Archive for ocean carbon uptake and storage – Page 11

Nutrient Distributions Reveal the Fate of Sinking Particles

Posted by mmaheigan 
· Monday, November 21st, 2016 

The ocean’s “biological pump” regulates the atmosphere-ocean partitioning of carbon dioxide (CO2), and has likely contributed to significant climatic changes over Earth’s history (1, 2). It comprises two processes, separated vertically in the water column: (i) production of organic carbon and export from the surface euphotic zone (0-100m), mostly as sinking particles; and (ii) microbial remineralization of organic carbon to CO2 in deeper waters, where it cannot exchange with the atmosphere.

The depth of particulate organic carbon (POC) remineralization controls the longevity of carbon storage in the ocean (3), and strongly influences the atmospheric CO2 concentration (4). CO2 released in the mesopelagic zone (100-1000m) is returned to the atmosphere on annual to decadal timescales, whereas POC remineralization in the deep ocean (>1000m) sequesters carbon for centuries or longer (5). A common metric for the efficiency of the biological pump is thus the fraction of sinking POC that reaches the deep ocean before remineralization (6), referred to as the particle transfer efficiency, or Teff.

Currently, the factors that govern particle remineralization depth are poorly understood and crudely represented in climate models, compared to the lavish treatment of POC production by autotrophic communities in the surface (7). This compromises our ability to predict the biological pump’s response to anthropogenic warming, and its potential feedback on atmospheric CO2 (8). Over the last decade, a number of studies have identified a promising path towards closing this gap. If systematic spatial variations inTeff can be identified throughout the modern ocean, we might discern their underlying environmental or ecological causes (9, 10). However, direct observations from sediment traps are too sparse to constrain time-mean particle fluxes through the mesopelagic zone at the global scale, and no consensus pattern of Teff has emerged from these analyses.

Particle flux reconstruction

Instead of relying on sparse particle flux observations, a recent study took an alternative approach, leveraging the geochemical signatures that are left behind when particles remineralize (11). Products of remineralization include inorganic nutrients like phosphate (PO43-), whose global distributions are well characterized by hundreds of thousands of shipboard observations (12). In shallow subsurface waters, nutrient accumulation reflects the remineralization of both organic particles and dissolved organic matter, which is advected and entrained from the euphotic zone. Dissolved organic phosphorous (DOP) decomposes rapidly, and is almost completely absent

In shallow subsurface waters, nutrient accumulation reflects the remineralization of both organic particles and dissolved organic matter, which is advected and entrained from the euphotic zone. Dissolved organic phosphorous (DOP) decomposes rapidly, and is almost completely absent by depths of ~300m in the stratified low latitude ocean (13), and below the wintertime mixed layer in high latitudes (14). Deeper in the water column, particulate organic phosphorous (POP) remineralization is the only process that generates PO43- within water masses as they flow along isopycnal surfaces (Fig. 1). Rates of POP remineralization can therefore be diagnosed from the accumulation rate of PO43- along transport pathways in an ocean circulation model. This calculation requires a very faithful representation of the large-scale circulation, as provided by the Ocean Circulation Inverse Model (OCIM), whose flow fields are optimized to match observed water mass tracer distributions (15).

Assuming that organic matter burial in sediments is negligible, the integrated POP remineralization beneath a given depth horizon is equal to the flux of POP (FPOP) through that horizon, allowing complete reconstruction of flux profiles from ~300m to the deep ocean. Averaging these fluxes over large ocean regions serves to extract the large-scale signal from small-scale noise (Fig. 2). Regional-mean FPOP profiles show striking differences in shape and magnitude between subarctic, tropical, and subtropical regions, which are remarkably consistent between the Pacific and Atlantic Oceans (Fig 2a,b). FPOP near 300m is similar in subarctic and tropical zones, but attenuates faster through the mesopelagic in the tropics, reaching values of ~5mmol m-2yr-1 at 1000m, compared to ~7mmol m-2yr-1 in subarctic oceans. Subtropical FPOP attenuates even faster, and is indistinguishable from zero throughout most of the water column. In the Southern Ocean, FPOP is ~5mmol m-2yr-1 at 1000m in both the Antarctic and subantarctic regions, but the subantarctic flux profile attenuates slightly faster (Fig. 2c).

Patterns of transfer efficiency and underlying mechanisms

While these reconstructions place a robust constraint on POP fluxes to the deep ocean, they do not constrain rates of POP export at the base of the euphotic zone (zeu) that are needed to estimate the particle transfer efficiency (Teff). Remote sensing approaches are widely used to estimate large-scale organic carbon export, which can be converted to POP using an empirical relationship for particulate P:C ratios (16). However, multiple algorithms have been proposed to estimate net primary production and convert it to export, yielding widely different regional-mean rates (11). One way to pare down this variability is to weight each algorithm based on its ability to reproduce tracer-based export estimates in each ocean region (17, 18). This yields an “ensemble” estimate for the areal-mean POP export rate in each region, and an uncertainty range that reflects both observational error and the variability between satellite algorithms (Fig. 3a).

