Drivers of elemental storage and cycling in boreal forests: evaluating the effects \nof forest disturbances and an introduced ungulate
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
Selective browsing by ungulates alters forest structure and composition with the potential to \nsuppress forest regeneration. Research suggests that ungulate impacts may be stronger in \nrecently disturbed forests and in novel environments (i.e., introduced ungulates). In this thesis, \nwe used observational and experimental (i.e., paired exclosure-controls) data to test the \nhypothesis that non-native moose and forest disturbances (i.e., fires and insect outbreaks) have \nnegative impacts on carbon storage (i.e., total, aboveground, and belowground carbon) and plantavailable \nnitrogen in Newfoundland’s boreal forests. Using our observational data, we found that \nforest disturbances were a key driver of carbon storage dynamics, but we did not find a \nrelationship between moose densities and carbon storage. We also found that supply rate of \nammonium was negatively correlated with soil temperature and positively correlated with moose \ndensity. Using our experimental data, we did not detect any effect of disturbance history or \nmoose presence on carbon storage or ammonium supply rates after 24-27 years of moose \nexclusion. This work demonstrates the impacts of natural disturbances and herbivory on forest \necosystem functions, such as carbon sequestration. Our findings will help natural resource \nmanagers consider the effects of moose and disturbances when developing nature-based \nsolutions to climate change.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it