# Bivalve tissues as a recorder of multidecadal global anthropogenic and climate-mediated change in coastal areas

Camilla Liénart, Alan Fournioux, Andrius Garbaras, Arnaud Lheureux, Hugues Blanchet, Nicolas Briant, Stanislas F Dubois, Aline Gangnery, Anne Grouhel Pellouin, Pauline Le Monier, et al.

<figure><img src="image_1.png" /></figure>

## To cite this version:

Camilla Liénart, Alan Fournioux, Andrius Garbaras, Arnaud Lheureux, Hugues Blanchet, et al. Bivalve tissues as a recorder of multidecadal global anthropogenic and climate-mediated change in coastal areas. Limnology and Oceanography Letters, In press, 10.1002/lol2.10399. hal-04575913

HAL Id: hal-04575913

https://hal.science/hal-04575913

Submitted on 15 May 2024

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Bivalve tissues as a recorder of multidecadal global anthropogenic and climate-mediated change in coastal areas

Camilla Liénart, Alan Fournioux, Andrius Garbaras, Arnaud Lheureux, Hugues Blanchet, Nicolas Briant, Stanislas F Dubois, Aline Gangnery, Anne Grouhel Pellouin, Pauline Le Monier, et al.

► To cite this version:

Camilla Liénart, Alan Fournioux, Andrius Garbaras, Arnaud Lheureux, Hugues Blanchet, et al. Bivalve tissues as a recorder of multidecadal global anthropogenic and climate-mediated change in coastal areas. Limnology and Oceanography Letters, In press, 10.1002/lol2.10399. hal-04575913

HAL Id: hal-04575913

https://hal.science/hal-04575913v1

Submitted on 15 May 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
## LETTER

# Bivalve tissues as a recorder of multidecadal global anthropogenic and climate-mediated change in coastal areas

Camilla Liénart<sup>1,*</sup> Alan Fournioux,<sup>1</sup> Andrius Garbaras<sup>1,2</sup> Arnaud Lheureux<sup>1,3</sup> Hugues Blanchet<sup>1</sup> Nicolas Briant,<sup>4</sup>

Stanislas F. Dubois<sup>1,5</sup> Aline Gangnery<sup>1,5</sup> Anne Grouhel Pellouin<sup>1,4</sup> Pauline Le Monier,<sup>4</sup> Xavier De Montaudouin,<sup>1</sup> Nicolas Savoye<sup>1</sup>

<sup>1</sup>Université de Bordeaux, CNRS, Bordeaux INP, EPOC, UMR 5805, Pessac, France; <sup>2</sup>Center for Physical Sciences and Technology, Vilnius, Lithuania; <sup>3</sup>Laboratoire de Biologie des Organismes et Écosystèmes Aquatiques (BOREA), MNHN, CNRS, IRD, SU, UCN, UA, CP53, Paris, France; <sup>4</sup>Ifremer, CCEM Contamination Chimique des Écosystèmes Marins, Nantes, France; <sup>5</sup>Ifremer, DYNECO, Plouzané, France

### Scientific Significance Statement

Global change affects physicochemical and biological compartments of coastal ecosystems from global to local scales. However, the multiple and interacting effects make it challenging to identify what causes ecosystem responses. By using bivalve species as a recorder of environmental changes, this study provides the evidence for global effects of anthropogenic activities (bivalves reflect the isotopic signal of atmospheric CO₂, which is directly affected by anthropogenic activities) and of climate change on coastal ecosystems at global scale, with possible cumulative, synergistic or antagonistic regional and/or local effects. This research is contributing to crucial understanding of coastal ecosystems responses to environmental and climate change.

### Abstract

Recent rapid changes in climate and environmental conditions have significantly impacted coastal ecosystem functioning. However, the complex interplay between global and local effects makes it challenging to pinpoint the primary drivers. In a multi-ecosystem study, we analyzed pluri-decadal trends of bivalve-$\delta^{13}$C as recorder of global environmental changes. These trends were correlated with large-scale natural and anthropogenic climate proxies to identify whether coastal biota responded to global effects. Our findings revealed decreasing bivalve-$\delta^{13}$C trends in all sea regions, mainly linked with increased temperature and atmospheric-CO$_2$

<footnote>*Correspondence: camilla.lienart@u-bordeaux.fr</footnote>

<footnote>Associate editor: Dick van Oevelen</footnote>

<footnote>**Author Contribution Statement:** LC performed conceptualization, methodology, investigation, formal analysis, visualization, writing–original draft preparation (lead). FA involved in investigation, formal analysis, visualization, review, and editing. G. Andrius did investigation. LA did investigation, formal analysis, review, and editing. BH performed conceptualization, methodology, review, and editing. BN performed investigation, review, and editing. FDS performed conceptualization, methodology, review, and editing. G. Aline performed investigation, review, and editing. GPA performed methodology, investigation, review, and editing. LMP did Investigation. deMX performed conceptualization, methodology, review, and editing. SN performed conceptualization, methodology, writing–review and editing.</footnote>

<footnote>**Data Availability Statement:** Data and metadata are uploaded in a freely accessible repository (Figshare) under the permanent identifier https://doi.org/10.6084/m9 figshare.24884871.v1.</footnote>

<footnote>Additional Supporting Information may be found in the online version of this article.</footnote>

<footnote>This is an open access article under the terms of the [Creative Commons Attribution License](https://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.</footnote>
## LETTER

# Bivalve tissues as a recorder of multidecadal global anthropogenic and climate-mediated change in coastal areas

Camilla Liénart<sup>1,*</sup> Alan Fournioux,<sup>1</sup> Andrius Garbaras<sup>1,2</sup> Arnaud Lheureux<sup>1,3</sup> Hugues Blanchet<sup>1</sup> Nicolas Briant,<sup>4</sup>

Stanislas F. Dubois<sup>1,5</sup> Aline Gangnery<sup>1,5</sup> Anne Grouhel Pellouin<sup>1,4</sup> Pauline Le Monier,<sup>4</sup> Xavier De Montaudouin,<sup>1</sup> Nicolas Savoye<sup>1</sup>

<sup>1</sup>Université de Bordeaux, CNRS, Bordeaux INP, EPOC, UMR 5805, Pessac, France; <sup>2</sup>Center for Physical Sciences and Technology, Vilnius, Lithuania; <sup>3</sup>Laboratoire de Biologie des Organismes et Écosystèmes Aquatiques (BOREA), MNHN, CNRS, IRD, SU, UCN, UA, CP53, Paris, France; <sup>4</sup>Ifremer, CCEM Contamination Chimique des Écosystèmes Marins, Nantes, France; <sup>5</sup>Ifremer, DYNECO, Plouzané, France

### Scientific Significance Statement

Global change affects physicochemical and biological compartments of coastal ecosystems from global to local scales. However, the multiple and interacting effects make it challenging to identify what causes ecosystem responses. By using bivalve species as a recorder of environmental changes, this study provides the evidence for global effects of anthropogenic activities (bivalves reflect the isotopic signal of atmospheric CO₂, which is directly affected by anthropogenic activities) and of climate change on coastal ecosystems at global scale, with possible cumulative, synergistic or antagonistic regional and/or local effects. This research is contributing to crucial understanding of coastal ecosystems responses to environmental and climate change.

### Abstract

Recent rapid changes in climate and environmental conditions have significantly impacted coastal ecosystem functioning. However, the complex interplay between global and local effects makes it challenging to pinpoint the primary drivers. In a multi-ecosystem study, we analyzed pluri-decadal trends of bivalve-δ¹³C as recorder of global environmental changes. These trends were correlated with large-scale natural and anthropogenic climate proxies to identify whether coastal biota responded to global effects. Our findings revealed decreasing bivalve-δ¹³C trends in all sea regions, mainly linked with increased temperature and atmospheric-CO₂

<footnote>*Correspondence: camilla.lienart@u-bordeaux.fr</footnote>

<footnote>Associate editor: Dick van Oevelen</footnote>

<footnote>**Author Contribution Statement:** LC performed conceptualization, methodology, investigation, formal analysis, visualization, writing-original draft preparation (lead). FA involved in investigation, formal analysis, visualization, review, and editing. G. Andrius did investigation. LA did investigation, formal analysis, review, and editing. BH performed conceptualization, methodology, review, and editing. BN performed investigation, review, and editing. FDS performed conceptualization, methodology, review, and editing. G. Aline performed investigation, review, and editing. GPA performed methodology, investigation, review, and editing. LMP did Investigation. deMX performed conceptualization, methodology, review, and editing. SN performed conceptualization, methodology, writing-review and editing.</footnote>

<footnote>**Data Availability Statement:** Data and metadata are uploaded in a freely accessible repository (Figshare) under the permanent identifier https://doi.org/10.6084/m9.figshare.24884871.v1.</footnote>

<footnote>Additional Supporting Information may be found in the online version of this article.</footnote>

<footnote>This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.</footnote>
concentrations, the later generating a decrease in atmospheric-CO₂ δ¹³C values (Suess effect) because of fossil-fuel burning. After removing the Suess effect from bivalve-δ¹³C trends, ongoing global climate variability continues to affect most ecosystems, possibly intensified by combined, interacting regional or local effects. These results highlight the need to consider large-scale effects to fully understand ecosystem and food web responses to the multiple effects of global change.

Over the past decades, the world ocean has undergone rapid climate and environmental changes with significant consequences on ecosystem functioning and services (Halpern et al. 2008; Bauer et al. 2013; Bartley et al. 2019; Benedetti et al. 2021; Cael et al. 2023). Coastal marine ecosystems form a dynamic land-ocean interface holding substantial ecological and economic value (Barbier et al. 2011). As the ultimate receptacle of dissolved and particulate continental inputs from natural and anthropogenic origin, these ecosystems are highly productive yet particularly sensitive to the multiple and interacting pressures of global change acting at various spatial and temporal scales (Harley et al. 2006). Climate and human-induced changes in precipitations, river discharge, nutrients load or land use, alter organic matter transformation and ultimately nutrient cycling and productivity along the land-ocean continuum (Milliman et al. 2008; Bauer et al. 2013). A key challenge remains to understand how the different components of global change affect coastal ecosystems responses.

Global change refers to planetary-scale changes in the Earth system encompassing interacting physicochemical and biological compartments, and human societies. It comprises the global climate (i.e., natural and anthropogenic components) and other, mostly local, human activities (e.g., land use, pollution) that affect ecosystems. Local changes may interact with global climate-induced changes in antagonistic, cumulative, or synergistic ways, thereby exacerbating ecosystems response (Harley et al. 2006; Cabral et al. 2019). Therefore, disentangling global from regional and or local effects is crucial for the understanding of coastal ecosystem functioning, especially to improve predictive scenarios and adapt management and conservation strategies.

Carbon is the primary currency in addressing global change. Carbon stable isotope (δ¹³C) is commonly used to understand physical-chemical processes in the ocean: it helps tracing organic matter origin and fate (Bristow et al. 2013) and to reveal global anthropogenic impact such as direct effect of increasing carbon dioxide (CO₂) emissions from anthropogenic activities (Quay et al. 2007). The CO₂ emitted by fossil fuels burning (e.g., coal, oil, and natural gas) has a lower proportion of ¹³C than the CO₂ naturally present in the atmosphere and dilute the overall concentration of ¹³C at global scale, creating the Suess effect (i.e., decline in global atmospheric δ¹³C values by 1.8‰ since the industrial revolution in 1850 to present day; Keeling 1979; Gruber et al. 1999; Graven et al. 2017; Dombrosky 2020). Low δ¹³C-CO₂

dissolved in seawater is biologically incorporated by primary producers during photosynthesis and propagates along the food web (e.g., Schloesser et al. 2009; Liénart et al. 2022), and potentially masks local influence of ¹³C-depleted sources (e.g., continental material from rivers; Liénart et al. 2017, 2022). Increasing anthropogenic CO₂ emissions also indirectly affects marine ecosystems through temperature increase leading, for example, to altered CO₂ solubility in water, phytoplankton phenology or precipitation patterns and river runoffs (Pörtner et al. 2005; Gittings et al. 2018; van Vliet et al. 2013).

Bivalve species, as bioindicators for environmental monitoring, offer an integrated view of the environmental conditions of their habitat through sessile, filter-feeding lifestyles (Briant et al. 2021; Karlson and Faxneld 2021; Chahouri et al. 2023). Measuring δ¹³C of bivalve tissues allows to trace dietary carbon resources (Magni et al. 2013) and its flows in food webs over space and time (Vander Zanden and Rasmussen 1999; Corman et al. 2018), and to understand ecological consequences of environmental changes in ecosystem functioning (Liénart et al. 2020). Bivalve-δ¹³C is primarily influenced by local dietary changes and physiological processes but global effects, like the Suess effect, can mask these processes in long-term isotope trends, hindering for precise interpretations of change (Clark et al. 2021). Considering Suess effect in isotope data is critical to unravel pure anthropogenic effects (fossil fuel burning) from other global and regional/local pressures.

Previous studies addressing global change from pluri-decadal trends of bivalve-δ¹³C found a link to climate change (Briant et al. 2018; Corman et al. 2018), with only few statistical evidence for indirect climate effects (Liénart et al. 2020, 2022). However, no study had distinctly estimated and removed global effects, particularly the Suess effect, before further examining other processes. Our study address whether pluri-decadal trends in bivalve-δ¹³C are due to the Suess effect, and if, when corrected, other global effects persist. In a multiecosystem approach, we measured δ¹³C in mussels and oysters across 32 stations in six contrasted sea regions, over four-decades time series (1981-2021). We correlated multidecadal changes in bivalve-δ¹³C with time-series of large-scale anthropogenic and climate proxies to identify global effects. By studying bivalve-δ¹³C time-series as a record of environmental changes, this study examines global effects of anthropogenic activities (i.e., reflect the isotopic signal of increased atmospheric CO₂) and of climate change on coastal temperate ecosystems at broad spatial scale.
concentrations, the later generating a decrease in atmospheric-CO₂ δ¹³C values (Suess effect) because of fossil-fuel burning. After removing the Suess effect from bivalve-δ¹³C trends, ongoing global climate variability continues to affect most ecosystems, possibly intensified by combined, interacting regional or local effects. These results highlight the need to consider large-scale effects to fully understand ecosystem and food web responses to the multiple effects of global change.

Over the past decades, the world ocean has undergone rapid climate and environmental changes with significant consequences on ecosystem functioning and services (Halpern et al. 2008; Bauer et al. 2013; Bartley et al. 2019; Benedetti et al. 2021; Cael et al. 2023). Coastal marine ecosystems form a dynamic land-ocean interface holding substantial ecological and economic value (Barbier et al. 2011). As the ultimate receptacle of dissolved and particulate continental inputs from natural and anthropogenic origin, these ecosystems are highly productive yet particularly sensitive to the multiple and interacting pressures of global change acting at various spatial and temporal scales (Harley et al. 2006). Climate and human-induced changes in precipitations, river discharge, nutrients load or land use, alter organic matter transformation and ultimately nutrient cycling and productivity along the land-ocean continuum (Milliman et al. 2008; Bauer et al. 2013). A key challenge remains to understand how the different components of global change affect coastal ecosystems responses.

