Host and tissue variations overshadow the response of boreal moss‐associated fungal communities to increased nitrogen load
Bibliographic record
Abstract
Human activity has more than doubled the amount of nitrogen entering the global nitrogen cycle, and the boreal forest biome is a nitrogen-limited ecosystem sensitive to nitrogen load perturbation. Although bryophyte-associated microbes contribute significantly to boreal forest ecosystem function, particularly in carbon and nitrogen cycling, little is known about their responses to anthropogenic global change. Amplicon pyrosequencing of the ITS2 region of rDNA was used to investigate how fungal communities associated with three bryophyte species responded to increased nitrogen loads in a long-term fertilization experiment in a boreal Picea abies forest in southern Norway. Overall, OTU richness, community composition and the relative abundance of specific ecological guilds were primarily influenced by host species identity and tissue type. Although not the primary factor affecting fungal communities, nitrogen addition did impact the abundance of specific guilds of fungi and the resulting overall community composition. Increased nitrogen loads decreased ectomycorrhizal abundance, with Amphinema, Cortinarius, Russula and Tylospora OTUs responding negatively to fertilization. Pathogen abundance increased with fertilization, particularly in the moss pathogen Eocronartium. Saprophytic fungi were both positively and negatively impacted by the nitrogen addition, indicating a complex community level response. The overshadowing of the effects of increased nitrogen loads by variation related to host and tissue type highlights the complexity of bryophyte-associated microbial communities and the intricate nature of their responses to anthropogenic global change.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".