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 6 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. 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Mixed Effects Models and Extensions in Ecology with R. Springer, New York, 574 pp. 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.
