DOI: 10.5061/dryad.v15dv428q
title: A mesocosm experiment testing the combined effects on plankton community of a terrestrial organic matter runoff and a warming in small freshwater reservoirs

description: Small freshwater reservoirs are ecosystems of global importance both for
 the great biodiversity they shelter, the ecosystem services they provide
 and the freshwater resources they constitute. An increase in temperatures
 and precipitation intensity due to climate change is expected by the end
 of the century. These changes should result in an increase in interactions
 between lakes and watersheds, leading in particular to increased inputs of
 terrestrial organic matter (tDOM) likely to impact the functioning of
 small lake ecosystems. In this context, a mesocosm experiment was carried
 out to study the combined effect of two disturbances - input of tDOM and
 temperature rise - on pelagic communities. The experiments were conducted
 within the National Experimental Platform for Aquatic Ecology (PLANAQUA)
 at CEREEP-Ecotron Ile-de-France located in Saint-Pierre-lès-Nemours
 (France). The experiment was carried out in twelve 1m3 mesocosms placed
 outside during 6 weeks, from June 8 to July 19, 2021. The mesocosms are
 circular tanks with walls allowing the circulation of a heat transfer
 fluid whose temperature is controlled by thermo-refrigerator pumps. The
 mesocosms were randomly filled with unfiltered water taken from small
 oligotrophic tanks located on the site and containing plankton and
 microorganisms. Four juvenile fish roach (Rutilus rutilus) were introduced
 at the start of the experiment in each mesocosm. Three replicates of two
 crossed treatments were carried out in these mesocosms. These treatments
 included a temperature differential of 6°C (18°C and 24°C) maintained
 throughout the experiment and, for the addition of tDOM, either no
 addition or an initial increase in tDOM concentration of 65 µM dissolved
 organic carbon originating from natural forest soil, representing a total
 enrichment in organic carbon of +25%. The mesocosms were manually stirred
 every day before sampling and measurements with different probes (see
 below for details).
description: <strong>Mesocosms</strong> The mesocosms (called ECORIUM) are made of double-walled 316 stainless steel tanks. The internal diameter is 1300 mm and the height is 820 mm. Glycol water circulates within the double wall to regulate the temperature inside the tank between -10°C and 45°C. The three <em>in situ</em> control mesocosms were labeled C1, C2, C3, the three mesocosms in which terrestrial runoff was simulated were labeled T1, T2, T3, the three mesocosms in which temperature warming was simulated were labeled W1, W2, W3, the three mesocosms in which both terrestrial runoff and temperature warming were simulated were labeled TW1, TW2, TW3. <strong>Sampling and</strong> <em><strong>in situ</strong></em> <strong>measurements</strong> Sampling was done using a 2-L sampling bottle (Uwitec Sapling Bailer USB 50020, Mondsee, Austria). Immersion of a multiparameter probe (YSI EXO2) was performed after stirring to measure the temperature, conductivity, turbidity, salinity, pH, O<sub>2</sub> saturation and Chlorophyll <em>a</em> values in surface waters. Immersion of a multispectral spectrofluorometer probe (FluoroProbe BBE Moldaenke) was performed after stirring the water in the mesocosms to measure the concentrations (in µg Chl-a.L^-1^) of different phytoplanktonic groups: green algae, cyanobacteria, diatoms and cryptophytes. Yellow substances and transmission (in %, as a proxy of the turbidity) were also measured. <strong>Nutrients analysis</strong> For the analysis of inorganic nutrients (PO<sub>4</sub><sup>2-</sup>, NO<sub>3</sub>^-, <sup>NO<sub>2</sub></sup>-^) water samples (30 mL) were filtered through 0.2 μm filters, stored in tubes at -20°C, and then analysed using an autoanalyser (AA3HR, Seal Analytical). <strong>Organic matter analyses</strong> For dissolved organic carbon (DOC) concentrations, samples (30 mL) were filtered through pre-calcined GF/F glass fiber filters with a diameter of 47 mm (Whatman), then stored in glass tubes and preserved with 35 μL of 85% H<sub>3</sub>PO<sub>4</sub> at room temperature and in