Spatial and temporal interaction between sediment and microphytobenthos in a temperate estuarine macro-intertidal bay

Abstract

Intertidal flats of the estuarine macro-intertidal Baie des Veys (France) were investigated to identify spatial features of sediment and microphytobenthos (MPB) in April 2003. Gradients occurred within the domain, and patches were identified close to vegetated areas or within the oyster-farming areas where calm physical conditions and biodeposition altered the sediment and MPB landscapes. Spatial patterns of chl a content were explained primarily by the influence of sediment features, while bed elevation and compaction brought only minor insights into MPB distribution regulation. The smaller size of MPB patches compared to silt patches revealed the interplay between physical structure defining the sediment landscape, the biotic patches that they contain, and that median grain-size is the most important parameter in explaining the spatial pattern of MPB. Small-scale temporal dynamics of sediment chl a content and grain-size distribution were surveyed in parallel during 2 periods of 14 d to detect tidal and seasonal variations. Our results showed a weak relationship between mud fraction and MPB biomass in March, and this relationship fully disappeared in July. Tidal exposure was the most important parameter in explaining the summer temporal dynamics of MPB. This study reveals the general importance of bed elevation and tidal exposure in muddy habitats and that silt content was a prime governing physical factor in winter. Biostabilisation processes seemed to behave only as secondary factors that could only amplify the initial silt accumulation in summer rather than primary factors explaining spatial or long-term trends of sediment changes. KEY WORDS: Benthic diatoms · Benthos · Coastal ecosystems · Intertidal flats · Baie des Veys · Normandie · Spatial pattern · Geostatistics · KrigingResale or republication not permitted without written consent of the publisher Mar Ecol Prog Ser 458: 53-68, 2012 Kronkamp 1999, Perissinotto et al. 2003). Dynamics of marine systems vary widely in their temporal and spatial components due to complexity in the benthopelagic coupling (Zajac 2008). The trophic environment of benthic fauna in these systems is therefore characterised by a high degree of spatial heterogeneity, such as transition zones and patches (Deegan & Garritt 1997, Dubois et al. 2007) that are related to the landscape of their habitats. It appears very relevant to understand the spatial patterns of primary producers in relation to sediment in order to elucidate the role they play in the trophic food web and to assess the respective contributions of both components to consumer's diet (Lefebvre et al. 2009). The questions of spatial distribution of benthic primary producer are thus critical to gain new insights in the dynamics and structure of macrozoobenthos that inhabit these environments (Herman et al. 2000).There is a general consensus that MPB biomass varies along wide-scale environmental gradients and is not affected by an isolated variable but, rather, depends on a combination of factors controlling ...

Tidal and seasonal effects on the short-term temporal patterns of bacteria, microphytobenthos and exopolymers in natural intertidal biofilms (Brouage, France)

“…The fluctuation of biomass of the uppermost cm of sediment peaked around the emersion period at noon. Similar to previous studies (Blanchard et al, 2001;Orvain et al, 2012), the tidal rhythm was observed to have an influence on the chl a concentration, however, the effect was masked by other effects described in this study. The presence of the gastropod Peringia ulvae was a key parameter controlling the MPB biomass and the main differences observed between seasons were probably caused by grazing pressure.…”

“…1B) were defined by the wood stakes. Each day, three replicate squares were chosen randomly according to the sampling design described in a previous field study (Orvain et al, 2012). In these squares, surficial sediment was sampled hourly from the beginning (0 hour after area emersion) to the end of emersion (3 hours after area emersion), leading to four sampling times during every emersion periods.…”

“…These non-parametric tests are most appropriate when data are spatially auto-correlated (Legendre and Legendre, 1998;Fortin and Gurevitch, 2001). The space-time clustering procedure of Mantel (Mantel correlation RM and partial Mantel correlation RM * ) was performed to relate a matrix of Euclidian geographic distance among sampling sites and 3 matrices of temporal distance (hour and date, separately) with a matrix of distance between values of response variables in a generalized regression approach (Orvain et al, 2012). In the present study, 2 000 iterations were run using home-made programs coded in MATLAB 2008B.…”

Using High-Resolution Airborne Data to Evaluate MERIS Atmospheric Correction and Intra-Pixel Variability in Nearshore Turbid Waters

“…SPM concentration is generally higher than 100 g•m −3 in the waters adjacent to the northern mudflats, and lower than 20 g•m −3 in the southern area [31][32][33]. Phytoplankton growth is limited by too high SPM concentration in the most turbid waters, but high concentration of chlorophyll-a (Chl-a), over 10 mg•m −3 , has been documented in the vicinity of the tidal flats [31,34] and is due to the resuspension of benthic microalgae [35]. …”

Microbenthic Net Metabolism Along Intertidal Gradients (Cadiz Bay, SW Spain): Spatio-Temporal Patterns and Environmental Factors

“…Oxygen measurements are then usually upscaled to larger areas using several models of PP MPB developed for the purpose (Pinckney and Zingmark, 1993;Serôdio and Catarino, 2000). Regardless of the method used, seasonal and spatial patterns of PP MPB , similarly to MPB biomass, have been explained by a wide array of biotic and abiotic environmental variables depending on the environment studied Jesus et al, 2009;Orvain et al, 2012;Savelli et al, 2018).…”