MétaCan
Menu
Back to cohort

Eco‐evolutionary dynamics of communities and ecosystems

2007· article· en· W2143913979 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFunctional Ecology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsUniversity of TorontoMcGill University
Fundersnot available
KeywordsEvolutionary dynamicsBiologyEcologyTraitEvolutionary ecologyPopulationAdaptation (eye)Computer science

Abstract

fetched live from OpenAlex

Summary We review theoretical and empirical studies to identify instances where evolutionary processes significantly affect the dynamics of populations, communities and ecosystems. Early theoretical work on eco‐evolutionary dynamics was concerned with the effect of (co)evolution on the stability of two‐species predator–prey systems and the occurrence of character displacement in simple competitive systems. Today's theoretical ecologists are extending this work to study the eco‐evolutionary dynamics of multispecies communities and the functioning and evolutionary emergence of ecosystems. In terms of methodology, eco‐evolutionary modelling has diversified from simple, locus‐based population genetic models to encompass models of clonal selection, quantitative trait dynamics and adaptive dynamics. The few empirical studies on community dynamics that explicitly considered evolutionary processes support the view that evolutionary and ecological dynamics often occur on similar time‐scales, and that they co‐determine the dynamical behaviour of ecological communities.

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.

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 score0.089
Threshold uncertainty score0.462

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 integrity0.0000.000
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 head0.007
GPT teacher head0.217
Teacher spread0.210 · 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