Improved correction for non-photochemical quenching of in situ chlorophyll fluorescence based on a synchronous irradiance profile

Increased sea ice melt as a driver of enhanced Arctic phytoplankton blooming

Phytoplankton primary production in the Arctic Ocean has been increasing over the last two decades. In 2019, a record spring bloom occurred in Fram Strait, characterized by a peak in chlorophyll that was reached weeks earlier than in other years and was larger than any previously recorded May bloom. Here, we consider the conditions that led to this event and examine drivers of spring phytoplankton blooms in Fram Strait using in situ, remote sensing, and data assimilation methods. From samples collected during the May 2019 bloom, we observe a direct relationship between sea ice meltwater in the upper water column and chlorophyll a pigment concentrations. We place the 2019 spring dynamics in context of the past 20 years, a period marked by rapid change in climatic conditions. Our findings suggest that increased advection of sea ice into the region and warmer surface temperatures led to a rise in meltwater input and stronger near-surface stratification. Over this time period, we identify large-scale spatial correlations in Fram Strait between increased chlorophyll a concentrations and increased freshwater flux from sea ice melt.

Biogenic carbon pool production maintains the Southern Ocean carbon sink

Through biological activity, marine dissolved inorganic carbon (DIC) is transformed into different types of biogenic carbon available for export to the ocean interior, including particulate organic carbon (POC), dissolved organic carbon (DOC), and particulate inorganic carbon (PIC). Each biogenic carbon pool has a different export efficiency that impacts the vertical ocean carbon gradient and drives natural air-sea carbon dioxide gas (CO2) exchange. In the Southern Ocean (SO), which presently accounts for ~40% of the anthropogenic ocean carbon sink, it is unclear how the production of each biogenic carbon pool contributes to the contemporary air-sea CO2 exchange. Based on 107 independent observations of the seasonal cycle from 63 biogeochemical profiling floats, we provide the basin-scale estimate of distinct biogenic carbon pool production. We find significant meridional variability with enhanced POC production in the subantarctic and polar Antarctic sectors and enhanced DOC production in the subtropical and sea-ice-dominated sectors. PIC production peaks between 47°S and 57°S near the "great calcite belt." Relative to an abiotic SO, organic carbon production enhances CO2 uptake by 2.80 ± 0.28 Pg C y-1, while PIC production diminishes CO2 uptake by 0.27 ± 0.21 Pg C y-1. Without organic carbon production, the SO would be a CO2 source to the atmosphere. Our findings emphasize the importance of DOC and PIC production, in addition to the well-recognized role of POC production, in shaping the influence of carbon export on air-sea CO2 exchange.

Seasonality of downward carbon export in the Pacific Southern Ocean revealed by multi-year robotic observations

At high latitudes, the biological carbon pump, which exports organic matter from the surface ocean to the interior, has been attributed to the gravitational sinking of particulate organic carbon. Conspicuous deficits in ocean carbon budgets challenge this as a sole particle export pathway. Recent model estimates revealed that particle injection pumps have a comparable downward flux of particulate organic carbon to the biological gravitational pump, but with different seasonality. To date, logistical constraints have prevented concomitant and extensive observations of these mechanisms. Here, using year-round robotic observations and recent advances in bio-optical signal analysis, we concurrently investigated the functioning of two particle injection pumps, the mixed layer and eddy subduction pumps, and the gravitational pump in Southern Ocean waters. By comparing three annual cycles in contrasting physical and biogeochemical environments, we show how physical forcing, phytoplankton phenology and particle characteristics influence the magnitude and seasonality of these export pathways, with implications for carbon sequestration efficiency over the annual cycle.

