The response of methane and nitrous oxide fluxes to forest change in Europe
Bibliographic record
Abstract
Abstract. Forests in Europe are changing due to interactions between climate change, nitrogen (N) deposition and new forest management practices. The concurrent impact on the forest greenhouse gas (GHG) balance is at present difficult to predict due to a lack of knowledge on controlling factors of GHG fluxes and response to changes in these factors. To improve the mechanistic understanding of the ongoing changes, we studied the response of soil–atmosphere exchange of nitrous oxide (N2O) and methane (CH4) at twelve experimental or natural gradient forest sites, representing anticipated future forest change. The experimental manipulations, one or more per site, included N addition (4 sites), changes of climate (temperature, 1 site; precipitation, 2 sites), soil hydrology (3 sites), harvest intensity (1 site), wood ash fertilisation (1 site), pH gradient in organic soil (1 site) and afforestation of cropland (1 site). On average, N2O emissions increased by 0.06 ± 0.03 (range 0–0.3) g N2O-N m−2 yr−1 across all treatments on mineral soils, but the increase was up to 10 times higher in an acidic organic soil. Soil moisture together with mineral soil C / N ratio and pH were found to significantly influence N2O emissions across all treatments. Emissions were increased by elevated N deposition, especially in interaction with increased soil moisture. High pH reduced the formation of N2O, even under otherwise favourable soil conditions. Oxidation (uptake) of CH4 was on average reduced from 0.16 ± 0.02 to 0.04 ± 0.05 g CH4-C m−2 yr−1 by the investigated treatments. The CH4 exchange was significantly influenced by soil moisture and soil C / N ratio across all treatments, and CH4 emissions occurred only in wet or water-saturated conditions. For most of the investigated forest manipulations or natural gradients, the response of both N2O and CH4 fluxes was towards reducing the overall GHG forest sink. The most resilient forests were dry Mediterranean forests, as well as forests with high soil C / N ratio or high soil pH. Mitigation strategies may focus on (i) sustainable management of wet forest areas and forested peatlands, (ii) continuous forest cover management, (iii) reducing atmospheric N input and, thus, N availability, and (iv) improving neutralisation capacity of acid soils (e.g. wood ash application).
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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) | 0.000 | 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 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".