Movement ecology of amphibians: from individual migratory behaviour to spatially structured populations in heterogeneous landscapes<sup>,</sup>
Bibliographic record
Abstract
Both genetic cohesion among local populations of animals and range expansion depend on the frequency of dispersers moving at an interpatch scale. Animal movement has an individual component that reflects behaviour and an ecological component that reflects the spatial organization of populations. The total movement capacity of an individual describes maximum movement distance theoretically achievable during a lifetime, whereas its variation among the members of a local population determines the magnitude of interpatch movements and thus of gene flow between neighbouring patches within metapopulation or patchy population systems. Here, I review information on dispersal and migration as components of the movement capacity of juvenile and adult pond-breeding amphibians and discuss how these components inform the spatial structure of populations. Amphibians disperse as juveniles and adults, but movement distances detected in tracking or capture–mark–recapture studies are usually far below the corresponding estimates based on molecular gene-flow data. This discrepancy reflects the constraints of available tracking methods for free-ranging individuals leading to inappropriate surrogates of annual movement capacity, but can be resolved using probabilistic approaches based on dispersal functions. There is remarkable capacity for and plasticity in movements in amphibians. Annual within-patch movements (migrations) of individuals can be large and likely represent an underestimated capacity for movement at the interpatch scale. Landscape resistance may influence the paths of dispersing amphibians, but rarely impedes interpatch movements. Juveniles emigrating unpredictably far from the natal pond and adults switching from within-patch migrations to dispersal to another patch demonstrate the plasticity of individual movement behaviour. Three basic conclusions can be drawn with respect to the linkage of individual movement behaviour and spatial or genetic structure of local amphibian populations embedded in a heterogeneous landscape: (1) individual movements or consecutive short-term series of movements are misleading surrogate measures of total movement capacity; (2) probabilistic modelling of movement capacity is the best available behavioural predictor of interpatch gene flow; (3) connectivity of local populations in heterogeneous landscapes is less affected by landscape resistance than previously expected.
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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) | 0.000 | 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) | 0.002 | 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".