Unexpected microbial metabolic responses to elevated temperatures and nitrogen addition in subarctic soils under different land uses
Bibliographic record
Abstract
Abstract Subarctic regions are particularly affected by global warming. As vegetation periods lengthen, boreal forests could gradually be converted into agricultural land. How land use alters the susceptibility of soil organic matter decomposition to rising temperatures or how changes in nutrient availability, such as nitrogen (N) fertilisation, affect carbon (C) cycling is unknown. Microbial carbon use efficiency (CUE) defines how much of the decomposed soil organic carbon is directed to growth or lost to the atmosphere. Here, we investigated the response of CUE (24 h) and soil organic matter decomposition (50 days) to + 10 °C warming and N addition in three subarctic soils derived from paired plots (forest, grassland, cropland) in the Yukon, Canada. Contrary to our literature-based expectations, boreal forest soils did not demonstrate the most sensitive response to warming and N addition. Temperature sensitivity was not affected by land-use type. In contrast to a generally assumed decline, short-term warming increased CUE by + 30%, which was positively correlated with microbial growth. N addition reduced overall CUE by − 7%, in contrast to the expectation that CUE would rise due to the alleviation of nutrient limitations. The response to N addition was negatively correlated with the ratio of fungi to bacteria, and presumably depended on the prevailing N-fertilisation regime. The temperature sensitivity of microbial metabolism was driven by site-specific parameters rather than by land-use type. Our results indicate that it may not be necessary to consider land use-specific temperature sensitivities when modelling soil organic carbon dynamics under future climate conditions.
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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) | 0.000 | 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".