Indirect impacts of a non-native ungulate browser on soil ecosystem function is variable across soil horizons in the boreal forests of Newfoundland, Canada
Bibliographic record
Abstract
Herbivores are key players in ecosystem function and connect nutrient cycling across animal and plant trophic levels. Herbivore impacts on ecosystems can be direct or indirect and it is necessary to study both paths to understand herbivore impacts on above-ground and below-ground ecosystem functioning. We conducted an experiment to test the hypothesis that non-native moose on the island of Newfoundland have negative impacts on plant communities, nutrient cycling, soil composition, and soil organism communities. We collected data on plant and invertebrate communities, climate, and soils in 11 paired exclosure-control plots in eastern and central Newfoundland that provide insight into 22-25 years of moose herbivory. Structural equations models revealed that moose had direct negative impacts on palatable tree height and abundance and an indirect negative impact on soil microbial C:N ratios. We found that moose had a direct negative impact on soil horizon depth and plant material and a positive impact on soil temperature and moisture, particularly in the first soil horizon. We detected no significant impact of moose on soil total C and N, net nitrogen mineralization, or macro-invertebrate communities. Overall, we unearthed evidence of indirect cascading impacts of moose on soil functions although these impacts are relatively weak.
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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 | 0.000 |
| 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 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".