The uptake of CO2 by leaves and its conversion to sugar, called photosynthesis, is the basis of life on land. We know much about the process; however scientists grapple with the challenge of finding a robust, globally applicable model for predicting photosynthetic CO2 uptake in the face of environmental change.
New research using TERN delivered data has just been published in Nature Plants that fills this information gap and proposes a universal CO2 uptake predictive model that combines light-use efficiency and photosynthesis theory.
The new model is applicable across global biomes and plant functional types, providing a potential basis for the reformulation of current Earth System Models used to predict the future of the terrestrial sink for anthropogenic CO2.
The international team of researchers has used a worldwide data set of more than 3,500 leaf stable carbon isotope measurements to develop a more accurate method that correctly predicts measured photosynthetic uptake (known as gross primary productivity or GPP) at global Fluxnet sites, including at TERN sites.
“TERN observations, as part of the global Fluxnet dataset, provided a world-class set of measures to develop, test and enhance our new carbon flow model,” says lead researcher, Dr Han Wang of China’s Northwest A&F University and Australia's Macquarie University.
“TERN’s modelling capability, together with the United States Department of Agriculture, also played a significant role in the development of the methods we used to partition the flux data for deriving GPP observations,” adds Han.
TERN is proud to be providing the data and research infrastructure that the international modelling community is demanding.
TERN’s field observatory together with our ecosystem data services and modelling capability were utilised in this global research collaboration. The former collecting the data required to understand ecosystem processes and changes, and the latter processing the data, enabling them to be easily consumed by the international research team.
Earth Systems Models have already played a vital role in greatly improving our ability to understand and predict how plants and ecosystems respond to changes in their environment. TERN recognises this and we are excited to be contributing to further advancements that lead to improved modelling of climate change and its impacts on the natural world.
TERN data, as part of the global Fluxnet dataset, captured by TERN nation-wide network of ecosystem observatories, such as TERN's Great Western Woodlands SuperSite in Western Australia (above), provided a world-class set of measures to develop, test and enhance the new plant CO2 updake model (image courtesy Suzanne Long)
Published in TERN newsletter September 2017