Environmental change can have a significant impact on biogeochemical cycles at high latitudes and be particularly important in ecologically valuable fjord ecosystems. Seasonality in biogeochemical cycling in a sub-Arctic fjord of northern Norway (Kaldfjorden) was investigated from October 2016 to September 2018. Monthly changes in total inorganic carbon (C T ), alkalinity (A T ), major nutrients and calcium carbonate saturation (Ω) were driven by freshwater discharge, biological production and mixing with subsurface carbon-rich coastal water. Stable oxygen isotope ratios indicated that meteoric water (snow melt, river runoff, precipitation) had stratified and freshened surface waters, contributing to 81% of the monthly C T deficit in the surface layer. The timing and magnitude of freshwater inputs played an important role in Ω variability, reducing A T and C T by dilution. This dilution effect was strongly counteracted by the opposing effect of primary production that dominated surface water Ω seasonality. The spring phytoplankton bloom rapidly depleted nitrate and C T to drive highest Ω (~2.3) in surface waters. Calcification reduced A T and C T , which accounted for 21% of the monthly decrease in Ω during a coccolithophore bloom. Freshwater runoff contributed C T , A T and silicates of terrestrial origin to the fjord. Lowest surface water Ω (~1.6) resulted from organic matter remineralisation and mixing into subsurface water during winter and spring. Surface waters were undersaturated with respect to atmospheric CO 2 , resulting in modest uptake of –0.32 ± 0.03 mol C m –2 yr –1 . Net community production estimated from carbon drawdown was 14 ± 2 g C m –2 yr –1 during the productive season. Kaldfjorden currently functions as an atmospheric CO 2 sink of 3.9 ± 0.3 g C m –2 yr –1 . Time-series data are vital to better understand the processes and natural variability affecting biogeochemical cycling in dynamic coastal regions and thus better predict the impact of future changes on important fjord ecosystems.

The decline of sea-ice thickness, area, and volume due to the transition from multi-year to first-year sea ice has improved the under-ice light environment for pelagic Arctic ecosystems. One unexpected and direct consequence of this transition, the proliferation of under-ice phytoplankton blooms (UIBs), challenges the paradigm that waters beneath the ice pack harbor little planktonic life. Little is known about the diversity and spatial distribution of UIBs in the Arctic Ocean, or the environmental drivers behind their timing, magnitude, and taxonomic composition. Here, we compiled a unique and comprehensive dataset from seven major research projects in the Arctic Ocean (11 expeditions, covering the spring sea-ice-covered period to summer ice-free conditions) to identify the environmental drivers responsible for initiating and shaping the magnitude and assemblage structure of UIBs. The temporal dynamics behind UIB formation are related to the ways that snow and sea-ice conditions impact the under-ice light field. In particular, the onset of snowmelt significantly increased under-ice light availability (>0.1–0.2 mol photons m –2 d –1 ), marking the concomitant termination of the sea-ice algal bloom and initiation of UIBs. At the pan-Arctic scale, bloom magnitude (expressed as maximum chlorophyll a concentration) was predicted best by winter water Si(OH) 4 and PO 4 3– concentrations, as well as Si(OH) 4 :NO 3 – and PO 4 3– :NO 3 – drawdown ratios, but not NO 3 – concentration. Two main phytoplankton assemblages dominated UIBs (diatoms or Phaeocystis ), driven primarily by the winter nitrate:silicate (NO 3 – :Si(OH) 4 ) ratio and the under-ice light climate. Phaeocystis co-dominated in low Si(OH) 4 (i.e., NO 3 :Si(OH) 4 molar ratios >1) waters, while diatoms contributed the bulk of UIB biomass when Si(OH) 4 was high (i.e., NO 3 :Si(OH) 4 molar ratios <1). The implications of such differences in UIB composition could have important ramifications for Arctic biogeochemical cycles, and ultimately impact carbon flow to higher trophic levels and the deep ocean.