Global change refers to planetary-scale changes in the Earth system encompassing interacting physicochemical and biological compartments, and human societies. It comprises the global climate (i.e., natural and anthropogenic components) and other, mostly local, human activities (e.g., land use, pollution) that affect ecosystems. Local changes may interact with global climate-induced changes in antagonistic, cumulative, or synergistic ways, thereby exacerbating ecosystems response (Harley et al. 2006; Cabral et al. 2019). Therefore, disentangling global from regional and or local effects is crucial for the understanding of coastal ecosystem functioning, especially to improve predictive scenarios and adapt management and conservation strategies.

Carbon is the primary currency in addressing global change. Carbon stable isotope (δ¹³C) is commonly used to understand physical-chemical processes in the ocean: it helps tracing organic matter origin and fate (Bristow et al. 2013) and to reveal global anthropogenic impact such as direct effect of increasing carbon dioxide (CO₂) emissions from anthropogenic activities (Quay et al. 2007). The CO₂ emitted by fossil fuels burning (e.g., coal, oil, and natural gas) has a lower proportion of ¹³C than the CO₂ naturally present in the atmosphere and dilute the overall concentration of ¹³C at global scale, creating the Suess effect (i.e., decline in global atmospheric δ¹³C values by 1.8‰ since the industrial revolution in 1850 to present day; Keeling 1979; Gruber et al. 1999; Graven et al. 2017; Dombrosky 2020). Low δ¹³C-CO₂

dissolved in seawater is biologically incorporated by primary producers during photosynthesis and propagates along the food web (e.g., Schloesser et al. 2009; Liénart et al. 2022), and potentially masks local influence of ¹³C-depleted sources (e.g., continental material from rivers; Liénart et al. 2017, 2022). Increasing anthropogenic CO₂ emissions also indirectly affects marine ecosystems through temperature increase leading, for example, to altered CO₂ solubility in water, phytoplankton phenology or precipitation patterns and river runoffs (Pörtner et al. 2005; Gittings et al. 2018; van Vliet et al. 2013).

Bivalve species, as bioindicators for environmental monitoring, offer an integrated view of the environmental conditions of their habitat through sessile, filter-feeding lifestyles (Briant et al. 2021; Karlson and Faxneld 2021; Chahouri et al. 2023). Measuring δ¹³C of bivalve tissues allows to trace dietary carbon resources (Magni et al. 2013) and its flows in food webs over space and time (Vander Zanden and Rasmussen 1999; Corman et al. 2018), and to understand ecological consequences of environmental changes in ecosystem functioning (Liénart et al. 2020). Bivalve-δ¹³C is primarily influenced by local dietary changes and physiological processes but global effects, like the Suess effect, can mask these processes in long-term isotope trends, hindering for precise interpretations of change (Clark et al. 2021). Considering Suess effect in isotope data is critical to unravel pure anthropogenic effects (fossil fuel burning) from other global and regional/local pressures.

Previous studies addressing global change from pluri-decadal trends of bivalve-δ¹³C found a link to climate change (Briant et al. 2018; Corman et al. 2018), with only few statistical evidence for indirect climate effects (Liénart et al. 2020, 2022). However, no study had distinctly estimated and removed global effects, particularly the Suess effect, before further examining other processes. Our study address whether pluri-decadal trends in bivalve-δ¹³C are due to the Suess effect, and if, when corrected, other global effects persist. In a multiecosystem approach, we measured δ¹³C in mussels and oysters across 32 stations in six contrasted sea regions, over four-decades time series (1981-2021). We correlated multidecadal changes in bivalve-δ¹³C with time-series of large-scale anthropogenic and climate proxies to identify global effects. By studying bivalve-δ¹³C time-series as a record of environmental changes, this study examines global effects of anthropogenic activities (i.e., reflect the isotopic signal of increased atmospheric CO₂) and of climate change on coastal temperate ecosystems at broad spatial scale.
# Methods

## Archived samples

Since the late 1970s, the French National Monitoring Network “ROCCH” (“Réseau d’Observation de la Contamination CHimique,” operated by IFREMER) uses bivalves from three different species as bioindicators of chemical contamination: the Pacific oyster *Crassostrea gigas*, and the blue mussels *Mytilus edulis* and *Mytilus galloprovincialis* (Fig. 1; see Supporting Information S1 for detailed sampling protocol). For the purpose of this study, we analyzed 1136 archived bivalves soft-tissues samples (total soft-tissues) from the ROCCH network, across 32 stations of six sea regions (Fig. 1,

English Channel; Western Brittany; Northern Bay of Biscay; Central Bay of Biscay; Arcachon Lagoon; Gulf of Lion) spanning 21–40 years over the period 1981–2021 (one sample per year, collected in mid-February ± 3 weeks, i.e., during low growth, mostly during non-reproductive period, to minimize the effects of lipids associated with gametogenesis as lipids are ¹³C depleted, Post et al. 2007). The stations were specifically selected to reflect environmental gradients on both large and local scale (Lheureux et al. 2023), for example, tidal regimes (microtidal to megatidal), climates (temperate, oceanic, Mediterranean), trophic status (oligotrophic to eutrophic), continental influence (gradients of influence of rivers).

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Geographical location of the 32 stations sampled for bivalves (*M. edulis*: blue circles, *M. galloprovincialis*: green triangles, *C. gigas*: orange squares) in the six sea regions (English Channel; Western Brittany; Northern Bay of Biscay; Central Bay of Biscay; Arcachon Lagoon; Gulf of Lion) over the period 1981–2021. At each station, only one of the three species was sampled: *M. edulis* in the English Channel and at two stations of the Northern Bay of Biscay, *C. gigas* in Western Brittany, Central Bay of Biscay, Arcachon Lagoon and three stations of the Northern Bay of Biscay, and *M. galloprovincialis* in the Gulf of Lion. The main river influencing the regions are represented by blue lines. The full list of station names is available in Supporting Information S1. Note that there is no Station number 17.</figcaption></figure>
# Methods

## Archived samples

Since the late 1970s, the French National Monitoring Network “ROCCH” (“Réseau d’Observation de la Contamination CHimique,” operated by IFREMER) uses bivalves from three different species as bioindicators of chemical contamination: the Pacific oyster *Crassostrea gigas*, and the blue mussels *Mytilus edulis* and *Mytilus galloprovincialis* (Fig. 1; see Supporting Information S1 for detailed sampling protocol). For the purpose of this study, we analyzed 1136 archived bivalves soft-tissues samples (total soft-tissues) from the ROCCH network, across 32 stations of six sea regions (Fig. 1,

English Channel; Western Brittany; Northern Bay of Biscay; Central Bay of Biscay; Arcachon Lagoon; Gulf of Lion) spanning 21–40 years over the period 1981–2021 (one sample per year, collected in mid-February ± 3 weeks, i.e., during low growth, mostly during non-reproductive period, to minimize the effects of lipids associated with gametogenesis as lipids are ¹³C depleted, Post et al. 2007). The stations were specifically selected to reflect environmental gradients on both large and local scale (Lheureux et al. 2023), for example, tidal regimes (microtidal to megatidal), climates (temperate, oceanic, Mediterranean), trophic status (oligotrophic to eutrophic), continental influence (gradients of influence of rivers).

<figure><img src="image_2.png" /><figcaption>**Fig. 1.** Geographical location of the 32 stations sampled for bivalves (*M. edulis*: blue circles, *M. galloprovincialis*: green triangles, *C. gigas*: orange squares) in the six sea regions (English Channel; Western Brittany; Northern Bay of Biscay; Central Bay of Biscay; Arcachon Lagoon; Gulf of Lion) over the period 1981–2021. At each station, only one of the three species was sampled: *M. edulis* in the English Channel and at two stations of the Northern Bay of Biscay, *C. gigas* in Western Brittany, Central Bay of Biscay, Arcachon Lagoon and three stations of the Northern Bay of Biscay, and *M. galloprovincialis* in the Gulf of Lion. The main river influencing the regions are represented by blue lines. The full list of station names is available in Supporting Information S1. Note that there is no Station number 17.</figcaption></figure>
Carbon stable isotope analysis

We analyzed aliquots of 400–700 µg of bivalve tissues of each archived sample for δ¹³C at the Center for Physical Science and Technology (Vilnius, Lithuania) with a Flash EA 1112 Series Elemental Analyzer (Thermo Finnigan) connected to a DeltaV Advantage Isotope Ratio Mass Spectrometer (Thermo Fisher). Results are expressed in per mil (‰) deviation from international references (see Supporting Information S1). Analytical precision was <0.15‰. Isotope data are available in the Figshare repository under the DOI 10.6084/m9 figshare.24884871.

Proxies for global environmental change

We compiled publicly available data over the period 1981–2021 for five hydro-climatic teleconnection indices representing climate patterns in the Northern hemisphere (see Supporting Information Fig. S1). Two indices are based on temperatures: the Atlantic Multidecadal Oscillation (AMO; Enfield et al. 2001) represents changes in the north Atlantic Ocean surface temperature after removing the anthropogenic component (effect of increasing greenhouse gases), whereas the Northern Hemisphere temperature (NHT) anomalies are calculated from North Atlantic 1901–2000 temperature average. Three indices are based on atmospheric pressures: the North Atlantic Oscillation (NAO; Hurrell 1995; Hurrell and Deser 2009) corresponds to the pressure difference between the Azores High and Icelandic Low; the East Atlantic Pattern (EAP; Barnston and Livezey 1987) values consist in a north–south dipole of pressure anomalies centered on the north Atlantic from east to west; the Arctic Oscillation (AO) is based on atmospheric pressures and is related to the Arctic climate and its southern incursions (Higgins et al. 2000). We used globally averaged North-Hemisphere atmospheric CO₂ concentrations (CO₂atm; Lan et al. 2023) and δ¹³C of atmospheric CO₂ (δ¹³C-CO₂atm; Graven et al. 2017) as global effect proxies resulting from anthropogenic activities. For each proxy and time series, we recalculated yearly averages based on the 12 months preceding bivalve sampling in order to integrate a temporal lag in bivalve-δ¹³C (except for δ¹³C-CO₂atm and seawater δ¹³C-CO₂, see below, where the previous calendar year was selected). Data origin and calculation details are available in Supporting Information S1.

The Suess effect

A step-by-step calculation of Suess effect is available in Supporting Information S1. Briefly, we calculated δ¹³C of CO₂ dissolved in seawater (δ¹³C-CO₂aq) for each region by adding the corresponding regional isotopic fractionation (ε) value to global δ¹³C-CO₂atm for each year on the period 1980–2021 (Table S1). The fractionation between gaseous and dissolved CO₂ phases was calculated from the equation of Vogel et al. (1970) as given by Mook (2000), and Zeebe and Wolf-Gladrow (2001): ε<sub>d/g</sub> = -373/T + 0.19‰ (T: absolute temperature in Kelvin). Despite differences in temperature within each time series and between regions, differences in

calculated ε, hence in δ¹³C-CO₂aq values was much lower than the analytical precision for bivalves-δ¹³C (see Supporting Information S1). Therefore, we used the average δ¹³C-CO₂aq value of all regions as a proxy to compare with bivalves-δ¹³C in statistical tests. Finally, we calculated regional slopes of δ¹³C-CO₂aq (i.e., the Suess effect) which was the same for all regions (–0.243‰ decade⁻¹, Table S1), and removed it from bivalve-δ¹³C cumulatively for each year (starting from year 1981) to obtain Suess-corrected bivalve-δ¹³C (bivalve-δ¹³C<sub>corr</sub>) for each station.

Equilibrium between δ¹³C-CO₂atm and δ¹³C-CO₂aq, and δ¹³C in phytoplankton and bivalves (i.e., tissue turnover) are possible processes altering δ¹³C signal propagation to bivalves. Considering that these lags are constant over years, it does not affect the multidecadal δ¹³C trends we are investigating. Also, we did not consider seasonal variation in atmospheric CO₂, nor in the δ¹³C of aquatic CO₂ linked to phytoplankton activity as we were looking at long-term trends in annual means. Hence, we considered equilibrium between atmosphere and seawater and calculated the trends of δ¹³C-CO₂aq as if the Suess effect was the only process occurring (i.e., considering physical-chemical processes only, Affek and Yakir 2014).

Statistical analyses

We examined unidirectional temporal trends in bivalve-
δ¹³C times series for each station with Mann-Kendall tests
corrected for autocorrelation (R-package "modifiedmk,"
Patakamuri and O'Brien 2021). We applied linear models to
calculate the value of the slope (in ‰ decade⁻¹). Over the
same time period, we evaluated relationships (1) in bivalve-
δ¹³C time series between pairs of stations and (2) between
bivalve-δ¹³C time series and global proxies using Spearman
two-sided correlation tests (p-values corrected for multiple
testing with Benjamini-Hochberg procedure). For reliable
comparison between datasets, we tested the trends on a
common period of three decades (1990–2021) corresponding
to 30 ± 2 years (criterion met for 28 stations), whereas corre-
lations were performed on complete datasets. Statistical ana-
lyses were performed with the R software (R Core
Team 2022).

Results

Pluri-decadal trends in bivalve-δ¹³C

During a shared period of 30 ± 2 years (1990–2021), bivalve-δ¹³C signal exhibited a significant decrease at 93% of the stations (26/28; Fig. 2, Table 1). The average decrease was –0.58 ± 0.24‰ decade⁻¹, ranging from –1.08 to –0.22‰ decade⁻¹ (i.e. –3.24 to –0.65‰ over 30 years). The decrease was not significant at only three stations (two in English Channel, one in Northern Bay of Biscay, over 30 years). Within each region, between station pairs, there were 80–100% of significant correlations in bivalve-δ¹³C in
Carbon stable isotope analysis

We analyzed aliquots of 400–700 µg of bivalve tissues of each archived sample for δ¹³C at the Center for Physical Science and Technology (Vilnius, Lithuania) with a Flash EA 1112 Series Elemental Analyzer (Thermo Finnigan) connected to a DeltaV Advantage Isotope Ratio Mass Spectrometer (Thermo Fisher). Results are expressed in per mil (‰) deviation from international references (see Supporting Information S1). Analytical precision was <0.15‰. Isotope data are available in the Figshare repository under the DOI 10.6084/m9 figshare. 24884871.

