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Journal Article

The deglacial forest conundrum

MPS-Authors
/persons/resource/persons37130

Dallmeyer,  Anne       
Climate Vegetation Dynamics, MPI for Meteorology, Max Planck Society;

/persons/resource/persons37205

Kleinen,  Thomas       
Climate-Biogeosphere Interaction, The Ocean in the Earth System, MPI for Meteorology, Max Planck Society;

/persons/resource/persons37123

Claussen,  Martin       
Climate Vegetation Dynamics, MPI for Meteorology, Max Planck Society;

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s41467-022-33646-6.pdf
(Publisher version), 2MB

Supplementary Material (public)

Dallmeyer_etal_2022_deglacial_forest_2.tgz
(Supplementary material), 3MB

video_biomes_model_recs.mp4
(Multimedia), 18MB

41467_2022_33646_MOESM1_ESM.pdf
(Supplementary material), 3MB

Citation

Dallmeyer, A., Kleinen, T., Claussen, M., Weitzel, N., Cao, X., & Herzschuh, U. (2022). The deglacial forest conundrum. Nature Communications, 13: 6035. doi:10.1038/s41467-022-33646-6.


Cite as: https://hdl.handle.net/21.11116/0000-000A-B8D5-6
Abstract
How fast the Northern Hemisphere (NH) forest biome tracks strongly warming climates is largely unknown. Regional studies reveal lags between decades and millennia. Here we report a conundrum: Deglacial forest expansion in the NH extra-tropics occurs approximately 4000 years earlier in a transient MPI-ESM1.2 simulation than shown by pollen-based biome reconstructions. Shortcomings in the model and the reconstructions could both contribute to this mismatch, leaving the underlying causes unresolved. The simulated vegetation responds within decades to simulated climate changes, which agree with pollen-independent reconstructions. Thus, we can exclude climate biases as main driver for differences. Instead, the mismatch points at a multi-millennial disequilibrium of the NH forest biome to the climate signal. Therefore, the evaluation of time-slice simulations in strongly changing climates with pollen records should be critically reassessed. Our results imply that NH forests may be responding much slower to ongoing climate changes than Earth System Models predict.