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Record W4248805313 · doi:10.24124/2000/bpgub161

Mineral weathering and ectomycorrhizae of Picea glauca x engelmannii (Moench.) Voss with emphasis on Piloderma

2000· dissertation· en· W4248805313 on OpenAlexaff
Kevin Ronald Glowa

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsOkanagan CollegeOkanagan University CollegeUniversity of British Columbia
Fundersnot available
KeywordsBiotiteWeatheringMicroclineChloriteBotanyMineralRhizosphereEctomycorrhizaeHorticultureBiologyChemistryGeologyGeochemistryMycorrhizaEcologySymbiosis

Abstract

fetched live from OpenAlex

Piloderma is one of the most recognizable ectomycorrhizal fungi in many forest ecosystems in North America. It is a broad host range fungus commonly observed in many economically important coniferous and deciduous trees in central interior British Columbia. Piloderma may benefit these forests through increased soil mineral weathering and nutrient availability. This thesis investigates the role of Piloderma in the weathering of common soil minerals to supply K and/or Mg in the rhizosphere soils of Picea glauca. I also documented the changes in the physical, chemical and mineralogical properties of rhizosphere soils influenced by Pilodermaand other common ectomycorrhizal fungi. In the first study, I investigated the role of Piloderma in weathering and extracting K and/or Mg from biotite, microcline, and chlorite. Specifically, I compared the in vitro growth, morphology, and chemical properties of Piloderma growing within three K and/or Mg-containing minerals that are commonly found in soils of central interior British Columbia. Piloderma cultures were grown for 110 days in medium enriched with K and/or Mg from biotite, microcline, and chlorite, in K and Mg poor media and in medium optimized for proper fungal growth. Chemical analysis indicated that Piloderma more efficiently weathered biotite to obtain K over microcline. The different growth, morphologies, and small amounts ofMg found in all treatments indicated that chlorite and biotite provide a sufficient supply ofMg. Piloderma grown in treatments with insufficient K showed distinct fibrillar growths, hypha! swellings, and hyphae devoid of ornamentation and could be indicative of nutrient deficiency. This study indicated that considerable amounts of K and minor amounts of Mg are essential for !"roper Piloderma growth and, perhaps more that Piloderma could provide sufficient amounts of K from the weathering of biotite. In the second study, the pH, total C and N, cation exchange capacity, and the contents of mica, chlorite, kaolinite, 2:1 type expandable clays, and amorphous materials were compared between two ectomycorrhizosphere soils (soils containing considerable ectomycorrhizal colonization) and non-ectomycorrhizosphere soils (bulk) of Picea glauca x engelmannii (Moench.) Voss) to elucidate the role of ectomycorrhizae on the chemical and mineralogical properties of soils in the field. The two ectomycorrhizosphere soils were characterized by colonization dominated by (1) Piloderma, and (2) Inocybe lacera-like and ~ Hebeloma-like morphotypes or where Piloderma colonization was <1 %. Results showed that pH was one unit lower in ectomycorrhizosphere compared to nonectomycorrhizosphere soils. Total C and N were significantly higher in ectomycorrhizosphere soils where C was three times higher and N was two times higher than non-ectomycorrhizosphere soils. Cation exchange capacity as well as exchangeable K+, and Na+ were higher in ectomycorrhizosphere soils compared to bulk soils where K+ >Na+. Base saturation was significantly lower in non-ectomycorrhizal soils compared to both ectomycorrhizosphere soils. Compared to bulk soils X-ray diffraction did suggest the transformation of mica and chlorite to 2:1 type expandable clays in ectomycorrhizosphere soils.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.196
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2000
Admission routes1
Has abstractyes

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