Biochemistry of Arctic kelp specimens is conditioned by the local environment

Biochemistry of Arctic kelp specimens is conditioned by the local environment Sarina Niedzwiedz a,* , Clara Voigt a , Sebastian Andersen b , Nora Diehl a , Rapha¨ elle Descˆ oteaux b , Børge Damsgård b , Kai Bischof a a Marine Botany, Faculty of Biology & Chemistry and MARUM, University of Bremen, 28359, Bremen, Germany b Arctic Biology Department, The University Centre in Svalbard (UNIS), Longyearbyen, NO-9171, Norway ARTICLE INFO Keywords: Phenotypic plasticity Saccharina latissima Svalbard Tolerance ABSTRACT Climate change causes temperature and light to change drastically in Arctic fjords, being the main drivers for ecosystem-engineering seaweeds (kelps; Laminariales, Phaeophyceae). Climate projections on kelps are often based on static performance curves, treating species as one homogenous unit with similar tolerances within their entire biogeographical range. This might lead to mis-extrapolations. We assessed how Arctic kelp specimens are conditioned by their specific in-situ environment. Therefore, we sampled Saccharina latissima sporophytes from eight fjords along the west coast of Svalbard, Norway. Analysing their biochemical response variables (pigment content and composition; antioxidative activity; total carbon and nitrogen content), we found a distinct clustering of the biochemical composition of S. latissima, which correlated significantly with their environment. S. latissima responded strongly to changes in run-off induced turbidity, i.e., light availability. High light availability correlated with a significant reduction of photosynthetic pigments indicating high light protection. Nevertheless, the kelps’ total carbon content increased. The kelps’ total nitrogen content increased with increasing turbidity, which might be a response to nutrients being washed into the fjord by run-off. We found no stress response to suboptimal temperatures (3 ◦C vs. 7 ◦C). This is a further indication of the importance of light as a driver for high-latitude kelp populations, and the necessity to include it in climate projections. In conclusion, we found a high site-specific plasticity of Arctic S. latissima sporophytes. This has to be considered when projecting the responses of kelps towards climatic changes and local management activities. 1. Introduction Canopy-forming seaweeds of the order Laminariales, kelps, dominate temperate and Arctic rocky coastlines (Steneck et al., 2002; Wernberg et al., 2019). Kelp forests have been classified to be among the most productive ecosystems (Pessarrodona et al., 2022), acting as ecosystem engineers and foundation species, and thus providing habitat, nursery ground and food for many associated organisms (Eckman et al., 1989; Filbee-Dexter et al., 2019; Wernberg et al., 2019, 2024). Being sedentary, kelps cannot actively escape stressors and are susceptible to environmental changes. Within their genetically set tolerance limits, they have developed various physiological and biochemical mechanisms to respond to the sum of environmental changes, i.e., acclimatisation (Collier et al., 2019). Thereby, they maintain a high performance, e.g., growth and reproduction (phenotypic plasticity; King et al., 2017; Diehl et al., 2024). Energy requirements are lowest at a species optimum, increasing towards their tolerance limits, resulting in a reduced performance (Wahl et al., 2020). A modification of the tolerance limits of species occurs over generations, by natural selection of favourable, heritable traits, i.e., adaptation (King et al., 2017; Collier et al., 2019). The main driver for kelps’ latitudinal distribution is temperature, while light has been described to define their vertical distribution over depth (Fragkopoulou et al., 2022). Both temperature and light, are changing drastically in Arctic fjords with global climate change (Gattuso et al., 2020; Previdi et al., 2020, 2021; England et al., 2021; Konik et al., 2021). Vranken et al. (2021) have shown that the rate of change occurs too fast for adaptive responses in some kelp populations. Given their key ecological role, the acclimatisation of kelps in future Arctic conditions has been subject to many recent studies. Increased water temperatures are predicted to result in an expansion of temperate kelp population to higher latitudes (e.g., Filbee-Dexter et al., 2019; Assis et al., 2022), while run-off induced deterioration of the underwater light climate has been * Corresponding author. E-mail address: [email protected] (S. Niedzwiedz). Contents lists available at ScienceDirect Marine Environmental Research journal homepage: www.elsevier.com/locate/marenvrev https://doi.org/10.1016/j.marenvres.2025.107604 Received 23 May 2025; Received in revised form 3 October 2025; Accepted 3 October 2025 Marine Environmental Research 212 (2025) 107604 Available online 9 October 2025 0141-1136/© 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ). shown to result in a shoaling of the kelp forest (e.g., Bartsch et al., 2016; Niedzwiedz and Bischof, 2023; Düsedau et al., 2024). Studies projecting climate change developments are often based on tolerances from a single population and/or single-case experiment (Reed et al., 2011; Diehl et al., 2024). By this approach, it is assumed that populations along the entire biogeographical range react as one physiological and biochemical unit (King et al., 2017). However, Bennett et al. (2019) reviewed that susceptibilities towards abiotic stressors do not only vary between but also within one species, depending on a population’s geographic location and environmental history, which is supported by several studies. For example, Olischl¨ ager et al. (2014) found distinct differences in the response of S. latissima populations from Helgoland and Svalbard towards the same treatments. Liesner et al. (2020) highlighted the importance of cold seasons for the plasticity towards warming of Laminaria digitata. Gauci et al. (2022) found that the performance of L. digitata sporophytes increased if their gametophytes were cold-primed. Assessing the effects of marine heatwaves on north Atlantic kelp populations, Filbee-Dexter et al. (2020) concluded that local temperature thresholds have to be considered in predictions of marine heatwave consequences. Niedzwiedz et al. (2022) showed that the susceptibility of the kelp Saccharina latissima towards experimental heatwaves strongly depends on the field conditions they experienced before the experiment. As cold-edge populations in general showed large within-species variation (Bennett et al., 2019), the upscaling of the responses of one, often temperate, population for the entire Arctic might pose some risk for mis-extrapolation due to local acclimatisation and adaptation processes. Saccharina latissima is a widely distributed, cold-temperate kelp species, occurring from northern Portugal to Svalbard (Araújo et al., 2016), with its temperature optimum being described between 10 and 15 ◦C (Bolton and Lüning, 1982). Given its essential ecological and economic role, it is well-studied, serving as model species (Diehl et al., 2024; Sæther et al., 2024). In this study, we aim to characterise the intraspecific biochemical