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Article

High Ecophysiological Plasticity of Desmarestia aculeata (Phaeophyceae) Present in an Arctic Fjord under Varying Salinity and Irradiance Conditions

by
Johanna Marambio
1,2,3,4,*,
Nora Diehl
1,2,5 and
Kai Bischof
1,2,5
1
Marine Botany, University of Bremen, Leobner Str. NW2, 28359 Bremen, Germany
2
Alfred Wegener Institute for Polar and Marine Research, Functional Ecology, 27570 Bremerhaven, Germany
3
Laboratory of Antarctic and Sub-Antarctic Marine Ecosystems (LEMAS), Department of Sciences, University of Magallanes, Punta Arenas 6200000, Chile
4
Cape Horn International Center (CHIC), University of Magallanes, Punta Arenas 6200000, Chile
5
Center for Marine Environmental Sciences, University of Bremen, 28359 Bremen, Germany
*
Author to whom correspondence should be addressed.
Biology 2022, 11(10), 1499; https://doi.org/10.3390/biology11101499
Submission received: 26 August 2022 / Revised: 10 October 2022 / Accepted: 10 October 2022 / Published: 13 October 2022
(This article belongs to the Special Issue Polar Ecosystem: Response of Organisms to Changing Climate)
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Abstract

:

Simple Summary

The Arctic region has been affected by rising temperatures, directly affecting the organisms living there. One of the organisms that inhabit this area is the seaweed Desmarestia aculeata (Phaeophyceae), widely distributed in the North Atlantic. It is exposed to the high Arctic light regime and fluctuating salinity conditions from glacial and terrestrial run-off. Despite its abundance, little is known about D. aculeata and how environmental drivers will affect it in a future altered by climate change. During the summer of 2019, D. aculeata was collected in Kongsfjorden, Svalbard (78.9° N, 11.9° E) to investigate its physiological and biochemical responses to salinities of 34, 28, and 18, and daily cycles of irradiance (50–500 μmol photons m−2s−1) at 0 °C over 21 days. Photosynthetic parameters and high pigment concentrations show how this species has an effective acclimation to irradiance changes, being unaffected by low salinity. The high concentration of antioxidant phlorotannins at low salinity show how D. aculeata can regulate its daily cycle despite the hyposaline conditions. Salinity and light are interacting factors in the acclimation process. Our work shows the high plasticity of D. aculeata, such that the species will probably be able to tolerate future changes in the Arctic.

Abstract

The seaweed Desmarestia aculeata (Phaeophyceae) is distributed in the temperate zone of the North Atlantic up to the Arctic, where it is exposed to a high Arctic light regime and fluctuating salinity conditions resulting from glacial and terrestrial run-off. Information on how this species is able to thrive under current and future Arctic conditions is scarce. During the Arctic summer of 2019, D. aculeata was collected in Kongsfjorden, Svalbard (78.9° N, 11.9° E) to investigate its physiological and biochemical responses to variations in salinity (salinities: 34, 28 and 18) and daily cycles of irradiance (50–500 μmol photons m−2s−1) at 0 °C over 21 days. The species revealed effective short-term acclimation to both abiotic drivers. Maximal quantum yield of PSII (Fv/Fm) fluctuated with the light cycle at a salinity of 34, while the maximum relative electron transport rate (rETRmax) significantly differed between salinities of 28 and 18. Chlorophyll a and β-Carotene remained at high concentrations in all treatments showing pronounced acclimation during the experiment. High mannitol concentrations were measured throughout the experiment, while phlorotannins were high at low salinity. Hyposalinity and light are interacting drivers of the physiological and biochemical acclimation process for D. aculeata. Our experiment highlights the high ecophysiological plasticity of D. aculeata, suggesting that the species will likely be capable of withstanding future habitat changes in the Arctic.

1. Introduction

Global warming generates a series of changes in Arctic marine biota, also strongly affecting the Svalbard Archipelago [1]. Marine benthic communities are constantly interacting with changes in environmental factors, especially in the intertidal zone. Increasing temperatures in the surface waters of Arctic fjords [2] result in changes in the thickness and extent of sea ice [3]. Furthermore, elevated atmospheric temperatures will increase the meltwater inflow to the fjords, altering both salinity and irradiance conditions in the water column [4]. These changes directly affect marine benthic communities, which have long been the focus of studies in Kongsfjorden, Svalbard [5]. There, habitat-providing ecosystem engineers, such as marine seaweeds, are of high ecological importance [6,7] and are key primary producers [8]. More than 197 species of seaweed have been described for the Svalbard region [9]. Among them, the brown alga Desmarestia aculeata has been shown to host a particularly diverse associated fauna comprised of 36 invertebrate species [6].
There are four possible responses of benthic communities to environmental perturbations: acclimation, adaptation, migration or death [10,11]. Therefore, only species with high ecophysiological plasticity are likely to prevail in shifting marine environments. Desmarestia aculeata can adjust pigmentation and photosynthetic responses to pronounced environmental variation throughout the summer period in Kongsfjorden, decreasing chlorophyll a concentration in the months of highest irradiance [12,13] D. aculeata has a wide distribution in the North Atlantic [14], even extensively inhabiting the Arctic coastal zone [15,16]. It is frequently found in association with its congener species D. viridis [17,18]. The species is also commonly found attached to rocks and as an epiphyte on other brown seaweeds, such as Saccharina latissima or Laminaria hyperborea [19,20], and forms extensive submarine meadows in the shallow subtidal and intertidal zones during the summer [17].
Previous studies in D. aculeata have described the lack of gene regulation under variations in temperature and carbon dioxide (CO2) levels [21], presumably resulting in high energy costs for maintenance. Furthermore, nutrient assimilation does not seem to be affected by nutrient enrichment during the summer season, thus presenting a plastic response towards this factor [22]. The effect of irradiance and temperature, and the interaction between these factors, on photosynthetic parameters (α, rETRmax or Ek) and biochemical analysis (pigment and antioxidant analysis) has been previously reported for D. aculeata [12,23,24]. In this context, temperature defines the distribution range of D. aculeata, due to its wide tolerance range of 0–20 °C [25]. The effect of other factors, such as hyposalinity, has been previously described as having negative effects on algae, e.g., P. palmata [26] or Alaria esculenta [27]. However, other species, such as Laminaria digitata or L. solidungula, show a high tolerance to hyposaline conditions [28]. In general, few studies have tested the acclimation responses of D. aculeata to multiple, and presumably interacting, abiotic factors, particularly to those relevant under climate change scenarios. Such assessment is essential to predict the performance of this species of high ecological relevance in Arctic fjord systems.
Hence, this study aims to explore the effect of interacting environmental drivers relevant to the habitat of the brown seaweed D. aculeata, specifically salinity fluctuations and light cycles (irradiance) at low temperatures. In addition, the study will contribute to our understanding of the limits of physiological tolerance of D. aculeata from the Arctic in a scenario of climate change.

