Determinants and consequences of dispersal in vertebrates with complex life cycles: a review of pond-breeding amphibians
Bibliographic record
Abstract
Dispersal is a central process in ecology and evolution. It strongly influences the dynamics of spatially structured populations, by affecting population growth rate and local colonization-extinction processes. Dispersal can also influence evolutionary processes because it determines rates and patterns of gene flow in spatially structured populations and is closely linked to local adaptation. For these reasons, dispersal has received considerable attention from ecologists and evolutionary biologists. However, although it has been studied extensively in taxa such as birds and mammals, much less is known about dispersal in vertebrates with complex life cycles such as pond-breeding amphibians. Over the past two decades, researchers have taken an interest in amphibian dispersal and initiated both fundamental and applied studies, using a broad range of experimental and observational approaches. This body of research reveals complex dispersal patterns, causations and syndromes, with dramatic consequences for the demography and genetics of amphibian populations. In this review, our goals are to (1) redefine and clarify the concept of amphibian dispersal, (2) review current knowledge about the effects of individual (i.e., condition-dependent dispersal) and environmental (i.e., context-dependent dispersal) factors during the three stages of dispersal (i.e., emigration, immigration, transience), (3) identify the demographic and genetic consequences of dispersal in spatially structured amphibian populations, and (4) propose new research avenues to extend our understanding of amphibian dispersal. In particular, we emphasize the need to (1) quantify dispersal rate and distance rigorously using suitable model systems, (2) investigate the genetic basis and dispersal evolution patterns, and (3) examine dispersal-related eco-evolutionary dynamics. These proposed research avenues tap from the recent advances in quantitative and molecular methods and have the potential to improve our understanding of dispersal in organisms with complex life cycles.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".