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Record W2548277342 · doi:10.5849/jof.15-111

Using Risk Analysis to Reveal Opportunities for the Management of Unplanned Ignitions in Wilderness

2016· article· en· W2548277342 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Forestry · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsCanadian Parks and Wilderness Society
Fundersnot available
KeywordsWildernessWilderness areaEnvironmental resource managementContext (archaeology)GeographyNatural resourceFire regimeResource (disambiguation)Environmental planningEnvironmental scienceEcologyComputer scienceArchaeology

Abstract

fetched live from OpenAlex

A goal of fire management in wilderness is to allow fire to play its natural ecological role without intervention. Unfortunately, most unplanned ignitions in wilderness are suppressed, in part because of the risk they might pose to values outside of the wilderness. We capitalize on recent advances in fire risk analysis to demonstrate a risk-based approach for revealing where unplanned ignitions in wilderness pose little risk to nonwilderness values and therefore where fire can be managed for its longer term ecological benefits. Using a large wilderness area as a case study, we conduct an exposure analysis and quantify the potential for unplanned ignitions inside the wilderness area to spread outside the wilderness boundary onto adjacent lands. Results show that, in general, ignitions that occur inside a large core area of the wilderness have very low likelihoods of escaping the wilderness boundary, especially early and late in the fire season. These “windows” may thus represent opportunities for allowing natural fire to occur. We discuss our approach in the broader context of spatial fire risk management and planning across public lands. Management and Policy Implications: Fire management plans need to address the location and conditions under which resource objectives can be met with fire. The exposure analysis demonstrated here helps meet this need by identifying “windows of opportunity” for using unplanned ignitions to meet natural resource management objectives. In addition, it integrates well with spatial fire planning (USDA Forest Service 2014) activities that are increasingly being adopted to support both preseason planning and real-time incident management decision environments and can be updated on an annual basis to reflect current fuel and vegetation conditions. Implementing these methods in small wilderness areas or wilderness areas adjacent to wildland-urban interface zones may reveal previously unrecognized opportunities for allowing unplanned ignitions to burn. Forest managers can use such findings to amend existing fire management plans to expand the use of unplanned ignitions to meet resource objectives. Although this approach was demonstrated in the context of wilderness fire management, it has broad applicability and could support spatial fire and fuels management planning efforts in nonwilderness settings.

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.

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 score0.127
Threshold uncertainty score0.147

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 head0.049
GPT teacher head0.281
Teacher spread0.231 · 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