Coastal wetlands face threats from climate change-induced flooding and biological invasions. Plants respond to these stressors through changes in their phytochemical metabolome, but it is unclear whether stressors affecting one tissue compartment (e.g., leaves) create vulnerabilities in others (e.g., roots) or elicit similar responses across tissues. Additionally, responses to multiple simultaneous stressors remain poorly understood due to the focus on individual metabolites in past studies. This study aims to elucidate how the phytochemical metabolome of three Phragmites australis (Cav.) lineages, common in the Mississippi River Delta, responds to flooding and infestation by the non-native scale insect Nipponaclerda biwakoensis (Kuwana). Among these lineages, one is non-native and poses a threat to North American wetlands. Results indicate that metabolomic responses are highly specific, varying with lineage, tissue type, stressor type, and the presence of multiple stressors. Notably, the non-native lineage displayed high chemical evenness, while the other two showed stressor-dependent responses. The 10 most informative features identified by a machine learning model showed less than 1% overlap with known metabolites linked to water and herbivory stress, underscoring gaps in our understanding of plant responses to environmental stressors. Our metabolomic approach offers a valuable tool for identifying candidate plant genotypes for wetland restoration.
Keywords: Roseau cane scale; climate change; intraspecific; machine learning; metabolomics; non-native species; phytochemical diversity; salt marsh.