Data from: Positive relationships between association strength and phenotypic similarity characterize the assembly of mixed-species bird flocks worldwide
Bibliographic record
Abstract
Competition theory predicts that communities at small spatial scales should consist of species more dissimilar than expected by chance. We find a strikingly different pattern in a multi-continent dataset (55 presence-absence matrices from 24 locations) on the composition of mixed-species bird flocks, important subunits of local bird communities the world over. Using null models and randomization tests followed by meta-analysis, we find the association strength of species in flocks to be strongly related to similarity in body size and foraging behavior, and higher for congeneric compared with non-congeneric species pairs. Given the small spatial scale of our individual analyses, differences in habitat preferences of species are unlikely to have caused these association patterns; therefore, the patterns are most likely the outcome of species interactions. Extending group-living and social information use theory to a heterospecific context, we discuss potential behavioral mechanisms leading to positive interactions among similar species in flocks as well as ways in which competition costs are reduced. Our findings highlight the need to consider positive interactions along with competition when seeking to explain community assembly.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.014 |
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".