Indirect effects of an ecosystem engineer: how the Canadian beaver can drive the reproduction of saproxylic beetles
Bibliographic record
Abstract
Abstract Environmental rearrangements by ecosystem engineers influence food‐web characteristics by altering resource accessibility/availability in the newly created habitat. However, the paucity of empirical studies on this indirect interaction has hindered the integration of ecosystem engineering and food‐web theory. Here, we investigated the effect of the Canadian beaverCastor canadensison the activity, realized fecundity and ecosystem functions provided by saproxylic beetles by quantifying beetle emergence holes on woody debris within the Kouchibouguac National Park, New Brunswick, Canada. We tested the hypothesis that perturbation induced by beaver activity enhances the activity and realized fecundity of saproxylic beetles by modifying their habitat and resource accessibility. We used 16 sites identified as beaver modified, each paired with a control site <500 m away. At each site, we quantified insect emergence holes on snags at increasing distances from the watercourse. Our results suggest that engineered habitat patches enhance the activity and reproduction of saproxylic beetle species, small emergence holes from Scolytinae being only observed in abundance on small trees located close to the watercourse and large emergence holes from Cerambycidae being one third more abundant throughout beaver‐modified sites. The complementary relationship between the Canadian beaver and saproxylic beetles demonstrates the potential for conservation measures encapsulating all of these organisms.
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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 | 0.001 | 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".