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The ecology of the biological carbon pump

Posted by mmaheigan

· Tuesday, October 15th, 2019

Plankton in the surface ocean convert CO₂ into organic biomass thereby fueling marine food webs. Part of this organic biomass sinks down into the deep ocean, where the surface-derived organic carbon, or respired CO₂, is locked in for decades to millennia. Without the biological carbon pump, atmospheric CO₂ would be ~200 ppm higher than it is today. We know that ecological processes in the surface ocean plankton communities have a paramount importance on the efficiency of the biological carbon pump. Unfortunately, however, the mechanisms how ecology determines sinking fluxes are poorly understood.

A recent study in Global Biogeochemical Cycles used large-scale in situ mesocosms to explore how the ecological interplay within plankton communities affects the downward flux of organic material. Organic biomass tends to sink faster when produced by smaller organisms because the sinking material they generate forms dense aggregates. Conversely, larger organisms produce relatively porous particles that sink more slowly.

Figure: Flow chart illustrating how plankton community structure affects the properties of sinking organic particles and ultimately the strength and efficiency of the biological carbon pump. The thick arrows at the bottom indicate that flux attenuation depends on the properties of particulate matter formed in the surface ocean. For example, slow-sinking porous aggregates containing large amounts of easily degradable organic substances will decay faster (right side) than dense aggregates of more refractory organic matter (left side).

The key finding of this study was the unexpectedly large influence that plankton community composition has on the degradation rate of sinking organic biomass. In fact, degradation rates changed maximally 15-fold over the course of the study while sinking speed changed only 3-fold. Degradation rate of sinking material, measured in oxygen consumption assays, was quite variable and tended to be higher for more easily degradable fresh organic matter. The rate was lower during harmful algal blooms, which produce toxic substances that inhibit organisms that feed on aggregates thereby reducing degradation rates. These findings are an important step forward as they show that our predictive understanding of the biological carbon pump could be improved substantially when linking degradation rates of sinking material with ecological processes in surface ocean plankton communities.

Authors:
L. T. Bach (University of Tasmania)
P. Stange, J. Taucher, E. P. Achterberg, M. Esposito, U. Riebesell (GEOMAR)
M. Algueró‐Muñiz (Alfred-Wegener-Institut Helmholtz)
H. Horn (NIOZ and Utrecht University)

Upwelling and solubility drive global surface dissolved inorganic carbon (DIC) distribution

Posted by mmaheigan

· Tuesday, August 20th, 2019

What drives the latitudinal gradient in open-ocean surface DIC concentration? Understanding the processes that drive the distribution of carbon in the surface ocean is essential to the study of the ocean carbon cycle and future predictions of ocean acidification and the ocean carbon sink.

Authors of a recent study in Biogeosciences investigated causes of the observed latitudinal trend in DIC and salinity-normalized DIC (nDIC) (Figure 1). The latitudinal trend in nDIC is not driven solely by the latitudinal gradient in temperature (through its effects on solubility), as is commonly assumed. Careful analysis using the Global Ocean Data Analysis Project version 2 (GLODAPv2) database revealed that physical supply from below (upwelling, entrainment in winter) at high latitudes is another major driver of the latitudinal pattern. The contribution of physical exchange explains an otherwise puzzling observation: Surface waters are lower in nDIC in the high-latitude North Atlantic than in other basins. This cannot be accounted for by temperature difference but rather is explained by a difference in the carbon content of deeper waters (lower in the subarctic North Atlantic than in the subarctic North Pacific or Southern Ocean) that are mixed up into the surface during winter months.

Figure caption: (Top) spatial distributions of surface ocean DIC and (bottom) salinity-normalised (nDIC). Both, most notably nDIC, increase towards the poles. Values are normalised to year 2005 to remove bias from changing levels of atmospheric CO2 in some observations before and after 2005. Data are from GLODAPv2.

These results also suggest that the upwelling/entrainment of water that is high in alkalinity generates a large and long-lasting effect on DIC, one that persists beyond the timescale of CO₂ gas exchange equilibration with the . That is to say, the impact of changes in upwelling on the ocean’s carbon source-sink strength depends not only on the DIC content of the upwelled water but also on its TA content.

