A long-term (1986-2010) phytoplankton dataset from the LTER-Italy site Lake Candia

Study extent

Phytoplankton integrated samples in the whole euphotic zone were gathered approximately monthly, at the station of lake maximum depth (7.7 m). They were then analysed in the lab through the inverted microscope, estimating abundance and biovolume of each taxa from March 1986 to December 2010.

A total of 266 sampling events, from March 1986 to December 2010, with 10120 georeferenced occurrence records at the species level or higher rank have been uploaded to the GBIF repository

Sampling

Phytoplankton data were collected monthly from 1986 to 2010, at the point of lake maximum depth (7.7 m) as integrated samples of the euphotic water column.

Phytoplankton determinations were carried out on subsamples of the integrated sample preserved in acetic Lugol’s solution. Phytoplankton organisms were counted using the Utermöhl technique (Utermöhl, 1958), classifying the taxa to the species level, whenever possible, using a Zeiss Axiovert 10 inverted microscope at 200x and 400x until 400 cells for the most important taxa were counted. Biomass of each taxa in the sample was estimated from abundance data and original measurements of cell volume (Smayda, 1978; Hillebrand et al., 1999; Sun and Liu, 2003). Finally, total biovolume was calculated from the sum of the biovolumes of each taxon in the sample (cell number x specific cell volume).

All records are validated to the currently accepted nomenclature using the taxonomic backbone of GBIF, Algaebase: Listing of World’s Algae (Guiry and Guiry, 2022), and World Register of Marine Species WoRMS (Ahyong et al., 2022). Life Science Identifiers (LSIDs) are used to identify univocally the taxon and to facilitate data integration and interoperability.

Taxon specialists: Martina Austoni, Radiana Cozza, Giuseppe Morabito, Alessandro Oggioni, Pierisa Panzani, Alessandra Pugnetti, Teresa Ruffoni, Delio Ruggiu, Karin Sparber.

Quality control

Quality control for geographic data: Reliability of coordinates was checked with open source Geographic Information System (Quantum GIS – http://www.qgis.org/) to identify the correctness of sampling station position. Geographic coordinate format and the absence of anomalous ASCII characters in the dataset were also double checked.

Quality control for taxonomic data: Nomenclature validation and cleaning were based on the global algal database AlgaeBase (Guiry and Guiry, 2022), World Register of Marine Species WoRMS (Ahyong et al., 2022) and on the taxonomic backbone of GBIF. To check the taxonomic classification and to fill the information about taxa, taxon rank, occurrences status, and taxonomic status we used ReLTER R package (Oggioni, et al. 2022).