variation of Arctic S. latissima, to answer the question whether it can be regarded as one unit. We targeted this question with an in-situ approach in fjords along western Svalbard, Norway. We mapped the abiotic drivers for kelps (temperature, light availability; Fragkopoulou et al., 2022) and sampled S. latissima individuals in eight fjords, analysing the following biochemical responses. The kelp pigment content (chlorophyll a) and composition (ratio of accessory pigments to chlorophyll a (Acc:Chla); de-epoxidation state of xanthophyll cycle pigments (DPS; Demmig-Adams and Adams, 1996) respond to light availability to meet cellular energy requirements (Blain and Shears, 2019). Further, we analysed the antioxidant activity, as antioxidants were reported to be a protective mechanism against all types of abiotic stressors (Bischof and Rautenberger, 2012; Sharma et al., 2012). The total carbon (C) and total nitrogen (N) contents, as well as their ratio (C:N) were analysed to draw conclusions about the content of storage compounds and nutritional status of kelps at different sampling stations (Atkinson and Smith, 1983). This study was guided by three hypotheses: 1) Low-light intensities from run-off result in an increased pigment content and a lower carbon content. 2) Cold-temperatures lead to an increased stress level (high DPS and antioxidant activity). 3) A high cellular N content will be associated to high run-off intensities washing nutrients into the fjord 2. Material and methods 2.1. Sampling The Arctic Archipelago of Svalbard is located between ~77 and 80◦N and characterised by strong environmental gradients. The main sampling campaign was conducted from 05 to August 16, 2022 by ship (MS Spitsbergen). Station 4 (Isfjorden) and 5 (Eckmanfjorden), were sampled at the end of August (27–August 31, 2022). Additional temperature data from July and August 2022 are part of a monitoring program of the University Centre in Svalbard (UNIS). Saccharina latissima was collected at eight sampling stations along the west coast of Spitsbergen (Fig. 1: 1 to 8; detailed map of different fjords with sampling locations: Fig. A1). At each sampling station, similarly sized sporophytes (n =5) were collected from 5 ±2 m water depth using a plant rake (Plant rake 19.000, acc. to Sigurd Olsen, KC Denmark, Silkeborg, Denmark). 2.2. Abiotic parameters CTD data. One CTD profile per station was run in open fjord water (except for station 4 and 5, where CTD and kelp sampling stations were the same). Water parameters (temperature [◦C], salinity [S A ], turbidity [NTU]) of the water column were measured using an RBR Maestro 3 (RBR Ltd., Ottawa, Canada). The downcast profile was used to monitor an undisturbed turbidity profile. The CTD was lowered at a speed of approx. 1 m s −1 . Data were smoothed by the mean for every meter interval. Values were reported as mean ±SD of the upper 15 m of the water column. Further CTD profiles from cruises in 2022 before the sampling period were evaluated to demonstrate prevailing in-situ temperature patterns in the respective fjords. Light data. The spectrally down-welling irradiance (λ 400–700 nm) was measured with a RAMSES-ACC-UV/VIS radiometer (TriOS Optical Sensor, Oldenburg, Germany; alternative calibration) above the kelp forest in water depths from the surface until the bottom was reached (max 10 m; 2 to 3 profiles per station). The irradiance of each wavelength (I λ ) was measured in mW m −2 nm −1 and converted to μ mol photons m −2 s −1 after Niedzwiedz and Bischof (2023). By integrating I λ from 400 to 700 nm, the photosynthetically active radiation (PAR) was calculated (Niedzwiedz and Bischof, 2023). The light attenuation coefficient (K d ; m −1 ) was calculated between the surface and 3 m water depth after Hanelt et al. (2001). The spectrum peak (nm) at 3 m water depth was defined as the wavelength with the maximum irradiance transmission through the water column. 2.3. Kelp biochemistry After the samples were taken they were transported dark, wet and cool to the laboratory for further processing. For all biochemical measurements, subsamples were taken from each sporophyte by cutting discs for pigment analyses, 2 cm 2 in diameter, from the meristem (approx. basal 5 cm of the blade), within 2 h of sampling. All samples were dried in silica gel, which was replaced regularly. Samples were stored dry, cool and dark until biochemical analyses. Biochemical measurements are based on dry weight (DW). Pigment analyses. The kelp pigment composition reacts to cellular energy requirements and responds to light availability (Blain and Shears, 2019). Pigment concentrations were determined following Koch et al. (2015). Per specimen, two aliquots of 30–100 mg powdered material (n =3–5) were extracted in 1 mL 90 % acetone at 4 ◦C for 24 h in darkness. The supernatant was filtered and analysed by a High-Performance Liquid Chromatography (HPLC; LaChromElite® system, L-2200 autosampler (chilled), DA-detector L-2450; VWR-Hitachi International GmbH, Darmstadt, Germany). After Wright et al. (1991), the pigments were separated in a Spherisorb® ODS-2 column (250 ×4.6 mm, 5 μ m; Waters, Milford, MA, USA). Pigment peaks were identified and quantified using respective standards. Pigment concentrations were calculated as μ g g DW −1 . Accessory pigment content (Acc) was calculated as the sum of chlorophyll c, fucoxanthin and β-carotene. The ratio of accessory pigments to chlorophyll a (Acc:Chla) was calculated. The pool of xanthophyll cycle pigments (VAZ; μ g g DW −1 ) and its ratio to chlorophyll a was calculated (VAZ:Chla). The de-epoxidation state of xanthophyll cycle pigments (DPS; Demmig-Adams and Adams, 1996) was determined after Colombo-Pallotta et al. (2006). Antioxidative activity. Bischof and Rautenberger (2012) reported antioxidants to be a protective mechanism against all types of abiotic stressors. Following the ABTS ⋅+ (2, S. Niedzwiedz et al. Marine Environmental Research 212 (2025) 107604 2 2 ′ -azino-bis-3-ethylbenzthiazoline-6-sulphonic acid, 7 mM in biDest H2O) assay (Re et al., 1999), the kelps’ antioxidative activity (AOA) was determined. One aliquot of 50 mg powdered material (n =3–5), was dark-extracted in 1 mL 70 % ethanol for 4 h at 47 ◦C. 10 μ L of the supernatant were mixed with 1 mL ABTS ⋅+ -working-standard (absorption range: 0.740 ±0.01; 734 nm). After an incubation of 6 min, the absorption (λ 734 nm) was measured. AOA is reported as Trolox-equivalents (TE) by calibrating the ABTS ⋅+ -working-solution with a Trolox dilution series (6-hydroxy-2,5,7,8-tetramethychroman-2-carboxylic acid; 2.5 mM in 70 % v/v ethanol). Carbon and nitrogen content. The total carbon (C) and total nitrogen (N) contents, as well as their ratio (C:N) were analysed to draw conclusions about the nutritional status of kelp at different sampling stations (Atkinson and Smith, 1983). C and N contents were analysed using powdered material (2–3 mg; n =3–5). Samples were weighed into tin cartridges (5 ×9 mm) and combusted at 1000 ◦C. Acetanilide was used as standard (Verardo et al., 1990). An elemental analyser (Euro EA 3000 Elemental Analyser, EuroVector S.P.A., Milano, Italy) quantified the absolute C and N content automatically. Total C and N contents were expressed in mg g DW −1 and as ratio. 