Proxies for global environmental change

We compiled publicly available data over the period 1981–2021 for five hydro-climatic teleconnection indices representing climate patterns in the Northern hemisphere (see Supporting Information Fig. S1). Two indices are based on temperatures: the Atlantic Multidecadal Oscillation (AMO; Enfield et al. 2001) represents changes in the north Atlantic Ocean surface temperature after removing the anthropogenic component (effect of increasing greenhouse gases), whereas the Northern Hemisphere temperature (NHT) anomalies are calculated from North Atlantic 1901–2000 temperature average. Three indices are based on atmospheric pressures: the North Atlantic Oscillation (NAO; Hurrell 1995; Hurrell and Deser 2009) corresponds to the pressure difference between the Azores High and Icelandic Low; the East Atlantic Pattern (EAP; Barnston and Livezey 1987) values consist in a north–south dipole of pressure anomalies centered on the north Atlantic from east to west; the Arctic Oscillation (AO) is based on atmospheric pressures and is related to the Arctic climate and its southern incursions (Higgins et al. 2000). We used globally averaged North-Hemisphere atmospheric CO₂ concentrations (CO₂atm; Lan et al. 2023) and δ¹³C of atmospheric CO₂ (δ¹³C-CO₂atm; Graven et al. 2017) as global effect proxies resulting from anthropogenic activities. For each proxy and time series, we recalculated yearly averages based on the 12 months preceding bivalve sampling in order to integrate a temporal lag in bivalve-δ¹³C (except for δ¹³C-CO₂atm and seawater δ¹³C-CO₂, see below, where the previous calendar year was selected). Data origin and calculation details are available in Supporting Information S1.

The Suess effect

A step-by-step calculation of Suess effect is available in Supporting Information S1. Briefly, we calculated δ¹³C of CO₂ dissolved in seawater (δ¹³C-CO₂aq) for each region by adding the corresponding regional isotopic fractionation (ε) value to global δ¹³C-CO₂atm for each year on the period 1980–2021 (Table S1). The fractionation between gaseous and dissolved CO₂ phases was calculated from the equation of Vogel et al. (1970) as given by Mook (2000), and Zeebe and Wolf-Gladrow (2001): ε<sub>d/g</sub> = -373/T + 0.19‰ (T: absolute temperature in Kelvin). Despite differences in temperature within each time series and between regions, differences in

calculated ε, hence in δ¹³C-CO₂aq values was much lower than the analytical precision for bivalves-δ¹³C (see Supporting Information S1). Therefore, we used the average δ¹³C-CO₂aq value of all regions as a proxy to compare with bivalves-δ¹³C in statistical tests. Finally, we calculated regional slopes of δ¹³C-CO₂aq (i.e., the Suess effect) which was the same for all regions (–0.243‰ decade⁻¹, Table S1), and removed it from bivalve-δ¹³C cumulatively for each year (starting from year 1981) to obtain Suess-corrected bivalve-δ¹³C (bivalve-δ¹³C<sub>corr</sub>) for each station.

Equilibrium between δ¹³C-CO₂atm and δ¹³C-CO₂aq, and δ¹³C in phytoplankton and bivalves (i.e., tissue turnover) are possible processes altering δ¹³C signal propagation to bivalves. Considering that these lags are constant over years, it does not affect the multidecadal δ¹³C trends we are investigating. Also, we did not consider seasonal variation in atmospheric CO₂, nor in the δ¹³C of aquatic CO₂ linked to phytoplankton activity as we were looking at long-term trends in annual means. Hence, we considered equilibrium between atmosphere and seawater and calculated the trends of δ¹³C-CO₂aq as if the Suess effect was the only process occurring (i.e., considering physical–chemical processes only, Affek and Yakir 2014).

Statistical analyses

We examined unidirectional temporal trends in bivalve-
δ¹³C times series for each station with Mann-Kendall tests
corrected for autocorrelation (R-package "modifiedmk,"
Patakamuri and O'Brien 2021). We applied linear models to
calculate the value of the slope (in ‰ decade⁻¹). Over the
same time period, we evaluated relationships (1) in bivalve-
δ¹³C time series between pairs of stations and (2) between
bivalve-δ¹³C time series and global proxies using Spearman
two-sided correlation tests (p-values corrected for multiple
testing with Benjamini-Hochberg procedure). For reliable
comparison between datasets, we tested the trends on a
common period of three decades (1990–2021) corresponding
to 30 ± 2 years (criterion met for 28 stations), whereas corre-
lations were performed on complete datasets. Statistical ana-
lyses were performed with the R software (R Core
Team 2022).

Results

Pluri-decadal trends in bivalve-δ¹³C

During a shared period of 30 ± 2 years (1990–2021), bivalve-δ¹³C signal exhibited a significant decrease at 93% of the stations (26/28; Fig. 2, Table 1). The average decrease was –0.58 ± 0.24‰ decade⁻¹, ranging from –1.08 to –0.22‰ decade⁻¹ (i.e. –3.24 to –0.65‰ over 30 years). The decrease was not significant at only three stations (two in English Channel, one in Northern Bay of Biscay, over 30 years). Within each region, between station pairs, there were 80–100% of significant correlations in bivalve-δ¹³C in
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Pluri-decadal variability in bivalve-$\delta^{13}$C over the period 1981–2021 for the 32 stations of the six sea regions. Black lines correspond to significant trends (calculated on the period 1990–2021; Mann-Kendall tests; *p*-value < 0.05). One outlier (CB-21-PALL in 2014, -27‰) was removed for statistical tests. Colors correspond to species.</figcaption></figure>
<figure><img src="image_3.png" /><figcaption>**Fig. 2.** Pluri-decadal variability in bivalve-$\delta^{13}$C over the period 1981–2021 for the 32 stations of the six sea regions. Black lines correspond to significant trends (calculated on the period 1990–2021; Mann-Kendall tests; *p*-value < 0.05). One outlier (CB-21-PALL in 2014, –27‰) was removed for statistical tests. Colors correspond to species.</figcaption></figure>
<table><caption>**Table 1.** Raw values (mean ± SD, over the total dataset; n total = number of years of the time series) and decadal slopes of bivalve δ¹³C (dark gray) and bivalve δ¹³C corrected for the Suess effect (light gray, δ¹³Ccorr) calculated over a common period of 30 ± 2 years (1990–2021).</caption><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="2">δ¹³C raw values</th><th colspan="2">Years</th><th colspan="2">Slope (‰ decade<sup>-1</sup>)</th></tr><tr><th>n total</th><th>Average ± sd</th><th>n</th><th>Start</th><th>End</th><th>δ¹³C</th><th>δ¹³Ccorr</th></tr></thead><tbody><tr><td rowspan="8">English Channel (EC)</td><td>EC-1-AMBL</td><td>36</td><td>-18.8 ± 0.9</td><td>31</td><td>1990</td><td>2021</td><td><strong>-0.37</strong></td><td>-0.13</td></tr><tr><td>EC-2-PSQT</td><td>34</td><td>-18.9 ± 0.7</td><td>32</td><td>1990</td><td>2021</td><td>0.04</td><td><strong>0.28</strong></td></tr><tr><td>EC-3-VARE</td><td>37</td><td>-19.1 ± 0.6</td><td>32</td><td>1990</td><td>2021</td><td>-0.04</td><td>0.20</td></tr><tr><td>EC-4-ANTI</td><td>36</td><td>-19.3 ± 0.8</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.44</strong></td><td>-0.19</td></tr><tr><td>EC-5-CLHV</td><td>29</td><td>-20.1 ± 0.7</td><td>25</td><td>1990</td><td>2017</td><td>-0.15</td><td>0.09</td></tr><tr><td>EC-6-VILL</td><td>36</td><td>-20.7 ± 1.0</td><td>31</td><td>1990</td><td>2021</td><td><strong>-0.51</strong></td><td>-0.27</td></tr><tr><td>EC-7-OUIS</td><td>27</td><td>-19.0 ± 1.1</td><td>27</td><td>1994</td><td>2021</td><td><strong>-1.08</strong></td><td><strong>-0.84</strong></td></tr><tr><td>EC-8-PBES</td><td>37</td><td>-19.1 ± 1.2</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.93</strong></td><td><strong>-0.69</strong></td></tr><tr><td rowspan="4">Western Brittany (WB)</td><td>EC-9-BDVG</td><td>37</td><td>-19.5 ± 0.9</td><td>30</td><td>1990</td><td>2021</td><td><strong>-0.84</strong></td><td><strong>-0.59</strong></td></tr><tr><td>WB-10-PLAN</td><td>37</td><td>-19.5 ± 1.0</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.83</strong></td><td><strong>-0.59</strong></td></tr><tr><td>WB-11-PASS</td><td>21</td><td>-20.6 ± 0.8</td><td>21</td><td>2001</td><td>2021</td><td><strong>-1.13</strong></td><td><strong>-0.89</strong></td></tr><tr><td>WB-12-PERS</td><td>21</td><td>-20.3 ± 0.9</td><td>21</td><td>2001</td><td>2021</td><td><strong>-0.93</strong></td><td><strong>-0.69</strong></td></tr><tr><td rowspan="5">Northern Bay of Biscay (NB)</td><td>WB-13-AULN</td><td>38</td><td>-19.8 ± 0.7</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.40</strong></td><td>-0.16</td></tr><tr><td>NB-14-GUIL</td><td>39</td><td>-18.8 ± 0.6</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.39</strong></td><td>-0.15</td></tr><tr><td>NB-15-PEBE</td><td>40</td><td>-18.6 ± 0.6</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.27</strong></td><td>-0.03</td></tr><tr><td>NB-16-CHEM</td><td>39</td><td>-20.1 ± 0.7</td><td>32</td><td>1990</td><td>2021</td><td>0.04</td><td>0.28</td></tr><tr><td>NB-18-BOUR</td><td>37</td><td>-17.9 ± 0.8</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.23</strong></td><td>0.01</td></tr><tr><td rowspan="5">Central Bay of Biscay (CB)</td><td>NB-19-NOIR</td><td>38</td><td>-18.8 ± 0.7</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.49</strong></td><td>-0.24</td></tr><tr><td>CB-20-RIVE</td><td>40</td><td>-19.1 ± 1.0</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.94</strong></td><td><strong>-0.69</strong></td></tr><tr><td>CB-21-PALL</td><td>38</td><td>-18.7 ± 0.7</td><td>31</td><td>1990</td><td>2021</td><td><strong>-0.67</strong></td><td><strong>-0.42</strong></td></tr><tr><td>CB-22-BOYV</td><td>38</td><td>-18.9 ± 0.9</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.79</strong></td><td><strong>-0.54</strong></td></tr><tr><td>CB-23-PONT</td><td>38</td><td>-19.5 ± 0.8</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.63</strong></td><td><strong>-0.38</strong></td></tr><tr><td rowspan="4">Arcachon lagoon (AL)</td><td>CB-24-FOSS</td><td>40</td><td>-20.7 ± 1.0</td><td>31</td><td>1990</td><td>2021</td><td><strong>-0.63</strong></td><td><strong>-0.38</strong></td></tr><tr><td>AL-25-FERR</td><td>39</td><td>-19.2 ± 0.6</td><td>31</td><td>1990</td><td>2021</td><td><strong>-0.22</strong></td><td>0.02</td></tr><tr><td>AL-26-JACQ</td><td>38</td><td>-18.8 ± 0.5</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.32</strong></td><td>-0.08</td></tr><tr><td>AL-27-COMP</td><td>40</td><td>-19.1 ± 0.9</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.91</strong></td><td><strong>-0.67</strong></td></tr><tr><td rowspan="6">Gulf of lion (GL)</td><td>GL-28-BANY</td><td>32</td><td>-19.9 ± 0.9</td><td>28</td><td>1991</td><td>2021</td><td><strong>-0.55</strong></td><td><strong>-0.30</strong></td></tr><tr><td>GL-29-HRLT</td><td>31</td><td>-20.2 ± 0.8</td><td>28</td><td>1990</td><td>2021</td><td><strong>-0.48</strong></td><td>-0.24</td></tr><tr><td>GL-30-STMM</td><td>38</td><td>-20.3 ± 0.8</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.44</strong></td><td><strong>-0.19</strong></td></tr><tr><td>GL-31-CART</td><td>37</td><td>-20.6 ± 1.1</td><td>30</td><td>1990</td><td>2021</td><td><strong>-0.63</strong></td><td><strong>-0.39</strong></td></tr><tr><td>GL-32-COUR</td><td>37</td><td>-19.3 ± 0.8</td><td>31</td><td>1990</td><td>2021</td><td><strong>-0.64</strong></td><td><strong>-0.40</strong></td></tr><tr><td>GL-33-POME</td><td>24</td><td>-19.8 ± 0.8</td><td>24</td><td>1998</td><td>2021</td><td><strong>-0.85</strong></td><td><strong>-0.61</strong></td></tr></tbody></table>

Slope values were calculated from linear models and values are expressed in permille per decade. Significant slopes are in bold (Mann-Kendall tests; *p*-value <0.05). Time series that do not match time length requirements of 30 ± 2 years are in italics (four Sta. 5, 11, 12, and 33).

Western Brittany, Central Bay of Biscay, Arcachon Lagoon, Gulf of Lion, and 47–70% for Northern Bay of Biscay and English Channel (but all western English Channel stations were correlated, Table 2). When comparing station pairs between regions, there was an increase in correlation from north to south: the English Channel stations were poorly correlated with stations from the other regions (29–42%) while the Gulf of Lion, the Central Bay of Biscay and the Arcachon Lagoon showed more correlations (60–87%) between station pairs.

