# Carbon budgets within temperate coastal ecosystems and comparaison with picard estuaries (north of France)

Kentin Plègue, Nicolas Spilmont, Lionel Denis

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Kentin Plègue, Nicolas Spilmont, Lionel Denis. Carbon budgets within temperate coastal ecosystems and comparaison with picard estuaries (north of France). Jean-Yves Reynaud; Eric Armynot du Châtelet. Short Papers from the 19th French Congress of Sedimentology, Lille, 84, Association des Sédimentologistes Français, pp.145-150, 2025, 2-907205-83-8. 10.70665/OHCQ6606. hal-05036963

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Submitted on 16 Apr 2025

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# CARBON BUDGETS WITHIN TEMPERATE COASTAL ECOSYSTEMS AND COMPARISON WITH PICARD ESTUARIES (NORTH OF FRANCE)

Kentin Plègue, Nicolas Spilmont and Lionel Denis

Univ. Lille, CNRS, Univ. Littoral Côte d'Opale, IRD, UMR 8187 LOG, Station Marine de Wimereux, F-59000 Lille,
France.

Corresponding author: kentin.plegue@univ-lille.fr

**Abstract:** In estuarine sediments, the balance between organic matter mineralization and primary production determines whether the system is autotrophic (dominated by production processes, i.e. CO₂ sink) or heterotrophic (dominated by respiration/mineralization processes, i.e. CO₂ source). Some autotrophic systems, such as mangroves, seagrass meadows or salt-marshes, are capable of sequestering carbon over long periods, and are referred to as “blue carbon” ecosystems. Salt-marshes are located in the upper part of the estuarine intertidal zone and are only submerged during high tides for a short period. Even if these vegetated areas are generally considered as carbon sinks, the status of the entire intertidal estuarine zone as a “blue carbon” ecosystem is still debated. To accurately assess their carbon sequestration capacity, it is therefore crucial to understand the dynamics of carbon fluxes and stocks in the various typical zones of estuaries (such as channels, mudflats and salt-marshes) across different temporal scales. The aim of this work was to review the knowledge on carbon fluxes and stocks in temperate intertidal ecosystems, particularly within the Picard estuaries (North of France), identify gaps in the current understanding of carbon fluxes and outline objectives and methodologies to quantify the role of these estuaries in carbon sequestration.

**Keywords:** carbon fluxes, salt-marshes, mudflats, intertidal, blue carbon

## 1 INTRODUCTION

Coastal zones, situated at the intersection of land and ocean, include tidal wetlands, estuaries, and continental shelf waters. All of them play a vital role in the global carbon cycle (Duarte *et al.*, 2005). Organic matter mineralization, driven by bacterial activity and respiration, releases carbon as dissolved inorganic carbon (DIC) into the water or as CO₂ into the atmosphere. Conversely, primary production by autotrophs (e.g., microphytobenthos, seagrass, salt-marsh plants) fixes CO₂, with a portion potentially sequestered in sediments. The carbon budget depends on the balance between these processes: a heterotrophic system (carbon source) is characterized by respiration processes exceeding photosynthesis, whereas an autotrophic system (carbon sink) is dominated by photosynthesis. Mcleod *et al.* (2011) defined carbon stored in marine sediments by primary producers as "Blue Carbon"; despite covering only 0.2% of the ocean surface, "Blue Carbon" systems such as mangroves and seagrass meadows can store up to 50% of oceanic carbon (Duarte *et al.*, 2013, Oueslati *et al.*, 2025). However, only a fraction of fixed CO₂ is ultimately buried, as a portion is released back to the environment by mineralization (Liang *et al.*, 2017). The carbon budget based on autotrophy/heterotrophy reflects short-term exchanges, while long-term sequestration depends on complex dynamics. The high spatio-temporal variability of these processes in intertidal systems makes their contribution to carbon sequestration difficult to quantify. Like mangroves and seagrass, salt-marshes have high primary production and contribute significantly to carbon sequestration (Chmura *et al.*, 2003; Duarte *et al.*, 2005). However, less than 10% of carbon fixed by photosynthesis is buried in salt-marshes (Howes *et al.*, 1985), and their role as carbon sinks remains uncertain, due to limited data and the influence of spatio-temporal variations across estuarine habitats (channels, mudflats, low and high shore) over different time scales (tidal cycles, seasonal changes). This review has multiples aims: (i) synthesize the current knowledge on carbon fluxes in temperate intertidal ecosystems, (ii) compare them with data from the Picard estuaries, defined by a mixed energy regime (influenced by both tides and waves and limited freshwater inputs) and a massive sand-platform at the south of their mouths (Voltz *et al.*, 2021), (iii) identify key research gaps.

