Mammalian dispersal behaviour and its fitness correlates
Bibliographic record
Abstract
This thesis is an investigation of the factors influencing the decisions made by juveniles during the three phases of dispersal: departure from the natal area, search and settlement. I used literature data on gregarious and solitary territorial mammals to test whether changes in mortality risk during dispersal and density influenced the probability of leaving the natal area. In gregarious mammals, dispersal probability remained constant with changes in mortality risk and increased with density. These results suggested that increased reproductive success might compensate for high disperser mortality when group membership in the natal area exceeded optimal group sizes among gregarious species. In solitary mammals, the decision to leave the natal area appeared to depend on the fitness costs to dispersal. Few juveniles dispersed when the mortality risk during dispersal was high and when conspecific density was high and competition for territorial sites outside the natal area, presumably, intense. Next, I examined the effect of mortality risk on search and settlement in the solitary, territorial American marten ('Martes americana'). I compared dispersal between a landscape composed of young, regenerating forests, hypothesized to represent suboptimal marten habitat, and an uncut landscape composed of mature, old-growth forests. Juveniles from the regenerating landscape dispersed shorter distances and travelled more slowly than juveniles from the uncut landscape. A more detailed analysis revealed that the accumulation of mortality risk with increasing dispersal distance was two times higher in the regenerating versus uncut landscape. Differences in body condition, supported by previous studies of hunting efficiency, suggested that juveniles from the regenerating landscape were less capable of coping with the energetic demands of dispersal compared to juveniles from the uncut landscape. Neither dispersal cost, nor adult despotism appeared to influence patterns of juvenile settlement. Most juveniles settled <=1 km from their capture location and occupied home ranges of similar quality to adults. The proportional increase in home range size with body mass suggested that juvenile settled in areas to satisfy their energetic requirements. This is the first study to quantify the effect of mortality risk on natal dispersal behaviour among territorial solitary mammals and, in particular, juvenile marten.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".