Voles looking for an edge: habitat selection across forest ecotones
Bibliographic record
Abstract
We searched for the presence of "edge effects" in the occupation of adjacent boreal-forest habitats by red-backed voles (Clethrionomys gapperi). First, we reviewed four models that differ in their predictions of abundance at habitat boundaries. Three of the models predicted an edge effect, while the so-called matrix or habitat model served as a null expectation. We then developed a protocol to detect, objectively, the ecotone between two habitats that is necessary to differentiate among the four models. The protocol revealed both abrupt and gradual ecotones along transects crossing conifer to cutover and conifer to deciduous habitats. Though vole density was almost always higher on one side of the ecotone than on the other, we were unable to detect an edge effect of any kind. Vole density within ecotones was intermediate to that on each side (refuting the existence of an ecotone effect). There were also no differences in the pattern of density between abrupt and gradual ecotones (refuting the existence of a permeability effect), and no consistent pattern of vole density away from either type of ecotone (refuting the existence of a habitat-selection effect). Simulations that manipulated vole densities along the transects suggested, however, that the habitats may have been too similar to allow a habitat-selection effect to be detected. We suspect that our result will be common to moderately generalised species, and we recommend that controlled experiments be carried out to evaluate the conditions under which habitat-selecting species may exhibit edge effects.
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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 | 0.001 | 0.002 |
| 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 | 0.000 | 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".