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Record W2097919457 · doi:10.1093/jpe/rtr035

Large-scale spatial synchrony and the stability of forest biodiversity revisited

2012· article· en· W2097919457 on OpenAlexaboutno aff
Annette Ostling

Bibliographic record

VenueJournal of Plant Ecology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiological dispersalEcologyNull hypothesisNull modelNeutral theory of molecular evolutionBiodiversitySpatial ecologyScale (ratio)Stability (learning theory)Spatial distributionGeographyBiologyEconometricsComputer scienceMathematicsCartographyRemote sensingMachine learningPopulation

Abstract

fetched live from OpenAlex

AimsMechanisms contributing to species coexistence have at least one of two modes of action: (i) stabilization of populations through restoring forces and (ii) equalization of fitness across individuals of different species. Recently, ecologists have begun gleaning the relative roles of these by testing the predictions of neutral theory, which predicts the properties of communities under pure fitness equalization. This null hypothesis was rejected for forests of southern Ontario based on large-scale (∼100 km) spatial synchrony evident in the fossil pollen record over the entire Holocene, and the argument that a species' relative abundance would instead vary independently at such distances in the absence of stabilizing mechanisms. This test of neutral theory was criticized based on the idea that the synchrony might be produced by dispersal alone. Here, I revisit this test of neutral theory by explicitly calculating the synchrony expected in these forests using a novel simulation method enabling examination of the distribution of a species over large spatial and temporal scales.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score1.000

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)0.0010.000

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 head0.012
GPT teacher head0.215
Teacher spread0.203 · 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.

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

Citations10
Published2012
Admission routes1
Has abstractyes

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