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Diversity of Ladybird Beetles (Coleoptera: Coccinellidae) in Tenerife and La Gomera (Canary Islands): The Role of Size and Other Island Characteristics.

Jerzy RomanowskiPiotr CeryngierJaroslav VětrovecChristian ZmudaKarol Szawaryn
Published in: Insects (2024)
This paper provides new data on the ladybird beetles (Coccinellidae) from two islands in the Canary archipelago: Tenerife, the largest island, and La Gomera, the second smallest. As they clearly differ in size but are similar in location and geological age, they are a suitable model for testing the species-area relationship. Our study shows that, in line with this main assumption of the theory of island biogeography, clearly more species occur on a large island (Tenerife) than on a small one (La Gomera). The field surveys documented the occurrence of 35 ladybird species on Tenerife (including 5 not previously reported from this island) and of 20 species on La Gomera (2 species new to the island). Coelopterus sp. collected on Tenerife (a single female that could not be identified to species) is the first record of this genus for the whole Canary Islands. Taking our data and previously published records into account, 47 species of Coccinellidae are known to occur on Tenerife and 26 species on La Gomera. Tenerife has by far the richest ladybird fauna of all the Canary Islands (the next in line, Gran Canaria, has 41 recorded species), but it also has the highest number of non-native ladybird species. All of the ten non-native species recorded in the Canary Islands are found on Tenerife, and for most of them, Tenerife was the island of their first appearance in the archipelago. This island, much more distant from the mainland than the other relatively large islands (Fuerteventura, Lanzarote), appears to be the main recipient of ladybirds immigrating to the Canary Islands. Tenerife can play this role probably because of its great habitat diversity and altitude variation, as well as intensive tourism and trade-related transport.
Keyphrases
  • genetic diversity
  • systematic review
  • climate change
  • cross sectional
  • lymph node
  • deep learning
  • artificial intelligence
  • big data