Evolutionary, ecological, and anthropogenic drivers of phenotypic diversity in ants
Bibliographic record
Abstract
The drivers of phenotypic diversity have puzzled humanity for centuries. Functional trait approaches have helped advance the mechanistic understanding of the diversity of life forms. Previous work has shown that evolutionary history and environmental adaptation contribute to the observed diversity of phenotypes. However, most of our understanding comes from plants and studies that often neglect the influence of intraspecific variability. My thesis aims to investigate the drivers of phenotypic diversity across organizational levels using ants as study organisms. In Chapter 2, I examined the influence of evolutionary and environmental heterogeneity on the phenotypic diversity of ant lineages. I found a negative relationship between the diversity of climates occupied by ant genera and their phenotypic integration. This indicates that phenotypic integration may limit ant phenotypic diversification into new climatic zones. For Chapter 3, I examined geographic variation in community-wide patterns of phenotypic diversity, at different organizational levels (i.e., worker, colony, and species), along a 9° latitude gradient in Quebec, Canada. The results suggest that stressful environmental conditions typical of northern ecosystems exert a strong selection pressure on ant morphology causing shifts in optimal trait values of antennae length and eye size. Specifically, I found that shorter antennae and larger eyes possibly represent adaptations to cold, dry, and open habitats. In Chapter 4, I evaluated the impact of coffee plantation management practices on community-wide patterns of ant phenotypic diversity and composition. I found that intensified monocultures harbored phenotypically distinct ant communities. Moreover, community-wide phenotypic composition was more homogeneous in intensified plantations than in nearby forest patches or shade-grown plantations. This indicates that shade-grown strategies in coffee plantations buffer the impoverishment of ant phenotypic diversity following forest conversion, which could help preserve ecosystem services provided by ants. Overall, my thesis suggests that ant phenotypic diversity patterns are limited by phenotypic integration, vary among organizational levels (worker, colony, and species), and are influenced by anthropogenic disturbance across facets (taxonomic, phylogenetic, and functional). These findings have important implications for understanding how phenotypically complex organisms respond to climate change and provide guidance for conservation strategies targeting vulnerable lineages.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".