Bibliographic record
Abstract
Hypotheses about the impacts of elevated atmospheric deposition of nitrogen on the forest ecosystem include an increased sensitivity to natural stress, impacts on roots, reduced species diversity of the ground vegetation, reduced growth, and unbalanced nutritional status due to eutrophication and acidification. The impact of N deposition has gained in ecological importance during recent decades, in part due to the steady decline in S emissions. Results of throughfall and deposition measurements at 163 plots in Europe show that total deposition of S and N compounds ranged from 100 to 3000 mol ha 1 yr 1 in approximately 90% of the plots, but values up to 40008000 mol ha 1 yr 1 were also observed. Approximately 50% of the plots received N inputs, dominated by NH 4 , above 1000 mol ha 1 yr 1 , which is a deposition level at which species diversity of the ground vegetation may be at risk. Results of inputoutput budgets for plots concentrated in Northern and Western Europe indicate that nitrate leaching starts to occur at throughfall inputs above 10 kg ha 1 yr 1 , specifically in soils with C/N ratios in the humus layer below 25. Examples are given of field evidence for impacts of elevated N deposition, including elevated N contents in foliage and soil, Al release in soil response to increased nitrate concentrations, reduced shoot/root ratios, and a reduction in species diversity. Although knowledge about the response of forest ecosystems to N inputs has increased over the last decade, there is still a lack of information on the dynamics of N accumulation and related critical N loads in a range of environmental conditions. Furthermore, a European-wide perspective of N saturation in forest ecosystems is still lacking.Key words: nitrogen, deposition, inputoutput budgets, nitrogen status, forests, effects.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".