Fungal and bacterial communities across meadow–forest ecotones in the western Cascades of Oregon
Bibliographic record
Abstract
Meadows are natural dynamic features of forested mountain landscapes of the Pacific Northwest. Proportions of meadows and forests change with environmental conditions and disturbance history. We investigated the belowground microbial communities associated with these two vegetation types and how they change across the meadow–forest transition at two sites in Oregon. Soils were sampled along replicate transects extending from meadow into forest. We quantified total bacterial and fungal biomass using direct microscopy and described the composition of bacterial and fungal communities using a DNA-based fingerprinting technique. Bacterial biomass was similar in meadow and forest soils, but fungal biomass was significantly higher in forest soil. Meadow and forest soils had distinct communities of bacteria and fungi. Bacterial communities near the meadow–forest boundary reflected current vegetation, but fungal communities under meadow vegetation near the forest edge were intermediate in composition between those found in meadow and forest soils. The more gradual transition observed with fungal communities may reflect the influence of tree roots and their associated ectomycorrhizal fungi or possibly colonization by saprotrophic fungi associated with tree litter accumulating near the forest edge. Invasion of forest-associated fungi into the meadow soils may presage subsequent expansion of forest vegetation into meadows.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".