Oceanographic research is a multidisciplinary endeavor that involves the acquisition of an increasing amount of in-situ and remotely sensed data. A large and growing number of studies and data repositories are now available on-line. However, manually integrating different datasets is a tedious and grueling process leading to a rising need for automated integration tools. A key challenge in oceanographic data integration is to map between data sources that have no common schema and that were collected, processed, and analyzed using different methodologies. Concurrently, artificial agents are becoming increasingly adept at extracting knowledge from text and using domain ontologies to integrate and align data. Here, we deconstruct the process of ocean science data integration, providing a detailed description of its three phases: discover, merge, and evaluate/correct. In addition, we identify the key missing tools and underutilized information sources currently limiting the automation of the integration process. The efforts to address these limitations should focus on (i) development of artificial intelligence-based tools for assisting ocean scientists in aligning their schema with existing ontologies when organizing their measurements in datasets; (ii) extension and refinement of conceptual coverage of – and conceptual alignment between – existing ontologies, to better fit the diverse and multidisciplinary nature of ocean science; (iii) creation of ocean-science-specific entity resolution benchmarks to accelerate the development of tools utilizing ocean science terminology and nomenclature; (iv) creation of ocean-science-specific schema matching and mapping benchmarks to accelerate the development of matching and mapping tools utilizing semantics encoded in existing vocabularies and ontologies; (v) annotation of datasets, and development of tools and benchmarks for the extraction and categorization of data quality and preprocessing descriptions from scientific text; and (vi) creation of large-scale word embeddings trained upon ocean science literature to accelerate the development of information extraction and matching tools based on artificial intelligence.

The high degree of heterogeneity in the ice-ocean-atmosphere system in marginal ice zones leads to a complex set of dynamics which control fluxes of heat and buoyancy in the upper ocean. Strong fronts may occur near the ice edge between the warmer waters of the ice-free regions and the cold, fresh waters near and under the ice. This study presents observations of a well-defined density front located along the ice edge in the Beaufort Sea. The evolution of the front over a ~3-day survey period is captured by multiple cross-front sections measured using an underway conductivity-temperature-depth system, with simultaneous measurements of atmospheric forcing. Synthetic aperture radar images bookending this period show that the ice edge itself underwent concurrent evolution. Prior to the survey, the ice edge was compact and well defined while after the survey it was diffuse and filamented with coherent vortical structures. This transformation might be indicative of the development an active ocean eddy field in the upper ocean mixed layer. Over the course of hours, increasing wind stress is correlated with changes to the lateral buoyancy gradient and frontogenesis. Frontal dynamics appear to vary from typical open-ocean fronts (e.g., here the frontogenesis is linked to an “up-front” wind stress). Convective and shear-driven mixing appear to be unable to describe deepening at the heel of the front. While there was no measurable spatial variation in wind speed, we hypothesize that spatial heterogeneity in the total surface stress input, resulting from varying ice conditions across the marginal ice zone, may be a driver of the observed behaviour.

Monitoring the trend of sea ice breakup and formation in Hudson Bay is vital for maritime operations, such as local hunting or shipping, particularly in response to the lengthening of the ice-free period in the Bay driven by climate change. Satellite passive microwave sea ice concentration products are commonly used for large-scale sea ice monitoring and predictive modelling; however, these product algorithms are known to underperform during the summer melt period due to the changes in sea ice thermophysical properties. This study investigates the evolution of in situ and satellite-retrieved brightness temperature (T B ) throughout the melt season using a combination of in situ passive microwave measurements, thermophysical sampling, unmanned aerial vehicle (UAV) surveys, and satellite-retrieved T B . In situ data revealed a strong positive correlation between the presence of liquid water in the snow matrix and in situ T B in the 37 and 89 GHz frequencies. When considering T B ratios utilized by popular sea ice concentration algorithms (e.g., NASA Team 2), liquid water presence in the snow matrix was shown to increase the in situ T B gradient ratio of 37/19V. In situ gradient ratios of 89/19V and 89/19H were shown to correlate positively with UAV-derived melt pond coverage across the ice surface. Multi-scale comparison between in situ T B measurements and satellite-retrieved T B (by Advanced Microwave Scanning Radiometer 2) showed a distinct pattern of passive microwave T B signature at different stages of melt, confirmed by data from in situ thermophysical measurements. This pattern allowed for both in situ and satellite-retrieved T B to be partitioned into three discrete stages of sea ice melt: late spring, early melt and advanced melt. The results of this study thus advance the goal of achieving more accurate modeled predictions of the sea ice cover during the critical navigation and breakup period in Hudson Bay.

