicularis and P. variabilis (LM and GM). Tolerance responses to desiccation stress were evaluated monthly
during the summer and winter by quantifying oxidized biomolecules (i.e., lipoperoxide, a marker of cellular changes), cellular activity, the activation of antioxidant enzymes (i.e., CAT
and PRX), and the relative expression of cat and prx genes. In
situ experiments were performed according to Contreras-Porcia et al. (2011) and Flores-Molina et al. (2014). For this, naturally hydrated (>6 h during high tide) samples (20 individuals)
of P. variabilis morphotypes (LM and GM) and of P. orbicularis
were collected. These samples were labeled and immediately
stored in liquid nitrogen, including a control group. Then, 40
additional individuals of P. variabilis morphotypes (LM and
GM) and of P. orbicularis were exposed to air in the upper
intertidal zone, where P. orbicularis naturally occurs, for 1, 2, 4,
and 6 h. This procedure ensured that all individuals were
exposed to the same stress conditions (common garden experiment) that P. orbicularis naturally endures during low tide
(Contreras-Porcia et al. 2011, L
opez-Cristoffanini et al. 2015,
Guajardo et al. 2016, Fierro et al. 2017). After 6 h of desiccation, one sample group (20 individuals) for each species and
morphotype was rehydrated in seawater for 1, 2, 4, or 6 h to
simulate the daily tide cycle. Following this, the samples were
immediately frozen in liquid nitrogen and transported to the
laboratory for analyses.
Analysis of oxidized biomolecules. Levels of oxidized lipid
(lipoperoxide), an indicator of desiccation stress, were determined through the thiobarbituric acid method using 0.5 g of
dried algal tissue for all groups (naturally hydrated, desiccated, and rehydrated) as described by Contreras-Porcia et al.
(2011).
Cellular activity assays. Cellular activity was determined
using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide; Life Technologies, Carlsbad, CA, USA), a
compound reduced primarily through dehydrogenases, thus
forming an insoluble blue compound termed formazan (Towill and Mazur 1975). Sections of algae tissue (1 cm2) were dissected; incubated in a 2 mL solution containing 1.25 mM of
MTT dissolved in 50 mM of PBS buffer pH 7.4, and 3%
NaCl, and maintained in the dark at room temperature and
without agitation for 20 h (Chang et al. 1999). Then, the
solution was diluted in 95% ethanol and incubated for
20 min in a temperature-controlled boiling bath (100°C).
Finally, MTT reduction was determined through spectrophotometry at 570 nm wavelength.
Analysis of enzymatic activity. To quantify enzymatic activity,
protein extracts were obtained according to Contreras et al.
(2005). Between 0.5 and 1 g of algal tissue (fresh weight) was
frozen in liquid nitrogen and pulverized with a mortar and
pestle. A total of 20 mL of solution (5 mM 2-mercaptoethanol in 1 M of phosphate buffer pH 7.0) was added during
homogenization. The homogenate was filtered through Miracloth paper and centrifuged at 7,700g for 15 min at 4°C. The
pellet was discarded, and the proteins were precipitated with
0.5 g of ammonium sulfate per mL of extract for 2.5 h on
ice. The proteins were centrifuged at 7,700g for 15 min at
4°C; the supernatant was removed, and the pellet was washed
with 3–5 mL of a solution containing 2 mM 2-mercaptoethanol prepared in 1 M of phosphate buffer pH 7.0. Then, the
proteins were centrifuged at 7,700g for 15 min h at 4°C; the
supernatant was discarded, and, finally, the pellet was resuspended in a 1 mL solution of 1 M phosphate buffer pH 7.0.
The extracts were stored at 20°C. Extract protein concentration was determined using a protein quantification kit (Pierce
BCA Protein Assay Kit; Thermo Scientific) and the bicinchoninic acid (BCA) method (Smith et al. 1985). CAT activity
was accomplished using a reaction solution containing
16 mM H2O2 and 50–100 lg of proteins, in a total reaction
volume of 1 mL supplemented with 0.1 M phosphate buffer
pH 7.0. Activity was measuring by H2O2 consumption
through spectrophotometry at k 240 nm for 5–10 min using
a molar extinction coefficient of H2O2 (e = 39.4 mM1 cm1). In turn, PRX activity was determined with a 1 mL
reaction containing 0.1 M phosphate buffer, according to
Lovazzano et al. (2013), and using 50–100 lg of proteins and
0.2 mM DTT. This methodology inactivated antioxidant
enzymes other than PRX. The H2O2 remained as unutilized
by the enzyme was indirectly detected by adding ferrous
ammonium sulfate ([NH4]2Fe[SO4]2.6H2O), which oxidizes
in the presence of H2O2 and, consequently, forms a red complex with potassium thiocyanate (KSCN; Thurman et al.
