Simultaneous influence of canopy decline and deer herbivory on regeneration in a conifer–broadleaf forest
Bibliographic record
Abstract
Understanding how forests respond to multiple disturbances is becoming increasingly important under global change. We examined the simultaneous influence of canopy decline and deer browsing on regeneration in an old-growth reserve and surrounding managed forest dominated by Fagus sylvatica L. and Abies alba Mill. in Slovenia. We quantified both disturbance processes by measuring characteristics of canopy gaps and reconstructing historical deer densities. Forest response was assessed with repeated measurements of tree regeneration and regeneration patterns within deer exclosures. Most gaps were formed by mortality of A. alba (71%), and gapmaker characteristics suggest that gaps formed slowly and often expanded, resulting in a mosaic of openings covering 17% of the old-growth reserve. Fagus sylvatica dominated the regeneration layer throughout the reserve and recruited to taller height classes over the past 26 years. The recruitment failure of preferred browse species (A. alba and Acer pseudoplatanus L.) in the reserve and the successful recruitment of these species within exclosures indicate that selective browsing by deer has altered the successional response to A. alba decline, facilitating the dominance of F. sylvatica. Given that global change may increase forest decline worldwide and the ubiquitous nature of deer browsing in many temperate forests, understanding their combined effects on forests will become increasingly important.
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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 | 0.000 | 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) | 0.000 | 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".