Massive phytoplankton blooms develop at the Arctic ice edge, sometimes extending far under the pack ice. An extensive culturing effort was conducted before and during a phytoplankton bloom in Baffin Bay between April and July 2016. Different isolation strategies were applied, including flow cytometry cell sorting, manual single cell pipetting, and serial dilution. Although all three techniques yielded the most common organisms, each technique retrieved specific taxa, highlighting the importance of using several methods to maximize the number and diversity of isolated strains. More than 1,000 cultures were obtained, characterized by 18S rRNA sequencing and optical microscopy, and de-replicated to a subset of 276 strains presented in this work. Strains grouped into 57 phylotypes defined by 100% 18S rRNA sequence similarity. These phylotypes spread across five divisions: Heterokontophyta, Chlorophyta, Cryptophyta, Haptophyta and Dinophyta. Diatoms were the most abundant group (193 strains), mostly represented by the genera Chaetoceros and Attheya . The genera Baffinella and Pyramimonas were the most abundant non-diatom nanoplankton strains, while Micromonas polaris dominated the picoplankton. Diversity at the class level was higher during the peak of the bloom. Potentially new species were isolated, in particular within the genera Navicula, Nitzschia, Coscinodiscus, Thalassiosira, Pyramimonas, Mantoniella and Isochrysis . Culturing efforts such as this one highlight the unexplored eukaryotic plankton diversity in the Arctic and provide a large number of strains for analyzing physiological and metabolic impacts in this changing environment.

Aquaculture, the fastest growing food sector, is expected to expand to produce an additional 30 million metric tons of fish by 2030, thus filling the gap in supplies of seafood for humans. Salmonids aquaculture exploits the vast majority of fishmeal and fish oil rendered from ocean-dwelling forage fish. Most forage fish diverted to these commodities are human-food grade, and all are primary prey for marine predators. Rising costs, price volatility, and environmental sustainability concerns of using these commodities for aquaculture feed are driving the global search for alternatives, including marine microalgae originating from the base of marine food webs but produced in culture. We report the first evaluation of two marine microalgae, Nannochloropsis sp. and Isochrysis sp., for their potential to fully replace fishmeal and fish oil in diets of rainbow trout ( Oncorhynchus mykiss ), an important model for all salmonid aquaculture. We conducted a digestibility experiment with dried whole cells of Nannochloropsis sp. and Isochrysis sp., followed by a growth experiment using feeds with different combinations of Nannochloropsis sp., Isochrysis sp., and Schizochytrium sp. We found that digestibilities of crude protein, crude lipid, amino acids, fatty acids, omega 3 polyunsaturated fatty acids (n3 PUFA), docosahexaenoic acid (DHA), n6 (omega 6) PUFA in Isochrysis sp. were significantly higher than those in Nannochloropsis sp. Digestibility results suggest that for rainbow trout diets Isochrysis sp. is a better substitute for fishmeal and fish oil than Nannochloropsis sp. The lower feed intake by fish fed diets combining multiple microalgae, compared to fish fed the reference diet, was a primary cause of the growth retardation. In trout fillets, we detected an equal amount of DHA in fish fed fish-free diet and reference diet. This study suggests that Isochrysis sp. and Schizochytrium sp. are good candidates for DHA supplementation in trout diet formulations.

