The role of eastern spruce dwarf mistletoe in stand dynamics of lowland black spruce forests in Minnesota, USA
Bibliographic record
Abstract
In many forests, low to moderate severity disturbances exert significant influence on the development of forest structure and species composition over time and are important components of stand dynamics. Here, we investigated the effects of eastern spruce dwarf mistletoe ( Arceuthobium pusillum, hereafter ESDM) on stand structure and composition of peatland black spruce ( Picea mariana) forests in northern Minnesota, USA, to better understand the role of this native, biotic disturbance agent on stand dynamics in the region. Conditions in three uninfested black spruce stands and three ESDM-caused mortality centers were sampled and differences in forest structure, composition, and spatial arrangement were quantified. We found an increase in species richness and structural diversity as well as a shift in diameter distribution in post-mortality forests—showing ESDM to be a driver of stand dynamics and a source of structural complexity in peatland forests. Our results illuminate patterns of species composition found in peatland forests and can help develop novel, ecologically-based silvicultural approaches for black spruce. Additionally, with many disturbances influencing ecosystems, our results highlight the importance of including non-stand-replacing disturbances in our understanding of stand development.
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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".