Figure 1.
Factors involved in sediment resuspension and the associated microphytobenthos.
Figure 2.
Location of the Baie des Veys and sampling grid.
Table 1.
Variogram models with their parameter values and cross-validation results.
Figure 3.
PCA results of the benthic log-transformed variables for the 2 seasons.
Bathymetry (m), Chl a concentration (µg.g−1), mud fraction (% of total sediment) and mollusk biomass (g AFDW.m−2). Data used for the PCA resulted from the extraction of the corresponding kriged maps on the general sampling grid. Bathymetry was used as an auxiliary variable. A: Correlation circle; B: Scatter plot of individuals, “South (Spr)” and “South (Sum)” captions are confounded.
Figure 4.
BDV spring and summer kriged maps of benthic variables for the 2 seasons.
All variables were kriged on different variogram models depending on the data (Table 1). Geometrical scales were used to maximize the visualization of both gradients and the patchiness of the different variables. Mollusk maps are at different scales to account for the discrepancy in the data between the 2 sampling campaigns. A, B: Chl a concentration (µg.g−1); C, D: Mud fraction (%<63 µm of total sediment); E, F: Mollusks biomass (g AFDW g.m2). G: Bathymetry of the BDV, from low to high tide spring tide levels (m). H: Representation of the 3 subdomains defined by the PCA.
Table 2.
Mean weight and number of mollusks per m2 in the 2 samplings.
Table 3.
Response of selected variables to log-transformed benthic and pelagic variables.
Figure 5.
PCA results of the pelagic log-transformed variables for the 2 seasons.
Bathymetry (m), Chl a concentration (µg.L−1), SPIM (mg.L−1) and salinity. Data used for the PCA resulted from the extraction of the corresponding kriged maps at the location of the general sampling grid. A: Correlation circle; B: Scatter plot of individuals (Spr = Spring; Sum = Summer).
Figure 6.
BDV spring and summer kriged maps of pelagic variables for the 2 seasons.
All variables were kriged on different variogram models depending on the data (Table 1). Geometrical scales were used to maximize the visualization of both gradients and the patchiness of the different variables. Mollusk maps are at different scales to account for the discrepancy in the data between the 2 samplings. A, B: Chl a concentration (µg.L−1); C, D: SPiM amount (mg.L−1). E, F: Bottom mean current velocities and direction at the 2 sampling periods, calculated by the MARS-3D hydrodynamic model.
Table 4.
Comparison of inertia resulting from the separate analyses of each dataset.
Figure 7.
Cross-table resulting from the co-inertia analysis.
Represents the correlation between the benthic and pelagic datasets.
Table 5.
List of determined microalgal taxa from Lugol fixed water samples.
Figure 8.
BDV summer kriged maps of both benthic (A) and pelagic (B) phaeopigments.
Results are presented as % of total pigments.
Figure 9.
Temporal variations of δ13C and δ15N for C. gigas at 6 locations in the BDV.
Isotopic signature (A), Isotopic signature before (gray) and after (black) fractionation (B), contribution of sources to oyster diets (C), location of oysters within the farming structures in the north-western part of the bay (D). Organic matter sources are plotted with standard deviations (see Lefebvre et al., 2009) to distinguish their relative contribution to the diets in the 2 sampling campaigns (B). Horizontal bars indicate the ±SD of the mean for n = 5.