1972). This was achieved by adding 200 lL of 10 mM ([NH4]
2Fe[SO4]2.6H2O) and 100 lL of 2.5 M KSCN to 700 lL of
reaction solution. Complex formation was recorded through
spectrophotometry at 480 nm wavelength, with the remaining
concentration of H2O2 calculated through the calibration
curve using between 10 and 80 lM H2O2.
Total RNA extraction. It was isolated from 1 g of fresh tissue according to Contreras-Porcia et al. (2013). RNA yield
and quality were assessed with the NanoDropTM 1,000 Spectrophotometer (Thermo Fisher Scientific, Wilmington, DE,
USA) and denaturing 1.2% formaldehyde agarose gel electrophoresis, respectively. Residual genomic DNA was removed
using DNase I Amplification Grade (Invitrogen, Carlsbad, CA,
USA) according to the manufacturer’s instructions. Subsequently, 1 lg of RNA was reverse transcribed into cDNA for
50 min at 42°C using SuperScript II (Invitrogen) according
to the manufacturer’s protocol.
RT-qPCR. qPCR analysis was performed using the Step
OneTM Real Time PCR System (Thermo Fisher Scientific).
Specific primers were used for the following genes: senescence
associated protein (sen) -as an endogenous control gene-, catalase (cat), and peroxiredoxin (prx; Fierro et al. 2017). Each
qPCR reaction mixture contained 5 lL of the Fast SYBR
Green Master Mix, 125 ng of cDNA, 400 nM of each primer
(see Table S1 in the Supporting Information for primers and
full name of genes that were used), and RNase-free water to
a final volume of 10 lL. Amplifications were performed in
triplicate with the following thermal cycling conditions: initial
activation at 95°C for 3 min, followed by 40 cycles of 3 s at
95°C and 30 s at 60°C. Additionally, no template control reaction was included. SYBR Green fluorescence was consistently
recorded during the linear phase of cycling. To confirm the
presence of a single PCR product, a dissociation curve analysis of PCR products was performed (see Fig. S1 in the Supporting Information for melting curves). In order to estimate
assay efficiency, fivefold dilution series were created from a
I N TE R T I D A L D I S T R I B U T I O N O F P YR OP I A S P E C I E S B Y E N V I R O N ME N T A L S T R E S S
cDNA pool for each set of primers. Efficiency values were estimated from the slope of the curve following the efficiency
equation Eff = 10^1/slope. qPCR data were analyzed using Ct
values and the reference gene sen (Contreras-Porcia et al.
2013; HE859069).
Statistical analysis. All data were subjected to assessments
of homogeneity of variance (Bartlett test) and normality
(Anderson-Darling test). In order to determine the spatial
and seasonal distribution of Pyropia species and relate its variations to physical environment variables (PAR, T, and RH)
we used multivariate generalized linear models (multiGLMs)
available in the mvabund package (Wang et al. 2012) of R
Core Team (2017). First, we modeled the abundance and the
coverage of the species in response to the seasons (winter,
spring, and summer) and the intertidal habitats (upper, middle, lower, and rocky walls) as predictors. Secondly, we modeled the abundance and the coverage of the species in
response to the three environmental variables (PAR, T, and
RH). In all four models we use the negative binomial distribution (Zuur et al. 2009, O’Hara and Kotze 2010). In addition, we use a multivariate linear model (multiLM) to
determine seasonal and intertidal differences of the environment variables (Wang et al. 2012). Finally, linear models were
used to analyze the results for biomolecule lipid peroxidation, cellular activity (MTT), antioxidant enzyme activity
(CAT and PRX), and gene expressions (cat and prx). The
ecotypes were compared via a Tukey’s test using a 95% confidence interval. All analyses were performed in the R Core
Team (2017).
RESULTS
Percentage cover of Pyropia orbicularis and P. variabilis
(LM and GM) across the rocky intertidal zone. Pyropia
orbicularis and the P. variabilis morphotypes (LM
FIG. 2. Annual
distribution
patterns for Pyropia orbicularis and
P. variabilis (LM and GM).
Coverage is shown as the average
values for eight replicates within
the intertidal zone during each
evaluated season in 2014 and
2015. No individuals of either
species were found in the study
zone during autumn.
