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.

FjordLight

An R package to aid in accessing the fjord PAR data product created for the FACE-IT project.

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)

heatwave3

An R package for the detection of heatwaves and cold-spells directly on NetCDF files.

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.

Sea Ice and Substratum Shape Extensive Kelp Forests in the Canadian Arctic

The coastal zone of the Canadian Arctic represents 10% of the world’s coastline and is one of the most rapidly changing marine regions on the planet. To predict the consequences of these environmental changes, a better understanding of how environmental gradients shape coastal habitat structure in this area is required. We quantified the abundance and diversity of canopy forming seaweeds throughout the nearshore zone (5–15 m) of the Eastern Canadian Arctic using diving surveys and benthic collections at 55 sites distributed over 3,000 km of coastline. Kelp forests were found throughout, covering on average 40.4% (±29.9 SD) of the seafloor across all sites and depths, despite thick sea ice and scarce hard substrata in some areas. Total standing macroalgal biomass ranged from 0 to 32 kg m–2 wet weight and averaged 3.7 kg m–2 (±0.6 SD) across all sites and depths. Kelps were less abundant at depths of 5 m compared to 10 or 15 m and distinct regional assemblages were related to sea ice cover, substratum type, and nutrient availability. The most common community configuration was a mixed assemblage of four species: Agarum clathratum (14.9% benthic cover ± 12.0 SD), Saccharina latissima (13% ± 14.7 SD), Alaria esculenta (5.4% ± 1.2 SD), and Laminaria solidungula (3.7% ± 4.9 SD). A. clathratum dominated northernmost regions and S. latissima and L. solidungula occurred at high abundance in regions with more open water days. In southeastern areas along the coast of northern Labrador, the coastal zone was mainly sea urchin barrens, with little vegetation. We found positive relationships between open water days (days without sea ice) and kelp biomass and seaweed diversity, suggesting kelp biomass could increase, and the species composition of kelp forests could shift, as sea ice diminishes in some areas of the Eastern Canadian Arctic. Our findings demonstrate the high potential productivity of this extensive coastal zone and highlight the need to better understand the ecology of this system and the services it provides.

Kelp in the Eastern Canadian Arctic: Current and Future Predictions of Habitat Suitability and Cover

Climate change is transforming marine ecosystems through the expansion and contraction of species’ ranges. Sea ice loss and warming temperatures are expected to expand habitat availability for macroalgae along long stretches of Arctic coastlines. To better understand the current distribution of kelp forests in the Eastern Canadian Arctic, kelps were sampled along the coasts for species identifications and percent cover. The sampling effort was supplemented with occurrence records from global biodiversity databases, searches in the literature, and museum records. Environmental information and occurrence records were used to develop ensemble models for predicting habitat suitability and a Random Forest model to predict kelp cover for the dominant kelp species in the region – Agarum clathratum, Alaria esculenta, and Laminariaceae species (Laminaria solidungula and Saccharina latissima). Ice thickness, sea temperature and salinity explained the highest percentage of kelp distribution. Both modeling approaches showed that the current extent of arctic kelps is potentially much greater than the available records suggest. These modeling approaches were projected into the future using predicted environmental data for 2050 and 2100 based on the most extreme emission scenario (RCP 8.5). The models agreed that predicted distribution of kelp in the Eastern Canadian Arctic is likely to expand to more northern locations under future emissions scenarios, with the exception of the endemic arctic kelp L. solidungula, which is more likely to lose a significant proportion of suitable habitat. However, there were differences among species regarding predicted cover for both current and future projections. Notwithstanding model-specific variation, it is evident that kelps are widespread throughout the area and likely contribute significantly to the functioning of current Arctic ecosystems. Our results emphasize the importance of kelp in Arctic ecosystems and the underestimation of their potential distribution there.

Marine cold-spells

Characterising ocean temperature variability and extremes is fundamental for understanding the thermal bounds in which marine ecosystems have adapted. While there is growing evidence of how marine heatwaves threaten marine ecosystems, prolonged periods of extremely cold ocean temperatures, marine cold-spells, have received less global attention. We synthesize the literature on cold ocean temperature extremes and their ecological impacts and physical mechanisms. Ecological impacts of these events were observed across a range of species and biophysical processes, including mass mortalities, range shifts, marine habitat loss, and altered phenology. The development of marine cold-spells is often due to wind-induced ocean processes, but a range of physical mechanisms are documented in the literature. Given the need for consistent comparison of marine cold-spells, we develop a definition for detecting these events from temperature time series and for classifying them into four categories. This definition is used to consistently detect marine cold-spells globally over the satellite record and to compare the characteristics of notable cold events. Globally, marine cold-spells’ occurrence, duration, and intensity are decreasing, with some areas, such as the Southern Ocean, showing signs of increase over the past 15 years. All marine cold-spell categories are affected by these decreases, with the exception of “IV Extreme” events, which were so rare that there has been little decrease. While decreasing occurrences of marine cold-spells could be viewed as providing a beneficial reduction in cold stress for marine ecosystems, fewer cold spells will alter the temperature regime that marine ecosystems experience and could have important consequences on ecological structure and function.

