說明
資料紀錄
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版本
以下的表格只顯示可公開存取資源的已發布版本。
如何引用
研究者應依照以下指示引用此資源。:
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
權利
研究者應尊重以下權利聲明。:
此資料的發布者及權利單位為 Museo di Zoologia (MZUR) - Sapienza University of Rome。 This work is licensed under a Creative Commons Attribution Non Commercial (CC-BY-NC 4.0) License.
GBIF 註冊
此資源已向GBIF註冊，並指定以下之GBIF UUID: e0370da7-b32b-414c-8a61-1d86125075f3。 Museo di Zoologia (MZUR) - Sapienza University of Rome 發佈此資源，並經由Participant Node Managers Committee同意向GBIF註冊成為資料發佈者。
關鍵字
Occurrence; Marine; Mollusca; Italy
聯絡資訊
- 元數據提供者 ●
- 出處 ●
- 連絡人
- PhD Student
https://orcid.org/0000-0003-0147-2563
- 典藏經理
地理涵蓋範圍
Collected data occurred within the Italian Exclusive Economic Zone in the Mediterranean Sea.
| 界定座標範圍 | 緯度南界 經度西界 [35.35, 7.605], 緯度北界 經度東界 [45.784, 18.795] |
|---|
分類群涵蓋範圍
The dataset includes 44096 occurrences of 1513 Italian marine mollusc species.
| Class | Bivalvia, Monoplacophora, Gastropoda, Scaphopoda, Polyplacophora, Cephalopoda |
|---|---|
| Order | 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 |
計畫資料
無相關描述
| 計畫名稱 | THE NATIONAL CHECKLIST OF ITALIAN FAUNA - DEVELOPMENT OF A MODERN DATABASE |
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參與計畫的人員:
取樣方法
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.
| 研究範圍 | 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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方法步驟描述:
- 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.