2. Materials and Methods

2.1. Collection of Algal Material

This experiment was conducted at Kings Bay Marine Laboratory, Ny-Ålesund, Kongsfjorden, Spitsbergen-Svalbard in July 2019. Samples of the brown seaweed Desmarestia aculeata were collected in the intertidal zone at low tide in front of the marine laboratory (78°55′39.8″ N; 11°55′48.3″ E). The specimens were kept in seawater while they were cleaned from epiphytes and sediment. Subsequently, samples of algal tissue were collected from the frond.

2.2. Experimental Set-Up

The samples were kept in a pre-control treatment, for five days, in aerated 1 L tanks, at 0 °C with salinity (SA) 34 seawater enriched with 1/2 Provasoli solution (1/2 PES, [29], modifications: HEPES-buffer instead of Tris, double the concentration of Na2 glycerophosphate, iodine enrichment after [30]) and a constant irradiance of 50 μmol photons m−2s−1. After an acclimation period over 5 days, the experiment ran for 21 days. Therefore, the samples were pre-acclimatised to the control salinity SA 34. For 21 days at the start of the experiment, a part of the samples was kept at the control SA 34 and we proceeded to test the effects of hyposalinity at SA 28 and 18. All treatments were maintained at 0 °C. To simulate the meltwater inflow from glacial run-off, the water in the experiment was diluted using fresh water [31]. The water was exchanged every fourth day throughout the experiment. Measurements and samples were taken on days 1 and 21.
Regarding the light intensity values, these are based on Kongsfjorden values during a daily cycle [32]. Irradiance was cycled every 12 h between the highest irradiance point at 500 μmol photons m−2s−1 (HL) and the lowest at 50 μmol photons m−2s−1 (LL). The light points were reached every 12 h, increasing hourly for 12 h until HL was reached and decreasing hourly for 12 h until LL was reached, making up the 24 h daily cyclic irradiance. Measurements were made specifically at 500 μmol photons m−2s−1 (HL) and at the 50 μmol photons m−2s−1 (LL) period. The configuration of the light cycles was carried out using the ProfiLux 3 system (with LED Mitras daylight, GHL Advanced Technology, Kaiserslautern, Germany).
After the measurements (see below Physiological parameters), the samples were shock-frozen in liquid nitrogen and stored at −80 °C. Afterward, the samples were freeze-dried for 24 h, the dry weight (DW) was obtained, and the biochemical analyses were performed.

2.3. Physiological Parameters

The maximum quantum yield of photosystem II (Fv/Fm) was measured in vivo after leaving the samples for 10 min in the dark. Subsequently, photosynthesis-irradiance (P-E) curves were recorded up to an irradiance of 600 μmol photons m−2s−1 to obtain the following parameters: photosynthetic capacity expressed as maximum relative electron transport rate (rETRmax), saturation irradiance (Ek), and photosynthetic efficiency (α, initial linear slope). The (P-E) curves were fitted according to the equation of Platt et al. [33], using the program KaleidaGraph version 4.5.4 (Synergy Software, Reading, PA, USA). All analyses were performed using an amplitude-modulated chlorophyll fluorometer (Imaging PAM, Heinz Walz GmbH, Effeltrich, Germany).

2.4. Biochemical Parameters

Pigment analysis of Desmarestia aculeata was carried out following the methodology of Koch et al. [34] for brown seaweeds. Freeze-dried samples weighing 30 mg (n = 3) were measured using a high-performance liquid chromatography (HPLC) LaChromeElite system with a chilled L-2200 autosampler and an L-2450 DAD detector (VWR-Hitachi International GMBh, Darmstadt, Germany). Subsequently, using the methodology of Wright et al. [35], the following pigments were quantified: Chlorophyll a (Chl a), Chlorophyll c2 (Chl c2), Fucoxanthin (Fucox), β-Carotene (β-Car), Violaxanthin (Viol), Antheraxanthin (Anthera) and Zeaxanthin (Zeax). Pigment content was finally expressed as µg g−1 (DW). Additionally, the xanthophyll cycle pool (VAZ: violaxanthin, antheraxanthin, zeaxanthin) and the de-epoxidation state (DPS) were calculated for D. aculeata.
The quantification of the content of the sugar alcohol mannitol in Desmarestia aculeata was carried out following the methodology proposed by Karsten et al. [36]. Freeze-dried samples weighing 10–15 mg were incubated in 1 mL of aqueous ethanol (70%, v/v) in a water bath at 70 °C for 4 h. Concentration determination was performed according to Diehl et al. [26]. D(-)-mannitol (C6H14O6, Roth) standards of 1, 10, and 20 mM were used for calibration. The mannitol concentration was expressed in mg g−1 (DW).
For total carbon C (% DW), total nitrogen N (% DW), and C:N (%) ratio, 4–5 mg of freeze-dried sample (n = 3) sampled at days 1 and 21 of the Desmarestia aculeata culture were used. The measurement time of each sample was 150 s The samples were combusted at 1000 °C, acetanilide (C8H9NO) was used as standard, C and N samples were quantified using the Euro EA 3000 Elemental Analyser (Eurovector S.P.A., Milan, Italy). Total C and N concentrations were expressed in mg g−1 dry weight (DW). The C:N ratio (%) was obtained based on these results.
The concentration of phlorotannins in D. aculeata was measured using the Folin-Ciocalteu method described by Cruces et al. [37]. Purified phloroglucinol (Sigma-Aldrich) was used as standard. Freeze-dried samples of 20 mg (n = 3) were used for extraction and quantification. One millilitre of acetone (70%, v/v) was added to each sample and subsequently kept at 4 °C for 24 h in the dark. Absorbance was measured at λ = 730 nm using a microplate spectrophotometer. Finally, the quantification of total soluble phlorotannins was expressed in mg g−1 (DW).

2.5. Statistical Analysis

Statistical analyses were performed considering day 1 and 21 of culture. Tests for normal distribution (Shapiro-Wilk test; p > 0.05) were performed for all data sets. The data were log10-transformed where necessary. Three-way ANOVAs were then performed for each parameter measured. Tukey’s post-hoc test was applied to detect significant differences (p < 0.05). This test was applied for each parameter analysed. Statistical analyses were run using RStudio (version 1.1.383, Boston, MA, USA).

