Evidence map›Paper›PMID 41853091›Full record

ArticleNational science review2026

Carry-over effects between spring and autumn phenology differ among the world's biomes.

Zhaofei Wu, Yongshuo H Fu, Thomas W Crowther, Susanne S Renner, Yann Vitasse, Lidong Mo, Yibiao Zou, Leila Mirzagholi, Mingwei Li, Dominic Rebindaine and 4 more

Abstract read
In one paragraph

Article in National science review, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

14 authors.

Zhaofei WuCollege of Water Sciences, Beijing Normal University, Beijing 100875, China.
Yongshuo H FuCollege of Water Sciences, Beijing Normal University, Beijing 100875, China.ORCID https://orcid.org/0000-0002-9761-5292
Thomas W CrowtherBRANCH Institute, Zug 6300, Switzerland.
Susanne S RennerDepartment of Biology, Washington University in St. Louis, Saint Louis, MO 63130, USA.
Yann VitasseEcosystem Ecology, Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf 8903, Switzerland.ORCID https://orcid.org/0000-0002-7454-505X
Lidong MoCollege of Life Science, Nankai University, Tianjin 300071, China.ORCID https://orcid.org/0000-0003-3805-7638
Yibiao ZouEcosystem Ecology, Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf 8903, Switzerland.
Leila MirzagholiDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Mingwei LiCollege of Water Sciences, Beijing Normal University, Beijing 100875, China.
Dominic RebindaineEcosystem Ecology, Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf 8903, Switzerland.
Yufeng GongCollege of Water Sciences, Beijing Normal University, Beijing 100875, China.
Zhendong GuoCollege of Water Sciences, Beijing Normal University, Beijing 100875, China.
Nan WangCollege of Water Sciences, Beijing Normal University, Beijing 100875, China.
Constantin M ZohnerBRANCH Institute, Zug 6300, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Climate warming alters the start (SOS) and end (EOS) of growing seasons, impacting biotic interactions and biogeochemical cycles, yet the carry-over links between SOS and EOS remain poorly understood, limiting future projections. Using MODIS satellite-derived phenology data for seasonal vegetation and European ground observations for deciduous tree species, we show that an earlier SOS typically advances the EOS [on average by 0.19 ± 0.001 days per day (MODIS) and 0.10 ± 0.002 days per day (ground)], while EOS exerts a weaker influence on subsequent SOS. The SOS-to-EOS effect often outweighed abiotic factors, with SOS emerging as the best predictor of EOS in 34% of pixels (β = 0.27). When predicting SOS, EOS was the primary predictor in only 7.9% of pixels, while preseason temperature dominated in 58% (β = -0.33). More importantly, we identified a dampening interaction, where an increase in one carry-over effect reduced the other. Thus, the SOS-to-EOS effect was twice as strong as the EOS-to-SOS effect in temperate deciduous forests, while the EOS-to-SOS effect was up to three times stronger in boreal taiga and tundra. The observed carry-over effects likely reflect developmental (cell and tissue growth) and stress-related constraints (SOS-to-EOS effect), as well as chilling requirements (EOS-to-SOS effect at high latitudes). These findings highlight how physiological feedback affects phenological responses to climate change, emphasizing the need to integrate plant-internal carry-over effects into future ecosystem models.

Indexed as

climate changeleaf-outleaf senescencephenological carry-over effectsphysiological constraints

Identifiers

PMID41853091
PMCPMC12993445

What OpenQuestion holds

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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.