MétaCan
Menu
Back to cohort
Record W1920693300 · doi:10.1073/pnas.1513125112

Community rescue in experimental metacommunities

2015· article· en· W1920693300 on OpenAlexaff
Étienne Low‐Décarie, Marcus Kolber, Paige Homme, Andrea Lofano, Alex J. Dumbrell, Andrew Gonzalez, Graham Bell

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiological dispersalEcologyEnvironmental stressCommunityBiologyDisturbance (geology)Environmental degradationDiversity (politics)Community structureEnvironmental resource managementEcosystemEnvironmental scienceEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

The conditions that allow biodiversity to recover following severe environmental degradation are poorly understood. We studied community rescue, the recovery of a viable community through the evolutionary rescue of many populations within an evolving community, in metacommunities of soil microbes adapting to a herbicide. The metacommunities occupied a landscape of crossed spatial gradients of the herbicide (Dalapon) and a resource (glucose), whereas their constituent communities were either isolated or connected by dispersal. The spread of adapted communities across the landscape and the persistence of communities when that landscape was degraded were strongly promoted by dispersal, and the capacity to adapt to lethal stress was also related to community size and initial diversity. After abrupt and lethal stress, community rescue was most frequent in communities that had previously experienced sublethal levels of stress and had been connected by dispersal. Community rescue occurred through the evolutionary rescue of both initially common taxa, which remained common, and of initially rare taxa, which grew to dominate the evolved community. Community rescue may allow productivity and biodiversity to recover from severe environmental degradation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.001
Research integrity0.0000.001
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 head0.082
GPT teacher head0.348
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations88
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicEvolution and Genetic DynamicsFrench-language works237,207