## Correlations between bivalve-δ¹³C and global proxies

Bivalve-δ¹³C was positively correlated with δ¹³C-CO₂aq for 78% of the stations (Table 3). Both δ¹³C decreased concomitantly over time. There was a negative correlation between bivalve-δ¹³C and CO₂atm and NHT for 78% and 75% of the stations respectively. The higher the atmospheric CO₂ concentrations and the warmer the air temperatures (positive anomalies) in the Northern hemisphere, the more negative were bivalve-δ¹³C values. The EAP (pressure) and AMO (temperature) indices were negatively correlated with
<table><caption>**Table 1.** Raw values (mean ± SD, over the total dataset; n total = number of years of the time series) and decadal slopes of bivalve δ¹³C (dark gray) and bivalve δ¹³C corrected for the Suess effect (light gray, δ¹³Ccorr) calculated over a common period of 30 ± 2 years (1990–2021).</caption><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="2">δ¹³C raw values</th><th colspan="2">Years</th><th colspan="2">Slope (‰ decade<sup>-1</sup>)</th></tr><tr><th>n total</th><th>Average ± sd</th><th>n</th><th>Start</th><th>End</th><th>δ¹³C</th><th>δ¹³Ccorr</th></tr></thead><tbody><tr><td rowspan="8">English Channel (EC)</td><td>EC-1-AMBL</td><td>36</td><td>-18.8 ± 0.9</td><td>31</td><td>1990</td><td>2021</td><td><strong>-0.37</strong></td><td>-0.13</td></tr><tr><td>EC-2-PSQT</td><td>34</td><td>-18.9 ± 0.7</td><td>32</td><td>1990</td><td>2021</td><td>0.04</td><td><strong>0.28</strong></td></tr><tr><td>EC-3-VARE</td><td>37</td><td>-19.1 ± 0.6</td><td>32</td><td>1990</td><td>2021</td><td>-0.04</td><td>0.20</td></tr><tr><td>EC-4-ANTI</td><td>36</td><td>-19.3 ± 0.8</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.44</strong></td><td>-0.19</td></tr><tr><td>EC-5-CLHV</td><td>29</td><td>-20.1 ± 0.7</td><td>25</td><td>1990</td><td>2017</td><td>-0.15</td><td>0.09</td></tr><tr><td>EC-6-VILL</td><td>36</td><td>-20.7 ± 1.0</td><td>31</td><td>1990</td><td>2021</td><td><strong>-0.51</strong></td><td>-0.27</td></tr><tr><td>EC-7-OUIS</td><td>27</td><td>-19.0 ± 1.1</td><td>27</td><td>1994</td><td>2021</td><td><strong>-1.08</strong></td><td><strong>-0.84</strong></td></tr><tr><td>EC-8-PBES</td><td>37</td><td>-19.1 ± 1.2</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.93</strong></td><td><strong>-0.69</strong></td></tr><tr><td rowspan="4">Western Brittany (WB)</td><td>EC-9-BDVG</td><td>37</td><td>-19.5 ± 0.9</td><td>30</td><td>1990</td><td>2021</td><td><strong>-0.84</strong></td><td><strong>-0.59</strong></td></tr><tr><td>WB-10-PLAN</td><td>37</td><td>-19.5 ± 1.0</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.83</strong></td><td><strong>-0.59</strong></td></tr><tr><td>WB-11-PASS</td><td>21</td><td>-20.6 ± 0.8</td><td>21</td><td>2001</td><td>2021</td><td><strong>-1.13</strong></td><td><strong>-0.89</strong></td></tr><tr><td>WB-12-PERS</td><td>21</td><td>-20.3 ± 0.9</td><td>21</td><td>2001</td><td>2021</td><td><strong>-0.93</strong></td><td><strong>-0.69</strong></td></tr><tr><td rowspan="5">Northern Bay of Biscay (NB)</td><td>WB-13-AULN</td><td>38</td><td>-19.8 ± 0.7</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.40</strong></td><td>-0.16</td></tr><tr><td>NB-14-GUIL</td><td>39</td><td>-18.8 ± 0.6</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.39</strong></td><td>-0.15</td></tr><tr><td>NB-15-PEBE</td><td>40</td><td>-18.6 ± 0.6</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.27</strong></td><td>-0.03</td></tr><tr><td>NB-16-CHEM</td><td>39</td><td>-20.1 ± 0.7</td><td>32</td><td>1990</td><td>2021</td><td>0.04</td><td>0.28</td></tr><tr><td>NB-18-BOUR</td><td>37</td><td>-17.9 ± 0.8</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.23</strong></td><td>0.01</td></tr><tr><td rowspan="5">Central Bay of Biscay (CB)</td><td>NB-19-NOIR</td><td>38</td><td>-18.8 ± 0.7</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.49</strong></td><td>-0.24</td></tr><tr><td>CB-20-RIVE</td><td>40</td><td>-19.1 ± 1.0</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.94</strong></td><td><strong>-0.69</strong></td></tr><tr><td>CB-21-PALL</td><td>38</td><td>-18.7 ± 0.7</td><td>31</td><td>1990</td><td>2021</td><td><strong>-0.67</strong></td><td><strong>-0.42</strong></td></tr><tr><td>CB-22-BOYV</td><td>38</td><td>-18.9 ± 0.9</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.79</strong></td><td><strong>-0.54</strong></td></tr><tr><td>CB-23-PONT</td><td>38</td><td>-19.5 ± 0.8</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.63</strong></td><td><strong>-0.38</strong></td></tr><tr><td rowspan="4">Arcachon lagoon (AL)</td><td>CB-24-FOSS</td><td>40</td><td>-20.7 ± 1.0</td><td>31</td><td>1990</td><td>2021</td><td><strong>-0.63</strong></td><td><strong>-0.38</strong></td></tr><tr><td>AL-25-FERR</td><td>39</td><td>-19.2 ± 0.6</td><td>31</td><td>1990</td><td>2021</td><td><strong>-0.22</strong></td><td>0.02</td></tr><tr><td>AL-26-JACQ</td><td>38</td><td>-18.8 ± 0.5</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.32</strong></td><td>-0.08</td></tr><tr><td>AL-27-COMP</td><td>40</td><td>-19.1 ± 0.9</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.91</strong></td><td><strong>-0.67</strong></td></tr><tr><td rowspan="6">Gulf of lion (GL)</td><td>GL-28-BANY</td><td>32</td><td>-19.9 ± 0.9</td><td>28</td><td>1991</td><td>2021</td><td><strong>-0.55</strong></td><td><strong>-0.30</strong></td></tr><tr><td>GL-29-HRLT</td><td>31</td><td>-20.2 ± 0.8</td><td>28</td><td>1990</td><td>2021</td><td><strong>-0.48</strong></td><td>-0.24</td></tr><tr><td>GL-30-STMM</td><td>38</td><td>-20.3 ± 0.8</td><td>32</td><td>1990</td><td>2021</td><td><strong>-0.44</strong></td><td><strong>-0.19</strong></td></tr><tr><td>GL-31-CART</td><td>37</td><td>-20.6 ± 1.1</td><td>30</td><td>1990</td><td>2021</td><td><strong>-0.63</strong></td><td><strong>-0.39</strong></td></tr><tr><td>GL-32-COUR</td><td>37</td><td>-19.3 ± 0.8</td><td>31</td><td>1990</td><td>2021</td><td><strong>-0.64</strong></td><td><strong>-0.40</strong></td></tr><tr><td>GL-33-POME</td><td>24</td><td>-19.8 ± 0.8</td><td>24</td><td>1998</td><td>2021</td><td><strong>-0.85</strong></td><td><strong>-0.61</strong></td></tr></tbody></table>

Slope values were calculated from linear models and values are expressed in permille per decade. Significant slopes are in bold (Mann-Kendall tests; *p*-value <0.05). Time series that do not match time length requirements of 30 ± 2 years are in italics (four Sta. 5, 11, 12, and 33).

Western Brittany, Central Bay of Biscay, Arcachon Lagoon, Gulf of Lion, and 47–70% for Northern Bay of Biscay and English Channel (but all western English Channel stations were correlated, Table 2). When comparing station pairs between regions, there was an increase in correlation from north to south: the English Channel stations were poorly correlated with stations from the other regions (29–42%) while the Gulf of Lion, the Central Bay of Biscay and the Arcachon Lagoon showed more correlations (60–87%) between station pairs.

## Correlations between bivalve-δ¹³C and global proxies

Bivalve-δ¹³C was positively correlated with δ¹³C-CO₂aq for 78% of the stations (Table 3). Both δ¹³C decreased concomitantly over time. There was a negative correlation between bivalve-δ¹³C and CO₂atm and NHT for 78% and 75% of the stations respectively. The higher the atmospheric CO₂ concentrations and the warmer the air temperatures (positive anomalies) in the Northern hemisphere, the more negative were bivalve-δ¹³C values. The EAP (pressure) and AMO (temperature) indices were negatively correlated with
<table><caption>**Table 2.** Correlation matrix between station pairs for bivalves δ¹³C (bivalve-δ¹³C, lower half triangle, dark gray) and bivalves δ¹³C corrected for Sues effect (bivalve-δ¹³C<sub>corr</sub>, upper half triangle, light gray).</caption><thead><tr><th rowspan="2">English Channel (EC)</th><th colspan="12">English Channel (EC)</th><th colspan="4">Western Brittany (WB)</th><th colspan="4">Northern Bay of Biscay (NB)</th></tr><tr><th>EC-1</th><th>EC-2</th><th>EC-3</th><th>EC-4</th><th>EC-5</th><th>EC-6</th><th>EC-7</th><th>EC-8</th><th>EC-9</th><th>WB-10</th><th>WB-11</th><th>WB-12</th><th>WB-13</th><th>NB-14</th><th>NB-15</th><th>NB-16</th><th>NB-18</th><th>NB-19</th></tr><tr><th>δ¹³C<sub>corr</sub></th><th>δ¹³C</th><th>AMBL</th><th>PSQT</th><th>VARE</th><th>ANTI</th><th>CLHV</th><th>VILL</th><th>OUIS</th><th>PBES</th><th>BDVG</th><th>PLAN</th><th>PASS</th><th>PERS</th><th>AULN</th><th>GUIL</th><th>PEBE</th><th>CHEM</th><th>BOUR</th><th>NOIR</th></tr></thead><tbody><tr><td>EC-1-AMBL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-2-PSQT</td><td>0.42</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-3-VARE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-4-ANTI</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-5-CLHV</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-6-VILL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-7-OUIS</td><td>0.55</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-8-PBES</td><td>0.54</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-9-BDVG</td><td>0.54</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-10-PLAN</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-11-PASS</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-12-PERS</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-13-AULN</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-14-GUIL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-15-PEBE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-16-CHEM</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-18-BOUR</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-19-NOIR</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-20-RIVE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-21-PALL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-22-BOYV</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-23-PONT</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-24-FOSS</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-25-FERR</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-26-JACQ</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-27-COMP</td><td>0.51</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-28-BANY</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-29-HRLT</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-30-STMM</td><td>0.41</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-31-CART</td><td>0.4</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-32-COUR</td><td>0.45</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-33-POME</td><td>0.47</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-31-AMBL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-32-PSQT</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-33-PONE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-34-ANTI</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-5-CLHV</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-6-VILL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-7-OUIS</td><td>0.55</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-8-PBES</td><td>0.54</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-9-BDVG</td><td>0.54</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-10-PLAN</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-11-PASS</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-12-PERS</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-13-AULN</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-14-GUIL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-15-PEBE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-16-CHEM</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-18-BOUR</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-19-NOIR</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-20-RIVE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-21-PALL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-22-BOYV</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-23-PONT</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-24-FOSS</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-25-FERR</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-26-JACQ</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-27-COMP</td><td>0.51</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-28-BANY</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-29-HRLT</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-30-STMM</td><td>0.41</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-31-CART</td><td>0.4</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-32-COUR</td><td>0.45</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-33-POME</td><td>0.47</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-34-ANTI</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-5-CLHV</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-6-VILL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-7-OUIS</td><td>0.55</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-8-PBES</td><td>0.54</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-9-BDVG</td><td>0.54</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-10-PLAN</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-11-PASS</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-12-PERS</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-13-AULN</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-14-GUIL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-15-PEBE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-16-CHEM</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-18-BOUR</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-19-NOIR</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-20-RIVE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-21-PALL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-22-BOYV</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-23-PONT</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-24-FOSS</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-25-FERR</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-26-JACQ</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-27-COMP</td><td>0.51</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-28-BANY</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-29-HRLT</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-30-STMM</td><td>0.41</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-31-CART</td><td>0.4</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-32-COUR</td><td>0.45</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-33-POME</td><td>0.47</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><caption>**Table 2.** Correlation matrix between station pairs for bivalves δ¹³C (bivalve-δ¹³C, lower half triangle, dark gray) and bivalves δ¹³C corrected for Sues effect (bivalve-δ¹³C<sub>corr</sub>, upper half triangle, light gray).</caption><thead><tr><th rowspan="2">English Channel (EC)</th><th colspan="12">English Channel (EC)</th><th colspan="4">Western Brittany (WB)</th><th colspan="4">Northern Bay of Biscay (NB)</th></tr><tr><th>EC-1</th><th>EC-2</th><th>EC-3</th><th>EC-4</th><th>EC-5</th><th>EC-6</th><th>EC-7</th><th>EC-8</th><th>EC-9</th><th>WB-10</th><th>WB-11</th><th>WB-12</th><th>WB-13</th><th>NB-14</th><th>NB-15</th><th>NB-16</th><th>NB-18</th><th>NB-19</th></tr><tr><th></th><th>AMBL</th><th>PSQT</th><th>VARE</th><th>ANTI</th><th>CLHV</th><th>VILL</th><th>OUIS</th><th>PBES</th><th>BDVG</th><th>PLAN</th><th>PASS</th><th>PERS</th><th>AULN</th><th>GUIL</th><th>PEBE</th><th>CHEM</th><th>BOUR</th><th>NOIR</th></tr></thead><tbody><tr><td>EC-1-AMBL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-2-PSQT</td><td>0.42</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-3-VARE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-4-ANTI</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-5-CLHV</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-6-VILL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-7-OUIS</td><td>0.55</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-8-PBES</td><td>0.54</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-9-BDVG</td><td>0.54</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-9-BDVG</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>WB-10-PLAN</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>WB-11-PASS</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>WB-12-PERS</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>WB-13-AULN</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Northern Bay of Biscay (NB)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NB-14-GUIL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NB-15-PEBE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NB-16-CHEM</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NB-18-BOUR</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NB-19-NOIR</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>CB-20-RIVE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>CB-21-PALL</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>CB-22-BOYV</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>CB-23-PONT</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>CB-24-FOSS</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Arcachon lagoon (AL)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>AL-26-JACQ</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>AL-27-COMP</td><td>0.51</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>GL-28-BANY</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>GL-29-HRLT</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>GL-30-STMM</td><td>0.41</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>GL-31-CART</td><td>0.4</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>GL-32-COUR</td><td>0.45</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>GL-33-POME</td><td>0.47</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
bivalve-δ¹³C for 56% and 44% of the stations respectively. Positive phases of both EAP and AMO, which increase sea surface temperature and are linked to milder and wetter precipitation in winter months over most of Northern Europe, were linked to more negative bivalve-δ¹³C values. There was no significant correlation between bivalve-δ¹³C and AO and NAO. Regionally, the English Channel and Northern Bay of Biscay showed less correlations (47% and 40%, respectively) with global proxies (out of AO, NAO, and δ¹³C-CO₂atm) than the Gulf of Lion and Arcachon Lagoon (87%) (Table 3).

## Remaining pluri-decadal trends in Suess-corrected bivalve-δ¹³C

After removing the Suess effect from bivalve-δ¹³C trends, we tested the significance of the remaining trends. Over the common period of 30 ± 2 yr (1990–2021), bivalve-δ¹³Ccorr significantly decreased for 50% of the stations, while 46% exhibited no significant change, and one station experienced a significant increase (EC-2-PSQT) (Table 1). The average decrease was -0.45 ± 0.27‰ decade⁻¹ ranging from -0.84 to -0.19‰ decade⁻¹ (from -2.52 to -0.58‰ over 30 years). There were only 28–50% significant correlations in bivalve-δ¹³Ccorr between station pairs within each region except for Central Bay of Biscay (70%; Table 2). There was almost no correlation remaining between station pairs of different regions (0–33%; Table 2).

