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Record W2046557917 · doi:10.1029/2005gl023646

Observed and predicted responses of plant growth to climate across Canada

2005· article· en· W2046557917 on OpenAlexaboutno aff
Andrew G. Bunn, S. J. Goetz, Greg Fiske

Bibliographic record

VenueGeophysical Research Letters · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsClimatologyClimate changeEnvironmental sciencePhysical geographyGeologyGeographyMeteorologyOceanography

Abstract

fetched live from OpenAlex

Using satellite observations from 1981–2000, and data interpolated from surface weather stations, we examined the association between gross photosynthetic activity (Pg) and climate across the boreal forest and tundra of Canada. The response of annual and interannual Pg was tightly coupled to climate, and seasonal associations between Pg and climate varied with plant functional types. The most important variable for modeling summer growth of conifer forests was the previous spring minimum temperature, whereas tundra responded primarily to summer maximum temperature. Using general circulation model predictors to 2050, we project that tundra will continue to grow vigorously in the coming decades while conifer forests will not. Increased tundra productivity will likely be associated with changes in vegetation composition (e.g., woody proliferation). If these biotic responses are stationary and persist as predicted, terrestrial carbon budgets will need to be modified.

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)0.001
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 score0.021
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.047
GPT teacher head0.294
Teacher spread0.247 · 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

Citations72
Published2005
Admission routes1
Has abstractyes

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