Descripción
Registros
Los datos en este recurso de registros biológicos han sido publicados como Archivo Darwin Core(DwC-A), el cual es un formato estándar para compartir datos de biodiversidad como un conjunto de una o más tablas de datos. La tabla de datos del core contiene 44.096 registros.
Este IPT archiva los datos y, por lo tanto, sirve como repositorio de datos. Los datos y los metadatos del recurso están disponibles para su descarga en la sección descargas. La tabla versiones enumera otras versiones del recurso que se han puesto a disposición del público y permite seguir los cambios realizados en el recurso a lo largo del tiempo.
Versiones
La siguiente tabla muestra sólo las versiones publicadas del recurso que son de acceso público.
¿Cómo referenciar?
Los usuarios deben citar este trabajo de la siguiente manera:
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
Derechos
Los usuarios deben respetar los siguientes derechos de uso:
El publicador y propietario de los derechos de este trabajo es Museo di Zoologia (MZUR) - Sapienza University of Rome. Esta obra está bajo una licencia Creative Commons de Atribución/Reconocimiento-NoComercial (CC-BY-NC 4.0).
Registro GBIF
Este recurso ha sido registrado en GBIF con el siguiente UUID: e0370da7-b32b-414c-8a61-1d86125075f3. Museo di Zoologia (MZUR) - Sapienza University of Rome publica este recurso y está registrado en GBIF como un publicador de datos avalado por Participant Node Managers Committee.
Palabras clave
Occurrence; Marine; Mollusca; Italy
Contactos
- Proveedor De Los Metadatos ●
- Originador ●
- Punto De Contacto
- PhD Student
- Curador
Cobertura geográfica
Collected data occurred within the Italian Exclusive Economic Zone in the Mediterranean Sea.
Coordenadas límite | Latitud Mínima Longitud Mínima [35,35, 7,605], Latitud Máxima Longitud Máxima [45,784, 18,795] |
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Cobertura taxonómica
The dataset includes 44096 occurrences of 1513 Italian marine mollusc species.
Class | Bivalvia, Monoplacophora, Gastropoda, Scaphopoda, Polyplacophora, Cephalopoda |
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Orden | Nudibranchia, Cardiida, Ellobiida, Pectinida, Gadilida, Neopilinida, Chitonida, Carditida, Aplysiida, Lepidopleurida, Sepiida, Dentaliida, Oegopsida, Callochitonida, Myida, Solemyida, Lepetellida, Systellommatophora, Cocculinida, Caenogastropoda incertae sedis, Arcida, Mytilida, Trochida, Nuculanida, Siphonariida, Myopsida, Ostreida, Neogastropoda, Cycloneritida, Umbraculida, Limida, Cephalaspidea, Galeommatida, Venerida, Littorinimorpha, Pleurobranchida, Seguenziida, Runcinida, Adapedonta, Pteropoda, Gastrochaenida, Nuculida, Lucinida, Octopoda |
Datos del proyecto
No hay descripción disponible
Título | THE NATIONAL CHECKLIST OF ITALIAN FAUNA - DEVELOPMENT OF A MODERN DATABASE |
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Personas asociadas al proyecto:
Métodos de muestreo
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.
Área de Estudio | The present work aims at collecting and making usable in the form of point-occurrences the distributional data of marine mollusc species reported in Italy, by integrating via harmonisation and georeferencing processes both primary (i.e. newly digitised specimen from public and private Natural History Collections) and secondary biodiversity data (i.e. non databased spatial information of species reported in publicly-accessible papers). |
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Descripción de la metodología paso a paso:
- 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.
Metadatos adicionales
Identificadores alternativos | https://cloud.gbif.org/eca/resource?r=mzur_sap_zoo_01 |
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