Carbon isotope discrimination in forest and pasture ecosystems of the Amazon Basin, Brazil
Bibliographic record
Abstract
Our objective was to measure the stable carbon isotope composition of leaf tissue and CO 2 released by respiration (δ r ), and to use this information as an estimate of changes in ecosystem isotopic discrimination that occur in response to seasonal and interannual changes in environmental conditions, and land‐use change (forest‐pasture conversion). We made measurements in primary forest and pastures in the Amazon Basin of Brazil. At the Santarém forest site, δ r values showed a seasonal cycle varying from less than −29‰ to approximately −26‰. The observed seasonal change in δ r was correlated with variation in the observed monthly precipitation. In contrast, there was no significant seasonal variation in δ r at the Manaus forest site (average δ r approximately −28‰), consistent with a narrower range of variation in monthly precipitation than occurred in Santarém. Despite substantial (9‰) vertical variation in leaf δ 13 C, the average δ r values observed for all forest sites were similar to the δ 13 C values of the most exposed sun foliage of the dominant tree species. This suggested that the major portion of recently respired carbon dioxide in these forests was metabolized carbohydrate fixed by the sun leaves at the top of the forest canopy. There was no significant seasonal variation observed in the δ 13 C values of leaf organic matter for the forest sites. We sampled in pastures dominated by the C 4 grass, Brachiaria spp., which is planted after forest vegetation has been cleared. The carbon isotope ratio of respired CO 2 in pastures was enriched in 13 C by approximately 10‰ compared to forest ecosystems. A significant temporal change occurred in δ r after the Manaus pasture was burned. Burning removed much of the encroaching C 3 shrub vegetation and so allowed an increased dominance of the C 4 pasture grass, which resulted in higher δ r values.
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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".