Decomposition and nutrient release from four epiphytic lichen litters in sub-boreal spruce forests
Bibliographic record
Abstract
Epiphytic lichens are highly abundant in many sub-boreal forests and may be important components of nutrient cycling. Decomposition of, and nutrient release from, two cyanolichens (with N 2 -fixing cyanobacterial partners) and two chlorolichens (with green-algal partners) were quantified to estimate N inputs from epiphytic lichen litter in late-seral forests. Initial decay rates were strongly correlated with initial %N; the high-N cyanolichen litters ( Nephroma helveticum Ach. and Lobaria pulmonaria (L.) Hoffm.) lost 26% more mass than the lower-N chlorolichen litters ( Alectoria sarmentosa (Ach.) Ach. and Platismatia glauca (L.) W.L. Culb. & C.F. Culb.) over the first 4 months. Morphological characteristics also influenced decay, as decomposition of the hair chlorolichen (A. sarmentosa) was similar to that of the foliose cyanolichens, despite an N concentration that was 87% lower. N was immediately released from cyanolichen litters and retained in chlorolichen litters. After 24 months of decay, N concentrations remained highly divergent with 22–27 and 7–8 mg N·g –1 in cyanolichen and chlorolichen litter, respectively. Cyanolichen litter represents 0.1%–2.3% of the total aboveground litter biomass and 0.5%–11.5% of the total N input from aboveground litterfall. Decomposition of cyanolichen litter is estimated to release up to 2.1 kg N·ha –1 ·year –1 of newly fixed N that would otherwise be unavailable in mature sub-boreal forests.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".