Do animal personalities promote species coexistence? <scp>A</scp> test with sympatric boreal rodents
Bibliographic record
Abstract
The coexistence of competing species requires density feedbacks that have a larger effect on their own species' population growth than they do on others in the assembly. The feedbacks are often associated with behavioral tradeoffs that enable species to differentially exploit underlying axes of heterogeneity. Conjoining theories of species coexistence with foraging behavior and density-dependent habitat selection reveals that such tradeoffs impinge on invasion probabilities and equilibrium dynamics emerging from species' differences in habitat use. The resulting habitat separation promotes coexistence by reducing the overall interaction among species. Differential habitat selection depends on the behavioral abilities of organisms to identify and exploit the most profitable habitats and resource patches. One might thus expect that each species will evolve behavioral types distinct from those of other potential competitors. Accordingly, we exposed four coexisting species in four genera of boreal rodents to open-field tests. We used principal components (PC) to summarize their behaviors along three independent axes corresponding with clines of exploratory, vigilant, and apprehensive personalities. We confirmed that the axes represented repeatable behaviors (personalities) and assessed differences among species with a general linear model (GLM). The GLM revealed highly distinct differences among species, and between pairs of species, on each PC. Even so, it is difficult to infer the adaptive advantages of personality to the habitat segregation that reduces otherwise high interactions among species. Rather, personalities are best interpreted as co-adaptive behaviors reflecting the complex of morphological, physiological and behavioral attributes that dictate tradeoffs and enable coexistence.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".