Seasonal survey of metazoan meiofauna and surface sediment organics in a non-tidal turbulent sublittoral prodelta (northwestern Mediterranean)

As part of the French research program ECOMARGE, metazoan meiofauna abundances along with local physical, chemical and microbial characteristics were monitored generally monthly over a 14-month period in a silty-muddy prodelta located at 26 m depth off the Teˆt River outlet in the northwestern (NW) Mediterranean. Meiofauna densities ranged from 1266 to 5586 individuals 10 cm−2, and were dominated by nematodes (91–98%), followed by harpacticoid copepods (1.37–6.96%) and kinorhynchs (up to 1.40%). Bottom water temperature varied between 9.5°C in winter to over 20°C in early autumn. All parameters analysed in the surface sediment also exhibited high temporal variability: fine particle content (7.6–18.4% < 40 μm), alcium carbonate (5–8.6%), total organic carbon (4.1–7.3 mg g−1), organic nitrogen (0.35–0.95 mg g−1), C:N ratios (5.6–19.7), total amino acids (159–2358 μg g−1) and sugars (315–1553 μg g−1), lignin by-products (6–61 μg g−1), chlorophyll- a (0.30–1.20 μg g−1), phaeopigments (1.12–3.62 μg g−1), total chloroplastic pigments (1.42–4.58 μg−1), viable bacterial numbers (1.9 x 105–3.9 x 107 Colony Forming Units ml−1), microheterotrophic total uptake (18.3–74.2% after 5 h) and respiration (5.2–28.8%) of14C-glucose. Seasonal trends were not always obvious, and some variables were significantly correlated with each other. Because the survey was carried out in a complex system affected by strong frequent winds and irregular discharges of the river, different expressions of these climatic factors were included in the data set in an attempt to understand the relationships between variables and ultimately highlight the forces driving the observed abundance patterns. Further analysis showed that: (1) most of the parameters were strongly influenced by the climatic events that occurred prior to sampling, and (2) most of the correlations were largely explained by the concomittant influence of these events on the corresponding variables. Although some parameters were enhanced, many were affected negatively due to physical disturbance (mixing, resuspension, erosion). The observed patterns and relationships appeared to result primarily from the high physical variabilily of the system combined with a low sampling frequency.