Sponge skeletons as an important sink of silicon in the global oceans

Silicon (Si) is a pivotal element in the biogeochemical and ecological functioning of the ocean. The marine Si cycle is thought to be in internal equilibrium, but the recent discovery of Si entries through groundwater and glacial melting have increased the known Si inputs relative to the outputs in the global oceans. Known outputs are due to the burying of diatom skeletons or their conversion into authigenic clay by reverse weathering. Here we show that non-phototrophic organisms, such as sponges and radiolarians, also facilitate significant Si burial through their siliceous skeletons. Microscopic examination and digestion of sediments revealed that most burial occurs through sponge skeletons, which, being unusually resistant to dissolution, had passed unnoticed in the biogeochemical inventories of sediments. The preservation of sponge spicules in sediments was 45.2 ± 27.4%, but only 6.8 ± 10.1% for radiolarian testa and 8% for diatom frustules. Sponges lead to a global burial flux of 1.71 ± 1.61 TmolSi yr−1 and only 0.09 ± 0.05 TmolSi yr−1 occurs through radiolarians. Collectively, these two non-phototrophically produced silicas increase the Si output of the ocean to 12.8 TmolSi yr−1, which accounts for a previously ignored sink that is necessary to adequately assess the global balance of the marine Si cycle.


Maldonado, M., López-Acosta, M., Sitjà, C., García-Puig, M., Galobart, C., Ercilla, G., & Leynaert, A. (2019). Sponge skeletons as an important sink of silicon in the global oceans. Nature Geoscience. https://doi.org/10.1038/s41561-019-0430-7


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Compound-specific recording of gadolinium pollution in coastal waters by great scallops

Gadolinium-based contrast agents (GBCAs), routinely used in magnetic resonance imaging (MRI), end up directly in coastal seawaters where gadolinium concentrations are now increasing. Because many aquatic species could be sensitive to this new pollution, we have evaluated the possibility of using shellfish to assess its importance. Gadolinium excesses recorded by scallop shells collected in Bay of Brest (Brittany, France) for more than 30 years do not reflect the overall consumption in GBCAs, but are largely controlled by one of them, the gadopentetate dimeglumine. Although its use has been greatly reduced in Europe over the last ten years, gadolinium excesses are still measured in shells. Thus, some gadolinium derived from other GBCAs is bioavailable and could have an impact on marine wildlife.

Fig. 3b : Gadolinium anomalies (a: Gd/Gd*), gadolinium excesses (b: ΔGd) recorded by scallop shells sampled from 1960 to 2018 in Bay of Brest, and GBCA consumption in France recorded in the Medic’AM database22 maintained by the CPAM (French Health Insurance agency) (c: total consumption and macrocyclic GBCAs, d: linear GBCAs).

These excesses in scallop shells (ΔGd = 0–2.3 ng/g) display a complex temporal evolution (Fig. 3b). The oldest sample collected in 1960, before the use of GBCAs, does not show any significant excess in gadolinium. A marked increase in gadolinium excesses is seen from 1989 to 2005, followed by a sharp decline until 2010 when normal levels are observed again. Afterwards, the excesses seem to increase again without reaching the 2005 maximum, but the data show some spread. Such an evolution is unexpected because the use of GBCAs has always been increasing since their introduction on the market. It could depend on the bioavailability of anthropogenic gadolinium as determined by its speciation in seawater.


Le Goff, S., Barrat, J.-A., Chauvaud, L., Paulet, Y.-M., Gueguen, B., & Salem, D. B. (2019). Compound-specific recording of gadolinium pollution in coastal waters by great scallops. Scientific Reports, 9(1), 8015. https://doi.org/10.1038/s41598-019-44539-y


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In Silico Analysis of Pacific Oyster (Crassostrea gigas) Transcriptome over Developmental Stages Reveals Candidate Genes for Larval Settlement

Valentin FOULON, Pierre BOUDRY, Sébastien ARTIGAUD, Fabienne GUÉRARD et Claire HELLIO

