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Record W2147178170 · doi:10.15517/rbt.v60i4.2050

Phenology of tropical understory trees: patterns and correlates

2012· article· es· W2147178170 on OpenAlexafffund
W. Alice Boyle, Judith L. Bronstein

Bibliographic record

VenueRevista de Biología Tropical · 2012
Typearticle
Languagees
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of ArizonaNational Science Foundation
KeywordsPhenologyEcologyUnderstoryBiologyAbiotic componentTransectCanopyGeography

Abstract

fetched live from OpenAlex

Reproductive phenologies of plants are constrained by climate in highly seasonal regions. In contrast, plants growing in wet tropical forests are freed from many abiotic constraints, which in canopy tree communities lead to a rich diversity of phenological patterns within and among individuals, species and communities. However, basic descriptions of tropical phenological patterns and the processes that shape them are rare. Here, we document the individual-, population-, and landscape-level phenological patterns of two dominant families of understory woody plants important to avian frugivores, the Melastomataceae and Rubiaceae, along an elevational transect in Costa Rica. The 226 individual plants belonging to 35 species in this study, varied in the number of reproductive bouts/year, and the timing, duration, and synchrony of reproductive stages. This variation was not related to factors related to their interactions with mutualists and antagonists, nor did it appear to be constrained by phylogeny. Diverse phenological patterns among species led to relatively aseasonal patterns at the community and landscape level. Overall, evidence for biotic processes shaping temporal patterns of fruiting phenology was weak or absent. These findings reveal a number of unexplained patterns, and suggest that factors shaping phenology in relatively aseasonal forests operate in idiosyncratic ways at the species level.

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 score0.032
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.045
GPT teacher head0.236
Teacher spread0.191 · 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

Citations35
Published2012
Admission routes2
Has abstractyes

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