Evidence map›Paper›PMID 38824461›Full record

ArticleOecologia2024

Disturbance history, neighborhood crowding and soil conditions jointly shape tree growth in temperate forests.

Shuai Fang, Jing Ren, Marc William Cadotte, Zuoqiang Yuan, Zhanqing Hao, Xugao Wang, Fei Lin, Claire Fortunel

Abstract read
PubMed Publisher
In one paragraph

Article in Oecologia, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Shuai FangCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China.
Jing RenCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China.
Marc William CadotteDepartment of Biological Sciences, University of Toronto-Scarborough, Toronto, ON, M1C 1A4, Canada.
Zuoqiang YuanResearch Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an, China.
Zhanqing HaoResearch Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an, China.
Xugao WangCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China.
Fei LinCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China. linfei@iae.ac.cn.
Claire FortunelAMAP (Botanique et Modélisation de l'Architecture des Plantes et des Végétations), CIRAD, CNRS, INRAE, IRD, Université de Montpellier, Montpellier, France. claire.fortunel@ird.fr.ORCID http://orcid.org/0000-0002-8367-1605

Funding

Doctoral Start-up Foundation of Liaoning Province 2022-BS-020Major Program of Institute of Applied Ecology, Chinese Academy of Science IAEMP202201National Key Research and Development Program of China 2021YFD2200402National Key Research and Development Program of China 2022YFF1300501National Key Research and Development Program of China 2023YFF0805801National Natural Science Foundation of China 31961133027National Natural Science Foundation of China 32001121Strategic Priority Research Program of the Chinese Academy of Sciences XDB31000000
6 · The paper itself

Abstract

Understanding how different mechanisms act and interact in shaping communities and ecosystems is essential to better predict their future with global change. Disturbance legacy, abiotic conditions, and biotic interactions can simultaneously influence tree growth, but it remains unclear what are their relative contributions and whether they have additive or interactive effects. We examined the separate and joint effects of disturbance intensity, soil conditions, and neighborhood crowding on tree growth in 10 temperate forests in northeast China. We found that disturbance was the strongest driver of tree growth, followed by neighbors and soil. Specifically, trees grew slower with decreasing initial disturbance intensity, but with increasing neighborhood crowding, soil pH and soil total phosphorus. Interestingly, the decrease in tree growth with increasing soil pH and soil phosphorus was steeper with high initial disturbance intensity. Testing the role of species traits, we showed that fast-growing species exhibited greater maximum tree size, but lower wood density and specific leaf area. Species with lower wood density grew faster with increasing initial disturbance intensity, while species with higher specific leaf area suffered less from neighbors in areas with high initial disturbance intensity. Our study suggests that accounting for both individual and interactive effects of multiple drivers is crucial to better predict forest dynamics.

Indexed as

EcosystemForestsSoilTreesChinaSoilDisturbanceFunctional traitNeighborhood crowdingSoilTree growth

Identifiers

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.