Combining the ensemble estimates of POP export with reconstructed FPOP at 1000m reveals a systematic pattern of transfer efficiency from zeu to the deep ocean (Fig. 3a).  The subtropics exhibit the lowest Teff of ~5%, significantly lower than expected from the canonical Martin Curve relationship (19), which is often considered to represent an “average” particle flux profile. In the tropics and the subantarctic zone of the Southern Ocean, Teff clusters close to the Martin Curve prediction of ~15%. The subarctic and Antarctic regions (i.e. high latitudes) are the most efficient at delivering the surface export flux to depth with Teff>25%, although these values are also associated with the largest uncertainty (Fig. 3a).

What controls the strong latitudinal variation of transfer efficiency? Particle flux attenuation is determined by the sinking speed and bacterial decomposition rate of particles: fast sinking and slow decomposition both result in greater delivery of organic matter to the deep ocean. Decomposition rates increase as a function of temperature in laboratory incubation studies (20), controlled by the temperature-dependence of bacterial metabolism. In a recent compilation of Neutrally Buoyant Sediment Trap (NBST) observations, particle flux attenuation was strongly correlated with upper ocean temperature between 100-500m (21), consistent with this effect. An almost identical temperature relationship explains ~80% of the variance in reconstructed regional Teff estimates (Fig. 3b).

An equally compelling argument can be made for particle sinking speeds controlling the pattern of Teff. According to the current paradigm of marine food webs (22), communities dominated by small phytoplankton export small particles that sink slowly, relative to the large aggregates and fecal pellets produced when large plankton dominate. The fraction of photosynthetic biomass contributed by tiny picoplankton (Fpico) varies from <30% in subarctic regions to >55% in oligotrophic subtropical regions (23), and explains ~86% of the variance in reconstructed Teff (Fig. 3c). Fpico also predicts flux attenuation in NBST profiles as skillfully as upper-ocean temperature (R2 = 0.81 and 0.82 respectively), but was not considered previously (21). Due to the spatial covariation of these factors in the ocean, statistical analysis alone is insufficient to determine the relative contributions of temperature and particle size to latitudinal variations in transfer efficiency.

Conclusions and future directions

Reconstructing deep-ocean particle fluxes has left us with a clearer understanding of the biological pump in the contemporary ocean and its climate sensitivity. Deep remineralization in high latitude regions results in efficient long-term carbon storage, whereas carbon exported in subtropical regions is recirculated to the atmosphere on short timescales (11). Atmospheric CO2 is likely more sensitive to increased high latitude nutrient utilization during glacial periods than previously recognized, whereas the expansion of subtropical gyres in a warming climate might result in a less efficient biological pump.

One caveat is that the new results highlighted here constrain POP transfer efficiency, not POC, and the two might be decoupled by preferential decomposition of one element relative to the other. The close agreement of these results with Neutrally Buoyant Sediment Trap observations (which measure POC) is encouraging, and suggests that the reconstructed pattern ofTeff is applicable to carbon. More widespread deployment of NBSTs, which circumvent the sampling biases of older sediment trap systems (24), would help confirm or refute this conclusion. A second limitation is that the wide degree of uncertainty in high latitude export rates (Fig. 3a) obscures estimates ofTeff in these regions. New tracer-based methods to integrate export across the seasonal cycle (25) will hopefully close this gap and enable more careful groundtruthing of satellite predictions.

Two plausible mechanisms –particle size and temperature – have been identified to explain large latitudinal variations in transfer efficiency, and new observational systems hold the potential to disentangle their effects. Underwater Visual Profilers (UVP) can now accurately resolve the size distribution of particles in mesopelagic waters (26). Although UVPs provide only instantaneous snapshots (quite literally) of the particle spectrum rather than time-mean properties, large compilations of these data will help establish the spatial pattern of particle size and its relationship to microbial community structure. In parallel, ongoing development of the RESPIRE particle incubator will allow for in-situ measurement of POC respiration (27), and better establish its temperature sensitivity.

Over the next few years, the upcoming EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) campaign stands to revolutionize our understanding of the fate of organic carbon (28). These insights will allow for a more balanced treatment of the “dark side” of the biological pump in global climate models, compared to euphotic zone processes, improving our predictions of biological carbon sequestration in a warming ocean.

