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ACCELERATING THE DISCOVERY OF RARE TREE SPECIES IN AMAZONIAN FORESTS: INTEGRATING LONG MONITORING TREE PLOT DATA WITH METABOLOMICS AND PHYLOGENETICS FOR THE DESCRIPTION OF A NEW SPECIES IN THE HYPERDIVERSE GENUS INGA MILL: integrating long monitoring tree plot data with metabolomics and phylogenetics for the description of a new species in the hyperdiverse genus Inga Mill

  • Juan Ernesto Guevara Andino*
  • , Consuelo Hernández
  • , Renato Valencia
  • , Dale Forrister
  • , María José Endara*
  • *Autor correspondiente de este trabajo

Producción científica: RevistaArtículorevisión exhaustiva

Resumen

In species-rich regions and highly speciose genera, the need for species identification and taxonomic recognition has led to the development of emergent technologies. Here, we combine long-term plot data with untargated metabolomics, and morphological and phylogenetic data to describe a new rare species in the hyperdiverse genus of trees Inga Mill. Our combined data show that Inga coleyana is a new lineage splitting from their closest relatives I. coruscans and I. cylindrica. Moreover, analyses of the chemical defensive profile demonstrate that I. coleyana has a very distinctive chemistry from their closest relatives, with I. coleyana having a chemistry based on saponins and I. cylindrica and I. coruscans producing a series of dihydroflavonols in addition to saponins. Finally, data from our network of plots suggest that I. coleyana is a rare and probably endemic taxon in the hyper-diverse genus Inga. Thus, the synergy produced by different approaches, such as long-term plot data and metabolomics, could accelerate taxonomic recognition in challenging tropical biomes.

Idioma originalInglés
Número de artículoe13767
PublicaciónPeerJ
Volumen10
DOI
EstadoPublicada - 29 ago 2022

Nota bibliográfica

Publisher Copyright:
Copyright 2022 Guevara Andino et al.

Financiación

FinanciadoresNúmero del financiador
Artificial Intelligence for Species Discovery National GeographicNGS-72018T-20
Universidad de las Américas PueblaFGE.JGA.20.04

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