Baffin Bay, located at the Arctic Ocean’s ‘doorstep’, is a heterogeneous environment where a warm and salty eastern current flows northwards in the opposite direction of a cold and relatively fresh Arctic current flowing along the west coast of the bay. This circulation affects the physical and biogeochemical environment on both sides of the bay. The phytoplanktonic species composition is driven by its environment and, in turn, shapes carbon transfer through the planktonic food web. This study aims at determining the effects of such contrasting environments on ecosystem structure and functioning and the consequences for the carbon cycle. Ecological indices calculated from food web flow values provide ecosystem properties that are not accessible by direct in situ measurement. From new biological data gathered during the Green Edge project, we built a planktonic food web model for each side of Baffin Bay, considering several biological processes involved in the carbon cycle, notably in the gravitational, lipid, and microbial carbon pumps. Missing flow values were estimated by linear inverse modeling. Calculated ecological network analysis indices revealed significant differences in the functioning of each ecosystem. The eastern Baffin Bay food web presents a more specialized food web that constrains carbon through specific and efficient pathways, leading to segregation of the microbial loop from the classical grazing chain. In contrast, the western food web showed redundant and shorter pathways that caused a higher carbon export, especially via lipid and microbial pumps, and thus promoted carbon sequestration. Moreover, indirect effects resulting from bottom-up and top-down control impacted pairwise relations between species differently and led to the dominance of mutualism in the eastern food web. These differences in pairwise relations affect the dynamics and evolution of each food web and thus might lead to contrasting responses to ongoing climate change.

To better understand the response of the western Arctic upper ocean to late summer ice-ocean interactions, a range of surface, interior, and basal sea ice conditions were simulated in a 1-D turbulent boundary layer model. In-ice and under-ice autonomous observations from the 2014 Marginal Ice Zone Experiment provided a complete characterization of the late melt-season sea ice and were used to set initial conditions, update boundary conditions, and conduct model validation studies. Results show that underestimates of open water and melt pond fraction at the sea ice surface had the largest influence on ocean-to-ice turbulent heat fluxes reducing basal melt rates by as much as 32%. This substantial reduction in latent heat loss was attributed to underestimates of open water areas and the exclusion of melt ponds by low-resolution synthetic aperture radar imagery. However, the greatest overall effect on the ice-ocean boundary layer came from mischaracterizations of basal roughness, with smooth ice scenarios resulting in 7 m of summer halocline shoaling and preservation of the near-surface temperature maximum. Rough ice conditions showed a 23% deepening of the mixed layer and erosion of heat storage above 40 m. Adjustments of conductive heat fluxes had little effect on the near-interface heat budget due to small internal thermal gradients within the late summer sea ice. Results from the 1-D boundary layer simulations highlight the most influential components of sea ice structure during late summer conditions and provide the magnitude of errors expected when ice conditions are mischaracterized.

Suspended particulate organic carbon (POC susp ) in the Gulf of Mexico is unique compared to other seas and oceans. In addition to surface primary production, isotopic analysis indicates that microbial cycling of oil and riverine inputs are primary sources of carbon to POC susp in the Gulf. To characterize POC susp from seep sites and non-seep north central Gulf (NCG) sites potentially affected by the Deepwater Horizon (DWH) spill, we analyzed 277 and 123 samples for δ 13 C and Δ 14 C signatures, respectively. Depth, partitioned into euphotic (<300 m) and deep (>300 m), was the main driver of spatial δ 13 C differences, with deep depths exhibiting 13 C depletion. Both deep depths and proximity to sources of natural seepage resulted in 14 C depletion. A two-endmember mixing model based on Δ 14 C indicated that sources to POC susp were 14–29% fossil carbon at NCG sites and 19–57% at seep sites, with the balance being modern surface production. A six-component Bayesian mixing model MixSIAR, using both 13 C and 14 C, suggested that riverine inputs were an important carbon source to POC susp contributing 34–46%. The influence of seeps was localized. Below the euphotic zone at seep sites, 46 ± 5% (n = 9) of the carbon in POC susp was derived from environmentally degraded, transformed oil; away from seeps, transformed oil contributed 15 ± 4% (n = 39). We hypothesized that, at NCG sites removed from hydrocarbon seep sources, isotopic signatures would be depleted following the spill and then shift towards background-like enriched values over time. At deep depths we observed decreasing Δ 14 C signatures in POC susp from 2010 to 2012, followed by isotopic enrichment from 2012 to 2014 and a subsequent recovery rate of 159‰ per year, consistent with this hypothesis and with biodegraded material from DWH hydrocarbons contributing to POC susp .

