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Record W2067884343 · doi:10.1086/660286

Facilitation within Species: A Possible Origin of Group-Selected Superorganisms

2011· article· en· W2067884343 on OpenAlexafffund
Eliot J. B. McIntire, Alex Fajardo

Bibliographic record

VenueThe American Naturalist · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsFacilitationBiologyGroup (periodic table)Evolutionary biologyEcologyZoologyGeographyChemistryNeuroscience

Abstract

fetched live from OpenAlex

Facilitation (positive interactions) has emerged as a dominant ecological mechanism in many ecosystems. Its importance has recently been expanded to include intraspecific interactions, creating the potential for higher-level natural selection within species. Using multiple lines of evidence, we show that conspecific facilitation within the southern beech tree, Nothofagus pumilio, appears to overcome competition in two life phases. In a seedling experiment addressing stress and planting-density effects, we found that mortality was lowest (∼0%) where there was no stress and was indistinguishable across densities. Furthermore, in mature forests (45 years old), genetically variable, merged individuals had lower mortality (-50%) than unmerged individuals in locations without identifiable stress. Thus, a full understanding of the occurrence of facilitation may require a more general model of resource improvements than the commonly cited stress gradient hypothesis. Additionally, the merged trees showed a density-dependent mortality pattern at the level of the group. These data demonstrate a potential mechanism (facilitation) driving natural selection at this higher level, via stem merging. These merged "superorganisms" would confirm theoretical predictions whereby facilitation acts as an ecological mechanism driving group selection.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.736

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.059
GPT teacher head0.221
Teacher spread0.163 · 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

Citations54
Published2011
Admission routes2
Has abstractyes

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