Description: Background: Kelps (Laminariales, Phaeophyceae) are brown macroalgae of utmost ecological, and increasingly economic, importance on temperate to polar rocky shores. Omics approaches in brown algae are still scarce and knowledge of their acclimation mechanisms to the changing conditions experienced in coastal environments can benefit from the application of RNA-sequencing. Despite evidence of ecotypic differentiation, transcriptomic responses from distinct geographical locations have, to our knowledge, never been studied in the sugar kelp Saccharina latissima so far. Results: In this study we investigated gene expression responses using RNA-sequencing of S. latissima from environments with contrasting temperature and salinity conditions – Roscoff, in temperate eastern Atlantic, and Spitsbergen in the Arctic. Juvenile sporophytes derived from uniparental stock cultures from both locations were pre-cultivated at 8 °C and SA 30. Sporophytes acclimated to 0 °C, 8 °C and 15 °C were exposed to a low salinity treatment (SA 20) for 24 h. Hyposalinity had a greater impact at the transcriptomic level than the temperature alone, and its effects were modulated by temperature. Namely, photosynthesis and pigment synthesis were extensively repressed by low salinity at low temperatures. Although some responses were shared among sporophytes from the different sites, marked differences were revealed by principal component analysis, differential expression and GO enrichment. The interaction between low temperature and low salinity drove the largest changes in gene expression in sporophytes from Roscoff while specimens from Spitsbergen required more metabolic adjustment at higher temperatures. Moreover, genes related to cell wall adjustment were differentially expressed between Spitsbergen and Roscoff control samples. Conclusions: Our study reveals interactive effects of temperature and salinity on transcriptomic profiles in S. latissima. Moreover, our data suggest that under identical culture conditions sporophytes from different locations diverge in their transcriptomic responses. This is probably connected to variations in temperature and salinity in their respective environment of origin. The current transcriptomic results support the plastic response pattern in sugar kelp which is a species with several reported ecotypes. Our data provide the baseline for a better understanding of the underlying processes of physiological plasticity and may help in the future to identify strains adapted to specific environments and its genetic control.

Description: Kelp forests represent a major habitat type in coastal waters worldwide and their structure and distribution is predicted to change due to global warming. Despite their ecological and economical importance, there is still a lack of reliable spatial information on their abundance and distribution. In recent years, various hydroacoustic mapping techniques for sublittoral environments evolved. However, in turbid coastal waters, such as off the island of Helgoland (Germany, North Sea), the kelp vegetation is present in shallow water depths normally excluded from hydroacoustic surveys. In this study, single beam survey data consisting of the two seafloor parameters roughness and hardness were obtained with RoxAnn from water depth between 2 and 18 m. Our primary aim was to reliably detect the kelp forest habitat with different densities and distinguish it from other vegetated zones. Five habitat classes were identified using underwater-video and were applied for classification of acoustic signatures. Subsequently, spatial prediction maps were produced via two classification approaches: Linear discriminant analysis (LDA) and manual classification routine (MC). LDA was able to distinguish dense kelp forest from other habitats (i.e. mixed seaweed vegetation, sand, and barren bedrock), but no variances in kelp density. In contrast, MC also provided information on medium dense kelp distribution which is characterized by intermediate roughness and hardness values evoked by reduced kelp abundances. The prediction maps reach accordance levels of 62% (LDA) and 68% (MC). The presence of vegetation (kelp and mixed seaweed vegetation) was determined with higher prediction abilities of 75% (LDA) and 76% (MC). Since the different habitat classes reveal acoustic signatures that strongly overlap, the manual classification method was more appropriate for separating different kelp forest densities and low-lying vegetation. It became evident that the occurrence of kelp in this area is not simply linked to water depth. Moreover, this study shows that the two seafloor parameters collected with RoxAnn are suitable indicators for the discrimination of different densely vegetated seafloor habitats in shallow environments.