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Record W2005899147 · doi:10.1139/x01-064

Mechanism of nitrate loss from a forested catchment following a small-scale, natural disturbance

2001· article· en· W2005899147 on OpenAlexvenueno aff
Satoru Hobara, Naoko Tokuchi, Nobuhito Ohte, Keisuke Koba, Masanori Katsuyama, Su‐Jin Kim, Asami Nakanishi

Bibliographic record

VenueCanadian Journal of Forest Research · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsNitrateNitrificationEnvironmental scienceSoil waterHydrology (agriculture)GroundwaterSurface waterNitrogen cycleNitrogenSoil scienceEcologyChemistryGeologyEnvironmental engineeringBiology

Abstract

fetched live from OpenAlex

In Matsu-zawa catchment, central Japan, nitrate concentrations in stream water increased following a small-scale, natural disturbance involving an outbreak of pine wilt disease that affected ~25% of the forested catchment. To clarify nutrient dynamics in soils and their relationship with stream water nitrate, we investigated soil nitrogen dynamics and soil water chemistry in disturbed and undisturbed, water-unsaturated and -saturated plots. The highest values for nitrification rate, nitrate concentration in soil solution, and nitrate exported from the root zone were observed for the disturbed plot. The ratio of nitrification to mineralization in surface soil of the disturbed plot dramatically increased from 1989 (pre-disturbance) to 1997. Root zone leachate from the disturbed area showed gradually increasing groundwater nitrate concentrations in the temporarily saturated zone during lateral, matrix flow. The catchment's deep soils and associated hydrologic processes limited the degree of plant uptake of the nitrate generated in the disturbed area. It was inferred that the persistent high levels of nitrate observed in the stream water resulted largely from the stable high nitrate concentrations observed in the saturated groundwater of this catchment. Stream water nitrate loads discharged following the disturbance were about 16 times greater than prior to it.

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)0.001
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 score0.185
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.023
GPT teacher head0.260
Teacher spread0.238 · 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

Citations58
Published2001
Admission routes1
Has abstractyes

Explore more

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