Author

By Thomas Weber (University of Rochester)

Acknowledgment

This work was supported by NSF grant OCE-1635414 and the Gordon and Betty Moore Foundation (GBMF 3775).

References

1. J. L. Sarmiento et al., Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 325, 3–21 (1988).
2. A. Mart.nez-Garc.a et al., Science 343, 1347–50 (2014).
3. U. Passow, C. Carlson, Mar. Ecol. Prog. Ser. 470, 249–271 (2012).
4. E. Y. Kwon, F. Primeau, J. L. Sarmiento, Nat. Geosci. 2, 630–635 (2009).
5. T. Devries, F. Primeau, C. Deutsch, Geophys. Res. Lett. 39, 1–5 (2012).
6. P. J. Lam, S. C. Doney, J. K. B. Bishop, Glob. Biogeochem. Cycles. 25, 1–14 (2011).
7. J. K. Moore, S. C. Doney, J. a. Kleypas, D. M. Glover, I. Y. Fung, Deep. Res. Part II Top. Stud. Oceanogr. 49, 403–462 (2002).
8. L. Bopp et al., Biogeosci. 10, 6225–6245 (2013).
9. S. a. Henson, R. Sanders, E. Madsen, Glob. Biogeochem. Cycles. 26, 1–14 (2012).
10. M. J. Lutz, K. Caldeira, R. B. Dunbar, M. J. Behrenfeld, J. Geophys. Res. 112, C10011 (2007).
11. T. Weber, J. A. Cram, S. W. Leung, T. Devries, C. Deutsch, Proc. Nat. Acad. Sci. 113, 8606–8611 (2016).
12. H. E. Garcia et al., NOAA World Ocean Atlas (2010).
13. J. Abell, S. Emerson, P. Renaud, J. Mar. Res. 58, 203–222 (2000).
14. S. Torres-Vald.s et al., Glob. Biogeochem. Cycles. 23, 1–16 (2009).
15. T. Devries, Glob. Biogeochem. Cycles. 28, 631–647 (2014).
16. E. D. Galbraith, A. C. Martiny, Proc. Nat. Acad. Sci., 201423917 (2015).
17. M. K. Reuer, B. A. Barnett, M. L. Bender, P. G. Falkowski, M. B. Hendricks, Deep. Res. Part I Oceanogr. Res. Pap. 54, 951–974 (2007).
18. S. Emerson, Glob. Biogeochem. Cycles. 28, 14–28 (2014).
19. J. H. Martin, G. A. Knauer, D. M. Karl, W. W. Broenkow, Deep Sea Res. Part A, Oceanogr. Res. Pap. 34, 267–285 (1987).
20. M. H. Iversen, H. Ploug, Biogeosciences. 10, 4073–4085 (2013).
21. C. M. Marsay, R. J. Sanders, S. A. Henson, K. Pabortsava, E. P. Achterberg, Proc. Nat. Acad. Sci., 112, 1089–1094 (2014).
22. D. A. Siegel et al., Glob. Biogeochem. Cycles. 28, 181–196 (2014).
23. T. Hirata et al., Biogeosci. 8, 311–327 (2011).
24. K. O. Buesseler et al., Science 316, 567–570 (2007).
25. S. M. Bushinsky, S. Emerson, Glob. Biogeochem. Cycles. 29, 2050–2060 (2015).
26. M. Picheral et al., Limnol. Oceanogr. Methods. 8, 462–473 (2010).
27. A. M. P. McDonnell, P. W. Boyd, K. O. Buesseler, Glob. Biogeochem. Cycles. 29, 175–193 (2015).
28. D. A. Siegel et al., Front. Mar. Sci. 3, 1–10 (2016).

A chalkier ocean? Multi-decadal increases in North Atlantic coccolithophore populations

Posted by mmaheigan 
· Saturday, November 19th, 2016 

Coccolithophores and the carbon cycle

Increasing atmospheric CO2 concentrations are resulting in both warmer sea surface temperatures due to the greenhouse effect and increasingly carbon-rich surface waters. The ocean has absorbed roughly one third of anthropogenic carbon emissions (1), causing a shift in carbon chemistry equilibrium to more acidic conditions with lower calcium carbonate saturation states (ocean acidification). Organisms that produce calcium carbonate structures are thought to be particularly susceptible to these changes (2-4).

Coccolithophores are the most abundant type of calcifying unicellular micro-algae in the ocean, producing microscopic calcium carbonate plates called coccoliths (5). Low-pH conditions have been shown to disrupt the formation of coccoliths (calcification; e.g., (6)). Therefore, it is generally expected that a higher-CO2 ocean will cause a reduction in calcification rates or a decrease in the abundance of these calcifiers. Such changes could have far-reaching consequences for marine ecosystems, as well as global carbon cycling and carbon export to the deep sea.

