Environmental drivers of juvenile dispersal and adult non-breeding movements in <i>Ambystoma</i> salamanders
Bibliographic record
Abstract
Understanding the environmental drivers of species’ dispersal and migration patterns is needed to accurately predict climate change impacts on populations. For pond-breeding amphibians, adult movements associated with the breeding period are well studied but major gaps exist in our knowledge of the drivers of adult and juvenile non-breeding movements. Here, we assess environmental drivers of adult and juvenile Ambystoma maculatum (Shaw, 1802), Ambystoma jeffersonianum (Green, 1827), and their unisexual dependants’ ( Ambystoma laterale–jeffersonianum (Uzzell, 1964)) summer and fall non-breeding movements using data from pitfall trapping and radio telemetry tracking. We used generalized linear models to assess the influence of precipitation, minimum temperature, day of year, and days since last precipitation on salamander movements. Juvenile summer dispersal movements were related to days since last precipitation in Jefferson Salamander complex individuals and 24 h precipitation in Spotted Salamanders. Adult and juvenile fall movements were driven by minimum temperature, 24 h precipitation, and days since last precipitation, and the effect of these environmental factors varied slightly between species and between Jefferson bisexuals and unisexuals. Our work indicates that changes in both temperature and precipitation will likely impact non-breeding dispersal and migration in these species and, overall, improves our understanding of ecological patterns throughout their entire life cycle.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".