3. Results

Regarding the photosynthetic parameters of Desmarestia aculeata, only a few clear impacts could be determined (Table 1). The rETRmax and α tended to decrease over time, while Ek and the Fv/Fm remained almost unchanged. Even though significant differences regarding salinity were found for rETRmax and Ek. Light had no major impact on the photosynthesis, however, significantly higher rETRmax, Ek and Fv/Fm values were measured in the HL treatments, mainly at SA 34 on day 1. Interestingly, different interactions between days, light and salinity were detected within all parameters, mainly in the parameters rETRmax, Ek, and Fv/Fm (Table S1: Photosynthetic parameter).
Pigments were almost unaffected throughout the experiment and by the different treatments (Table 2 and Table 3), and an interaction between days, light and salinity was only detected for fucoxanthin (Table S1: Pigments). Few significant differences in pigment concentrations were found for Chl c2, β-Car and Fucox, which, however, could not be directly assigned to the sampling day, high light (HL), low light (LL) or hyposalinity. The VAZ significantly decreased from day 1 to day 21 at SA 34 and 28, and revealed lower concentrations in the HL treatments on day 1. Increases in the DPS were only determined when comparing day 1 and 21 at SA 34 and 28. No differences were found for the light and salinity treatments.
Mannitol (Figure 1a) neither changed over time nor was affected by light or salinity. However, significant interactions between light and salinity were found (Table S1: Sugar Alcohol). Overall, high mannitol values were recorded in all samples during the experiment (Figure 1a). Significantly higher phlorotannin concentrations were measured at lower salinities (SA 28 and 18) and the content increased over time (Figure 1b). Regarding the different light treatments, no significant differences between HL and LL were detected, except for the samples from day 21 at SA 34.
The total carbon (C) content remained completely unchanged throughout the experiment (Figure 2b). Similarly, total nitrogen (N) showed no significant differences with light or salinity (Figure 2a). However, total N significantly changed over time; there was no trend towards higher or lower concentrations. The C:N ratio did not reveal clear effects in the different treatments (Figure 2c). Over time, higher C:N ratios were only found at SA 28 and the significant impact by salinity could not be assigned to the absolute salinities in general. Significantly lower total N at SA 28 and HL on days 21 resulted in significantly higher C:N ratios in the same samples. However, total N, total C and the C:N ratio exhibited days:light:salinity interactions (Table S1: Total Contents).

4. Discussion

In this study, physiological and biochemical acclimation processes of the brown seaweed Desmarestia aculeata were evaluated after simulating different salinity conditions and diurnal changes in irradiance. The tested environmental parameters and time were observed to mainly have an impact on the photosynthetic responses of D. aculeata, while biochemical acclimation was less pronounced. The observed strong interactive effects of light, salinity and time highlight the complex interplay of the various environmental factors affecting the species.
Salinity variation, as a consequence of increased meltwater discharge to Arctic fjords, has been widely described as a direct effect of climate change [38,39]. It has been observed that decreasing salinity in the first few meters of the water column directly affects photosynthetic performance in polar brown algae [26,27,40]. However, in addition to such changes occurring by global warming, diurnal variation in irradiance represents an additional stress factor for seaweeds. Hanelt et al. [41,42] described how fluctuations in daily irradiance levels during the Arctic summer affect internal photosynthetic and biochemical regulation in seaweeds. Hence, brown seaweeds inhabiting the shallow subtidal zone are constantly exposed to marked variations in salinity and irradiance levels. Our study revealed the resilience of the species D. aculeata to environmental changes, namely changes in salinity and irradiance, facilitated by a high plasticity of its internal regulation.
This high tolerance of certain brown seaweeds to varying salinity agrees with what was recorded in our experiment. The Fv/Fm of D. aculeata was not diminished by decreasing salinities. However, other photosynthetic parameters such as rETRmax and Ek showed clear responses to low salinities of SA 28 and 18, respectively. The variations of rETRmax and Ek show how this species is able to regulate its photosynthetic activity and ensure that the maximal quantum yield of PSII is maintained at high values. Irradiance plays a fundamental role in the photosynthetic processes of seaweeds [43]. However, during our experiment, the photosynthetic variables of D. aculeata were not generally affected by variations in the daily course of irradiance. The fact that both high light (HL) and low light (LL) had no major effect highlights the high plasticity of D. aculeata to a fluctuating light climate, given by its ability for internal regulation. This observation differs from the high sensitivity described for D. aculeata under constant light intensities. Marambio and Bischof [24] described how high constant irradiance affects the photosynthetic parameters of D. aculeata, such as Fv/Fm, rETRmax, α, and Ek, over time. Fv/Fm has been observed to decrease during periods of high irradiance, for example in L. digitata and Saccharina latissima [44,45] or Chondrus crispus analysed under natural and laboratory conditions [46]. All these species showed a high acclimation to daily cyclic variations in irradiance.
Regarding pigments, we observed that Chl a and β-Car in D. aculeata were neither affected by high nor low daily irradiance, or by low salinity. On the other hand, the accessory pigments Chl c2 and Fucox apparently have a crucial role as photosynthetic regulators: under the variation of daily cyclic irradiance, these two pigments showed a high acclimation to HL and LL during the experiment at high and low salinity, but VAZ and DPS were not affected by the low salinities SA 28 and 18. This is contrary to what has been observed in other species, such as S. latissima, which in laboratory culture has been shown to be strongly affected by the low salinity [47].
Mannitol is part of carbon storage in the photosynthetic process in brown seaweeds [48]. Additionally, this photosynthetic product acts as protectant against osmotic stress [49,50]. However, during our experiment, we did not find any effect of salinity or irradiance on the mannitol concentration in D. aculeata during the 21 days of treatment. Still, high concentrations were observed throughout all treatments. On the one hand, constant high mannitol content could be an acclimation to the frequently experienced environmental fluctuations in the intertidal zone, where D. aculeata was collected. On the other hand, we suspect that the high concentrations are an additional thermal protection mechanism of D. aculeata, since mannitol can also act as an anti-freezing compound [51]. As reported by Monteiro et al. [52], the brown alga S. latissima also reaches concentrations of approximately 200 mg g−1 DW at SA 30 and 0 °C, which is in agreement with what was measured in our study. However, the effect of low temperature on D. aculeata was not specifically evaluated during our experiment.
Phlorotannins, another important group of brown algal compounds, have been described as contributing to the reinforcement of cell walls under hyposaline conditions, e.g., in the brown alga Alaria esculenta [53]. In addition, phlorotannins are actively involved in protection against intense irradiance, and protection of tissues against pathogenic microbial activity and herbivory [54,55,56]. For D. aculeata, high phlorotannin values were observed at all salinities tested in this experiment. Our results are in agreement with those described by Springer et al. [53] for A. esculenta at different salinity levels and with those observed by Ragan & Jensen [57] for Fucus vesiculosus during winter with low temperatures. Although the content of phlorotannins is overall high, a variation in concentration was observed at SA 34 under daily cycles of irradiance. Importantly, phlorotannins may be activated depending on conditions and move through the cell wall to increase their site-specific content [53,58]. It remains unresolved whether the response of phlorotannins to SA 28 and 18 on day 21 of cultivation is a driver-specific or a non-specific response of the seaweed to non-favourable conditions.
In contrast to previous studies on L. solidungula [34] and F. serratus [59] from Spitsbergen, total N and the C:N ratio of D. aculeata were not affected by salinity variations. Samples were also not affected by HL and LL. However, even though the samples were maintained at ½ PES, all treatments revealed C:N ratios higher than 20, indicating N limitation [60]. The uptake and assimilation of nutrients are known to be impacted by temperature-changing enzymatic processes [61]. It is possible that N limitation was caused by reduced N uptake potential due to the slowed enzymatic action at 0 °C.

