Functional responses in habitat use explain changes in animal–habitat interactions during forest succession
Bibliographic record
Abstract
The growing rate of resource extraction forces increasing numbers of late-seral species to occupy habitats that are in early stages of succession. Sustainable management must maintain habitat features that are required for recovery of these species, which may be challenging because their response to those features can vary following nonsystematic trends during stages of succession. We investigated whether simple movement rules could explain such variations by assessing how movements of a late-seral species, the red-backed vole (Myodes gapperi (Vigors, 1830)), vary during postlogging forest succession using the spool and line technique in recent cuts, mid-successional forests, and old-growth forests. We found that voles moved selectively along coarse woody material (CWM), and this selection was weaker in mid-successional forests. This change was best explained by a simple functional response, whereby voles selected CWM more strongly in stands where canopy cover availability was moderately high. Likewise, voles more rapidly left patches that had high canopy cover when it was less available in stands and tended to spend more time in patches with high CWM volumes. Our study demonstrates that the highly dynamic nature of animal–habitat relationships observed during forest succession can be summarized by a few simple functional responses in movement and habitat selection.
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 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 | 0.001 |
| 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".