Soil respiration in four different land use systems in north central Alberta, Canada
Bibliographic record
Abstract
This study compares soil respiration and its heterotrophic and autotrophic components in four land use types: agriculture, 2 and 9 year old hybrid poplar plantations, grassland, and a native aspen stand in north central Alberta, Canada, over a period of two growing seasons (2006 and 2007). The differences were examined with respect to substrate quality and quantity, fine root biomass, and nutrient availability, in addition to soil temperature and soil water content. Cumulative soil C loss via soil respiration averaged over the two growing seasons was (in decreasing order) 781, 551, 523, 502, and 428 g C m−2 for native aspen stand, 9 year old hybrid poplar plantation, grassland, agriculture and 2 year old hybrid poplar plantation, respectively. We found that ∼75% of soil respiration in the native aspen stand originated from the top 7.5–10 cm litter‐fibric‐humus layer. Seasonal heterotrophic and autotrophic respiration among the land uses ranged from 97 to 272 and 333 to 560 g C m−2, respectively, contributing up to 35% and 83% of total soil respiration, respectively. The variability in soil respiration across different land uses was explained mainly by site differences in soil temperature (88–94%). Soil respiration followed a pronounced seasonal trend: increasing during the growing season and converging to a minimum in the fall. Soil respiration under different land uses was influenced by (1) ecosystem C stock, (2) temperature sensitivity (Q10) of organic matter present, and (3) organic matter decomposability as indicated by the natural abundance of δ13C. Heterotrophic respiration was influenced by soil temperature, while autotrophic respiration was influenced by fine root biomass and nutrient (NO3− and P) availability. These results are useful in estimating potential responses of soil respiration and its components to future land management and climate change.
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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 | 0.002 |
| 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) | 0.001 | 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".