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Do leaf‐cutting ant nests make “bottom–up” gaps in neotropical rain forests?: a critical review of the evidence

2000· review· en· W2052335158 on OpenAlexaff
Farji‐Brener, Illes

Bibliographic record

VenueEcology Letters · 2000
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsAttaUnderstoryNest (protein structural motif)EcologyRainforestBiologyPlant ecologyTropicsProductivityAnt colonyPlant communityAgroforestryHymenopteraEcological successionCanopy

Abstract

fetched live from OpenAlex

We discuss the role of leaf cutting ant nests ( Atta sp.) on the formation of understory “bottom–up” gaps in tropical rain forests. We (i) describe the characteristics of Atta nests that qualify them as promoters of understory gaps; (ii) review the effects of Atta nests on the dynamics of systems other than tropical forests; and (iii) discuss the hypotheses that in neotropical rain forests Atta nests affect plant productivity, and also influence distribution and community composition of the flora. Finally, we discuss the importance of Atta nests in the dynamics of forests and compare their effects with the better‐known effects of treefall gaps. Atta nests modify soil structure, soil nutrient content, light intensity at ground level, seed bank composition and understory structure. The presence of the nest and associated refuse also accelerates the soil nutrient cycles. The size, high frequency, turnover rate and duration of these nests could make them a good substrate for particular species of plants. In spite of their potential importance, little information exists on the effects of Atta nests on plant productivity and/or plant composition in neotropical rain 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.939
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.097
GPT teacher head0.312
Teacher spread0.216 · 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 designOther design
Domainnot available
GenreReview

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

Citations100
Published2000
Admission routes1
Has abstractyes

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