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Record W2033847467 · doi:10.1111/jbi.12229

The legacy of mid‐Holocene fire on a Tasmanian montane landscape

2013· article· en· W2033847467 on OpenAlexaff
Michael‐Shawn Fletcher, Brent B. Wolfe, Cathy Whitlock, David P. Pompeani, Simon Haberle, Patricia Gadd, David M. J. S. Bowman

Bibliographic record

VenueJournal of Biogeography · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsWilfrid Laurier University
FundersNational Science Foundation
KeywordsVegetation (pathology)EcologyFire regimeRainforestClimate changeDrainage basinHoloceneErosionPhysical geographyEnvironmental scienceGeographyGeologyEcosystemArchaeologyBiologyGeomorphology

Abstract

fetched live from OpenAlex

Abstract Aim To assess the long‐term impacts of landscape fire on a mosaic of pyrophobic and pyrogenic woody montane vegetation. Location South‐west T asmania, A ustralia. Methods We undertook a high‐resolution multiproxy palaeoecological analysis of sediments deposited in L ake O sborne ( H artz M ountains N ational P ark, southern T asmania), employing analyses of pollen, macroscopic and microscopic charcoal, organic and inorganic geochemistry and magnetic susceptibility. Results Sequential fires within the study catchment over the past 6500 years have resulted in the reduction of pyrophobic rain forest taxa and the establishment of pyrogenic E ucalyptus ‐dominated vegetation. The vegetation change was accompanied by soil erosion and nutrient losses. The rate of post‐fire recovery of widespread rain forest taxa ( N othofagus cunninghamii and E ucryphia spp.) conforms to ecological models, as does the local extinction of fire‐sensitive rain forest taxa ( N othofagus gunnii and C upressaceae) following successive fires. Main conclusions The sedimentary analyses indicate that recurrent fires over several centuries caused a catchment‐wide transition from pyrophobic rain forest to pyrophytic eucalypt‐dominated vegetation. The fires within the lake catchment during the 6500‐year long record appear to coincide with high‐frequency E l N iño events in the equatorial Pacific Ocean, signalling a potential threat to these highly endemic rain forests if E l N iño intensity amplifies as predicted under future climate scenarios.

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)0.000
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 score0.164
Threshold uncertainty score0.515

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 head0.004
GPT teacher head0.183
Teacher spread0.180 · 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.

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

Citations73
Published2013
Admission routes1
Has abstractyes

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