Evidence map›Paper›PMID 40721540›Full record

ArticleNature ecology & evolution2025

Lagged precipitation effects on plant production across terrestrial biomes.

Lei He, Jian Wang, Drew M P Peltier, François Ritter, Philippe Ciais, Josep Peñuelas, Jingfeng Xiao, Thomas W Crowther, Xing Li, Jian-Sheng Ye and 3 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature ecology & evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

13 authors.

Lei HeState Key Laboratory of Efficient Utilization of Arable Land in China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China.ORCID http://orcid.org/0000-0001-5989-1870
Jian WangThe Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China. wangjian@igsnrr.ac.cn.ORCID http://orcid.org/0000-0003-0813-5965
Drew M P PeltierSchool of Life Sciences, University of Nevada-Las Vegas, Las Vegas, NV, USA.
François RitterLaboratoire des Sciences du Climat et de l'Environnement, CEA/CNRS/UVSQ/ Université Paris Saclay, Gif-sur-Yvette, France.
Philippe CiaisLaboratoire des Sciences du Climat et de l'Environnement, CEA/CNRS/UVSQ/ Université Paris Saclay, Gif-sur-Yvette, France.ORCID http://orcid.org/0000-0001-8560-4943
Josep PeñuelasCSIC, Global Ecology CREAF-CSIC-UAB, Cerdanyola del Vallès, Barcelona, Spain.ORCID http://orcid.org/0000-0002-7215-0150
Jingfeng XiaoEarth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA.ORCID http://orcid.org/0000-0002-0622-6903
Thomas W CrowtherInstitute of Integrative Biology, ETH Zurich (Swiss Federal Institute of Technology), Zurich, Switzerland.ORCID http://orcid.org/0000-0001-5674-8913
Xing LiSchool of Geography and Planning, Sun Yat-sen University, Guangzhou, China.ORCID http://orcid.org/0000-0003-2206-0429
Jian-Sheng YeState Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystems, College of Ecology, Lanzhou University, Lanzhou, China.ORCID http://orcid.org/0000-0001-5335-7896
Takehiro SasakiGraduate School of Environment and Information Science, Yokohama National University, Yokohama, Japan.ORCID http://orcid.org/0000-0001-8727-9152
Chenghu ZhouCenter for Ocean Remote Sensing of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China.
Zhao-Liang LiState Key Laboratory of Efficient Utilization of Arable Land in China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China. lizhaoliang@caas.cn.ORCID http://orcid.org/0000-0002-4861-4357

Funding

National Natural Science Foundation of China (National Science Foundation of China) 41921001NSF | BIO | Division of Environmental Biology (DEB) 41921001
6 · The paper itself

Abstract

Precipitation effects on plant carbon uptake extend beyond immediate timeframes, reflecting temporal lags between rainfall and plant growth. Mechanisms and relative importance of such lagged effects are expected to vary across ecosystems. Here we draw on an extensive collections of productivity proxies from long-term ground measurements, satellite observations and model simulations to show that preceding-year precipitation exerts a comparable influence on plant productivity to current-year precipitation. Statistically supported lagged precipitation effects are detected in 13.4%-19.7% of the grids depending on the data source. In these sites, preceding-year precipitation positively controls current-year plant productivity in water-limited areas, while negative effects occur in some wet regions, such as tropical forests. While aridity emerges as the main driver of this spatial variability, machine learning-based spatial attribution also indicates interactions among plant traits, climatic conditions and soil properties. We also show that soil water dynamics, plant phenology and foliar structure might mediate lagged precipitation effects across time. Our findings highlight the role of preceding-year precipitation in global plant productivity.

Indexed as

EcosystemPlant DevelopmentPlantsRainSoilSoil

Identifiers

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.