the dark. DOC concentrations were then determined using the high catalytic oxidation technique with a Shimadzu TOC-L analyser. For optical properties of dissolved organic matter (DOM), 60 mL of each sample was filtered through a 47 mm diameter GF/F filter and collected in an amber glass tube. All samples were stored at 4°C in the dark prior to characterization. Absorbance measurements of colored DOM (CDOM) were performed using a spectrophotometer HP8453 (Hewlett–Packard, Agilent Technologies, Massy, France). Fluorescence measurements of DOM (FDOM) were performed using a Varian Cary Eclipse spectrofluorometer according to Murphy et al. (2013). Data were analysed using three-dimensional excitation-emission matrix fluorescence spectroscopy (EEM) and parallel factor analysis (PARAFAC). The emission and excitation characteristics allowed compounds to be identified into two categories: humic substances with humic acids (Component 3) and fulvic acids (Component 5), and substances of protein origin with aromatic amino acids such as tyrosine (Component 1) and tryptophan (Component 4). The nature of Component 2 (protein-like compound) has not been identified. Indices were calculated to characterise the organic matter composition, including the BIX biological index indicating recent indigenous contributions (Huguet et al., 2009), the HIX humification index providing information on the source, degree of humification and molecular structure, the fluorescence index FI, which provides information on the source or degree of organic matter degradation (Fellman et al., 2010), and the a254 index, which indicates the content of aromatic amino acids (D’Andrilli et al., 2022). Samples (70 to 170 mL) for particulate organic carbon (POC) and nitrogen (PON) concentrations (mg.L^-1^) were filtered onto pre-calcined GF/F glass fiber filterswith a diameter of 47 mm (Whatman). In order to remove the mineral fraction from filters, 550 μL of H<sub>2</sub>SO<sub>4</sub> was added to the filters, which were then dried at 50°C for several hours. The concentrations of carbon and nitrogen were then determined after combustion through a CHN elemental analyser (Flash EA 1112 Series, Thermo Electron Corporation) according to Sharp (1974). <strong>Cytometric analysis</strong> Samples for bacterial abundance (1.5 mL) were preserved with glutaraldehyde (1% final concentration) and stored at -80°C. Samples were stained with SYBR<sup>TM</sup> Green I (Thermofisher Scientific) and analyzed on a flow cytometer (FACSCanto, BD Biosciences) according to Gasol and Del Giorgio (2000). Samples for phytoplankton abundance (1.5 mL) were preserved with glutaraldehyde (1% final concentration) and stored at -80°C. Samples were analyzed on a flow cytometer (FACSCanto, BD Biosciences). Populations were identified and enumerated based on forward scatter (FSC), side scatter (SSC) light diffractions, and natural pigment fluorescence (chlorophyll-a, phycoerythrin). This allowed the discrimination of two groups of picophytoplancton (PicoEuk1 and PicoEuk2), and one group of nanophytoplankton (Nano). <strong>Microbial respiration</strong> Respiration rates were derived from continuous dissolved oxygen (O<sub>2</sub>) measurements using a SensorDish Reader (SDR; Presens, Germany) optical sensing system equipped with 24 glass vials of 5 mL containing non-invasive O<sub>2</sub> sensors (OxoDish). Incubations were performed at <em>in situ</em> temperature (18°C or 24°C) in the dark in climatic chambers. <strong>Aminopeptidase activity</strong> Extracellular aminopeptidase activity was measured with the use of a fluorogenic substrate (Hoppe, 1983) with the modifications for plate readers described in the study by Sala et al. (2016). Incubations were performed at <em>in situ</em> temperature (18°C or 24°C) in the dark in climatic chambers. <strong>Microbial metabolism on 31 C-substrates</strong> The metabolic profile of microbial communities was estimated using the Biolog® EcoPlate™ method according to Garland et al. (2001). At some selected sampling dates, raw water (150 µL) was inoculated in each well of the microplates (Alliance Bio-expertise, Guipry-Messac, France). Microplates were then incubated in the dark either at 18°C or at 24°C, depending on the