Temperature sensitivity of biomass‐specific microbial exo‐enzyme activities and CO<sub>2</sub> efflux is resistant to change across short‐ and long‐term timescales
Bibliographic record
Abstract
Abstract Accurate representation of temperature sensitivity (Q10) of soil microbial activity across time is critical for projecting soil CO2 efflux. As microorganisms mediate soil carbon (C) loss via exo‐enzyme activity and respiration, we explore temperature sensitivities of microbial exo‐enzyme activity and respiratory CO2 loss across time and assess mechanisms associated with these potential changes in microbial temperature responses. We collected soils along a latitudinal boreal forest transect with different temperature regimes (long‐term timescale) and exposed these soils to laboratory temperature manipulations at 5, 15, and 25°C for 84 days (short‐term timescale). We quantified temperature sensitivity of microbial activity per g soil and per g microbial biomass at days 9, 34, 55, and 84, and determined bacterial and fungal community structure before the incubation and at days 9 and 84. All biomass‐specific rates exhibited temperature sensitivities resistant to change across short‐ and long‐term timescales (mean Q10 = 2.77 ± 0.25, 2.63 ± 0.26, 1.78 ± 0.26, 2.27 ± 0.25, 3.28 ± 0.44, 2.89 ± 0.55 for β‐glucosidase, N‐acetyl‐β‐d‐glucosaminidase, leucine amino peptidase, acid phosphatase, cellobiohydrolase, and CO2 efflux, respectively). In contrast, temperature sensitivity of soil mass‐specific rates exhibited either resilience (the Q10 value changed and returned to the original value over time) or resistance to change. Regardless of the microbial flux responses, bacterial and fungal community structure was susceptible to change with temperature, significantly differing with short‐ and long‐term exposure to different temperature regimes. Our results highlight that temperature responses of microbial resource allocation to exo‐enzyme production and associated respiratory CO2 loss per unit biomass can remain invariant across time, and thus, that vulnerability of soil organic C stocks to rising temperatures may persist in the long term. Furthermore, resistant temperature sensitivities of biomass‐specific rates in spite of different community structures imply decoupling of community constituents and the temperature responses of soil microbial activities.
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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 | 0.001 |
| 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 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".