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Record W1982496871 · doi:10.1139/x03-073

Effects of <i>Tsuga canadensis</i> mortality on soil water chemistry and understory vegetation: possible consequences of an invasive insect herbivore

2003· article· en· W1982496871 on OpenAlexvenueno aff
Thad E. Yorks, Donald J. Leopold, Dudley J. Raynal

Bibliographic record

VenueCanadian Journal of Forest Research · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsTsugaGirdlingUnderstoryBiologyInfestationBotanyAgronomyEcologyHorticultureCanopy

Abstract

fetched live from OpenAlex

Soil water chemistry and vegetation were monitored for almost 1 year before and 4 years after treatment in two healthy Tsuga canadensis (L.) Carrière (eastern hemlock) stands and two T. canadensis stands subjected to a girdling treatment. The girdling treatment was applied to simulate infestation and mortality by the introduced pest Adelges tsugae Annand. The girdling of T. canadensis trees resulted in elevated concentrations of NO 3 – and most cations in soil water within 2–3 months, and concentrations of several ions remained high relative to control stands for the duration of the study (e.g., NO 3 – , Ca 2+ , K + , Mg 2+ ). Maximum mean monthly concentrations were generally observed 12–18 months after girdling (e.g., 473–2272 µequiv. NO 3 – /L, 22–126 µequiv. NH 4 + /L). Maximum mean annual weighted ion concentrations and fluxes (e.g., 236 µequiv. NO 3 – /L and 18 kg NO 3 – -N/ha, respectively) were observed 2–3 years after girdling and were comparable to values reported in the literature regarding clear-cutting effects on stream water ion concentrations and losses. Betula alleghaniensis Britt. seedling densities and percent cover of several herbaceous species (Dennstaedtia punctilobula (Michx.) Moore, Dryopteris intermedia (Muhl.) A. Gray, Oxalis acetosella L., Thelypteris noveboracensis (L.) Nieuwl.) increased in response to T. canadensis mortality. Total percent cover of understory vegetation more than doubled in the first 3 years after girdling.

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 score0.612
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
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 head0.029
GPT teacher head0.264
Teacher spread0.235 · 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

Citations67
Published2003
Admission routes1
Has abstractyes

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