Forest management in the Earth system
Forstwissenschaften
Zusammenfassung der Projektergebnisse
The Emmy Noether Group aims at a better understanding of the impact of global land use change and land management on climate and the carbon cycle. A key focus lies on forest management. While the effects of climate on forest productivity is well established in forestry models, the effects of forest management on climate are less understood. Closing this feedback cycle is crucial to understand the driving forces behind past climate changes to be able to predict future climate responses and thus the required effort to adapt to it or avert it. The key tool for this aim is a global Earth system model (ESM). Such models typically represent land use as a change in land cover (e.g., clearing forest for agriculture), but lack detail of land management (such as harvesting a forest). The Max Planck Institute's ESM has been substantially extended in this respect: The new forest management module contains a scheme of forest regrowth based on observed allometric relationships combined with age/size cohorts in a new version of the Max Planck Institute's ESM. This reduced former model biases and allows us to assess the interactions between managed forests and climate. The group has also contributed more generally to the process understanding of the effects of land use change and land management. In particular, we have contributed to reducing the large uncertainties related to carbon fluxes induced by land use change and to a better understanding of their controls. We have provided a framework to separate local and nonlocal effects of deforestation, bridging the gap between observational and modeling evidence of biogeophysical effects. We evaluated different future land use options in terms of effects and side-effects on climate from local to global scale, linking adaptation to mitigation aspects. We helped bridging the communities of Earth system modeling, Earth observation and land system science to identify challenges and opportunities related to model structure, data availability and process understanding to represent the world's most prominent land management types in ESMs. Our estimates of land-use CO2 emissions have become an integral part of the Global Carbon Project's annual CO2 budgets and the IPCC Assessments. Regular media coverage of the group's work occurred on e.g. trade-offs of carbon potentials and side-effects of afforestation, general climate change, and concrete studies such as the Global Carbon Budget. The group performed outreach to the general public through articles in popular science magazines, podcasts and a museum catalogue.
Projektbezogene Publikationen (Auswahl)
- (2019). Global carbon budget 2019. Earth System Science Data, 11, 1783-1838
Friedlingstein, P., Jones, M., O'Sullivan, M., Andrew, R., Hauck, J., Peters, G., Peters, W., Pongratz, J., Sitch, S., Le Quéré, C., Bakker, D., Canadell, J., Ciais, P., Jackson, R., Anthoni, P., Barbero, L., Bastos, A., Bastrikov, V., Becker, M., Bopp, L., Buitenhuis, E., Chandra, N., Chevallier, F., Chini, L., Currie, K., Feely, R., Gehlen, M., Gilfillan, D., Gkritzalis, T., Goll, D., Gruber, N., Gutekunst, S., Harris, I., Haverd, V., Houghton, R., Hurtt, G., Ilyina, T., Jain, A., Joetzjer, E., Kaplan, J., Kato, E., Klein Goldewijk, K., Korsbakken, J., Landschützer, P., Lauvset, S., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Marland, G., McGuire, P., Melton, J., Metzl, N., Munro, D., Nabel, J., Nakaoka, S.-I., Neill, C., Omar, A., Ono, T., Peregon, A., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Séférian, R., Schwinger, J., Smith, N., Tans, P., Tian, H., Tilbrook, B., Tubiello, F., van der Werf, G., Wiltshire, A. & Zaehle, S.
(Siehe online unter https://doi.org/10.5194/essd-2019-183) - (2014). Terminology as a key uncertainty in net land use and land cover change carbon flux estimates. Earth System Dynamics, 5, 177-195
Pongratz, J., Reick, C., Houghton, R. & House, J.
(Siehe online unter https://doi.org/10.5194/esd-5-177-2014) - (2015). Relevance of methodological choices for accounting of land use change carbon fluxes. Global Biogeochemical Cycles, 29, 1230-1246
Hansis, E., Davis, S. & Pongratz, J.
(Siehe online unter https://doi.org/10.1002/2014GB004997) - (2016). Reforestation in a high- CO2 world - Higher mitigation potential than expected, lower adaptation potential than hoped for. Geophysical Research Letters, 43, 6546-6553
Sonntag, S., Pongratz, J., Reick, C. & Schmidt, H.
(Siehe online unter https://doi.org/10.1002/2016GL068824) - (2016). Soil carbon response to land-use change: Evaluation of a global vegetation model using meta-data. Biogeosciences, 13, 5661-5675
Nyawira, S.-S., Nabel, J., Don, A., Brovkin, V. & Pongratz, J.
(Siehe online unter https://doi.org/10.5194/bg-2016-161) - (2018). Models meet data: challenges and opportunities in implementing land management in Earth System Models. Global Change Biology, 24, 1470-1487
Pongratz, J., Dolman, H., Don, A., Erb, K.-H., Fuchs, R., Herold, M., Jones, C., Luyssaert, S., Kuemmerle, T., Meyfroidt, P. & Naudts, K.
(Siehe online unter https://doi.org/10.1111/gcb.13988) - (2018). Unexpectedly large impact of forest management and grazing on global vegetation biomass. Nature, 553, 73-76
Erb, K.-H., Kastner, T., Plutzar , C., Bais, A., Carvalhais, N., Fetzel, T., Gingrich, S., Haberl, H., Lauk, C., Niedertscheider, M., Pongratz, J., Thurner, M. & Luyssaert, S.
(Siehe online unter https://doi.org/10.1038/nat»re25138) - (2019). Nonlocal effects dominate the global mean surface temperature response to the biogeophysical effects of deforestation. Geophysical Research Letters, 46, 745-755
Winckler, J., Lejeune, Q., Reick, C. & Pongratz, J.
(Siehe online unter https://doi.org/10.1029/2018GL080211) - (2019). Simulating growth-based harvest adaptive to future climate change. Biogeosciences, 16, 241-254
Yousefpour, R., Nabel, J. & Pongratz, J.
(Siehe online unter https://doi.org/10.5194/bg-16-241-2019) - (2020). Accounting for forest age in the tile-based dynamic global vegetation model JSBACH4 (4.20p7; git feature/forests) - a land surface model for the ICON-ESM. Geoscientific Model Development, 13, 185-200
Nabel, J., Naudts, K. & Pongratz, J.
(Siehe online unter https://doi.org/10.5194/gmd-13-185-2020)
