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Physicochemical and biological variables measured in 110 national monitoring lakes between 1992 and 2022.

https://doi.org/10.5878/03t1-sv66

Physicochemical and biological data 110 national monitoring lakes for the years 1992 to 2022 were downloaded from the data host https://miljodata.slu.se/MVM/Opens in a new tab. Climate data were extracted from Climate Research Unit gridded Time Series dataset (version 4.06; Harris et al., 2020; https://crudata.uea.ac.uk/cru/data/hrg/Opens in a new tab) Eight data sets were compiled: 1. Physicochemical variables from surface water samples (10 variables): EU id Year Colour_absorbance_420nm Ca mg/l Conductivity_mS/m pH TOC mg/l C DIN_ µg/l_N TP_ µg/l_P Water_Temperature_°C. Lake physicochemical and climate data were log10(x + 1) transformed to approximate normal distribution prior to the analyses. 2. Climate data: annual mean air temperature (°C) and precipitation (mm per month for each lake in each year) extracted from the interpolated Climate Research Unit gridded Time Series dataset (version 4.06; Harris et al., 2020; https://crudata.uea.ac.uk/cru/data/hrg/Opens in a new tab) 3. Phytoplankton taxon abundances (biovolumes) for individual taxa collected in August (n = 780 taxa). Biovolumes were Hellinger transformed. 4. Phytoplankton metrics (n=5): number of taxa, taxon biovolumes, diversity (Hills N2), % cyanobacteria and between-year Euclidean distance*. 5. Littoral taxon abundances (numbers per unit effort) for samples collected in October/November (n=681 taxa). Abundances were Hellinger transformed. 6. Littoral metrics (n=4): number of taxa, total abundance, diversity (N2) and between-year Euclidean distance 7. Profundal taxa abundances (individual per m2) for samples collected in October/November (n=321 taxa). Abundances were Hellinger transformed. 8. Profundal metrics (n=4): number of taxa, total abundance, diversity (N2) and between-year Euclidean distance. * Between-year Euclidean distances were calculated using detrended correspondence analysis axes 1-3 as as d=√((x2 – x1)² + (y2 – y1)²) + (z2 – z1)²), where x1, y1, z1 represent DC axis scores one, two and three, respectively, at any year and x2, y2, z2 represent DC axis scores one, two and three, respectively, for the previous year.

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doris
Swedish University of Agricultural Sciences