2.4. Statistical analyses As abiotic measurements were not independent from each other (measurements over depth of one profile) and often the limited number of replicates did not allow a statistical evaluation, we showed the mean and standard deviation over depth. In the biochemical data, outliers were removed from the dataset if they were classified as extreme (function: identify_outliers; package: rstatix; Kassambara, 2023). A linear model was fit on each response parameter (function: lm; package: stats; R Core Team (2023) with sampling station as single-fixed effect to detect significant variations in kelp biochemistry. The model’s residuals were tested for normality (Shapiro-Wilk test, p >0.05) and homoscedasticity (Levene’s test, p > 0.05). As prerequisites were met, analysis of variance was tested on the model (function: anova; package: stats; R Core Team (2023). Pairwise performance (function: emmeans; package: emmeans; Lenth (2024) was used to calculate the degrees of freedom, with Tukey’s adjustment of the p-value. Pearson correlations were analysed (function: cor.test; package: stats; R Core Team (2023). A correlogram was plotted to allow conclusions to be drawn on the relationship between kelp biochemistry and abiotic variations (function: ggcorr; package: GGally; Schloerke et al., 2023). Data were evaluated, plotted and analysed in R (RStudio; V 2023.12.1 using R-4.3.2-win; R Core Team, 2023), within “tidyverse” (Wickham et al., 2019). Maps were created with ggOceanMaps (Vihtakari, 2024). 3. Results 3.1. Abiotic parameters Water column measurements revealed a distinct gradient of all parameters (Fig. 2A). Stations 1 and 2 (south of Svalbard) were characterised by cold temperatures (3.7 ±0.7 ◦C) and highest turbidity values (2.8 ±2.0 NTU). At stations 3, 4 and 5 (mid of Svalbard) temperatures of 5.5 ±0.9 ◦C, and turbidity values 1.8 ±0.7 NTU were measured. Stations 6 and 7 in the north of the Archipelago were characterised by highest temperatures (6.6 ±0.3 ◦C) and lowest turbidity values (0.4 ± 0.1 NTU). Mean salinity values across all stations ranged between S A 32.0 and 33.8. Analysis of in-situ temperature data from July and August 2022 (Fig. 2B) confirmed the overall pattern between the fjords during the time of sampling: Mean PAR intensities per sampling station at 3 m water depth ranged between 2.3 and 137 μ mol photons m −2 s −1 (Fig. 2C). Highest K d values were measured at station 2 (south; K d =1.8 ±0.4 m -1 ) and 5 (mid; K d = 1.0 ±0.1 m -1 ). Stations 6, 7, and 8 (north) clustered very closely, being characterised by lowest K d values (0.2 ±0.1 m -1 ). Spectrum peaks ranged between λ 510 and 580 nm, being highest at sampling station 2 (λ 577 ±3.7 nm) and 5 (λ 582 ±1.2 nm). Complete CTD (temperature, salinity, turbidity) profiles over depth and the spectral resolution of PAR for each depth are provided as supplementary material (Figure A2, Figure A3). 3.2. Kelp biochemistry All statistical results are summarised in Table 1 and are not given in the text for overview reasons. Pigments. The pigment composition differed significantly between stations (Fig. 3A). Chlorophyll a ( μ g g DW −1 ) concentration of samples from Fig. 1. Sampling stations (1–8) of Saccharina latissima along the west coast of Svalbard. Mean seasurface temperature (SST) data (colour gradient) were downloaded from the NOAA database (https://coastwatch.pfeg.noaa.gov/erddap/, downloaded: May 08, 2024; Chamberlain, 2024), integrating the SST in 2022 until sampling (01/01/to August 16, 2022). Maps were created with ggOceanMaps (Vihtakari, 2024). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.) S. Niedzwiedz et al. Marine Environmental Research 212 (2025) 107604 3 station 2 (south) was 50–87 % higher than in other fjords. Acc ( μ g g DW −1 ) and VAZ ( μ g g DW −1 ) showed similar patterns (Fig. A4). The Acc:Chla showed an increasing trend with higher latitude, being significantly lower at stations 1 and 2 (south) compared to stations 6 and 7 (north). While only the de-epoxidation state of xanthophyll cycle pigments (DPS) of station 1 (south) was significantly lower compared to station 6, an overall increase of DPS values with higher latitude was observed. Antioxidative activity. AOA (TE mM 100 mg DW −1 ; Fig. 3B) was significantly affected by sampling stations; however, no latitudinal trend was found for the significant differences. Carbon and nitrogen content. The C and N content, as well as C:N were significantly affected by station (Fig. 3C). Mean C content ranged between 280 and 345 mg g DW −1 and increased with higher latitudes, with the C content of station 1, 2 (south) being significantly lower compared to station 7 (north). Mean N (7.1 and 20.1 mg g DW −1 ) showed a decreasing trend with higher latitude, although station 7 (north) had the overall highest N content. Mean C:N (15.9 and 47.4) of station 6 was significantly higher, compared to the other stations (except station 4). 3.3. Correlations Correlations between abiotic parameters and kelp responses are shown in Fig. 4. Overall, a latitudinal gradient of environmental parameters was observed: Temperature increased significantly with higher latitude; turbidity decreased (not-significantly) with higher latitude. Temperature correlated negatively with turbidity. High turbidity values correlated with high K d values. Kelp pigment concentrations (chlorophyll a, Acc, VAZ) correlated positively and pigment ratios (Acc:Chla, DPS) correlated negatively with turbidity, the spectrum peak and K d . DPS was found to correlate positively with temperature and latitude (significant) and negatively with turbidity (non-significant). The chlorophyll a concentration, Acc and VAZ correlated positively with each other. Although AOA correlated positively with PAR, this correlation was not significant. The total C correlated positively with temperature and latitude; and negatively with turbidity and K d (significant). Regarding total N these correlations were reversed, though they were not significant. 4. Discussion The kelp Saccharina latissima is well-studied, being a key species in kelp forests along North Atlantic coasts (Araújo et al., 2016; Diehl et al., Fig. 2. Abiotic parameters along the Svalbard latitudinal gradient. Stations: 1 – Gnålodden, Hornsund. 2 – Burgerbukta, Hornsund. 3 – Lyshamna, Bellsund. 4 – Bjørndalen, Isfjorden. 5 – V` orneset, Ekmanfjorden. 6 – Worsleyhamna, Woodfjorden. 7 – Alicehamna, Raudfjorden. 