Temperature sensitivity of soil microbial communities: An application of macromolecular rate theory to microbial respiration
Bibliographic record
Abstract
Abstract There is compelling evidence that microbial communities vary widely in their temperature sensitivity and may adapt to warming through time. To date, this sensitivity has been largely characterized using a range of models relying on versions of the Arrhenius equation, which predicts an exponential increase in reaction rate with temperature. However, there is growing evidence from laboratory and field studies that observe nonmonotonic responses of reaction rates to variation in temperature, indicating that Arrhenius is not an appropriate model for quantitatively characterizing temperature sensitivity. Recently, Hobbs et al. (2013) developed macromolecular rate theory (MMRT), which incorporates thermodynamic temperature optima as arising from heat capacity differences between isoenzymes. We applied MMRT to measurements of respiration from soils incubated at different temperatures. These soils were collected from three grassland sites across the U.S. Great Plains and reciprocally transplanted, allowing us to isolate the effects of microbial community type from edaphic factors. We found that microbial community type explained roughly 30% of the variation in the CO 2 production rate from the labile C pool but that temperature and soil type were most important in explaining variation in labile and recalcitrant C pool size. For six out of the nine soil × inoculum combinations, MMRT was superior to Arrhenius. The MMRT analysis revealed that microbial communities have distinct heat capacity values and temperature sensitivities sometimes independent of soil type. These results challenge the current paradigm for modeling temperature sensitivity of soil C pools and understanding of microbial enzyme dynamics.
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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 | 0.005 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".