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Record W1996981148 · doi:10.1139/x09-195

Size-symmetric versus size-asymmetric competition and growth partitioning among trees in forest stands along an ecological gradient in central Europe

2010· article· en· W1996981148 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Forest Research · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
FundersDeutsche Forschungsgemeinschaft
KeywordsScots pineCompetition (biology)Picea abiesEcologyBasal areaQuercus petraeaInterspecific competitionRange (aeronautics)Pinus <genus>BiologyEnvironmental scienceBotany

Abstract

fetched live from OpenAlex

Current individual tree growth models rarely consider the mode of tree competition, which can be size-asymmetric when growth is limited by light or size-symmetric when belowground resources are scarce. Even with the same competition index, growth reactions may vary considerably due to a prevailing resource limitation, as the dominant trees in a stand benefit disproportionately more on light-limited sites. To scrutinize and model the relationship between mode of competition and site conditions, 34 long-term experiments with 120 plots dating back to 1871 were used. The data cover the dominating tree species in central Europe along a broad range of ecological conditions. For Norway spruce ( Picea abies (L.) Karst.), Scots pine ( Pinus sylvestris L.), and sessile oak ( Quercus petrea (Matt.) Liebl.), stronger light competition can be shown on fertile sites compared with sites with poorer conditions. Based on these findings, we constructed an enhanced version of a classic potential modifier growth model. Simulations for archetypical stands yield a transition from size-asymmetric to size-symmetric competition along the gradient from fertile to poor sites that is not covered by traditional models. It was concluded that by integrating the interaction between competition and site quality, individual tree models become more site sensitive, a prerequisite for their application under fluctuating environmental conditions.

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.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.935
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.264
Teacher spread0.240 · 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