8 – Ytre Norskøya. A) CTD data. Temperature (◦C), Turbidity (NTU) of the upper 15 m of the water column (mean ±SD over depth; n (profiles per station) =1). Note: Station 8 is missing in the CTD profiles. B) Temperature (◦C) of the upper 15 m of the water column in July and August 2022 (mean ±SD; n (profiles per station) =1–3). Note that stations from subplot A) are included in the August mean. C) PAR: Photosynthetically Active Radiation ( μ mol photons m −2 s −1 ) at the surface (triangle; 0 m) and on 3 m depth. K d (m −1 ): light attenuation coefficient between the water’s surface and 3 m depth (mean ±SD; n =1–3). Spectrum peak at 3 m water depth: wavelength (nm) with the highest irradiance (mean ±SD; n =1–3). Table 1 Statistics of biochemical parameters of kelps. Results of Analysis of Variance (ANOVA) to evaluate the effect of station as single fixed effect. Significant results (p <0.05) are marked in bold. Acc:Chla: ratio of accessory pigments to chlorophyll a. DPS: De-epoxidation state of xanthophyll cycle pigments. AOA: antioxidative activity. Total C: total carbon content. Total N: total nitrogen content. C:N: carbon to nitrogen ratio. Parameter numDF denDF F value p value Chlorophyll a7 30 9.5 <0.001 Acc:Chla7 30 7.54 <0.001 DPS 7 27 2.9 0.02 AOA 7 26 4.8 0.001 Total C 7 31 4.5 0.001 Total N 7 28 15.9 <0.001 C:N 7 28 12.5 <0.001 Note: numDF: numerator degrees of freedom. denDF: denominator degrees of freedom. S. Niedzwiedz et al. Marine Environmental Research 212 (2025) 107604 4 2024), and is expected to expand poleward with ongoing climate change (Filbee-Dexter et al., 2019; Assis et al., 2022). Modelling studies are often based on responses from single populations or single-case experiments (Reed et al., 2011; Diehl et al., 2024). Thereby, the intraspecific variation is being neglected. In this study, we aim to analyse the intraspecific biochemical variation of Arctic S. latissima. Confirming hypothesis 1, we found that low-light intensities in southern Svalbard fjords correlated with a higher content of photosynthetic pigments and a lower carbon content. Contradicting hypothesis 2, we found higher DPS values (indicating physiological stress) with warmer temperatures. We attribute this to the high-light availability, which increased along the same gradient as rising temperatures. Regarding hypothesis 3, we found a spatial variation in the kelps N content, which was higher when kelps were influenced by local run-off (station 2; south) or coastal upwelling (station 7; north). These significant variations in the biochemical composition of kelps from different fjords are likely to result in different responses to environmental changes as are expected with ongoing climate change. Hence, treating kelps as one homogenous unit in climate projections might lead to mis-extrapolations, as they might be more or less tolerant locally than expected. 4.1. Biochemical composition responds strongly to the local environment We assessed the biochemical variation of S. latissima along the west coast of Svalbard. To be able to discuss these variations in an environmental context, we monitored temperature and light availability, as they have been described to be the most important drivers for kelp distribution (Fragkopoulou et al., 2022). We found spatial differences for both drivers (Figs. 1 and 2). Fjord temperature patterns are influenced by currents (Cottier et al., 2010). Southern fjords in Svalbard (especially Hornsund; station 1, 2) are characterised by cold temperatures, being influenced by the Sørkapp Current carrying Arctic water masses (Konik et al., 2021). With higher latitude, we measured warmer temperatures, as the influence of the West Spitsbergen Current increased, carrying warm Atlantic water masses (Svendsen et al., 2002). All measured temperatures during the sampling, ranged from 3 to 7◦C, which is well below the described growth optimum for S. latissima of 10–15 ◦C (Bolton and Lüning, 1982). Several experimental studies assessed how S. latissima responds to temperatures below their optimum: Monteiro et al. (2021) found an increasing trend of chlorophyll a and a significant decrease of the DPS from 0 to 15 ◦C in young S. latissima of a temperate population (Roscoff, Brittany). Testing the same temperature range on young sporophytes from a Svalbard population, Li et al. (2020) also found decreasing DPS values with warmer temperature. As the DPS is part of the kelps’ intercellular stress response (Gross and Jakob, 2010), these results indicate cold temperatures inflict more physiological stress than temperatures closer to the optimum. We would have expected a similar response in Hornsund (station 1, 2). However, we found a contrary response where temperature correlated positively with DPS values. It has to be noted that both Monteiro et al. (2021) and Li et al. (2020) worked with young sporophytes from stock cultures, while we worked on adult sporophytes. Even though sporophytes of different ages can show different response patterns to stressors (Martins et al., 2017), we do not assume that these different responses were due to age differences or altered thermal tolerances of Arctic populations. Interpreting the biochemical composition of populations in this study, it has to be considered that warmer temperatures correlated with less run-off and a clearer water column (i.e., lower turbidity, K d ; Figs. 2 and 4). Hence, we assume that high DPS values did not predominantly respond to changes in temperature but rather counteracted high-light stress (note that the Fig. 3. Kelp biochemistry along the Svalbard latitudinal gradient (mean ±SD; n =3–5). Stations: 1 – Gnålodden, Hornsund. 2 – Burgerbukta, Hornsund. 3 – Lyshamna, Bellsund. 4 – Bjørndalen, Isfjorden. 5 – V` orneset, Ekmanfjorden. 6 – Worsleyhamna, Woodfjorden. 7 – Alicehamna, Raudfjorden. 8 – Ytre Norskøya. Different letters indicate significant (p <0.05) differences between stations. Some error bars are within the diameter of the symbol. A) Chl a: chlorophyll a concentration ( μ g g DW −1 ). Acc:Chla: ratio of accessory pigments to chlorophyll a. DPS: de-epoxidation state of xanthophyll cycle pigments. В) AOA: Antioxidative activity (TE mM 100 mg DW −1 ). C) C: total carbon content (mg g DW −1 ). N: total nitrogen content (mg g DW −1 ). C:N: carbon to nitrogen ratio. S. Niedzwiedz et al. Marine Environmental Research 212 (2025) 107604 5 correlation is not significant; Fig. 4). High light availability might saturate the photosynthetic electron transport chain and deplete reductive equivalents (Bischof and Rautenberger, 2012). Excessive electrons contribute to form reactive oxygen species (ROS), which can destroy critical macromolecules (Sharma et al., 2012). DPS functions as protective mechanism to dissipate excessive energy (Demmig-Adams and Adams, 1996), thereby reducing the potential of ROS formation. Kelps being exposed to higher light availability were further characterised by a significantly lower chlorophyll a content, mitigating high-light stress as less electrons enter the electron transport chain (Kirk, 2011). The ratio of Acc:Chla further confirmed this response pattern. Acc:Chla correlated negatively with the spectrum peak, indicating that the pigment composition did not respond to run-off-induced spectrum shifts (Fig. 2, A3) in order to close the green gap of chlorophyll a (Stomp et al., 2007). As we found Acc:Chla to increase with higher light availability (Figs. 3 and 4), the reduction of the light harvesting antenna complex at photosynthetic reaction centres further prevented electrons being transmitted into the electron transport chain (Falkowski and Raven, 2007). It has to be noted that we measured a maximum absolute PAR value of ~140 μ mol photon m −2 s −1 at 3 m water depth (Fig. 2C), which is well below PAR values that kelps experience in other regions, e. g., in the German Bight (400–500 μ mol photons m −2 s −1 , Stahl et al., 2024). It also has to be considered that point