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Is there limiting similarity in the phenology of fleshy fruits?

2005· article· en· W1988778794 on OpenAlexaffabout
Kevin C. Burns

Bibliographic record

VenueJournal of Vegetation Science · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsBamfield Marine Sciences Centre
Fundersnot available
KeywordsBiologyLimitingPhenologyAbundance (ecology)Competition (biology)EcologyHorticultureBotany

Abstract

fetched live from OpenAlex

Abstract Question: Is there evidence for limiting similarity in the timing of fruit production by a bird‐dispersed plant community? Is the rate of fruit removal in each plant species inversely related to fruit availability in other species? Can simple measurements of fruit phenologies (i.e. temporal changes in fruit availability) obscure important fruit attributes that influence their removal by birds? Location: Vancouver Island, British Columbia, Canada. Methods: Periods of fruit availability were measured in ten woody angiosperm species for two years. In the second year, the fate of individual fruits was quantified to disentangle dates of fruit maturation, removal and mortality from measurements of availability. Results: Null model analyses of fruit availability distributions showed no evidence for limiting similarity. However, fruit removal rates of most plant species were correlated with their relative abundance in the community, indicating fruits were removed more rapidly when other fruits were less abundant. Species with similar periods of fruit availability often had different dates of fruit maturation, rates of fruit removal and fruit persistence times, indicating fruit availability measurements can obscure important bird‐fruit interactions. Conclusions: Competition for dispersers appears to occur. However, it has not resulted in limiting similarity in fruit availability distributions. A likely explanation for this discrepancy is that fruit availability distributions often confound several important fruit attributes that can independently influence fruit removal by birds.

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)0.002
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 score0.055
Threshold uncertainty score0.250

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.298
Teacher spread0.271 · 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

Citations25
Published2005
Admission routes2
Has abstractyes

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