temperature of the mesocosm from which the water samples were taken. Absorbance was measured at 590 nm every 24h during 9 days using a Microplate Reader (Bio-Rad Laboratories, Model 680). After data trimming (absorbance-threshold value of 0.10), the average well-colour development (AWCD) was determined for the whole microplate, per substrate family and per substrate. The functional richness (FR) was expressed as the number of different substrates used by the microbial community. The NUSE index (Nitrogen Use Index) was expressed as the relative absorbance of Nitrogen-containing substrates (Sala et al., 2006). The Shannon diversity and Pielou evenness indices were calculated. All data used were acquired after 4 days of incubation, to ensure that all enzymatic reactions were detected. <strong>Zooplankton</strong> Zooplankton were collected on the following dates: 08/06, 11/06, 15/06, 21/06, 28/06, 05/07, 12/07 and 19/07. Samples were obtained by filtering 50 μm of water through a nylon filter, collected using a Niskin bottle for each mesocosm. A total of 27.44 L of water was filtered per mesocosm (28 L collected minus samples taken for phytoplankton and protista analysis). The zooplankton collected were transferred to a polypropylene vial stored in 80% ethanol at 4°C in the dark. Prior to analysis, the samples were refiltered into 3 categories: greater than 850 μm, between 850 μm and 400 μm and less than 400 μm. The first category was processed using a binocular magnifier, while the other two were processed using the Flowcam 8100 (Beckman Coulter) and Ecotaxa software (Picheral et al., 2017). The Flowcam is an imaging tool used to classify and measure organisms and particles contained in a liquid medium. Before being run through the Flowcam, each sample was diluted in distilled water to obtain 500mL and 5 mL were taken using a propipette and then placed on the device for analysis. The images generated by Flowcam were sorted and determined using the Ecotaxa online platform. The results are expressed in nb/L and have been grouped into functional groups: (1) Large filter feeders corresponding to Ostracods and Cladocerans; (2) Small filter feeders corresponding to Rotifers and Nauplii; (3) Predators corresponding to Copepods except Nauplii. <strong>Fish</strong> Four fish fry (<em>Rutilus rutilus</em>) were introduced into each mesocosm at the start of the experiment. The average biomass of the fry introduced at the start of the experiment was calculated by weighing 32 fish from the same batch as those used to inoculate the mesocosms, thus avoiding handling and injuring the individuals introduced into the mesocosms. At the end of the experiment, all fish were caught from each mesocosm and weighed (Kern ABT 220-4M). The four individuals were found in all mesocosms except for two replicates of the T treatment and one replicate of the TW treatment, where two, three and three fish were caught, respectively.
description: # A mesocosm experiment testing the combined effects on plankton community
 of a terrestrial organic matter runoff and a warming in small freshwater
 reservoirs Dataset DOI: [10.5061/dryad.v15dv428q](10.5061/dryad.v15dv428q)
 ## Access information Comments and requests should be addressed to D.
 Lamy, F.D. Hulot, S. Fiorini and F. Joux. **Acnowledgements** These
 datasets were produced thanks to the help of Francis Dohou from CEREEP,
 Gwendal Latouche, Clotilde Perrot-Guillaume, Marion Francisque, Élise
 Cabanne, Geoffrey Devisse, from ESE. This work was part of the RESTORE
 project, funded by the French National Research Agency under the grant
 n°ANR-19-CE32-0013. ## Description of the data and file structure
 **Temporal extent**: 2021-06-8 – 2021-07-19 **Location** 48.283305N,
 2.671189E ### Files and variables The dataset resulting from this
 experiment are included in the archive
 "Data_WP2_RESTORE_mesocosm_experiment.zip". Please note that the
 variables definitions are included as excel sheets in the different data
 files. It includes: “Data_WP2_multiparametric_probe.xlsx” contains the
 values of temperature, salinity, turbidity, O~2~ saturation and pH
 measured by a multi-parametric probe. “Data_WP2_BBE.xlxs” contains the
 concentrations of the main phytoplanktonic groups by BBE probe.
