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Record W1974384865 · doi:10.2980/17-2-3335

Ant nest architecture and seed burial depth: Implications for seed fate and germination success in a myrmecochorous savanna shrub

2010· article· en· W1974384865 on OpenAlexvenueno aff
Delphine Renard, Bertrand Schatz, Doyle McKey

Bibliographic record

VenueEcoscience · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
Fundersnot available
KeywordsSeed dispersalGerminationNest (protein structural motif)BiologySeedlingBiological dispersalShrubEcologyBotanyPopulation

Abstract

fetched live from OpenAlex

Placement of seeds in favourable microsites by inhumation in ant nests is considered a principal advantage of myrmecochory. However, nest chambers may be too deep to allow seedling emergence. In this case, successful germination requires secondary transport of seeds to shallower sites. Little is known about the architecture of nests of seed-dispersing ants and the locations within nests to which seeds are initially transported. These data are essential to assess the importance of secondary transport for germination success of seeds. We studied dispersal of Manihot esculenta subsp. flabellifolia seeds by Ectatomma brunneum ants in French Guianan savannas. We followed movements of seeds within nests by offering marked diaspores to foraging workers, observing transport into the nest, then excavating to determine locations of marked seeds. In 4 nests, chambers ranged from 2 to 40 cm deep. Because elaiosomes are fed to brood, Manihot diaspores were initially transported to deep chambers, where brood was concentrated. Recovered diaspores had been carried to chambers 14–40 cm deep, all deeper than the maximum burial depth for emergence (= 13.8 cm) predicted from the mass (= 0.13 g) of Manihot seeds. Nest architecture thus makes secondary vertical transport of seeds crucial for dispersal success of this species. Failure of secondary transport may be an underestimated mortality factor in myrmecochorous plants.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score0.988

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 studies0.0000.000
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 head0.026
GPT teacher head0.243
Teacher spread0.217 · 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

Citations27
Published2010
Admission routes1
Has abstractyes

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