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Turning down the heat: vegetation feedbacks limit fire regime responses to global warming

2017· article· en· W2763407294 on OpenAlex
Jean Marchal, Steve Cumming, Eliot J. B. McIntire

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFaculty of 1000 Research Ltd · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsCanadian Forest ServiceNatural Resources CanadaUniversité Laval
Fundersnot available
KeywordsEnvironmental scienceClimate changeAbies balsameaVegetation (pathology)TaigaBorealGlobal changeGlobal warmingClimatologyEcologyAtmospheric sciencesDisturbance (geology)Yellow birchBlack sprucePhysical geographyBalsamGeographyBiologyGeology

Abstract

fetched live from OpenAlex

Climate change is projected to dramatically increase boreal wildfire activity, with broad ecological and socioeconomic consequences. As global temperatures rise, periods with elevated fire weather are expected to increase in frequency and duration, which would be expected to increase the number and size of fires. Statistical forecasts or simulations of future fire activity often account for direct climatic effects only, neglecting other controls of importance, such as biotic feedbacks. This could result in overestimating the effects of climate change on fire activity, if the future distribution of vegetation or fuels were to change. We incorporated sensitivity to climate or fire weather and vegetation in a fire simulation model and represented explicitly two key biotic feedbacks linked to succession and regeneration processes. We used this model to forecast annual fire activity from 2011 to 2099 over a large region of boreal forest in Quebec, Canada, dominated by balsam fir (Abies balsamea (L.) Mill) and yellow birch (Betula alleghaniensis Britt.) or paper birch (Betula papyrifera Marsh.), with and without the biotic feedbacks. Our simulations show that vegetation changes triggered by fire disturbance altered future fire activity and may even be as important a driver as climate change itself. Indeed, over the course of the century, vegetation changes were projected to offset much of the increase in fire activity that would be expected due to global warming as such. It follows that if biotic feedbacks are not included in statistical or simulation-based forecasts, the resultant projections of future fire activity could be biased upward to a very considerable degree. For the case of end-of-century mean annual burn rate, we estimated this positive bias to be as high as 400%. Accounting for biotic feedbacks in simulation models is therefore necessary for accurate projection of future wildfire activity and associated vegetation changes. Purely statistical forecasts based on current vegetation cannot be relied upon, in the presence of biotic feedbacks. Our results further suggest that vegetation management could reduce fire risk in some systems by altering the abundance and distribution of the most highly flammable fuels and thus mitigate the impact of climate change on fire activity.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.038
GPT teacher head0.353
Teacher spread0.315 · 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