Studying the distribution of zooplankton in relation to their prey and predators is challenging, especially in situ . Recent developments in underwater imaging enable such fine-scale research. We deployed the Lightframe On-sight Keyspecies Investigation (LOKI) image profiler to study the fine-scale (1 m) vertical distribution of the copepods Calanus hyperboreus and C. glacialis in relation to the subsurface chlorophyll maximum (SCM) at the end of the grazing season in August in the North Water and Nares Strait (Canadian Arctic). The vertical distribution of both species was generally consistent with the predictions of the Predator Avoidance Hypothesis. In the absence of a significant SCM, both copepods remained at depth during the night. In the presence of a significant SCM, copepods remained at depth in daytime and a fraction of the population migrated in the SCM at night. All three profiles where the numerically dominant copepodite stages C4 and C5 of the two species grazed in the SCM at night presented the same intriguing pattern: the abundance of C. hyperboreus peaked in the core of the SCM while that of C. glacialis peaked just above and below the core SCM. These distributions of the same-stage congeners in the SCMs were significantly different. Lipid fullness of copepod individuals was significantly higher in C. hyperboreus in the core SCM than in C. glacialis above and below the core SCM. Foraging interference resulting in the exclusion from the core SCM of the smaller C. glacialis by the larger C. hyperboreus could explain this vertical partitioning of the actively grazing copepodite stages of the two species. Alternatively, specific preferences for microalgal and/or microzooplankton food hypothetically occupying different layers in the SCM could explain the observed partitioning. Investigating the observed fine-scale co-distributions further will enable researchers to better predict potential climate change effects on these important Arctic congeners.

The Arctic Ocean is particularly affected by climate change, with changes in sea ice cover expected to impact phytoplankton primary production. During the Green Edge expedition, the development of the late spring–early summer diatom bloom was studied in relation with the sea ice retreat by multiple transects across the marginal ice zone. Biogenic silica concentrations and uptake rates were measured. In addition, diatom assemblage structures and their associated carbon biomass were determined, along with taxon-specific contributions to total biogenic silica production using the fluorescent dye PDMPO. Results indicate that a diatom bloom developed in open waters close to the ice edge, following the alleviation of light limitation, and extended 20–30 km underneath the ice pack. This actively growing diatom bloom (up to 0.19 μmol Si L –1 d –1 ) was associated with high biogenic silica concentrations (up to 2.15 μmol L –1 ), and was dominated by colonial fast-growing centric ( Chaetoceros spp. and Thalassiosira spp.) and ribbon-forming pennate species ( Fragilariopsis spp./ Fossula arctica ). The bloom remained concentrated over the shallow Greenland shelf and slope, in Atlantic-influenced waters, and weakened as it moved westwards toward ice-free Pacific-influenced waters. The development resulted in a near depletion of all nutrients eastwards of the bay, which probably induced the formation of resting spores of Melosira arctica . In contrast, under the ice pack, nutrients had not yet been consumed. Biogenic silica and uptake rates were still low (respectively <0.5 μmol L –1 and <0.05 μmol L –1 d –1 ), although elevated specific Si uptake rates (up to 0.23 d –1 ) probably reflected early stages of the bloom. These diatoms were dominated by pennate species ( Pseudo-nitzschia spp., Ceratoneis closterium , and Fragilariopsis spp./ Fossula arctica ). This study can contribute to predictions of the future response of Arctic diatoms in the context of climate change.