Authors:
Yingxu Wu (University of Southampton)
Mathis Hain (University of California, Santa Cruz)
Matthew Humphreys (University of East Anglia and University of Southampton)
Sue Hartman (National Oceanography Centre, Southampton)
Toby Tyrrell (University of Southampton)

Air-sea gas exchange estimates biased by multi-day surface trapping

Posted by mmaheigan

· Tuesday, August 20th, 2019

Routine measurements of air-sea gas exchange assume a homogeneous gas concentration across the upper few meters of the ocean. But is this assumption valid? A recent study in Biogeosciences revealed substantial systematic gradients of nitrous oxide (N₂O) in the top few meters of the Peruvian upwelling regime. These gradients lead to a 30% overestimate of integrated N₂O emissions across the entire region, with local emissions overestimated by as much as 800%.

Figure caption: Air-sea gas exchange estimates can be biased by gas concentration gradients within the upper few meters of the ocean; in particular, surface trapping over several days’ duration can generate substantial gradients.

The N₂O gradients off Peru form during multi-day events of surface trapping, in which near-surface stratification dampens turbulent mixing. Until now, surface trapping was assumed to be a diurnal (driven by solar warming) process without memory, whereby only weak gradients would form during the hours of trapping and then dissipate. It is likely that multi-day surface trapping occurs in other ocean regions as well. The total impact on emission estimates of different greenhouse gases is yet to be quantified, but given the findings in the Peruvian upwelling system, could be significant globally.

Authors:
Tim Fischer, Annette Kock, Damian L. Arévalo-Martínez, Marcus Dengler, Peter Brandt, Hermann W. Bange (GEOMAR)

Can microzooplankton shape the depth distribution of phytoplankton?

Posted by mmaheigan

· Tuesday, July 23rd, 2019

Photosynthetic, single-celled phytoplankton form the base of many marine and lacustrine (lake) food webs. These microscopic algae typically occur in the sunlit surface layer, but in many ecosystems, there are also sub-surface peaks in phytoplankton and chlorophyll-a, their key photosynthetic pigment. Historically, scientists have explained deep chlorophyll maximum (DCM) formation by invoking “bottom-up” processes such as nutrient and light co-limitation, while less attention has been paid to “top-down” controls such as predation.

A recent study in Nature Communications challenges this conventional wisdom by arguing that microzooplankton (top-down control) can cause the formation of DCMs by preferentially consuming phytoplankton near the surface. This can occur when microzooplankton exhibit light-dependent grazing—a known but not well-understood phenomenon in which prey consumption rates increase with increasing light intensity. By incorporating this phenomenon into mathematical models, the authors showed that this can create a “spatial refuge” for phytoplankton in deeper, darker parts of the water column, where there is enough sunlight to photosynthesize, but too little for efficient microzooplankton predation. Furthermore, when light-dependent grazing is incorporated into a global ocean biogeochemistry model (COBALT: Carbon, Ocean Biogeochemistry and Lower Trophics – planktonic ecosystem model), DCMs that are already present due to bottom-up controls deepen, improving agreement between model predictions, satellite data, and in situ observations.

Figure legend: Global comparison of annual mean deep chlorophyll maxima (DCM) depths (A) predicted by the unmodified COBALT model, (B) predicted by the COBALT model modified to include light-dependent microzooplankton grazing, and (C) estimated based on satellite data. Incorporating light-dependent grazing deepens the DCM, especially in oligotrophic gyres, and improves agreement with observational data.

These findings highlight the importance of higher trophic levels in regulating aquatic primary productivity. The model predictions suggest that not only can microzooplankton suppress primary production near the surface, but by shifting phytoplankton abundances deeper, they may increase carbon export via the biological pump. Future field tests of this hypothesis—i.e. detailed grazing measurements in stratified water columns with DCMs—can elucidate the extent to which light-dependent grazing shapes phytoplankton distribution in real biological systems.

Authors:
Holly Moeller (University of California Santa Barbara)
Charlotte Laufkötter (University of Bern and Princeton University)
Edward Sweeney (Sea Education Association and Santa Barbara Museum of Natural History)
Matthew Johnson (Woods Hole Oceanographic Institution)

Nutrient and carbon limitation drive broad-scale patterns of mixotrophy in the ocean

Posted by mmaheigan

· Tuesday, May 14th, 2019

In the ocean, unicellular eukaryotes are often mixotrophic, which means they photosynthesize and also consume prey. In recent decades, it has become clear that mixotrophs are ubiquitous in sunlit ocean habitats. Additionally, models predict that mixotrophs have important impacts on productivity, nutrient cycling, carbon export, and food web structure. However, there is little understanding of the environmental conditions that select for a mixotrophic lifestyle, and it is unclear how mixotrophs succeed in competition with autotrophic and heterotrophic specialists. A recent study in PNAS that synthesized measurements of mixotrophic nanoflagellates showed that mixotrophs are more abundant in stratified, well-lit, low latitude environments (Figure 1A). They are also more abundant, relative to pure heterotrophs, in productive coastal environments (Figure 1B). A trait-based model analysis revealed that the success of mixotrophs depends on the fact that they are less nutrient-limited than autotrophs (due to prey-derived nutrients) and less carbon-limited than heterotrophs (due to photosynthesis). This synergy requires sufficient light, leading to success in low latitude environments. Similarly, a greater supply of dissolved nutrients relative to prey, as commonly observed in coastal environments, favors mixotrophs relative to heterotrophs. One implication of these results is that carbon fixation at lower latitudes may be enhanced by mixotrophy, while limiting nutrients may be more efficiently transferred to higher trophic levels.