## 2 MATERIAL AND METHODS

We mainly focused this review (i) on intertidal temperate ecosystems along the Atlantic coast of Western Europe (Figure 1) and (ii) on studies using one of the main measurement methods described below.
<figure><img src="image_2.png" /><figcaption>Figure 1: Location of the different sites in the considered studies.</figcaption></figure>

## 2.1 Measurements at the Sediment/Atmosphere interface

The studies presented two approaches to quantify CO₂ exchanges between sediment and the atmosphere: enclosed systems and atmospheric micro-meteorological measurements. The first approach involves measuring CO₂ concentration in a flow of air passing over a section of the community enclosed within a benthic chamber. Details on the design and use of this type of chamber are provided by Migné et al. (2002). The different measurements were carried out under ambient light and in darkness to estimate Net Community primary Production (NCP) and Community Respiration (CR), respectively. The second approach is based on the eddy-covariance method, which uses wind analysis to quantify net CO₂ exchanges at the ecosystem-atmosphere interface. The details and design of this method are presented in Polsenaere et al. (2012) and Mayen et al. (2024).

## 2.2 Measurements at the Sediment/Water interface

Benthic chambers are also employed to quantify DIC fluxes, using underwater versions of the systems. There is a type of benthic chamber known as "flow through" chamber, which allows continuous measurement of DIC fluxes measurement (Ouisse et al, 2014). Another technique involves core sampling and subsequent ex-situ whole-core incubations (Cores incubations) in the dark (Denis et al., 2001).

# 3 RESULTS

During emersion periods, the ecosystems analyzed exhibited negative CO₂ fluxes under light conditions (i.e., CO₂ uptakes, Table 1) and positive fluxes under dark conditions (i.e., CO₂ efflux, Table 1). There was spatial variability both between the different study sites and among the sediment types within each site (Table 1). For example, the highest CO₂ uptake was measured in the Fier d'Ars salt-marshes, and the highest CO₂ efflux was measured in the low part of the Authie salt-marsh. Moreover, Canche and Authie salt-marshes showed higher CO₂ efflux at dark in summer than the other ecosystems. A seasonal pattern was observed, with more intense CO₂ fluxes during the summer, except in Mont Saint-Michel and Fier d'Ars salt-marshes. During immersion periods, a seasonal pattern was also evident, with higher DIC fluxes in summer compared to spring, when data were available for both seasons (Table 2). A spatial variability was again observed, both between the different study sites and among sediment types within each site. For instance, DIC fluxes were higher in the mudflat and low salt-marsh in Canche estuary during summer compared to other systems. A clear gradient was also observed along the Canche estuary transect, with DIC fluxes decreasing from the mudflat to the high salt-marsh during spring and summer. However, the DIC fluxes measured in Canche remained similar to those in other systems, such as the *Zostera noltei* beds in Roscoff or the sand colonized by *Ruditapes philippinarum* in the Rance estuary during spring.