Abstract: Following their planktonic phase, the larvae of benthic marine organisms must locate a suitable habitat to settle and metamorphose. For oysters, larval adhesion occurs at the pediveliger stage with the secretion of a proteinaceous bioadhesive produced by the foot, a specialized and ephemeral organ. Oyster bioadhesive is highly resistant to proteomic extraction and is only produced in very low quantities, which explains why it has been very little examined in larvae to date. In silico analysis of nucleic acid databases could help to identify genes of interest implicated in settlement. In this work, the publicly available transcriptome of Pacific oyster Crassostrea gigas over its developmental stages was mined to select genes highly expressed at the pediveliger stage. Our analysis revealed 59 sequences potentially implicated in adhesion of C. gigas larvae. Some related proteins contain conserved domains already described in other bioadhesives. We propose a hypothetic composition of C. gigas bioadhesive in which the protein constituent is probably composed of collagen and the von Willebrand Factor domain could play a role in adhesive cohesion. Genes coding for enzymes implicated in DOPA chemistry were also detected, indicating that this modification is also potentially present in the adhesive of pediveliger larvae.

Schematic representation of the hypothetical molecular interactions involved in the adhesion of C. gigas pediveliger larvae, based on the selection of genes specifically expressed at the pediveliger stage.


Foulon, V., Boudry, P., Artigaud, S., Guerard, F., and Hellio, C. 2019. In Silico Analysis of Pacific Oyster (Crassostrea gigas) Transcriptome over Developmental Stages Reveals Candidate Genes for Larval Settlement. Int. J. Mol. Sci. 20(1): 197. doi:10.3390/ijms20010197.


Click here for the journal website (article in open access).


A Model of Mercury Distribution in Tuna from the Western and Central Pacific Ocean: Influence of Physiology, Ecology and Environmental Factors

Patrick Houssard, David Point, Laura Tremblay-Boyer, Valérie Allain, Heidi Pethybridge, Jeremy Masbou, Bridget E. Ferriss, Pascale A. Baya, Christelle Lagane, Christophe E. Menkes, Yves Letourneur, et Anne Lorrain



  • Information on ocean scale drivers of methylmercury levels and variability in tuna is scarce, yet crucial in the context of anthropogenic mercury (Hg) inputs and potential threats to human health. Here we assess Hg concentrations in three commercial tuna species (bigeye, yellowfin, and albacore, n = 1000) from the Western and Central Pacific Ocean (WCPO).
  • Models were developed to map regional Hg variance and understand the main drivers. Mercury concentrations are enriched in southern latitudes (10°S−20°S) relative to the equator (0°−10°S) for each species, with bigeye exhibiting the strongest spatial gradients. Fish size is the primary factor explaining Hg variance but physical oceanography also contributes, with higher Hg concentrations in regions exhibiting deeper thermoclines.
  • Tuna trophic position and oceanic primary productivity were of weaker importance. Predictive models perform well in the Central Equatorial Pacific and Hawaii, but underestimate Hg concentrations in the Eastern Pacific. A literature review from the global ocean indicates that size tends to govern tuna Hg concentrations, however regional information on vertical habitats, methylmercury production, and/or Hg inputs are needed to understand Hg distribution at a broader scale. Finally, this study establishes a geographical context of Hg levels to weigh the risks and benefits of tuna consumption in the WCPO.

Observed spatial variation in mercury concentrations (mg*kg −1 , dry weight) for bigeye, yellowfin, and albacore muscle samples captured in the Western and Central Pacific Ocean. Gray lines outline the five biogeochemical regions as defined in Houssard et al., 2017: NPTG (North Pacific Tropical Gyre), WARMm (Warm Pool modified), PEQD (Pacific Equatorial Divergence), SPSGm (South Pacific Subtropical Gyre modified) and ARCHm (Archipelagic deep basins modified) along with AUS-TAZ (Australia-Tasmania) and NZ (New Zealand).


