Increased belowground carbon inputs and warming promote loss ofsoil organic carbon through complementary microbial responses
Bibliographic record
Abstract
Current carbon cycle-climate models predict that future soil carbon storage will be determined by the balance between CO2 fertilization and warming. However, it is uncertain whether greater carbon inputs to soils with elevated CO2 will be sequestered, particularly since warming hastens soil carbon decomposition rates, and may alter the response of soils to new plant inputs. We studied the effects of elevated CO2 and warming on microbial soil carbon decomposition processes using laboratory manipulations of carbon inputs and soil temperature. We incubated soils from the Aspen Free Air CO2 Enrichment experiment, where no accumulation of soil carbon has been observed despite a decade of increased carbon inputs to soils under elevated CO2. We added isotopically-labeled sucrose to these soils in the laboratory to mimic and trace the effects of increased carbon inputs on soil organic carbon decomposition and its temperature sensitivity. Sucrose additions caused a positive priming of soil organic carbon decomposition, demonstrated by increased respiration derived from soil carbon, increased microbial abundance, and a shift in the microbial community towards faster growing microorganisms. Similar patterns were observed for elevated CO2 soils, suggesting that the priming effect was responsible for reductions in soil carbon accumulation at the site. Laboratory warming accelerated the rate of the priming effect, but the magnitude of the priming effect was not different amongst temperatures, suggesting that the priming effect was limited by substrate availability, not soil temperature. No changes in substrate use efficiency were observed with elevated CO2 or warming. The stimulatory effects of warming on the priming effect suggest that increased belowground carbon inputs from CO2 fertilization are not likely to be stored in mineral soils. © 2014 The Authors.
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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 | 0.001 |
| 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".