The role of temperature in carbon and nitrogen mineralization from selected arable Nova Scotia soils.
Bibliographic record
Abstract
This thesis focuses on the effects of soil management history and temperature on C and N mineralization. A preliminary field study indicated that N uptake by a crop was related to variability in substrate quantity and quality, and environmental factors. Further experiments in soil microcosms investigated the effects of soil temperature and management history on net C and N mineralization using soils from a fertility experiment with and without a history of manure application. Microcosms were incubated at 5, 15, 25 or 35°C, with and without the addition of 14C-labelled wheat. For native C and N, and 14C, the size of the substrate pool estimated using the first-order model of decomposition changed with temperature, contradicting one of the key assumptions of the first-order approach to modelling net C and N mineralization in soils. The temperature response of native C and N mineralization differed in the non-amended microcosms, with a substantial increase in the rate of N mineralization relative to C mineralization between 5 and 15°C. Microbial community structure changed with temperature, with distinct fungal communities present at 5°C. The size of the microbial biomass declined with increasing temperature, and metabolic quotients were also highest at 35°C. A further study using 13C-labelled wheat indicated some differences in the accessibility of the wheat C due to management history at the coldest incubation temperature. The use of DNA-SIP along with density gradient centrifugation was used to separate wheat C from native C metabolizing communities, with a trend towards declining diversity with increasing density within the fungal population.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".