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Record W2966140861 · doi:10.5424/fs/2019282-14782

Replacing an oriental beech forest with a spruce plantation impacts nutrient concentrations in throughfall, stemflow, and O layer

2019· article· en· W2966140861 on OpenAlexaff
Pedram Attarod, Parisa Abbasian, Thomas Grant-Pypker, Mohammad Taghi Ahmadi, Ghavamoddin Zahedi-Amiri, Hamid Soofi-Mariv, Vilma Bayramzadeh

Bibliographic record

VenueForest Systems · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsThompson Rivers University
FundersIran National Science FoundationNational Science Foundation
KeywordsThroughfallStemflowBeechFagus orientalisEnvironmental scienceFagus sylvaticaCanopyPicea abiesForestryNutrientLeaching (pedology)AgroforestryBotanyEcologyGeographySoil waterBiologySoil science

Abstract

fetched live from OpenAlex

Aim of study: To measure the nutrient leaching from canopy and the O layer in a natural oriental beech (Fagus orientalis Lipsky) forest and a Norway spruce (Picea abies) plantation.Materials and methods: From mid-July to early November, 2013, we measured throughfall (TF) (n=45), stemflow (SF) (n=12) and leaching from the O layer (n = 30) in a 0.5 ha sample plot in the Caspian region, Mazandaran province in northern Iran.Main results: Concentrations of PO43-, Na+, Mg2+, Ca2+ and K+ in the throughfall and the O layer in both beech and spruce forests significantly increased relative to gross rainfall. Concentrations of Ca2+ and Na+ in TF and SF were significantly higher in the spruce forest compared with the beech forest. Furthermore, in both forests, cumulative fluxes of all studied elements (with the exception of NH4+ and NO3-) during the study period were statistically different from those of GR (P<0.05).Research highlights: This study demonstrates that changing from a natural beech forest to a spruce plantation significantly alters nutrient fluxes exiting the canopy and the O layer. This information provides essential information on how planting exotic species will affect nutrient cycles in this region.Keywords: Beech forest; Norway spruce plantation; Throughfall; Nutrient leaching; O layer.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.991

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.217
Teacher spread0.210 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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