Artificial Upwelling in Singular and Recurring Mode: Consequences for Net Community Production and Metabolic Balance

Artificial upwelling of nutrient-rich waters and the corresponding boost in primary productivity harbor the potential to enhance marine fishery yields and strengthen the biological pump for sequestration of atmospheric CO2. There is increasing urgency to understand this technology as a “ocean-based solution” for counteracting two major challenges of the 21st century—climate change and overfishing. Yet, little is known about the actual efficacy and/or possible side effects of artificial upwelling. We conducted a large-scale off-shore mesocosm study (∼44 m3) in the oligotrophic waters of the Canary Islands to identify the community-level effects of artificial upwelling on a natural oligotrophic plankton community. Four upwelling intensities were simulated (approx. 1.5/3/5.7/10 μmol L–1 of nitrate plus phosphate and silicate) via two different upwelling modes (a singular deep-water pulse vs. recurring supply every 4 days) for 37 days. Here we present results on the response of net community production (NCP), metabolic balance and phytoplankton community composition (<250 μm). Higher upwelling intensities yielded higher cumulative NCP. Following upwelling onset, the phytoplankton community became dominated by diatoms in all treatments, but other taxa such as Coccolithophores increased later in the experiment. The magnitude of effects on the metabolic balance scaled with the amount of added deep water, leading to (i) a balanced to net-heterotrophic system in the singular and (ii) a net-autotrophic system in the recurring upwelling treatments. Accordingly, the mode in which nutrients are supplied to an oligotrophic system plays a crucial role in the ecosystem response, with recurring upwelling leading to higher long-term positive NCP than singular upwelling. These results highlight the importance of empirically measured local responses to upwelling such as community structure and metabolism, with major implications for the potential employment of artificial upwelling as an ocean-based solution to generate (primary) production.

Derivation of seawater <i>p</i>CO₂ from net community production identifies the South Atlantic Ocean as a CO₂ source

A key step in assessing the global carbon budget is the determination of the partial pressure of CO2 in seawater (pCO2 (sw)). Spatially complete observational fields of pCO2 (sw) are routinely produced for regional and global ocean carbon budget assessments by extrapolating sparse in situ measurements of pCO2 (sw) using satellite observations. As part of this process, satellite chlorophyll a (Chl a) is often used as a proxy for the biological drawdown or release of CO2. Chl a does not, however, quantify carbon fixed through photosynthesis and then respired, which is determined by net community production (NCP). In this study, pCO2 (sw) over the South Atlantic Ocean is estimated using a feed forward neural network (FNN) scheme and either satellite-derived NCP, net primary production (NPP) or Chl a to compare which biological proxy produces the most accurate fields of pCO2 (sw). Estimates of pCO2 (sw) using NCP, NPP or Chl a were similar, but NCP was more accurate for the Amazon Plume and upwelling regions, which were not fully reproduced when using Chl a or NPP. A perturbation analysis assessed the potential maximum reduction in pCO2 (sw) uncertainties that could be achieved by reducing the uncertainties in the satellite biological parameters. This illustrated further improvement using NCP compared to NPP or Chl a. Using NCP to estimate pCO2 (sw) showed that the South Atlantic Ocean is a CO2 source, whereas if no biological parameters are used in the FNN (following existing annual carbon assessments), this region appears to be a sink for CO2. These results highlight that using NCP improved the accuracy of estimating pCO2 (sw) and changes the South Atlantic Ocean from a CO2 sink to a source. Reducing the uncertainties in NCP derived from satellite parameters will ultimately improve our understanding and confidence in quantification of the global ocean as a CO2 sink.

