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Record W2007770196 · doi:10.1139/x08-088

Nutrient fluxes via leaching from coarse woody debris in a Fagus sylvatica forest in the Solling Mountains, Germany

2008· article· en· W2007770196 on OpenAlexvenueno aff
Christian Kuehne, C. Donath, Sabine Müller-Using, Norbert Bartsch

Bibliographic record

VenueCanadian Journal of Forest Research · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsThroughfallFagus sylvaticaBeechEnvironmental scienceCoarse woody debrisStemflowLysimeterEnvironmental chemistryLeachateNutrientNitrateLeaching (pedology)Forest floorChemistryHydrology (agriculture)Soil waterEcologySoil scienceGeology

Abstract

fetched live from OpenAlex

To evaluate the importance of nutrient fluxes via leaching from coarse woody debris (CWD) in an area with high atmospheric nitrogen (N) inputs, throughfall and CWD leachate from logs at different stages of decomposition were investigated over a period of 14 and 27 months, respectively, in a 160-year-old European beech ( Fagus sylvatica L.) forest in northwestern Germany. Water samples, collected from 30 zero-tension lysimeters installed in pairs along 15 logs and from 27 neighboring raingauges, were chemically analyzed in the laboratory. Generally, as CWD decay advanced, the ratio of leachate to throughfall decreased, and the amount of dissolved nutrients in the leachate increased. With the exception of ammonium (NH 4 + ) and dissolved inorganic carbon, the element concentrations in the CWD leachate were significantly higher than those in the throughfall. The concentrations of NH 4 + and nitrate (NO 3 – ) in the CWD leachate, which were very high compared with values from North American studies, were caused by the continuously high atmospheric N inputs, and the resulting N saturation in the forest ecosystem investigated. The low concentrations of the cations calcium and magnesium indicate that at this site nutrients limiting plant and fungal growth are retained and accumulated in the CWD.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score0.887

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.266
Teacher spread0.201 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations55
Published2008
Admission routes1
Has abstractyes

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