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Record W4234013494 · doi:10.7287/peerj.preprints.26440

Historical contingency, niche conservatism and the tendency for some taxa to be more diverse towards the poles

2018· preprint· en· W4234013494 on OpenAlexaff
Ignacio Morales‐Castilla, Jonathan Davies, Miguel Á. Rodrı́guez

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiological dispersalNicheEcologyDiversity (politics)GeographyTaxonCladeLand bridgeConservatismBiologyEconomic geographyPhylogenetic treePopulationDemography

Abstract

fetched live from OpenAlex

Successful explanations for diversity gradients should account for both the generalized tendency towards a higher tropical diversity and its exceptions. Moreover, identifying exceptions to general trends, such as the latitudinal diversity gradient can give insight into the mechanistic explanations responsible for structuring them. The Cenozoic biotic exchange of mammals across the Bering land-bridge provides an illuminating case-study. It allows comparing the diversity of clades that participated in the exchange (colonizers), whose ancestors withstood the Beringian cold temperatures, with that of the clades that did not participate (sedentaries). We find that assemblages of colonizers are more diverse towards higher latitudes, opposing the traditional latitudinal diversity gradient which is followed by sedentaries. Despite the long passage of time since this major dispersal event, the geographic distribution of colonizers is more strongly correlated to the distributions of other colonizers inhabiting a different continent than by the distribution of sedentary species. These results highlight the importance of historical migrations and dispersal in configuring present-day diversity gradients. Importantly, we also suggest that colonizers may be particularly vulnerable to projected climate change because of the predicted decrease in climate space in the extra-tropical realm where they are currently most diverse.

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)0.001
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: none
Teacher disagreement score0.621
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.082
GPT teacher head0.278
Teacher spread0.196 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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