measurements of absolute PAR values are subject to transient weather conditions (pers. obs.), such as clear sky (station 4) vs. cloud cover (stations 6, 7, 8). Niedzwiedz et al. (2024) argued that light stress at relatively low light intensities is caused by long photoperiod and the lack of a recovery phase. Our in-situ study supports their experimental findings. This line of argument also further adds to the findings of Diehl et al. (2021). They described overall low DPS values and exceptionally high growth rates as a response to experimental temperatures between 0 and 6 ◦C (including in-situ conditions). To be able to compare experiments across latitudes, they exposed the Svalbard samples to a 16:8 h L:D cycle. We hypothesise that the overall, temperature-independent increase in performance Diehl et al. (2021) found in kelps from the Arctic is due to a more optimal light regime and a recovery from high-light stress. These findings are a further indication of the importance of light, shaping the performance and latitudinal distribution of high-latitude kelps (Diehl et al., 2024a). We did not detect the same stress response in AOA as for DPS. We suggest that high-light stress was already effectively mitigated by changes in the pigment composition of the photosystem, preventing overall higher cellular stress response. As the AOA was significantly influenced by the sampling stations (Table 1), we assume that parameters not quantified in this study might have triggered it. We found a clear trend of increasing total C content with higher latitudes, which is correlating significantly with warmer temperatures and higher light availability (lower turbidity; lower kd). A higher C content might indicate more storage compounds, e.g., mannitol and laminarin (Graiff et al., 2016). Scheschonk et al. (2019) showed that S. latissima’s storage compounds were depleted by 96 % after three months of Polar Night. A reduced carbon content at the end of the Arctic summer period might increase the likelihood of S. latissima having an overall negative carbon balance, i.e., might run into starvation during winter months. To be able to predict the actual kelp loss due to run-off-induced low-light intensities, the cumulative annual PAR availability would have to be monitored along fjord gradients. Castro de la Guardia et al. (2023) found that kelps need a minimum of 49 mol photons m −2 yr −1 to form a stable population. C:N ratios above 20 indicated that kelps from all sampling stations were N limited (Fig. 3; Atkinson and Smith, 1983). In summer, Arctic water masses are stratified by strong temperature and salinity gradients (Fig. A2), leading to the absence of vertical mixing and re-supply of deep-water nutrients (Cottier et al., 2010). The total N content showed a decreasing trend with higher latitude (Fig. 3). We attribute this to the higher run-off influence in southern Svalbard fjords (higher turbidity; Fig. 2), carrying nutrients from terrestrial sources (McGovern et al., 2020). Kelps from station 7 are an exception, being characterised by a high N content. At station 7, temperature gradients over depth were very weak (Fig. A2), showing almost no variation within the upper 15 m of the water column (Fig. 2, A2). As salinity and turbidity differences were likewise not very pronounced, we suggest that station 7 might have been influenced by local upwelling, leading to a local resupply of nutrients. As C:N ratios reflect food quality of kelps (Lowman et al., 2022), this difference might change the efficiency of energy transfer to higher trophic levels (Lowman et al., 2022) and the ecosystem’s nutrient cycling. 4.2. Saccharina latissima specimens are not one homogenous unit Bolton and Lüning (1982) described the temperature optimum for S. latissima between 10 and 15 ◦C. Following the resulting performance curve, this indicates an increasing stress level as temperatures deviate from the optimum. Interacting with high light, we found the opposite trend; stress levels increased with temperatures closer to the species optimum. Probably temperatures closer to the optimum might already have mitigated high-light stress, as was experimentally shown by Niedzwiedz et al. (2024) and Diehl et al. (2024a). Further, we found kelps in most fjords to be nitrogen limited. Nutrient limitation was shown to weaken kelps, making them more susceptible for other stressors, such as UV radiation (Davison et al., 2007). Our data suggest that the natural variation in present-day Arctic fjords leads to significant variations in the biochemical composition of kelps and consequently altered susceptibilities towards stressors. Comparing the biochemical composition of S. latissima across Europe, Diehl et al. (2023) found neither a clear latitudinal gradient nor a clustering of populations driven by abiotic conditions. In their study, Fig. 4. Linear dependency between kelp response parameters and abiotic conditions. Colour scale: Pearson correlation co-efficient (r). PAR: Photosynthetically Active Radiation. K d : light attenuation coefficient. Acc: accessory pigments. VAZ: pool of xanthophyll cycle pigments. Acc:Chla: ratio of accessory pigments to chlorophyll a. DPS: de-epoxidation state of xanthophyll cycle pigments. AOA: antioxidative activity. C: total carbon content. N: total nitrogen content. C:N: carbon to nitrogen ratio. Asterisks: significance of correlation (*: p <0.05; **: p <0.01; ***: p <0.001). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.) S. Niedzwiedz et al. Marine Environmental Research 212 (2025) 107604 6 they focussed on temperature and salinity as main drivers, not measuring light availability or light-dependent responses (e.g., pigments). Based on the results of our study, we hypothesise that the inclusion of light availability might have resulted in a more distinct clustering of sampling stations; especially the observed phlorotannin concentrations in the study of Diehl et al. (2023) indicated the significance of light on the biochemistry of kelps and population differences. 4.3. Methodological considerations Our study was carried out in August 2022 and consists of temporal and spatial point measurements of both abiotic and biotic samples. Hence, the values reported here do not reflect the seasonal development or conditions of parameters and are also not representative for the entire fjords, which are known to be characterised by strong environmental gradients (Meire et al., 2017; Sejr et al., 2024). However, satellite data of the fjord boundary conditions (Fig. 1) and additional temperature measurements of previous cruises (Fig. 2B), confirm the described temperature patterns during the kelp sampling. Additional data on the light availability were not available to us. We mainly focussed on temperature and light availability, as they were described to act as main drivers for the distribution of kelps (Fragkopoulou et al., 2022). Consistent with that, we found several significant correlations of the biochemical parameters with temperature and light availability (Fig. 4). In experimental studies in the laboratory, biochemical responses to environmental conditions in kelps were detected within a few days (e.g., Diehl et al., 2021; Niedzwiedz et al., 2024), which is