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The Southern Ocean (SO) is highly sensitive to climate change. Therefore, an accurate estimate of phytoplankton biomass is key to being able to predict the climate trajectory of the 21st century. In this study, MODerate resolution Imaging Spectroradiometer (MODIS), on board EOS Aqua spacecraft, Level 2 (nominal 1 km × 1 km resolution) chlorophyll-a (C S a t ) and Particulate Organic Carbon (POC s a t ) products are evaluated by comparison with an in situ dataset from 11 research cruises (2008–2017) to the SO, across multiple seasons, which includes measurements of POC and chlorophyll-a (C i n s i t u ) from both High Performance Liquid Chromatography (C H P L C ) and fluorometry (C F l u o ). Contrary to a number of previous studies, results highlighted good performance of the algorithm in the SO when comparing estimations with HPLC measurements. Using a time window of ±12 h and a mean satellite chlorophyll from a 5 × 5 pixel box centered on the in situ location, the median C S a t :C i n s i t u ratios were 0.89 (N = 46) and 0.49 (N = 73) for C H P L C and C F l u o respectively. Differences between C H P L C and C F l u o were associated with the presence of diatoms containing chlorophyll-c pigments, which induced an overestimation of chlorophyll-a when measured fluorometrically due to a potential overlap of the chlorophyll-a and chlorophyll-c emission spectra. An underestimation of ∼0.13 mg m − 3 was observed for the global POC algorithm. This error was likely due to an overestimate of in situ POC i n s i t u measurements from the impact of dissolved organic carbon not accounted for in the blank correction. These results highlight the important implications of different in situ methodologies when validating ocean colour products.

Marine net primary production supports critical ecosystem services and the carbon cycle. However, the lack of consensus in the direction and magnitude of projected change in net primary production from models undermines efforts to assess climate impacts on marine ecosystems with confidence. Here we use contemporary remote sensing net primary production trends (1998–2023) from six remote sensing algorithms to discriminate amongst fifteen divergent model projections. A model ranking scheme, based on the similarity of linear responses of net primary production to changes in sea surface temperature, chlorophyll- a and the mixed layer, finds that future declines in net primary production are more likely than presently predicted. Even the best ranking models still underestimate the sensitivity of declines in net primary production to ocean warming, suggesting shortcomings remain. Reproducing this greater temperature sensitivity may lead to even larger declines in future net primary production than presently considered for impact assessment. Earth system models underestimate the decline in net primary productivity associated with ocean warming, meaning future net primary productivity decline is more likely than currently estimated, according to a ranking of Earth system models using remote sensing data.

Phytoplankton blooms in the Southern Ocean (SO) are seasonally limited by light and micronutrients. As such, regional variations in iron supply from mixed‐layer winter entrainment are expected to impact the extent of seasonal iron limitation. Here, we determined seasonal iron limitation in the Atlantic SO by conducting iron addition incubation experiments during winter, prior to the maximum mixed‐layer deepening, and in spring, prior to the peak of the summer bloom. Both the polar and subantarctic zones displayed evidence of iron limitation in spring, based on increased photosynthetic efficiency, with evidence of the subantarctic zone being limited in winter. In contrast, there was no evidence of limitation in either season in the sub‐tropical and Antarctic zones. The large degree of zonal variability in the timing of iron supply resulting from winter entrainment impacts the seasonal characteristics of iron limitation, phytoplankton physiology and the potential for growth.

Climate change is expected to elicit widespread alterations to nutrient and light supply, which interact to influence phytoplankton growth and their seasonal cycles. Using 25 years of satellite chlorophyll a data, we show that large regions of the Southern Ocean express significant multi-decadal trends in phenological indices that are typically larger (<50 days decade–1) than previously reported in modelling studies (<10 days decade–1). Although regionally dependent, there is an overall tendency for phytoplankton blooms to increase in amplitude, decline in seasonality, initiate later, terminate earlier and have shorter durations, except in the ice, which initiate earlier and have longer durations. Investigating relationships with prominent climate drivers highlights regional sensitivities and complexities of multiple interacting aspects of a changing climate. Seasonal adjustments of this magnitude at the base of the food web can de-synchronize energy transfer to higher trophic levels, threatening ecosystem services and impacting global climate by altering natural CO2 uptake.Using 25 years of satellite chlorophyll a data, the authors demonstrate significant and widespread changes in the amplitude, timing, duration and seasonality of Southern Ocean phytoplankton blooms. Such changes threaten ecosystem services and can impact global climate by altering natural CO2 uptake.

