To go or not to go: variable density-dependent dispersal in small mammals
Bibliographic record
Abstract
Abstract Population density has been widely understood to be a key influencer of dispersal behavior; however, the generality of density-dependent (DD) dispersal in vertebrates is unclear. We conducted a review of the available empirical data on small mammal DD dispersal, distinguishing between the three dispersal stages: emigration, immigration, and transience (dispersal distance). We focused on small mammals because they are a well-studied, functionally similar group of vertebrates, with a distinct ecological importance. We also examined the effect of season, body mass, study length, and study type on the strength and direction of DD dispersal. The majority of emigration and dispersal distance studies reported negative density dependence, while immigration was mostly independent of density. No correlative patterns were detected; however, interpretation of the available data was hindered by inconsistencies in experimental and analytical approach across studies. Our results suggest that the three phases of the dispersal process may be influenced differently by density and highlight the importance of distinguishing between emigration, immigration, and transience when considering the effects of density dependence. As well, our study identifies several limitations with the current available data which limit the ability to compare DD dispersal behavior across systems, and calls for future investigations that consider all three phases of dispersal in the same system.
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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 | 0.001 | 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 | 0.000 | 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) | 0.007 | 0.001 |
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".