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Record W3176817982 · doi:10.1111/jbi.14156

Source pool diversity and proximity shape the compositional uniqueness of insular mammal assemblages worldwide

2021· article· en· W3176817982 on OpenAlexafffund
Katherine Hébert, Virginie Millien, J. LESSARD

Bibliographic record

VenueJournal of Biogeography · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsMcGill UniversityConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsInsular biogeographyBiological dispersalEcologyArchipelagoSpecies richnessBiogeographyMetacommunityBiologyTaxonNestednessPhylogenetic diversityBeta diversityPhylogenetic treeSpecies diversityPopulation

Abstract

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Abstract Aim Islands have been the test bed of several theories in community ecology, biogeography, and evolutionary biology. Progress within these disciplines has given a more comprehensive and mechanistic understanding of the processes governing variation in species richness among islands. However, it remains unclear whether these same processes also explain variation in species and phylogenetic composition among islands. Integrating theory from ecology and biogeography, we infer the roles of dispersal, selection, and stochasticity on the composition of insular assemblages within archipelagos. We further assess the influence of source pool diversity and connectivity on the compositional uniqueness of insular assemblages. Location Island systems worldwide. Taxon Mammals. Methods We compiled data on species composition of nonvolant mammals on ~200 islands in nine archipelagos distributed worldwide from the literature. We used variation partitioning to quantify the relative influence of the environment (selection) and geographic distance (dispersal) relative to a null model (stochasticity, randomness) on taxonomic and phylogenetic compositional turnover within archipelagos. We then used a linear mixed model to gain further insight into the underlying mechanisms shaping variation in assemblage composition among islands at a global scale. Specifically, we assessed the influence of source pool diversity, isolation from the source pool, and island characteristics on compositional uniqueness. Results Our results suggest that within‐archipelago variation in the composition of insular mammal assemblages is associated with stochastic or unmeasured processes rather than abiotic selection or dispersal limitation. The diversity and proximity of the source pool, as well as some island characteristics, explained variation in phylogenetic, but not taxonomic, compositional uniqueness globally. Globally, isolated islands associated with phylogenetically diverse source pools exhibit high phylogenetic uniqueness whereas well‐connected islands associated with phylogenetically clustered source pools show the opposite trend. Phylogenetically unique assemblages also tend occur on islands with a small elevational span and low annual temperature variation. Main conclusions Taken together, our results suggest that source pool diversity, along with the potential for colonization from those pools, has a strong influence on the composition of insular mammal assemblages worldwide.

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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 score0.008
Threshold uncertainty score0.388

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 studies0.0010.000
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 head0.015
GPT teacher head0.210
Teacher spread0.195 · 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

Citations25
Published2021
Admission routes2
Has abstractyes

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