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Perception of wildfire behaviour and fire suppression tactics among Swedish incident commanders

2022· book-chapter· en· W4313017524 on OpenAlexaboutno aff
Johan Sjöström, Anders Granström, Lotta Vylund

Bibliographic record

VenueImprensa da Universidade de Coimbra eBooks · 2022
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsIncident reportPerceptionFirefightingEnvironmental resource managementTruckFire protectionEngineeringEnvironmental scienceForensic engineeringGeographyPsychologyCartographyCivil engineering

Abstract

fetched live from OpenAlex

Unlike most regions with high-intensity wildfire potential, Sweden lacks specialized wildfire suppression organization. Instead, wildfire suppression is handled by highly decentralized and multitask municipal rescue services. This prompts the question how the incident commanders (ICs) perceive and interpret variation in fire behaviour and how they respond to wildfire incidents with regard to dispatching for initial attack and selecting tactics. To elucidate this, we exposed a spectrum of Swedish ICs to a questionnaire and round-table-exercises of different fire scenarios. The informants had on average 13 years of experience as incident commanders and had on average managed 6 wildfires over the last 5 years. Despite minimal formal wildfire training the respondents showed reasonable consensus in rating of fire behaviour in response to fuels and weather, suggesting that their knowledge was built on personal and group experience. Likewise, they gave estimates on rate of production of hose-lays similar to published expert assessments from Canada. When exposed to a spectrum of fire scenarios, resource dimensioning by ICs was linearly related to the Canadian FWI-index, although most organizations did not have any preordained schemas or rules of initial dispatching resources to guide them. Tactics employed were based mainly on accessing the fire from the nearest road and using direct attack with hose-line laid from the engine and water ferried on trucks. In a scenario where initial attack failed, suppression crews typically fell back on roads, which however would be breached by intense fire, and which also exposed the operation to risk of being outflanked. This response was in fact similar to that employed during a 2014 catastrophic wildfire in central Sweden and may indicate a fundamental flaw in tactics employed for large and intense fires. The present structure of the Swedish wildfire suppression system developed during the second half of the 1900s and depends on rapid access to the fire by a relatively small number of firefighters. The study suggests a relatively high capacity for suppressing forest fires, despite that the organization is primarily rigged for other purposes and that ICs have minimal formal training in this area. Climate change-scenarios suggest longer fire season and more risk days in parts of the country, but the future wildfire scene may be even more sensitive to de-population and diminishing economic resources in heavily forested regions of the country.

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)0.003
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 score0.071
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.204
Teacher spread0.196 · 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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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