why we consider it plausible that the biochemistry responded to environmental parameters. Long-term monitoring programs of abiotic conditions are necessary to be able to draw conclusions on temporal variations. While the absolute reported values in this study are a snapshot of the situation during the sampling, we showed that the intraspecific variability of S. latissima along the west coast of Svalbard is high and that the species cannot be regarded as one homogeneous unit. 4.4. Concluding remarks In this monitoring study, we compared S. latissima from eight Arctic fjords. Based on their variation in biochemical signatures they cannot be regarded as one homogenous unit in climate projections. We related the biochemical responses to differences in temperature and light availability of their local environment. Thereby, our study highlights the importance of considering light as a driver for the biogeographical distribution of kelps at their colddistribution edge. While the high biochemical variation we found indicates a high phenotypic plasticity of S. latissima, the significant correlations with abiotic environmental factors also suggests that the kelps are conditioned by their local environments (Fig. 4). Hence, responses from single location have to be extrapolated with care and local environmental conditions have to be considered. CRediT authorship contribution statement Sarina Niedzwiedz: Writing – review & editing, Writing – original draft, Visualization, Validation, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Clara Voigt: Writing – review & editing, Validation, Investigation, Formal analysis, Data curation. Sebastian Andersen: Writing – review & editing, Validation, Methodology, Investigation. Nora Diehl: Writing – review & editing, Validation, Conceptualization. Rapha¨ elle Descˆ oteaux: Writing – review & editing, Validation, Software, Investigation. Børge Damsgård: Writing – review & editing, Validation, Supervision, Resources, Funding acquisition. Kai Bischof: Writing – review & editing, Validation, Resources, Funding acquisition, Conceptualization. Financial Support The field work on Svalbard was granted under RiS number: 10890. This study was conducted in the frame of the project FACE-IT (The Future of Arctic Coastal Ecosystems – Identifying Transitions in Fjord Systems and Adjacent Coastal Areas) and SEA-Quester (Blue Carbon Production, Export and Sequestration in Emerging Polar Ecosystems). FACE-IT has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 869154. SEA-Quester has received funding from the European Union’s Horizon Europe research and innovation programme under Grant Agreement No. 101136480. Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union. Neither the European Union nor the grant authority can be held responsible for them. Declaration of competing interest The authors declare no conflict of interest. Acknowledgements The authors thank the University Centre in Svalbard (UNIS) and crew from MS Spitsbergen (HX Expeditions) for assistance during field work and for logistical, laboratory and administrative support. We thank Britta Iken and Andreas Suchopar for their support during biochemical analyses. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.marenvres.2025.107604. Data availability All primary data supporting this study are openly available: https://doi.pangaea.de/10.1594/PANGAEA.968466 https://doi.pangaea.de/10.1594/PANGAEA.968464 https://doi.pangaea.de/10.1594/PANGAEA.968642. As mean temperature data of July/August 2022 were included as meta-analysis in this study and are part of another study, they will be published along with it. Meanwhile contact Rapha¨ elle Descˆ oteaux ([email protected]) for more information. References Araújo, R.M., Assis, J., Aguillar, R., Airoldi, L., B´ arbara, I., Bartsch, I., Bekkby, T., Christie, H., Davoult, D., Derrien-Courtel, S., Fernandez, C., Fredriksen, S., Gevaert, F., Gundersen, H., Le Gal, A., L´ evˆ eque, L., Mieszkowska, N., Norderhaug, K. M., Oliveira, P., Ouente, A., Rico, J.M., Rinde, E., Schubert, H., Strain, E.M., Valero, M., Viard, F., Sousa-Pinto, I., 2016. Status, trends and drivers of kelp forests in Europe: an expert assessment. Biodivers. Conserv. 25, 1319–1348. https://doi. org/10.1007/s10531-016-1141-7. Assis, J., Serr˜ ao, E., Duarte, C.M., Fragkopoulou, E., Krause-Jensen, D., 2022. Major expansion of marine forests in a warmer Arctic. Front. Mar. Sci. 9, 850368. https:// doi.org/10.3389/fmars.2022.850368. Atkinson, M.J., Smith, S.V., 1983. C:N:P ratios of benthic marine plants. Limnol. Oceanogr. 28, 568–574. https://doi.org/10.4319/lo.1983.28.3.0568. Bartsch, I., Paar, M., Fredriksen, S., Schwanitz, M., Daniel, C., Hop, H., Wiencke, C., 2016. Changes in kelp forest biomass and depth distribution in Kongsfjorden, Svalbard, between 1996-1998 and 2012-2014 reflect Arctic warming. Polar Biol. 39, 2021–2036. https://doi.org/10.1007/s00300-015-1870-1. Bennett, S., Duarte, C.M., Marb` a, N., Wernberg, T., 2019. Integrating within-species variation in thermal physiology into climate change ecology. Philos. Trans. R. Soc. B 374, 20180550. https://doi.org/10.1098/rstb.2018.0550. Bischof, K., Rautenberger, R., 2012. Seaweed responses to environmental stress: reactive oxygen and antioxidant strategies. In: Wiencke, C., Bischof, K. (Eds.), Seaweed Biology. Springer Verlag, Berlin-Heidelberg, pp. 109–132. Blain, C.O., Shears, N.T., 2019. Seasonal and spatial variation in photosynthetic response of the kelp Ecklonia radiata across a turbidity gradient. Photosynth. Res. 140, 21–38. https://doi.org/10.1007/s11120-019-00636-7. S. Niedzwiedz et al. Marine Environmental Research 212 (2025) 107604 7 Bolton, J.J., Lüning, K., 1982. Optimal growth and maximal survival temperatures of Atlantic Laminaria species (Phaeophyta) in culture. Mar. Biol. 66, 89–94. https://doi. org/10.1007/BF00397259. Castro de la Guardia, L., Filbee-Dexter, K., Reimer, J., MacGregor, K.A., Garrido, I., Singh, R.K., B´ elanger, S., Konar, B., Iken, K., Johnson, L.E., Archambault, P., Sejr, M. K., Søreide, J.E., Mundy, C.J., 2023. Increasing depth distribution of Arctic kelp with increasing number of open water days with light. Elementa Sci. Anthropocene 11, 1. https://doi.org/10.1525/elementa.2022.00051. Chamberlain, S., 2024. rerddap: general purpose client for ’ERDDAP’ servers. R package version 1.1.0. https://CRAN.R-project.org/package=rerddap. Collier, R.J., Baumgard, L.H., Zimbelman, R.B., Xiao, Y., 2019. Heat stress: physiology of acclimation and adaptation. Feature Art. 9, 12–19. https://doi.org/10.1093/af/ vfy031. Colombo-Pallotta, M.F., García-Mendoza, E., Ladah, L.B., 2006. Photosynthetic performance, light absorption, and pigment composition of Macrocystis pyrifera (Laminariales, Phaeophyceae) blades from different depths. J. Phycol. 42, 1225–1234. https://doi.org/10.1111/j.1529-8817.2006.00287.x. Cottier, F.R., Nilsen, F., Skogseth, R., Tverberg, V., Skarđhamar, J., Svendsen, H., 2010. Arctic fjords: a review of the oceanographic environment and dominant physical processes. Geological Soc. London Special Publ. 344, 35–50. https://doi.org/ 10.1144/SP344.4. Davison, I.R., Jordan, T.L., Fegley, J.C., Grobe, C.W., 2007. Response of Laminaria saccharina (Phaeophyta) growth and photosynthesis to simultaneous ultraviolet radiation and nitrogen limitation. J. Phycol. 