5. Conclusions

The response of this population of D. aculeata revealed a high potential for acclimation to the different environmental parameters to which it was exposed to. In our experiment, D. aculeata responded rapidly through metabolic regulation to cyclic light variations and was not affected by the hyposaline condition. As previously mentioned, the D. aculeata population studied inhabits the intertidal and upper subtidal zone and is therefore constantly exposed to a highly dynamic abiotic environment, including exposure to meltwater (field observation). This could explain the high plasticity of this population of D. aculeata to low salinity and large fluctuations in irradiance. The reaction of photosynthetic and biochemical parameters of D. aculeata to different factors shows how this phenotype can cope with change in multiple drivers. This mechanism is key to generating resistance through a rapid and effective acclimation process [40,62].
Ecologically, D. aculeata is not a strictly polar seaweed; its life history as a temperate-boreal species gives it a unique characteristic, and it is distributed over a wide geographical range. Therefore, future changes in the habitat of this species will be determined by the intensity and duration of climate change events. Our data support that this population of D. aculeata will be able to quickly adjust to changing environmental conditions in the Arctic coastal zone due to its high ecophysiological plasticity. Finally, through the study of this population, it was possible to obtain important information about the resilience of these D. aculeata individuals, in order to predict future responses to environmental changes.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/biology11101499/s1. Table S1: Results of three-way ANOVA for Desmarestia aculeata.

Author Contributions

Conceptualization, data collection, and data analysis: J.M.; Methodology: J.M. and K.B.; Data interpretation and visualization: J.M., N.D. and K.B.; Writing—review and editing: J.M., N.D. and K.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are available in PANGEA.

Acknowledgments

The authors would like to thank the AWIPEV Research Base located in Ny-Ålesund for hosting and providing logistical and financial support from the Alfred Wegener Institute, and the AWI dive team. J.M. would like to thank the Agencia Nacional de Investigación y Desarrollo (ANID)/Programa de Becas Chile-DAAD/DOCTORADO BECAS CHILE/2017-72180000. The authors are grateful to the staff of the University of Rostock for allowing the use of laboratories for running the mannitol analyses, to the University of Bremen for the C:N analyses, and to B. Iken (University of Bremen) for pigment analyses. This study was further funded in the frame of the project FACE-IT (The Future of Arctic Coastal Ecosystems—Identifying Transitions in Fjord Systems and Adjacent Coastal Areas). FACE-IT has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869154.”

