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Record W2038150976 · doi:10.1086/660830

Adaptive Radiation and Ecological Opportunity in Sulawesi and Philippine Fanged Frog (<i>Limnonectes</i>) Communities

2011· article· en· W2038150976 on OpenAlexaff
Mohammad Iqbal Setiadi, Jimmy A. McGuire, Rafe M. Brown, Mohammad Zubairi, Djoko T. Iskandar, Noviar Andayani, Jatna Supriatna, Ben J. Evans

Bibliographic record

VenueThe American Naturalist · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsMcMaster University
FundersNational Science Foundation
KeywordsEcologyAdaptive radiationBiologyGeographyPhylogenetics

Abstract

fetched live from OpenAlex

Because island communities are derived from mainland communities, they are often less diverse by comparison. However, reduced complexity of island communities can also present ecological opportunities. For example, amphibian diversity on Sulawesi Island is lower than it is in the Philippines, but Sulawesi supports a surprising diversity of Sulawesi fanged frogs (Limnonectes). Here we examine molecular, morphological, and geographical variation of fanged frogs from these two regions. Using genealogical concordance, morphology, and a Bayesian approach to species delimitation, we identified 13 species on Sulawesi, only four of which have been previously described. After evolutionary history is accounted for, a model with multiple body size optima in sympatric species is favored over a "random-walk" model of body size evolution. Additionally, morphological variation is higher among sympatric than nonsympatric species on Sulawesi but not in the Philippines. These findings suggest that adaptive radiation of fanged frogs on Sulawesi was driven by natural selection to infiltrate ecological niches occupied by other frog lineages in the Philippines. This supports a role of ecological opportunity in community assembly: diversification in mature communities, such as the Philippines, is limited by a dearth of unoccupied ecological niches. On Sulawesi, evolutionary novelties originated in a predictable and replicated fashion in response to opportunities presented by a depauperate ancestral community.

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 score0.177
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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.232
Teacher spread0.200 · 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

Citations83
Published2011
Admission routes1
Has abstractyes

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