Multidecadal trend of increasing iron stress in Southern Ocean phytoplankton

Southern Ocean primary productivity is principally controlled by adjustments in light and iron limitation, but the spatial and temporal determinants of iron availability, accessibility, and demand are poorly constrained, which hinders accurate long-term projections. We present a multidecadal record of phytoplankton photophysiology between 1996 and 2022 from historical in situ datasets collected by Biogeochemical Argo (BGC-Argo) floats and ship-based platforms. We find a significant multidecadal trend in irradiance-normalized nonphotochemical quenching due to increasing iron stress, with concomitant declines in regional net primary production. The observed trend of increasing iron stress results from changing Southern Ocean mixed-layer physics as well as complex biological and chemical feedback that is indicative of important ongoing changes to the Southern Ocean carbon cycle.

Chlorophyll a estimation in lakes using multi-parameter sonde data

Algae blooms are of considerable concern in freshwater lakes and reservoirs worldwide. In-situ Chlorophyll a (Chl-a) fluorometers are widely used for rapid assessments of algae biomass. However, accurately converting Chl-a fluorescence to an equivalent concentration is challenging due to natural variations in the relationship as well as nonphotochemical quenching (NPQ) which occurs commonly in surface waters during daytime. This study is based on water quality data from a freshwater lake from October 2018 to December 2020. Initial analysis of sonde Chl-a fluorescence and laboratory extracted Chl-a concentrations shows that the two data sets exhibit a nonlinear relationship with positive correlation and significant errors. A bias correction method was next developed based on (1) concurrent sonde measurements of other water quality parameters (to account for nonlinearities) and (2) a bias correction approach for nonphotochemical quenching effects in surface waters. The new Chl-a model exhibits much improved accuracy, with a root mean square error (RMSE) less than 0.95 µg/L. The new method facilitates accurate Chl-a characterization in freshwater lakes and reservoirs based on readily obtainable in-situ fluorescence sonde measurements.

Deep Chlorophyll Maxima in the Global Ocean: Occurrences, Drivers and Characteristics

Stratified oceanic systems are characterized by the presence of a so-called Deep Chlorophyll a Maximum (DCM) not detectable by ocean color satellites. A DCM can either be a phytoplankton (carbon) biomass maximum (Deep Biomass Maximum, DBM), or the consequence of photoacclimation processes (Deep photoAcclimation Maximum, DAM) resulting in the increase of chlorophyll a per phytoplankton carbon. Even though these DCM (further qualified as either DBMs or DAMs) have long been studied, no global-scale assessment has yet been undertaken and large knowledge gaps still remain in relation to the environmental drivers responsible for their formation and maintenance. In order to investigate their spatial and temporal variability in the open ocean, we use a global data set acquired by more than 500 Biogeochemical-Argo floats given that DCMs can be detected from the comparative vertical distribution of chlorophyll a concentrations and particulate backscattering coefficients. Our findings show that the seasonal dynamics of the DCMs are clearly region-dependent. High-latitude environments are characterized by a low occurrence of intense DBMs, restricted to summer. Meanwhile, oligotrophic regions host permanent DAMs, occasionally replaced by DBMs in summer, while subequatorial waters are characterized by permanent DBMs benefiting from favorable conditions in terms of both light and nutrients. Overall, the appearance and depth of DCMs are primarily driven by light attenuation in the upper layer. Our present assessment of DCM occurrence and of environmental conditions prevailing in their development lay the basis for a better understanding and quantification of their role in carbon budgets (primary production and export).

Detection of Coccolithophore Blooms With BioGeoChemical-Argo Floats

Coccolithophores (calcifying phytoplankton) form extensive blooms in temperate and subpolar oceans as evidenced from ocean-color satellites. This study examines the potential to detect coccolithophore blooms with BioGeoChemical-Argo (BGC-Argo) floats, autonomous ocean profilers equipped with bio-optical and physicochemical sensors. We first matched float data to ocean-color satellite data of calcite concentration to select floats that sampled coccolithophore blooms. We identified two floats in the Southern Ocean, which measured the particulate beam attenuation coefficient (c p) in addition to two core BGC-Argo variables, Chlorophyll-a concentration ([Chl-a]) and the particle backscattering coefficient (b bp). We show that coccolithophore blooms can be identified from floats by distinctively high values of (1) the b bp/c p ratio, a proxy for the refractive index of suspended particles, and (2) the b bp/[Chl-a] ratio, measurable by any BGC-Argo float. The latter thus paves the way to global investigations of environmental control of coccolithophore blooms and their role in carbon export.