# 4 DISCUSSION

A part of the variability in carbon fluxes observed between studies can be attributed to methodological differences. Benthic chambers provide localized, low-frequency measurements over small areas (dm²), limiting the integration of large macrophytes, whereas eddy-covariance covers large surface areas (hundreds of m²) but is sensitive to physical variables such as friction velocity.
<table><caption>**Table 1:** Mean CO₂ fluxes (in mmol C m⁻² h⁻¹) during emersion as reported in the literature on French intertidal ecosystems along the Atlantic coast including the locations, sediment types, methods used (Benthic Chambers: BC; Eddy-Covariance: EC) and corresponding references. Negative values indicate a flux from the atmosphere to the sediment, while positive values indicate a flux from the sediment to the atmosphere.</caption><thead><tr><th rowspan="2">Location</th><th rowspan="2">Sediment type</th><th rowspan="2">Method</th><th colspan="2">Winter</th><th colspan="2">Summer</th></tr><tr><th>Light</th><th>Dark</th><th>Light</th><th>Dark</th></tr></thead><tbody><tr><td>Roscoff</td><td>Sand</td><td>BC (Migné et al., 2011)</td><td>-0.2</td><td>0.31</td><td>-1.18</td><td>0.69</td></tr><tr><td>Seine</td><td>Mud</td><td>BC (Spilmont et al., 2006)</td><td>-2.65</td><td>0.48</td><td>-3.54</td><td>1.93</td></tr><tr><td>Seine</td><td>Sand + Mud</td><td>BC (Spilmont et al., 2006)</td><td>-1.76</td><td>0.54</td><td>-5.44</td><td>2.54</td></tr><tr><td>St Michel</td><td>Sand</td><td>BC (Davoult et al., 2009)</td><td>-0.59</td><td>0.17</td><td>-0.54</td><td>0.19</td></tr><tr><td>St Michel</td><td>Mud</td><td>BC (Davoult et al., 2009)</td><td>-1.36</td><td>1.61</td><td>-1.55</td><td>0.77</td></tr><tr><td>Moraix</td><td>Sand + Zostera noltei</td><td>BC (Ouisse et al., 2010)</td><td>-6.4</td><td>1.1</td><td>-4.79</td><td>3.93</td></tr><tr><td>Arcachon</td><td>Sand</td><td>BC (Migné et al., 2016)</td><td>-0.15</td><td>0.17</td><td>-1.33</td><td>0.73</td></tr><tr><td>Arcachon</td><td>Mud</td><td>BC (Migné et al., 2016)</td><td>-2.17</td><td>0.26</td><td>-6.58</td><td>1.2</td></tr><tr><td>Arcachon</td><td>Sand + Zostera noltei</td><td>BC (Migné et al., 2016)</td><td>-1.97</td><td>1.07</td><td>-3.27</td><td>1.86</td></tr><tr><td>Arcachon</td><td>Sand + Zostera noltei</td><td>EC (Polsenaere et al., 2012)</td><td>NA</td><td>NA</td><td>-1.08</td><td>3.24</td></tr><tr><td>Fier d'Ars</td><td>High Salt-marsh</td><td>EC (Mayen et al., 2024)</td><td>-11.34</td><td>9.72</td><td>-15.9</td><td>7.6</td></tr><tr><td>Canche</td><td>Mud</td><td>BC (Karelus, 2024)</td><td>NA</td><td>NA</td><td>-3.41 ± 2.97<br>n = 5</td><td>3.1 ± 1.54<br>n = 6</td></tr><tr><td>Canche</td><td>Low Salt-marsh</td><td>BC (Karelus, 2024)</td><td>NA</td><td>NA</td><td>-6.73 ± 2.26<br>n = 6</td><td>20.51 ± 7.93<br>n = 6</td></tr><tr><td>Canche</td><td>High Salt-marsh</td><td>BC (Karelus, 2024)</td><td>NA</td><td>NA</td><td>-4.10 ± 2.63<br>n = 4</td><td>12.03 ± 3.32<br>n = 5</td></tr><tr><td>Authie</td><td>Sand</td><td>BC (Voltz et al., 2019)</td><td>NA</td><td>NA</td><td>NA</td><td>9.76</td></tr><tr><td>Authie</td><td>Mud</td><td>BC (Voltz et al., 2019)</td><td>NA</td><td>NA</td><td>NA</td><td>9.47</td></tr><tr><td>Authie</td><td>Low Salt-marsh</td><td>BC (Voltz et al., 2019)</td><td>NA</td><td>NA</td><td>NA</td><td>24.73</td></tr><tr><td>Authie</td><td>High Salt-marsh</td><td>BC (Voltz et al., 2019)</td><td>NA</td><td>NA</td><td>NA</td><td>17.78</td></tr></tbody></table>

