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Record W2192470278 · doi:10.1139/cjb-2015-0143

Endemism in native floras of California’s Channel Islands correlated with seasonal patterns of aeolian processes

2015· article· en· W2192470278 on OpenAlexvenueno aff
Lynn Riley, Mitchell E. McGlaughlin

Bibliographic record

VenueBotany · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEndemismBiological dispersalFlora (microbiology)EcologyPhytogeographyBiologyInsular biogeographyMainlandIntroduced speciesBiogeographyTaxonPopulationPaleontology

Abstract

fetched live from OpenAlex

This study revisits the hypothesis that dispersal to California’s Channel Islands follows a stepping-stone pattern from mainland California, based on earlier work indicating that the floras conform to classic island-biogeographic expectations. A re-examination of data incorporating the directions of prevailing and seasonal Santa Ana winds greatly strengthens the power of the model to explain levels of endemism in the Channel Island floras, and suggests the importance of aoelian processes for island colonization. Regression analysis of percent endemism in the native flora against distances measured along the axis of winds improves the r 2 from 0.099 to 0.482. The endemic species that flower in the dry season as a percent of the native flora of the islands is also strongly related to these revised source distances (r 2 = 0.665). Furthermore, the native floras of the southern islands are nested subsets of the floras of the northern islands, and angiosperm flowering peaks during the dry season, providing seed for seasonally based dispersal. These results suggest that the northern islands may have served as a source of colonists for the southern islands, and that the pattern of aeolian inputs into an island system should be considered in other plant biogeographic studies.

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 score0.007
Threshold uncertainty score0.225

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 head0.013
GPT teacher head0.225
Teacher spread0.212 · 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

Citations11
Published2015
Admission routes1
Has abstractyes

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