A novel approach to quantify metrics of upwelling intensity, frequency, and duration

The importance of coastal upwelling systems is widely recognized. However, several aspects of the current and future behaviors of these systems remain uncertain. Fluctuations in temperature because of anthropogenic climate change are hypothesized to affect upwelling-favorable winds and coastal upwelling is expected to intensify across all Eastern Boundary Upwelling Systems. To better understand how upwelling may change in the future, it is necessary to develop a more rigorous method of quantifying this phenomenon. In this paper, we use SST data and wind data in a novel method of detecting upwelling signals and quantifying metrics of upwelling intensity, duration, and frequency at four sites within the Benguela Upwelling System. We found that indicators of upwelling are uniformly detected across five SST products for each of the four sites and that the duration of those signals is longer in SST products with higher spatial resolutions. Moreover, the high-resolution SST products are significantly more likely to display upwelling signals at 25 km away from the coast when signals were also detected at the coast. Our findings promote the viability of using SST and wind time series data to detect upwelling signals within coastal upwelling systems. We highlight the importance of high-resolution data products to improve the reliability of such estimates. This study represents an important step towards the development of an objective method for describing the behavior of coastal upwelling systems.

Drivers of Marine Heatwaves in the Northwest Atlantic: The Role of Air–Sea Interaction During Onset and Decline

Marine heatwaves (MHWs) are increasing in duration and intensity at a global scale and are projected to continue to increase due to the anthropogenic warming of the climate. Because MHWs may have drastic impacts on fisheries and other marine goods and services, there is a growing interest in understanding the predictability and developing practical predictions of these events. A necessary step toward prediction is to develop a better understanding of the drivers and processes responsible for the development of MHWs. Prior research has shown that air–sea heat flux and ocean advection across sharp thermal gradients are common physical processes governing these anomalous events. In this study we apply various statistical analyses and employ the self-organizing map (SOM) technique to determine specifically which of the many candidate physical processes, informed by a theoretical mixed-layer heat budget, have the most pronounced effect on the onset and/or decline of MHWs on the Northwest Atlantic continental shelf. It was found that latent heat flux is the most common driver of the onset of MHWs. Mixed layer depth (MLD) also strongly modulates the onset of MHWs. During the decay of MHWs, atmospheric forcing does not explain the evolution of the MHWs well, suggesting that oceanic processes are important in the decay of MHWs. The SOM analysis revealed three primary synoptic scale patterns during MHWs: low-pressure cyclonic Autumn-Winter systems, high-pressure anti-cyclonic Spring-Summer blocking, and mild but long-lasting Summer blocking. Our results show that nearly half of past MHWs on the Northwest Atlantic shelf are initiated by positive heat flux anomaly into the ocean, but less than one fifth of MHWs decay due to this process, suggesting that oceanic processes, e.g., advection and mixing are the primary driver for the decay of most MHWs.

Variation and Change of Upwelling Dynamics Detected in the World’s Eastern Boundary Upwelling Systems

Global increases in temperature are altering land-sea temperature gradients. Bakun (1990) hypothesized that changes within these gradients will directly affect atmospheric pressure cells associated with the development of winds and will consequently impact upwelling patterns within ecologically important Eastern Boundary Upwelling Systems (EBUS). In this study we used daily time series of NOAA Optimally Interpolated sea surface temperature (SST) and ERA 5 reanalysis wind products to calculate a series novel of metrics related to upwelling dynamics. We then use these to objectively describe upwelling signals in terms of their frequency, intensity and duration throughout the four EBUS during summer months over the last 37 years (1982–2019). We found that a decrease (increase) in SST is associated with an increase (decrease) in the number of upwelling “events,” a decrease (increase) in the intensity of upwelling, and an increase (decrease) in the cumulative intensity of upwelling, with differences between EBUS and regions within EBUS. The Humboldt Current is the only EBUS that shows a consistent response from north to south with a general intensification of upwelling. However, we could not provide clear evidence for associated changes in the wind dynamics hypothesized to drive the upwelling dynamics.

