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Evolutionary constraints on regional faunas: whom, but not how many

2008· article· en· W2149332995 on OpenAlexaff
Adam C. Algar, Jeremy T. Kerr, David J. Currie

Bibliographic record

VenueEcology Letters · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCladogenesisSpecies richnessEcologyNicheMacroecologyBiologyBiogeographyBiodiversitySpecies diversityEcological nichePhylogenetic treeCladeHabitat

Abstract

fetched live from OpenAlex

The latitudinal diversity gradient has been hypothesized to reflect past evolutionary dynamics driven by climatic niche conservation during cladogenesis, i.e. the tropical conservatism hypothesis. Here we show that the species diversity of treefrogs (Hylidae) across the western hemisphere is actually independent of evolutionary niche dynamics. We evaluated three key predictions of the tropical conservatism hypothesis that relate to the relationships between climate, species richness and the phylogenetic structure of regional treefrog faunas across the continental Americas. Species composition was dependent on the inability of some lineages to evolve cold tolerance, but the actual number of species in a region was strongly predicted by precipitation, not temperature. Moreover, phylogenetic structure was independent of precipitation. Thus, species in low-richness areas were no more closely related than species in highly diverse regions. These results provide no support for the tropical conservatism hypothesis. Instead, they show that regional species composition and richness are constrained by different climatic components, demonstrating that global biodiversity gradients can be independent of niche stasis during cladogenesis.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.219
Teacher spread0.187 · 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 source (direct Gemma or distilled Codex), 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

Citations88
Published2008
Admission routes1
Has abstractyes

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