5
and GM) presented marked seasonal distribution
patterns in the intertidal zone (Fig. 2). During summer, P. orbicularis dominated the upper intertidal
zone, presenting average cover of ~8% and 7% during the years 2014 and 2015 respectively. In the
same years, P. variabilis LM had a relative cover of
~4.5% and 5% (Fig. 2), respectively, in the upper
intertidal zone. However, P. variabilis GM was only
recorded on rocky walls during the summer of
2014, with less than ~2% coverage, while in summer
2015 the coverage was 0% (Fig. 2).
Greater coverage values were recorded for Pyropia
variabilis (LM and GM) during winter and spring
(Fig. 2). Maximum values for P. variabilis GM were
obtained during winter on rocky walls, reaching
100% cover (Fig. 2). By contrast, P. variabilis LM in
the upper intertidal zone reached 50% and 60%
cover during winter and spring 2014 respectively
(Fig. 2). No individuals of either species were found
in the study zone during autumn, possibly due to
sand accretion processes. Analysis of multivariate
generalized linear models (multiGLMs) revealed significant differences in cover and abundance for
P. orbicularis and the P. variabilis morphotypes (GM
and LM) in regard to season and intertidal zone
(Table S2 in the Supporting Information).
Intensity of environmental factors associated with Pyropia orbicularis and P. variabilis (LM and GM) distribution across the rocky intertidal zone. During the study
period, photosynthetically active radiation (PAR)
ranged from 40 to 3,224 lmol photons m2 s1
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J A V I E R Z A PA T A E T A L .
TABLE 1. A) Statistical analysis of multivariate linear models (multiLMs) of environmental variables (radiation, temperature, and humidity) in response to seasonality and
intertidal level. B) Statistical analysis of multivariate Generalized linear models (multiGLMs) of coverage and
abundance of Pyropia orbicularis and P. variabilis (GM and
LM) in response to environmental variables (radiation,
temperature, and humidity).
A)
Res.df
Seasonality
Intertidal
92
89
df
3
3
21.43
29.08
Seasonality
Radiation
Temperature
Humidity
Coverage x
Environment
P. orbicularis
P. variabilis
LM
P. variabilis
GM
Abundance x
Environment
P. orbicularis
P. variabilis
LM
P. variabilis
GM
<0.00
<0.00
Intertidal
F
Pr(>F)
F
Pr(>F)
5.23
13.49
9.17
0.003
<0.00
<0.00
8.71
11.16
16.96
<0.00
<0.00
<0.00
Radiation
B)
Pr(>F)
F
Dev
Pr(>Dev)
Humidity
Dev
Pr(>Dev)
Temperature
Dev
Pr(>Dev)
0.77 0.851
0.63 0.434
0.04 0.826
3.69 0.285
0.38 0.523
3.50 0.068
12.39
0.04
0.71
0.008
0.851
0.412
0.13 0.724
0.07 0.774
11.76
2.24 0.502
2.10 0.154
0.42 0.520
4.83 0.165
2.54 0.107
3.54 0.063
10.31
1.685
0.031
0.015
0.202
0.862
0.06 0.804
0.01 0.975
8.936
0.002
<0.00
P values lower than 0.05 indicate significant differences.
Res.df: residual degrees of freedom; df: degrees of freedom;
F: f value; Pr(>F): P values; Dev: deviance value; Pr(>Dev):
P values.
FIG. 3. Annual environmental factors in the different intertidal zones. A) Photosynthetically active radiation (PAR); B) environmental temperature (T); and C) relative humidity (RH).
Values represent the average of 57 measurements taken from the
intertidal zone during 2014 and 2015. The center line of the boxplot represents the median, the vertical lines (whiskers) above
and below the boxplot represent limit for the detection of outliers, the points represent outliers that are beyond the lower or
upper limit.
(Fig. 3A). The lowest PAR levels were recorded on
rocky walls during winter, while the highest PAR values were found in the upper intertidal zone during
summer (Fig. 3A). The minimum environmental
temperature (T) of 13.5°C was registered at rocky
walls during the winter, whereas the maximum temperature (45.5°C) was recorded at middle intertidal
zone during the summer (Fig. 3B). Additionally,
rocky walls temperature was lower on average
(~20.6°C) than the other intertidal zones across seasons (Fig. 3B). Regarding relative humidity (RH),
the lowest values (15.9%) were recorded in the
upper intertidal zone during summer, while maximum values (91.9%) were found on rocky walls during winter (Fig. 3C). Indeed, rocky walls presented
on average (68.25%) greater RH values than the
other intertidal zones across seasons (Fig. 3C).
