General and specific responses of understory vegetation to cervid herbivory across a range of boreal forests
Bibliographic record
Abstract
Understanding the responses of ecological communities to perturbation is a key challenge within contemporary ecology research. In this study we seek to separate specific community responses from general community responses of plant communities to exclusion of large cervid herbivores. Cervid herbivory and forestry are the main drivers of vegetation structure and diversity in boreal forests. While many studies focus on the impact of cervids on trees, a high proportion of the biodiversity and ecosystem services in boreal forests is found in the field layer. However, experimental approaches investigating the influence of herbivory on understory vegetation are highly localised. In this study we use a regional‐scale design with 51 sites in four boreal forest regions of Norway, to investigate the influence of cervid herbivory on the physical and ecological structure of field layer vegetation. Our study sites cover a range of forest types differing in productivity, management and dominant cervid species, allowing us to identify generic responses and those that are specific to particular conditions. We found that the height of the field layer and the abundances of individual species were most susceptible to change following short‐term cervid exclusion across different forest types and cervid species. Total vegetation density and vascular plant diversity did not respond to cervid exclusion on the same time scale. We also found that the field‐layer vegetation in clear‐cut forests used by moose was more susceptible to change following cervid exclusion than mature forests used by red deer, but no strong evidence that the response of vegetation to herbivore exclusion varied with productivity. Our study suggests that the parameters that respond to cervid exclusion are consistent across forest types, but that the responsiveness of different forest types is idiosyncratic and hard to predict.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".