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Record W2340994711 · doi:10.3390/f7040083

Burn Severity Dominates Understory Plant Community Response to Fire in Xeric Jack Pine Forests

2016· article· en· W2340994711 on OpenAlexaffabout
Bradley D. Pinno, Ruth C. Errington

Bibliographic record

VenueForests · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsNatural Resources CanadaCanadian Forest Service
Fundersnot available
KeywordsDeserts and xeric shrublandsUnderstoryPlant communitySpecies richnessForbGraminoidEcologyPrescribed burnDisturbance (geology)RevegetationEnvironmental scienceCanopyBiologyEcological successionGrasslandHabitat

Abstract

fetched live from OpenAlex

Fire is the most common disturbance in northern boreal forests, and large fires are often associated with highly variable burn severities across the burnt area. We studied the understory plant community response to a range of burn severities and pre-fire stand age four growing seasons after the 2011 Richardson Fire in xeric jack pine forests of northern Alberta, Canada. Burn severity had the greatest impact on post-fire plant communities, while pre-fire stand age did not have a significant impact. Total plant species richness and cover decreased with disturbance severity, such that the greatest richness was in low severity burns (average 28 species per 1-m2 quadrat) and plant cover was lowest in the high severity burns (average 16%). However, the response of individual plant groups differed. Lichens and bryophytes were most common in low severity burns and were effectively eliminated from the regenerating plant community at higher burn severities. In contrast, graminoid cover and richness were positively related to burn severity, while forbs did not respond significantly to burn severity, but were impacted by changes in soil chemistry with increased cover at pH >4.9. Our results indicate the importance of non-vascular plants to the overall plant community in this harsh environment and that the plant community is environmentally limited rather than recruitment or competition limited, as is often the case in more mesic forest types. If fire frequency and severity increase as predicted, we may see a shift in plant communities from stress-tolerant species, such as lichens and ericaceous shrubs, to more colonizing species, such as certain graminoids.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.141
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.012
GPT teacher head0.226
Teacher spread0.214 · 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.

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

Citations28
Published2016
Admission routes2
Has abstractyes

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