Analysis of multiGLMs evidenced significant differences for environmental factors in association with
season and intertidal zone (Table 1A). Integrative
analysis for coverage in relation to environmental
factors revealed a significant effect of T on species
distribution (Table 1B). These differences were
attributed to variations in coverage and abundance
of Pyropia variabilis GM across the intertidal zone
and on rocky walls concerning the different seasons.
Comparative in situ analyses of desiccation tolerance
responses between Pyropia orbicularis and P. variabilis
(LM and GM). Lipoperoxide (LPX). The highest levels
of lipoperoxidation were recorded during desiccation in winter for both species, with maximum values obtained in Pyropia variabilis (GM = 698.23
nmoles g TS1 and LM = 418.67 nmoles g TS1;
Fig. 4A). For both species and morphotypes, LPX
contents decreased to basal levels during rehydration (Fig. 4A). Both P. variabilis morphotypes (LM
and GM) and P. orbicularis showed lower LPX values
I N TE R T I D A L D I S T R I B U T I O N O F P YR OP I A S P E C I E S B Y E N V I R O N ME N T A L S T R E S S
in the summer than in the winter. Linear models
analyses revealed significant differences in lipoperoxidation values in association with season (ANOVA,
F1,96 = 53.47, P < 0.05) and tidal cycle (ANOVA,
F2,96 = 15.41; P < 0.05). However, significant differences were not found between the P. variabilis morphotypes (LM and GM) and P. orbicularis (ANOVA,
F2,96 = 0.79; P = 0.45; Table S3A in the Supporting
Information).
Cellular activity. Cellular activity differed significantly as a consequence of exposure to tidal cycles
(desiccation, rehydration, and a period of maximum
natural hydration; ANOVA, F2,150 = 68.50, P < 0.05)
and seasons (ANOVA, F1,150 = 55.09, P < 0.05;
Fig. 4B). Although, no significant differences were
found between species (ANOVA, F2,150 = 2.09,
P = 0.126), the highest values of cellular activity during desiccation were found in Pyropia orbicularis
(Fig. 4B). In summer, P. variabilis LM and P. orbicularis showed high cellular activity levels during desiccation as compared with maximum natural rehydration.
During rehydration, these levels decreased to basal
FIG. 4. A) Cell membrane
damage (lipoperoxides) and B)
cellular activity (MTT) in Pyropia
orbicularis (P.O), P. variabilis LM
[P.V (LM)], and P. variabilis GM
[P.V (GM)] in the winter and
summer during the daily tide cycle
(i.e. desiccation, rehydration, and
natural hydration). Values represent the average of six replicas per
treatment. The center line of the
boxplot represents the median,
the vertical lines (whiskers) above
and below the boxplot represent
limit for the detection of outliers,
the points represent outliers that
are beyond the lower or upper
limit.
7
conditions (Fig. 4B). The P. variabilis GM morphotype
did not show an increase in cellular activity during
either desiccation or rehydration in summer.
Antioxidant enzyme activities of catalase (CAT) and
peroxiredoxin (PRX). Over the different seasons, the
assessed species presented varied enzyme levels in
association with the tidal cycle (Fig. 5). The highest
activity levels of CAT and PRX were recorded during winter for all species (Fig. 5, A and B). More
specifically, Pyropia orbicularis presented the highest
CAT and PRX activities during the desiccation-rehydration cycle in winter. Significant differences were
found for CAT activity between species (ANOVA,
F2,150 = 68.20, P < 0.05), in relation to the tidal
cycle (ANOVA, F2,150 = 7.97, P < 0.05) and season
(ANOVA, F1,150 = 175.75, P < 0.05; Table S4A in the
Supporting Information), whereas PRX activity differed between species (ANOVA, F2,150 = 5.42,
P < 0.05) and the tidal cycle (ANOVA, F2,150 = 4.87,
P < 0.05; Table S4B). Tukey’s post hoc test indicated significant differences in CAT activity between
P. orbicularis and P. variabilis LM (t = 5.94;
8
J A V I E R Z A PA T A E T A L .
FIG. 5. Enzyme activity for A)
CAT and B) PRX in Pyropia
orbicularis (P.O), P. variabilis LM
[P.V (LM)], and P. variabilis GM
[P.V (GM)] in the winter and
summer during the daily tide cycle
(i.e., desiccation, rehydration, and
natural
hydration).
