Dataset from a mesocosm experiment testing the effects of a terrestrial runoff on a Mediterranean plankton community

Climate change is expected to induce more frequent and intense extreme rainfall events in the Mediterranean region, causing increased runoff of land-derived matter into coastal waters. To understand how this affects plankton communities, an in situ mesocosm experiment was conducted in the Mediterranean Thau lagoon (43°24’53’’N, 3°41’16’’E), south of France, in spring 2021. Soil from a nearby oak forest, the Puéchabon state forest (43°44’29’’N, 3°35’45’’E), mixed with water from the main river tributary, La Vène (43°30'56.4"N 3°41'33.5"E), was used to simulate terrestrial runoff in replicate mesocosms. High-frequency monitoring of dissolved oxygen concentration, chlorophyll-a fluorescence, salinity, photosynthetically available radiation (PAR), and temperature was performed during the entire experiment in every mesocosm enclosure at a depth of 1m. Additionally, manual sampling for the analysis of organic and inorganic nutrients (nitrate, nitrite, ammonium, silicate, orthophosphate, particulate organic carbon, particulate organic nitrogen, dissolved organic carbon, dissolved inorganic carbon), pH, carbonate chemistry, and maximum quantum yield (Fv : Fm) of Photosystem II (PSII) was performed multiple time during the experiment. High-frequency data were used to estimate gross oxygen primary production (GPP), respiration (R), and phytoplankton growth (µ) and loss (L) rates, fllowing two recently published methods (Soulié et al. 2021; 2022). 


Biological oceanography, Environment


mesocosm experiment, high-frequency data, plankton metabolism, terrestrial runoff, Thau Lagoon, Mediterranean Sea


43.414699N, 43.414699S, 3.688125E, 3.688125W


The two control mesocosms were labeled C1 and C2, and the two mesocosms in which a terrestrial runoff was simulated were labeled B1 and B2.

High-frequency sensor measurements:

-Chlorophyll-a fluorescence: ECO-FLNTU, Sea-Bird Scientific. Before the experiment, sensors were calibrated with diluted and undiluted lagoon water whose Chlorophyll-a concentrations, measured with a spectrofluorometer (LS 45, Perkins Elmer), ranged from 0 to 1.24 µg L-1. After the experiment, the sensor Chlorophyll-a fluorescence data was corrected with Chlorophyll-a concentrations measured daily and in each mesocosm using High Performance Liquid Chromatography (HPLC, Shimadzu) and the method of Zapata et al. (2000).

-Dissolved oxygen: Aanderaa 3835. Before the experiment, sensors were calibrated with a 0% and a 100% saturation points. The 0% saturation point was reached by adding potassium metabisulfite into distilled water. The 100% saturation point was optained by bubbling air into the distilled water. After the experiment, the sensor data were corrected for temperature and salinity following the procedure detailed in Bittig et al. (2018), data were also corrected with dissolved oxygen concentrations measured daily and in each mesocosm using the Winkler method (Soulié et al. 2021).

-Conductivity: Aanderaa 4319. Before the experiment, sensors were calibrated with freshwater (salinity 0) and lagoon water (salinity 37.36).

-Water temperature: Thermistore Probe 107, Campbell Scientific. Before the experiment, sensors were calibrated in a temperature-controlled water bath at 10°C, 15°C, 20°C, and 25°C.

-Underwater photosynthetically available radiation (PAR): Li-193, Li-Cor. 


Plankton processes estimated from high-frequency measurements:

-Respiration, Gross Primary Production: Calculated from high-frequency dissolved oxygen concentration measurements according to the method detailed in Soulié et al. (2021).

-Phytoplankton growth and loss rates: Calculated from high-frequency chlorophyll-a concentration measurements according to the method detailed in Soulié et al. (2022).


Monitoring for chemical variables from manual sampling of the mesocosms:

-Dissolved nitrate, nitrite, orthophosphate, silicate concentrations: Measured with an automated colorimeter (Skalar Analytical), following Aminot and Kérouel (2007).

