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Record W2117857640 · doi:10.5194/bg-10-5061-2013

Timing of fire relative to seed development may enable non-serotinous species to recolonize from the aerial seed banks of fire-killed trees

2013· article· en· W2117857640 on OpenAlexafffund
Sean T. Michaletz, Edward A. Johnson, William Mell, David F. Greene

Bibliographic record

VenueBiogeosciences · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsConcordia UniversityUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaWestern Canada Research GridCompute Canada
KeywordsFire regimeCrown (dentistry)BiologyEnvironmental scienceEcologyEcosystem

Abstract

fetched live from OpenAlex

Abstract. The existence of non-serotinous, non-sprouting species in fire regimes where serotiny confers an adaptive advantage is puzzling, particularly when these species recruit poorly from soil seed banks or from burn edges. In this paper, white spruce (Picea glauca (Moench) Voss) was used to show how the timing of fire relative to seed development may permit non-serotinous species to recolonize burned areas from the aerial seed banks of fire-killed trees. To estimate survival of seeds within closed cones during crown fires, cone heating was simulated using a one-dimensional conduction model implemented in a three-dimensional computational fluid dynamics fire behavior model. To quantify the area burned when germinable seed would be contained within closed cones during a mast year, empirical fire occurrence and seed development (germinability and cone opening) data were compared for multiple locations across the white spruce range. Approximately 12% of cones contained viable seed following crown fire simulations (0.072 m s−1 mean spread rate; 9147 kW m−1 mean intensity), and roughly half of the historical area burned resulted from fires that occurred when closed cones would contain germinable seed. Together, these results suggest that non-serotinous species may recolonize burned areas from in situ aerial seed banks, and that this may be an important cause of their existence in fire regimes to which they otherwise seem poorly suited.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.311
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.209
Teacher spread0.195 · 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; both teacher heads agree on what is shown here.

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

Citations29
Published2013
Admission routes2
Has abstractyes

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