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Record W2020717432 · doi:10.1139/x03-185

Forest soil disturbance intervals inferred from soil charcoal radiocarbon dates

2003· article· en· W2020717432 on OpenAlexvenueaboutno aff
Daniel G. Gavin

Bibliographic record

VenueCanadian Journal of Forest Research · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsCharcoalDisturbance (geology)Environmental scienceRadiocarbon datingSoil carbonSoil horizonHorizonSoil scienceGeologyHydrology (agriculture)Soil waterGeomorphology

Abstract

fetched live from OpenAlex

Forest soil disturbance intervals are usually too long to measure using plot-based studies, and thus they are poorly understood. The mean soil disturbance interval (MSDI) in an old-growth forest on the west coast of Vancouver Island was estimated from radiocarbon dates of charcoal from organic and mineral soil horizons. Two assumptions are required to estimate the MSDI: (1) charcoal from forest fires is deposited within the organic horizon and eventually mixed into deeper mineral horizons by soil disturbances, and (2) the probability of soil disturbance is spatially homogeneous and affected only by the time since the last fire or the last soil disturbance. The MSDI is then estimated by the rate at which the proportion of undisturbed sample sites (determined by the proportion of sites with charcoal from the most recent fire in the organic horizon) decreases with increasing time since the last fire. Soil charcoal evidence of time since fire was determined at 83 sites using 141 radiocarbon dates. The estimated MSDI was greater on slopes (ca. 2010 years) than on terraces (ca. 920 years). The long periods between soil disturbances, especially on slopes, are consistent with other evidence from the study area that suggests infrequent tree uprooting is the predominant mode of soil disturbance.

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)0.003
metaresearch head score (Gemma)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.027
GPT teacher head0.271
Teacher spread0.245 · 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 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

Citations56
Published2003
Admission routes2
Has abstractyes

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