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Record W2128952771 · doi:10.1890/06-0781.1

DISPERSAL OF SEEDS BY THE TROPICAL SEA BREEZE

2008· article· en· W2128952771 on OpenAlexaff
David F. Greene, Maurício Quesada, C. Calogeropoulos

Bibliographic record

VenueEcology · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsConcordia University
Fundersnot available
KeywordsBiological dispersalSea breezeWind speedSeed dispersalAbscissionGlobal wind patternsPrevailing windsWind directionEcologyRelative humidityNocturnalEnvironmental scienceSunriseOceanographyAtmospheric sciencesBiologyGeographyGeologyMeteorologyBotanyPopulation

Abstract

fetched live from OpenAlex

Given the dependence of most wind-pollinated and wind-dispersed species on low relative humidity (RH) for abscission, and the minimization of RH in the early afternoon, there ought to be a marked directional bias in seed dispersal at sites with a strong local diurnal circulation. We filmed the abscission of seeds of five wind-dispersed tropical species near the coast of Mexico (Jalisco). We found that (1) most abscission occurred during the period from 10:00 to 17:00 hours; (2) there was a strong bias for landward dispersal due to the midday sea breeze; (3) the little nocturnal dispersal that occurred was toward the sea (due to the night land breeze); (4) there was no abscission in the absence of wind (i.e., indoors) except for one species; and (5) holding relative humidity constant, the proportion of seeds diurnally abscising is strongly correlated with horizontal wind speed. We predict that a similar bias (this time for upslope dispersal) for xerochastic dispersal will occur in complex terrain. We conclude that in coastal and mountainous terrain, dispersal models (and inverse modeling efforts) must include a directionality term.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.997

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)0.0040.000

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 head0.010
GPT teacher head0.185
Teacher spread0.175 · 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.

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

Citations71
Published2008
Admission routes1
Has abstractyes

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