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Malavenda, S. Species diversity of macroalgae in Gronfjorden, Spitsbergen, Svalbard. Polar Res. 2021, 40, 3682. [Google Scholar] [CrossRef]
  2. Blaszczyk, M.; Ignatiuk, D.; Uszczyk, A.; Cielecka-Nowak, K.; Grabiec, M.; Jania, J.; Moskalik, M.; Walczowski, W. Freshwater input to the Arctic fjord Hornsund (Svalbard). Polar Res. 2019, 38, 3506. [Google Scholar] [CrossRef]
  3. Polyakov, I.V.; Timokhov, L.A.; Alexeev, V.A.; Bacon, S.; Dmitrenko, I.A.; Fortier, L.; Frolov, I.E.; Gascard, J.C.; Hansen, E.; Ivanov, V.V.; et al. Arctic Ocean warming contributes to reduced Polar Ice cap. J. Phys. Oceanogr. 2010, 40, 2743–2756. [Google Scholar] [CrossRef]
  4. Wiencke, C.; Clayton, M.N.; Goméz, I.; Iken, K.; Lüder, U.H.; Amsler, C.D.; Karsten, U.; Hanelt, D.; Bischof, K.; Dunton, K. Life strategy, ecophysiology and ecology of algae in polar waters. Rev. Environ. Sci. Biotechnol. 2006, 6, 95–126. [Google Scholar] [CrossRef] [Green Version]
  5. Wiencke, C.; Hop, H. Ecosystem Kongsfjorden: New views after more than a decade of research. Polar Biol. 2016, 39, 1679–1687. [Google Scholar] [CrossRef] [Green Version]
  6. Lippert, H.; Iken, K.; Rachor, E.; Wiencke, C. Macrofauna associated with macroalgae in the Kongsfjorden (Spitsbergen). Polar Biol. 2001, 24, 512–522. [Google Scholar] [CrossRef]
  7. Krause-Jensen, D.; Duarte, C.M.; Hendriks, I.E.; Meire, L.; Blicher, M.E.; Marbà, N.; Sejr, M.K. Macroalgae contribute to nested mosaics of pH variability in a Subarctic fjord. Biogeosciences 2015, 12, 4895–4911. [Google Scholar] [CrossRef] [Green Version]
  8. Steneck, R.S.; Graham, M.H.; Bourque, B.J.; Corbett, D.; Erlandson, J.M.; Estes, J.A.; Tegner, M.J. Kelp forest ecosystems: Biodiversity, stability, resilience and future. Environ. Conserv. 2002, 29, 436–459. [Google Scholar] [CrossRef] [Green Version]
  9. Fredriksen, S.; Karsten, U.; Bartsch, I.; Woelfel, J.; Koblowsky, M.; Schumman, R.; Roang, R.; Steneck, R.; Wiktor, J.; Hop, H.; et al. Biodiversity of benthic macro- and microalgae from Svalbard with special focus on Kongsfjorden. In The Ecosystem of Kongsfjorden, Svalbard, Advances in Polar Ecology, 2nd ed.; Hop, H., Wiencke, C., Eds.; Springer: Cham, Switzerland, 2019; pp. 331–372. [Google Scholar]
  10. Gienapp, P.; Teplitsky, C.; Alho, J.S.; Mills, A.; Merila, J. Climate change and evolution: Disentangling environmental and genetic responses. Mol. Ecol. 2008, 17, 167–178. [Google Scholar] [CrossRef]
  11. Schaum, C.E.; Collins, S. Plasticity predicts evolution in a marine alga. Proc. R. Soc. B 2014, 281, 20141486. [Google Scholar] [CrossRef]
  12. Aguilera, J.; Bischof, K.; Karsten, U.; Hanelt, D.; Wiencke, C. Seasonal variation in ecophysiological patterns in macroalgae from an Arctic fjord. II. Pigment accumulation and biochemical defence systems against high light stress. Mar. Biol. 2002, 140, 1087–1095. [Google Scholar] [CrossRef]
  13. Bischof, K.; Hanelt, D.; Aguilera, J.; Karsten, U.; Vögele, B.; Sawall, T.; Wiencke, C. Seasonal variation in ecophysiological patterns in macroalgae from an Arctic fjord. I. Sensitivity of photosynthesis to ultraviolet radiation. Mar. Biol. 2002, 140, 1097–1106. [Google Scholar] [CrossRef]
  14. Mathieson, A.C.; Dawes, C.J. Seaweeds of the Northwest Atlantic; University of Massachusetts Press: Amherst, MA, USA, 2017. [Google Scholar]
  15. Wiencke, C.; Vögele, B.; Kovaltchouk, N.A.; Hop, H. Species composition and zonation of marine benthic macroalgae at Hansneset in Kongsfjorden, Svalbard. Ber. Polarforsch. Meeresforsch. 2004, 492, 55–62. [Google Scholar]
  16. Nielsen, R.; Lundsteen, S. Denmark’s Sea Algae, Brown Algae (Phaeophyceae) and Green Algae (Chlorophyta), Scientia Danica; The Royal Danish Academy of Sciences and Letters: Copenhagen, Denmark, 2019; pp. 1–476. [Google Scholar]
  17. Conway, E. Aspects of algal ecology. Br. Phycol. Bull. 1967, 3, 161–173. [Google Scholar] [CrossRef]
  18. Kain, J.; Jones, S. Algal recolonization of some cleared subtidal areas. J. Ecol. 1975, 63, 739–765. [Google Scholar] [CrossRef]
  19. Kitching, J.A. Studies in sublittoral ecology, III. Laminaria forest on the west coast of Scotland; A study of zonation in relation to wave action and illumination. Biol. Bull. 1941, 80, 324–337. [Google Scholar] [CrossRef]
  20. Pehlke, C.; Bartsch, I. Changes in depth distribution and biomass of sublittoral seaweeds at Helgoland (North Sea) between 1970 and 2005. Clim. Res. 2008, 37, 135–147. [Google Scholar] [CrossRef]
  21. Iñiguez, C.; Carmona, R.; Lorenzo, M.R.; Niell, F.X.; Wiencke, C.; Gordillo, F.J.L. Increased CO2 modifies the carbon balance and the photosynthetic yield of two common Arctic brown seaweeds: Desmarestia aculeata and Alaria esculenta. Polar Biol. 2015, 39, 1979–1991. [Google Scholar] [CrossRef]
  22. Gordillo, F.J.L.; Aguilera, J.; Jiménez, C. The response of nutrient assimilation and biochemical composition of Arctic seaweeds to a nutrient input in summer. J. Exp. Bot. 2006, 57, 2661–2671. [Google Scholar] [CrossRef] [Green Version]
  23. López-Figueroa, F. Control by light quality of Chlorophyll synthesis in the brown alga Desmarestia aculeata. Z. Für Nat. C 1991, 46, 542–548. [Google Scholar] [CrossRef]
  24. Marambio, J.; Bischof, K. Differential acclimation responses to irradiance and temperature in two co-occurring seaweed species in Arctic fjords. Polar Res. 2021, 40, 5702. [Google Scholar] [CrossRef]
  25. Lüning, K. Temperature tolerance and biogeography of seaweeds: The marine algal flora of Helgoland (North Sea) as an example. Helgol. Mar. Res. 1984, 28, 305–317. [Google Scholar] [CrossRef] [Green Version]
  26. Diehl, N.; Karsten, U.; Bischof, K. Impacts of combined temperature and salinity stress on the endemic Arctic brown seaweed Laminaria solidungula J. Agardh. Polar Biol. 2020, 43, 647–656. [Google Scholar] [CrossRef]
