Changes in relative abundance of snowshoe hares (<i>Lepus americanus</i>) across a 265-year gradient of boreal forest succession
Bibliographic record
Abstract
Understory regeneration within canopy gaps in old-growth boreal forests may provide suitable habitat for wildlife typically associated with early-seral stages, leading to an increase in their abundance in late succession. We surveyed a chronosequence of postfire (17–265 years) and postharvest (3–63 years) stands in Canada’s eastern boreal forest to determine whether snowshoe hares ( Lepus americanus Erxleben, 1777) followed a bimodal abundance distribution with stand age that reflects changes in food and cover during postdisturbance succession. A strong peak in relative hare abundance occurred during the first 80 years of succession, with highest faecal pellet densities observed between 40 and 50 years after disturbance. Changes in hare abundance during this period were similar among fire- and clearcut-origin stands and closely tracked changes in lateral cover and vertical cover. Pellet density increased again in stands >180 years. Variation in hare abundance during late succession was partially mediated by gap dynamics, with highest pellet densities in stands occupied by an intermediate proportion of mortality-origin canopy gaps. Hares thus undergo rapid changes in abundance during early succession followed by a much longer period of subtle changes in density as stands develop old-growth structure. Shifting forest age-class distribution induced by forest management could therefore significantly alter regional spatiotemporal dynamics of snowshoe hares.
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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 | 0.000 |
| 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".