 “Data_WP2_abiotic_biotic_parameters. xlsx” contains the values of: ·    
 Inorganic nutrients (NO~3~^-^, NO~2~^-^, NH~4~^+^, PO~4~^3-^)
 concentrations measured using an automated colorimetric technique ·    
 Dissolved organic carbon concentrations measured using the high catalytic
 oxidation technique ·     Particulate organic carbon and nitrogen
 concentrations measured by gaz chromatography after combustion (elemental
 CHN analyser) ·     Fluorescence of dissolved organic matter by
 spectrofluorometry ·     Absorbance of dissolved organic matter by
 spectrophotometry ·     Chlorophyll-a concentrations measured by a
 multiparametric probe ·     Bacterial, nano- and picoeukaryotes and
 phytoplankton abundances measured by flow cytometry ·     Taxonomic
 composition and abundances of phytoplankton identified using an inverted
 microscope ·     Microbial respiration measured by optodes ·    
 Aminopeptidase activity measured by fluorogenic substrate and
 spectrofluorometry “Data_WP2_zooplancton. xlsx” contains the values of the
 counts of the main functional groups of zooplankton identified by
 microscopy and Flowcam. “Data_WP2_Ecoplates.xlsx” contains the values of
 the microbial metabolism on 31 C-substrates measured using Biolog
 Ecoplates © and spectrophotometry. “Data_WP2_fish.xlsx” contains the
 weight values of the fish that were introduced into each mesocosm at the
 start of the experiment. **References**  D’Andrilli J, Silverman V,
 Buckley S, Rosario-Ortiz FL. (2022) Inferring ecosystem function from
 dissolved organic matter optical properties: a critical review. Environ
 Sci Technol 56:11146–61.
 [doi.org/10.1021/acs.est.2c04240](https://doi.org/10.1021/acs.est.2c04240
 "DOI URL") Fellman JB, Hood E, Spencer RGM. (2010) Fluorescence
 spectroscopy opens new windows into dissolved organic matter dynamics in
 freshwater ecosystems: A review. Limnol Oceanogr 55:2452–62.
 [doi.org/10.4319/lo.2010.55.6.2452](https://doi.org/10.4319/lo.2010.55.6.2452) Garland J.L, Mills A.L., Young J.S. (2001). Relative effectiveness of kinetic analysis *vs* single point readings for classifying environmental samples based on community-level physiological profiles (CLPP). Soil Biol and Bioch 33: 1059–1066. [doi.org/10.1016/S0038-0717(01)00011-6](http://doi.org/10.1016/S0038-0717\(01\)00011-6) Gasol J.M., Del Giorgio P.A. (2000) Using flow cytometry for counting natural planktonic bacteria and understanding the structure of planktonic bacterial communities. Sci Mar 64:197–224. [doi.org/10.3989/scimar.2000.64n2197](https://doi.org/10.3989/scimar.2000.64n2197) Hoppe H.G. (1983) Significance of exoenzymatic activities in the ecology of brackish water: measurements by means of methylumbelliferyl substrates. Mar Ecol Progr Ser 11: 299–308. [doi.org/10.3354/meps011299](http://doi.org/10.3354/meps011299) Huguet A, Vacher L, Relexans S, Saubusse S, Froidefond JM, Parlanti E. (2009) Properties of fluorescent dissolved organic matter in the Gironde Estuary. Org Geochem 40:706–19. [doi.org/10.1016/j.orggeochem.2009.03.002](http://doi.org/10.1016/j.orggeochem.2009.03.002) Murphy KR, Stedmon CA, Graeber D, Bro R. (2013) Fluorescence spectroscopy and multi-way techniques. PARAFAC. Anal Methods 5:6541-6882. Picheral M, Colin S, Irisson J-O. (2017) EcoTaxa, a tool for the taxonomic classification of images. [http://ecotaxa.obs-vlfr.fr](http://ecotaxa.obs-vlfr.fr) Sala M.M., Estrada M., Gasol J.M. (2006) Seasonal changes in the functional diversity of bacterioplankton in contrasting coastal environments of the NW Mediterranean. Aquat Microb Ecol.  44:1–9. [doi.org/10.3354/ame044001](http://doi.org/10.3354/ame044001)  Sala M.M., Aparicio F.L., Balagué V., Boras J.A., Borrull E., Cardelús C., et al. (2016) Contrasting effects of ocean acidification on the microbial food web under different trophic conditions. ICES J Marine Sci 73:670–679. [doi.org/10.1093/icesjms/fsv130](https://doi.org/10.1093/icesjms/fsv130) Sharp J.H. (1974) Improved analysis for particulate organic carbon and nitrogen from seawater. Limnol Oceanogr 19:984–989. [doi.org/10.4319/lo.1974.19.6.0984](https://doi.org/10.4319/lo.1974.19.6.0984) #