Development of a bio-optical model for the Barents Sea to quantitatively link glider and satellite observations

A bio-optical model for the Barents Sea is determined from a set of in situ observations of inherent optical properties (IOPs) and associated biogeochemical analyses. The bio-optical model provides a pathway to convert commonly measured parameters from glider-borne sensors (CTD, optical triplet sensor-chlorophyll and CDOM fluorescence, backscattering coefficients) to bulk spectral IOPs (absorption, attenuation and backscattering). IOPs derived from glider observations are subsequently used to estimate remote sensing reflectance spectra that compare well with coincident satellite observations, providing independent validation of the general applicability of the bio-optical model. Various challenges in the generation of a robust bio-optical model involving dealing with partial and limited quantity datasets and the interpretation of data from the optical triplet sensor are discussed. Establishing this quantitative link between glider-borne and satellite-borne data sources is an important step in integrating these data streams and has wide applicability for current and future integrated autonomous observation systems. This article is part of the theme issue 'The changing Arctic Ocean: consequences for biological communities, biogeochemical processes and ecosystem functioning'.

Deep chlorophyll maxima across a trophic state gradient: A case study in the Laurentian Great Lakes

Deep chlorophyll maxima (DCM) are common in stratified lakes and oceans, and phytoplankton growth within DCM often contributes significantly to total system production. Theory suggests that properties of DCM should be predictable by trophic state, with DCM becoming deeper, broader, and less productive with greater oligotrophy. However, rigorous tests of these expectations are lacking in freshwater systems. We use data generated by the U.S. EPA from 1996 to 2017, including in situ profile data for temperature, photosynthetically active radiation (PAR), chlorophyll, beam attenuation (c _p), and dissolved oxygen (DO), to investigate patterns in DCM across lakes and over time. We consider trophic state, 1% PAR depth (z _1%), thermal structure, and degree of photoacclimation as potential drivers of DCM characteristics. DCM depth and thickness generally increased while DCM chlorophyll concentration decreased with decreasing trophic state index (greater oligotrophy). The z _1% was a stronger predictor of DCM depth than thermal structure. DCM in meso-oligotrophic waters were closely aligned with maxima in c _p and DO saturation, suggesting they are autotrophically productive. However, the depths of these maxima diverged in ultra-oligotrophic waters, with DCM occurring deepest. This is likely a consequence of photoacclimation in high-transparency waters, where c _p can be a better proxy for phytoplankton biomass than chlorophyll. Our results are generally consistent with expectations from DCM theory, but they also identify specific gaps in our understanding of DCM in lakes, including the causes of multiple DCM, the importance of nutriclines, and the processes forming DCM at higher light levels than expected.

Arctic mid-winter phytoplankton growth revealed by autonomous profilers

It is widely believed that during winter and spring, Arctic marine phytoplankton cannot grow until sea ice and snow cover start melting and transmit sufficient irradiance, but there is little observational evidence for that paradigm. To explore the life of phytoplankton during and after the polar night, we used robotic ice-avoiding profiling floats to measure ocean optics and phytoplankton characteristics continuously through two annual cycles in Baffin Bay, an Arctic sea that is covered by ice for 7 months a year. We demonstrate that net phytoplankton growth occurred even under 100% ice cover as early as February and that it resulted at least partly from photosynthesis. This highlights the adaptation of Arctic phytoplankton to extreme low-light conditions, which may be key to their survival before seeding the spring bloom.