Values
represent the average of twelve
replicas per treatment. The center
line of the boxplot represents the
median,
the
vertical
lines
(whiskers) above and below the
boxplot represent limit for the
detection of outliers, the points
represent outliers that are beyond
the lower or upper limit.
P < 0.01), as well as with P. variabilis GM (t = 3.78;
P < 0.01) (Table S4A). For PRX activity, differences
were found between P. orbicularis and P. variabilis
GM (t = 2.66; P < 0.05; Table S4B).
Gene expression of antioxidant enzymes. Standard and
melting curve analyses revealed an amplification efficiency of 100 10% (Table S1) and a single sharp
melting peak between 71.31°C and 80.87°C for each
primer set design (Fig. S1). The quantity of transcripts
for cat and prx varied over winter-summer and the tidal
cycle (Fig. 6). Unlike lower cat expression during desiccation in summer, it was significantly higher in Pyropia orbicularis compared to P. variabilis during
desiccation in the winter (Fig. 6A). However, prx transcripts were higher in P. orbicularis as compared to
P. variabilis GM for both seasons (Fig. 6B; Table S5 in
the Supporting Information).
DISCUSSION
The results of this study showed differential distribution of Pyropia species and morphotypes along
the intertidal zone and across seasons at Maitencillo
Beach. Tolerance to environmental stress associated
with intertidal microhabitats could explain largely
the occurrence of Pyropia variabilis GM on rocky
walls of the upper intertidal; nonetheless, the distribution patterns displayed by P. variabilis LM and
P. orbicularis would probably also be regulated by
other abiotic and biotic factors. Indeed, substrate
availability, competition, herbivory and meso-scale
oceanographic processes (i.e., upwelling and downwelling) are usually mentioned regulating the local
relative abundance and persistence of marine populations (in this case, seaweeds). Concerning trophic
interactions, fissurellid limpets along with browsing
fish can have large effects, due to their high per
capita consumption rate, on both adult and juvenile
stages of algae along Chilean rocky shores (ephemeral and corticated); whereas, small molluscan grazers can have an influence mostly by removing early
life stages of algae (e.g., Buschmann 1990, Aguilera
2011). These grazers and grazers/browsers (respectively) would sequentially affect processes, such as
I N TE R T I D A L D I S T R I B U T I O N O F P YR OP I A S P E C I E S B Y E N V I R O N ME N T A L S T R E S S
9
FIG. 6. Relative
transcript
levels (mRNA) for A) cat and B)
prx in Pyropia orbicularis (P.O) and
P. variabilis GM [P.V (GM)] in the
winter and summer during the
daily tide cycle (i.e., desiccation,
rehydration, and natural hydration). Values represent the
average of three replicas per
treatment. The center line of the
boxplot represents the median,
the vertical lines (whiskers) above
and below the boxplot represent
limit for the detection of outliers,
the points represent outliers that
are beyond the lower or upper
limit.
colonization, germination of spores, and establishment of (adult) algae, in a negative way. Concerning negative nontrophic interactions (mainly
interference competition for space), these are pervasive among basal sessile species of the rocky intertidal of central Chile, and could also play a key role
in the regulation of marine seaweed populations
(K
efi et al. 2015). Among positive interactions,
some mesograzers have been shown to have positive
effects on opportunistic foliose algae and limpets in
the Chilean coast, indirectly favoring their colonization by removing preemptive competitors (TejadaMartinez et al. 2016). In contrast, while cover of
corticated algae in the mid intertidal zone has been
shown to be positively correlated with sites directly
influenced by upwelling; abundance of ephemeral
and corticated algae showed significant negative correlations among them along the shores of central
Chile (26° S–36° S; Broitman et al. 2001).
Despite all the above, in our study multivariate
analyses of both coverage and abundance of Pyropia
spp. in relation to environmental variables revealed
a significant effect of temperature on the P. variabilis GM annual intertidal distribution (Table 1B).