Figure 1. Estimated abundance of autotrophic, mixotrophic, and heterotrophic nanoflagellates across environmental gradients in the ocean.

Author:
Kyle Edwards (Univ. Hawaii at Manoa)

Zooplankton vertical migrations represent a significant source of carbon export in the ocean

Posted by mmaheigan

· Friday, March 15th, 2019

Huge numbers of tiny marine animals, known as zooplankton, migrate between the surface ocean and the twilight zone (200 – 1,000 m below the surface) everyday; it is the largest migration event anywhere on the planet. How much carbon do these animals transport with them and how much do they leave behind sequestered in the deep ocean? In a recent publication in Global Biogeochemical Cycles, Archibald et al. (2019) used a simple model to estimate the magnitude of carbon flux into the twilight zone from zooplankton vertical migrations and observed that it was a significant contributor to carbon export on a global scale. The study also revealed strong regional patterns in migration-mediated carbon flux, with the greatest impact on export occurring at subtropical latitudes (Figure 1).

Figure 1. Percent increase in the modeled carbon export flux out of the surface ocean as a result of zooplankton vertical migrations.

Migrating zooplankton also consume significant amounts of oxygen at depth, generating a local maximum in the oxygen utilization profile at depth within the migration layer. By including the effect of the metabolism of migrating zooplankton, the model is able to produce a more detailed picture of oxygen utilization over the twilight zone. The model in this study effectively simulates the complex phenomenon of zooplankton vertical migrations, providing a simple framework that will allow researchers to investigate how this key component of the global carbon cycle might change under future climatic conditions. For example, if increased stratification leads to a greater representation of small cells in phytoplankton communities, then zooplankton migration-mediated carbon export is expected to make up a proportionally larger fraction of the total carbon export flux.

Authors:
Kevin M. Archibald (Woods Hole Oceanographic Institution and Massachusetts Institute of Technology)
David A. Siegel (University of California, Santa Barbara)
Scott C. Doney (University of Virginia)

Rapid warming and salinity changes mask acidification in Gulf of Maine waters

Posted by mmaheigan

· Wednesday, February 20th, 2019

Why don’t we see ocean acidification in over a decade of high-frequency observations in the Gulf of Maine? The answer lies in a recent decade of changes that raised sea surface temperature and salinity, and in turn dampened the expected acidification signal and caused the saturation states of calcite minerals to increase. From 2004 to 2014, sea surface temperatures in the Gulf of Maine were higher than any observations recorded in the region over the past 150 years. This greatly impacted both CO₂ solubility and the sea surface carbonate system, as detailed in a recent paper in Biogeochemistry.

Over the 34 years of the time-series, the recent event is extreme, but interannual and decadal salinity and temperature variability also influenced carbonate system parameters, which makes it difficult to isolate and quantify an anthropogenic ocean acidification signal, especially if relying on shorter-term observations (Figure 1).

Figure 1: Modeled Ω_Aragonite (top panel) and pH (bottom panel) anomalies relative to monthly 2004 data. The red lines show trends prior to and after 2004, after which warming accelerated.

For those with a stake in profiting from or managing extractive resources that are susceptible to ocean acidification such as commercially important lobster and bivalves, understanding how ecosystems will be affected is critical. These analyses clearly demonstrate how physical processes can either accelerate or mitigate ocean carbonate system changes, thus confounding the detection of ocean acidification that is expected from increasing atmospheric carbon dioxide. To assess whether an ecosystem or species is at risk or aided by such processes, it is important to observe, understand, and be able to model all sources of carbonate system variability.

Authors:
Joe Salisbury and Bror Jönsson (Both at Ocean Processes Analysis Laboratory, University of New Hampshire)

Efficient carbon drawdown allows for a high future carbon uptake in the North Atlantic

Posted by mmaheigan

· Wednesday, November 7th, 2018

As one of the major carbon sinks in the global ocean, the North Atlantic is a key player in mediating and ameliorating the ongoing global warming. Current projections of the North Atlantic carbon sink in a high-CO₂ future vary greatly among models, with some showing that a slowdown in carbon uptake has already begun and others predicting that this slowdown will not occur until nearly 2100. To ensure the credibility of future projections as needed for finding adequate mitigation strategies, it is important to address and reduce this uncertainty.

