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Record W2031137351 · doi:10.1139/a00-006

Nitrogen deposition and effects on European forests

2000· article· en· W2031137351 on OpenAlexvenueno aff
Jan Willem Erisman, W. de Vries

Bibliographic record

VenueEnvironmental Reviews · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsThroughfallEnvironmental scienceDeposition (geology)Soil waterEcosystemEutrophicationNitrateSoil acidificationTerrestrial ecosystemForest ecologyLeaching (pedology)NitrogenVegetation (pathology)Environmental chemistryEcologyAgronomyChemistrySoil pHNutrientSoil scienceBiology

Abstract

fetched live from OpenAlex

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 4000–8000 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 input–output 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, input–output budgets, nitrogen status, forests, effects.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.008
GPT teacher head0.189
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations94
Published2000
Admission routes1
Has abstractyes

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