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Record W2799075107 · doi:10.1126/sciadv.aau4403

Seed predation increases from the Arctic to the Equator and from high to low elevations

2019· article· en· W2799075107 on OpenAlexafffund
Anna L. Hargreaves, Esteban Suárez, Klaus Mehltreter, Isla H. Myers‐Smith, Sula Vanderplank, Heather L. Slinn, Yalma L. Vargas‐Rodriguez, Sybille Haeussler, Santiago David, Jenny Muñoz, R. Carlos Almazán-Núñez, Deirdre Loughnan, John W. Benning, David A. Moeller, Jedediah F. Brodie, Haydn J. D. Thomas, Paula Andrea Morales-Morales

Bibliographic record

VenueScience Advances · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsCanada's Michael Smith Genome Sciences CentreMcGill UniversityUniversity of British Columbia
FundersUniversity of British ColumbiaNatural Environment Research CouncilSight Research UKSan Diego Natural History MuseumNational Science Foundation
KeywordsEcotonePredationEcologyBiodiversityEcosystemProductivityBiologyLatitudeInvertebrateArcticEquatorTropical climateTropicsGeographyHabitat

Abstract

fetched live from OpenAlex

Species interactions have long been predicted to increase in intensity toward the tropics and low elevations because of gradients in climate, productivity, or biodiversity. Despite their importance for understanding global ecological and evolutionary processes, plant-animal interaction gradients are particularly difficult to test systematically across large geographic gradients, and evidence from smaller, disparate studies is inconclusive. By systematically measuring postdispersal seed predation using 6995 standardized seed depots along 18 mountains in the Pacific cordillera, we found that seed predation increases by 17% from the Arctic to the Equator and by 17% from 4000 meters above sea level to sea level. Clines in total predation, likely driven by invertebrates, were consistent across treeline ecotones and within continuous forest and were better explained by climate seasonality than by productivity, biodiversity, or latitude. These results suggest that species interactions play predictably greater ecological and evolutionary roles in tropical, lowland, and other less seasonal ecosystems.

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 score0.018
Threshold uncertainty score0.922

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.005
GPT teacher head0.231
Teacher spread0.226 · 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

Citations94
Published2019
Admission routes2
Has abstractyes

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