The high-latitude North Atlantic (HLNA) is characterized by a marked seasonal phytoplankton bloom, which removes the majority of surface macronutrients. However, incomplete nitrate depletion is frequently observed during summer in the region, potentially reflecting the seasonal development of an iron (Fe) limited phytoplankton community. In order to investigate the seasonal development and spatial extent of iron stress in the HLNA, nutrient addition experiments were performed during the spring (May) and late summer (July and August) of 2010. Grow-out experiments (48–120 h) confirmed the potential for iron limitation in the region. Short-term (24 h) incubations further enabled high spatial coverage and mapping of phytoplankton physiological responses to iron addition. The difference in the apparent maximal photochemical yield of photosystem II (PSII) (Fv:Fm) between nutrient (iron) amended and control treatments (Δ(Fv:Fm)) was used as a measure of the relative degree of iron stress. The combined observations indicated variability in the seasonal cycle of iron stress between different regions of the Irminger and Iceland Basins of the HLNA, related to the timing of the annual bloom cycle in contrasting biogeochemical provinces. Phytoplankton iron stress developed during the transition from the prebloom to peak bloom conditions in the HLNA and was more severe for larger cells. Subsequently, iron stress was reduced in regions where macronutrients were depleted following the bloom. Iron availability plays a significant role in the biogeochemistry of the HLNA, potentially lowering the efficiency of one of the strongest biological carbon pumps in the ocean.

Knowing the magnitude and timing of pelagic primary production is important for ecosystem and carbon sequestration studies, in addition to providing basic understanding of phytoplankton functioning. In this study we use data from an ecosystem cruise to Kong Håkon VII Hav, in the Atlantic sector of the Southern Ocean, in March 2019 and more than two decades of satellite-derived ocean color to study phytoplankton bloom phenology. During the cruise we observed phytoplankton blooms in different bloom phases. By correlating bloom phenology indices (i.e., bloom initiation and end) based on satellite remote sensing to the timing of changes in environmental conditions (i.e., sea ice, light, and mixed layer depth) we studied the environmental factors that seemingly drive phytoplankton blooms in the area. Our results show that blooms mainly take place in January and February, consistent with previous studies that include the area. Sea ice retreat controls the bloom initiation in particular along the coast and the western part of the study area, whereas bloom end is not primarily connected to sea ice advance. Light availability in general is not appearing to control the bloom termination, neither is nutrient availability based on the autumn cruise where we observed non-depleted macronutrient reservoirs in the surface. Instead, we surmise that zooplankton grazing plays a potentially large role to end the bloom, and thus controls its duration. The spatial correlation of the highest bloom magnitude with marked topographic features indicate that the interaction of ocean currents with sea floor topography enhances primary productivity in this area, probably by natural fertilization. Based on the bloom timing and magnitude patterns, we identified five different bloom regimes in the area. A more detailed understanding of the region will help to highlight areas with the highest relevance for the carbon cycle, the marine ecosystem and spatial management. With this gained understanding of bloom phenology, it will also be possible to study potential shifts in bloom timing and associated trophic mismatch caused by environmental changes.

Phytoplankton photosynthetic physiology can be investigated through single-turnover variable chlorophyll fluorescence (ST-ChlF) approaches, which carry unique potential to autonomously collect data at high spatial and temporal resolution. Over the past decades, significant progress has been made in the development and application of ST-ChlF methods in aquatic ecosystems, and in the interpretation of the resulting observations. At the same time, however, an increasing number of sensor types, sampling protocols, and data processing algorithms have created confusion and uncertainty among potential users, with a growing divergence of practice among different research groups. In this review, we assist the existing and upcoming user community by providing an overview of current approaches and consensus recommendations for the use of ST-ChlF measurements to examine in-situ phytoplankton productivity and photo-physiology. We argue that a consistency of practice and adherence to basic operational and quality control standards is critical to ensuring data inter-comparability. Large datasets of inter-comparable and globally coherent ST-ChlF observations hold the potential to reveal large-scale patterns and trends in phytoplankton photo-physiology, photosynthetic rates and bottom-up controls on primary productivity. As such, they hold great potential to provide invaluable physiological observations on the scales relevant for the development and validation of ecosystem models and remote sensing algorithms.