Simultaneous assessment of oxygen- and nitrate-based net community production in a temperate shelf sea from a single ocean glider

The continental shelf seas are important at a global scale for ecosystem services. These highly dynamic regions are under a wide range of stresses, and as such future management requires appropriate monitoring measures. A key metric to understanding and predicting future change are the rates of biological production. We present here the use of an autonomous underwater glider with an oxygen (O2) and a wet-chemical microfluidic total oxidised nitrogen (NOx-=NO3-+NO2-) sensor during a spring bloom as part of a 2019 pilot autonomous shelf sea monitoring study. We find exceptionally high rates of net community production using both O2 and NOx- water column inventory changes, corrected for air–sea gas exchange in case of O2. We compare these rates with 2007 and 2008 mooring observations finding similar rates of NOx- consumption. With these complementary methods we determine the O2:N amount ratio of the newly produced organic matter (7.8 ± 0.4) and the overall O2:N ratio for the total water column (5.7 ± 0.4). The former is close to the canonical Redfield O2:N ratio of 8.6 ± 1.0, whereas the latter may be explained by a combination of new organic matter production and preferential remineralisation of more reduced organic matter at a higher O2:N ratio below the euphotic zone.

Cyanobacteria net community production in the Baltic Sea as inferred from profiling <i>p</i>CO₂ measurements

Organic matter production by cyanobacteria blooms is a major environmental concern for the Baltic Sea, as it promotes the spread of anoxic zones. Partial pressure of carbon dioxide (pCO2) measurements carried out on Ships of Opportunity (SOOP) since 2003 have proven to be a powerful tool to resolve the carbon dynamics of the blooms in space and time. However, SOOP measurements lack the possibility to directly constrain depth-integrated net community production (NCP) in moles of carbon per surface area due to their restriction to the sea surface. This study tackles the knowledge gap through (1) providing an NCP best guess for an individual cyanobacteria bloom based on repeated profiling measurements of pCO2 and (2) establishing an algorithm to accurately reconstruct depth-integrated NCP from surface pCO2 observations in combination with modelled temperature profiles. Goal (1) was achieved by deploying state-of-the-art sensor technology from a small-scale sailing vessel. The low-cost and flexible platform enabled observations covering an entire bloom event that occurred in July–August 2018 in the Eastern Gotland Sea. For the biogeochemical interpretation, recorded pCO2 profiles were converted to CT*, which is the dissolved inorganic carbon concentration normalised to alkalinity. We found that the investigated bloom event was dominated by Nodularia and had many biogeochemical characteristics in common with blooms in previous years. In particular, it lasted for about 3 weeks, caused a CT* drawdown of 90 µmol kg−1, and was accompanied by a sea surface temperature increase of 10 ∘C. The novel finding of this study is the vertical extension of the CT* drawdown up to the compensation depth located at around 12 m. Integration of the CT* drawdown across this depth and correction for vertical fluxes leads to an NCP best guess of ∼1.2 mol m−2 over the productive period. Addressing goal (2), we combined modelled hydrographical profiles with surface pCO2 observations recorded by SOOP Finnmaid within the study area. Introducing the temperature penetration depth (TPD) as a new parameter to integrate SOOP observations across depth, we achieve an NCP reconstruction that agrees to the best guess within 10 %, which is considerably better than the reconstruction based on a classical mixed-layer depth constraint. Applying the TPD approach to almost 2 decades of surface pCO2 observations available for the Baltic Sea bears the potential to provide new insights into the control and long-term trends of cyanobacteria NCP. This understanding is key for an effective design and monitoring of conservation measures aiming at a Good Environmental Status of the Baltic Sea.

Decline in plankton diversity and carbon flux with reduced sea ice extent along the Western Antarctic Peninsula

Since the middle of the past century, the Western Antarctic Peninsula has warmed rapidly with a significant loss of sea ice but the impacts on plankton biodiversity and carbon cycling remain an open question. Here, using a 5-year dataset of eukaryotic plankton DNA metabarcoding, we assess changes in biodiversity and net community production in this region. Our results show that sea-ice extent is a dominant factor influencing eukaryotic plankton community composition, biodiversity, and net community production. Species richness and evenness decline with an increase in sea surface temperature (SST). In regions with low SST and shallow mixed layers, the community was dominated by a diverse assemblage of diatoms and dinoflagellates. Conversely, less diverse plankton assemblages were observed in waters with higher SST and/or deep mixed layers when sea ice extent was lower. A genetic programming machine-learning model explained up to 80% of the net community production variability at the Western Antarctic Peninsula. Among the biological explanatory variables, the sea-ice environment associated plankton assemblage is the best predictor of net community production. We conclude that eukaryotic plankton diversity and carbon cycling at the Western Antarctic Peninsula are strongly linked to sea-ice conditions.

