Long- and short-term temperature differences affect organic and inorganic nitrogen availability in forest soils
Bibliographic record
Abstract
Boczulak, S. A., Hawkins, B. J., Maynard, D. G. and Roy, R. 2015. Long- and short-term temperature differences affect organic and inorganic nitrogen availability in forest soils. Can. J. Soil Sci. 95: 77–86. Soil microbial activity determines rates of decomposition and is strongly influenced by temperature. Soil microbial communities may be adapted to site characteristics, including temperature, through physiological modification of microbial populations or changes in species composition; however, response to short-term changes in temperature may also occur. We searched for evidence of short- and long-term temperature response of microbial communities involved in soil nitrogen (N) cycling by measuring the relative availability of organic and inorganic N forms in forest soils from a high and a low elevation site, incubated at 10, 16 and 20°C for 16 wk. By week 16, ammonium concentrations were greater in soils incubated at 16 and 20°C than at 10°C, and in soil from the low elevation site, compared with high elevation. Nitrate concentrations increased in soil from the low elevation site incubated at 16 and 20°C, but changed little in other treatments. Assessment of autotrophic nitrification potential showed gross nitrification in soil from the low elevation site was likely from classical chemolithotrophic nitrifiers. Organic N concentration increased over time in the 16 and 20°C incubations of soil from the low elevation site, but only increased in the 20°C treatment for soil from the high elevation site. Long-lasting site effects were indicated by the more active microbial community in soil from low elevation, which could be related to site temperature. Evidence of short-term temperature response of N cycling processes was observed in soils from both elevations.
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".