Evidence map›Paper›PMID 41128161›Full record

ArticleThe New phytologist2025

Demography, dynamics and data: building confidence for simulating changes in the world's forests.

Annemarie H Eckes-Shephard, Arthur P K Argles, Bogdan Brzeziecki, Peter M Cox, Martin G De Kauwe, Adriane Esquivel-Muelbert, Rosie A Fisher, George C Hurtt, Jürgen Knauer, Charles D Koven and 16 more

Abstract read
In one paragraph

Article in The New phytologist, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Tree growth after a major hurricane reflects predisturbance vigor rather than canopy damage.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
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

26 authors.

Annemarie H Eckes-ShephardDepartment of Physical Geography and Ecosystem Science, Lund University, Lund, 22362, Sweden.ORCID https://orcid.org/0000-0002-2453-3843
Arthur P K ArglesMet Office Hadley Centre, Exeter, Devon, EX1 PB, UK.ORCID https://orcid.org/0000-0002-1346-6518
Bogdan BrzezieckiDepartment of Silviculture, Institute of Forest Sciences, Warsaw University of Life Sciences, Warsaw, 02-776, Poland.ORCID https://orcid.org/0000-0001-5786-3075
Peter M CoxDepartment of Mathematics and Statistics, Faculty of Environment, Science and Economy, University of Exeter, Exeter, EX4 4QF, UK.ORCID https://orcid.org/0000-0002-0679-2219
Martin G De KauweSchool of Biological Sciences, University of Bristol, Bristol, BS8 1TQ, UK.ORCID https://orcid.org/0000-0002-3399-9098
Adriane Esquivel-MuelbertSchool of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK.ORCID https://orcid.org/0000-0001-5335-1259
Rosie A FisherCICERO Center for International Climate Research, Oslo, 0349, Norway.ORCID https://orcid.org/0000-0003-3260-9227
George C HurttDepartment of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA.ORCID https://orcid.org/0000-0001-7278-202X
Jürgen KnauerHawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, 2751, Australia.ORCID https://orcid.org/0000-0002-4947-7067
Charles D KovenClimate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.ORCID https://orcid.org/0000-0002-3367-0065
Aleksi LehtonenNatural Resources Institute Finland (Luke), Helsinki, FI-00790, Finland.ORCID https://orcid.org/0000-0003-1388-0388
Sebastiaan LuyssaertAmsterdam Institute for Life and Environment, Vrije Universiteit Amsterdam, Amsterdam, 1081, the Netherlands.ORCID https://orcid.org/0000-0003-1121-1869
Laura MarquésInstitute of Geography, University of Bern, Bern, 3012, Switzerland.ORCID https://orcid.org/0000-0002-3593-5557
Lei MaDepartment of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA.ORCID https://orcid.org/0000-0002-3959-4155
Guillaume MarieScience Partners, Paris, 75010, France.
Jonathan R MooreDepartment of Mathematics and Statistics, Faculty of Environment, Science and Economy, University of Exeter, Exeter, EX4 4QF, UK.ORCID https://orcid.org/0000-0002-7725-3343
Jessica F NeedhamCICERO Center for International Climate Research, Oslo, 0349, Norway.ORCID https://orcid.org/0000-0003-3653-3848
Stefan OlinDepartment of Physical Geography and Ecosystem Science, Lund University, Lund, 22362, Sweden.ORCID https://orcid.org/0000-0002-8621-3300
Mikko PeltoniemiNatural Resources Institute Finland (Luke), Helsinki, FI-00790, Finland.ORCID https://orcid.org/0000-0003-2028-6969
Karl PiltzDepartment of Physical Geography and Ecosystem Science, Lund University, Lund, 22362, Sweden.
Hisashi SatoResearch Institute for Global Change (RIGC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), 3173-25 Showamachi, Kanazawa-ku, Yokohama, 236-0001, Japan.ORCID https://orcid.org/0000-0002-6510-4914
Stephen SitchDepartment of Geography, Faculty of Environment, Science and Economy, University of Exeter, Exeter, EX4 4QF, UK.ORCID https://orcid.org/0000-0003-1821-8561
Benjamin D StockerInstitute of Geography, University of Bern, Bern, 3012, Switzerland.ORCID https://orcid.org/0000-0003-2697-9096
Ensheng WengCenter for Climate Systems Research, Columbia University and NASA Goddard Institute for Space Studies, New York, NY, 10025, USA.ORCID https://orcid.org/0000-0002-1858-4847
Daniel ZuletaForest Global Earth Observatory, Smithsonian Tropical Research Institute, Washington, DC, 20013-7012, USA.ORCID https://orcid.org/0000-0001-9832-6188
Thomas A M PughDepartment of Physical Geography and Ecosystem Science, Lund University, Lund, 22362, Sweden.ORCID https://orcid.org/0000-0002-6242-7371

