The role of mosses in ecosystem succession and function in Alaska’s boreal forestThis article is one of a selection of papers from The Dynamics of Change in Alaska’s Boreal Forests: Resilience and Vulnerability in Response to Climate Warming.
Bibliographic record
Abstract
Shifts in moss communities may affect the resilience of boreal ecosystems to a changing climate because of the role of moss species in regulating soil climate and biogeochemical cycling. Here, we use long-term data analysis and literature synthesis to examine the role of moss in ecosystem succession, productivity, and decomposition. In Alaskan forests, moss abundance showed a unimodal distribution with time since fire, peaking 30–70 years post-fire. We found no evidence of mosses compensating for low vascular productivity in low-fertility sites at large scales, although a trade-off between moss and vascular productivity was evident in intermediate-productivity sites. Mosses contributed 48% and 20% of wetland and upland productivity, respectively, but produced tissue that decomposed more slowly than both nonwoody and woody vascular tissues. Increasing fire frequency in Alaska is likely to favor feather moss proliferation and decrease Sphagnum abundance, which will reduce soil moisture retention and decrease peat accumulation, likely leading to deeper burning during wildfire and accelerated permafrost thaw. The roles of moss traits in regulating key aspects of boreal performance (ecosystem N supply, C sequestration, permafrost stability, and fire severity) represent critical areas for understanding the resilience of Alaska’s boreal forest region under changing climate and disturbance regimes.
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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 | 0.005 | 0.001 |
| 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".