Changes in soil organic carbon storage predicted by Earth system models during the 21st century
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. Soil is currently thought to be a sink for carbon; however, the response of this sink to increasing levels of atmospheric carbon dioxide and climate change is uncertain. In this study, we analyzed soil organic carbon (SOC) changes from 11 Earth system models (ESMs) contributing simulations to the Coupled Model Intercomparison Project Phase 5 (CMIP5). We used a reduced complexity model based on temperature and moisture sensitivities to analyze the drivers of SOC change for the historical and high radiative forcing (RCP 8.5) scenarios between 1850 and 2100. ESM estimates of SOC changed over the 21st century (2090–2099 minus 1997–2006) ranging from a loss of 72 Pg C to a gain of 253 Pg C with a multi-model mean gain of 65 Pg C. Many ESMs simulated large changes in high-latitude SOC that ranged from losses of 37 Pg C to gains of 146 Pg C with a multi-model mean gain of 39 Pg C across tundra and boreal biomes. All ESMs showed cumulative increases in global NPP (11 to 59%) and decreases in SOC turnover times (15 to 28%) over the 21st century. Most of the model-to-model variation in SOC change was explained by initial SOC stocks combined with the relative changes in soil inputs and decomposition rates (R2 = 0.89, p < 0.01). Between models, increases in decomposition rate were well explained by a combination of initial decomposition rate, ESM-specific Q10-factors, and changes in soil temperature (R2 = 0.80, p < 0.01). All SOC changes depended on sustained increases in NPP with global change (primarily driven by increasing CO2). Many ESMs simulated large accumulations of SOC in high-latitude biomes that are not consistent with empirical studies. Most ESMs poorly represented permafrost dynamics and omitted potential constraints on SOC storage, such as priming effects, nutrient availability, mineral surface stabilization, and aggregate formation. Future models that represent these constraints are likely to estimate smaller increases in SOC storage over the 21st century.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it