Vertical partitioning between sister species of <i><scp>R</scp>hizopogon</i> fungi on mesic and xeric sites in an interior <scp>D</scp>ouglas‐fir forest
Bibliographic record
Abstract
Understanding ectomycorrhizal fungal (EMF) community structure is limited by a lack of taxonomic resolution and autecological information. Rhizopogon vesiculosus and Rhizopogon vinicolor (Basidiomycota) are morphologically and genetically related species. They are dominant members of interior Douglas-fir (Pseudotsuga menziesii var. glauca) EMF communities, but mechanisms leading to their coexistence are unknown. We investigated the microsite associations and foraging strategy of individual R. vesiculosus and R. vinicolor genets. Mycelia spatial patterns, pervasiveness and root colonization patterns of fungal genets were compared between Rhizopogon species and between xeric and mesic soil moisture regimes. Rhizopogon spp. mycelia were systematically excavated from the soil and identified using microsatellite DNA markers. Rhizopogon vesiculosus mycelia occurred at greater depth, were more spatially pervasive, and colonized more tree roots than R. vinicolor mycelia. Both species were frequently encountered in organic layers and between the interface of organic and mineral horizons. They were particularly abundant within microsites associated with soil moisture retention. The occurrence of R. vesiculosus shifted in the presence of R. vinicolor towards mineral soil horizons, where R. vinicolor was mostly absent. This suggests that competition and foraging strategy may contribute towards the vertical partitioning observed between these species. Rhizopogon vesiculosus and R. vinicolor mycelia systems occurred at greater mean depths and were more pervasive in mesic plots compared with xeric plots. The spatial continuity and number of trees colonized by genets of each species did not significantly differ between soil moisture regimes.
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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 | 0.001 | 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) | 0.000 | 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".