Characterization of Fungal Communities in Limed and Unlimed Lands Contaminated with Metals: Phospholipid Fatty Acid (PLFA) Analysis and Soil Respiration
Bibliographic record
Abstract
Northern Ontario (Canada) especially the Greater Sudbury region is highly known for its nickel, copper and other metal deposits. The mining, roasting and smelting of these elements have caused disastrous effects on the vegetation and overall environment. Dolomitic lime which contains calcium and magnesium carbonate was applied to soils from 1980 to 1995 at different locations across Northern Ontario. The objective of the present study is to determine fungi diversity and abundance in selected limed and unlimed areas contaminated with metals in the Region. Soil respiration, fungi cultures and Phospholipid Fatty Acid (PLFA) were analyzed. The liming did maintain an increase in soil pH from extremely acid to slightly acid, even 25 to 30 years after liming applications. A total of 52 fungi species belonging to 34 genera were identified on growth media. The majority of fungi (up to 70%) in all the sites belong to the Ascomycota phylum. Some species were specific to one or two sites, while others were present in the majority of the sites. Fungal diversity and abundance were higher in limed soils compared to unlimed samples based on SDA medium growth. The rates of soil respiration in limed sites were also higher compared to unlimed areas. Phospholipid Fatty Acid (PLFA) analysis revealed a significantly higher total microbial biomass in samples from limed areas compared to unlimed samples. Total and arbuscular mycorrhizal fungi abundance based on this analysis followed the same trend. Surprisingly, there were 7 to 10 fold more bacteria than fungi in all the sites. Moreover, there was twice more Gram (-) bacteria than Gram (+) indicating that the sites are still severely stressed. Soil pH appears to be the most important factor for microbial abundance, diversity and activities than total metal content.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.008 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".