Conversely, no significant impact of environmental
variables was verified on P. variabilis LM and P. orbicularis percent cover and abundance (Table 1B). As
previously reported in distributional studies supported by molecular tools for intertidal sites in New
England, USA (West et al. 2005), and in the southern West Cape, South Africa (Griffin et al. 1999),
frequently a single (or two) Pyropia/Porphyra species
dominates a specific microhabitat (mostly of the
upper intertidal) with a seasonal variation of its
(their) abundance(s), whereas the other intertidal
microhabitats (in the upper or mid intertidal) are
occupied by foliose Bangiales species showing an
overlapping distribution. In this case, Pyropia variabilis (LM and GM) morphotypes, in winter and
spring, dominated the rocky walls and flat rocky
platforms (respectively) mostly of the upper intertidal zone, Pyropia variabilis GM being almost the
only foliose Bangiales occupying rocky walls. In
accordance with previous works (e.g., Ramırez et al.
10
J A V I E R Z A PA T A E T A L .
2014, Guillemin et al. 2016, Betancourtt et al. 2018,
Meynard et al. 2019), Pyropia orbicularis was found to
be distributed mostly on flat rocky platforms of the
upper intertidal zone with the highest coverage during summer time, where it showed an overlapping
distribution with the co-dominant Pyropia variabilis
LM (Fig. 2). These results suggest that P. variabilis
has managed to adapt and occupy rocky walls microhabitat (within the upper intertidal) by evolving a
wider physiological plasticity (than the other foliose
Bangiales), or by genetic divergence of a new ecotype (indeed, P. variabilis GM). These results also
suggest that other ecological factors, in addition to
microhabitat physical environmental variables, contribute to regulate abundance and persistence of
P. variabilis LM and P. orbicularis distribution on flat
rocky platforms of (mostly) the upper intertidal in
summer.
As previously mentioned, integrative statistical
analysis showed a significant impact of temperature
in the annual intertidal distribution of the Pyropia
variabilis (GM) morphotype. Concordantly, a number of studies have demonstrated the regulatory
effects of temperature on the ontogenetic development of algal species with heteromorphic life histories (Bolton and L€
uning 1982, tom Dieck (Bartsch)
1992, Gevaert et al. 2002, Wiencke and Amsler
2012). This is the case with species belonging to the
Porphyra/Pyropia complex due to alternations in the
gametophyte (macroscopic, haploid phase) and
sporophyte (microscopic, diploid phase) phases
(conchocelis). Furthermore, different optimal temperatures and PAR values have been determined for
Pyropia yezoensis and Pyropia tenera for the gametophyte and sporophyte phases (Watanabe et al. 2014,
2016), with seasonal variations existing between
gametophytes (winter-spring) and sporophytes (summer; Watanabe et al. 2014). Considering this, we
suggest that P. orbicularis and P. variabilis (LM and
GM) may possess different physiological responses
in both life stages; where P. orbicularis gametophytes
occurring in the summer would have greater environmental tolerances due to being faced with
higher temperatures, reproducing in the early winter when environmental pressures are lower. In fact,
we have recently determined that the conchocelis
phase in P. orbicularis can be found during all year,
but the major number of conchosporangia is
observed under short photoperiod (8:16 h light:dark; Figs. S2 and S3 in the Supporting Information). In P. variabilis, the major number of
conchosporangia would be observed under a lower
temperature (10°C; C.R. Bulboa-Contador, pers.
comm.), and probably its reproduction is earlier in
winter than P. orbicularis.
Results must be interpreted considering that in
this study we performed in situ common garden
experiments, where all individuals were exposed to
the same stress conditions that Pyropia orbicularis naturally endures during low tide. This common
garden experiment condition implies, in the first
place, that P. variabilis morphotypes (LM and GM)
were subjected to an environmental setting (or
intertidal microniche) that favors primarily desiccation stress, that is to say water deprivation. Conversely, the fact that experiments took place
monthly and over seasons in the field, with all its
concomitant variability in the intensity of diverse
environmental factors, could also have some degree
of influence on the intensity or variability of some
biological responses, mainly in winter. In relation to
the first point, levels of lipoperoxidation were not
significantly different between species during the
tidal cycle in summer, indicating that probably both
species are able to cope with desiccation stress.
Nonetheless, despite nonsignificant statistical differences, a high variability was observed in the level of
lipoperoxidation of P. variabilis GM during desiccation in winter, indicating that probably a confounding environmental factor could be influencing this
response. This is in accordance, in winter, with P. orbicularis showing a clear higher CAT activity and a
better regulation of (and higher) relative mRNA
levels of this enzyme (return to basal levels when
rehydrated) in comparison to P. variabilis (very high
mRNA levels when rehydrated). Similar to our findings, a significant high transcriptional regulation of
the CAT enzyme in P. orbicularis during desiccation
and rehydration was previously demonstrated (Fierro
et al. 2017). Another remarkable result was that, in
summer, the relatively low cellular activity of P. variabilis GM (Fig. 4B), along with its absence in flat
rocky platforms (Fig. 2), suggests that this morphotype would probably experience a strong fitness
trade-off between its capacity to survive, on one hand,
and to grow and proliferate, on the other hand.
