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Museu de Ciències Naturals de Barcelona: MCNB-Malac

Authors: Eulàlia Garcia;

Museu de Ciències Naturals de Barcelona: MCNB-Malac

Abstract

[Spanish] El año 1882 Francesc Martorell donó su colección malacológica al ayuntamiento de Barcelona. Esta fecha enmarca la fundación del propio museo. Desde entonces la colección ha crecido gracias a la contribución de malacólogos como Artur Bofill, Joan B. d'Aguilar-Amat, Lluis Gasull, Baltasar Serradell, Manuel Chía, Joan Rosals, Miquel Bech. La gran mayoría de registros anteriores al siglo XXI son muestras conquiológicas, en seco, mientras que a finales del siglo XX hasta la actualidad predominan muestras de ejemplares enteros conservados en alcohol. [English] F. Martorell donated his malacological collection in 1882. This date can be considered as the beginning of the formation of the Museum. Since this date, the malacological collection has been increased with the contribution of the malacologists: A. Bofill, J.B. Aguilar-Amat, L. Gasull, B. Serradell, M. Chía, J. Rosals. An aspect peculiar of the collection is represented by samples collected in subterranean environments.

Keywords

Occurrence, Levante, Baleares, Cataluña, Mediterráneo

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Powered by OpenAIRE graph
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average