Bibliographic record
Abstract
An animal's capacity to recolonize a patch depends on at least two components: its ability to detect the patch and its ability to reach it. However, the disruption of such processes by anthropic disturbances could explain low animal abundance patterns observed by many investigators in certain landscapes. Through field experiments, we compared the orientation and homing success of northern green frogs (Rana clamitans melanota Rafinesque, 1820) and northern leopard frogs (Rana pipiens Schreber, 1782) translocated across disturbed or undisturbed surfaces. We also monitored the path selected by individuals when presented with a choice between a short distance over a disturbed surface and a longer, undisturbed route. Finally, we measured the water loss and behaviour of frogs on substrates resulting from anthropogenic disturbances and a control. When presented with a choice, 72% of the frogs avoided disturbed surfaces. Although able to orient towards the pond of capture when translocated on disturbed surfaces, frogs had a lower probability of homing successfully to the pond than when translocated at a similar distance on an undisturbed surface. Frogs lost the most water on substrates associated with disturbance and in the absence of cover. Our data illustrate that anthropically disturbed areas devoid of cover, such as mined peatlands and agricultural fields, disrupt the ability of frogs to reach habitat patches and are likely explanations to their reduced abundance patterns in such environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.007 | 0.001 |
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; both teacher heads agree on what is shown here.
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".