Bibliographic record
Abstract
Boreal forest soils are complex, heterogeneous growth substrates where organic and mineral components provide nutrient resources for soil organisms and plants. Mineral nutrients are cycled between living and dead organic components of the forest soil and weathering of soil minerals provides an important input of new resources, compensating for losses from the ecosystem. Predicting soil responses to changing climate and management practices is important to determine their effect on forest production. Models for this purpose are largely based on the concept of the soil solution as the interface controlling soil processes such as weathering and nutrient uptake by plants, whereas soil microbiology recognises microbial processes as the driving force in soil nutrient cycling. In boreal forests most tree root tips are colonised by ectomycorrhizal fungi. The mycelia of these symbiotic fungi mediate nutrient uptake by their tree hosts. These fungi are abundant in the organic layer of forest soils and ectomycorrhizal research has therefore largely focused on nutrient uptake from this horizon. Minerals in the soil may, however, also serve as nutrient resources for ectomycorrhizal fungi. Through combined chemical and physical processes fungi can affect nutrient availability by weathering minerals. This thesis describes a field experiment investigating the distribution of different ectomycorrhizal fungi in organic and mineral forest soil horizons, in vitro studies of fungal acidification of artificial substrates with different mineral element composition, microcosm studies of growth and carbon allocation in intact ectomycorrhizal systems colonising heterogeneous mineral substrates and a preliminary investigation of changes in surface micro-topography of minerals colonised by ectomycorrhizal hyphae. Half of the fungal species identified in the forest soil occurred exclusively in the mineral horizons. Mycelial growth, carbon allocation and substrate acidification by fungi colonising different mineral substrates in vitro and in microcosms appeared to be influenced by mineral element composition. Interpretation of possible modification of mineral surface micro-topography is more difficult but together the results obtained suggest that ectomycorrhizal fungi may contribute to the development of microenvironments on colonised mineral surfaces, where increased weathering can take place. Processes regulating nutrient availability in such microenvironments are different from those estimated from the bulk soil solution.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".