Evaluation of Ocean Color Remote Sensing Algorithms for Diffuse Attenuation Coefficients and Optical Depths with Data Collected on BGC-Argo Floats

The vertical distribution of irradiance in the ocean is a key input to quantify processes spanning from radiative warming, photosynthesis to photo-oxidation. Here we use a novel dataset of thousands local-noon downwelling irradiance at 490 nm (Ed(490)) and photosynthetically available radiation (PAR) profiles captured by 103 BGC-Argo floats spanning three years (from October 2012 to January 2016) in the world’s ocean, to evaluate several published algorithms and satellite products related to diffuse attenuation coefficient (Kd). Our results show: (1) MODIS-Aqua Kd(490) products derived from a blue-to-green algorithm and two semi-analytical algorithms show good consistency with the float-observed values, but the Chla-based one has overestimation in oligotrophic waters; (2) The Kd(PAR) model based on the Inherent Optical Properties (IOPs) performs well not only at sea-surface but also at depth, except for the oligotrophic waters where Kd(PAR) is underestimated below two penetration depth (2zpd), due to the model’s assumption of a homogeneous distribution of IOPs in the water column which is not true in most oligotrophic waters with deep chlorophyll-a maxima; (3) In addition, published algorithms for the 1% euphotic-layer depth and the depth of 0.415 mol photons m−2 d−1 isolume are evaluated. Algorithms based on Chla generally work well while IOPs-based ones exhibit an overestimation issue in stratified and oligotrophic waters, due to the underestimation of Kd(PAR) at depth.

Observing the Global Ocean with Biogeochemical-Argo

Biogeochemical-Argo (BGC-Argo) is a network of profiling floats carrying sensors that enable observation of as many as six essential biogeochemical and bio-optical variables: oxygen, nitrate, pH, chlorophyll a, suspended particles, and downwelling irradiance. This sensor network represents today's most promising strategy for collecting temporally and vertically resolved observations of biogeochemical properties throughout the ocean. All data are freely available within 24 hours of transmission. These data fill large gaps in ocean-observing systems and support three ambitions: gaining a better understanding of biogeochemical processes (e.g., the biological carbon pump and air-sea CO₂ exchanges) and evaluating ongoing changes resulting from increasing anthropogenic pressure (e.g., acidification and deoxygenation); managing the ocean (e.g., improving the global carbon budget and developing sustainable fisheries); and carrying out exploration for potential discoveries. The BGC-Argo network has already delivered extensive high-quality global data sets that have resulted in unique scientific outcomes from regional to global scales. With the proposed expansion of BGC-Argo in the near future, this network has the potential to become a pivotal observation system that links satellite and ship-based observations in a transformative manner.

Evaluating tropical phytoplankton phenology metrics using contemporary tools

The timing of phytoplankton growth (phenology) in tropical oceans is a crucial factor influencing the survival rates of higher trophic levels, food web structure and the functioning of coral reef ecosystems. Phytoplankton phenology is thus categorised as an 'ecosystem indicator', which can be utilised to assess ecosystem health in response to environmental and climatic perturbations. Ocean-colour remote sensing is currently the only technique providing global, long-term, synoptic estimates of phenology. However, due to limited available in situ datasets, studies dedicated to the validation of satellite-derived phenology metrics are sparse. The recent development of autonomous oceanographic observation platforms provides an opportunity to bridge this gap. Here, we use satellite-derived surface chlorophyll-a (Chl-a) observations, in conjunction with a Biogeochemical-Argo dataset, to assess the capability of remote sensing to estimate phytoplankton phenology metrics in the northern Red Sea - a typical tropical marine ecosystem. We find that phenology metrics derived from both contemporary platforms match with a high degree of precision (within the same 5-day period). The remotely-sensed surface signatures reflect the overall water column dynamics and successfully capture Chl-a variability related to convective mixing. Our findings offer important insights into the capability of remote sensing for monitoring food availability in tropical marine ecosystems, and support the use of satellite-derived phenology as an ecosystem indicator for marine management strategies in regions with limited data availability.