Coccolithophores use sunlight to synthesize both organic carbon through photosynthesis and particulate inorganic carbon (PIC) through calcification. Detrital coccolithophore shells form aggregates with organic material, enhancing carbon export to the deep sea (7). Coccolithophores also produce dimethyl sulfide (DMS), a climatically relevant trace gas that impacts cloud formation, ultimately influencing Earth’s albedo (8, 9). At the ecosystem level, coccolithophores compete for nutrients with other phytoplankton and provide energy for the rest of the marine food web. Coccolithophores have a broad range of irradiance, temperature, and salinity tolerances (10, 11). Moreover, their relatively low nutrient requirements and slow growth rates offer a competitive advantage under projected global warming and ocean stratification (5). This plasticity and opportunistic behavior can be critical for persistence in a changing oceanic environment. Given the wide range of biogeochemical and ecological processes impacted by coccolithophores, it is important to assess how anthropogenic changes may affect coccolithophore growth and calcification.

Many laboratory studies have investigated the impact of future environmental conditions on coccolithophores by decreasing pH, increasing dissolved inorganic carbon, and increasing temperature to mimic end-of-century projections. However, these have often yielded conflicting results: Some show a decrease, while others show no change or even increased calcification (e.g., (6, 12, 13)). For example, laboratory simulations of contemporary oceanic changes (increasing CO2 and decreasing pH) show that coccolithophores have the ability to modulate organic carbon production and calcification in response to variable amounts of dissolved inorganic carbon (DIC) but that low pH only affects these processes below a certain threshold (14). Another study indicated that coccolithophores could adapt to warming and highCO2 levels over the course of a year, maintaining their relative particulate organic carbon (POC) and PIC production per cell (15). One of the limitations of all laboratory experiments is that only a handful of species (and strains) are studied, which is only a tiny fraction of the diversity present in the oceans. Given the challenges of extrapolating laboratory results to real world oceans, studying recent trends in natural populations may lead to important insights.

The North Atlantic is both a region with rapid accumulation of anthropogenic CO2 (1) and an important coccolithophore habitat (Fig. 1), making this region a good starting point to search for in situ evidence of anthropogenic carbon effects on diverse coccolithophore populations. Two recent studies did precisely that: Rivero- Calle et al. (2015)(16) in the subpolar North Atlantic, and Krumhardt et al. (2016)(17) in the North Atlantic subtropical gyre. Using independent datasets, these two studies concluded that coccolithophores in the North Atlantic appear to be increasing in abundance and, contrary to the prevailing paradigm, responding positively to the extra carbon in the upper mixed layer.

Evidence from long-term in situ monitoring (two independent case studies)

Rivero-Calle et al. (2015) used data from the Continuous Plankton Recorder (CPR), a filtering device installed on ships of opportunity, to assess changes in coccolithophore populations from 1965 to 2010 in the subpolar North Atlantic. This highly productive, temperate region is dominated by large phytoplankton and characterized by strong seasonal changes in the mixed layer depth, nutrient upwelling, and gas exchange that lead to intense, well-established spring phytoplankton blooms.

Because coccolithophore cells are smaller than the mesh size used by the CPR, they cannot be accurately quantified in the CPR data set. Some coccolithophore cells do, however, get caught in the mesh and their occurrence (i.e. probability of presence) can be calculated and serve as a proxy for coccolithophore abundance. Using recorded presence or absence of coccolithophores over this multidecadal time-series, the authors showed that coccolithophore occurrence in the subpolar North Atlantic increased from being present in only 1% of samples to > 20% over the past five decades (Fig. 2). To assess the importance of a wide range of diverse environmental drivers on changes in coccolithophore occurrence, Rivero-Calle and co-authors used random forest statistical models. Specifically, they examined more than 20 possible biological and physical predictors, including CO2 concentrations, nutrients, sea surface temperature and the Atlantic Multidecadal Oscillation (AMO), as well as possible predators and competitors. Global and local CO2 concentrations were shown to be the best predictors of coccolithophore occurrence. The AMO, which has been in a positive phase since the mid-1990s (Fig. 2) and is associated with anomalously warmer temperatures over the North Atlantic, was also a good predictor of coccolithophore occurrence, but not as strong of a predictor as CO2.

The authors hypothesize that the synergistic effects of increasing anthropogenic CO2, the recent positive phase of the AMO, and increasing global temperatures contributed to the observed increase in coccolithophore occurrence in the CPR samples from 1965 to 2010. Complementing the Rivero-Calle et al. (2015) study, Krumhardt et al. (2016) used phytoplankton pigment concentration data from the long-running Bermuda Atlantic Time-series Study (BATS) and satellite-derived PIC data to assess recent changes in coccolithophore abundance in the subtropical North Atlantic. This region of the North Atlantic is characterized by Ekman convergence and downwelling, resulting in an oligotrophic environment. Despite relatively low productivity, subtropical gyres cover vast expanses of the global ocean and are thus important on a global scale.