43, 636–646. https://doi.org/10.1111/ j.1529-8817.2007.00360.x. Demmig-Adams, B., Adams, W.W., 1996. Xanthophyll cycle and light stress in nature: uniform response to excess direct sunlight among higher plant species. Planta 198, 460–470. https://doi.org/10.1007/BF00620064. Diehl, N., Roleda, M.Y., Bartsch, I., Karsten, U., Bischof, K., 2021. Summer heatwave impacts on the European kelp Saccharina latissima across its latitudinal distribution gradient. Front. Mar. Sci. 8, 695821. https://doi.org/10.3389/fmars.2021.695821. Diehl, N., Steiner, N., Bischof, K., Karsten, U., Heesch, S., 2023. Exploring intraspecific variability – biochemical and morphological traits of the sugar kelp Saccharina latissima along latitudinal and salinity gradients in Europe. Front. Mar. Sci. 10, 995982. https://doi.org/10.3389/fmars.2023.995982. Diehl, N., Li, H., Scheschonk, L., Burgunter-Delamare, B., Niedzwiedz, S., Forbord, S., Sæther, M., Bischof, K., Monteiro, C., 2024. The sugar kelp Saccharina latissima I: recent advances in a changing climate. Ann. Bot. 133, 183–211. https://doi.org/ 10.1093/aob/mcad173. Diehl, N., Laeseke, P., Bartsch, I., Bligh, M., Buck-Wiese, H., Hehemann, J.-H., Niedzwiedz, S., Plag, N., Karsten, U., Shan, T., Bischof, K., 2024a. Photoperiod and temperature interaction drive the latitudinal distribution of Laminaria hyperborea (Laminarials, Phaeophyceae) under climate change. J. Phycol. 60, 1237–1255. https://doi.org/10.1111/jpy.13497. Düsedau, L., Fredriksen, S., Brand, M., Fischer, P., Karsten, U., Bischof, K., Savoie, A., Bartsch, I., 2024. Kelp forest community structure and demography in Kongsfjorden (Svalbard) across 25 years of Arctic warming. Ecol. Evol. 14, e11606. https://doi. org/10.1002/ece3.11606. Eckman, J.E., Duggins, D.O., Sewell, A.T., 1989. Ecology of understory kelp environments. I. Effects of kelps on flow and particles transport near the bottom. J. Exp. Mar. Biol. Ecol. 129, 173–187. https://doi.org/10.1016/0022-0981(89) 90055-5. England, M.R., Eisenman, I., Lutsko, N.J., Wagner, T.J.W., 2021. The recent emergence of Arctic amplification. Geophys. Res. Lett. 48, e2021GL094086. https://doi.org/ 10.1029/2021GL094086. Falkowski, P.G., Raven, J.A., 2007. Aquatic Photosynthesis, second ed. Princeton Univ. Press. Filbee-Dexter, K., Wernberg, T., Fredriksen, S., Norderhaug, K.M., Pedersen, M.F., 2019. Arctic kelp forests: diversity, resilience and future. Global Planet. Change 172, 1–14. https://doi.org/10.1016/j.gloplacha.2018.09.005. Filbee-Dexter, K., Wernberg, T., Grace, S.P., Thormar, J., Fredriksen, S., Narvaez, C.N., Feehan, C.J., Norderhaug, K.M., 2020. Marine heatwaves and the collapse of marginal North Atlantic kelp forests. Sci. Rep. 10, 13388. https://doi.org/10.1038/ s41598-020-70273-x. Fragkopoulou, E., Serr˜ ao, E., De Clerck, O., Costello, M.J., Araújo, M.B., Duarte, C.M., Krause-Jensen, D., Assis, J., 2022. Global biodiversity patterns of marine forests of brown macroalgae. Global Ecol. Biogeogr. 31. https://doi.org/10.1111/geb.13450, 363-348. Gattuso, J.-P., Gentili, B., Antoine, D., Doxaran, D., 2020. Global distribution of photosynthetically available radiation on the seafloor. Earth Syst. Sci. Data 12, 1697–1709. https://doi.org/10.5194/essd-12-1697-2020. Gauci, C., Bartsch, I., Martins, N., Liesner, D., 2022. Cold thermal priming of Laminaria digitata (Laminariales, Phaeophyceae) gametophytes enhances gametogenesis and thermal performance of sporophytes. Front. Mar. Sci. 9, 862923. https://doi.org/ 10.3389/fmars.2022.862923. Graiff, A., Ruth, W., Kragl, U., Karsten, U., 2016. Chemical characterization and quantification of the brown algal storage compound laminarin – a new methodological approach. J. Appl. Phycol. 28, 533–543. https://doi.org/10.1007/ s10811-015-0563-z. Gross, R., Jakob, T., 2010. Regulation and function of xanthophyll cycle-dependent photoprotection in algae. Photosynth. Res. 106, 103–122. https://doi.org/10.1007/ s11120-010-9536-x. Hanelt, D., Tüg, H., Bischof, K., Groß, C., Lippert, H., Sawall, T., Wiencke, C., 2001. Light regime in an Arctic fjord: a study related to stratospheric ozone depletion as a basis for determination of UV effects on algal growth. Mar. Biol. 138, 649–658. https:// doi.org/10.1007/s002270000481. Kassambara, A., 2023. rstatix: Pipe-friendly framework for basic statistical tests. R package version 0.7.2. https://CRAN.R-project.org/package=rstatix. King, N.G., McKeown, N.J., Smale, D.A., Moore, P.J., 2017. The importance of phenotypic plasticity and local adaptation in driving intraspecific variability in thermal niches of marine macrophytes. Ecography 41, 1469–1484. https://doi.org/ 10.1111/ecog.03186. Kirk, J.T.O., 2011. Light and Photosynthesis in Aquatic Systems, third ed. Cambridge Univ. Press. Koch, K., Thiel, M., Tellier, F., Hagen, W., Graeve, M., Tala, F., Laeseke, P., Bischof, K., 2015. Species separation within the Lessonia nigrescens complex (Phaeophyceae, Laminariales) is mirrored by ecophysiological traits. Bot. Mar. 58, 91–92. https:// doi.org/10.1515/bot-2014-0086. Konik, M., Darecki, M., Pavlov, A.K., Sagan, S., Kowalczuk, P., 2021. Darkening of the Svalbard fjords waters observed with satellite ocean color imagery in 1997–2019. Front. Mar. Sci. 8, 699318. https://doi.org/10.3389/fmars.2021.699318. Lenth, R., 2024. Emmeans: estimated marginal means, aka least-squares means. R package version 1.10.0. https://CRAN.R-project.org/package=emmeans. Li, H., Monteiro, C., Heinrich, S., Bartsch, I., Valentin, K., Harms, L., Gl¨ ockner, G., Corre, E., Bischof, K., 2020. Responses of the kelp Saccharina latissima (Phaeophyceae) to the warming Arctic: from physiology to transcriptomics. Physiol. Plantarum 168, 5–26. https://doi.org/10.1111/ppl.13009. Liesner, D., Sharma, L.N.S., Diehl, N., Valentin, K., Bartsch, I., 2020. Thermal plasticity of the kelp Laminaria digitata (Phaeophyceae) across life cycle stages reveals the importance of cold seasons for marine forests. Front. Mar. Sci. 7, 456. https://doi. org/10.3389/fmars.2020.00456. Lowman, H.E., Emery, K.A., Dugan, J.E., Miller, R.J., 2022. Nutritional quality of giant kelp declines due to warming ocean temperatures. Oikos, e08619. https://doi.org/ 10.1111/oik.08619. Martins, N., Tanttu, H., Pearson, G.A., Serr˜ ao, E., Bartsch, I., 2017. Interactions of daylength, temperature and nutrients affect thresholds for life stage transition in the kelp Laminaria digitata (Phaeophyceae). Bot. Mar. 60, 109–121. https://doi.org/ 10.1515/bot-2016-0094. McGovern, M., Pavlov, A.K., Deininger, A., Granskog, M.A., Leu, E., Søreide, J., Poste, A. E., 2020. Terrestrial inputs drive seasonality in organic matter and nutrient biogeochemistry in a high Arctic fjord system (Isfjorden, Svalbard). Front. Mar. Sci. 7, 542563. https://doi.org/10.3389/fmars.2020.542563. Meire, L., Mortensen, J., Meire, P., Juul-Pedersen, T., Sejr, M.K., Rysgaard, S., Nygaard, R., Huybrechts, P., Meysman, F.J.R., 2017. Marine-terminating glaciers sutain high productivity in Greenland fjords. Glob. Change Biol. 23, 5344–5357. https://doi.org/10.1111/gcb.13801. Monteiro, C., Li, H., Diehl, N., Coll´ en, J., Heinrich, S., Bischof, K., Bartsch, I., 2021. Modulation of physiological performance by temperature and salinity in the sugar kelp Saccharina latissima. Phycol. Res. 69, 48–57. https://doi.org/10.1111/ pre.12443. Niedzwiedz, S., Bischof, K., 2023. Glacial retreat and rising temperatures are limiting the expansion of temperate kelp species in the future Arctic. Limnol. Oceanogr. 