## Remaining correlations between Suess-corrected bivalve-δ¹³C and global proxies

Overall, the number of correlations with global proxies decreased after removing the Suess effect. Bivalve-δ¹³Ccorr was still correlated with δ¹³C-CO₂aq at 53% of the stations, mostly positively (negatively correlated at two stations; Table 3). There were 47–53% correlations left between bivalve-δ¹³Ccorr and NHT and CO₂atm, mostly negative, and only 25–34% correlations remained for the other hydro-climatic indices. Still, there was no significant correlation between bivalve-δ¹³Ccorr, and AO and NAO. Regionally, more correlations were remaining with global proxies (55–60%, out of AO NAO and δ¹³C-CO₂atm) for Western Brittany and Gulf of Lion than for the other regions (28–44%).

## Discussion

We found an overall global temporal decrease in bivalves δ¹³C tissues in all sea regions, independently of bivalve species and despite differences in trophic status, tidal regime, continental influence, etc., of the studied ecosystems (Lheureux et al. 2023). This decrease was of same order of magnitude in all regions and with numerous correlations between stations of different sea regions. These results are consistent with the literature regarding marine organisms from different trophic levels (e.g., Druffel and Benavides 1986;

Aharon 1991; Bauch et al. 2000; Schloesser et al. 2009) including bivalve species from other sea areas (Liénart et al. 2022, -0.45‰ decade⁻¹). The decrease in bivalve-δ¹³C correlates in all regions with the global decrease in δ¹³C of dissolved CO₂ linked to the Suess effect (Keeling 1979). Among global processes directly altering bivalve-δ¹³C, the Suess effect can be measured, and therefore removed from pluri-decadal trends. After its correction, 46% of previous bivalve-δ¹³C slopes were not significant anymore and there were almost no correlations left between regions, showing that part of global direct anthropogenic effect on bivalve-δ¹³C was removed. Yet, significant decrease in bivalve-δ¹³Ccorr was still observed for 50% of the stations, and up to 60% of correlations with other global proxies remained in some regions (Gulf of Lion), indicating that other global processes affecting bivalve-δ¹³C values are still ongoing.

In addition to the Suess effect, increasing temperatures and CO₂ concentrations affect bivalve-δ¹³C via trophic pathway (Corman et al. 2018). Indeed, even after the Suess-effect correction, a large proportion of stations still exhibited negative correlation between bivalve-δ¹³Ccorr, atmospheric CO₂ concentration and NHT (both proxies for anthropogenic activities), and with AMO and EAP (proxies for natural climate, which trends indicate increased surface temperatures in Northern Atlantic; Comas-Bru and McDermott 2014; Zampieri et al. 2017). Changes in phytoplankton physiology and community assemblages can also both explain the decrease in bivalve-δ¹³C over time. Carbon isotope fractionation (i.e., enrichment of one isotope relative to another during [bio]chemical or physical processes) between phytoplankton and dissolved CO₂ is modulated by the balance between carbon demand (i.e., productivity/growth rate) and CO₂ availability (Fry 1996): as the increase in water temperature increases carbon demand (productivity) and decreases dissolved CO₂ concentration (CO₂ availability), phytoplankton isotopic fractionation decreases, leading to an overall increase in phytoplankton-δ¹³C; in contrast, as atmospheric and seawater CO₂ concentration increase due to fossil fuel burning, phytoplankton isotopic fractionation increases, leading to a decrease in phytoplankton-δ¹³C. Additionally, temperature increase may change phytoplankton community toward smaller cell-sized species (e.g., David et al. 2012; Hernández-Fariñas et al. 2014), which display lower δ¹³C values (e.g., Tuerena et al. 2019). All these processes are likely to occur concomitantly and reflect into bivalve tissues as any changes in phytoplankton-δ¹³C directly alter bivalve-δ¹³C by trophic propagation (Lefebvre et al. 2009).

Global change also affects bivalve-δ¹³C through bivalve physiology. Bivalve isotope fractionation directly relates to metabolic rates, (e.g., assimilation and growth, Lefebvre and Dubois 2016) which are temperature-dependent (Hiebenthal et al. 2013; Matoo et al. 2021). In their study, Marín Leal et al. (2008) showed that lower δ¹³C during winter were associated with lower metabolic rate. Increasing water temperature over
bivalve-δ¹³C for 56% and 44% of the stations respectively. Positive phases of both EAP and AMO, which increase sea surface temperature and are linked to milder and wetter precipitation in winter months over most of Northern Europe, were linked to more negative bivalve-δ¹³C values. There was no significant correlation between bivalve-δ¹³C and AO and NAO. Regionally, the English Channel and Northern Bay of Biscay showed less correlations (47% and 40%, respectively) with global proxies (out of AO, NAO, and δ¹³C-CO₂atm) than the Gulf of Lion and Arcachon Lagoon (87%) (Table 3).

## Remaining pluri-decadal trends in Suess-corrected bivalve-δ¹³C

After removing the Suess effect from bivalve-δ¹³C trends, we tested the significance of the remaining trends. Over the common period of 30 ± 2 yr (1990–2021), bivalve-δ¹³Ccorr significantly decreased for 50% of the stations, while 46% exhibited no significant change, and one station experienced a significant increase (EC-2-PSQT) (Table 1). The average decrease was -0.45 ± 0.27‰ decade⁻¹ ranging from -0.84 to -0.19‰ decade⁻¹ (from -2.52 to -0.58‰ over 30 years). There were only 28–50% significant correlations in bivalve-δ¹³Ccorr between station pairs within each region except for Central Bay of Biscay (70%; Table 2). There was almost no correlation remaining between station pairs of different regions (0–33%; Table 2).

## Remaining correlations between Suess-corrected bivalve-δ¹³C and global proxies

Overall, the number of correlations with global proxies decreased after removing the Suess effect. Bivalve-δ¹³Ccorr was still correlated with δ¹³C-CO₂aq at 53% of the stations, mostly positively (negatively correlated at two stations; Table 3). There were 47–53% correlations left between bivalve-δ¹³Ccorr and NHT and CO₂atm, mostly negative, and only 25–34% correlations remained for the other hydro-climatic indices. Still, there was no significant correlation between bivalve-δ¹³Ccorr, and AO and NAO. Regionally, more correlations were remaining with global proxies (55–60%, out of AO NAO and δ¹³C-CO₂atm) for Western Brittany and Gulf of Lion than for the other regions (28–44%).

## Discussion

We found an overall global temporal decrease in bivalves δ¹³C tissues in all sea regions, independently of bivalve species and despite differences in trophic status, tidal regime, continental influence, etc., of the studied ecosystems (Lheureux et al. 2023). This decrease was of same order of magnitude in all regions and with numerous correlations between stations of different sea regions. These results are consistent with the literature regarding marine organisms from different trophic levels (e.g., Druffel and Benavides 1986;

Aharon 1991; Bauch et al. 2000; Schloesser et al. 2009) including bivalve species from other sea areas (Liénart et al. 2022, -0.45‰ decade⁻¹). The decrease in bivalve-δ¹³C correlates in all regions with the global decrease in δ¹³C of dissolved CO₂ linked to the Suess effect (Keeling 1979). Among global processes directly altering bivalve-δ¹³C, the Suess effect can be measured, and therefore removed from pluri-decadal trends. After its correction, 46% of previous bivalve-δ¹³C slopes were not significant anymore and there were almost no correlations left between regions, showing that part of global direct anthropogenic effect on bivalve-δ¹³C was removed. Yet, significant decrease in bivalve-δ¹³Ccorr was still observed for 50% of the stations, and up to 60% of correlations with other global proxies remained in some regions (Gulf of Lion), indicating that other global processes affecting bivalve-δ¹³C values are still ongoing.

In addition to the Suess effect, increasing temperatures and CO₂ concentrations affect bivalve-δ¹³C via trophic pathway (Corman et al. 2018). Indeed, even after the Suess-effect correction, a large proportion of stations still exhibited negative correlation between bivalve-δ¹³Ccorr, atmospheric CO₂ concentration and NHT (both proxies for anthropogenic activities), and with AMO and EAP (proxies for natural climate, which trends indicate increased surface temperatures in Northern Atlantic; Comas-Bru and McDermott 2014; Zampieri et al. 2017). Changes in phytoplankton physiology and community assemblages can also both explain the decrease in bivalve-δ¹³C over time. Carbon isotope fractionation (i.e., enrichment of one isotope relative to another during [bio]chemical or physical processes) between phytoplankton and dissolved CO₂ is modulated by the balance between carbon demand (i.e., productivity/growth rate) and CO₂ availability (Fry 1996): as the increase in water temperature increases carbon demand (productivity) and decreases dissolved CO₂ concentration (CO₂ availability), phytoplankton isotopic fractionation decreases, leading to an overall increase in phytoplankton-δ¹³C; in contrast, as atmospheric and seawater CO₂ concentration increase due to fossil fuel burning, phytoplankton isotopic fractionation increases, leading to a decrease in phytoplankton-δ¹³C. Additionally, temperature increase may change phytoplankton community toward smaller cell-sized species (e.g., David et al. 2012; Hernández-Fariñas et al. 2014), which display lower δ¹³C values (e.g., Tuerena et al. 2019). All these processes are likely to occur concomitantly and reflect into bivalve tissues as any changes in phytoplankton-δ¹³C directly alter bivalve-δ¹³C by trophic propagation (Lefebvre et al. 2009).

Global change also affects bivalve-δ¹³C through bivalve physiology. Bivalve isotope fractionation directly relates to metabolic rates, (e.g., assimilation and growth, Lefebvre and Dubois 2016) which are temperature-dependent (Hiebenthal et al. 2013; Matoo et al. 2021). In their study, Marín Leal et al. (2008) showed that lower δ¹³C during winter were associated with lower metabolic rate. Increasing water temperature over
<table><caption>**Table 3.** Correlations between global anthropogenic and climate proxies, and both bivalve δ¹³C (bivalve-δ¹³C, left panel, dark gray) and bivalves δ¹³C corrected for the Suss effect (bivalve-δ¹³C<sub>corr</sub>, right panel, light gray) for each station of the six sea regions.</caption><thead><tr><th rowspan="2"></th><th colspan="10">Bivalve-δ¹³C</th><th colspan="5">Bivalve-δ¹³C<sub>corr</sub></th></tr><tr><th>AO</th><th>NAO</th><th>AMO</th><th>EAP</th><th>NHT</th><th>CO<sub>2</sub>atm</th><th>δ¹³C<sub>atm</sub></th><th>δ¹³C<sub>aq</sub></th><th>AO</th><th>NAO</th><th>AMO</th><th>EAP</th><th>NHT</th><th>CO<sub>2</sub>atm</th><th>δ¹³C<sub>atm</sub></th><th>δ¹³C<sub>aq</sub></th></tr></thead><tbody><tr><td rowspan="10">English Channel (EC)</td><td>EC-1-AMBL</td><td></td><td></td><td></td><td></td><td>-0.39</td><td>0.39</td><td>0.39</td><td></td><td></td><td></td><td></td><td></td><td>0.39</td><td>0.46</td><td>-0.45</td><td>-0.45</td></tr><tr><td>EC-2-PSQT</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-3-VARE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-4-ANTI</td><td></td><td></td><td></td><td>-0.47</td><td>-0.41</td><td>0.43</td><td>0.43</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-5-CLHV</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-6-VILL</td><td></td><td></td><td></td><td></td><td>-0.55</td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.4</td><td></td><td></td><td></td><td></td></tr><tr><td>EC-7-OUIS</td><td></td><td></td><td></td><td>-0.47</td><td>-0.68</td><td>-0.79</td><td>0.79</td><td>0.79</td><td></td><td></td><td></td><td>-0.46</td><td>-0.62</td><td>-0.74</td><td>0.74</td><td>0.74</td></tr><tr><td>EC-8-PBES</td><td></td><td></td><td></td><td>-0.46</td><td>-0.5</td><td>-0.68</td><td>-0.72</td><td>0.72</td><td>0.72</td><td></td><td></td><td>-0.4</td><td>-0.54</td><td>-0.56</td><td>0.57</td><td>0.57</td></tr><tr><td>EC-9-BDVG</td><td></td><td></td><td></td><td>-0.43</td><td>-0.57</td><td>-0.65</td><td>-0.67</td><td>0.67</td><td>0.67</td><td></td><td></td><td>-0.48</td><td>-0.39</td><td>-0.37</td><td>0.37</td><td>0.37</td></tr><tr><td>WB-10-PLAN</td><td></td><td></td><td></td><td>-0.65</td><td>-0.58</td><td>-0.82</td><td>-0.88</td><td>0.88</td><td>0.88</td><td></td><td></td><td>-0.61</td><td>-0.56</td><td>-0.75</td><td>0.81</td><td>0.8</td></tr><tr><td rowspan="5">Western Bretagne (WB)</td><td>WB-11-PASS</td><td></td><td></td><td></td><td>-0.51</td><td>-0.67</td><td>-0.8</td><td>0.8</td><td>0.8</td><td></td><td></td><td>-0.59</td><td>-0.66</td><td>-0.75</td><td>0.75</td><td>0.75</td></tr><tr><td>WB-12-PERS</td><td></td><td></td><td></td><td></td><td></td><td>-0.54</td><td>-0.68</td><td>0.68</td><td>0.68</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>WB-13-AULN</td><td></td><td></td><td></td><td></td><td></td><td>-0.56</td><td>-0.56</td><td>0.57</td><td>0.57</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NB-14-GUIL</td><td></td><td></td><td></td><td></td><td></td><td>-0.37</td><td>-0.53</td><td>0.52</td><td>0.52</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NB-15-PEBE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="7">Central Bay of Biscay (MB)</td><td>NB-16-CHEM</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.49</td><td></td><td>0.53</td><td>0.56</td><td>-0.56</td><td>-0.56</td></tr><tr><td>NB-18-BOUR</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NB-19-NOIR</td><td></td><td></td><td></td><td>-0.42</td><td>-0.38</td><td>-0.65</td><td>-0.69</td><td>0.69</td><td>0.69</td><td></td><td></td><td>-0.43</td><td>-0.44</td><td>0.44</td><td>0.44</td><td>0.44</td></tr><tr><td>CB-20-RIVE</td><td></td><td></td><td></td><td>-0.65</td><td>-0.49</td><td>-0.81</td><td>-0.88</td><td>0.88</td><td>0.88</td><td></td><td></td><td>-0.57</td><td>-0.46</td><td>-0.73</td><td>-0.79</td><td>0.78</td></tr><tr><td>CB-21-PALL</td><td></td><td></td><td></td><td>-0.5</td><td>-0.59</td><td>-0.64</td><td>-0.58</td><td>0.58</td><td>0.58</td><td></td><td></td><td>-0.44</td><td></td><td></td><td></td><td></td></tr><tr><td>CB-22-BOYV</td><td></td><td></td><td></td><td>-0.73</td><td>-0.45</td><td>-0.82</td><td>-0.88</td><td>0.88</td><td>0.88</td><td></td><td></td><td>-0.66</td><td>-0.38</td><td>-0.73</td><td>-0.77</td><td>0.77</td></tr><tr><td>CB-23-PONT</td><td></td><td></td><td></td><td></td><td></td><td>-0.38</td><td>-0.45</td><td>-0.56</td><td>0.55</td><td>0.55</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="8">Arcachon lagoon (AL)</td><td>AL-25-FERR</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>AL-26-JACQ</td><td></td><td></td><td></td><td></td><td></td><td>-0.43</td><td>-0.38</td><td>-0.49</td><td>0.47</td><td>0.47</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>AL-27-COMP</td><td></td><td></td><td></td><td>-0.53</td><td>-0.54</td><td>-0.72</td><td>-0.79</td><td>0.78</td><td>0.78</td><td></td><td></td><td>-0.35</td><td>-0.47</td><td>-0.55</td><td>-0.62</td><td>0.62</td></tr><tr><td>GL-28-BANY</td><td></td><td></td><td></td><td>-0.65</td><td>-0.38</td><td>-0.69</td><td>-0.75</td><td>0.75</td><td>0.75</td><td></td><td></td><td>-0.54</td><td></td><td>-0.52</td><td>-0.59</td><td>0.58</td><td>0.58</td></tr><tr><td>GL-29-HRLT</td><td></td><td></td><td></td><td>-0.45</td><td></td><td></td><td>-0.52</td><td>-0.51</td><td>0.52</td><td>0.52</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>GL-30-STMM</td><td></td><td></td><td></td><td>-0.46</td><td>-0.41</td><td>-0.64</td><td>-0.73</td><td>0.73</td><td>0.73</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>GL-31-CART</td><td></td><td></td><td></td><td>-0.61</td><td></td><td></td><td>-0.62</td><td>-0.74</td><td>0.73</td><td>0.73</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>GL-32-COUR</td><td></td><td></td><td></td><td>-0.69</td><td>-0.49</td><td>-0.81</td><td>-0.89</td><td>0.89</td><td>0.89</td><td></td><td></td><td>-0.59</td><td>-0.4</td><td>-0.68</td><td>-0.76</td><td>0.75</td></tr><tr><td>GL-33-POME</td><td></td><td></td><td></td><td></td><td></td><td>-0.53</td><td>-0.7</td><td>0.7</td><td>0.7</td><td></td><td></td><td></td><td></td><td></td><td>-0.54</td><td>0.54</td><td>0.54</td></tr></tbody></table>

