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Record W2120931434 · doi:10.1139/x07-092

Fire and substrate interact to control the northern range limit of black spruce (<i>Picea mariana</i>) in Alaska

2007· article· en· W2120931434 on OpenAlexvenueaboutno aff
Andrea H. Lloyd, Christopher L. Fastie, Hilary Genevieve Eisen

Bibliographic record

VenueCanadian Journal of Forest Research · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsBlack spruceEcologySubstrate (aquarium)Range (aeronautics)Picea abiesSexual reproductionReproductionBiologyTaiga

Abstract

fetched live from OpenAlex

Black spruce ( Picea mariana (Mill.) BSP) is a common treeline species in eastern Canada but rare at treeline in Alaska. We investigated fire and substrate effects on black spruce populations at six sites along a 74 km transect in the Brooks Range, Alaska. Our southern sites, on a surface deglaciated >50 000 years ago, had significantly more acidic soils, more black spruce, and higher seed viability than our northern sites, which were deglaciated approximately 13 000 years ago. Despite similar fire history at five of our six sites, postfire recruitment dynamics varied with surface age. Sexual reproduction was vigorous in both postfire and nonfire years in populations on the older surface. On the younger surface, vigorous sexual reproduction was restricted to postfire decades and clonal reproduction by branch layering predominated in nonfire years. At the northernmost site, which was unburned, black spruce reproduced almost exclusively by layering. The species’ northern range limit thus reflects an interaction between fire and substrate: on recently deglaciated surfaces, sexual reproduction is restricted to postfire years. This substrate-induced dependence on fire may restrict the range of black spruce to sites that burn sufficiently often to allow occasional sexual reproduction.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.042
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.017
GPT teacher head0.262
Teacher spread0.245 · 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 source (direct Gemma or distilled Codex), 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

Citations18
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Forest Research→Same topicFire effects on ecosystems→French-language works237,207→