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Elsevier, Deep Sea Research Part I: Oceanographic Research Papers, (100), p. 1-12, 2015

DOI: 10.1016/j.dsr.2015.02.006

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Temporal variability of nutrient concentrations in the northwestern Mediterranean sea (DYFAMED time-series station)

This paper is available in a repository.
This paper is available in a repository.

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Abstract

Nitrate, phosphate, and silicate concentration profiles were measured at monthly frequency at the DYFAMED time-series station (central Ligurian Sea) between 1991 and 2011. The resulting data set, which constitutes the longest open-ocean time-series in the Mediterranean Sea, underwent quality control. A reproducible climatological pattern was observed with an unprecedented resolution, confirming the typical seasonal cycle of mid-latitudes. In summer and autumn, when the water mass is well stratified, i.e. the mixed layer depth (MLD) is shallow, nutrient concentrations in surface are very low or under the detection limit. In winter, as a result of the MLD extent, nutrients are supplied to the surface layer. Then, nutrient concentrations progressively decrease during spring. MLD appears to play a key role in controlling nutrient availability in the surface layer, but a direct, quantitative relationship between MLD and nutrient concentrations is difficult to establish due to undersampling. Regarding nutrient molar ratios (N:P, Si:N, and Si:P), results show anomalous values compared to those of other oceanic regions, presumably due to strong influence of external sources. As a consequence, nutrient molar ratios exhibit a seasonal pattern, with, in particular, an increase of the N:P ratio in condition of stratification. Over the period 1991–2011, the DYFAMED data set reveals decadal trends in nitrate and phosphate concentrations in deep waters (+0.23% and –0.62%, respectively) resulting in increasing N:P and Si:P ratios (+1.14% and +0.85% per year, respectively). Such a long-term variability is presumably related to changes in water mass and/or changes in external sources, even if it is difficult to assess due to not enough concomitant data from atmospheric and riverine inputs.