Only significant correlations are shown (two-sided Spearman tests rho values [rank correlation coefficient], *p*-values < 0.05).
<table><caption>**Table 3.** Correlations between global anthropogenic and climate proxies, and both bivalve δ¹³C (bivalve-δ¹³C, left panel, dark gray) and bivalves δ¹³C corrected for the Suss effect (bivalve-δ¹³C<sub>corr</sub>, right panel, light gray) for each station of the six sea regions.</caption><thead><tr><th rowspan="2"></th><th colspan="10">Bivalve-δ¹³C</th><th colspan="5">Bivalve-δ¹³C<sub>corr</sub></th></tr><tr><th>AO</th><th>NAO</th><th>AMO</th><th>EAP</th><th>NHT</th><th>CO<sub>2</sub>atm</th><th>δ¹³C<sub>atm</sub></th><th>δ¹³C<sub>aq</sub></th><th>AO</th><th>NAO</th><th>AMO</th><th>EAP</th><th>NHT</th><th>CO<sub>2</sub>atm</th><th>δ¹³C<sub>atm</sub></th><th>δ¹³C<sub>aq</sub></th></tr></thead><tbody><tr><td rowspan="10">English Channel (EC)</td><td>EC-1-AMBL</td><td></td><td></td><td></td><td></td><td>-0.39</td><td>0.39</td><td>0.39</td><td></td><td></td><td></td><td></td><td></td><td>0.39</td><td>0.46</td><td>-0.45</td><td>-0.45</td></tr><tr><td>EC-2-PSQT</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-3-VARE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-4-ANTI</td><td></td><td></td><td></td><td>-0.47</td><td>-0.41</td><td>0.43</td><td>0.43</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-5-CLHV</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EC-6-VILL</td><td></td><td></td><td></td><td></td><td>-0.55</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.4</td><td></td><td></td><td></td></tr><tr><td>EC-7-OUIS</td><td></td><td></td><td></td><td>-0.47</td><td>-0.68</td><td>-0.79</td><td>0.79</td><td>0.79</td><td></td><td></td><td></td><td></td><td>-0.46</td><td>-0.62</td><td>-0.74</td><td>0.74</td></tr><tr><td>EC-8-PBES</td><td></td><td></td><td></td><td>-0.46</td><td>-0.5</td><td>-0.68</td><td>-0.72</td><td>0.72</td><td>0.72</td><td></td><td></td><td></td><td>-0.4</td><td>-0.54</td><td>-0.56</td><td>0.57</td></tr><tr><td>EC-9-BDVG</td><td></td><td></td><td></td><td>-0.43</td><td>-0.57</td><td>-0.65</td><td>-0.67</td><td>0.67</td><td>0.67</td><td></td><td></td><td></td><td>-0.48</td><td>-0.39</td><td>-0.37</td><td>0.37</td></tr><tr><td>WB-10-PLAN</td><td></td><td></td><td></td><td>-0.65</td><td>-0.58</td><td>-0.82</td><td>-0.88</td><td>0.88</td><td>0.88</td><td></td><td></td><td></td><td>-0.61</td><td>-0.56</td><td>-0.75</td><td>0.8</td></tr><tr><td rowspan="5">Western Bretagne (WB)</td><td>WB-11-PASS</td><td></td><td></td><td></td><td>-0.51</td><td>-0.67</td><td>-0.8</td><td>0.8</td><td>0.8</td><td></td><td></td><td></td><td>-0.59</td><td>-0.66</td><td>-0.75</td><td>0.75</td></tr><tr><td>WB-12-PERS</td><td></td><td></td><td></td><td></td><td></td><td>-0.54</td><td>-0.68</td><td>0.68</td><td>0.68</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>WB-13-AULN</td><td></td><td></td><td></td><td>-0.47</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NB-14-GUIL</td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.37</td><td>-0.53</td><td>0.52</td><td>0.52</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NB-15-PEBE</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="7">Central Bay of Biscay (MB)</td><td>NB-16-CHEM</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.49</td><td>0.53</td><td>0.56</td><td>-0.56</td><td>-0.56</td></tr><tr><td>NB-18-BOUR</td><td></td><td></td><td></td><td>-0.37</td><td></td><td>-0.53</td><td>-0.58</td><td>0.58</td><td>0.58</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NB-19-NOIR</td><td></td><td></td><td></td><td>-0.42</td><td>-0.38</td><td>-0.65</td><td>-0.69</td><td>0.69</td><td>0.69</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>CB-20-RIVE</td><td></td><td></td><td></td><td>-0.65</td><td>-0.49</td><td>-0.81</td><td>-0.88</td><td>0.88</td><td>0.88</td><td></td><td></td><td></td><td>-0.57</td><td>-0.46</td><td>-0.73</td><td>0.78</td></tr><tr><td>CB-21-PALL</td><td></td><td></td><td></td><td>-0.5</td><td>-0.59</td><td>-0.64</td><td>-0.58</td><td>0.58</td><td>0.58</td><td></td><td></td><td></td><td>-0.44</td><td></td><td></td><td></td></tr><tr><td>CB-22-BOYV</td><td></td><td></td><td></td><td>-0.73</td><td>-0.45</td><td>-0.82</td><td>-0.88</td><td>0.88</td><td>0.88</td><td></td><td></td><td></td><td>-0.66</td><td>-0.38</td><td>-0.73</td><td>0.77</td></tr><tr><td>CB-23-PONT</td><td></td><td></td><td></td><td>-0.38</td><td>-0.45</td><td>-0.56</td><td>0.55</td><td>0.55</td><td>0.55</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="7">Northern Bay of Biscay (NB)</td><td>CB-24-FOSS</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>AL-25-FERR</td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.38</td><td>-0.41</td><td>-0.51</td><td>0.49</td><td>0.49</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>AL-26-JACQ</td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.43</td><td>-0.38</td><td>-0.49</td><td>0.47</td><td>0.47</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>AL-27-COMP</td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.53</td><td>-0.54</td><td>-0.72</td><td>-0.79</td><td>0.78</td><td>0.78</td><td></td><td></td><td></td><td></td></tr><tr><td>GL-28-BANY</td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.65</td><td>-0.38</td><td>-0.69</td><td>-0.75</td><td>0.75</td><td>0.75</td><td></td><td></td><td></td><td></td></tr><tr><td>GL-29-HRLT</td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.45</td><td></td><td>-0.52</td><td>-0.51</td><td>0.52</td><td>0.52</td><td></td><td></td><td></td><td></td></tr><tr><td>GL-30-STMM</td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.46</td><td>-0.41</td><td>-0.64</td><td>-0.73</td><td>0.73</td><td>0.73</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="4">Gulf of lion (GL)</td><td>GL-31-CART</td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.61</td><td></td><td>-0.62</td><td>-0.74</td><td>0.73</td><td>0.73</td><td></td><td></td><td></td><td></td></tr><tr><td>GL-32-COUR</td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.69</td><td>-0.49</td><td>-0.81</td><td>-0.89</td><td>0.89</td><td>0.89</td><td></td><td></td><td></td><td></td></tr><tr><td>GL-33-POME</td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.53</td><td>-0.7</td><td>-0.7</td><td>0.7</td><td>0.7</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

Only significant correlations are shown (two-sided Spearman tests rho values [rank correlation coefficient], *p*-values < 0.05).
multidecadal scales should result in increased metabolic activity, hence in bivalves-δ¹³C as a pure metabolic effect. In addition, lipid content in bivalves (reflected by higher C:N ratio when it increases) should decrease with warmer temperatures in temperate regions (Tan et al. 2023) translating to increased bivalves-δ¹³C values and decreased C:N (Post et al. 2007). However, this is not the observed trend (decreasing bivalve-δ¹³C, no overall decreasing trend in C:N ratio; data not shown), which suggests that bivalve physiology is likely not a dominant process for the multidecadal bivalve-δ¹³C trends of this study. These trends are rather explained by direct (through diet) or indirect (through the effect of abiotic factors on phytoplankton physiology) changes in bivalve-δ¹³C through food availability and quality (Liénart et al. 2020, 2023).

As these effects are linked to global drivers, they should similarly affect all regions and stations. However, ‘only’ 50% of the stations still exhibit significant decrease in Suess-corrected bivalves-δ¹³C (most of the stations of Western Brittany, Central Bay of Biscay and Gulf of Lion) and only 43% of the stations still exhibit a correlation between bivalves-δ¹³Ccorr and global proxies (out of AO NAO and δ¹³C-CO₂atm; most of the stations of Western Brittany and Gulf of Lion). This indicates that beyond global drivers, bivalves-δ¹³C also responds to regional/local drivers that have cumulative, synergetic (for the stations exhibiting more negative slopes) or antagonistic (for the stations exhibiting less negative slope, nonsignificant or even positive slope) effect with global drivers. It is beyond the scope of this article to discuss these regional/local drivers but the present results clearly enlighten their effect on bivalves-δ¹³C.

To summarize, the global increase in atmospheric CO₂ has many impacts (e.g., global warming), including on marine ecosystems (e.g., increased seawater temperature, increased primary production). Such changes go beyond physical-chemical processes or changes in the production base and have an impact on species at the base of the food webs, with potential knock-on effects expected on upper trophic levels, including isotopic signal. Our study demonstrates that the changes in the chemical composition of the atmosphere (increase in CO₂ and associated decrease in δ¹³C-CO₂atm) are recorded in bivalves soft-tissues. This global effect is likely related to ‘passive’ processes (Suess effect; changes in δ¹³C-CO₂atm directly modify bivalve-δ¹³C through physical and chemical processes, i.e., without change in biological processes), but is also associated to ‘active’ processes (i.e., biological, due to change in phytoplankton or bivalve fractionation and physiology). Indeed, even after removing the Suess effect, a link between bivalve-δ¹³C and global indices remains for half of the stations. Beyond global effect, regional and/or local effects likely occur in cumulative, synergistic or antagonistic ways. Correcting δ¹³C time series for the Suess effect is a first and necessary step required when comparing biological samples collected one or more decades apart (as previously

advised by Misarti et al. 2009; Dombrosky 2020; Clark et al. 2021). Further studies are required to comprehensively investigate regional/local processes related to changes in bivalve-δ¹³C once corrected for the Suess effect, which will contribute to a deeper understanding of ecosystem responses to global change.

## Funding Information

This work is part of the research project EVOLECO-BEST funded by the Office Français de la Biodiversité (OFB).