A likely confounding variable explaining the
apparently better performance of Pyropia orbicularis
in comparison to P. variabilis (mainly the GM morphotype) in winter would be salinity, associated with
some events, such as coastal breeze or intermittent
rain during winter sampling, able to cause a loss of
ions and an alteration in cellular ion ratios in more
sensible species. This would be congruent with the
more northern distribution of P. variabilis, and its
likely better adaptation to higher salinities in comparison to P. orbicularis, in a region where rainfall is
infrequent, RH is lower, Sea Surface Temperature
(SST) is higher and UV radiation is considerably
higher during emersion (than the southern region
where P. orbicularis occurs). It is noteworthy that our
common garden experiments took place in “waveprotected” areas of the upper intertidal, which comprised most of the upper intertidal in summer, but
a smaller proportion of this microhabitat in winter
due to more frequent storms in winter. The high
cover of P. variabilis GM observed in the upper
intertidal in winter is probably due to the greater
area comprised by “wave-exposed” rocks in this season. It is also noteworthy that the rocky faces
I N T E R T I D A L D I S T R I B U T I O N O F PY R O P I A S P E C I E S B Y E N V I R O N M E N T A L S T R E S S
selected for sampling were also more wave-exposed
than the flat rocky platforms, or at least were waveprotected less time during the tidal cycle in summer
(accordingly with the differentiation observed in the
three environmental variables measured for this
microhabitat, as seen in Fig. 3). Other confounding
variables explaining differential performances in Pyropia spp. could be light quality and quantity, and high
temperature, usually mentioned as regulatory environmental factors affecting the photosynthetic activity of seaweed (Breeman 1988, H€ader and Figueroa
1997), many seaweeds being sensitive to enhanced
solar radiation (G
omez et al. 2004). Furthermore,
higher UV radiation, PAR and temperature are associated with oxidative stress due to ROS generation eventually leading to PSII inactivation and degradation of
reaction centers, primarily of the D1 protein, thus lowering the growth, survival, and reproduction in algal
cells (Aguilera et al. 2002, Apel and Hirt 2004). High
PAR and UV-B radiation have also been demonstrated
to differently affect the growth and photosynthetic
processes of algae distributed in different intertidal
zones, evidencing their differential abilities to tolerate
light induced photoinhibition (Bischof et al. 2006,
Roleda et al. 2006, Wiencke et al. 2007). For example,
Pyropia tenera is sensitive to photoactive radiation and
shows photoinhibition at a PAR value of
500 lmol photons m2 s1; whereas the highly tolerant Pyropia nereocystis shows photoinhibition only at a
PAR value of 2,000 lmol photons m2 s1 (Watanabe et al. 2014). In Chile species belonging to the Porphyra/Pyropia complex present sun-adaption and are
highly UV tolerant, showing no marked decreases in
photosynthesis and efficient mechanisms of photoprotection (Huovinen et al. 2006). To acclimate to a wide
spectrum of irradiances, macroalgae frequently adjust
their photosynthetic apparatus and/or regulate the
relative content of light protective pigments, such as
phycobiliproteins in different seasons (Marquardt
et al. 2010). Thus, our work suggests differences in
microniches partitioning between Pyropia spp., revealing dissimilarities in physiological tolerance to desiccation stress exposure.
CONCLUSIONS
Pyropia orbicularis and Pyropia variabilis show a nonrandom but usually overlapping distribution in
intertidal microhabitats of the central Chilean coast
and across seasons, these distributions being to
some extent determined by environmental variables.
