The establishment of apple orchards as temperate forest garden systems and their impact on indigenous bacterial and fungal population abundance in Southern Ontario, Canada
Bibliographic record
Abstract
Abstract This research investigated soil microbial abundances affected by different ground management systems in establishing apple ( Malus domestica cv. Idared, M9) orchards in Ontario, Canada. Four treatments, including forest garden systems with and without compost (FGSC and FGS), and grass understory systems with and without compost (GC and G), were assessed over two establishment years for gene copy abundance of soil arbuscular mycorrhizal (AM) fungi, total fungi and total bacteria using quantitative real-time polymerase chain reactions. Time had a greater effect on all three soil microbial abundances, with total bacterial and AM fungi decreasing and total fungal abundance increasing from spring 2013 to fall 2014. The changes were greatest between the sampling dates of fall 2013 and spring 2014, which is 1 yr after the establishment of the experimental apple plots. There were no significant differences in soil microbial abundances between treatments at any specific sampling date. Apple tree trunk circumference was greatest for FGSC and FGS after 2 yr, but no significant differences in GC and G treatments. In the last sampling period, fall 2014, FGSC plots had significantly greater trunk circumferences compared with G plots. Soil chemical properties neither changed over the 2 yr, nor did they differ between treatments at any one sampling time. We conclude that the apple-based FGS treatments can benefit apple tree growth and there is a basis for future research to explore specific plant–plant, plant–microbe and microbe–microbe relations in FGSs.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".