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Digging for historical data on the occurrence of benthic macrofaunal species in the southeastern Mediterranean
Tsikopoulou, I.; Legaki, A.; Dimitriou, P.D.; Avramidou, E.; Bailly, N.; Nikolopoulou, S. (2016). Digging for historical data on the occurrence of benthic macrofaunal species in the southeastern Mediterranean. Biodiversity Data Journal 4: e10071. https://dx.doi.org/10.3897/bdj.4.e10071
In: Biodiversity Data Journal. Pensoft Publishers: Sofia. ISSN 1314-2836; e-ISSN 1314-2828
Peer reviewed article  

Available in  Authors 
    Vlaams Instituut voor de Zee: Open access 296922 [ download pdf ]

Keyword
    Marine/Coastal
Author keywords
    Marine biodiversity; macrofauna; Egypt expedition; eastern Mediterranean; historical dataset; data digitization; data rescue

Authors  Top 
  • Tsikopoulou, I.
  • Legaki, A.
  • Dimitriou, P.D.
  • Avramidou, E.
  • Bailly, N.
  • Nikolopoulou, S.

Abstract
    Background: The benthic macrofaunal biodiversity of the southeastern Mediterranean is considerably understudied compared to other Mediterranean regions. Monitoring biodiversity in this area is crucial as this region is particularly susceptible to biological invasions and temperature alteration. Historical biodiversity data could provide a useful baseline for monitoring potential changes and provide informarion to support a better understanding of the possible effects of anthropogenic activities on marine benthic communities.New information: In this study, performed under the LifeWatchGreece Research Infrastructure, we present historical benthic occurrence data obtained from the sampling expedition carried out in 1933 by Adolf Steuer in the coastal area around Alexandria, Egypt, eastern Mediterranean. The occurrences were geo-referenced to more than 170 stations, mostly located in the area of Alexandria, and the nearby coasts and lakes. All records were digitized and species names were cross-checked and taxonomically updated using the World Register of Marine Species. The outcome clearly shows that such initiatives can reveal an unexpected amount of highly valuable biodiversity information for “data-poor” regions.

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