Functional trait dissimilarity drives arboreal ant community assembly while competitive trait hierarchies shape colony performance in experimental mesocosms
Bibliographic record
Abstract
Abstract Many broad‐scale studies along spatial and habitat gradients show that organisms' traits can strongly influence community assembly by facilitating dispersal and environmental filtering. Nonetheless, how traits structure local faunal communities within habitats remains poorly understood. In particular, the often‐assumed role of traits in affecting the outcome of competition among animal species is rarely tested. We coupled a field study with a mesocosm experiment to explore how arboreal ant species' traits shaped competition and community structure, leveraging a small mangrove ecosystem which conceivably imposed minimal dispersal and environmental filtering effects on ant community assembly. We first surveyed the ant communities inhabiting 115 mangrove trees using >2000 carbohydrate and protein baits, and measured multiple morphological, physiological (critical thermal maximum) and dietary (stable isotope trophic position) traits of all ant species. We then coupled co‐occurrence network analyses with meta‐analytical models to uncover the trait‐based mechanisms structuring species co‐occurrences in the field. Finally, in a mesocosm experiment, we reared 87 colonies of eight ant species from the mangrove over 30 days under different competition treatments to investigate trait‐mediated effects of competition on ant colony performance. Patterns of ant species co‐occurrences and bait recruitment indicated strong competition for limited protein‐rich resources. Accordingly, dissimilarities in three traits—eye size, pronotum width and antennal scape length—consistently explained species co‐occurrences, suggesting that the communities were competitively assembled by a partitioning of resource acquisition strategies among species. Species co‐occurrences were also, to a lesser extent, explained by similarities in critical thermal limits, suggesting mild environmental filtering. In the mesocosm experiment, increasing directional differences in eye size and pronotum width between neighbouring ant colonies exacerbated interspecific competitive effects on colony survival and growth. Our results empirically demonstrate that traits linked to resource acquisition shape both coexistence and exclusion in ants. More broadly, by contrasting field patterns of niche partitioning with experimentally measured competitive effects, we show that the same traits can underpin stabilising processes that promote coexistence through limiting similarity, or equalising processes that drive exclusion through hierarchical differences, with their relative importance shifting across spatial scales and environmental contexts. Read the free Plain Language Summary for this article on the Journal blog.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".