Drivers of contrasting boreal understory vegetation in coniferous and broadleaf deciduous alternative states
Bibliographic record
Abstract
Abstract Alternative states defined by tree‐canopy dominance result in different ecosystem functioning and shape habitat conditions for the understory vegetation. One example in the boreal forest is the alternation between broadleaf deciduous and coniferous forests. Disturbances related to natural fires and human land uses have produced changes in tree‐canopy dominance in the boreal region where coniferous forests change to broadleaved forests, affecting understory community dynamics and their related ecosystem processes and functions. To analyze the factors driving changes in understory vegetation and the resistance of its vegetation to shifts between alternative states, we compared the effects of changes in the system between two contrasting boreal forest types (black spruce vs. trembling aspen) in adjacent stands with similar topoedaphic conditions. We performed a 5‐year in situ experiment using alternative states as a theoretical framework including two approaches: (1) the ecosystem approach, manipulating environmental conditions of light, litter, and nutrients in each forest type to determine the main mechanisms associated with tree‐canopy dominance that affect the diversity and composition of understory communities; and (2) the community approach, physically exchanging understory communities between alternative states, to determine their resistance under a new tree‐canopy dominance through time, as well as the resilience of the forest understory after a small‐scale disturbance. Results indicate that the understory vegetation of trembling aspen forests were resistant through time both after changes in local conditions in the ecosystem approach and in the new black spruce‐dominated alternative state in the community approach. In contrast, mosses and ericaceous plants that typically dominate the forest floor of black spruce forests were negatively affected by the physical effect of broadleaf litter addition in our ecosystem approach and they were not resistant when transplanted to trembling aspen forests in the community approach, as they decreased in abundance and were invaded by aspen understory community species over time. The understory vegetation is a key forest ecosystem driver that can contribute to maintain the resilience of the boreal system and help to preserve their ecosystem services, which is a key aspect to consider in forest management faced with the effects of climate change.
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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 | 0.001 |
| 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".