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Record W4211097646 · doi:10.1111/ele.13682

Ecophylogenetics redux

2021· review· en· W4211097646 on OpenAlexaff
T. Jonathan Davies

Bibliographic record

VenueEcology Letters · 2021
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEcologyPhylogenetic treeBiologyCommunityNicheEcological successionBiodiversityPhylogeneticsEcosystem

Abstract

fetched live from OpenAlex

Species' evolutionary histories shape their present-day ecologies, but the integration of phylogenetic approaches in ecology has had a contentious history. The field of ecophylogenetics promised to reveal the process of community assembly from simple indices of phylogenetic pairwise distances - communities shaped by environmental filtering were composed of closely related species, whereas communities shaped by competition were composed of less closely related species. However, the mapping of ecology onto phylogeny proved to be not so straightforward, and the field remains mired in controversy. Nonetheless, ecophylogenetic methods provided important advances across ecology. For example the phylogenetic distances between species is a strong predictor of pest and pathogen sharing, and can thus inform models of species invasion, coexistence and the disease dilution/amplification effect of biodiversity. The phylogenetic structure of communities may also provide information on niche space occupancy, helping interpret patterns of facilitation, succession and ecosystem functioning - with relevance for conservation and restoration - and the dynamics among species within foodwebs and metacommunities. I suggest leveraging advances in our understanding of the process of evolution on phylogenetic trees would allow the field to progress further, while maintaining the essence of the original vision that proved so seductive.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.961
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.090
GPT teacher head0.257
Teacher spread0.167 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations58
Published2021
Admission routes1
Has abstractyes

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