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Record W2056616882 · doi:10.1086/504603

Scale, Environment, and Trophic Status: The Context Dependency of Community Saturation in Rocky Intertidal Communities

2006· article· en· W2056616882 on OpenAlexaff
Roly Russell, Spencer A. Wood, Gary W. Allison, Bruce A. Menge

Bibliographic record

VenueThe American Naturalist · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSpecies richnessIntertidal zoneEcologyHabitatSpatial ecologyGeographyTrophic levelCommunity structureContext (archaeology)CommunityIntertidal ecologyBiology

Abstract

fetched live from OpenAlex

Our understanding of the relative influence of different ecological drivers on the number of species in a place remains limited. Assessing the relative influence of local ecological interactions versus regional species pools on local species richness should help bridge this conceptual gap. Plots of local species richness versus regional species pools have been used to address this question, yet after an active quarter-century of research on the relative influence of local interactions versus regional species pools, consensus remains elusive. We propose a conceptual framework that incorporates spatial scale and ecological interaction strength to reconcile current disparities. We then test this framework using a survey of marine rocky intertidal algal and invertebrate communities from the northeast Pacific. We reach two main conclusions. First, these data show that the power of regional species pools to predict local richness disintegrates at small spatial scales coincident with the scale of biological interactions, when studying ecologically interactive groups of species, and in generally more abiotically stressful habitats (e.g., the high intertidal). Second, conclusions of past studies asserting that the regional species pool is the primary driver of local species richness may be artifacts of large spatial scales or ecologically noninteractive groups of species.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.419

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 studies0.0000.001
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 head0.010
GPT teacher head0.200
Teacher spread0.190 · 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

Citations57
Published2006
Admission routes1
Has abstractyes

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