Evidence map›Paper›PMID 39967323›Full record

ArticleEcology letters2025

Paleorecords Reveal Biological Mechanisms Crucial for Reliable Species Range Shift Projections Amid Rapid Climate Change.

Victor Van der Meersch, Edward Armstrong, Florent Mouillot, Anne Duputié, Hendrik Davi, Frédérik Saltré, Isabelle Chuine

Abstract read
In one paragraph

Article in Ecology letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

7 authors.

Victor Van der MeerschCEFE, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France.ORCID https://orcid.org/0000-0001-7746-4098
Edward ArmstrongDepartment of Geosciences and Geography, University of Helsinki, Helsinki, Finland.
Florent MouillotCEFE, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France.
Anne DuputiéUMR 8198-EEP-Evo-Eco-Paleo, Université de Lille, CNRS, Lille, France.
Hendrik DaviURFM, INRAE, Avignon, France.
Frédérik SaltréBiogeography Ecology and Modelling, School of Life Sciences, University Technology Sydney, Sydney, New South Wales, Australia.
Isabelle ChuineCEFE, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France.

Funding

Australian Research Council Centre of Excellence for Indigenous and Environmental Histories and Futures CE230100009European Union's Horizon 2020 101003890Université de Montpellier
6 · The paper itself

Abstract

The recent acceleration of global climate warming has created an urgent need for reliable projections of species distributions, widely used by natural resource managers. Such projections have been mainly produced by species distribution models with little information on their performances in novel climates. Here, we hindcast the range shifts of forest tree species across Europe over the last 12,000 years to compare the reliability of three different types of models. We show that in the most climatically dissimilar conditions, process-explicit models (PEMs) tend to outperform correlative species distribution models (CSDMs), and that PEM projections are likely to be more reliable than those made with CSDMs by the end of the 21st century. These results demonstrate for the first time the often promoted albeit so far untested idea that explicit description of mechanisms confers model robustness, and highlight a new avenue to increase model projection reliability in the future.

Indexed as

Climate ChangeModels, BiologicalTreesEuropeForestsclimate changeecological modellinghindcastingmodel transferabilityspecies range shift

Identifiers

PMID39967323
PMCPMC11836547

What OpenQuestion holds

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LicenceCC BY
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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.