In the North Atlantic subtropical gyre, researchers at BATS have performed phytoplankton pigment analyses since the late 1980s, as well as a suite of other oceanographic measurements (nutrients, temperature, salinity, etc.). This rich dataset provided insight into phytoplankton dynamics occurring at BATS over the past two decades. Coccolithophores contain a suite of pigments distinctive to haptophytes. Though there are many species of non-calcifying haptophytes in the ocean (18), the main contributors to the haptophyte community in oligotrophic gyres are coccolithophores (19). Using a constant haptophyte pigment to chlorophyll a ratio Krumhardt et al. (2016) quantified relative abundance of the coccolithophore chlorophyll a (Chlahapto) over the BATS time-series. A simple linear regression revealed that coccolithophore pigments have increased in the upper euphotic zone by 37% from 1990 to 2012 (Figure 2). On the other hand, total chlorophyll a at BATS only increased slightly over this time period.

While satellite-derived chlorophyll a is used as a proxy for biomass and abundance of the entire phytoplankton community (20), satellite-derived PIC is formulated to specifically retrieve calcium carbonate from coccolithophore shells (21, 22). Therefore, satellite PIC can be used as a proxy for coccolithophore abundance. Although there has been virtually no change in total chlorophyll a over most of the North Atlantic subtropical gyre over the satellite era (1998-2014), predominantly positive trends were shown over this time period for PIC (17). This indicates that coccolithophore populations appear to be increasing over and above other phytoplankton species in the subtropical gyre.

Like Rivero-Calle et al., Krumhardt et al. explored possible environmental drivers of this increase in coccolithophore pigments at BATS and coccolithophore PIC throughout the gyre. They performed linear correlations between variability of hypothesized drivers and coccolithophore chlorophyll a concentrations at the BATS site. Increasing DIC, specifically the bicarbonate ion (HCO3–) fraction, showed a strong positive correlation with pigments from coccolithophores, explaining a significant fraction of the coccolithophore pigment variability. DIC in the upper mixed layer at BATS has been increasing steadily over the past several decades from absorption of anthropogenic CO2 (Fig. 2; 23) and coccolithophores may be responding to this. But how does extra carbon in the water explain the increases in coccolithophore populations?

Environmental controls on coccolithophore growth

A few studies have shown that, in contrast to most other phytoplankton, coccolithophore photosynthesis (specifically, the widespread coccolithophore species Emiliania huxleyi) can be carbon-limited at today’s CO2 levels (e.g., 14, 24). This suggests that increases in surface DIC (e.g., due to the uptake of anthropogenic CO2) may alleviate growth limitation of coccolithophores. By reducing the amount of energy spent on carbon concentrating mechanisms, coccolithophores may invest in other metabolic processes such as growth, PIC or POC production. This explains why a relatively small increase in DIC could increase coccolithophore competitive ability, especially in oligotrophic environments where phytoplankton are routinely in competition for scarce nutrients. Rivero-Calle and co-authors compiled numerous published laboratory studies that assessed coccolithophore growth rates as a function of pCO2. The compilation, which included several species and strains of coccolithophores, showed that there is a quasi-hyperbolic increase in coccolithophore growth rates as pCO2 increases (Fig. 3). The range of local pCO2 concentrations in the subpolar/temperate North Atlantic from 1965 to 2010 (~175 to 435 ppm) spanned the pCO2 levels over which there is a substantial increase in published coccolithophore growth rates (Fig. 3). Growth rates tend to stabilize at ~500 ppmCO2, indicating that coccolithophore populations may continue to respond positively to increasing CO2 for the next few decades.

Other environmental factors (e.g., temperature, light, and available nutrients) may also impact and modulate coccolithophore growth rates, resulting in a net neutral or net negative impact in spite of increasing atmospheric (marine) CO2 (DIC) concentrations (see conceptual model, Fig. 3). For example, severe nutrient limitation in the subtropics may cause coccolithophores to be outcompeted by smaller marine cyanobacteria. In the subpolar North Atlantic, nutrients are more plentiful than in the subtropics, but Earth system models have predicted that climatic warming in this region may result in increased water column stratification (25). Under these stratified low-nutrient conditions, smaller phytoplankton such as coccolithophores could become more prevalent at the expense of larger phytoplankton such as diatoms (26, 27). However, if nutrient concentrations decline to the point at which they become the limiting factor for growth, then coccolithophore populations will also be negatively affected. Furthermore, the associated drop in pH from CO2 dissolving into the upper mixed layer can eventually be detrimental to coccolithophore growth and calcification. Specifically, pH values below 7.7 negatively affected the coccolithophore Emiliania huxleyi in laboratory experiments (14), though most oceanic regions will not show such a low pH any time in the near future. In short, anthropogenic CO2 entering the ocean may allow coccolithophores a competitive edge in the near future in some regions such as the North Atlantic, but other compounding influences from anthropogenic climate change such as severe nutrient limitation or ocean acidification are also important to consider, particularly in the oligotrophic gyres.