Houssard, P., Point, D., Tremblay-Boyer, L., Allain, V., Pethybridge, H., Masbou, J., Ferriss, B.E., Baya, P.A., Lagane, C., Menkes, C.E., Letourneur, Y., and Lorrain, A. 2019. A Model of Mercury Distribution in Tuna from the Western and Central Pacific Ocean: Influence of Physiology, Ecology and Environmental Factors. Environmental Science & Technology. doi:10.1021/acs.est.8b06058.

Click here for the IRD news about this study (in French).

Modeling reproductive traits of an invasive bivalve species under contrasting climate scenarios from 1960 to 2100

Mélaine Gourault, Sébastien Petton,Yoann Thomas, Laure Pecquerie, Gonçalo M. Marques, Christophe Cassou, Élodie Fleury,Yves-Marie Paulet et Stéphane Pouvreau


  • The DEB model available for the Pacific oyster was applied in a new coastal environment: the bay of Brest (France).
  • This version was successfully calibrated using a new dataset covering 6 years (from 2009 to 2014) of field monitoring.
  • The model successfully predicted in detail the complex reproductive processes of C. gigas, especially its spawning behavior.
  • Hindcasting and forecasting simulations of the reproductive phenology of C. gigas were performed using IPCC scenarios.


Identifying the drivers that control the reproductive success of a population is vital to forecasting the consequences of climate change in terms of distribution shift and population dynamics. In the present study, we aimed to improve our understanding of the environmental conditions that allowed the colonization of the Pacific oyster, Crassostrea gigas, in the Bay of Brest since its introduction in the 1960s. We also aimed to evaluate the potential consequences of future climate change on its reproductive success and further expansion.

Three reproductive traits were defined to study the success of the reproduction: the spawning occurrence, synchronicity among individuals and individual fecundity. We simulated these traits by applying an individual-based modeling approach using a Dynamic Energy Budget (DEB) model. First, the model was calibrated for C. gigas in the Bay of Brest using a 6-year monitoring dataset (2009–2014). Second, we reconstructed past temperature conditions since 1960 in order to run the model backwards (hindcasting analysis) and identified the emergence of conditions that favored increasing reproductive success. Third, we explored the regional consequences of two contrasting IPCC climate scenarios (RCP2.6 and RCP8.5) on the reproductive success of this species in the bay for the 2100 horizon (forecasting analysis). In both analyses, since phytoplankton concentration variations were, at that point, unknown in the past and unpredicted in the future, we made an initial assumption that our six years of observed phytoplankton concentrations were informative enough to represent “past and future possibilities” of phytoplankton dynamics in the Bay of Brest. Therefore, temperature is the variable that we modified under each forecasting and hindcasting runs.

The hindcasting simulations showed that the spawning events increased after 1995, which agrees with the observations made on C. gigas colonization. The forecasting simulations showed that under the warmer scenario (RCP8.5), reproductive success would be enhanced through two complementary mechanisms: more regular spawning each year and potentially precocious spawning resulting in a larval phase synchronized with the most favorable summer period. Our results evidenced that the spawning dates and synchronicity between individuals mainly relied on phytoplankton seasonal dynamics, and not on temperature as expected. Future research focused on phytoplankton dynamics under different climate change scenarios would greatly improve our ability to anticipate the reproductive success and population dynamics of this species and other similar invertebrates.

Figure 4: Oyster growth and spawning simulations obtained by the DEB model compared with observed data from 2009 to 2014 (DFM = Dry Flesh Mass). Observed DFM is represented by black dots with standard deviation bars (n = 30). Grey lines represent individual growth trajectories simulated by the model. The dark red bold line represents the mean of the 30 trajectories.


Gourault, M., Petton, S., Thomas, Y., Pecquerie, L., Marques, G.M., Cassou, C., Fleury, E., Paulet, Y.-M., & Pouvreau, S. 2019. Modeling reproductive traits of an invasive bivalve species under contrasting climate scenarios from 1960 to 2100. Journal of Sea Research 143: 128–139. doi:10.1016/j.seares.2018.05.005.

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