Percentage of anthropogenically altered carbon stored in the deep North Atlantic (left panel) and North Atlantic uptake of anthropogenically altered carbon (right panel) as simulated by 11 different Earth System Models for a high CO2-future. Black x and line in left panel mark the observational estimate and its uncertainties, while blue and red shading reflect model spread, including models that simulate deep ocean storage within (blue) and outside (red) these observational uncertainties.

A new study in the Journal of Climate identified some of the mechanisms behind this ambiguity by analyzing the output of 11 Earth System Models for a high-CO₂ future. The authors show that discrepancies among models largely originate around high-latitude gateways from the surface to the deep ocean. Through biological production, deep convection and subsequent transport via the deep western boundary current, these gateways remove carbon from the upper ocean. When enough carbon is removed to maintain a lower oceanic pCO₂ relative to atmospheric pCO₂, the ocean continues to take up carbon. The study reveals that the fraction of anthropogenic carbon that is stored below 1000 m depth is not only an indicator of current carbon removal from the upper ocean but also a predictor of future ocean carbon uptake. When models that lie outside the range of observational uncertainties in deep carbon storage (red shading, left panel of figure) were excluded, revised projections showed higher North Atlantic carbon uptake in the future with lower associated uncertainties (blue shading, right panel of figure). This result highlights the need to depart from the concept of more or less randomly chosen models when reporting on future projections and their uncertainties. Results that are more reliable and hence of better use for mitigation strategies can be gained by focusing solely on models that simulate key mechanisms within observational uncertainties.

Authors:
N. Goris (Bjerknes Centre for Climate Research, Norway)
J.F. Tjiputra (Bjerknes Centre for Climate Research, Norway)
A. Olsen (University of Bergen and Bjerknes Centre for Climate Research, Norway)
J. Schwinger (Bjerknes Centre for Climate Research, Norway)
S.K. Lauvset (Bjerknes Centre for Climate Research, Norway)
E. Jeansson (Bjerknes Centre for Climate Research, Norway)

Investigating variability and change in subpolar Southern Ocean pCO2 via time-series and float data

Posted by mmaheigan

· Tuesday, November 6th, 2018

The Southern Ocean dominates the mean global ocean sink for anthropogenic carbon, but its sparse sampling relative to other basins limits our capacity to quantify carbon uptake and accompanying seasonal to interannual variability, which is critical to predicting future ocean carbon uptake and storage. Since 2002, underway pCO₂measurements collected as part of the Drake Passage Time-series (DPT) Program have informed our understanding of seasonally varying air-sea pCO₂gradients and by inference, the carbon fluxes in this region. Understanding whether Drake Passage air-sea fluxes are representative of the broader subpolar Southern Ocean was the focus of a recent study in Biogeosciences.

Top left panel: Mean surface ocean seasonal pCO2 cycle estimate for datasets from the Surface Ocean CO2 Atlas (SOCAT) in the subpolar Southern Ocean: black- SOCAT within the Drake Passage (DP) region; green- SOCAT outside the DP region; blue- all SOCAT in Southern Ocean Subpolar Seasonally Stratified (SPSS) biome; red- Self Organizing Map Feed-forward Network (SOM-FFN) product. Shading represents 1 standard error for biome-scale monthly means driven by interannual variability. Bar plot indicates the number of years containing observations in a given month (maximum of 15 years).
Top right panel: Mean surface ocean pCO2 seasonal cycle estimate for black: underway Drake Passage Time-series data for years 2002–2016; purple: DPT for years 2016–2017 to match years covered by the floats; and orange: SOCCOM floats. Seasonal cycles are shown on an 18-month cycle, calculated from a monthly mean time series with the atmospheric correction to year 2017. Shading represents 1 standard error accounting for the spatial and temporal heterogeneity of the sample and the measurement error (2.7 % or ±11 µatm at a pCO2 of 400 µatm for floats; ±2 µatm for DPT data) combined using the square root of the sum of squares.

