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Record W3155876146 · doi:10.1139/cjfr-2020-0491

Dendroclimatic analysis of central Appalachian red spruce in West Virginia

2021· article· en· W3155876146 on OpenAlexvenueno aff
Eric Yetter, Sophan Chhin, John P. Brown

Bibliographic record

VenueCanadian Journal of Forest Research · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsLatitudeGeographyGrowing seasonPhysical geographyDendroclimatologyRange (aeronautics)Climate changeForestryBlack spruceEnvironmental scienceTaigaClimatologyEcologyDendrochronologyArchaeologyBiologyGeology

Abstract

fetched live from OpenAlex

We conducted dendroclimatic analyses and constructed future growth projections for red spruce (Picea rubens Sarg.) throughout the central Appalachians in the state of West Virginia. This study involved field sampling of 18 sites across red spruce’s range in six regions throughout the Monongahela National Forest that were selected based on pairwise combinations of three latitudinal groups (north, central, and south) with two aspects (north and south). Each combination of latitudinal group and aspect was referred to as a landscape cluster. Growth was negatively impacted by high summer temperature stress but responded favorably to high fall temperatures. The results also suggested that red spruce was likely impacted by the degree of winter harshness in all landscape clusters. In the northern latitudinal landscape clusters, red spruce responded favorably to warm spring temperatures by allowing an early start to the growing season. Growth projections under a future climate change scenario show that future expected increases in mean and maximum monthly temperatures will have negative effects on future spruce growth. The forecasting results suggested that red spruce in northern latitudes on south aspects or central latitudes on north aspects are the landscape clusters that will likely be the most resilient to future climate change. Dendroclimatic results and future growth projections can assist with identifying locations that are most suitable for future red spruce restoration activities.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.907
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.037
GPT teacher head0.295
Teacher spread0.258 · 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.

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

Citations9
Published2021
Admission routes1
Has abstractyes

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