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Record W2150088413 · doi:10.1093/treephys/tps064

Sunflecks in trees and forests: from photosynthetic physiology to global change biology

2012· review· en· W2150088413 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTree Physiology · 2012
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to elevated CO2
Canadian institutionsWestern University
Fundersnot available
KeywordsCanopyPhotosynthesisEnvironmental scienceCarbon fixationPhotosynthetic capacityBiologyAtmospheric sciencesClimate changeSeedlingCarbon cycleBotanyEcologyAgronomyEcosystemPhysics

Abstract

fetched live from OpenAlex

Sunflecks are brief, intermittent periods of high photon flux density (PFD) that can significantly improve carbon gain in shaded forest understories and lower canopies of trees. In this review, we discuss the physiological basis of leaf-level responses to sunflecks and the mechanisms plants use to tolerate sudden changes in PFD and leaf temperature induced by sunflecks. We also examine the potential effects of climate change stresses (including elevated temperatures, rising CO(2) concentrations and drought) on the ability of tree species to use sunflecks, and advocate more research to improve our predictions of seedling and tree carbon gain in future climates. Lastly, while we have the ability to model realistic responses of photosynthesis to fluctuating PFD, dynamic responses of photosynthesis to sunflecks are not accounted for in current models of canopy carbon uptake, which can lead to substantial overestimates of forest carbon fixation. Since sunflecks are a critical component of seasonal carbon gain for shaded leaves, sunfleck regimes and physiological responses to sunflecks should be incorporated into models to more accurately capture forest carbon dynamics.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.088
GPT teacher head0.309
Teacher spread0.220 · 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