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

PeerJ. 2022 Aug 29:10:e13767. doi: 10.7717/peerj.13767. eCollection 2022.

Abstract

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.

Keywords: Amazon; Chemocoding; Diversity; Integration; Monitoring; Plot network; Rare; Tree species.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Ecosystem
  • Fabaceae*
  • Forests*
  • Metabolomics
  • Phylogeny

Grants and funding

This work was supported by the Universidad de las Américas research grant (FGE.JGA.20.04) and the Artificial Intelligence for Species Discovery National Geographic Grant (NGS-72018T-20). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.