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Record W2575270351 · doi:10.1139/cjb-2016-0252

Comparative phenology of mistletoes shows effect of different host species and temporal niche partitioning

2017· article· en· W2575270351 on OpenAlexvenueno aff
Luíza Teixeira-Costa, Fábio Machado Coelho, Gregório Ceccantini

Bibliographic record

VenueBotany · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsnot available
FundersUniversidade de São Paulo
KeywordsPhenologyBiologyEvergreenDeciduousHost (biology)NicheEcologyBotanyPopulation

Abstract

fetched live from OpenAlex

The study of plant phenology deals with seasonal events and how these are influenced by environmental factors, including symbiotic interactions. Considering host–mistletoe associations, our goal was to analyze the potential effects of host tree deciduousness on the life cycle of a mistletoe. Thus, Struthanthus martianus Dettke & Waechter was analyzed while growing upon a deciduous host tree and upon an evergreen one. We also compared the phenology of S. martianus with that of a closely related and sympatric species, Struthanthus flexicaulis (Mart. ex Schult. f.) Mart., growing upon a different but also evergreen host. Reproductive and vegetative phenological events were recorded during a three year period following a semiquantitative method. Circular statistical analysis was employed to compare phenological patterns. The peak of leaf production in S. martianus was observed to depend on host deciduousness, as the population infesting a deciduous host showed significant leaf flush during host defoliation. When comparing S. martianus and S. flexicaulis, nearly opposite patterns of flowering and fruiting phenology were recorded. Based on these observations, we conclude that Struthanthus species show niche partitioning to avoid competition. Additionally, we observed that the relationship established with different hosts can alter the mistletoe phenology. This observation highlights the uniqueness of the each host–mistletoe relationship.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.129

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)0.0000.000

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 head0.031
GPT teacher head0.257
Teacher spread0.226 · 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

Citations12
Published2017
Admission routes1
Has abstractyes

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