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Record W1986205291 · doi:10.1139/x05-015

Adaptive strategies in seedlings of three co-occurring, ecologically distinct northern coniferous tree species across an elevational gradient

2005· article· en· W1986205291 on OpenAlexfundvenueno aff
D Scott Green

Bibliographic record

VenueCanadian Journal of Forest Research · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
FundersUniversity of British ColumbiaUniversity of Northern British Columbia
KeywordsAbies lasiocarpaPicea engelmanniiPinus contortaBiologyEcologyTree lineSpecific leaf areaBotanyClimate changePhotosynthesis

Abstract

fetched live from OpenAlex

The inherent clinal responses of four quantitative traits thought to be adaptive for trees in cold-limited environments (i.e., height-growth cessation, growth rate, resource allocation to aboveground and belowground tissues, and resource allocation to photosynthetic and nonphotosynthetic tissues in the shoot) were characterized under nonlimiting conditions in a controlled glasshouse study for seedlings of three ecologically distinct and co-occurring northern tree species (Pinus contorta Dougl. var. latifolia Engelm. (lodgepole pine), Picea glauca (Moench) Voss × Picea engelmannii Parry ex Engelm. (interior spruce), and Abies lasiocarpa (Hook.) Nutt. (subalpine fir)). For each species, clinal trends were quantified among populations adapted to increasingly cold-limited climates across an elevation gradient approaching the tree line. In subalpine fir seedlings, strong clinal variation for all the quantitative traits indicated an increasingly conservative response to climate moving toward harsher conditions. Variation in lodgepole pine and interior spruce seedlings suggested a more plastic strategy, favoring competitive traits across a wide range of climate conditions. Study findings suggest that ecologically distinct species may exhibit different strategies in adapting to local climates.

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)0.002
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 score0.947
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.086
GPT teacher head0.326
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

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

Citations33
Published2005
Admission routes2
Has abstractyes

Explore more

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