Quantitative morphometrics suggest that the widespread Neotropical Humiria balsamifera (Aubl.) St. Hil. is a species complex

• Autor(a) principal: Holanda,Ana Sofia Sousa de
• Data de Publicação: 2021
• Outros Autores: Vicentini,Alberto, Chave,Jerome, Carvalho,Fernanda Antunes, Zartman,Charles E.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Acta Botanica Brasilica
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-33062021000800339
• topic: Amazon; morphological species concept; phenotypic variation; quantitative taxonomy; species delimitation; white-sands forest

ABSTRACT Humiria balsamifera is an infraspecific complex of high phenotypic variation and widely distributed in northern South America. Leaf traits are traditionally considered the most relevant taxonomic characters for varietal level delimitation in the group. However, substantial phenotypic overlap among vegetative characters complicates taxonomic diagnoses in this complex. The objective of this study was to quantify and analyze phenotypic variation among individuals of the complex at a continental scale using uni- and multivariable analyses to assess whether morphometric analyses detect discontinuities. Secondarily, these quantitative data were used to test whether phenotypic similarity was related to geographic distance. Twenty- five quantitative and 27 qualitative character traits did not overtly reveal a topology corresponding to traditional varietal classification, nor to geographic structure. However, petiole length alone revealed a definitive separation of H. balsamifera var. guianensis (together with another recognized species Humiria wurdackii, and variety H. balsamifera var. laurina) from the rest of the taxa. Our results highlight substantial morphological overlap among vegetative and reproductive characters including those used in identification keys, and no morphological discontinuities suitable for clearly separating taxa within the complex were encountered demonstrating a future need to integrate multiple sources of information, including molecular data, to resolve this complex.