Response of Root Respiration to Warming and Nitrogen Addition Depends on Tree Species
Bibliographic record
Abstract
ABSTRACT Roots contribute a large fraction of CO2 efflux from soils, yet the extent to which global change factors affect root‐derived fluxes is poorly understood. We investigated how red maple (Acer rubrum) and red oak (Quercus rubra) root biomass and respiration respond to long‐term (15 years) soil warming, nitrogen addition, or their combination in a temperate forest. We found that ecosystem root respiration was decreased by 40% under both single‐factor treatments (nitrogen addition or warming) but not under their combination (heated × nitrogen). This response was driven by the reduction of mass‐specific root respiration under warming and a reduction in maple root biomass in both single‐factor treatments. Mass‐specific root respiration rates for both species acclimated to soil warming, resulting in a 43% reduction, but were not affected by N addition or the combined heated × N treatment. Notably, the addition of nitrogen to warmed soils alleviated thermal acclimation and returned mass‐specific respiration rates to control levels. Oak roots contributed disproportionately to ecosystem root respiration despite the decrease in respiration rates as their biomass was maintained or enhanced under warming and nitrogen addition. In contrast, maple root respiration rates were consistently higher than oak, and this difference became critical in the heated × nitrogen treatment, where maple root biomass increased, contributing significantly more CO2 relative to single‐factor treatments. Our findings highlight the importance of accounting for the root component of respiration when assessing soil carbon loss in response to global change and demonstrate that combining warming and N addition produces effects that cannot be predicted by studying these factors in isolation.
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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 | 0.000 |
| 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 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".