Evidence map›Paper›PMID 41066155›Full record

ArticleeLife2025

Partitioning changes in ecosystem productivity by effects of species interactions in biodiversity experiments.

Jing Tao, Charles A Nock, Eric B Searle, Shongming Huang, Rongzhou Man, Hua Yang, Grégoire T Freschet, Cyrille Violle, Ji Zheng

Abstract read
In one paragraph

Article in eLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Jing TaoJilin Provincial Academy of Forestry Sciences, Changchun, China.
Charles A NockDepartment of Renewable Resources, Faculty of Agriculture, Life, and Environmental Sciences, University of Alberta, Edmonton, Canada.
Eric B SearleOntario Ministry of Natural Resources and Forestry, Ontario Forest Research Institute, Sault Ste. Marie, Canada.
Shongming HuangForestry Division, Department of Agriculture and Forestry, Government of Alberta, Edmonton, Canada.
Rongzhou ManOntario Ministry of Natural Resources and Forestry, Ontario Forest Research Institute, Sault Ste. Marie, Canada.ORCID https://orcid.org/0000-0003-4560-5620
Hua YangCollege of Forestry, Beijing Forestry University, Beijing, China.
Grégoire T FreschetStation d'Ecologie Théorique et Expérimentale, CNRS, Foix, France.
Cyrille ViolleCEFE, CNRS, EPHE, IRD, Montpellier, France.
Ji ZhengSchool of Agriculture and Biology, and Shanghai Urban Forest Ecosystem Research Station of National Forestry and Grassland Administration, Shanghai Jiao Tong University, Shanghai, China.ORCID https://orcid.org/0000-0003-4936-1168

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Species interactions affect ecosystem productivity. Positive interactions (resource partitioning and facilitation) increase productivity while negative interactions (species interference) decrease productivity relative to the null expectations defined by monoculture yields. Effects of competitive interactions (resource competition) can be either positive or negative. Distinguishing effects of species interactions is therefore difficult, if not impossible, with current biodiversity experiments involving mixtures and full density monocultures. To partition changes in ecosystem productivity by effects of species interactions, we modify null expectations with competitive growth responses, i.e., proportional changes in individual size (biomass or volume) expected in mixture based on species differences in growth and competitive ability. We use partial density (species density in mixture) monocultures and the competitive exclusion principle to determine maximum competitive growth responses and full density monoculture yields to measure species ability to achieve maximum competitive growth responses in mixture. Deviations of observed yields from competitive expectations represent the effects of positive/negative species interactions, while the differences between competitive and null expectations reflect the effects of competitive interactions. We demonstrate the effectiveness of our competitive partitioning model in distinguishing effects of species interactions using both simulated and experimental species mixtures. Our competitive partitioning model enables meaningful assessments of species interactions at both species and community levels and helps disentangle underlying mechanisms of species interactions responsible for changes in ecosystem productivity and identify species mixtures that maximize positive effects.

Indexed as

BiodiversityEcosystemBiomassModels, Biologicalbiodiversity effectbiodiversity-productivity relationshipcompetitive expectationcompetitive interactioncompetitive partitioningecologynoneplant species interactions

Identifiers

PMID41066155
PMCPMC12510681

What OpenQuestion holds

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LicenceCC BY
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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.