Soil carbon sequestration in a pine forest after 9 years of atmospheric CO<sub>2</sub> enrichment
Bibliographic record
Abstract
Abstract The impact of anthropogenic CO2 emissions on climate change may be mitigated in part by C sequestration in terrestrial ecosystems as rising atmospheric CO2 concentrations stimulate primary productivity and ecosystem C storage. Carbon will be sequestered in forest soils if organic matter inputs to soil profiles increase without a matching increase in decomposition or leaching losses from the soil profile, or if the rate of decomposition decreases because of increased production of resistant humic substances or greater physical protection of organic matter in soil aggregates. To examine the response of a forest ecosystem to elevated atmospheric CO2 concentrations, the Duke Forest Free‐Air CO2 Enrichment (FACE) experiment in North Carolina, USA, has maintained atmospheric CO2 concentrations 200 μL L−1 above ambient in an aggrading loblolly pine (Pinus taeda) plantation over a 9‐year period (1996–2005). During the first 6 years of the experiment, forest‐floor C and N pools increased linearly under both elevated and ambient CO2 conditions, with significantly greater accumulations under the elevated CO2 treatment. Between the sixth and ninth year, forest‐floor organic matter accumulation stabilized and C and N pools appeared to reach their respective steady states. An additional C sink of ∼30 g C m−2 yr−1 was sequestered in the forest floor of the elevated CO2 treatment plots relative to the control plots maintained at ambient CO2 owing to increased litterfall and root turnover during the first 9 years of the study. Because we did not detect any significant elevated CO2 effects on the rate of decomposition or on the chemical composition of forest‐floor organic matter, this additional C sink was likely related to enhanced litterfall C inputs. We also failed to detect any statistically significant treatment effects on the C and N pools of surface and deep mineral soil horizons. However, a significant widening of the C : N ratio of soil organic matter (SOM) in the upper mineral soil under both elevated and ambient CO2 suggests that N is being transferred from soil to plants in this aggrading forest. A significant treatment × time interaction indicates that N is being transferred at a higher rate under elevated CO2 (P=0.037), suggesting that enhanced rates of SOM decomposition are increasing mineralization and uptake to provide the extra N required to support the observed increase in primary productivity under elevated CO2.
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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 | 0.000 | 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 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".