Natal dispersal in a social landscape: Considering individual behavioral phenotypes and social environment in dispersal ecology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Natal dispersal, the movement of an organism from its birthplace to the site of first reproduction, is fundamental to many ecological and evolutionary processes. Mechanistically, individual dispersal decisions can depend on both individual phenotype and environmental cues. In particular, many established evolutionary theories of dispersal highlight the importance of the social environment. More recent research in behavioral ecology has focused on the importance of individual behavioral phenotypes. We reviewed the literature on individual behavioral phenotypes and dispersal and suggest that how individual behavioral phenotypes interact with the immediate social environment experienced by individuals in influencing dispersal is still poorly understood, despite growing interest. We found that very few studies had examined the interaction of individual behavioral phenotypes and social factors, and behavioral phenotypes related to social tendencies were less commonly measured than were behavioral phenotypes related to exploration or response to risk. Further, and unsurprisingly, studies on social behavioral phenotypes and dispersal behaviors during the transience stage of dispersal were underrepresented compared to the departure or settlement stages. Future studies in this area should aim to: a) make explicit links between behavioral traits and their proposed effects on dispersal decisions throughout multiple stages of dispersal, b) integrate more continuous dispersal variables, and c) consider the effects of the spatial distribution and phenotypes of conspecifics (i.e., the social landscape) encountered by individual dispersers.
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.
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 | 0.000 | 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) | 0.000 | 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 it