Periodic Reporting for period 1 - iCUE-Forest (Improving tree carbon use efficiency for climate-adapted more productive forests)
Berichtszeitraum: 2020-07-01 bis 2022-06-30
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
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
Work performed during the iCUE-Forest project includes:
1. Compilation of a database on N concentration in tree tissues of boreal and temperate tree species
2. Testing of a set of hypothesis on the controls of tree tissue N concentration and allocation
3. Derivation of the relationships between tissue N concentration and underlying abiotic and biotic drivers at tree-level
4. Estimating the spatial distribution of N concentration and content in tree tissues of northern boreal and temperate forests
I demonstrate how tree tissue N concentrations of boreal and temperate trees are related to tree age/size, growth rate and unfavorable climate conditions (Thurner et al., prepared for submission):
1. Tissue N concentration decreases with tree age/size.
2. Deciduous trees have higher tissue N concentrations than evergreen trees.
3. Trees which are slow-growing or growing under unfavorable climatic conditions (very cold temperatures, very dry climate) allocate a lower share of N to their leaves and a higher share of N to their stems compared to trees which are fast-growing or growing under favorable conditions.
4. Tissue N concentration does not consistently increase with soil N concentration.
These results are presented in a manuscript prepared for submission. Another manuscript is prepared on the spatial estimation of tree tissue N concentration and content in boreal and temperate forests. In addition, the N concentration database, which contains also information on fine roots, is contributing to a co-author manuscript focussing on the controls of fine root N concentration currently under review in Nature.
The results have also been presented at several scientific conferences, workshops, and institutions. Moreover, I participated in the Book a Scientist format in April 2022 and was outreaching there to two German politicians (members of the Bundestag and the Landtag) and a family with young children. I was also discussing my work in an online meeting with the CCO of a start-up company which offers solutions on compensating carbon emissions.
1. Compilation of a database on N concentration in tree tissues of boreal and temperate tree species
2. Testing of a set of hypothesis on the controls of tree tissue N concentration and allocation
3. Derivation of the relationships between tissue N concentration and underlying abiotic and biotic drivers at tree-level
4. Estimating the spatial distribution of N concentration and content in tree tissues of northern boreal and temperate forests
I demonstrate how tree tissue N concentrations of boreal and temperate trees are related to tree age/size, growth rate and unfavorable climate conditions (Thurner et al., prepared for submission):
1. Tissue N concentration decreases with tree age/size.
2. Deciduous trees have higher tissue N concentrations than evergreen trees.
3. Trees which are slow-growing or growing under unfavorable climatic conditions (very cold temperatures, very dry climate) allocate a lower share of N to their leaves and a higher share of N to their stems compared to trees which are fast-growing or growing under favorable conditions.
4. Tissue N concentration does not consistently increase with soil N concentration.
These results are presented in a manuscript prepared for submission. Another manuscript is prepared on the spatial estimation of tree tissue N concentration and content in boreal and temperate forests. In addition, the N concentration database, which contains also information on fine roots, is contributing to a co-author manuscript focussing on the controls of fine root N concentration currently under review in Nature.
The results have also been presented at several scientific conferences, workshops, and institutions. Moreover, I participated in the Book a Scientist format in April 2022 and was outreaching there to two German politicians (members of the Bundestag and the Landtag) and a family with young children. I was also discussing my work in an online meeting with the CCO of a start-up company which offers solutions on compensating carbon emissions.
I compiled an unprecedented database of N concentrations in tree stems, roots and branches covering all common boreal and temperate tree genera. This novel database allowed testing different hypotheses on the controls of tree tissue N concentration at global scale for the first time (Thurner et al., prepared for submission). Subsequently, I applied machine learning algorithms (generalized additive models) to derive the first spatial maps of stem, root and branch as well as total tree N concentration and content covering the entire northern hemisphere boreal and temperate forests (Thurner et al., in prep.). These estimates together with recent satellite-driven maps of tree living biomass (Thurner et al., 2014; Thurner et al., 2019) allow quantifying the N storage in boreal and temperate forest ecosystems and are the basis for novel spatial estimates of Ra, NPP and CUE.
The iCUE-Forest project informs forest managers on which species to grow under which environmental conditions in order to maximize N storage and CUE and thus wood production and bioenergy. The identification of the controls of tree tissue N concentration and CUE is highly beneficial for our ecological understanding, for studies on the impact of forest management on socio-ecological forest functions (Erb et al., 2018) and for informing future climate and forestry policies like the Sustainable Forest Management (SFM) strategy of the EU. Estimates of N concentration and content, Ra, NPP and CUE are highly relevant for upcoming assessment reports of the Intergovernmental Panel on Climate Change (IPCC), since spatial and reliable estimates of these carbon fluxes and properties are lacking so far. In this way, the results of iCUE-Forest may contribute to the communication of science to the policy and public and influence future climate policy.
Erb, K.-H. et al. Nature 553, 73-76 (2018).
Manzoni, S. et al. Biogeosciences 15, 5929-5949 (2018).
Thurner, M. et al. Glob. Ecol. Biogeogr. 23, 297-310 (2014).
Thurner, M. et al. Glob. Ecol. Biogeogr. 28, 640-660 (2019).
The iCUE-Forest project informs forest managers on which species to grow under which environmental conditions in order to maximize N storage and CUE and thus wood production and bioenergy. The identification of the controls of tree tissue N concentration and CUE is highly beneficial for our ecological understanding, for studies on the impact of forest management on socio-ecological forest functions (Erb et al., 2018) and for informing future climate and forestry policies like the Sustainable Forest Management (SFM) strategy of the EU. Estimates of N concentration and content, Ra, NPP and CUE are highly relevant for upcoming assessment reports of the Intergovernmental Panel on Climate Change (IPCC), since spatial and reliable estimates of these carbon fluxes and properties are lacking so far. In this way, the results of iCUE-Forest may contribute to the communication of science to the policy and public and influence future climate policy.
Erb, K.-H. et al. Nature 553, 73-76 (2018).
Manzoni, S. et al. Biogeosciences 15, 5929-5949 (2018).
Thurner, M. et al. Glob. Ecol. Biogeogr. 23, 297-310 (2014).
Thurner, M. et al. Glob. Ecol. Biogeogr. 28, 640-660 (2019).