Production of the dataset was conducted as part of the eLTER PLUS TA project 078. The project aimed to collect water samples from the three LTER sites for the analysis of microbiota and ichthyofauna diversity using DNA sequencing. The three LTER sites used are: Lehrforst Rosalia (LR) [AT], Lago Maggiore (LM) [IT], and Rhine-Main Observatory (RMO) [DE]. At randomly chosen points for LM and RMO and at all sampled points at LR, physico-chemical parameters were assessed to make a robust estimate of the link between biota and basic water quality indicators. For LM and RMO, where collection of samples was done from the same water body (Lake Maggiore and river Kinzig, respectively), coordinates for sampling were selected based on historical data from national fish and water quality monitoring programs, in such a manner as to maximize the heterogeneity between the samples and increase microbial and fish diversity. For LR, in the absence of historical data, nine distinct water bodies (ponds and rivers) were chosen for sampling: Grasliegengraben, Ofenbach, Leitha, Pitten, Schlattenbach, Schwarza, Feistritz, and two unidentified water bodies. Based on the imputed historical data (LR and RMO) and the results of on-site measurements of water quality, clustering silhouette scores obtained for LR, LM and RMO are: 0.334, 0.444 and 0.673, respectively, indicating moderate to good clustering (sample diversification). Comparison of water quality indicators suggested higher DO (median 10.38 mg/L) and EC (median 570 μS/cm), and lower water temperature (median 18.55 °C) at RMO, and higher pH (median 8.775) at LM. These differences between the research sites are expected to further contribute to heterogeneity of the biota in collected water samples.
A total of 75 samples were collected (15 at LR, 30 at LM and 30 at RMO). Water was collected in polypropylene bottles and filtered through 0.45 μm Polyethersulfone (PES) filters (0.8-1.5 L of water and 2-3 filters per sample, depending on water turbidity). Depending on the operating organization, samples were filtered using manual filtration, vacuum, or peristaltic pumps. Filters are preserved in Nucleic Acid Preservation (NAP) buffer and stored at -20°C and will be subjected to further analysis through DNA metabarcoding. In addition, seven blanks were collected to control for filtering equipment, airborne contamination and bottle cleaning. Physicochemical parameters were assessed using a multiprobe to measure dissolved oxygen (DO), pH, water temperature (°C), and electro-conductivity (EC) (reference temperature 25°C). Kruskal-Wallis with Dunn's post-hoc was used for comparing the water quality between research sites, while Mean Shift and Gower's distance clustering were used to estimate the heterogeneity of collected samples, based on imputed monitoring data (LM and RMO) or on-site measured values (LR). Python 3.12 was used to develop interactive maps and carry out computational analysis for selecting sampling locations, clustering and statistical analyses.
The project implementation and collections of samples was kindly supported by site managers and research staff: Eugenio Diaz-Pines, Carolina Boom and Johannes Marschick from the University of Natural Resources and Life Sciences, Vienna (BOKU), Michela Rogora, Ester Eckert, Andrea Lami and Pietro Volta from the Water Research Institute (CNR-IRSA), Beatrice Kulawig, Prof. Peter Haase and Marius Laurischkat from the Senckenberg Research Institute and Natural History Museum Frankfurt (SGN).
