Niche filtering rather than partitioning shapes the structure of temperate forest ant communities
Bibliographic record
Abstract
An ever-increasing number of studies use tools from community phylogenetics to infer the processes underlying the assembly of communities. However, very few studies simultaneously use experimental approaches to characterize the ecological niches of species and directly assess the importance of these structuring processes. In this study, we developed an experimental approach for quantifying the use of four types of food resources and three habitat templets in temperate forest ant assemblages. We then used null models to assess whether niches overlapped more or less than expected by chance. Finally, we integrated comparative phylogenetic methods with experimental data on niche use to assess the degree of phylogenetic signal in several key components of the niche. We found that niche filtering, rather than partitioning, was the predominant structuring force. Niche filtering resulted from conservatism in habitat niches in evolutionary time and limitations in the availability of food resources in ecological time. Our study thus supports the idea that similarities in niches among species, rather than the differences, drive the assembly of ant communities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".