Only the occupation of rocky walls by Pyropia variabilis appears to be associated exclusively with environmental stressors (at least at Maitencillo Beach),
as reflected by the significant relationship found
between temperatures, and its greater abundance and
cover in this microhabitat. Indeed, among the intertidal microhabitats considered, this was the only one
that was clearly differentiated in terms of T, RH, and
PAR intensities. The distribution of P. orbicularis and
11
P. variabilis is nonrandom because both algae showed
an efficient machinery to deal with desiccation stress,
in a microhabitat as (flat rocky platforms of) the
upper intertidal where few other marine organisms
are able to survive and proliferate. Pyropia and Porphyra spp. could then have converged in relation to
their morphology, but still have different (e.g., ecophysiological) adaptations to deal with specific microhabitat environmental conditions, these adaptations
being part of their “fundamental niche”. Nonetheless, the overlapping distribution observed in this
microhabitat reveals that other factors (e.g., herbivory, competition for space, mesoscale oceanographic factors like upwelling or downwelling) could
also affect their relative abundance and persistence
and then their “realized niche” and distribution. The
next logical step would be determining the magnitude of effects that these different factors exert on
the abundance and persistence of Porphyra/Pyropia
species at small spatial scale in the intertidal. Finally,
even though environmental and cover (and abundance) data suggest that an environmental (or combination of environmental) variable(s) regulate the
presence of P. variabilis GM on rocky walls, it would
be necessary to perform common garden experiments where all individuals would be exposed to the
same stress conditions that this morphotype naturally
endures during low tide (i.e., on rocky walls), or evaluate in the laboratory the independent response to
factors, such as salinity stress or temperature.
This work was supported by FONDECYT 1170881, and DI-50114/R (Universidad Andr
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Supporting Information
Additional Supporting Information may be
found in the online version of this article at the
publisher’s web site:
Figure S1. Melting curves (temperature vs. fluorescence [-d(F1)/dT]) for sen A), prx B), and cat
C) genes. All reactions with cDNA as template
showed one sharp and fully overlapping melting
peak, indicating the specificity of primers
designed. The black-filled arrow indicates the
melting temperature (Tm) of specific product in
each reaction.
Figure S2. Morphology of the mature conchocelis (microscopic stage) of Pyropia orbicularis
from Maitencillo (Chile) showing the branched
filaments and its reproductive structures, the conchosporangia. The arrow points to a fully developed conchosporangium. Scale bar = 30 µm.
Figure S3. Effect of the photoperiod on conchosporangia formation, as percentage of conchocelis
having
conchosporangia.
The
conchocelis filaments showing the maximum
effect were those cultured at an irradiance of
20 lmol photons m2 s1, a temperature of
15°C, and a short photoperiod (8:16 h light:dark
for 4 weeks) as shown in the figure. Barplots represent the average of six replicas per treatment,
vertical bars showing standard deviations, and different letters indicating statistically different
groups. Statistical analyses consisted of an analysis
of variance (ANOVA) followed by a post-hoc
Tukey test. These analyses indicated that significant differences existed between photoperiods,
the highest percentage of conchocelis with
14
J A V I E R Z A PA T A E T A L .
conchosporangia formation was observed under a
short photoperiod (8:16 h light:dark or “a”
group” in the figure) in comparison to the neutral (12:12) and long (16:8) photoperiods (both
belonging to the “b” group).
Table S1. Primers and full name of genes that
were used in the RT-qPCR analyses.
Table S2. Statistical analysis of multivariate
Generalized linear models (multiGLMs) of coverage and abundance of Pyropia orbicularis and
P. variabilis (GM and LM) in response to seasonality and intertidal level. P values lower than 0.05
indicate significant differences. Res.df: residual
degrees of freedom; df: degrees of freedom; Dev:
deviance value; Pr(>Dev): P values.
Table S3. Statistical analysis of linear models of
A) lipoperoxidation of biomolecules and B) cell
activity respect to seasonality of Pyropia orbicularis,
P. variabilis (GM and LM) and treatments (hydrated, desiccated, and rehydrated). P values
lower than 0.05 indicate significant differences.
df: degrees of freedom; Sum q: Sum square;
Mean Sq: Mean square; F: f value; Pr(>F): P values.
Table S4. Statistical analysis of linear models of
enzymatic activity CAT A), and PRX B) with
respect to seasonality, species (Pyropia orbicularis)
and morphotypes P. variabilis (GM and LM) and
treatments (hydrated, desiccated, and rehydrated). P values lower than 0.05 indicate significant differences. df: degrees of freedom; Sum q:
Sum square; Mean Sq: Mean square; F: f value; Pr
(>F): P values; Std Error: Standard Error; t: t
value; P values.
Table S5. Statistical analysis of linear models of
relative level of cat and prx transcripts, with respect
to seasonality, species (Pyropia orbicularis) and morphotype P. variabilis (GM) and treatments (hydrated, desiccated, and rehydrated). P values lower
than 0.05 indicate significant differences. df:
degrees of freedom; Sum q: Sum square; Mean Sq:
Mean square; F: f value; Pr(>F): P values.
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