  27. Karsten, U. Salinity tolerance of Arctic kelps from Spitsbergen. Phycol. Res. 2007, 55, 257–262. [Google Scholar] [CrossRef]
  28. Marambio, J.; Rosenfeld, S.; Bischof, K. Hyposalinity affects diurnal photoacclimation patterns in the rhodophyte Palmaria palmata under mimicked Arctic summer conditions. J. Photochem. Photobiol. 2022, 11, 100124. [Google Scholar] [CrossRef]
  29. Provasoli, L. Media and prospects for the cultivation of marine algae. In Cultures and Collections of Algae, Proceedings of the Japanese Conference Hakone, Hakone, Japan, 12–15 September 1966; Watanabe, A., Hattori, A., Eds.; Japanese Society of Plant Physiologists: Tokyo, Japan, 1968; pp. 63–75. [Google Scholar]
  30. Tatewaki, M. Formation of a crustaceous sporophyte with unilocular sporangia in Scytosiphon lomentaria. Phycologia 1966, 6, 62–66. [Google Scholar] [CrossRef]
  31. Bendtsen, J.; Mortensen, J.; Rysgaard, S. Seasonal surface layer dynamics and sensitivity to runoff in a high Arctic fjord (Young Sound/Tyrolerfjord, 74° N). J. Geophys. Res.-Oceans 2014, 119, 6461–6478. [Google Scholar] [CrossRef]
  32. Bartsch, I.; Paar, M.; Fredriksen, S.; Schwanitz, M.; Daniel, C.; Hop, H.; Wiencke, C. Changes in kelp forest biomass and depth distribution in Kongsfjorden, Svalbard, between 1996–1998 and 2012–2014 reflect Arctic warming. Polar Biol. 2016, 39, 2021–2036. [Google Scholar] [CrossRef]
  33. Platt, T.; Gallegos, C.L.; Harrison, W.G. Photoinhibition of photosynthesis in natural assemblages of marine phytoplankton. J. Mar. Res. 1980, 38, 687–701. [Google Scholar]
  34. Koch, K.; Thiel, M.; Tellier, F.; Hagen, W.; Graeve, M.; Tala, F.; Laesecke, P.; Bischof, K. Species separation within the Lessonia nigrescens complex (Phaeophyceae, Laminariales) is mirrored by ecophysiological traits. Bot. Mar. 2015, 58, 81–92. [Google Scholar] [CrossRef]
  35. Wright, S.W.; Jeffrey, S.W.; Mantoura, R.F.C.; Llewellyn, C.A.; Bjørnland, T.; Repeta, D.; Welschmeyer, N. Improved HPLC method for the analysis of chlorophylls and carotenoids from marine phytoplankton. Mar. Ecol. Prog. Ser. 1991, 77, 183–196. [Google Scholar] [CrossRef]
  36. Karsten, U.; Thomas, D.N.; Weykam, G.; Daniel, C.; Kirst, G.O. A simple and rapid method for extraction and separation of low molecular weight carbohydrates from macroalgae using high-performance liquid chromatography. Plant Physiol. Biochem. 1991, 29, 373–378. [Google Scholar]
  37. Cruces, E.; Huovinen, P.; Gómez, I. Phlorotannin and antioxidant responses upon short-term exposure to UV radiation and elevated temperature in three south pacific kelps. Photochem. Photobiol. 2012, 88, 58–66. [Google Scholar] [CrossRef]
  38. Van Pelt, W.J.; Kohler, J. Modelling the long-term mass balance and firn evolution of glaciers around Kongsfjorden, Svalbard. J. Glaciol. 2015, 61, 731–744. [Google Scholar] [CrossRef] [Green Version]
  39. Małecki, J. Accelerating retreat and high-elevation thinning of glaciers in central Spitsbergen. Cryosphere 2016, 10, 1317–1329. [Google Scholar] [CrossRef] [Green Version]
  40. Fredersdorf, J.; Müller, R.; Becker, S.; Wiencke, C.; Bischof, K. Interactive effects of radiation, temperature and salinity on different life history stages of the Arctic kelp Alaria esculenta (Phaeophyceae). Oecologia 2009, 160, 483–492. [Google Scholar] [CrossRef] [Green Version]
  41. Hanelt, D.; Huppertz, K.; Nultsch, W. Daily course of photosynthesis and photoinhibition in marine macroalgae investigated in the laboratory and field. Mar. Ecol. Progr. Ser. 1993, 97, 31–37. [Google Scholar] [CrossRef]
  42. Hanelt, D.; Jaramillo, M.J.; Nultsch, W.; Senger, S.; Westermeier, R. Photoinhibition as a regulative mechanism of photosynthesis in marine algae of Antarctica. Ser. Cient. INACH 1994, 44, 76–77. [Google Scholar]
  43. Wiencke, C.; Gómez, I.; Dunton, K. Phenology and seasonal physiological performance of polar seaweeds. Bot. Mar. 2009, 52, 585–592. [Google Scholar] [CrossRef]
  44. Hanelt, D.; Melchersmann, B.; Wiencke, C.; Nultsch, W. Effects of high light stress on photosynthesis of polar macroalgae in relation to depth distribution. Mar. Ecol. Progr. Ser. 1997, 149, 255–266. [Google Scholar] [CrossRef] [Green Version]
  45. Hallerud, C.B. Pigment Composition of Macroalgae from a Norwegian Kelp Forest. Master’s Thesis, Norwegian University of Science and Technology, Trondheim, Norway, 2014. [Google Scholar]
  46. Sagert, S.; Forster, R.; Feuerpfeil, P.; Schibert, H. Daily course of photosynthesis and photoinhibition in Chondrus crispus (Rhodophyta) from different shore levels. Eur. J. Phycol. 1997, 32, 363–371. [Google Scholar] [CrossRef] [Green Version]
  47. Li, H.; Monteiro, C.; Heinrich, S.; Bartsch, I.; Valentin, K.; Harms, L.; Glöckner, G.; Corre, E.; Bischof, K. Responses of the kelp Saccharina latissima (Phaeophyceae) to the warming Arctic: From physiology to transcriptomics. Physiol. Plantarum. 2020, 168, 5–26. [Google Scholar] [CrossRef]
  48. Groisillier, A.; Shao, Z.; Miche, G.; Goulitquer, S.; Bonin, P.; Krahulec, S.; Nidetzky, B.; Duan, D.; Boyen, C.; Tonon, T. Mannitol metabolism in brown algae involves a new phosphatase family. J. Exp. Bot. 2013, 65, 559–570. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  49. Conde, A.; Silva, P.; Agasse, A.; Conde, C.; Geró, H. Mannitol transport and mannitol dehydrogenase activities are coordinated in Olea europaea under salt and osmotic stresses. Plant Cell Physiol. 2011, 52, 1766–1775. [Google Scholar] [CrossRef] [PubMed]
  50. Dittami, S.M.; Gravot, A.; Renault, D.; Goulitquer, S.; Eggert, A.; Bouchereau, A.; Boyen, C.; Tonon, T. Integrative analysis of metabolite and transcript abundance during the short-term response to abiotic stress in the brown alga Ectocarpus siliculosus. Plant Cell Environ. 2011, 34, 629–642. [Google Scholar] [CrossRef] [PubMed]
