One mechanism by which marine organisms may respond to climate shifts is range shifts. The corkwing wrasse (Symphodus melops) is a temperate fish species, inhabiting the coasts of Europe, that show strong indications of current as well as historical (ice-age) range shifts towards the north. Nine neutral microsatellite DNA markers were screened to study genetic signatures and spatial population structure over the entire geographic and thermal gradient of the species from Portugal to Norway. A major genetic break (F_ST = 0.159 average among pairs) was identified between Scandinavian and more southern populations, with a marked reduction (30% or more) in levels of genetic variability in Scandinavia. The break is probably related to bottleneck(s) associated with post-glacial colonization of the Scandinavian coasts, and indicates a lack of present gene flow across the North Sea. The lack of gene flow can most likely be attributed to the species’ need for rocky substrate for nesting and a relatively short pelagic larval phase, limiting dispersal by ocean currents. These findings demonstrate that long-distance dispersal may be severely limited in the corkwing wrasse, and that successful range-shifts following present climate change may be problematic for this and other species with limited dispersal abilities, even in the seemingly continuous marine environment.

Kelp forests are highly productive systems that are important ecologically and commercially as well as in a blue carbon perspective. Given their importance, there is an urgent need to achieve reliable estimates of the spatial distribution of their biomass. Species distribution modelling is a powerful tool for producing such estimates, but it requires a solid framework, including important environmental covariates that have a direct effect on their biomass, a proper sampling strategy, and an independent evaluation dataset. Using Laminaria hyperborea as a model species, we developed a modelling framework considering these requirements and necessary steps to produce reliable predictions. Our modelling framework included proportion of hard substrate and bottom wave exposure, both crucial covariates that have a direct effect on the biomass of L. hyperborea, but rarely included in modelling studies. Furthermore, we devised a sampling strategy with field observations covering the whole environmental covariate space present in the study area. Subsequently, we fitted GAMs relating the field observations of the biomass of L. hyperborea to relevant environmental covariates. The best model containing the predictors bottom wave exposure, depth, and proportion hard substrate explained most of the variance in the dataset (83.1% deviance explained). This model was then used to predict the spatial distribution of biomass across the whole study area. To assess the reliability of the biomass predictions, we used an independent dataset of L. hyperborea biomass observations from the same area. This independent dataset correlated very well with spatial predictions of biomass based on our best model (R = 0.85). In total, we predicted a biomass of 457,000 tonnes in a 1,150 km² study area on the West coast of Norway. Our modelling framework provides the means for developing a biomass model on a broader geographical scale. Such a model will be invaluable in improving kelp management regimes as well as for estimating the contribution of kelp forests to ecosystem services such as carbon sequestration and climate budgets.

Small‐scale fisheries (SSFs) tend to target shallow waters, but the depth distributions of coastal fish can vary depending on species, size, and sex. This creates a scope for a form of fishing selectivity that has received limited attention but can have considerable implications for monitoring and management of these fisheries. We conducted a case study on the Norwegian wrasse fishery, a developing SSF in which multiple species are caught in shallow waters (mean depth = 4.5 m) to be used as cleaner fish in aquaculture. Several of these wrasses have life histories and behaviors that are sensitive to selective fishing mortality, such as sexual size dimorphism, paternal care, and sex change. An experimental fishery was undertaken over three sampling periods in 2018. Data on catch, length, and sex of wrasses across a depth gradient (0–18 m) were collected and analyzed. We found that depth distributions were species specific and the vertical overlap with the fishery was high for Corkwing Wrasse Symphodus melops and Ballan Wrasse Labrus bergylta, which were most abundant at depths less than 5 m. Three other wrasse species had invariant or increasing abundance with depth and were therefore less likely to be negatively impacted by this fishery. Body size was positively correlated with depth for these wrasses, and sex ratio became more male biased for the Corkwing Wrasse, the only species that could be visually sexed. This study demonstrates that depth can have strong effects on fishing selectivity at multiple scales and that such knowledge is necessary to develop management strategies that balance fishing mortality sustainably across species, sizes, and sexes. We recommend that management priorities be directed toward the Ballan and Corkwing wrasses—the species having the highest vertical overlap with the fishery. Furthermore, CPUE was strongly affected by seasonality and positively correlated with increasing wave exposure for one of the species. This underscores the general importance of standardizing catch data for several environmental covariates when monitoring species that are affected by SSFs.

The use of habitat distribution models (HDMs) has become common in benthic habitat mapping for combining limited seabed observations with full-coverage environmental data to produce classified maps showing predicted habitat distribution for an entire study area. However, relatively few HDMs include oceanographic predictors, or present spatial validity or uncertainty analyses to support the classified predictions. Without reference studies it can be challenging to assess which type of oceanographic model data should be used, or developed, for this purpose. In this study, we compare biotope maps built using predictor variable suites from three different oceanographic models with differing levels of detail on near-bottom conditions. These results are compared with a baseline model without oceanographic predictors. We use associated spatial validity and uncertainty analyses to assess which oceanographic data may be best suited to biotope mapping. Our results show how spatial validity and uncertainty metrics capture differences between HDM outputs which are otherwise not apparent from standard non-spatial accuracy assessments or the classified maps themselves. We conclude that biotope HDMs incorporating high-resolution, preferably bottom-optimised, oceanography data can best minimise spatial uncertainty and maximise spatial validity. Furthermore, our results suggest that incorporating coarser oceanographic data may lead to more uncertainty than omitting such data.

Using national and international research survey data and applying a combination of models and mapping tools, this study revealed temperature and depth as the crucial environmental drivers of both the distribution and the abundance of four benthopelagic chondrichthyans inhabiting Norwegian and Icelandic waters: rabbitfish (Chimaera monstrosa), velvet‐belly lanternshark (Etmopterus spinax), blackmouth catshark (Galeus melastomus) and spurdog (Squalus acanthias). C. monstrosa and E. spinax seem to prefer similar spatial and ecological habitats, that is deep and cold waters. In contrast, G. melastomus and S. acanthias both prefer similar ecological habitats, that is warmer and shallower waters; nonetheless, they exhibit a different spatial distribution pattern. The species' varied habitat and spatial preferences may lead to different levels of exposure to fishing activities and associated by‐catch risks. Findings of the species' spatial distributions and their driving forces are expected to inform the sustainable management of these species and the ecosystems they inhabit.