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Record W2950709831 · doi:10.1177/0959683619854523

Long-term climate, vegetation and fire regime change in a managed municipal water supply area, British Columbia, Canada

2019· article· en· W2950709831 on OpenAlexaffabout
Gerrit Schoups, Nicholas Conder, KAP Smith, J. A. Trofymow

Bibliographic record

VenueThe Holocene · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of VictoriaNatural Resources CanadaUniversity of British ColumbiaCanadian Forest Service
Fundersnot available
KeywordsFire regimeClimate changeVegetation (pathology)WoodlandEnvironmental scienceHoloceneDisturbance (geology)EcosystemPhysical geographyCharcoalWatershedGlacial periodGeographyHydrology (agriculture)EcologyGeologyArchaeologyOceanography

Abstract

fetched live from OpenAlex

Post-glacial climate, vegetation and fire history were reconstructed from a sediment record from Begbie Lake, British Columbia, Canada, located in a municipal water supply area servicing > 350,000 people. Watershed managers have identified wildfire as a threat to water supply and seek to understand how vegetation and fire have varied through time with climate. In the cold late-glacial, open Pinus woodlands, periodically disturbed by fire, transitioned to mixed conifer forests subject to high-severity fire. The early Holocene is of interest to watershed managers because climate was warmer and drier than present. During this interval, low streamflow, abundant fire-adapted taxa, elevated background charcoal and regional increases in biomass burning indicate that fire seasons were longer and that fire was an important disturbance mechanism. Climate moistened in the mid Holocene, facilitating canopy closure and decreased fire disturbance. However, surface fires prevailed in Quercus ecosystems, which were expanding locally. Charcoal increased between 6180–2500 cal yr BP as climate further cooled and moistened, likely reflecting human activity and/or increased climate variability. Modern conditions arose within the last few millennia, impacted most recently by European settlement. In combination with paleoclimate modelling, modern management practices and forecast simulations, the Begbie Lake record informs about ecosystem changes within the watershed, yielding insights for management.

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 score0.026
Threshold uncertainty score0.707

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.190
Teacher spread0.182 · 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

Citations20
Published2019
Admission routes2
Has abstractyes

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