Context-dependent dispersal determines relatedness and genetic structure in a patchy amphibian population
Bibliographic record
Abstract
Dispersal is a central process in ecology and evolution with far reaching consequences for the dynamics and genetics of spatially structured populations (SSPs). Individuals can adjust their decisions to disperse according to local fitness prospects, resulting in context-dependent dispersal. By determining dispersal rate, distance, and direction, these individual-level decisions further modulate the demography, relatedness, and genetic structure of SSPs. Here, we examined how context-dependent dispersal influences the dynamics and genetics of a Great Crested Newt (Triturus cristatus) SSP. We collected capture-recapture data of 5564 individuals and genetic data of 950 individuals across a SSP in northern Germany. We added genetic data from six sites outside this SSP to assess genetic structure and gene flow at a regional level. Dispersal rates within the SSP were high but dispersal distances were short. Dispersal was context-dependent: individuals preferentially immigrated into high-quality ponds where breeding probabilities were higher. The studied SSP behaved like a patchy population, where subpopulations at each pond were demographically interdependent. High context-dependent dispersal led to weak but significant spatial genetic structure and relatedness within the SSP. At the regional level, a strong hierarchical genetic structure with very few first-generation migrants as well as low effective dispersal rates suggest the presence of independent demographic units. Overall, our study highlights the importance of habitat quality for driving context-dependent dispersal and therefore demography and genetic structure in SSPs. Limited capacity for long-distance dispersal seems to increase genetic structure within a population and leads to demographic isolation in anthropogenic landscapes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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 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".