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)

引用 0|浏览13
暂无评分
摘要
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.
更多
查看译文
关键词
Rare, Diversity, Amazon, Tree species, Chemocoding, Integration, Plot network, Monitoring
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要