Chlorophyll fluorescence, primarily used to derive phytoplankton biomass, has long been an underutilized source of information on phytoplankton physiology. Diel fluctuations in chlorophyll fluorescence are affected by both photosynthetic efficiency and non-photochemical quenching (NPQ), where NPQ is a decrease in fluorescence through the dissipation of excess energy as heat. NPQ variability is linked to iron and light availability, and has the potential to provide important diagnostic information on phytoplankton physiology. Here we establish a relationship between NPQsv (Stern-Volmer NPQ) and indices of iron limitation from nutrient addition experiments in the sub-Antarctic zone (SAZ) of the Atlantic Southern Ocean, through the derivation of NPQmax (the maximum NPQsv value) and αNPQ (the light limited slope of NPQsv). Significant differences were found for both Fv/Fm and αNPQ for iron versus control treatments, with no significant differences for NPQmax. Similar results from CTDs indicated that changes in NPQ were driven by increasing light availability from late July to December, but by both iron and light from January to February. We propose here that variability in αNPQ, which has removed the effect of light availability, can potentially be used as a proxy for iron limitation (as shown here for the Atlantic SAZ), with higher values being associated with greater iron stress. This approach was transferred to data from a buoyancy glider deployment at the same location by utilising the degree of fluorescence quenching as a proxy for NPQGlider, which was plotted against in situ light to determine αNPQ. Seasonal increases in αNPQ are consistent with increased light availability, shoaling of the mixed layer depth (MLD) and anticipated seasonal iron limitation. The transition from winter to summer, when positive net heat flux dominates stratification, was coincident with a 24% increase in αNPQ variability and a switch in the dominant driver from incident PAR to MLD. The dominant scales of αNPQ variability are consistent with fine scale variability in MLD and a significant positive relationship was observed between these two at a ~10 day window. The results emphasise the important role of fine scale dynamics in driving iron supply, particularly in summer when this micronutrient is limiting.

The uptake and application of single turnover chlorophyll fluorometers to the study of phytoplankton ecosystem status and microbial functions has grown considerably in the last two decades. However, standardization of measurement protocols, processing of fluorescence transients and quality control of derived photosynthetic parameters is still lacking and makes community goals of large global databases of high-quality data unrealistic. We introduce the Python package Phytoplankton Photophysiology Utilities (PPU), an adaptable and open-source interface between Fast Repetition Rate and Fluorescence Induction and Relaxation instruments and python. The PPU package includes a variety of functions for the loading, processing and quality control of single turnover fluorescence transients from many commercially available instruments. PPU provides the user with greater flexibility in the application of the Kolber-Prasil-Falkowski model; tools for plotting, quality control, correcting instrument biases and high-throughput processing with ease; and a greater appreciation for the uncertainties in derived photosynthetic parameters. Using data from three research cruises across different biogeochemical regimes, we provide example applications of PPU to fit raw active chlorophyll-a fluorescence data from three commercial instruments and demonstrate tools which help to reduce uncertainties in the final fitted parameters.

Underwater gliders have become widely used in the last decade. This has led to a proliferation of data and the concomitant development of tools to process the data. These tools are focused primarily on converting the data from its raw form to more accessible formats and often rely on proprietary programming languages. This has left a gap in the processing chain for glider data, specifically academics, who often need to perform secondary quality control, calibrate, correct, interpolate and visualise data. Here, we present GliderTools, an open-source Python package that addresses these needs of the glider user community. The tool is designed to change the focus from the processing to the data. In this paper, we present a set of tools, that includes: secondary cleaning and calibration, calibration procedures for bottle samples, fluorescence quenching correction, photosynthetically available radiation corrections and data interpolation in the vertical and horizontal dimensions. Many of these processes have been described in several other studies, but do not exist in a collated package designed for underwater glider data. Importantly, we provide potential users with guidelines on how these tools are used so that they can be easily and rapidly accessible to a wide range of users that span the student to the experienced researcher. We recognise that this package may not be all-encompassing for every user and we thus welcome community contributions and promote GliderTools as a community-driven project for scientists.