Open questions and future directions

While recent work has provided new insight into the impact of several environmental factors (irradiance, nutrients, temperature, pH, DIC) on coccolithophores, many questions remain. Among these, the vertical distribution of coccolithophore communities, grazing rates, and viral infection on coccolithophores, and species-specific responses to environmental change are relatively unexplored areas of research. For instance, some studies have shown species-specific and even strain-specific variability in the response of coccolithophores to CO2 (28, 29), but how various coccolithophore species respond to nutrient or light limitation is relatively unknown. Due to its cosmopolitan distribution and ability to grow relatively easily in the lab, E. huxleyi, has become the “lab rat” species. However, it may not be the most important calcite producer globally (30), nor the most representative of the coccolithophore group as a whole. As part of its peculiarities, E. huxleyi can both produce several layers of coccoliths and also exhibit a naked form without coccoliths, posing questions about the importance of non-calcified forms in the projected acidified oceans and about the role of calcification per se (31). Indeed, the fundamental question of why coccolithophores calcify is still unresolved and may vary between species (5, 32). In addition, while we recognize that some zooplankton groups graze on coccolithophores (coccoliths have been found in pelagic tintinnid ciliates (33), as well as copepod guts and fecal pellets (34-36)), little is known about predation rates or specificity in natural populations. Finally, we know that viruses can also cause bloom termination and that E. huxleyi can induce coccolith detachment to avoid viral invasion (37); however, there are still many unknowns related to bloom dynamics. Until we understand what drives coccolithophore calcification and variations in growth and mortality rates, we will have an incomplete picture of the role that coccolithophores play in marine ecology and the carbon cycle.

Krumhardt et al (2016) and Rivero-Calle et al (2016) both arrive at a simple conclusion: Coccolithophore presence in the North Atlantic is increasing. The common denominators in this equation are increasing global CO2 levels and increasing global surface temperatures. Therefore, even given regional oceanic variability in environmental drivers, we might expect to see similar trends in coccolithophore abundance in other regions. Given coccolithophores’ positive response to increasing anthropogenic CO2 and temperature, as well as general fitness under conditions that may be more prevalent in the future ocean, coccolithophores may become an even bigger player in the marine carbon cycle, which may have unexpected consequences.

Authors
Kristen Krumhardt (University of Colorado Boulder)
Sara Rivero-Calle (University of Southern California, Los Angeles)
Acknowledgments
We would like to thank co-authors on the Rivero-Calle et al. (2015) and Krumhardt et al. (2016) studies for their contributions to the research described. We also would like to thank Nikki Lovenduski and Naomi Levine for helpful comments in composing this OCB Newsletter piece. Many thanks to APL, NSF, NOAA and NASA for funding, and SAHFOS, ICOADS, the BATS research group, and NASA for their long-term data and making it freely available.

