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Stability in the patterns of long‐term development and growth of the Canadian spruce–moss forest

2010· article· en· W1495997430 on OpenAlexaffabout
Stefanie L. Pollock, Serge Payette

Bibliographic record

VenueJournal of Biogeography · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversité LavalNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsBlack spruceMossAbies balsameaTaigaForestryQuadratBalsamTransectOld-growth forestStand developmentForest ecologyChronosequenceGeographyEcologySecondary forestEnvironmental scienceForest floorPicea abiesDisturbance (geology)Forest dynamicsEcosystemBiologyBotany

Abstract

fetched live from OpenAlex

Abstract Aim The spruce–moss forest is the main forest ecosystem of the North American boreal forest. We used stand structure and fire data to examine the long‐term development and growth of the spruce–moss ecosystem. We evaluate the stability of the forest with time and the conditions needed for the continuing regeneration, growth and re‐establishment of black spruce ( Picea mariana ) trees. Location The study area occurs in Québec, Canada, and extends from 70°00′ to 72°00′ W and 47°30′ to 56°00′ N. Methods A spatial inventory of spruce–moss forest stands was performed along 34 transects. Nineteen spruce–moss forests were selected. A 500 m 2 quadrat at each site was used for radiocarbon and tree‐ring dating of time since last fire (TSLF). Size structure and tree regeneration in each stand were described based on diameter distribution of the dominant and co‐dominant tree species [black spruce and balsam fir ( Abies balsamea )]. Results The TSLF of the studied forests ranges from 118 to 4870 cal. yr bp . Forests < 325 cal. yr bp are dominated by trees of the first post‐fire cohort and are not yet at equilibrium, whereas older forests show a reverse‐J diameter distribution typical of mature, old‐growth stands. The younger forests display faster height and radial growth‐rate patterns than the older forests, due to factors associated with long‐term forest development. Each of the stands examined established after severe fires that consumed all the soil organic material. Main conclusions Spruce–moss forests are able to self‐regenerate after fires that consume the organic layer, thus allowing seed regeneration at the soil surface. In the absence of fire the forests can remain in an equilibrium state. Once the forests mature, tree productivity eventually levels off and becomes stable. Further proof of the enduring stability of these forests, in between fire periods, lies in the ages of the stands. Stands with a TSLF of 325–4870 cal. yr bp all exhibited the same stand structure, tree growth rates and species characteristics. In the absence of fire, the spruce–moss forests are able to maintain themselves for thousands of years with no apparent degradation or change in forest type.

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 score0.722
Threshold uncertainty score0.926

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 head0.006
GPT teacher head0.190
Teacher spread0.184 · 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".

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Citations47
Published2010
Admission routes2
Has abstractyes

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