## References

Affek, H. P., and D. Yakir. 2014. The stable isotopic composition of atmospheric CO₂, p. 179–212. *In* H. D. Holland and K. K. Turekian [eds.], *Treatise on geochemistry*, v. **5**, Second ed. Elsevier. doi:10.1016/B978-0-08-095975-7.00407-1

Aharon, P. 1991. Recorders of reef environment histories: Stable isotopes in corals, giant clams, and calcareous algae. *Coral Reefs* **10**: 71–90. doi:10.1007/BF00571826

Barbier, E. B., S. D. Hacker, C. Kennedy, E. W. Koch, A. C. Stier, and B. R. Silliman. 2011. The value of estuarine and coastal ecosystem services. Ecol. Monogr. **81**: 169–193. doi: 10.1890/10-1510.1

Barnston, A. G., and R. E. Livezey. 1987. Classification, seasonality and persistence of low-frequency atmospheric circulation patterns. Mon. Weather Rev. **115**: 1083–1126. doi:10.1175/1520-0493(1987)115<1083:CSAPOL>2.0.CO;2

Bartley, T. J., and others. 2019. Food web rewiring in a changing world. Nat. Ecol. Evol. **3**: 345–354. doi:10.1038/s41559-018-0772-3

Bauch, D., J. Carstens, G. Wefer, and J. Thiede. 2000. The imprint of anthropogenic CO₂ in the Arctic Ocean: Evidence from planktic δ¹³C data from water column and sediment surfaces. Deep Res. Part II Top. Stud. Oceanogr. **47**: 1791–1808. doi:10.1016/S0967-0645(00)00007-2

Bauer, J. E., W.-J. Cai, P. A. Raymond, T. S. Bianchi, C. S. Hopkinson, and P. A. G. Regnier. 2013. The changing carbon cycle of the coastal ocean. Nature **504**: 61–70. doi:10.1038/nature12857

Benedetti, F., M. Vogt, U. H. Elizondo, D. Righetti, N. E. Zimmermann, and N. Gruber. 2021. Major restructuring of marine plankton assemblages under global warming. Nat. Commun. **12**: 1–15. doi:10.1038/s41467-021-25385-x

Briant, N., and others. 2018. Carbon and nitrogen elemental and isotopic ratios of filter-feeding bivalves along the French coasts: An assessment of specific, geographic, seasonal and multi-decadal variations. Sci. Total Environ. **613-614**: 196–207. doi:10.1016/j.scitotenv.2017.08.281

Briant, N., P. Le Monier, S. Bruzac, T. Sireau, D. F. Araújo, and A. Grouhel. 2021. Rare earth element in bivalves' soft tissues of French metropolitan coasts: Spatial and temporal distribution. Arch. Environ. Contam. Toxicol. **81**: 600–611. doi:10.1007/s00244-021-00821-7
Bristow, L. A., T. D. Jickells, K. Weston, A. Marca-Bell, R. Parker, and J. E. Andrews. 2013. Tracing estuarine organic matter sources into the southern North Sea using C and N isotopic signatures. Biogeochemistry **113**: 9–22. doi:10.1007/s10533-012-9758-4

Cabral, H., V. Fonseca, T. Sousa, and M. C. Leal. 2019. Syner-gistic effects of climate change and marine pollution: An overlooked interaction in coastal and estuarine areas. Int. J. Environ. Res. Public Health **16**: 1–17. doi:10.3390/ijerph16152737

Cael, B. B., K. Bisson, E. Boss, S. Dutkiewicz, and S. Henson. 2023. Global climate change trends detected in indicators of ocean ecology. Nature **619**: 551–554. doi:10.1038/s41586-023-06321-z

Chahouri, A., B. Yacoubi, A. Moukrim, and A. Banaoui. 2023. Bivalve molluscs as bioindicators of multiple stressors in the marine environment: Recent advances. Cont. Shelf Res. **264**: 105056. doi:10.1016/j.csr.2023.105056

Clark, C. T., M. R. Cape, M. D. Shapley, F. J. Mueter, B. P. Finney, and N. Misarti. 2021. SuessR: Regional corrections for the effects of anthropogenic CO₂ on δ¹³C data from marine organisms. Methods Ecol. Evol. **12**: 1508–1520. doi:10.1111/2041-210X.13622

Comas-Bru, L., and F. Mcdermott. 2014. Impacts of the EA and SCA patterns on the European twentieth century NAO-winter climate relationship. Q. J. Roy. Meteorol. Soc. **140**: 354–363. doi:10.1002/qj.2158

Corman, A. M., and others. 2018. Decreasing δ¹³C and δ¹⁵N values in four coastal species at different trophic levels indi-cate a fundamental food-web shift in the southern north and Baltic seas between 1988 and 2016. Environ. Monit. Assess. **190**: 1–12. doi:10.1007/s10661-018-6827-8

David, V., M. Ryckaert, M. Karpytchev, C. Bacher, V. Arnareau, N. Vidal, D. Maurer, and N. Niquil. 2012. Spa-tial and long-term changes in the functional and structural phytoplankton communities along the French Atlantic coast. Estuar. Coast. Shelf Sci. **108**: 37–51. doi:10.1016/j.ecss.2012.02.017

Dombrosky, J. 2020. A ~1000-year ¹³C Suess correction model for the study of past ecosystems. Holocene **30**: 474–478. doi:10.1177/0959683619887416

Druffel, E. R. M., and L. M. Benavides. 1986. Input of excess CO₂ to the surface ocean based on ¹³C/¹²C ratios in a banded Jamaican sclerosponge. Nature **321**: 58–61. doi:10.1038/321058a0

Enfield, D. B., A. M. Mestas-Nuñez, and P. J. Trimble. 2001. The Atlantic multidecadal oscillation and its relation to rainfall and river flows in the continental U.S. Geophys. Res. Lett. **28**: 2077–2080. doi:10.1029/2000GL012745

Fry, B. 1996. ¹³C/¹²C fractionation by marine diatoms. Mar. Ecol. Prog. Ser. **134**: 283–294. doi:10.3354/meps134283

Gittings, J. A., D. E. Raitsos, G. Krokos, and I. Hoteit. 2018. Impacts of warming on phytoplankton abundance and phenology in a typical tropical marine ecosystem. Sci. Rep. **8**: 2240. doi:10.1038/s41598-018-20560-5

Graven, H., and others. 2017. Compiled records of carbon iso-topes in atmospheric CO₂ for historical simulations in CMIP6. Geosci. Model Dev. **10**: 4405–4417. doi:10.5194/gmd-10-4405-2017

Gruber, N., and others. 1999. Spatiotemporal patterns of carbon-13 in the global surface ocean and the oceanic Suess effect. Global Biogeochem. Cycles **13**: 307–335. doi:10.1029/1999GB900019

Halpern, B. S., and others. 2008. A global map of human impact on marine ecosystems. Science **319**: 948–952. doi:10.1126/science.1149345

Harley, C. D. G., and others. 2006. The impacts of climate change in coastal marine systems. Ecol. Lett. **9**: 228–241. doi:10.1111/j.1461-0248.2005.00871.x

Hernández-Fariñas, T., and others. 2014. Temporal changes in the phytoplankton community along the French coast of the eastern English Channel and the southern bight of the North Sea. ICES J. Mar. Sci. **71**: 821–833. doi:10.4135/9781412953924.n678

Hiebenthal, C., E. E. R. Philipp, A. Eisenhauer, and M. Wahl. 2013. Effects of seawater pCO₂ and temperature on shell growth, shell stability, condition and cellular stress of West-ern Baltic Sea *Mytilus edulis* (L.) and *Arctica islandica* (L.). Mar. Biol. **160**: 2073–2087. doi:10.1007/s00227-012-2080-9

Higgins, R. W., A. Leetmaa, Y. Xue, and A. Barnston. 2000. Dominant factors influencing the seasonal predictability of U.S. precipitation and surface air temperature. J. Climate **13**: 3994–4017. doi:10.1175/1520-0442(2000)013<3994:DFITSP>2.0.CO;2

Hurrell, J. W. 1995. Decadal trends in the North Atlantic oscil-lation: Regional temperatures and precipitation. Science **269**: 676–679. doi:10.1126/science.269.5224.676

Hurrell, J. W., and C. Deser. 2009. North Atlantic climate vari-ability: The role of the North Atlantic oscillation. J. Mar. Syst. **78**: 28–41. doi:10.1016/j.jmarsys.2008.11.026

Karlson, A. M. L., and S. Faxneld. 2021. Polycyclic aromatic hydrocarbons and stable isotopes of carbon and nitrogen in Baltic Sea blue mussels: Time series data 1981–2016. Data Br. **35**: 4–8. doi:10.1016/j.dib.2021.106777

Keeling, C. D. 1979. The Suess effect: ¹³Carbon-¹⁴Carbon interrelations. Environ. Int. **2**: 229–300. doi:10.1016/016-0-4120(79)90005-9

Lan, X., P. Tans, and K. W. Thoning. 2023. Trends in globally-averaged CO₂ determined from NOAA global monitoring laboratory measurements. Version 2023-04. doi:10.15138/9N0H-ZH07

Lefebvre, S., J. C. Marín Leal, S. Dubois, F. Orvain, J.-L. Blin, M.-P. Bataillé, A. Ourry, and R. Galois. 2009. Seasonal dynamics of trophic relationships among co-occurring sus-pension feeders in two shellfish culture dominated ecosystems. Estuar. Coast. Shelf Sci. **82**: 415–425. doi:10.1016/j.ecss.2009.02.002

Lefebvre, S., and S. F. Dubois. 2016. The stony road to under-stand isotopic enrichment and turnover rates: Insight into
Bristow, L. A., T. D. Jickells, K. Weston, A. Marca-Bell, R. Parker, and J. E. Andrews. 2013. Tracing estuarine organic matter sources into the southern North Sea using C and N isotopic signatures. Biogeochemistry **113**: 9–22. doi:10.1007/s10533-012-9758-4

Cabral, H., V. Fonseca, T. Sousa, and M. C. Leal. 2019. Syner-gistic effects of climate change and marine pollution: An overlooked interaction in coastal and estuarine areas. Int. J. Environ. Res. Public Health **16**: 1–17. doi:10.3390/ijerph16152737

Cael, B. B., K. Bisson, E. Boss, S. Dutkiewicz, and S. Henson. 2023. Global climate change trends detected in indicators of ocean ecology. Nature **619**: 551–554. doi:10.1038/s41586-023-06321-z

Chahouri, A., B. Yacoubi, A. Moukrim, and A. Banaoui. 2023. Bivalve molluscs as bioindicators of multiple stressors in the marine environment: Recent advances. Cont. Shelf Res. **264**: 105056. doi:10.1016/j.csr.2023.105056

Clark, C. T., M. R. Cape, M. D. Shapley, F. J. Mueter, B. P. Finney, and N. Misarti. 2021. SuessR: Regional corrections for the effects of anthropogenic CO₂ on δ¹³C data from marine organisms. Methods Ecol. Evol. **12**: 1508–1520. doi:10.1111/2041-210X.13622

Comas-Bru, L., and F. Mcdermott. 2014. Impacts of the EA and SCA patterns on the European twentieth century NAO-winter climate relationship. Q. J. Roy. Meteorol. Soc. **140**: 354–363. doi:10.1002/qj.2158

Corman, A. M., and others. 2018. Decreasing δ¹³C and δ¹⁵N values in four coastal species at different trophic levels indi-cate a fundamental food-web shift in the southern north and Baltic seas between 1988 and 2016. Environ. Monit. Assess. **190**: 1–12. doi:10.1007/s10661-018-6827-8

David, V., M. Ryckaert, M. Karpytchev, C. Bacher, V. Arnareau, N. Vidal, D. Maurer, and N. Niquil. 2012. Spa-tial and long-term changes in the functional and structural phytoplankton communities along the French Atlantic coast. Estuar. Coast. Shelf Sci. **108**: 37–51. doi:10.1016/j.ecss.2012.02.017

Dombrosky, J. 2020. A ~1000-year ¹³C Suess correction model for the study of past ecosystems. Holocene **30**: 474–478. doi:10.1177/0959683619887416

Druffel, E. R. M., and L. M. Benavides. 1986. Input of excess CO₂ to the surface ocean based on ¹³C/¹²C ratios in a banded Jamaican sclerosponge. Nature **321**: 58–61. doi:10.1038/321058a0

Enfield, D. B., A. M. Mestas-Nuñez, and P. J. Trimble. 2001. The Atlantic multidecadal oscillation and its relation to rainfall and river flows in the continental U.S. Geophys. Res. Lett. **28**: 2077–2080. doi:10.1029/2000GL012745

Fry, B. 1996. ¹³C/¹²C fractionation by marine diatoms. Mar. Ecol. Prog. Ser. **134**: 283–294. doi:10.3354/meps134283

Gittings, J. A., D. E. Raitsos, G. Krokos, and I. Hoteit. 2018. Impacts of warming on phytoplankton abundance and phenology in a typical tropical marine ecosystem. Sci. Rep. **8**: 2240. doi:10.1038/s41598-018-20560-5

Graven, H., and others. 2017. Compiled records of carbon iso-topes in atmospheric CO₂ for historical simulations in CMIP6. Geosci. Model Dev. **10**: 4405–4417. doi:10.5194/gmd-10-4405-2017

Gruber, N., and others. 1999. Spatiotemporal patterns of carbon-13 in the global surface ocean and the oceanic Suess effect. Global Biogeochem. Cycles **13**: 307–335. doi:10.1029/1999GB900019

Halpern, B. S., and others. 2008. A global map of human impact on marine ecosystems. Science **319**: 948–952. doi:10.1126/science.1149345

Harley, C. D. G., and others. 2006. The impacts of climate change in coastal marine systems. Ecol. Lett. **9**: 228–241. doi:10.1111/j.1461-0248.2005.00871.x

Hernández-Fariñas, T., and others. 2014. Temporal changes in the phytoplankton community along the French coast of the eastern English Channel and the southern bight of the North Sea. ICES J. Mar. Sci. **71**: 821–833. doi:10.4135/9781412953924.n678

Hiebenthal, C., E. E. R. Philipp, A. Eisenhauer, and M. Wahl. 2013. Effects of seawater pCO₂ and temperature on shell growth, shell stability, condition and cellular stress of West-ern Baltic Sea *Mytilus edulis* (L.) and *Arctica islandica* (L.). Mar. Biol. **160**: 2073–2087. doi:10.1007/s00227-012-2080-9

Higgins, R. W., A. Leetmaa, Y. Xue, and A. Barnston. 2000. Dominant factors influencing the seasonal predictability of U.S. precipitation and surface air temperature. J. Climate **13**: 3994–4017. doi:10.1175/1520-0442(2000)013<3994:DFITSР>2.0.CO;2

Hurrell, J. W. 1995. Decadal trends in the North Atlantic oscil-lation: Regional temperatures and precipitation. Science **269**: 676–679. doi:10.1126/science.269.5224.676

Hurrell, J. W., and C. Deser. 2009. North Atlantic climate vari-ability: The role of the North Atlantic oscillation. J. Mar. Syst. **78**: 28–41. doi:10.1016/j.jmarsys.2008.11.026

Karlson, A. M. L., and S. Faxneld. 2021. Polycyclic aromatic hydrocarbons and stable isotopes of carbon and nitrogen in Baltic Sea blue mussels: Time series data 1981–2016. Data Br. **35**: 4–8. doi:10.1016/j.dib.2021.106777

Keeling, C. D. 1979. The Suess effect: ¹³Carbon-¹⁴Carbon interrelations. Environ. Int. **2**: 229–300. doi:10.1016/016-0-4120(79)90005-9

Lan, X., P. Tans, and K. W. Thoning. 2023. Trends in globally-averaged CO₂ determined from NOAA global monitoring laboratory measurements. Version 2023-04. doi:10.15138/9N0H-ZH07

Lefebvre, S., J. C. Marín Leal, S. Dubois, F. Orvain, J.-L. Blin, M.-P. Bataillé, A. Ourry, and R. Galois. 2009. Seasonal dynamics of trophic relationships among co-occurring sus-pension feeders in two shellfish culture dominated ecosystems. Estuar. Coast. Shelf Sci. **82**: 415–425. doi:10.1016/j.ecss.2009.02.002