<table><caption>**Table 2:** Mean DIC fluxes (in mmol C m⁻² h⁻¹) measured in various studies during immersion in spring and summer across different temperate intertidal zones in France and Spain, under dark conditions.</caption><thead><tr><th>Location</th><th>Sediment type</th><th>Method</th><th>Spring</th><th>Summer</th></tr></thead><tbody><tr><td>Canche</td><td>Mud</td><td>Cores incubations (Karelus, 2024)</td><td>4.72 ± 2.08<br>n = 8</td><td>27.3 ± 6.35<br>n = 3</td></tr><tr><td>Canche</td><td>Low Salt-marsh</td><td>Cores incubations (Karelus, 2024)</td><td>3.56 ± 1.34<br>n = 9</td><td>20.56 ± 3.83<br>n = 3</td></tr><tr><td>Canche</td><td>High Salt-marsh</td><td>Cores incubations (Karelus, 2024)</td><td>1.33 ± 0.42<br>n = 9</td><td>7.15 ± 1.74<br>n = 3</td></tr><tr><td>Roscoff</td><td>Sand + Zostera marina</td><td>BC (Ouisse et al., 2011)</td><td>NA</td><td>15.50</td></tr><tr><td>Roscoff</td><td>Sand + Zostera noltei</td><td>BC (Ouisse et al., 2011)</td><td>NA</td><td>9.08</td></tr><tr><td>Roscoff</td><td>Sand + Zostera noltei</td><td>Flow through BC (Ouisse et al., 2014)</td><td>5.04</td><td>7.66</td></tr><tr><td>Rance estuary</td><td>Sand + R. philippinarum (High density)</td><td>BC (Migné et al., 2018)</td><td>4.00</td><td>6.00</td></tr><tr><td>Rance estuary</td><td>Sand + R. philippinarum (Low density)</td><td>BC (Migné et al., 2018)</td><td>NA</td><td>2.00</td></tr><tr><td>Bay of Cadiz</td><td>Sand</td><td>BC (Ortega et al., 2002)</td><td>NA</td><td>2.74</td></tr><tr><td>Ason estuary</td><td>Sand + Salt-Marshes</td><td>BC (Ortega et al., 2002)</td><td>NA</td><td>6.80</td></tr><tr><td>Oka estuary</td><td>Sand</td><td>BC (Ortega et al., 2002)</td><td>NA</td><td>15.75</td></tr></tbody></table>

During emersion, spatial variability both between and within sites can be driven by environmental factors such as vegetation cover, species assemblages, and sediment characteristics. Permeable sandy sediments promote advection, while mudflats retain porewater, and these processes can affect carbon fluxes (Migné et al., 2011). For instance, CO₂ fluxes increase faster in sandy flats (maximum values after one hour, Sasaki et
al., 2009) than in muddy flats (maximum values after three hours, Klaassen & Spilmont, 2012). The seasonal pattern observed at emersion can be driven by light and temperature, which influence photosynthesis and respiration. High temperatures enhance bacterial activity, increasing CO₂ fluxes in summer. During immersion, light attenuation due to water depth and turbidity limits photosynthesis, thereby explaining DIC release from sediment to water (Hoch, 1998). These fluxes can be enhanced by the macrofauna activity, such as bioturbation and excretion. For instance, bioturbation by infaunal organisms (e.g., annelids, bivalves) increases solute and oxygen infiltration (Deborde et al., 2008), and stimulates bacterial activity, while excretion recycles nutrients and consequently promotes primary production (Migné et al., 2018). Moreover, some studies showed that infaunal density can drive DIC fluxes in unvegetated environments, particularly in sandy sediments (Dye, 1981; Asmus, 1982) and mesocosm experiments confirmed that macrofauna increases inorganic carbon release (Gribsholt & Kristensen, 2002). Tidal range and immersion duration also contribute to variability, especially in estuarine transects. High salt-marsh zones, like those in the Canche estuary, are inundated only during spring tides. Seasonal variations in environmental factors such as temperature, riverine inputs, and nutrients further influence benthic metabolism, reinforcing heterotrophic activity and can explain a part of the seasonal pattern of DIC fluxes observed. Moreover, organic matter generally demonstrates higher accumulation rate in the lower part of the salt-marsh during immersion, leading to an increase in bacterial respiration and DIC fluxes.

## 5 CONCLUSION

This study revealed a spatio-temporal variability in carbon fluxes which can be explained by various biotic and abiotic factors such as macrofauna density and plant cover, temperature, immersion/emersion periods or the daylength. An inversion in carbon fluxes during the night is observed, with the system becoming a source of CO₂ under dark conditions as photosynthesis ceases. This inversion is also observed during immersion, where the ecosystem shows positive DIC fluxes. Several challenges and factors must be considered for future studies in the Canche estuary to produce the most reliable carbon budgets, given the complexity of the carbon cycle and flux dynamics. The different biotic and abiotic factors that drive carbon flux dynamics need to be more precisely identified. Additionally, effective methods and sampling strategies should be discussed to obtain a comprehensive understanding of this dynamic at various spatial and temporal scales.

## 6 ACKNOWLEDGEMENTS

This work received financial support from OFB-PNM-EPMO as well as CPER IDEAL program. This work is part of project CABESTAN of the exploratory research program FairCarboN and received government funding managed by the Agence Nationale de la Recherche under the France 2030 program, reference ANR-22-PEXF-0007. This paper was reviewed by Valérie Mesnage and Eric Armynot du Châtelet.

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