A georeferenced dataset of Italian occurrence records of the phylum Rotifera

Abstract

We report a dataset of known and published occurrence records of Italian taxa from species (and subspecies) to family rank of the phylum Rotifera; we considered only Bdelloidea, Monogononta, and Seisonacea, and did not include Acanthocephala. The dataset includes 15,525 records (12,015 of which with georeferenced coordinates) of 584 valid species and subspecies names, gathered from 332 published papers. The published literature spans the period from 1838 to 2022, with the lowest number of papers published during the Second World War followed by an increasing number of papers, from 20 to more than 60 in each decade. The Italian regions with the highest number of records and species are Emilia-Romagna, Lombardy, and Piedmont, whereas no records are known for Molise. The number of species known from each region mostly mirrors sampling efforts, measured as the number of publications per region. The dataset is available through the Open Science Framework (OSF), and all the georeferenced occurrence data have been uploaded to the Global Biodiversity Information Facility (GBIF).

Preface: Georeferenced Freshwater Biodiversity Data

“…2). In detail, Musazzi et al (2023) report 4,124 records of sedimentary diatoms in Lake Maggiore, a wide (2023) in comparison to 765 that were reported in the most recent review on African rotifers (Smolak et al, 2023); 584 species are reported for Italy by Ferrari et al (2023) in comparison to 483 reported in the most recent review on Italian rotifers (Fontaneto et al, 2022).…”

A century of research on micro-organisms from the inland waters of the largest Mediterranean island

“…An extensive review of rotifers occurring in Sicilian inland and marine waters, including geo-referenced occurrence localities, is reported in Ferrari et al (2023).…”

A georeferenced dataset for occurrence records of the phylum Rotifera in Africa

“…But few of those studies report datasets of georeferenced records to be used for biogeographical inference: e.g. for Antarctica ( (Smolak et al, 2023), and Italy (Ferrari et al, 2023). The aim of our study is to produce a georeferenced dataset of rotifers on Africa and many of its surrounding islands.…”