Funding

AI4PEX 101137682CLIMB-Forest 101059888European Research Council project Tree2Globe 101141836European Union's Horizon 2020 101003536European Union's Horizon 2020 101003687European Union's Horizon Europe Research and Innovation Programme, project NextGenCarbon 101184989European Union's Horizon Europe Research and the Innovation Programme projects ForestPaths 101056755Forest Global Earth ObservatoryForestValue programmeFormas for the project FORECOGENCi-TGCC 2024-06328General Directorate of State Forests in Poland EO.271.3.1.2019Horizon 2020, HoliSoils SEP-210673589Horizon Europe INFORMA 101060309International Science Partnerships FundMet Office Climate Science for Service PartnershipNASA Carbon Monitoring System 80NSSC21K1059NASA Carbon Monitoring System 80NSSC25K7221NASA GEDI Competed Science Team 80NSSC24K0599NASA Modeling, Analysis and Prediction (MAP) Program 80NSSC21K1496National Science Foundation DEB-00753102National Science Foundation DEB-0129874National Science Foundation DEB-0346488National Science Foundation DEB-0425651National Science Foundation DEB-0640386National Science Foundation DEB-7922197National Science Foundation DEB-8206992National Science Foundation DEB-8605042National Science Foundation DEB8906869National Science Foundation DEB-9100058National Science Foundation DEB-9221033National Science Foundation DEB-9405933National Science Foundation DEB-9615226National Science Foundation DEB-9909347Office of Biological and Environmental ResearchOffice of ScienceSwedish Research Council 2024-05057Swedish Strategic Research Area 'Biodiversity and Ecosystem services in a Changing Climate'Swiss National Science Foundation PCEFP2_181115The European CommissionThe John D. and Catherine T. MacArthur FoundationThe Mellon FoundationThe Small World Institute FundThe Smithsonian Tropical Research InstituteThe Swedish Energy AgencyThe UK Natural Environment Research Council NE/W010003/1US Department of EnergyVinnova
6 · The paper itself

Abstract

Vegetation demographic models (VDMs) are advanced tools for simulating forest responses to climate and land-use changes, and are essential for projecting carbon cycling and large-scale forest management strategies. Despite their increasing incorporation into Earth System Models, VDMs differ in their demographic assumptions, with no prior quantitative comparison of their performance. We benchmarked nine VDMs against observational data from boreal, temperate and tropical sites, assessing their accuracy in predicting tree growth, carbon turnover, biomass stocks and size distributions. Models were simulated under consistent climate conditions with postdisturbance recovery monitored for at least 420 yr. Postdisturbance carbon recovery trajectories showed significant variability while remaining within observational ranges. Initial regrowth rates varied substantially (0.03-0.60, 0.18-0.70 and 0.35-1.10 kgCm

Indexed as

Computer SimulationDemographyForestsTreesBiomassCarbonModels, BiologicalCarbondemographic vegetation model benchmarkingforest demographygrowth–mortality dynamicsland‐surface modellingmodel intercomparisonpostdisturbance recoveryself‐thinningvegetation carbon

Identifiers

PMID41128161
PMCPMC12630465

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.