In recent years, certain mono- and di-unsaturated highly branched isoprenoid (HBI) alkene biomarkers (i.e., IP 25 and HBI IIa) have emerged as useful proxies for sea ice in the Arctic and Antarctic, respectively. Despite the relatively large number of sea ice reconstructions based on IP 25 and HBI IIa, considerably fewer studies have addressed HBI variability in sea ice or in the underlying water column during a spring bloom and ice melt season. In this study, we quantified IP 25 and various other HBIs at high temporal and vertical resolution in sea ice and the underlying water column (suspended and sinking particulate organic matter) during a spring bloom/ice melt event in Baffin Bay (Canadian Arctic) as part of the Green Edge project. The IP 25 data are largely consistent with those reported from some previous studies, but also highlight: (i) the short-term variability in its production in sea ice; (ii) the release of ice algae with high sinking rates following a switch in sea ice conditions from hyper- to hyposaline within the study period; and (iii) the occurrence of an under-ice phytoplankton bloom. Outcomes from change-point analysis conducted on chlorophyll a and IP 25 , together with estimates of the percentage of ice algal organic carbon in the water column, also support some previous investigations. The co-occurrence of other di- and tri-unsaturated HBIs (including the pelagic biomarker HBI III) in sea ice are likely to have originated from the diatom Berkeleya rutilans and/or the Pleurosigma and Rhizosolenia genera, residing either within the sea ice matrix or on its underside. Although a possible sea ice source for HBIs such as HBI III may also impact the use of such HBIs as pelagic counterparts to IP 25 in the phytoplankton marker-IP 25 index, we suggest that the impact is likely to be small based on HBI distribution data.

Arctic sea ice is experiencing a shorter growth season and an earlier ice melt onset. The significance of spring microalgal blooms taking place prior to sea ice breakup is the subject of ongoing scientific debate. During the Green Edge project, unique time-series data were collected during two field campaigns held in spring 2015 and 2016, which documented for the first time the concomitant temporal evolution of the sea ice algal and phytoplankton blooms in and beneath the landfast sea ice in western Baffin Bay. Sea ice algal and phytoplankton blooms were negatively correlated and respectively reached 26 (6) and 152 (182) mg of chlorophyll a per m 2 in 2015 (2016). Here, we describe and compare the seasonal evolutions of a wide variety of physical forcings, particularly key components of the atmosphere–snow–ice–ocean system, that influenced microalgal growth during both years. Ice algal growth was observed under low-light conditions before the snow melt period and was much higher in 2015 due to less snowfall. By increasing light availability and water column stratification, the snow melt onset marked the initiation of the phytoplankton bloom and, concomitantly, the termination of the ice algal bloom. This study therefore underlines the major role of snow on the seasonal dynamics of microalgae in western Baffin Bay. The under-ice water column was dominated by Arctic Waters. Just before the sea ice broke up, phytoplankton had consumed most of the nutrients in the surface layer. A subsurface chlorophyll maximum appeared and deepened, favored by spring tide-induced mixing, reaching the best compromise between light and nutrient availability. This deepening evidenced the importance of upper ocean tidal dynamics for shaping vertical development of the under-ice phytoplankton bloom, a major biological event along the western coast of Baffin Bay, which reached similar magnitude to the offshore ice-edge bloom.

This paper presents the first empirical estimates of dimethyl sulfide (DMS) gas fluxes across permeable sea ice in the Arctic. DMS is known to act as a major potential source of aerosols that strongly influence the Earth’s radiative balance in remote marine regions during the ice-free season. Results from a sampling campaign, undertaken in 2015 between June 2 and June 28 in the ice-covered Western Baffin Bay, revealed the presence of high algal biomass in the bottom 0.1-m section of sea ice (21 to 380 µg Chl a L –1 ) combined with the presence of high DMS concentrations (212–840 nmol L –1 ). While ice algae acted as local sources of DMS in bottom sea ice, thermohaline changes within the brine network, from gravity drainage to vertical stabilization, exerted strong control on the distribution of DMS within the interior of the ice. We estimated both the mean DMS molecular diffusion coefficient in brine (5.2 × 10 –5 cm 2 s –1 ± 51% relative S.D., n = 10) and the mean bulk transport coefficient within sea ice (33 × 10 –5 cm 2 s –1 ± 41% relative S.D., n = 10). The estimated DMS fluxes ± S.D. from the bottom ice to the atmosphere ranged between 0.47 ± 0.08 µmol m –2 d –1 (n = 5, diffusion) and 0.40 ± 0.15 µmol m –2 d –1 (n = 5, bulk transport) during the vertically stable phase. These fluxes fall within the lower range of direct summer sea-to-air DMS fluxes reported in the Arctic. Our results indicate that upward transport of DMS, from the algal-rich bottom of first-year sea ice through the permeable sea ice, may represent an important pathway for this biogenic gas toward the atmosphere in ice-covered oceans in spring and summer.

