Inconsistent effects of nitrogen canopy enrichment and soil warming on black spruce epiphytic phyllosphere bacterial communities, taxa, and functions
Bibliographic record
Abstract
Phyllosphere microbial communities have received considerable attention given their important influence on their plant hosts and on ecosystem functioning. In a context where climate change threatens the sustainability of ecosystems, it is important to understand how phyllosphere microbes will respond to changes in their environment. We used 16S rRNA gene amplicon sequencing to quantify phyllosphere bacterial communities of black spruce (Picea mariana (Mill.) B.S.P.) exposed to nitrogen canopy enrichment and soil warming in the boreal forest of Quebec, Canada. The treatments were applied from April to September 2015 and the sampling was done in September. Neither treatment influenced the overall community structure and diversity of black spruce phyllosphere bacterial communities. However, some bacterial taxa and inferred microbial functions did differ among treatments, revealing in particular a stronger response of some bacteria to soil warming rather than nitrogen enrichment. Our results suggest that soil warming could potentially induce more changes in phyllosphere bacterial taxa abundances and functions than could nitrogen addition, with potential consequences for microbial diversity and boreal forest ecosystem function under likely climate change scenarios. Our study suggests avenues for further research to integrate a more mechanistic understanding of the importance of phyllosphere microbes for black spruce and boreal forest ecosystems.
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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 | 0.001 | 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) | 0.001 | 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".