Mobilising marine biodiversity data: a new malacological dataset of Italian records (Mollusca)

Записи данных

Данные этого occurrence ресурса были опубликованы в виде Darwin Core Archive (DwC-A), который является стандартным форматом для обмена данными о биоразнообразии в виде набора из одной или нескольких таблиц. Основная таблица данных содержит 44 096 записей.

Данный экземпляр IPT архивирует данные и таким образом служит хранилищем данных. Данные и метаданные ресурсов доступны для скачивания в разделе Загрузки. В таблице версий перечислены другие версии ресурса, которые были доступны публично, что позволяет отслеживать изменения, внесенные в ресурс с течением времени.

Версии

В таблице ниже указаны только опубликованные версии ресурса, которые доступны для свободного скачивания.

Как оформить ссылку

Исследователи должны дать ссылку на эту работу следующим образом:

Giannini A (2024). Mobilising marine biodiversity data: a new malacological dataset of Italian records (Mollusca). Version 1.0. Museo di Zoologia (MZUR) - Sapienza University of Rome. Occurrence dataset. https://cloud.gbif.org/eca/resource?r=mzur_sap_zoo_01&v=1.0

Права

Исследователи должны соблюдать следующие права:

Публикующей организацией и владельцем прав на данную работу является Museo di Zoologia (MZUR) - Sapienza University of Rome. Эта работа находится под лицензией Creative Commons Attribution Non Commercial (CC-BY-NC 4.0).

Регистрация в GBIF

Этот ресурс был зарегистрирован в GBIF, ему был присвоен следующий UUID: e0370da7-b32b-414c-8a61-1d86125075f3.  Museo di Zoologia (MZUR) - Sapienza University of Rome отвечает за публикацию этого ресурса, и зарегистрирован в GBIF как издатель данных при оподдержке Participant Node Managers Committee.

Ключевые слова

Occurrence; Marine; Mollusca; Italy

Контакты

Географический охват

Collected data occurred within the Italian Exclusive Economic Zone in the Mediterranean Sea.

Таксономический охват

The dataset includes 44096 occurrences of 1513 Italian marine mollusc species.

Данные проекта

Описание отсутсвует

Исполнители проекта:

Методы сбора

Data were gathered from two main sources: literature and Natural History Collections (NHCs). To collect literature data, a comprehensive search was performed on the public databases Scopus and Web of Science. In addition to this, we also searched data from journals specialised on mediterranean marine fauna, namely Iberus and all the volumes of both journals of the Italian Society of Malacology (Società Italiana di Malacologia, SIM): Bollettino Malacologico and Alleryana. Since until the publication of the Checklist of the Italian Fauna no unified standard existed for Italian molluscan taxonomy and nomenclature - and verifying the accuracy of identifications reported in literature would have been difficult without direct check of the actual specimens - the literature search was restricted to publications issued after the first edition of the Checklist of the Italian Fauna. Species distribution information published in various formats (e.g. data tables in supplementary materials or within the paper, species lists, statements reporting the species occurrence) were considered as potential raw data. Paper with data already published in public databases were excluded. In order to avoid collecting the same record several times, only papers with new data were considered (i.e. new data derived from a dedicated sampling or non-new data published for the first time). Data from NHCs were collected by direct request to private collectors and institutions. From both sources, records were included in the dataset if at least the occurrence locality and a taxonomic identification at the genus level (or more specific) were stated.

Описание этапа методики:

1. 1. Firstly, data were merged and formatted in a Darwin Core scheme, using Biodiversity Data Cleaning toolkit package in R. 2. With the same package, a first filter was performed to clean the dataset from duplicates and records lacking essential information (i.e. identification or locality/coordinates). Then, data were manually filtered to retrieve records that were: out of scope (i.e. occurrences outside Italian Marine Exclusive Economic Zone, fossils, non-marine species), too vague (i.e. broad locality, specimens with a higher level of identification than the genus), or dubious (dubious locality, ambiguous and/or unclear identification). 3. Taxonomy was aligned to the one proposed by the World Register of Marine Species (WoRMS Editorial Board 2024) using the taxon-match Life Watch webservice, also extracting the WoRMS Life Science Identifiers for each valid scientific name to trace as far as possible rehashes of taxonomy, which in marine molluscs are quite common, especially through molecular evidence. 4. The remaining dubious taxonomy that was not automatically validated was checked manually and then submitted to experts, which resulted in the removal of other records with dubious identification. 5. Open Nomenclature qualifiers were used to set uncertainty and provisional statuses for taxonomic identifications. 6. Subsequently, records were classified in 7 different groups based on the type of the geographic information they had, in order to georeference them by the most appropriate method. Georeferencing was performed following the point-radius method, using GEOLocate web-based collaborative client and QGIS. Each final processed record has associated coordinates expressed in WGS84 decimal degrees and an uncertainty measure in metres. GEBCO_2022 global terrain model was used to georeference depth data correctly. 7. During the georeferencing process it was possible to remove other data occurred outside study boundaries. We then excluded records with >5000 m of uncertainty radius. 8. As raw temporal data from NHCs arrived in various formats, this information was handled with the R package lubridate and converted to ISO 8601 format. The temporal information collected spans various degrees of resolution, from the exact date to time ranges between years. We decided to mantain also records without temporal information. No hourly data were collected.

Дополнительные метаданные