Factors affecting browsing by moose (<i>Alces alces</i>L. ) on European aspen (<i>Populus tremula</i>L.) in a managed boreal landscape
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There is considerable circumpolar concern regarding the regeneration of several tree species in the temperate and boreal landscape due to heavy browsing. We analyzed the risk of browsing on aspen (Populus tremula L.) at two different scales in a managed boreal forest in northern Sweden with one dominating browser in the system, the moose (Alces alces L.). At the stand level, we found that a high density of aspen ramets in connection to or surrounded by young forest (predominantly Scots pine Pinus sylvestris L.) attracted moose relatively more than aspen stands in mature forest and interior forest, respectively. If a stand was being used, a single aspen ramet faced the best chance of escaping browsing in a stand with a high density of aspen ramets, located far from arable land. This utilization pattern by the herbivores suggests that older forest may function as a temporal refuge for aspen regeneration in the managed boreal landscape, but this situation may change as remaining old forest stands eventually turn into young forest. Although cutting will favour aspen regeneration, our study highlights an apparent paradox, as the emerging aspen ramets will face a high browsing risk from attracted herbivores.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it