Earthworm-invaded boreal forest soils harbour distinct microbial communities
Bibliographic record
Abstract
Abstract. Earthworm invasion in North American forests has the potential to greatly impact soil microbial communities by altering soil physicochemical properties, including structure, pH, nutrient availability, and soil organic matter (SOM) dynamics. While most research on the topic has been carried out in northern temperate forests, little is known about the impact of invasive earthworms on soil microbial communities in hemiboreal and boreal forests, characterized by a slower decay of organic matter (OM). Earthworm activities can increase OM mineralization, altering nutrient cycling and biological activity in a biome where low carbon (C) and nitrogen (N) availability typically limits microbial and plant growth. Here, we characterized and compared microbial communities of earthworm-invaded and non-invaded soils in previously described sites across three major soil types found in the Canadian (hemi)boreal forest using a space-for-time approach. Microbial communities of forest floors and surface mineral soils were characterized using phospholipid fatty acid (PLFA) analysis and metabarcoding of the 16S rRNA gene for bacteria and archaea and of the internal-transcriber-spacer-2 (ITS2) region for fungi. In forest floors, the effects of earthworm invasion were minor. In mineral soil horizons, earthworm invasion was associated with higher fungal biomass and greater relative abundance of ectomycorrhizal fungi. Oligotrophic bacteria (Acidobacteriota and Chloroflexi) were less abundant in invaded mineral soils, where Gram(+) : Gram(−) ratios were also lower, while the opposite was observed for the copiotrophic Bacteroidota. Additionally, earthworm-invaded mineral soils harboured higher fungal and bacterial species diversity and richness. Considering the important role of soil microbial communities for ecosystem functioning, such earthworm-induced shifts in their community composition are likely to impact nutrient cycling, as well as vegetation development and forest productivity at a large scale, as the invasion progresses in these (hemi)boreal systems.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".