Marine Heatwaves

Marine heatwaves (MHWs) are increasing in duration and intensity at a global scale and are projected to continue to increase due to the anthropogenic warming of the climate. Because MHWs may have drastic impacts on fisheries and other marine goods and services, there is a growing interest in understanding the predictability and developing practical predictions of these events. A necessary step toward prediction is to develop a better understanding of the drivers and processes responsible for the development of MHWs. Prior research has shown that air–sea heat flux and ocean advection across sharp thermal gradients are common physical processes governing these anomalous events. In this study we apply various statistical analyses and employ the self-organizing map (SOM) technique to determine specifically which of the many candidate physical processes, informed by a theoretical mixed-layer heat budget, have the most pronounced effect on the onset and/or decline of MHWs on the Northwest Atlantic continental shelf. It was found that latent heat flux is the most common driver of the onset of MHWs. Mixed layer depth (MLD) also strongly modulates the onset of MHWs. During the decay of MHWs, atmospheric forcing does not explain the evolution of the MHWs well, suggesting that oceanic processes are important in the decay of MHWs. The SOM analysis revealed three primary synoptic scale patterns during MHWs: low-pressure cyclonic Autumn-Winter systems, high-pressure anti-cyclonic Spring-Summer blocking, and mild but long-lasting Summer blocking. Our results show that nearly half of past MHWs on the Northwest Atlantic shelf are initiated by positive heat flux anomaly into the ocean, but less than one fifth of MHWs decay due to this process, suggesting that oceanic processes, e.g., advection and mixing are the primary driver for the decay of most MHWs.

What and where? Predicting invasion hotspots in the Arctic marine realm

The risk of aquatic invasions in the Arctic is expected to increase with climate warming, greater shipping activity and resource exploitation in the region. Planktonic and benthic marine aquatic invasive species (AIS) with the greatest potential for invasion and impact in the Canadian Arctic were identified and the 23 riskiest species were modelled to predict their potential spatial distributions at pan-Arctic and global scales. Modelling was conducted under present environmental conditions and two intermediate future (2050 and 2100) global warming scenarios. Invasion hotspots—regions of the Arctic where habitat is predicted to be suitable for a high number of potential AIS—were located in Hudson Bay, Northern Grand Banks/Labrador, Chukchi/Eastern Bering seas and Barents/White seas, suggesting that these regions could be more vulnerable to invasions. Globally, both benthic and planktonic organisms showed a future poleward shift in suitable habitat. At a pan-Arctic scale, all organisms showed suitable habitat gains under future conditions. However, at the global scale, habitat loss was predicted in more tropical regions for some taxa, particularly most planktonic species. Results from the present study can help prioritize management efforts in the face of climate change in the Arctic marine ecosystem. Moreover, this particular approach provides information to identify present and future high-risk areas for AIS in response to global warming.

heatwaveR

An R package for the detection of heatwaves and cold-spells.

coastR

An R package with useful functions for coastal oceanography.

Detecting Marine Heatwaves With Sub-Optimal Data

Marine heatwaves (MHWs), or prolonged periods of anomalously warm sea water temperature, have been increasing in duration and intensity globally for decades. However, there are many coastal, oceanic, polar, and sub-surface regions where our ability to detect MHWs is uncertain due to limited high quality data. Here, we investigate the effect that short time series length, missing data, or linear long-term temperature trends may have on the detection of MHWs. We show that MHWs detected in time series as short as 10 years did not have durations or intensities appreciably different from events detected in a standard 30 year long time series. We also show that the output of our MHW algorithm for time series missing less than 25% data did not differ appreciably from a complete time series, and that the level of allowable missing data could cautiously be increased to 50% when gaps were filled by linear interpolation. Finally, linear long-term trends of 0.10°C/decade or greater added to a time series caused larger changes (increases) to the count and duration of detected MHWs than shortening a time series to 10 years or missing more than 25% of the data. The long-term trend in a time series has the largest effect on the detection of MHWs and has the largest range in added uncertainty in the results. Time series length has less of an effect on MHW detection than missing data, but adds a larger range of uncertainty to the results. We provide suggestions for best practices to improve the accuracy of MHW detection with sub-optimal time series and show how the accuracy of these corrections may change regionally.

Detecting marine heatwaves with sub-optimal data

Research conducted on how sub-optimal a time series may be and still produce comparable marine heatwaves to an optimal time series.

Marine Heatwave Tracker: The app to see when and where marine heatwaves are happening around the world

The Marine Heatwave Tracker software provides all of the tools necessary to download, process, and visualise marine heatwaves (MHWs) globally. This web application may be set up to show the occurrence of MHWs around the world in near-real-time (roughly a one-to-two day delay) using a cron job that runs a bash script calling ‘MHW_daily.R’. The Tracker also shows the historic records for the entire planet going back to January 1, 1982. Several additional data layers are offered in the Tracker. Further details are available through the app documentation.

heatwaveR: A central algorithm for the detection of heatwaves and cold-spells

heatwaveR is an R package that implements a consistent workflow for detecting and characterising marine heatwaves and cold-spells from temperature time series. The package provides the core algorithms, helper functions, and reproducible tooling needed to apply the Hobday et al. framework in research and operational settings.

