RESUMEN
We present two datasets composed of high frequency sensors data, vertical in situ profiles and laboratory chemical analysis data, acquired during two different aquatic mesocosm experiments performed at the OLA ("Long-term observation and experimentation for lake ecosystems") facility at the UMR CARRTEL in Thonon les Bains, on the French shore of Lake Geneva. The DOMLAC experiment lasted 3 weeks (4-21 October 2021) and aimed to simulate predicted climate scenarios (i.e. extreme events such as storms and floods) by reproducing changes in quality and composition of lake subsidies and runoff by increased inputs of terrestrial organic matter. The PARLAC experiment lasted 3 weeks (5-23 September 2022) and aimed to simulate turbid storms by light reduction. The experimental setup consisted of nine inland polyester laminated tanks (2.1 m length, 2.1 m width and 1.1 m depth) with a total volume of approximately 4000 L and filled with water directly supplied from the lake at 4m depth. Both experimental design included three treatments each replicated three times. The DOMLAC experiment involved a control treatment (no treatment applied) and two treatments simulating allochthonous inputs from two different dissolved organic matter (DOM) extract from peat moss Sphagnum sp. (Peat-Moss treatment) and Phragmites australis (Phragmite treatment). The PARLAC experiment involved a control treatment (no treatment applied) and two treatments simulating two different intensity of light reduction. In the Medium treatment transmitted light was reduced to 70% and in the High treatment transmitted light was reduced to 15%. The datasets are composed of: 1. In situ measures from automated data loggers of temperature, conductivity, dissolved oxygen and CO2 acquired every 5 minutes at 0.1, 0.5 and 1 m depth (DOMLAC) and 0.5m (PARLAC) for the entire period of the experiment. 2. In situ profiles (0-1 m) of temperature, conductivity, pH, dissolved oxygen (concentration and saturation) acquired twice a week during the experiment. 3. In situ measures of light spectral UV/VIS/IR irradiance (300-950 nm wavelength range) taken in the air and at 0, 0.5 and 1 m twice a week on the same day of the profiles at point 2. 4. Laboratory chemical analysis of integrated samples taken twice a week on the same day of the in situ profiles at point 2 and 3 of conductivity, pH, total alkalinity, NO3, total and particulate nitrogen (Ntot, Npart), PO4, total and particulate phosphorus (Ptot, Ppart), total and particulate organic carbon (TOC, POC), Ca, K, Mg, Na, Cl, SO4 and SiO2. Only for DOMLAC also analyses of NH4, NO2 and dissolved organic carbon (DOC). 5. Laboratory analysis of pigments (Chla, Chlc, carotenoids, phaeopigments) extracted from samples collected at point 4. 6. Only for DOMLAC, specific absorbance on the range 600-200nm of DOM (i.e. <0.7 µm) measured on samples collected at point 4. This dataset aims to contribute our understanding of how extreme climate events can alter lake subsidies and affect the regulation of ecosystem processes such as production, respiration, nutrient uptake and pigment composition. The data can be used for a wide range of applications as being included in meta-analysis aiming at generalising the effect of climate change on large lakes including simulating future scenarios in a broad range of geographical areas as we used different inputs of DOM leached from litters reproducing catchments characteristics typical of different latitudes, such as mostly dominated by large leaf forests and phragmites at middle latitude, and coniferous forests rich of peat mosses that spread along the water surface typical of Northern regions.
RESUMEN
This dataset complement a previously published dataset [1] and corresponds to the physico-chemical parameters data series produced during the MESOLAC experimental project [2]. The presented dataset is composed of: 1. In situ profiles (0-3m) of temperature, conductivity, pH, dissolved oxygen (concentration and saturation). 2. In situ measurements of light spectral UV/VIS/IR irradiance (300-950 nm wavelength range) taken at 0, 0.25, 0.5, 1, 1.5, 2 and 2.5m. 3. Laboratory chemical analysis of samples collected at 0 and 2 m (conductivity, pH, total alkalinity, NH4, NO2, NO3, total and particulate nitrogen (Ntot, Npart), PO4, total and particulate phosphorus (Ptot, Ppart), total, organic particulate and total particulate carbon (Ctot, Cpart-org, Cpart-tot), Cl, SO4, SiO2. 4. Laboratory analysis of pigments extracted from samples collected at 0 and 2 m (Chla, Chlc, carotenoids, phaeopigments). The experimental design is the same as in Tran-Khac et al [1]. Briefly, it consisted of nine pelagic mesocosms (about 3000 L, 3m depth) deployed in July 2019 in Lake Geneva near the shore of Thonon les Bains (France) aiming to simulate predicted climate scenarios (i.e. extreme events) and assess the response of planktonic communities, ecosystem functioning and resilience. During the experiment, physical parameters were measured twice a week. At the same time, samples were collected at 0 and 2m of depth for subsequent chemical laboratory analyses. These data are presented in the dataset file, ordered by sampling event (numbered from S1 to S8), treatment (Control-C, High-H and Medium-M) and replicates (1 to 3). For each sampling point the measured parameters are listed in columns, missing data and values below the detection limit are marked as NA (not available). This data set aims to contribute to the understanding of the effect of environmental forcing on lake physico-chemical characteristics (such as temperature, oxygen and nutrient concentration) under simulated intense weather events. To a broader extent, the presented data can be used for a wide variety of applications, including monitoring of a large peri-alpine lake functioning under environmental stress and being included in further meta-analysis to generalise the effect of climate change on large lakes. The two complementary dataset differ in the acquired data and methods, temporal and spatial resolution. They complete each other in terms of physico-chemical characterization of the experimental treatments and together can allow comparison of the two different monitoring strategies (continuous vs punctual) during in situ experimental manipulations.
RESUMEN
The effectiveness of environmental protection measures is based on the early identification and diagnosis of anthropogenic pressures. Similarly, restoration actions require precise monitoring of changes in the ecological quality of ecosystems, in order to highlight their effectiveness. Monitoring the ecological quality relies on bioindicators, which are organisms revealing the pressures exerted on the environment through the composition of their communities. Their implementation, based on the morphological identification of species, is expensive because it requires time and experts in taxonomy. Recent genomic tools should provide access to reliable and high-throughput environmental monitoring by directly inferring the composition of bioindicators' communities from their DNA (metabarcoding). The French-Swiss program SYNAQUA (INTERREG France-Switzerland 2017-2019) proposes to use and validate the tools of environmental genomic for biomonitoring and aims ultimately at their implementation in the regulatory bio-surveillance. SYNAQUA will test the metabarcoding approach focusing on two bioindicators, diatoms, and aquatic oligochaetes, which are used in freshwater biomonitoring in France and Switzerland. To go towards the renewal of current biomonitoring practices, SYNAQUA will (1) bring together different actors: scientists, environmental managers, consulting firms, and biotechnological companies, (2) apply this approach on a large scale to demonstrate its relevance, (3) propose robust and reliable tools, and (4) raise public awareness and train the various actors likely to use these new tools. Biomonitoring approaches based on such environmental genomic tools should address the European need for reliable, higher-throughput monitoring to improve the protection of aquatic environments under multiple pressures, guide their restoration, and follow their evolution.