Fjord

Predicting potential Arctic kelp distribution and lower-depth biomass from seafloor irradiance

This paper develops a framework for estimating potential Arctic kelp distribution and lower-depth biomass from seafloor irradiance. Using fjord-specific empirical relationships, it links standing stock estimates to light availability and its drivers, providing a baseline for tracking how changing coastal light environments may alter Arctic kelp biomass under ongoing environmental change.

Underwater light environment in Arctic fjords

Most inhabitants of the Arctic live near the coastline, which includes fjord systems where socio-ecological coupling with coastal communities is dominant. It is therefore critically important that the key aspects of Arctic fjords be measured as well as possible. Much work has been done to monitor temperature and salinity, but in-depth knowledge of the light environment throughout Arctic fjords is lacking. This is particularly problematic knowing the importance of light for benthic ecosystem engineers such as macroalgae, which also play a major role in ecosystem function. Here we document the creation and implementation of a high-resolution (∼50–150 m) gridded dataset for surface photosynthetically available radiation (PAR), diffuse attenuation of PAR through the water column (KPAR), and PAR available at the seafloor (bottom PAR) for seven Arctic fjords distributed throughout Svalbard, Greenland, and Norway during the period 2003–2022. In addition to KPAR and bottom PAR being available at a monthly resolution over this time period, all variables are available as a global average, annual averages, and monthly climatologies, with standard deviations provided for the latter two. Throughout most Arctic fjords, the interannual variability of monthly bottom PAR is too large to determine any long-term trends. However, in some fjords, bottom PAR increases in spring and autumn and decreases in summer. While a full investigation into these causes is beyond the scope of the description of the dataset presented here, it is hypothesized that this shift is due to a decrease in seasonal ice cover (i.e. enhanced surface PAR) in the shoulder seasons and an increase in coastal runoff (i.e. increased turbidity and decreased surface PAR) in summer. A demonstration of the usability of the dataset is given by showing how it can be combined with known PAR requirements of macroalgae to track the change in the potential distribution area for macroalgal habitats within fjords with time. The datasets are available on PANGAEA at https://doi.org/10.1594/PANGAEA.962895 (Gentili et al., 2023a) and https://doi.org/10.1594/PANGAEA.965460 (Gentili et al., 2024). A toolbox for downloading and working with this dataset is available in the form of the FjordLight R package, which is available via CRAN (Gentili et al., 2023b, https://doi.org/10.5281/zenodo.10259129) or may be installed via GitHub: https://face-it-project.github.io/FjordLight (last access: 29 April 2024).

FjordLight

A methodology, dataset, and accompanying R package to quantify the light environment within the waters of Arctic fjords.

A dataset for investigating socio-ecological changes in Arctic fjords

The collection of in situ data is generally a costly process, with the Arctic being no exception. Indeed, there has been a perception that the Arctic is lacking in situ sampling; however, after many years of concerted effort and international collaboration, the Arctic is now rather well sampled, with many cruise expeditions every year. For example, the GLODAP (Global Ocean Data Analysis Project) product has a greater density of in situ sampling points within the Arctic than along the Equator. While this is useful for open-ocean processes, the fjords of the Arctic, which serve as crucially important intersections of terrestrial, coastal, and marine processes, are sampled in a much more ad hoc process. This is not to say they are not well sampled but rather that the data are more difficult to source and combine for further analysis. It was therefore noted that the fjords of the Arctic are lacking in FAIR (findable, accessible, interoperable, and reusable) data. To address this issue, a single dataset has been created from publicly available, predominantly in situ data from seven study sites in Svalbard and Greenland. After finding and accessing the data from a number of online platforms, they were amalgamated into a single project-wide standard, ensuring their interoperability. The dataset was then uploaded to PANGAEA so that it can be findable and reusable in the future. The focus of the data collection was driven by the key drivers of change in Arctic fjords identified in a companion review paper. To demonstrate the usability of this dataset, an analysis of the relationship between the different drivers was performed. Via the use of an Arctic biogeochemical model, these relationships were projected forward to 2100 via Representative Carbon Pathways (RCPs) 2.6, 4.5, and 8.5. This dataset is a work in progress, and as new datasets containing the relevant key drivers are released, they will be added to an updated version planned for the middle of 2024. The dataset (Schlegel and Gattuso, 2022) is available on PANGAEA at https://doi.org/10.1594/PANGAEA.953115. A live version is available at the FACE-IT WP1 site and can be accessed by clicking the “Data access” tab: https://face-it-project.github.io/WP1/ (last access: 17 August 2023)

Drivers of change in Arctic fjord socio-ecological systems: Examples from the European Arctic

Fjord systems are transition zones between land and sea, resulting in complex and dynamic environments. They are of particular interest in the Arctic as they harbour ecosystems inhabited by a rich range of species and provide many societal benefits. The key drivers of change in the European Arctic (i.e., Greenland, Svalbard, and Northern Norway) fjord socio-ecological systems are reviewed here, structured into five categories: cryosphere (sea ice, glacier mass balance, and glacial and riverine discharge), physics (seawater temperature, salinity, and light), chemistry (carbonate system, nutrients), biology (primary production, biomass, and species richness), and social (governance, tourism, and fisheries). The data available for the past and present state of these drivers, as well as future model projections, are analysed in a companion paper. Changes to the two drivers at the base of most interactions within fjords, seawater temperature and glacier mass balance, will have the most significant and profound consequences on the future of European Arctic fjords. This is because even though governance may be effective at mitigating/adapting to local disruptions caused by the changing climate, there is possibly nothing that can be done to halt the melting of glaciers, the warming of fjord waters, and all of the downstream consequences that these two changes will have. This review provides the first transdisciplinary synthesis of the interactions between the drivers of change within Arctic fjord socio-ecological systems. Knowledge of what these drivers of change are, and how they interact with one another, should provide more expedient focus for future research on the needs of adapting to the changing Arctic.