Predominant Atmospheric and Oceanic Patterns during Coastal Marine Heatwaves

As the mean temperatures of the worlds oceans increase, it is predicted that marine heatwaves (MHWs) will occur more frequently and with increased severity. However, it has been shown that variables other than increases in sea water temperature have been responsible for MHWs. To better understand these mechanisms driving MHWs we have utilized atmospheric (ERA-Interim) and oceanic (OISST, AVISO) data to examine the patterns around southern Africa during coastal (<400 m from the low water mark; measured in situ) MHWs. Nonmetric multidimensional scaling (NMDS) was first used to determine that the atmospheric and oceanic states during MHW are different from daily climatological states. Self-organizing maps (SOMs) were then used to cluster the MHW states into one of nine nodes to determine the predominant atmospheric and oceanic patterns present during these events. It was found that warm water forced onto the coast via anomalous ocean circulation was the predominant oceanic pattern during MHWs. Warm atmospheric temperatures over the subcontinent during onshore or alongshore winds were the most prominent atmospheric patterns. Roughly one third of the MHWs were clustered into a node with no clear patterns, which implied that they were not forced by a recurring atmospheric or oceanic state that could be described by the SOM analysis. Because warm atmospheric and/or oceanic temperature anomalies were not the only pattern associated with MHWs, the current trend of a warming earth does not necessarily mean that MHWs will increase apace; however, aseasonal variability in wind and current patterns was shown to be central to the formation of coastal MHWs, meaning that where climate systems shift from historic records, increases in MHWs will likely occur.

Nearshore and offshore co-occurrence of marine heatwaves and cold-spells

A changing global climate places shallow water ecosystems at more risk than those in the open ocean as their temperatures may change more rapidly and dramatically. To this end, it is necessary to identify the occurrence of extreme ocean temperature events – marine heatwaves (MHWs) and marine cold-spells (MCSs) – in the nearshore (<400 m from the coastline) environment as they can have lasting ecological effects. The occurrence of MHWs have been investigated regionally, but no investigations of MCSs have yet to be carried out. The occurrence of MHWs have been investigated regionally, but no investigations of MCSs have yet to be carried out. A recently developed framework that defines these events in a novel way was applied to ocean temperature time series from (i) a nearshore in situ dataset and (ii) 1/4° NOAA Optimally Interpolated sea surface temperatures. Regional drivers due to nearshore influences (local-scale) and the forcing of two offshore ocean currents (broad-scale) on MHWs and MCSs were taken into account when the events detected in these two datasets were used to infer the links between offshore and nearshore temperatures in time and space. We show that MHWs and MCSs occur at least once a year on average but that proportions of co-occurrence of events between the broad- and local scales are low (0.20–0.50), with MHWs having greater proportions of co-occurrence than MCSs. The low rates of co-occurrence between the nearshore and offshore datasets show that drivers other than mesoscale ocean temperatures play a role in the occurrence of at least half of nearshore events. Significant differences in the duration and intensity of events between different coastal sections may be attributed to the effects of the interaction of oceanographic processes offshore, as well as with local features of the coast. The decadal trends in the occurrence of MHWs and MCSs in the offshore dataset show that generally MHWs are increasing there while MCSs are decreasing. This study represents an important first step in the analysis of the dynamics of events in nearshore environments, and their relationship with broad-scale influences.

Climate Change in Coastal Waters: Time Series Properties Affecting Trend Estimation

In South Africa, 129 in situ temperature time series of up to 43 years are used for investigations of the thermal characteristics of coastal seawater. They are collected with handheld thermometers or underwater temperature recorders (UTRs) and are recorded at precisions from 0.5° to 0.001°C. Using the natural range of seasonal signals and variability for 84 of these time series, their length, decadal trend, and data precision were systematically varied before fitting generalized least squares (GLS) models to study the effect these variables have on trend detection. The variables that contributed most to accurate trend detection, in decreasing order, were time series length, decadal trend, variance, percentage of missing data (% NA), and measurement precision. Time series greater than 30 years in length are preferred and although larger decadal trends are modeled more accurately, modeled significance (p value) is largely affected by the variance present. The risk of committing both type-1 and type-2 errors increases when ≥5% NA is present. There is no appreciable effect on model accuracy between measurement precision of 0.1°–0.001°C. Measurement precisions of 0.5°C require longer time series to give equally accurate model results. The implication is that the thermometer time series in this dataset, and others around the world, must be at least two years longer than their UTR counterparts to be useful for decadal-scale climate change studies. Furthermore, adding older lower-precision UTR data to newer higher-precision UTR data within the same time series will increase their usefulness for this purpose.