68, 816–830. https://doi.org/10.1002/lno.12312. Niedzwiedz, S., Diehl, N., Fischer, P., Bischof, K., 2022. Seasonal and inter-annual variability in the heatwave tolerance of the kelp Saccharina latissima (Laminariales, Phaeophyceae). Phycol. Res. 70, 212–222. https://doi.org/10.1111/pre.12501. Niedzwiedz, S., Vonnahme, T.R., Juul-Pedersen, T., Bischof, K., Diehl, N., 2024. Lightmediated temperature susceptibility of kelp species (Agarum clathratum, Saccharina latissima) in an Arctic summer heatwave scenario. Cambridge Prisms: Coastal Futures 2, 1–13. https://doi.org/10.1017/cft.2024.5. Olischl¨ ager, M., I˜ niguez, C., Gordillo, F.J.L., Wiencke, C., 2014. Biochemical composition of temperate and Arctic populations of Saccharina latissima after exposure to increased pCO 2 and temperature reveals ecotypic variation. Planta 240, 1213–1224. https://doi.org/10.1007/s00425-014-2143-x. Pessarrodona, A., Assis, J., Filbee-Dexter, K., Burrows, M.T., Gattuso, J.-P., Duarte, C.M., Krause-Jensen, D., Moore, P.J., Smale, D.A., Wernberg, T., 2022. Global seaweed production. Sci. Adv. 8, eabn2465. https://doi.org/10.1126/sciadv.abn2465. Previdi, M., Tyler, T.P., Chiodo, G., Smith, K.L., Polvani, L.M., 2020. Arctic amplification: a rapid response to radiative forcing. Geophys. Res. Lett. 47, e2020GL089933. https://doi.org/10.1029/2020GL089933. Previdi, M., Smith, K.L., Polvani, L.M., 2021. Arctic amplification of climate change: a review of underlying mechanisms. Environ. Res. 16, 093003. https://doi.org/ 10.1088/1748-9326/ac1c29. R Core Team, 2023. R: a language and environment for statistical computing. R Foundation for statistical computing. https://www.R-project.org/. Re, R., Pellegrini, N., Proteggente, A., Pannala, A., Yang, M., Rice-Evans, C., 1999. Antioxidant activity applying an improved ABTS radical cation decolorization assay. Free Radic. Biol. Med. 26, 1231–1237. https://doi.org/10.1016/s0891-5849(98) 00315-3. Reed, T.E., Schindler, D.E., Waples, R.S., 2011. Interacting effects of phenotypic plasticity and evolution on population persistence in a changing climate. Conserv. Biol. 25, 56–63. https://doi.org/10.1111/j.1523-1739.2010.01552.x. Sæther, M., Diehl, N., Monteiro, C., Li, H., Niedzwiedz, S., Burgunter-Delamare, B., Scheschonk, L., Bischof, K., Forbord, S., 2024. The sugar kelp Saccharina latissima II: recent advances in farming and applications. J. Appl. Phycol. https://doi.org/ 10.1007/s10811-024-03213-1. Scheschonk, L., Becker, S., Hehemann, J.-H., Diehl, N., Karsten, U., Bischof, K., 2019. Arctic kelp eco-physiology during the polar night in the face of global warming: a crucial role for laminarin. Mar. Ecol. Prog. Ser. 611, 59–74. https://doi.org/ 10.3354/meps12860. S. Niedzwiedz et al. Marine Environmental Research 212 (2025) 107604 8 Schloerke, B., Cook, D., Larmarange, J., Briatte, F., Marbach, M., Thoen, E., Elberg, A., Crowley, J., 2023. GGally: extension to ’ggplot2’. R package version 2.2.0. https://C RAN.R-project.org/package=GGally. Sejr, M.K., Poste, A.W., Renaud, P.E., 2024. Multiple climatic drivers increase pace and consequences of ecosystem change in the Arctic coastal ocean. Limnol. Oceanogr.: Lett. 9, 683–695. https://doi.org/10.1002/lol2.10431. Sharma, P., Jha, A.B., Dubey, R.S., Pessarakli, M., 2012. Reactive oxygen species, oxidative damage and antioxidative defense mechanism in plants under stressful conditions. J. Botany 217037. https://doi.org/10.1155/2012/217037. Stahl, F., Kappas, L., Uhl, F., Oppelt, N., Bischof, K., 2024. Feasibility study for kelp afforestation in the German bight: habitat availability and light requirements of Laminaria hyperborea. J. Sea Res. 102512. https://doi.org/10.1016/j. seares.2024.102512. Steneck, R.S., Graham, M.H., Bourque, B.J., Corbett, D., Erlandson, J.A., Estes, J.A., Tegner, M.J., 2002. Kelp forest ecosystems: biodiversity, stability, resilience and future. Environ. Conserv. 29, 436–459. https://doi.org/10.1017/ S0376892902000322. Stomp, M., Huisman, J., Stal, L.J., Matthijs, H.C.P., 2007. Colorful niches of phototrophic microorganisms shaped by vibrations of the water molecule. ISME J. 1, 271–282. https://doi.org/10.1038/ismej.2007.59. Svendsen, H., Beszczynska-Møller, A., Hagen, J.O., Lefauconnier, B., Tverberg, V., Gerland, S., Ørbæk, J.B., Bischof, K., Papucci, C., Zajaczkowski, M., Azzolini, R., Bruland, O., Wiencke, C., Winther, J.-G., Dallmann, W., 2002. The physical environment of Kongsfjorden-Krossfjorden, an Arctic fjord system in Svalbard. Polar Res. 21, 133–166. https://doi.org/10.3402/polar.v21i1.6479. Verardo, D.J., Froelich, P.N., McIntyre, A., 1990. Determination of organic carbon and nitrogen in marine sediments using the Carlo Erba NA-1500 analyzer. Deep-Sea Res. 37, 157–165. https://doi.org/10.1016/0198-0149(90)90034-S. Vihtakari, M., 2024. ggOceanMaps: Plot data on oceanographic maps using ’ggplot2’. R package version 2.2.0. https://CRAN.R-project.org/package=ggOceanMaps. Vranken, S., Wernberg, T., Scheben, A., Severn-Ellis, A.A., Batley, J., Bayer, P.E., Edwards, D., Wheeler, D., Coleman, M.A., 2021. Genotype-environment mismatch of kelp forests under climate change. Mol. Ecol. 30, 3730–37446. https://doi.org/ 10.1111/mec.15993. Wahl, M., Werner, F.J., Buchholz, B., Raddatz, S., Graiff, A., Matthiessen, B., Karsten, U., Hiebenthal, C., Hamer, J., Ito, M., Gülzow, E., Rilov, G., Guy-Haim, T., 2020. Season affects strength and direction of the interactive impacts of ocean warming and biotic stress in a coastal seaweed ecosystem. Limnol. Oceanogr. 65, 807–827. https://doi. org/10.1002/lno.11350. Wernberg, T., Krumhansl, K., Filbee-Dexter, K., Pedersen, M.F., 2019. Status and trends for the world’s kelp forests. In: Sheppard, C. (Ed.), World Seas: an Environmental Evaluation. Elsevier, pp. 57–78. https://doi.org/10.1016/B978-0-128050521.00003-6. Wernberg, T., Thomsen, M.S., Baum, J.K., Bishop, M.J., Bruno, J.F., Coleman, M.A., Filbee-Dexter, K., Gagnon, K., He, Q., Murdiyarso, D., Rogers, K., Silliman, B.R., Smale, D.A., Starko, S., Vanderklift, M.A., 2024. Impacts of climate change on marine foundation species. Ann. Rev. Mar. Sci 16, 247–282. https://doi.org/ 10.1146/annurev-marine-042023-093037. Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L.D., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T.L., Miller, E., Bache, S.M., Müller, K., Ooms, J., Robinson, D., Seidel, D.P., Spinu, V., Takahashi, K., Vaughan, D., Wilke, C., Woo, K., Yutani, H., 2019. Welcome to the tidyverse. J. Open Source Softw. 4, 1686. https://doi.org/10.21105/joss.01686. Wright, S.W., Jeffrey, S.W., Mantoura, R.F.C., Llewellyn, C.A., Bjørnland, T., Repeta, D., Welschmeyer, N., 1991. Improved HPLC method for the analysis of chlorophylls and carotenoids from marine phytoplankton. Mar. Ecol. Prog. Ser. 77, 183–196. https:// doi.org/10.3354/meps077183. S. Niedzwiedz et al. Marine Environmental Research 212 (2025) 107604 9