Derivation of seawater pCO₂ from net community production identifies the South Atlantic Ocean as a CO₂ source

A key step in assessing the global carbon budget is the determination of the partial pressure of CO2 in seawater (pCO2 (sw)). Spatially complete observational fields of pCO2 (sw) are routinely produced for regional and global ocean carbon budget assessments by extrapolating sparse in situ measurements of pCO2 (sw) using satellite observations. Within these schemes, satellite chlorophyll a (Chl a) is often used as a proxy for the biological drawdown or release of CO2. Chl a does not however quantify carbon fixed through photosynthesis and then respired, which is determined by net community production (NCP). In this study, pCO2 (sw) over the South Atlantic Ocean is estimated using a feed forward neural network (FNN) scheme and either satellite derived NCP, net primary production (NPP) or Chl a to compare which biological proxy is the most accurate. Estimates of pCO2 (sw) using NCP, NPP or Chl a were similar, but NCP was more accurate for the Amazon Plume and upwelling regions, which were not fully reproduced when using Chl a or NPP. Reducing the uncertainties in the satellite biological parameters to estimate pCO2 (sw), illustrated further improvement and greater differences for NCP compared to NPP or Chl a. Using NCP to estimate pCO2 (sw) showed that the South Atlantic Ocean is a CO2 source, whereas if no biological parameters are used in the FNN (following existing annual carbon assessments), this region becomes a sink for CO2. These results highlight that using NCP improved the accuracy of estimating pCO2 (sw), and changes the South Atlantic Ocean from a CO2 sink to a source. Reducing the uncertainties in NCP derived from satellite parameters will further improve our ability to quantify the global ocean CO2 sink.

ΔO2/N2′ as a New Tracer of Marine Net Community Production: Application and Evaluation in the Subarctic Northeast Pacific and Canadian Arctic Ocean

We compared field measurements of the biological O2 saturation anomalies, ΔO2/Ar and ΔO2/N2, from simultaneous oceanographic deployments of a membrane inlet mass spectrometer and optode/gas tension device (GTD). Data from the Subarctic Northeast Pacific and Canadian Arctic Ocean were used to evaluate ΔO2/N2 as an alternative to ΔO2/Ar for estimates of mixed layer net community production (NCP). We observed strong spatial coherence between ΔO2/Ar and ΔO2/N2, with small offsets resulting from differences in the solubility properties of Ar and N2 and their sensitivity to vertical mixing fluxes. Larger offsets between the two tracers were observed across hydrographic fronts and under elevated sea states, resulting from the differential time-response of the optode and GTD, and from bubble dissolution in the ship’s seawater lines. We used a simple numerical framework to correct for physical sources of divergence between N2 and Ar, deriving the tracer ΔO2/N2′. Over most of our survey regions, ΔO2/N2′ provided a better analog for ΔO2/Ar, and thus more accurate NCP estimates than ΔO2/N2. However, in coastal Arctic waters, ΔO2/N2 and ΔO2/N2′ performed equally well as NCP tracers. On average, mixed layer NCP estimated from ΔO2/Ar and ΔO2/N2′ agreed to within ∼2 mmol O2 m–2 d–1, with offsets typically smaller than other errors in NCP calculations. Our results demonstrate a significant potential to derive NCP from underway O2/N2 measurements across various oceanic regions. Optode/GTD systems could replace mass spectrometers for autonomous NCP derivation under many oceanographic conditions, thereby presenting opportunities to significantly expand global NCP coverage from various underway platforms.