MethodsX (Jan 2020)
Development of a portable leaf photosynthesis and volatile organic compounds emission system
Abstract
Understanding how plant carbon metabolism responds to environmental variables such as light is central to understanding ecosystem carbon cycling and the production of food, biofuels, and biomaterials. Here, we couple a portable leaf photosynthesis system to an autosampler for volatile organic compounds (VOCs) to enable field observations of net photosynthesis simultaneously with emissions of VOCs as a function of light. Following sample collection, VOCs are analyzed using automated thermal desorption-gas chromatograph-mass spectrometry (TD-GC–MS). An example is presented from a banana plant in the central Amazon with a focus on the response of photosynthesis and the emissions of eight individual monoterpenes to light intensity. Our observations reveal that banana leaf emissions represent a 1.1 +/- 0.1% loss of photosynthesis by carbon. Monoterpene emissions from banana are dominated by trans-β-ocimene, which accounts for up to 57% of total monoterpene emissions at high light. We conclude that the developed system is ideal for the identification and quantification of VOC emissions from leaves in parallel with CO2 and water fluxes.The system therefore permits the analysis of biological and environmental sensitivities of carbon metabolism in leaves in remote field locations, resulting in the emission of hydrocarbons to the atmosphere. • A field-portable system is developed for the identification and quantification of VOCs from leaves in parallel with leaf physiological measurements including photosynthesis and transpiration. • The system will enable the characterization of carbon and energy allocation to the biosynthesis and emission of VOCs linked with photosynthesis (e.g. isoprene and monoterpenes) and their biological and environmental sensitivities (e.g. light, temperature, CO2). • Allow the development of more accurate mechanistic global VOC emission models linked with photosynthesis, improving our ability to predict how forests will respond to climate change. It is our hope that the presented system will contribute with critical data towards these goals across Earth's diverse tropical forests.
