Tree carbon-use efficiency (CUE = NPP / GPP ; Manzoni et al., 2018) is defined as the ratio of net (NPP = GPP – Ra) to gross primary production (GPP) and is thus strongly determined by plant respiration (Ra). It is unknown how Ra and thus also CUE will respond to further increasing temperatures. Within the iCUE-Forest project I aim to identify the drivers of Ra and CUE and investigate how changes in those drivers will affect Ra and CUE in boreal and temperate forests. I concentrate on tree tissue nitrogen (N) concentrations and the controls of their spatial variation, since plant maintenance respiration is strongly related to N contents in different tree tissues (leaves, branches, stems, roots).
Wood production depends on how effectively plants convert atmospheric carbon dioxide (CO2) into wood. Moreover, forests mitigate climate change through their net carbon uptake from the atmosphere. Both these forest functions are crucially dependent on tree CUE. It is thus necessary to identify the response of CUE to environmental change and to increase CUE to enhance wood production and carbon stocks under future climatic conditions. In light of the typical rotation lengths, forest managers need to be informed already today on which species will be optimally adapted in certain regions to a changing climate.
The overall objectives of the iCUE-Forest project are to:
1. Compile an unprecedented database of N concentration measurements in tree tissues (leaves, branches, stems, roots; Thurner et al., prepared for submission)
2. Identify the controls of the variation in tree tissue N concentrations (Thurner et al., prepared for submission)
3. Develop novel data-driven estimates of tree tissue N concentrations and contents (Thurner et al., in prep.) based on the identified relationships and on recent satellite-driven maps of tree living biomass (Thurner et al., 2014; Thurner et al., 2019)
These key developments are the basis for follow-up objectives which are to:
4. Infer spatial estimates of Ra, NPP and tree CUE from the estimates of tree tissue N contents, respiratory costs per N content and temperature datasets
5. Investigate the spatial patterns in CUE under current climate and tree species distribution
6. Apply a dynamic global vegetation model (DGVM) to predict temporal changes in CUE in response to climate change and tree species distribution scenarios
The central conclusions of the iCUE-Forest project are:
1. Tree tissue N concentrations are critical traits determining Ra and tree CUE
2. The controls of tree tissue N concentrations (especially in branches, stems and roots) are explored at global scale for the first time (Thurner et al., prepared for submission)
3. Changes in the distribution of tree age/size, tree species, and extreme climate, induced by climate change, forest management or disturbances, may have substantial consequences for the CUE of boreal and temperate forests by their effects on tree tissue N concentrations (Thurner et al., prepared for submission)
4. Current DGVMs do not adequately account for the identified controls of tree tissue N concentration (Thurner et al., prepared for submission) and are thereby limited in their ability to realistically predict future changes in Ra and CUE
