Two Colors, One Species: The Case of Melissodes nigroaenea (Apidae: Eucerini), an Important Pollinator of Cotton Fields in Brazil

Autor: Carolina Grando, Nolan David Amon, Steven J Clough, Na Guo, Wei Wei, Patricia Azevedo, Margarita Maria López-Uribe, Maria Imaculada Zucchi
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: Sociobiology, Vol 65, Iss 4 (2018)
Druh dokumentu: article
ISSN: 0361-6525
2447-8067
DOI: 10.13102/sociobiology.v65i4.3464
Popis: Accurate taxonomic delimitation in ecological research is absolutely critical as studies that seek to evaluate levels of biodiversity and qualify human effects on the environment are rapidly undertaken. Coloration is a widely used morphological character for species identification through dichotomous keys. However, taxonomic identification based upon coloration is often unreliable because this character can exhibit high degree of intraspecific variation. In this study, we use a DNA barcoding approach to investigate the interpretation of two color morphs (yellow or dark) in the eucerine bee Melissodes nigroaenea. Our hypothesis is that if significant genetic divergence exists between each morphotype of M. nigroaenea, coloration reflects two distinct evolutionary lineages within this species, which may require taxonomic revision. Our alternative hypothesis is that, if genetic divergence is low between each morphotype of M. nigroaenea, we can attribute this variation to color polymorphism. Our Bayesian phylogenetic reconstruction revealed that both yellow and black individuals clustered together in a highly supported phylogenetic group. Additionally, pairwise genetic distances between M. nigroaenea color morphotypes were lower than 3%. These results indicate that both mesosome color morphs correspond to intraspecific variability within the same evolutionary unit. Together, our results indicate that mesosome coloration is not a reliable character for taxonomic differentiation of these Melissodes species, and that the incorporation of DNA barcoding approaches to taxonomic classification can help resolve some of the problems that originate while relying on purely morphological taxonomy.
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