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Record W4220851318 · doi:10.1111/ele.13997

Phylogenetic and functional clustering illustrate the roles of adaptive radiation and dispersal filtering in jointly shaping late‐Quaternary mammal assemblages on oceanic islands

2022· letter· en· W4220851318 on OpenAlexaff
Xingfeng Si, Marc W. Cadotte, T. Jonathan Davies, Alexandre Antonelli, Ping Ding, Jens‐Christian Svenning, Søren Faurby

Bibliographic record

VenueEcology Letters · 2022
Typeletter
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsUniversity of British ColumbiaThe Scarborough HospitalUniversity of Toronto
FundersProgram for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher LearningShanghai Rising-Star ProgramStiftelsen för Strategisk ForskningVetenskapsrådetNational Natural Science Foundation of ChinaStiftelsen för Strategisk ForskningCarlsbergfondetRoyal Botanical Gardens, KewFundamental Research Funds for the Central UniversitiesVillum Fonden
KeywordsBiological dispersalMammalEcologyAdaptive radiationQuaternaryPhylogenetic treeBiologyCommunityCluster analysisPaleontologyHabitatComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Islands frequently harbour unique assemblages of species, yet their ecological roles and differences are largely ignored in island biogeography studies. Here, we examine eco-evolutionary processes structuring mammal assemblages on oceanic islands worldwide, including all extant and extinct late-Quaternary mammal species. We find island mammal assemblages tend to be phylogenetically clustered (share more recent evolutionary histories), with clustering increasing with island area and isolation. We also observe that mammal assemblages often tend to be functionally clustered (share similar traits), but the strength of clustering is weak and generally independent from island area or isolation. These findings indicate the important roles of in situ speciation and dispersal filtering in shaping island mammal assemblages under pre-anthropogenic conditions, notably through adaptive radiation of a few clades (e.g. bats, with generally high dispersal abilities). Our study demonstrates that considering the functional and phylogenetic axes of diversity can better reveal the eco-evolutionary processes of island community assembly.

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 score0.025
Threshold uncertainty score0.996

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 integrity0.0000.001
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 head0.026
GPT teacher head0.208
Teacher spread0.182 · 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

Citations51
Published2022
Admission routes1
Has abstractyes

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