-Dissolved ammonium concentrations: Measured with the fluorometric method (Turner Design, 7200-067-W), following Holmes et al. (1999).

-Dissolved organic carbon: Measured with the high-temperature catalytic oxidation using a total organic carbon analyser (TOC-L-CSH, Shimadzu).

-Particulate organic carbon and nitrogen: Measured using a CHN analyser (Unicube, Elementar).

-pH: Measured spectrophotometrically (LAMBDA 365 UV/Vis, Perkins Elmer) according to Clayton and Byrne (1993) and Dickson et al. (2007).

-Total alkalinity: Measured using an open-cell potentiometric titration with a derivative determination of the end point, according to Hernandez-Ayon et al. (1999).

-Dissolved inorganic carbon concentration and carbon dioxyde partial pressure: Calculated using the CO2SYS program (Pierrot et al. 2006).



Aminot, A. and Kérouel R.: Dosage automatique des nutriments dans les eaux marines. Méthodes en flux continu. Ed. Ifremer; 336 p. ISBN 2-84433-133-5, 2007.

Bittig, H. C., Körtzinger, A., Neill, C., Van Ooijen, E., Plant, J. N., Hahn, J., et al.: Oxygen optode sensors: principle, characterization, calibration, and application in the Ocean. Front. Mar. Sci. 4:429., 2018.

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Dickson, A. G., Sabine, C. L., Christian, J. R., and North Pacific Marine Science Organization.: Guide to best practices for ocean CO₂ measurements. North Pacific Marine Science Organization., 2007.

Hernández-Ayón, J. M., Belli, S. L., and Zirino, A.: pH, alkalinity and total CO2 in coastal seawater by potentiometric titration with a difference derivative readout. Analytica Chimica Acta 394(1): 101–108., 1999.

Holmes, R. M., Aminot, A., Kérouel, R., Hooker, B. A., and Peterson, B. J.: A simple and precise method for measuring ammonium in marine and freshwater ecosystems. Can. J. Fish. Aq. Sci. 56(10): 1801-1808., 1999.

Pierrot, D. E., Lewis, D., and Wallace, W. R.: MS Excel Program Developed for CO2 System Calculations. ORNL/CDIAC‐105a. Oak Ridge, Tennessee: Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy., 2006.

Soulié, T., Mas, S., Parin, D., Vidussi, F., and Mostajir, B.: A new method to estimate planktonic oxygen metabolism using high-frequency sensor measurements in mesocosm experiments and considering daytime and nighttime respirations. Limnol. Oceanogr. Methods 19:303-316., 2021.

Soulié, T., Vidussi, F., Courboulès, J., Mas, S., and Mostajir, B. Metabolic responses of plankton to warming during different productive seasons in coastal Mediterranean waters revealed by in situ mesocosm experiments. Sci. Rep. 12:9001. Doi: 10.1038/s41598-022-12744-x, 2022.

Zapata, M., Rodriguez, F., and Garrido, J. L.: Separation of chlorophylls and carotenoids from marine phytoplankton: a new HPLC method using a reversed phase C8 column and pyridine-containing mobile phases. Mar. Ecol. Prog. Ser. 195: 29-45,, 2000.


Sensor measurements in the control (C1,C2) mesocosms and in the mesocosms in which a terrestrial runoff was simulated (B1,B2).
6 MoCSVQuality controlled data
Discrete measurements of chemical variables in the control (C1,C2) mesocosms and in the mesocosms in which a terrestrial runoff was simulated (B1,B2).
21 KoCSVQuality controlled data
Plankton processes estimated from high-frequency measurements in the control (C1,C2) mesocosms and in the mesocosms in which a terrestrial runoff was simulated (B1,B2).
6 KoCSVQuality controlled data
How to cite
Soulié Tanguy, Vidussi Francesca, Courboulès Justine, Heydon Marie, Mas Sébastien, Voron Florian, Cantoni Carolina, Joux Fabien, Mostajir Behzad (2023). Dataset from a mesocosm experiment testing the effects of a terrestrial runoff on a Mediterranean plankton community. SEANOE.

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