Smell the change: On the potential of gas-chromatographic ion mobility spectrometry in ecosystem monitoring.

Abstract

Plant volatile organic compounds (pVOCs) are being recognized as an important factor in plant–environment interactions. Both the type and amount of the emissions appear to be heavily affected by climate change. A range of studies therefore has been directed toward understanding pVOC emissions, mostly under laboratory conditions (branch/leaf enclosure). However, there is a lack of rapid, sensitive, and selective analytical methods, and therefore, only little is known about VOC emissions under natural, outdoor conditions. An increased sensitivity and the identification of taxon‐specific patterns could turn VOC analysis into a powerful tool for the monitoring of atmospheric chemistry, ecosystems, and biodiversity, with far‐reaching relevance to the impact of climate change on pVOCs and vice versa. This study for the first time investigates the potential of ion mobility spectrometry coupled to gas‐chromatographic preseparation (GC‐IMS) to dramatically increase sensitivity and selectivity for continuous monitoring of pVOCs and to discriminate contributing plant taxa and their phenology. Leaf volatiles were analyzed for nine different common herbaceous plants from Germany. Each plant turned out to have a characteristic metabolite pattern. pVOC patterns in the field would thus reflect the composition of the vegetation, but also phenology (with herbaceous and deciduous plants contributing according to season). The technique investigated here simultaneously enables the identification and quantification of substances characteristic for environmental pollution such as industrial and traffic emissions or pesticides. GC‐IMS thus has an enormous potential to provide a broad range of data on ecosystem function. This approach with near‐continues measurements in the real plant communities could provide crucial insights on pVOC‐level emissions and their relation to climate and phenology and thus provide a sound basis for modeling climate change scenarios including pVOC emissions.