Abstract
Invasive plants drive ecosystem degradation through developing aggressive phenotypes that can outcompete native flora. Several hypotheses explain this, like the Evolution of Increased Competitive Ability hypothesis and the Novel Weapons Hypothesis, but none have been proven conclusively. Changes in plant metabolites are critical to these hypotheses, but complete invasive secondary metabolomes have not been quantified. Here, statistical and unsupervised machine-learning approaches were used to analyse chemotype-to-phenotype relationships in invasive and non-invasive populations in species Ageratum conyzoides, Lantana camara, Melaleuca quinquenervia and Psidium cattleainum and on a family level analysing Asteraceae, Myrtaceae and Verbenaceae. Invasive metabolomes evolved according to the EICA and NWH, involving optimisation of aggressive strategies present in native populations and local adaptation.
Competing Interest Statement
The authors have declared no competing interest.