Long-term warming in a temperate forest accelerates soil organic matter decomposition despite increased plant-derived inputs
Bibliographic record
Abstract
Abstract Climate change may alter soil microbial communities and soil organic matter (SOM) composition. Soil carbon (C) cycling takes place over multiple time scales; therefore, long-term studies are essential to better understand the factors influencing C storage and help predict responses to climate change. To investigate this further, soils that were heated by 5 °C above ambient soil temperatures for 18 years were collected from the Barre Woods Soil Warming Study at the Harvard Forest Long-term Ecological Research site. This site consists of large 30 × 30 m plots (control or heated) where entire root systems are exposed to sustained warming conditions. Measurements included soil C and nitrogen concentrations, microbial biomass, and SOM chemistry using gas chromatography–mass spectrometry and solid-state 13 C nuclear magnetic resonance spectroscopy. These complementary techniques provide a holistic overview of all SOM components and a comprehensive understanding of SOM composition at the molecular-level. Our results showed that soil C concentrations were not significantly altered with warming; however, various molecular-level alterations to SOM chemistry were observed. We found evidence for both enhanced SOM decomposition and increased above-ground plant inputs with long-term warming. We also noted shifts in microbial community composition while microbial biomass remained largely unchanged. These findings suggest that prolonged warming induced increased availability of preferred substrates, leading to shifts in the microbial community and SOM biogeochemistry. The observed increase in gram-positive bacteria indicated changes in substrate availability as gram-positive bacteria are often associated with the decomposition of complex organic matter, while gram-negative bacteria preferentially break down simpler organic compounds altering SOM composition over time. Our results also highlight that additional plant inputs do not effectively offset chronic warming-induced SOM decomposition in temperate forests.
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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) | 0.001 | 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 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".