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Population and community variability in randomly fluctuating environments

2004· article· en· W2106114765 on OpenAlexaff
Andrew Gonzalez, Blandine Descamps‐Julien

Bibliographic record

VenueOikos · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsSpecies richnessEcologyBiomass (ecology)PopulationCompetition (biology)Abundance (ecology)Community structureCommunityBiologyEcological stabilityBiodiversityEcosystemDemography

Abstract

fetched live from OpenAlex

The prediction that environmental fluctuations may destabilise populations and yet stabilise aggregate community properties has remained largely untested. We examined population and community stability under constant and fluctuating temperatures in simple planktonic assemblages of differing algal richness. Temperature dependent resource competition produced a highly asymmetric community structure where algal community biomass was dominated by one species. For a given level of species richness, temperature fluctuations induced lower community covariance and thus stabilised community biomass. However, increasing algal species richness increased the variability of population abundance and growth rates, as well as population and community variability. Consumer dynamics were directly destabilised by environmental fluctuations. These results confirm recent theoretical studies suggesting a stabilising effect of environmental fluctuations at the community level. However, they also support the theoretical prediction that increasing species richness may be of limited value for community stability, most especially in asymmetric communities, when competition directly affects population variability.

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 score0.021
Threshold uncertainty score0.198

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 studies0.0000.000
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 head0.009
GPT teacher head0.231
Teacher spread0.222 · 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

Citations103
Published2004
Admission routes1
Has abstractyes

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