  51. Elliott, G.D.; Wang, S.; Fuller, B.J. Cryoprotectants: A review of the actions and applications of cryoprotective solutes that modulate cell recovery from ultra-low temperatures. Cryobiology 2017, 76, 74–91. [Google Scholar] [CrossRef]
  52. Monteiro, C.; Li, J.; Diehl, N.; Collén, J.; Heinrich, S.; Bischof, K.; Bartsch, I. Modulation of physiological performance by temperature and salinity in the sugar kelp Saccharina latissima. Phycol. Res. 2021, 69, 48–57. [Google Scholar] [CrossRef]
  53. Springer, K.; Cornelius, L.; Lütz-Meindl, U.; Wendt, A.; Bischof, K. Hyposaline conditions affect UV susceptibility in the Arctic kelp Alaria esculenta (Phaeophyceae). Phycologia 2017, 56, 675–685. [Google Scholar] [CrossRef]
  54. Schoenwaelder, M.E.A. The occurrence and cellular significance of physodes in brown algae. Phycologia 2002, 41, 125–139. [Google Scholar] [CrossRef]
  55. Amsler, C.D.; Fairhead, V.A. Defensive and sensory chemical ecology of brown algae. Adv. Bot. Res. 2006, 43, 1–91. [Google Scholar] [CrossRef]
  56. Falkenberg, L.; Connell, S.; Russell, B. Herbivory mediates the expansion of an algal habitat under nutrient and CO2 enrichment. Mar. Ecol. Progr. Ser. 2014, 497, 87–92. [Google Scholar] [CrossRef]
  57. Ragan, M.A.; Jensen, A. Quantitative studies on brown algal phenols. II. Seasonal variation in polyphenol content of Ascophyllum nodosum (L.) Le Jol. and Fucus vesiculosus (L.). J. Exp. Mar. Biol. Ecol. 1978, 34, 245–258. [Google Scholar] [CrossRef]
  58. Koivikko, R.; Loponen, J.; Honkanen, T.; Jormalainen, V. Contents of soluble, cell-wall-bound and exuded phlorotannins in the brown alga Fucus vesiculosus, with implications on their ecological functions. J. Chem. Ecol. 2005, 31, 195–212. [Google Scholar] [CrossRef] [Green Version]
  59. Gordillo, F.J.L.; Dring, M.J.; Savidge, G. Nitrate and phosphate uptake characteristics of three species of brown algae cultured at low salinity. Mar. Ecol. Progr. Ser. 2002, 234, 111–118. [Google Scholar] [CrossRef]
  60. Atkinson, M.J.; Smith, S.V. C: N: P ratios of benthic marine plants. Limnol. Oceanogr. 1983, 28, 568–574. [Google Scholar] [CrossRef]
  61. Hurd, C.L.; Harrison, P.J.; Bischof, K.; Lobban, C.S. Seaweed Ecology and Physiology, 2nd ed.; Cambridge University Press: Cambridge, UK, 2014. [Google Scholar]
  62. Alexieva, V.; Ivanov, S.; Sergiev, I.; Karanov, E. Interaction between stresses. Bulg. J. Plant Physiol. 2003, 29, 1–17. [Google Scholar]
Biology 11 01499 g001 550
Figure 1. Concentration in mg g−1 dry weight (DW) for compounds in Desmarestia aculeata: (a) Mannitol; (b) Phlorotannins. Experimental set-up: salinity (SA)–Light (L) (High Light (HL)–Low Light (LL)) treatments. Values are means ± SD (n = 3). Statistically significant differences between HL and LL per treatments are marked by different lowercase letters. Statistically significant differences between treatment days (1–21) are marked by different uppercase letters and differences between salinities (SA 34, 28, and 18) are marked by different uppercase letters outside the graph. For all the data, three-way ANOVA with post-hoc Tukey’s test was performed (p < 0.05).
Figure 1. Concentration in mg g−1 dry weight (DW) for compounds in Desmarestia aculeata: (a) Mannitol; (b) Phlorotannins. Experimental set-up: salinity (SA)–Light (L) (High Light (HL)–Low Light (LL)) treatments. Values are means ± SD (n = 3). Statistically significant differences between HL and LL per treatments are marked by different lowercase letters. Statistically significant differences between treatment days (1–21) are marked by different uppercase letters and differences between salinities (SA 34, 28, and 18) are marked by different uppercase letters outside the graph. For all the data, three-way ANOVA with post-hoc Tukey’s test was performed (p < 0.05).
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Biology 11 01499 g002 550
Figure 2. Elemental composition of Desmarestia aculeata at days 1 and 21 of treatment. (a) Contents of total N (% DW); (b) Contents of total C (% DW); (c) C:N ratio. Experimental set–up: salinity (SA)—Light (L) (High Light (HL)–Low Light (LL)) treatments. Values are means ± SD (n = 3). Statistically significant differences between HL and LL per treatments are marked by different lowercase letters. Statistically significant differences between treatment days (1–21) are marked by different uppercase letters and differences between salinities (SA 34, 28, and 18) are marked by different uppercase letters outside the graph. For all the data, three-way ANOVA with post-hoc Tukey’s test was performed (p < 0.05).
Figure 2. Elemental composition of Desmarestia aculeata at days 1 and 21 of treatment. (a) Contents of total N (% DW); (b) Contents of total C (% DW); (c) C:N ratio. Experimental set–up: salinity (SA)—Light (L) (High Light (HL)–Low Light (LL)) treatments. Values are means ± SD (n = 3). Statistically significant differences between HL and LL per treatments are marked by different lowercase letters. Statistically significant differences between treatment days (1–21) are marked by different uppercase letters and differences between salinities (SA 34, 28, and 18) are marked by different uppercase letters outside the graph. For all the data, three-way ANOVA with post-hoc Tukey’s test was performed (p < 0.05).
Biology 11 01499 g002
Table
Table 1. Photosynthetic parameters of Desmarestia aculeata: rETRmax, α, Ek, and Fv/Fm. Experimental set-up: salinity (SA)–Light (L) (High Light (HL)–Low Light (LL)) treatments. Values are means ± SD (n = 3). For each parameter (L, Days, SA), statistically significant differences are marked by different lowercase letters. For all the data, three-way ANOVA with post-hoc Tukey’s test was performed (p < 0.05).
