A method for measuring above- and below-ground C stocks in hillside landscapes
Bibliographic record
Abstract
Information on C stocks in agriculture and forest ecosystems in hillside landscapes is limited. The objective of this study was to develop and test field methods to measure above- and below-ground C stocks in hillside landscapes. Above-ground biomass in agricultural system was determined by measuring weight of residues left after crop harvest. In degraded secondary forests, tree biomass was estimated using allometric equations developed from in situ measurements. Herbs + bushes and litter dry weight were measured in two 0.25-m2 quadrats located within one 100-m2 treed plots. Carbon stocks were determined after chemical analysis of plant tissue and soil samples by dry combustion. Geo-referenced cores were taken inside a 1-m-diameter soil sampling clock that allows for spatial and temporal monitoring of soil C changes. The clock was marked with 12 divisions to establish the exact location of present and future sampling points. The below-ground fraction of C (mineral soil and fine roots) amounted to nearly 95% of the total C stock in agricultural systems and between 57 and 82% in the case of forest systems. Soil C stocks in hillside agricultural soils were higher than those found in forested soils with 70% of the C stored below-ground residing in the 0–45 cm of soil. The field method detected differences in C stocks in pools associated with various vegetations and soils in hillside ecosystems. Key words: Soil carbon, belowground carbon, sampling clock, hillside agriculture, Mexico
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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 | 0.001 |
| 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) | 0.002 | 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".