Evidence that invasive earthworms promote bacterial-mediated nitrous oxide emissions in forest ecosystems 
Bibliographic record
Abstract
Earthworms are newcomers to South-Eastern Canada, as they were unable to survive the last glaciation period that ended about 11,000 years ago. Since their introduction by Europeans over recent centuries, these exotic earthworm species have substantially affected pedological processes and soil functions. For example, a recent study in the province of Quebec found that earthworms invading native sugar maple (Acer saccharum Marsh.) forests could potentially increase soil nitrous oxide (N2O) emissions by increasing denitrification rates. However, the underlying microbial mechanisms driving the production of this greenhouse gas via denitrification remain unclear. This led us to conduct field and laboratory studies in order to explore whether earthworms preferentially promote bacterial and/or fungal denitrification pathways. We measured earthworm abundance and collected surface mineral soil samples from 38 sugar maple forests, half of which were earthworm-free. In each soil sample, we measured fungal, bacterial and total microbial biomass by substrate-induced respiration, we measured fungal, bacterial and total denitrification by acetylene inhibition, and we quantified the abundance bacterial (nirK, nirS and nosZ) and fungal (P450nor) denitrifying genes by qPCR. Earthworm abundance correlated positively with bacterial as well as fungal biomass, but did not affect the bacterial-to-fungal biomass ratio. Accordingly, bacterial-mediated and fungal-mediated denitrification rates both increased with the abundance of earthworms. However, earthworm abundance correlated positively with the specific bacterial denitrification rate (SBDR = (bacterial-mediated denitrification rate) ÷ (bacterial biomass)), but not with the specific fungal denitrification rate (SFDR = (fungal-mediated denitrification rate) ÷ (fungal biomass)). Moreover, qPCR analyses showed a positive correlation between earthworm abundance and the proportion of all bacterial denitrifying genes in the microbial population, but no such effect on fungal denitrifying genes. Taken collectively, our results suggest that earthworms may increase N2O emissions in sugar maple forest soils by preferentially promoting the bacterial-mediated denitrification pathway.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".