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Record W4410549663 · doi:10.1016/j.foreco.2025.122796

Assessing wildfire potential in a coastal forest watershed, British Columbia, Canada

2025· article· en· W4410549663 on OpenAlexafffundabout
Daniel D. B. Perrakis, Kendrick J. Brown, Kimberly Morrison, Daniel R. Horrelt, Stephen W. Taylor

Bibliographic record

VenueForest Ecology and Management · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of VictoriaNatural Resources CanadaOkanagan University CollegeCanadian Forest Service
FundersCapital Regional DistrictNatural Sciences and Engineering Research Council of CanadaUniversity of Victoria
KeywordsWatershedEnvironmental scienceGeographyEcologyAgroforestryBiology

Abstract

fetched live from OpenAlex

Wildfire disturbance in coastal western Canada has varied with changes in climate and human activity. Although infrequent during the past century, large fires in coastal forests occurred in the past, and current and future fire hazard are uncertain. We used multiple lines of evidence to characterize the contemporary regime of a forested water supply area around greater Victoria (GVWSA), British Columbia (BC), Canada, to provide a framework for assessing fire hazard more broadly in Pacific coast watersheds. Threshold conditions for locally significant fires (LSF; >10 ha) were established using recent fire and weather records. These data were used to 1) define baseline fire danger climatology for the GVWSA; 2) model fire behaviour and annual or cumulative burn probability (BP) across the region; 3) compare BP with late holocene fire return intervals derived from paleo-charcoal samples; and 4) evaluate modelling using recent fire records and case studies. The fire season was 14 days longer in the drier eastern portion of the watershed compared with the western portion. The fire season in recent years (2010–2022) was more pronounced, with higher Fire Weather Index (FWI) quantiles compared with older (1996–2009) records. LSF occurred under Fire Weather Index (FWI) ≥ 32 conditions (∼93rd percentile), although rare landscape-scale fires (> 1000 ha) were associated with more extreme events (approx. FWI ≥ ∼50, ca. 99.6th percentile), particularly summer outflow conditions. Models suggest that stands of mature Douglas-fir, the dominant vegetation type, require high sustained winds during high to extreme danger conditions for crown fire occurrence. The overall BP was lower (by 50–70 %) than values from interior BC, while the distribution of BP across the GVWSA reflected the influences of lightning maxima on exposed ridges and potential human ignitions outside the perimeter. Simulated fires were mostly small to moderate in size (median= 52 ha; 90 % < 308 ha), with the largest reaching ∼2800 ha within a 7 km fireshed. Charcoal-based paleofire reconstruction suggest the persistence of fire occurrence patterns. Data from four lakes around the watershed generally supported the landscape BP variability. Late-Holocene fire frequency was consistently 50–100 % higher than surrounding modelled present-day BP, reflecting the persistence of local climatic and topographic influences despite changes to anthropogenic influences. Wildfire potential in the forests of SVI is lower than in continental regions but poses a growing risk to water resources and other values. Environmental variability and sparse fire records suggest a multi-proxy approach can be effective for informing managers of fire hazard in similar areas of the Pacific coast.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.032
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0050.001
Scholarly communication0.0020.000
Open science0.0020.001
Research integrity0.0010.001
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 head0.002
GPT teacher head0.180
Teacher spread0.178 · 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 source (direct Gemma or distilled Codex), 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
Published2025
Admission routes3
Has abstractno

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