Over the past three decades, marine resource management has shifted conceptually from top-down sectoral approaches towards the more systems-oriented multi-stakeholder frameworks of integrated coastal management and ecosystem-based conservation. However, the successful implementation of such frameworks is commonly hindered by a lack of cross-disciplinary knowledge transfer, especially between natural and social sciences. This review represents a holistic synthesis of three decades of change in the oceanography, biology and human dimension of False Bay, South Africa. The productivity of marine life in this bay and its close vicinity to the steadily growing metropolis of Cape Town have led to its socio-economic significance throughout history. Considerable research has highlighted shifts driven by climate change, human population growth, serial overfishing, and coastal development. Upwelling-inducing winds have increased in the region, leading to cooling and likely to nutrient enrichment of the bay. Subsequently the distributions of key components of the marine ecosystem have shifted eastward, including kelp, rock lobsters, seabirds, pelagic fish, and several alien invasive species. Increasing sea level and exposure to storm surges contribute to coastal erosion of the sandy shorelines in the bay, causing losses in coastal infrastructure and posing risk to coastal developments. Since the 1980s, the human population of Cape Town has doubled, and with it pollution has amplified. Overfishing has led to drastic declines in the catches of numerous commercially and recreationally targeted fish, and illegal fishing is widespread. The tourism value of the bay contributes substantially to the country’s economy, and whale watching, shark-cage diving and water sports have become important sources of revenue. Compliance with fisheries and environmental regulations would benefit from a systems-oriented approach whereby coastal systems are managed holistically, embracing both social and ecological goals. In this context, we synthesize knowledge and provide recommendations for multidisciplinary research and monitoring to achieve a better balance between developmental and environmental agendas.

Oceanic oil-degrading bacteria produce copious amounts of exopolymeric substances (EPS) that facilitate their access to oil. The fate of EPS in the water column is in part determined by activities of heterotrophic microbes capable of utilizing EPS compounds as carbon and energy sources. To evaluate the potential of natural microbial communities to degrade EPS produced during oil degradation, we measured potential hydrolysis rates of six structurally distinct polysaccharides in two roller bottle experiments, using water from a natural oil seep in the northern Gulf of Mexico. The suite of polysaccharides used to measure the initial step in carbon degradation is indicative of polymers within microbial EPS. The treatments included (i) unamended surface or deep waters (whole water), and water amended with (ii) a water-accommodated fraction of oil (WAF), (iii) oil dispersant Corexit 9500, and (iv) WAF chemically-enhanced with Corexit (CEWAF). The oil and Corexit treatments were employed to simulate conditions during the Deepwater Horizon oil spill. Polysaccharide hydrolysis rates in the surface-water treatments were lowest in the WAF treatment, despite elevated levels of EPS in the form of transparent exopolymer particles (TEP). In contrast, the three deep-water treatments (WAF, Corexit, CEWAF) showed enhanced hydrolysis rates and TEP levels (WAF) compared to the whole water. We also observed variations in the spectrum of polysaccharide-hydrolyzing enzyme activities among the treatments. These substrate specificities were likely driven by activities of oil-degrading bacteria, shaping the pool of EPS and TEP as well as degradation products of hydrocarbons and Corexit compounds. A model calculation of potential turnover rates of organic carbon within the TEP pool suggests extended residence times of TEP in oil-contaminated waters, making them prone to serve as the sticky matrix for oily aggregates known as marine oil snow.

