MétaCan
Menu
Back to cohort
Record W2006460052 · doi:10.1073/pnas.0400814101

Neutrality, niches, and dispersal in a temperate forest understory

2004· article· en· W2006460052 on OpenAlexaff
Benjamin Gilbert, Martin J. Lechowicz

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of British ColumbiaMcGill University
Fundersnot available
KeywordsBiological dispersalEcologyNicheEcological nicheNeutral theory of molecular evolutionUnderstoryBiologyAbundance (ecology)Adaptation (eye)Niche segregationRelative abundance distributionCoexistence theoryCommunityCompetition (biology)Relative species abundanceHabitatPopulation

Abstract

fetched live from OpenAlex

A fundamental goal of ecology is to understand what controls the distribution and abundance of species. Both environmental niches and trade-offs among species in dispersal and competitive ability have traditionally been cited as determinants of plant community composition. More recently, neutral models have shown that communities of species with identical life-history characteristics and no adaptation to environmental niches can form spatial distribution patterns similar to those found in nature, so long as the species have a limited dispersal distance. If there is a strong correlation between geographic distance and change in environmental conditions, however, such spatial patterns can arise through either neutral or niche-based processes. To test these competing theories, we developed a sampling design that decoupled distance and environment in the understory plant communities of an old-growth, temperate forest. We found strong evidence of niche-structuring but almost no support for neutral predictions. Dispersal limitation acted in conjunction with environmental gradients to determine species' distributions, and both functional and phylogenetic constraints appear to contribute to the niche differentiation that structures community assembly. Our results indicate that testing a neutral hypothesis without accounting for environmental gradients will at best cause unexplained variation in plant distributions and may well provide misleading support for neutrality because of a correlation between geographic distance and environment.

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)0.001
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 score0.023
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.030
GPT teacher head0.279
Teacher spread0.249 · 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

Citations523
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicEcology and Vegetation Dynamics StudiesFrench-language works237,207