Table 1. Photosynthetic parameters of Desmarestia aculeata: rETRmax, α, Ek, and Fv/Fm. Experimental set-up: salinity (SA)–Light (L) (High Light (HL)–Low Light (LL)) treatments. Values are means ± SD (n = 3). For each parameter (L, Days, SA), statistically significant differences are marked by different lowercase letters. For all the data, three-way ANOVA with post-hoc Tukey’s test was performed (p < 0.05).
SADaysLrETRmaxSignificanceαSignificanceEkSignificanceFv/FmSignificance
(rel. Units)LDaysSA(µmol Photons m−2s−1)−1LDaysSA(µmol Photons m−2s−1)LDaysSA(rel. Units)LDaysSA
341HL31.360 (±2.05)aaab0.202 (±0.01)aaa156.473 (±22.28)aaa0.618 (±0.01)aaa
LL20.183 (±2.78)b 0.213 (±0.01)a 94.597 (±8.38)b 0.427 (±0.10)b
21HL13.130 (±1.77)ab 0.193 (±0.02)aa 69.221 (±17.52)ab 0.399 (±0.10)aa
LL12.893 (±1.25)a 0.229 (±0.02)a 56.430 (±6.35)a 0.532 (±0.02)a
281HL18.557 (±3.12)aaa0.235 (±0.03)aaa79.370 (±12.64)aab0.613 (±0.06)aaa
LL20.656 (±2.12)a 0.256 (±0.02)a 80.903 (±7.68)a 0.590 (±0.06)a
21HL13.046 (±0.52)ab 0.202 (±0.02)ab 64.996 (±7.43)aa 0.511 (±0.03)aa
LL14.239 (±2.14)a 0.187 (±0.02)a 76.627 (±14.93)a 0.394 (±0.04)b
181HL22.529 (±3.42)aab0.233 (±0.02)aaa97.819 (±22.09)aaa0.498 (±0.11)aaa
LL21.794 (±5.33)a 0.201 (±0.04)a 110.722 (±29.33)a 0.359 (±0.05)a
21HL20.863 (±4.95)aa 0.173 (±0.02)ab 120.807 (±24.36)aa 0.512 (±0.03)aa
LL16.210 (±3.97)a 0.178 (±0.02)a 90.114 (±13.74)a 0.532 (±0.03)a
Table
Table 2. Concentration of main pigments [µg g−1 dry weight (DW)] of Desmarestia aculeata: Chl a, Chl c2, β-Car, Fucox. Experimental set-up: salinity (SA)–Light (L) (High Light (HL)–Low Light (LL)) treatments. Values are means ± SD (n = 3). For each parameter (L, Days, SA), statistically significant differences are marked by different lowercase letters. For all the data, three-way ANOVA with post-hoc Tukey’s test was performed (p < 0.05).
Table 2. Concentration of main pigments [µg g−1 dry weight (DW)] of Desmarestia aculeata: Chl a, Chl c2, β-Car, Fucox. Experimental set-up: salinity (SA)–Light (L) (High Light (HL)–Low Light (LL)) treatments. Values are means ± SD (n = 3). For each parameter (L, Days, SA), statistically significant differences are marked by different lowercase letters. For all the data, three-way ANOVA with post-hoc Tukey’s test was performed (p < 0.05).
SADaysLChl aSignificanceChl c2Significanceβ-CarSignificanceFucoxSignificance
(µg g−1 DW)LDaysSA(µg g−1 DW)LDaysSA(µg g−1 DW)LDaysSA(µg g−1 DW)LLDaysSA
341HL478.73 (±61.74)aaa60.60 (±15.42)aaab21.03 (±4.32)aaa178.83 (±6.48)aaa
LL450.60 (±44.34)a 51.07 (±5.52)a 17.07 (±3.76)a 192.60 (±6.24)a
21HL447.53 (±51.20)aa 58.10 (±9.40)aa 18.10 (±2.07)aa 203.63 (±27.75)aa
LL328.70 (±41.66)a 87.73 (± 3.25)a 12.03 (±1.68)a 140.93 (±28.62)a
281HL526.90 (±144.48)aaa85.60 (±11.82)aaa19.57 (±5.86)aaa177.47 (±9.46)aaa
LL536.83 (±192.22)a 62.53 (±4.83)a 21.10 (±7.95)a 144.10 (±1.73)a
21HL394.53 (±74.28)aa 53.87(±14.77)aa 11.37 (±2.94)ab 183.17 (±43.07)aa
LL391.57 (±33.67)a 70.63 (±3.40)a 11.07 (±0.67)a 163.97 (±13.98)a
181HL454.47 (±111.25)aaa68.80 (±2.51)aab16.03 (±1.44)aaa167.43 (±6.82)aaa
LL405.10 (±12.87)a 48.37 (±2.32)b 15.17 (±1.22)a 165.27 (±2.25)a
21HL334.97 (±43.70)aa 39.37 (±5.89)aa 15.10 (±0.50)aa 140.03 (±20.06)aa
LL472.90 (±33.20)a 76.77 (±6.62)b 11.00 (±3.80)a 228.37 (±15.87)b
Table
Table 3. The pool of the xanthophyll cycle—VAZ (µg g−1 dry weight (DW)) and de-epoxidation state (DPS). Experimental set–up: salinity (SA)–Light (L) (High Light (HL)–Low Light (LL)) treatments of Desmarestia aculeata. Values are means ± SD (n = 3). For each parameter (L, Days, SA), statistically significant differences are marked by different lowercase letters. For all the data, three-way ANOVA with post-hoc Tukey’s test was performed (p < 0.05).
Table 3. The pool of the xanthophyll cycle—VAZ (µg g−1 dry weight (DW)) and de-epoxidation state (DPS). Experimental set–up: salinity (SA)–Light (L) (High Light (HL)–Low Light (LL)) treatments of Desmarestia aculeata. Values are means ± SD (n = 3). For each parameter (L, Days, SA), statistically significant differences are marked by different lowercase letters. For all the data, three-way ANOVA with post-hoc Tukey’s test was performed (p < 0.05).
SADaysLVAZSignificanceDPSSignificance
(µg g−1 DW)LDaysSA LDaysSA
341HL0.35 (±0.03)aaa1.58 (±0.12)aaa
LL0.27 (±0.04)a 1.95 (±0.28)a
21HL0.26 (±0.02)ab 2.16 (±0.07)ab
LL0.21 (±0.03)a 2.70 (±0.32)a
281HL0.40 (±0.06)aaa1.48 (±0.26)aaa
LL0.29 (±0.08)b 2.01 (±0.66)a
21HL0.23 (±0.04)ab 2.44 (±0.37)ab
LL0.19 (±0.04)a 2.82 (±0.41)a
181HL0.29 (±0.02)aaa1.83 (±0.15)aaa
LL0.24 (±0.02)b 2.26 (±0.17)a
21HL0.22 (±0.03)aa 2.52 (±0.31)aa
LL0.26 (±0.01)a 2.17 (±0.13)a
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Marambio, J.; Diehl, N.; Bischof, K. High Ecophysiological Plasticity of Desmarestia aculeata (Phaeophyceae) Present in an Arctic Fjord under Varying Salinity and Irradiance Conditions. Biology 2022, 11, 1499. https://doi.org/10.3390/biology11101499

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Marambio J, Diehl N, Bischof K. High Ecophysiological Plasticity of Desmarestia aculeata (Phaeophyceae) Present in an Arctic Fjord under Varying Salinity and Irradiance Conditions. Biology. 2022; 11(10):1499. https://doi.org/10.3390/biology11101499

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Marambio, Johanna, Nora Diehl, and Kai Bischof. 2022. "High Ecophysiological Plasticity of Desmarestia aculeata (Phaeophyceae) Present in an Arctic Fjord under Varying Salinity and Irradiance Conditions" Biology 11, no. 10: 1499. https://doi.org/10.3390/biology11101499

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