References

1. C. L. Sabine et al., Science 305 (2004).
2. Feely et al., Science 305, 362-366 (2004).
3. J. C. Orr et al., Nature 437, 681-686 (2005).
4. K. J. Kroeker et al., Global Change Biology 19, 1884-1896 (2013).
5. B. Rost, U. Riebesell, In Coccolithophores: from Molecular Processes to Global Impact, 99-125 (2004).
6. U. Riebesell et al., Nature 407, 364-367 (2000).
7. C. Klaas, D. E. Archer, Glob.Biogeochem. Cycles 16, (2002).
8. M. D. Keller, W. K. Bellows, R. R. L. Guillard, Acs Symposium Series 393, 167-182 (1989).
9. S. M. Vallina, R. Simo, Science 315, 506-508 (2007).
10. T. Tyrrell, A. Merico, In H. R. Thierstein, J. R. Young, Eds.,Coccolithophores: from Molecular Processes to Global Impact (2004),pp. 75-97.
11. W. M. Balch, In Coccolithophores: from Molecular Processes to Global Impact, 165-190 (2004).
12. M. D. Iglesias-Rodriguez et al., Science 320, 336-340 (2008).
13. S. Sett et al., Plos One 9, (2014).
14. L. T. Bach et al., New Phytol. 199, 121-134 (2013).
15. L. Schluter et al., Nature Clim. Change 4, 1024-1030 (2014).
16. S. Rivero-Calle, A. Gnanadesikan, C. E. Del Castillo, W. M.Balch, S. D. Guikema, Science 350, 1533-1537 (2015).
17. K. M. Krumhardt, N. S. Lovenduski, N. M. Freeman, N. R.Bates, Biogeosci. 13, 1163-1177 (2016).
18. H. Liu et al., Proc. Nat. Acad. Sci. 106, 12803-12808 (2009).
19. Y. Dandonneau, Y. Montel, J. Blanchot, J. Giraudeau, J. Neveux, Deep-Sea Res. Part I-Oceanographic Research Papers 53, 689-712(2006).
20. M. J. Behrenfeld, P. G. Falkowski, Limnol. Oceanogr. 42, 1-20(1997).
21. H. R. Gordon et al. (Geochemical Research Letters, 2001), vol.28, pp. 1587-1590.
22. W. M. Balch, H. R. Gordon, B. C. Bowler, D. T. Drapeau, E. S.
Booth, J. Geophys. Res.Oceans 110 (2005).
23. N. R. Bates et al., Oceanogr. 27, 126-141 (2014).
24. B. Rost, U. Riebesell, S. Burkhardt, D. Sultemeyer, Limnol.Oceanogr. 48, 55-67 (2003).
25. A. Cabr., I. Marinov, S. Leung, Clim.Dyn. 1-28 (2014).
26. L. Bopp, O. Aumont, P. Cadule, S. Alvain, M. Gehlen, Geophys.Res. Lett. 32, (2005).
27. I. Marinov, S. C. Doney, I. D. Lima, Biogeosci. 7, 3941-3959 (2010).
28. Langer et al., Geochem. Geophys. Geosys. 7, (2006).
29. Langer, G. Nehrke, I. Probert, J. Ly, P. Ziveri, Biogeosci. 6, 2637-2646 (2009).
30. C. J. Daniels et al., Marine Ecol. Prog. Ser. 555, 29-47 (2016).
31. M. N. Muller, T. W. Trull, G. M. Hallegraeff, Marine Ecol. Prog.Ser. 531, 81-90 (2015).
32. F. M. Monteiro et al., Science Advances 2, (2016).
33. J. Henjes, P. Assmy, Protist 159, 239-250 (2008).
34. S. Honjo, M. R. Roman, J. Marine Res. 36, 45-57 (1978).
35. R. P. Harris, Marine Biol. 119, 431-439 (1994).
36. J. D. Milliman et al., Deep Sea Res. Part I: Oceanographic Research Papers 46, 1653-1669 (1999).
37. M. Frada, I. Probert, M. J. Allen, W. H. Wilson, C. de Vargas, Proc. Nat. Acad. Sci. 105, 15944-15949 (2008).

Exploring sources of uncertainty in ocean carbon uptake projections

Posted by Katherine Joyce 
· Tuesday, October 25th, 2016 

Having absorbed ~30% of the carbon dioxide released to the atmosphere by human activities, the oceans play an important role in mitigating warming and other climate-related impacts of rising carbon dioxide levels. Predictions of future climate change thus require more accurate projections of ocean carbon uptake. Using two different model suites, a recent study by Lovenduski et al. (2016) published in Global Biogeochemical Cycles documents the relative contributions of internal climate variability, emissions scenario, and model structure to overall uncertainty in ocean carbon uptake predictions on both regional and global scales. Figure from Lovenduski et al. (2016).

