MétaCan
Menu
Back to cohort
Record W2174711265 · doi:10.1093/ee/nvv109

Postfire Succession of Ants (Hymenoptera: Formicidae) Nesting in Dead Wood of Northern Boreal Forest

2015· article· en· W2174711265 on OpenAlexafffund
Philippe Boucher, Christian Hébert, André Francoeur, Luc Sirois

Bibliographic record

VenueEnvironmental Entomology · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsNatural Resources CanadaCanadian Forest Service
FundersCanadian Forest Service
KeywordsChronosequenceEcological successionBiologyEcologyTaigaHymenopteraDead woodSnagAbundance (ecology)Dead treeNest (protein structural motif)BiodiversityHabitat

Abstract

fetched live from OpenAlex

Dead wood decomposition begins immediately after tree death and involves a large array of invertebrates. Ecological successions are still poorly known for saproxylic organisms, particularly in boreal forests. We investigated the use of dead wood as nesting sites for ants along a 60-yr postfire chronosequence in northeastern coniferous forests. We sampled a total of 1,625 pieces of dead wood, in which 263 ant nests were found. Overall, ant abundance increased during the first 30 yr after wildfire, and then declined. Leptothorax cf. canadensis Provancher, the most abundant species in our study, was absent during the first 2 yr postfire, but increased steadily until 30 yr after fire, whereas Myrmica alaskensis Wheeler, second in abundance, was found at all stages of succession in the chronosequence. Six other species were less frequently found, among which Camponotus herculeanus (Linné), Formica neorufibarbis Emery, and Formica aserva Forel were locally abundant, but more scarcely distributed. Dead wood lying on the ground and showing numerous woodborer holes had a higher probability of being colonized by ants. The C:N ratio was lower for dead wood colonized by ants than for noncolonized dead wood, showing that the continuous occupation of dead wood by ants influences the carbon and nitrogen dynamics of dead wood after wildfire in northern boreal forests.

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 score0.010
Threshold uncertainty score0.608

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 head0.017
GPT teacher head0.206
Teacher spread0.189 · 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

Citations13
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueEnvironmental EntomologySame topicForest Ecology and Biodiversity StudiesFrench-language works237,207