Conflicting effects of microhabitats on Long-toed Salamander (<i>Ambystoma</i> <i>macrodactylum</i>) movement: implications for landscape connectivity
Bibliographic record
Abstract
Understanding dispersal requires multiple lines of investigation, from the study of broad patterns of population connectivity to the identification of factors impacting movement at local scales. To determine the potential effects of different microhabitats on dispersal in the Long-toed Salamander (Ambystoma macrodactylum Baird, 1850), we experimentally evaluated mobility, moisture loss, and habitat choice in response to five common substrates (deciduous and coniferous leaf litter, grass, moss, and sand). Specifically, we examined differences in the efficiency with which salamanders moved across substrates when motivated to move. We then quantified moisture loss in each substrate and evaluated habitat preference. Our results point to a trade-off between substrates that are easily traversed and those that offer high protection against desiccation. Habitat choice appeared to balance these two aspects of performance, with salamanders favouring a substrate that offered both low resistance to movement and high protection against desiccation. This result was context-dependent, as preferences shifted towards wetter but less easily traversed substrates when supplemental cover objects were made available. Overall, our study highlights the potential for individuals to respond to a given substrate in ways that can both facilitate and limit dispersal and thus underscores the need to consider different aspects of individual performance and behaviour when studying population connectivity.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".