« Previous Page

Filter by Keyword

abundance acidification additionality advection africa air-sea air-sea interactions algae alkalinity allometry ammonium AMO AMOC anoxic Antarctic Antarctica anthro impacts anthropogenic carbon anthropogenic impacts appendicularia aquaculture aquatic continuum aragonite saturation arctic Argo argon arsenic artificial seawater AT Atlantic atmospheric CO2 atmospheric nitrogen deposition authigenic carbonates autonomous platforms AUVs bacteria bathypelagic BATS BCG Argo benthic bgc argo bio-go-ship bio-optical bioavailability biogeochemical cycles biogeochemical models biogeochemistry Biological Essential Ocean Variables biological pump biophysics bloom blue carbon bottom water boundary layer buffer capacity C14 CaCO3 calcification calcite carbon carbon-climate feedback carbon-sulfur coupling carbonate carbonate system carbon budget carbon cycle carbon dioxide carbon export carbon fluxes carbon sequestration carbon storage Caribbean CCA CCS changing marine chemistry changing marine ecosystems changing marine environments changing ocean chemistry chemical oceanographic data chemical speciation chemoautotroph chesapeake bay chl a chlorophyll circulation clouds CO2 CO3 coastal and estuarine coastal darkening coastal ocean cobalt Coccolithophores commercial community composition competition conservation cooling effect copepod copepods coral reefs CTD currents cyclone daily cycles data data access data assimilation database data management data product Data standards DCM dead zone decadal trends decomposers decomposition deep convection deep ocean deep sea coral denitrification deoxygenation depth diatoms DIC diel migration diffusion dimethylsulfide dinoflagellate dinoflagellates discrete measurements distribution DOC DOM domoic acid DOP dust DVM ecology economics ecosystem management ecosystems eddy Education EEZ Ekman transport emissions ENSO enzyme equatorial current equatorial regions ESM estuarine and coastal carbon fluxes estuary euphotic zone eutrophication evolution export export fluxes export production extreme events faecal pellets fecal pellets filter feeders filtration rates fire fish Fish carbon fisheries fishing floats fluid dynamics fluorescence food webs forage fish forams freshening freshwater frontal zone functional role future oceans gelatinous zooplankton geochemistry geoengineering geologic time GEOTRACES glaciers gliders global carbon budget global ocean global warming go-ship grazing greenhouse gas greenhouse gases Greenland ground truthing groundwater Gulf of Maine Gulf of Mexico Gulf Stream gyre harmful algal bloom high latitude human food human impact human well-being hurricane hydrogen hydrothermal hypoxia ice age ice cores ice cover industrial onset inland waters in situ inverse circulation ions iron iron fertilization iron limitation isotopes jellies katabatic winds kelvin waves krill kuroshio lab vs field land-ocean continuum larvaceans lateral transport LGM lidar ligands light light attenuation lipids low nutrient machine learning mangroves marine carbon cycle marine heatwave marine particles marine snowfall marshes mCDR mechanisms Mediterranean meltwater mesopelagic mesoscale mesoscale processes metagenome metals methane methods microbes microlayer microorganisms microplankton microscale microzooplankton midwater mitigation mixed layer mixed layers mixing mixotrophs mixotrophy model modeling model validation mode water molecular diffusion MPT MRV multi-decade n2o NAAMES NCP nearshore net community production net primary productivity new ocean state new technology Niskin bottle nitrate nitrogen nitrogen cycle nitrogen fixation nitrous oxide north atlantic north pacific North Sea NPP nuclear war nutricline nutrient budget nutrient cycles nutrient cycling nutrient limitation nutrients OA observations ocean-atmosphere ocean acidification ocean acidification data ocean alkalinity enhancement ocean carbon storage and uptake ocean carbon uptake and storage ocean color ocean modeling ocean observatories ocean warming ODZ oligotrophic omics OMZ open ocean optics organic particles oscillation outwelling overturning circulation oxygen pacific paleoceanography PAR parameter optimization parasite particle flux particles partnerships pCO2 PDO peat pelagic PETM pH phenology phosphate phosphorus photosynthesis physical processes physiology phytoplankton PIC piezophilic piezotolerant plankton POC polar polar regions policy pollutants precipitation predation predator-prey prediction pressure primary productivity Prochlorococcus productivity prokaryotes proteins pteropods pycnocline radioisotopes remineralization remote sensing repeat hydrography residence time resource management respiration resuspension rivers rocky shore Rossby waves Ross Sea ROV salinity salt marsh satellite scale seafloor seagrass sea ice sea level rise seasonal seasonality seasonal patterns seasonal trends sea spray seawater collection seaweed secchi sediments sensors sequestration shelf ocean shelf system shells ship-based observations shorelines siderophore silica silicate silicon cycle sinking sinking particles size SOCCOM soil carbon southern ocean south pacific spatial covariations speciation SST state estimation stoichiometry subduction submesoscale subpolar subtropical sulfate surf surface surface ocean Synechococcus technology teleconnections temperate temperature temporal covariations thermocline thermodynamics thermohaline thorium tidal time-series time of emergence titration top predators total alkalinity trace elements trace metals trait-based transfer efficiency transient features trawling Tris trophic transfer tropical turbulence twilight zone upper ocean upper water column upwelling US CLIVAR validation velocity gradient ventilation vertical flux vertical migration vertical transport warming water clarity water mass water quality waves weathering western boundary currents wetlands winter mixing zooplankton

Copyright © 2025 - OCB Project Office, Woods Hole Oceanographic Institution, 266 Woods Hole Rd, MS #25, Woods Hole, MA 02543 USA Phone: 508-289-2838  •  Fax: 508-457-2193  •  Email: ocb_news@us-ocb.org

link to nsflink to noaalink to WHOI

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.