The herpetological collections of the Instituto de Investigação Científica Tropical (Lisbon, Portugal) are the largest and most diverse collections of amphibians and reptiles in the country. These were collected in the mid-twentieth century in the former Portuguese colonies in Africa and Asia, and were the object of study of several naturalists that used them to describe and catalogue the herpetofauna of those areas. After the independence of these colonies in the mid 1970's, the research on this material nearly halted, and the collections became abandoned, without proper curation and lacking accessibility. In 2015, we started a process to recover these collections (Fig. 1). This encompassed basic curation, e.g. cleaning and substituting jars and fluid preservatives, cataloguing the entire collection, digitizing and georeferencing all the specimens, and making data available through the Global Biodiversity Information Facility at GBIF.org. While doing this, each specimen was also linked to its bibliographic data, its taxonomic identity carefully reviewed, and rare and important specimens (e.g., type specimens) flagged. Currently, the collection is completely accessible, both physically and electronically, and it is being used by researchers and students around the world. Some results have already been published including the description of species new to science (Ceríaco et al. 2016, Ceríaco et al. 2017, Ceríaco 2015, Soares et al. 2018), new country checklists, the publication of an Atlas of Angolan Herpetofauna (Marques et al. 2018), International Union for Conservation of Nature (IUCN) Red List assessments, and student training. This presentation provides an overview of the recovery process of the collection, discusses strategies on how to digitize and make historical collections available to the community, and demonstrates how biological collections amassed during colonial times can be of extreme importance to the study and preservation of present day biodiversity.
Benzer Makaleler | Yazar | # |
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Makale | Yazar | # |
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