Forest Composition Drives Bryophyte Biomass, Carbon, and Nitrogen Storage in the Boreal‐Temperate Ecotone
Bibliographic record
Abstract
ABSTRACT Background Climate change and forest management have profoundly altered forest ecosystem dynamics, with impacts on canopy composition and understory vegetation. Forest type affects bryophyte ecosystem processes, particularly related to carbon (C) and nitrogen (N) cycling. Within the boreal‐temperate ecotone, the Wabanaki‐Acadian Forest harbors a diverse canopy composition with many species at their distributional limit, making it sensitive to climate change and human alterations, with unknown impacts on bryophytes and their functions. Aims We aimed to quantify how canopy composition and moisture affect forest‐floor bryophyte biomass, and C and N stocks. Location We sampled in 49 stands representing six forest types of the Wabanaki‐Acadian Forest of New Brunswick (Canada): mesic coniferous, wet coniferous, mesic deciduous, wet deciduous, mixed, and cedar forests. Methods First, we developed an allometric model to predict bryophyte bulk density. We then estimated bryophyte biomass and C and N contents for five functional groups at each site using the ground layer indicator method and measured forest and soil characteristics at each site (e.g., forest composition, soil pH, moisture class). Linear models; multivariate, similarity percentages; and indicator species analyses were used for data analysis. Results The highest bryophyte biomass and C and N stocks were found in conifer‐dominated forests, especially where Sphagnum was abundant, whereas they were low in mixed and deciduous forests which also had a different functional composition. There was a strong negative nonlinear relationship between bryophyte biomass and broadleaf litter. Conclusions We provide the first reports of bryophyte biomass and C and N stocks in the Wabanaki‐Acadian Forest, which were consistent with its latitudinal location at the southern edge of the boreal forest. Our findings highlight the connections between forest composition and bryophytes in the Acadian Forest and reveal the potential contribution of forest‐floor bryophytes to C and N stocks.
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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 | 0.001 | 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 | 0.000 | 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".