Lefebvre, S., and S. F. Dubois. 2016. The stony road to under-stand isotopic enrichment and turnover rates: Insight into
the metabolic part. Vie Milieu Life Environ. **66**: 305-314
https://archimer.ifremer.fr/doc/00387/49856/

Lheureux, A., and others. 2023. Trajectories of nutrients con-
centrations and ratios in the French coastal ecosystems:
20 years of changes in relation with large-scale and local
drivers. Sci. Tot. Environ. **857**: 159619. doi:10.1016/j.scitot
env.2022.159619

Liénart, C., and others. 2017. Dynamics of particulate organic matter composition in coastal systems: A spatio-temporal study at multi-system scale. Prog. Oceanogr. **156**: 221-239. doi:10.1016/j-pocean.2017.03.001

Liénart, C., and others. 2020. Long-term changes in trophic ecology of blue mussels in a rapidly changing ecosystem. Limnol. Oceanogr. **66**: 694–710. doi:10.1002/lno.11633

Liénart, C., A. Garbaras, S. Qvarfordt, H. Lim, M. Chynel, C. Robinson, T. Meziane, and A. M. L. Karlson. 2022. Spatio-temporal variation in stable isotope and elemental composition of key-species reflect environmental changes in the Baltic Sea. Biogeochemistry **157**: 149–170. doi:10.1007/s10533-021-00865-w

Liénart, C., M. Tedengren, A. Garbaras, H. Lim, M. Chynel, C. Robinson, T. Meziane, and A. M. L. Karlson. 2023. Diet quality determines blue mussel physiological status: A long-term experimental multi-marker approach. J. Exp. Mar. Biol. Ecol. **563**: 151894. doi:10.1016/j.jembe.2023.151894

Magni, P., S. Rajagopal, S. Como, J. M. Jansen, G. van der Velde, and H. Hummel. 2013. δ¹³C and δ¹⁵N variations in organic matter pools, *Mytilus* spp. and *Macoma balthica* along the European Atlantic coast. Mar. Biol. **160**: 541–552. doi:10.1007/s00227-012-2110-7

Marín Leal, J. C., and others. 2008. Stable isotopes (δ13C, δ15N) and modelling as tools to estimate the trophic ecol-
ogy of cultivated oysters in two contrasting environments.
Mar. Biol. **153**: 673–688. doi:10.1007/s00227-007-0841-7

Matoo, O. B., G. Lannig, C. Bock, and I. M. Sokolova. 2021. Temperature but not ocean acidification affects energy metabolism and enzyme activities in the blue mussel, *Mytilus edulis*. Ecol. Evol. **11**: 336–3379. doi:10.1002/ece3.7289

Milliman, J. D., K. L. Farnsworth, P. D. Jones, K. H. Xu, and L. C. Smith. 2008. Climatic and anthropogenic factors affecting river discharge to the global ocean, 1951-2000. Glob. Planet. Change **62**: 187-194. doi:10.1016/j.gloplacha.2008.03.001

Misarti, N., B. Finney, H. Maschner, and M. J. Wooller. 2009. Changes in northeast Pacific marine ecosystems over the last 4500 years: Evidence from stable isotope analysis of bone collagen from archeological middens. Holocene **19**: 1139-1151. doi:10.1177/0959683609357824

Mook, W. G. 2000. *Environmental isotopes in the hydrological cycle: Principles and applications*. UNESCO.

Patakamuri, S., and N. O'Brien. 2021. Modifiedmk: Modified versions of Mann Kendall and Spearman's rho trend

tests. R package version 1.6. https://CRAN.R-project.org/
package=modifiedmk

Post, D. M., C. A. Layman, D. A. Arrington, G. Takimoto, J. Quattrochi, and C. G. Montaña. 2007. Getting to the fat of the matter: Models, methods and assumptions for dealing with lipids in stable isotope analyses. Oecologia **152**: 179–189. doi:10.1007/s00442-006-0630-x

Pörtner, H. O., M. Langenbuch, and B. Michaelidis. 2005. Synergistic effects of temperature extremes, hypoxia, and increases in CO₂ on marine animals: From earth history to global change. J. Geophys. Res. Ocean. **110**: 1–15. doi:10.1029/2004JC002561

Quay, P., R. Sonnerup, J. Stutsman, J. Maurer, A. Körtzinger, X. A. Padin, and C. Robinson. 2007. Anthropogenic CO₂ accumulation rates in the North Atlantic Ocean from changes in the ¹³C/¹²C of dissolved inorganic carbon. Global Bio-geochem. Cycles **21**: 1–15. doi:10.1029/2006GB002761

R Core Team. 2022. *R: A language and environment for statistical computing*. R Foundation for Statistical Computing, https://www.R-project.org/

Schloesser, R. W., J. R. Rooker, P. Louchuoarn, J. D. Neilson, and D. H. Secor. 2009. Interdecadal variation in seawater δ¹³C and δ¹⁸O recorded in fish otoliths. Limnol. Oceanogr. **54**: 1665–1668. doi:10.4319/lo.2009.54.5.1665

Tan, K., J. Ransangan, K. Tan, and K. L. Cheong. 2023. The impact of climate change on Omega-3 long-chain polyunsaturated fatty acids in bivalves. Crit. Rev. Food Sci. Nutr.: 1–11. doi:10.1080/10408398.2023.2242943

Tuerena, R. E., R. S. Ganeshram, M. P. Humphreys, T. J. Browning, H. Bouman, and A. P. Piotrowski. 2019. Isotopic fractionation of carbon during uptake by phytoplankton across the South Atlantic subtropical convergence. Biogeosciences **16**: 3621–3635. doi:10.5194/bg-16-3621-2019

Vander Zanden, M. J., and J. B. Rasmussen. 1999. Primary consumer δ¹³C and δ¹⁵N and the trophic position of aquatic consumers. Ecology **80**: 1395–1404. doi:10.1890/0012-9658(1999)080[1395:PCCANA]2.0.CO;2

van Vliet, M. T., W. H. Franssen, J. R. Yearsley, F. Ludwig, I. Haddeland, D. P. Lettenmaier, and P. Kabat. 2013. Global river discharge and water temperature under climate change. Glob. Environ. Chang. **23**: 450–464. doi:10.1016/j.gloenvcha.2012.11.002

Vogel, J. C., P. M. Grootes, and W. G. Mook. 1970. Isotope fractionation between gaseous and dissolved carbon dioxide. Z. Phys. **230**: 225–238. doi:10.1007/BF01394688

Zampieri, M., A. Toreti, A. Schindler, and S. Gualdi. 2017. Atlantic multi-decadal oscillation influence on weather regimes over Europe and the Mediterranean in spring and summer. Glob. Planet. Change **151**: 92–100. doi:10.1016/j.gloplacha.2016.08.014

Zeebe, R. E., and D. Wolf-Gladrow. 2001. CO₂ in seawater: Equilibrium, kinetics, isotopes, v. **65**. Elsevier Oceanography Series, p. 1–346.
the metabolic part. Vie Milieu Life Environ. **66**: 305-314
https://archimer.ifremer.fr/doc/00387/49856/

Lheureux, A., and others. 2023. Trajectories of nutrients con-
centrations and ratios in the French coastal ecosystems:
20 years of changes in relation with large-scale and local
drivers. Sci. Tot. Environ. **857**: 159619. doi:10.1016/j.scitot
env.2022.159619

Liénart, C., and others. 2017. Dynamics of particulate organic matter composition in coastal systems: A spatio-temporal study at multi-system scale. Prog. Oceanogr. **156**: 221-239. doi:10.1016/j-pocean.2017.03.001

Liénart, C., and others. 2020. Long-term changes in trophic ecology of blue mussels in a rapidly changing ecosystem. Limnol. Oceanogr. **66**: 694–710. doi:10.1002/lno.11633

Liénart, C., A. Garbaras, S. Qvarfordt, H. Lim, M. Chynel, C. Robinson, T. Meziane, and A. M. L. Karlson. 2022. Spatio-temporal variation in stable isotope and elemental composition of key-species reflect environmental changes in the Baltic Sea. Biogeochemistry **157**: 149–170. doi:10.1007/s10533-021-00865-w

Liénart, C., M. Tedengren, A. Garbaras, H. Lim, M. Chynel, C. Robinson, T. Meziane, and A. M. L. Karlson. 2023. Diet quality determines blue mussel physiological status: A long-term experimental multi-marker approach. J. Exp. Mar. Biol. Ecol. **563**: 151894. doi:10.1016/j.jembe.2023.151894

Magni, P., S. Rajagopal, S. Como, J. M. Jansen, G. van der Velde, and H. Hummel. 2013. δ¹³C and δ¹⁵N variations in organic matter pools, *Mytilus* spp. and *Macoma balthica* along the European Atlantic coast. Mar. Biol. **160**: 541-552. doi:10.1007/s00227-012-2110-7

Marín Leal, J. C., and others. 2008. Stable isotopes (δ13C, δ15N) and modelling as tools to estimate the trophic ecol-
ogy of cultivated oysters in two contrasting environments.
Mar. Biol. **153**: 673-688. doi:10.1007/s00227-007-0841-7

Matoo, O. B., G. Lannig, C. Bock, and I. M. Sokolova. 2021. Temperature but not ocean acidification affects energy metabolism and enzyme activities in the blue mussel, *Mytilus edulis*. Ecol. Evol. **11**: 336-3379. doi:10.1002/ece3.7289

Milliman, J. D., K. L. Farnsworth, P. D. Jones, K. H. Xu, and L. C. Smith. 2008. Climatic and anthropogenic factors affecting river discharge to the global ocean, 1951-2000. Glob. Planet. Change **62**: 187-194. doi:10.1016/j.gloplacha.2008.03.001

Misarti, N., B. Finney, H. Maschner, and M. J. Wooller. 2009. Changes in northeast Pacific marine ecosystems over the last 4500 years: Evidence from stable isotope analysis of bone collagen from archeological middens. Holocene **19**: 1139-1151. doi:10.1177/0959683609357824

Mook, W. G. 2000. *Environmental isotopes in the hydrological cycle: Principles and applications*. UNESCO.

Patakamuri, S., and N. O'Brien. 2021. Modifiedmk: Modified versions of Mann Kendall and Spearman's rho trend

tests. R package version 1.6. https://CRAN.R-project.org/
package=modifiedmk

Post, D. M., C. A. Layman, D. A. Arrington, G. Takimoto, J. Quattrochi, and C. G. Montaña. 2007. Getting to the fat of the matter: Models, methods and assumptions for dealing with lipids in stable isotope analyses. Oecologia **152**: 179-189. doi:10.1007/s00442-006-0630-x

Pörtner, H. O., M. Langenbuch, and B. Michaelidis. 2005. Synergistic effects of temperature extremes, hypoxia, and increases in CO₂ on marine animals: From earth history to global change. J. Geophys. Res. Ocean. **110**: 1-15. doi:10.1029/2004JC002561

Quay, P., R. Sonnerup, J. Stutsman, J. Maurer, A. Körtzinger, X. A. Padin, and C. Robinson. 2007. Anthropogenic CO₂ accumulation rates in the North Atlantic Ocean from changes in the ¹³C/¹²C of dissolved inorganic carbon. Global Bio-geochem. Cycles **21**: 1-15. doi:10.1029/2006GB002761

R Core Team. 2022. *R: A language and environment for statistical computing*. R Foundation for Statistical Computing, https://www.R-project.org/

Schloesser, R. W., J. R. Rooker, P. Louchuoarn, J. D. Neilson, and D. H. Secor. 2009. Interdecadal variation in seawater δ¹³C and δ¹⁸O recorded in fish otoliths. Limnol. Oceanogr. **54**: 1665-1668. doi:10.4319/lo.2009.54.5.1665

Tan, K., J. Ransangan, K. Tan, and K. L. Cheong. 2023. The impact of climate change on Omega-3 long-chain polyunsaturated fatty acids in bivalves. Crit. Rev. Food Sci. Nutr.: 1-11. doi:10.1080/10408398.2023.2242943

Tuerena, R. E., R. S. Ganeshram, M. P. Humphreys, T. J. Browning, H. Bouman, and A. P. Piotrowski. 2019. Isotopic fractionation of carbon during uptake by phytoplankton across the South Atlantic subtropical convergence. Biogeosciences **16**: 3621-3635. doi:10.5194/bg-16-3621-2019

Vander Zanden, M. J., and J. B. Rasmussen. 1999. Primary consumer δ¹³C and δ¹⁵N and the trophic position of aquatic consumers. Ecology **80**: 1395-1404. doi:10.1890/0012-9658(1999)080[1395:PCCANA]2.0.CO;2

van Vliet, M. T., W. H. Franssen, J. R. Yearsley, F. Ludwig, I. Haddeland, D. P. Lettenmaier, and P. Kabat. 2013. Global river discharge and water temperature under climate change. Glob. Environ. Chang. **23**: 450-464. doi:10.1016/j.gloenvcha.2012.11.002

Vogel, J. C., P. M. Grootes, and W. G. Mook. 1970. Isotope fractionation between gaseous and dissolved carbon dioxide. Z. Phys. **230**: 225-238. doi:10.1007/BF01394688

Zampieri, M., A. Toreti, A. Schindler, and S. Gualdi. 2017. Atlantic multi-decadal oscillation influence on weather regimes over Europe and the Mediterranean in spring and summer. Glob. Planet. Change **151**: 92-100. doi:10.1016/j.gloplacha.2016.08.014

Zeebe, R. E., and D. Wolf-Gladrow. 2001. CO₂ in seawater: Equilibrium, kinetics, isotopes, v. **65**. Elsevier Oceanography Series, p. 1-346.
Acknowledgments

This article is based on a collaborative work with the team of the ROCCH
monitoring network (Ifremer). We thank the members of the ROCCH and
of the different institutions, from the field workers and analysts to the
coordinators, who made the use of the data possible. We would like to
thank the different laboratories teams of the National Oceanic and
Atmospheric Administration for producing atmospheric and teleconnec-
tion indices data. We would like to thank the anonymous reviewers for
their valuable work that helped in improving this manuscript. This work is

part of the research project EVOLECO-BEST funded by the Office Français
de la Biodiversité (OFB).

Submitted 17 October 2023

Revised 10 April 2024

Accepted 14 April 2024
Acknowledgments

This article is based on a collaborative work with the team of the ROCCH
monitoring network (Ifremer). We thank the members of the ROCCH and
of the different institutions, from the field workers and analysts to the
coordinators, who made the use of the data possible. We would like to
thank the different laboratories teams of the National Oceanic and
Atmospheric Administration for producing atmospheric and teleconnec-
tion indices data. We would like to thank the anonymous reviewers for
their valuable work that helped in improving this manuscript. This work is

part of the research project EVOLECO-BEST funded by the Office Français
de la Biodiversité (OFB).

Submitted 17 October 2023

Revised 10 April 2024

Accepted 14 April 2024