An analysis of available Southern Ocean pCO₂ data from inside vs. outside the Drake Passage showed agreement in the timing and amplitude of seasonal pCO₂ variations, suggesting that the seasonality so carefully recorded by DPT is in fact representative of the broader subpolar Southern Ocean. DPT’s high temporal resolution sampling is critical to constraining estimates of the seasonal cycle of surface pCO₂ in this region, as wintertime underway pCO₂ data remain sparse outside the Drake Passage. Comparisons of the DPT data to an emerging dataset of float-estimated pCO₂ from the SOCCOM (Southern Ocean Carbon and Climate Observations and Modeling) project showed that both shipboard and autonomous platforms capture the expected seasonal cycle for the subpolar Southern Ocean, with an austral wintertime peak driven by deep mixing and a summertime low driven by biological uptake. However, the seasonal cycle derived from float-estimated pCO₂ has a larger seasonal amplitude compared to the DPT data due to an earlier and much lower observed summertime minimum.

The Drake Passage Time-series illustrates the large variability of surface ocean pCO₂ in the Southern Ocean and exemplifies the value of sustained observations for understanding changing ocean carbon uptake in this dynamic region. Coordinated monitoring efforts that combine a robust ship-based observational network with a well-calibrated array of autonomous biogeochemical floats will improve and expand our understanding of the Southern Ocean carbon cycle in the future.

Authors:
Amanda R. Fay (Lamont Doherty Earth Observatory)
Nicole S. Lovenduski (University of Colorado)
Galen A. McKinley (Lamont Doherty Earth Observatory)
David R. Munro (University of Colorado)
Colm Sweeney (University of Colorado, NOAA Earth System Research Laboratory)
Alison R. Gray (University of Washington)
Peter Landschützer (Max Planck Institute for Meteorology, Germany)
Britton B. Stephens (National Center for Atmospheric Research)
Taro Takahashi (Lamont Doherty Earth Observatory)
Nancy Williams (Oregon State University)

Improved method to identify and reduce uncertainties in marine carbon cycle predictions

Posted by mmaheigan

· Wednesday, September 26th, 2018

Improved method to identify and reduce uncertainties in marine carbon cycle predictions

How well do contemporary Earth System Models (ESMs) represent the dynamics of the modern day ocean? Often we question the fidelity of biological and chemical processes represented in these ESMs. The fact is representations of biogeochemical processes in models are plagued with some degree of uncertainties; therefore, identifying and reducing such deficiencies could advance ESM development and improve model predictions.

An overview of several models with respect to each of the variables, using absolute (left) and relative (right) scores to determine the degree of uncertainty in relation to referenced datasets.

A recent publication in Atmosphere described the ongoing efforts to develop the International Ocean Model Benchmarking (IOMB) package to evaluate ESM skill sets in simulating marine biogeochemical variables and processes. Model performances were scored based on how well they captured the distribution and variability contained in high-quality observational datasets. The authors highlighted systematic model–data benchmarking as a technique to identify ocean model deficiencies, which could provide a pathway to improving representations of sub-grid-scale parameterizations. They have scaled the absolute score from zero to unity, where the red color tends toward zero to quantify weaknesses in the skill set of a particular model in capturing values from the observational datasets. On the other side of the spectrum, the green color signifies considerable temporal and spatial overlap between the predicted and the observational values. The authors also present the standard score to show the relative scores within two standard deviations from the model mean. The benchmarking package was employed in the published study to assess marine biogeochemical process representations, with a focus on surface ocean concentrations and sea–air fluxes of dimethylsulfide (DMS). The production and emission of natural aerosols remain one of the major limitations in estimating global radiative forcing. Appropriate representation of aerosols in the marine boundary layer (MBL) is essential to reduce uncertainty and provide reliable information on offsets to global warming. Results show that model–data biases increased as DMS enters the MBL, with models over-predicting sea surface concentrations in the productive region of the eastern tropical Pacific by almost a factor of two and the sea–air fluxes by a factor of three. The associated uncertainties with oceanic carbon cycle processes may be additive or antagonistic; in any case, a constructive effort to disentangle the subtleties begins with an objective benchmarking effort, which is focused specifically on marine biogeochemical processes. The tool in development will ensure we satisfy some of the Model Intercomparison Project (MIP) benchmarking needs for the sixth phase of Coupled Model Intercomparison Project (CMIP6).

Authors:
Oluwaseun Ogunro (ORNL)
Scott Elliott (LANL)
Oliver Wingenter (New Mexico Tech)
Clara Deal (University of Alaska)
Weiwei Fu (UC Irvine)
Nathan Collier (ORNL)
Forrest M. Hoffman (ORNL)

Funding for the Ocean Carbon & Biogeochemistry Project Office is provided by the National Science Foundation (NSF) and the National Aeronautics and Space Administration (NASA). The OCB Project Office is housed at the Woods Hole Oceanographic Institution.

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