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Interspecific interactions and biomass allocation among grassland plant species

2003· article· en· W2170086783 on OpenAlexfundno aff
David A. Wardle, Duane A. Peltzer

Bibliographic record

VenueOikos · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInterspecific competitionMonocultureBiomass (ecology)ShootBiologyCompetition (biology)GrasslandAgronomyBotanyPlant speciesPlant communityEcologyEcological succession

Abstract

fetched live from OpenAlex

Although a handful of studies have shown how interspecific interactions may influence plant shoot to root ratios, the issue of how these interactions influence biomass partitioning among coexisting plant species remains largely unexplored. In this study, we determined whether a given plant species could induce other plant species to allocate relative biomass to each of four zones (aboveground, and three soil depth layers) in a different manner to what they would otherwise, and whether this may influence the nature of competitive or facilitative interactions amongst coexisting plant species. We used a glasshouse study in which mixtures and monocultures of ten grassland plant species were grown in cylindrical pots to determine the effects of plant species mixtures versus monocultures on the production of shoots and of roots of other species for each of three soil depths. Across all experiments, stimulation of production in mixtures was far less common than suppression of production. Different plant species shifted their allocation to shoots or roots at different depths, suggesting that interspecific interactions can either: (1) increase the ratio of deep to shallow roots, perhaps because competition reduces root growth in the uppermost part of the soil profile; or (2) decrease this ratio by reducing plant vigour to such an extent that the plant cannot produce roots that can reach deep enough to exploit resources at lower depths. Further, these results suggest that there are instances in which competition may have the potential to enforce resource partitioning between coexisting plant species by inducing different species to root at different depths to each other.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.221
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations63
Published2003
Admission routes1
Has abstractyes

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