Evidence map›Paper›PMID 36229452›Full record

ArticleNature communications2022

The deglacial forest conundrum.

Anne Dallmeyer, Thomas Kleinen, Martin Claussen, Nils Weitzel, Xianyong Cao, Ulrike Herzschuh

Abstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
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  6. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Anne DallmeyerMax Planck Institute for Meteorology, Bundesstrasse 53, 20146, Hamburg, Germany. anne.dallmeyer@mpimet.mpg.de.ORCID 0000-0002-3270-610X
Thomas KleinenMax Planck Institute for Meteorology, Bundesstrasse 53, 20146, Hamburg, Germany.ORCID 0000-0001-9550-5164
Martin ClaussenMax Planck Institute for Meteorology, Bundesstrasse 53, 20146, Hamburg, Germany.ORCID 0000-0001-6225-5488
Nils WeitzelInstitute of Environmental Physics, Heidelberg University, Im Neuenheimer Feld 229, 69120, Heidelberg, Germany.ORCID 0000-0002-2735-2992
Xianyong CaoAlpine Paleoecology and Human Adaptation Group (ALPHA), State Key Laboratory of Tibetan Plateau Earth System, and Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China.
Ulrike HerzschuhAlfred Wegner Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany.ORCID 0000-0003-0999-1261

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Climate ChangeForestsComputer SimulationEcosystemPollenTrees

Identifiers

PMID36229452
PMCPMC9562359

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.