The Arctic spring phytoplankton bloom has been reported to commence under a melting sea ice cover as transmission of photosynthetically active radiation (PAR; 400–700 nm) suddenly increases with the formation of surface melt ponds. Spatial variability in ice surface characteristics, i.e., snow thickness or melt pond distributions, and subsequent impact on transmitted PAR makes estimating light-limited primary production difficult during this time of year. Added to this difficulty is the interpretation of data from various sensor types, including hyperspectral, multispectral, and PAR-band irradiance sensors, with either cosine-corrected (planar) or spherical (scalar) sensor heads. To quantify the impact of the heterogeneous radiation field under sea ice, spectral irradiance profiles were collected beneath landfast sea ice during the Green Edge ice-camp campaigns in May–June 2015 and June–July 2016. Differences between PAR measurements are described using the downwelling average cosine, μ d , a measure of the degree of anisotropy of the downwelling underwater radiation field which, in practice, can be used to convert between downwelling scalar, E 0d , and planar, E d , irradiance. A significantly smaller μ d (PAR) was measured prior to snow melt compared to after (0.6 vs. 0.7) when melt ponds covered the ice surface. The impact of the average cosine on primary production estimates, shown in the calculation of depth-integrated daily production, was 16% larger under light-limiting conditions when E 0d was used instead of E d . Under light-saturating conditions, daily production was only 3% larger. Conversion of underwater irradiance data also plays a role in the ratio of total quanta to total energy (E Q /E W , found to be 4.25), which reflects the spectral shape of the under-ice light field. We use these observations to provide factors for converting irradiance measurements between irradiance detector types and units as a function of surface type and depth under sea ice, towards improving primary production estimates.

The vertical distribution and temporal changes in aggregate abundance and sizes were measured in the Ross Sea, Antarctica between 2002 and 2005 to acquire a more complete understanding of the mechanisms and rates of carbon export from the euphotic layer. Aggregate abundance was determined by photographic techniques, and water column parameters (temperature, salinity, fluorescence, transmissometry) were assessed from CTD profiles. During the first three years the numbers of aggregates increased seasonally, being much more abundant within the upper 200 m in late summer than in early summer from 50 to 100 m (12.5 L –1 in early summer vs. 42.9 L –1 in late summer). In Year 4 aggregate numbers were substantially greater than in other years, and average aggregate abundance was maximal in early rather than late summer (177 vs. 84.5 L –1 ), which we attributed to the maximum biomass and aggregate formation being reached earlier than in other years. The contribution of aggregate particulate organic carbon to the total particulate carbon pool was estimated to be 20%. Ghost colonies, collapsed colonies of the haptophyte Phaeocystis antarctica , were observed during late summer in Year 4, with maximum numbers in the upper 100 m of ca. 40 L –1 . Aggregate abundance, particulate organic carbon and ghost colonies all decreased exponentially with depth, and the rate of ghost colony disappearance suggested that their contribution to sedimentary input was small at the time of sampling. Bottom nepheloid layers were commonly observed in late summer in both transmissometer and aggregate data. Late summer nepheloid layers had fluorescent material within them, suggesting that the particles were likely generated during the same growing season. Longer studies encompassing the entire production season would be useful in further elucidating the role of these aggregates in the carbon cycle of these regions.

Sea ice algae are an important contributor of primary production in the Arctic ecosystem. Within the bottom-ice environment, access to nutrients from the underlying ocean is a major factor controlling production, phenology, and taxonomic composition of ice algae. Previous studies have demonstrated that tides and currents play an important role in driving the flux of nutrients to bottom-ice algal communities when biological demand during the spring bloom is high. In this study we investigate how surface currents under landfast first-year ice influence nutrient supply based on stoichiometric composition, algal chlorophyll a biomass and species composition during spring 2016, in Dease Strait, Nunavut. Stronger water dynamics over a shoaled and constricted strait dominated by tidal currents (tidal strait) supported turbulent flow more than 85% of the deployment duration in comparison to outside the tidal strait in an embayment where turbulent flow was only evidenced a small percentage (<15%) of the time. The system appeared to be nitrate-depleted with surface water concentrations averaging 1.3 μmol L –1 . Increased currents were correlated significantly with a decrease in ice thickness and an increase in ice algal chlorophyll a . Furthermore, pennate diatoms dominated the ice algal community abundance with greater contribution within the strait where currents were greatest. These observations all support the existence of a greater nutrient flux to the ice bottom where currents increased towards the center of the tidal strait, resulting in an increase of bottom ice chlorophyll a biomass by 5–7 times relative to that outside of the strait. Therefore, expanding beyond the long identified biological hotspots of open water polynyas, this paper presents the argument for newly identified hotspots in regions of strong sub-ice currents but persistent ice covers, so called “invisible polynyas”.