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Nitrogen nutrition of poplar trees

2010· review· en· W1719075847 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

VenuePlant Biology · 2010
Typereview
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsBiologyEcosystemNitrateNitrogen cycleCyclingForest ecologyEcologyNutrientAgronomyBark (sound)Nutrient cycleHerbaceous plantBotanyNitrogenEnvironmental scienceForestry

Abstract

fetched live from OpenAlex

Many forest ecosystems have evolved at sites with growth-limiting nitrogen (N) availability, low N input from external sources and high ecosystem internal cycling of N. By contrast, many poplar species are frequent constituents of floodplain forests where they are exposed to a significant ecosystem external supply of N, mainly nitrate, in the moving water table. Therefore, nitrate is much more important for N nutrition of these poplar species than for many other tree species. We summarise current knowledge of nitrate uptake and its regulation by tree internal signals, as well as acquisition of ammonium and organic N from the soil. Unlike herbaceous plants, N nutrition of trees is sustained by seasonal, tree internal cycling. Recent advances in the understanding of seasonal storage and mobilisation in poplar bark and regulation of these processes by temperature and daylength are addressed. To explore consequences of global climate change on N nutrition of poplar trees, responses of N uptake and metabolism to increased atmospheric CO(2) and O(3) concentrations, increased air and soil temperatures, drought and salt stress are highlighted.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.998
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.018
GPT teacher head0.247
Teacher spread0.229 · 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