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Record W2206343489 · doi:10.1139/cjfr-2015-0239

Soil moisture controls Engelmann spruce (<i>Picea engelmannii</i>) seedling carbon balance and survivorship at timberline in Utah, USA

2015· article· en· W2206343489 on OpenAlexvenueno aff
Richard Gill, Colin S. Campbell, Sarah M. Karlinsey

Bibliographic record

VenueCanadian Journal of Forest Research · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
FundersBrigham Young University
KeywordsPicea engelmanniiAbies lasiocarpaGrowing seasonEnvironmental scienceAbiotic componentAltitude (triangle)PrecipitationSeedlingEcologyBiologyAtmospheric sciencesPinus contortaAgronomyGeographyGeology

Abstract

fetched live from OpenAlex

Most hypotheses about controls over high-altitude forests, including treeline, the elevation for upright woody plants, or timberline, the upper elevation for aggregated forest, suggest that low temperature drives forest dynamics, either through effects on cell division and tree growth or indirectly through frost damage or nutrient availability. However, abiotic factors other than temperature, including water availability, may serve as other important controls at high elevations, particularly for seedlings. To test the hypothesis that the timing and amount of precipitation exerts a strong control over the high-elevation forest boundary on the Wasatch Plateau in central Utah, USA, we conducted a field experiment that manipulated water availability and monitored photosynthesis, growth, and survivorship in Picea engelmannii Parry ex Engelm. seedlings. Survivorship increased from the driest to the wettest conditions, whereas the timing of precipitation did not explain differences in survival. However, we found that large, infrequent rain events increased maximum photosynthetic flux density compared with small, frequent rain events. Our results highlight the potential role of growing season water availability in limiting timberline expansion below the low-temperature thermal limits of P. engelmannii. As a consequence, the infilling of trees below the treeline in this region in response to climate change is likely to be episodic and driven by multiyear periods of high water availability and frequency that overcome drought limitations.

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)0.005
metaresearch head score (Gemma)0.002
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 score0.697
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.054
GPT teacher head0.285
Teacher spread0.231 · 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

Citations26
Published2015
Admission routes1
Has abstractyes

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