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Record W1542495989 · doi:10.22230/jem.2008v9n2a391

The fire history of a 416-year-old western larch tree in southeastern British Columbia

2008· article· en· W1542495989 on OpenAlexaboutno aff
L.R. Mark Hall

Bibliographic record

VenueJournal of Ecosystems and Management · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsLarchFire regimeGeographyFire historyHistorical ecologyChronologyDisturbance (geology)DendrochronologyRestoration ecologyFire ecologyEcosystemForestryEcologyEnvironmental resource managementArchaeologyEnvironmental scienceClimate changeGeology

Abstract

fetched live from OpenAlex

The fire history obtained from pre-settlement fire-scarred trees provides useful benchmarks for the restoration of dry interior, fire-dependent forest ecosystems. In the Rocky Mountain Trench of southeast British Columbia, historical benchmarks obtained from periods prior to significant European influence (i.e., pre-1850) are common reference points for forest ecosystem restoration. This extension note discusses the fire history of a 416-year-old western larch (Larix occidentalis) whose growth rings recorded 268 years of fire history before 1850. The study tree's estimated mean fire interval (MFI) is 34.1 years, and its fire intervals ranged from 19 years to 51 years. The tree did not record a fire during the last 130 years of its life. This extension note also discusses the development of a network of cross-dated benchmark sites across the landscape that would create a master fire chronology for the region. Such a chronology would reflect the natural variability of historical fire patterns, helping policy-makers, managers, recovery teams, and restoration practitioners understand the spatial and temporal distribution of landscape-scale disturbances that historically have created fire-dependent ecological communities (many of which include wildlife and plant species now at risk). The creation of a benchmark network would also refine dry interior forest restoration/conservation programs and improve their efficacy.

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 score0.221
Threshold uncertainty score0.983

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 studies0.0000.000
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 head0.009
GPT teacher head0.180
Teacher spread0.171 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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