Ectomycorrhizal fungi and the nitrogen economy of conifers — implications for genecology and climate change mitigation
Bibliographic record
Abstract
The nitrogen (N) economy of conifers is hypothesized to reflect three spatially defined and interacting sources of variability in forest nutrition. These include the physiological adaptations of the host tree (N uptake capacities among populations), matched to the particular amount and nature of soil N supply (organic N, NH4+, and NO3–), as mediated by communities of site-adapted ectomycorrhizal (EM) fungi. The spatial attributes of an N economy may vary considerably over the ranges of tree species because of wide gradients in climate and soil fertility, underpinning a potentially important aspect of conifer genecology with implications for climate change mitigation. The evidence for an intersection of N supply with host demand, as mediated by EM fungi, will be briefly reviewed and then evaluated in light of assisted migration studies involving provenance trials of coastal Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var. menziesii) in southwestern British Columbia. The trials were established across a wide range of site types, and so they provide valuable data on host response to gradations in soil N supply and interactions with local EM fungal communities. Preliminary results and knowledge gaps will be discussed under the framework of an N economy and management of forest genetic resources.
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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 | 0.000 | 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".