MétaCan
Menu
Back to cohort
Record W2157341940 · doi:10.1139/x01-133

Photosynthesis, nitrogen-use efficiency, and water-use efficiency of jack pine seedlings in competition with four boreal forest plant species

2001· article· en· W2157341940 on OpenAlexvenueaboutno aff
Darren E. Robinson, Robert G. Wagner, Frederick W. Bell, Clarence J. Swanton

Bibliographic record

VenueCanadian Journal of Forest Research · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsnot available
FundersSustainable Forestry Initiative
KeywordsTaigaRubusWater-use efficiencyAgronomyBotanyNitrogenSoil waterCompetition (biology)BiologyEnvironmental sciencePhotosynthesisHorticultureChemistryEcology

Abstract

fetched live from OpenAlex

The objective of this study was to understand the mechanism underlying nitrogen (N) and water competition between jack pine (Pinus banksiana Lamb.) and four boreal forest species. Large-leaved aster (Aster macrophyllus L.), Canada blue-joint grass (Calamagrostis canadensis (Michx.) Beauv.), trembling aspen (Populus tremuloides (Michx.), and red raspberry (Rubus idaeus L.) were planted at a range of densities (0-8 plants/m 2 ) with jack pine seedlings. Net photosynthesis (P n ), nitrogen-use efficiency (NUE), water-use efficiency (WUE) of each species were monitored over three consecutive growing seasons. Changes in available soil N and water were also measured. Jack pine P n , NUE, and WUE decreased as competitor density increased, but these effects varied among species (p < 0.001) and over time (p < 0.001). The influence of density on jack pine P n decreased over time for aster and blue-joint grass and increased over time for aspen and raspberry (p < 0.001). At most sample times, jack pine P n correlated with available soil N. In contrast, the correlation between jack pine P n and soil water was rarely significant.

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 score0.481
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.041
GPT teacher head0.242
Teacher spread0.201 · 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

Citations46
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Forest ResearchSame topicSeedling growth and survival studiesFrench-language works237,207