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Record W3120293272 · doi:10.1139/cjfr-2020-0466

Positive response of tree productivity to warming is reversed by increased tree density at the Arctic tundra–taiga ecotone

2021· article· en· W3120293272 on OpenAlexvenueno aff
Xanthe J. Walker, Heather D. Alexander, Logan T. Berner, Molly Boyd, M. M. Loranty, Susan M. Natali, Michelle C. Mack

Bibliographic record

VenueCanadian Journal of Forest Research · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsTundraEcotoneNormalized Difference Vegetation IndexTaigaLarchProductivityEnvironmental scienceTree lineGrowing seasonBorealArcticPhysical geographyClimate changeEcologyBiologyGeographyShrub

Abstract

fetched live from OpenAlex

The transition zone between the northern boreal forest and the Arctic tundra, known as the tundra–taiga ecotone (TTE) has undergone rapid warming in recent decades. In response to this warming, tree density, growth, and stand productivity are expected to increase. Increases in tree density have the potential to negate the positive impacts of warming on tree growth through a reduction in the active layer and an increase in competitive interactions. We assessed the effects of tree density on tree growth and climate–growth responses of Cajander larch (Larix cajanderi Mayr.) and on trends in the normalized difference vegetation index (NDVI) in the TTE of Northeast Siberia. We examined 19 mature forest stands that all established after a fire in 1940 and ranged in tree density from 300 to 37 000 stems·ha −1 . High-density stands with shallow active layers had lower tree growth, higher stand productivity, and more negative growth responses to growing season temperatures compared with low-density stands with deep active layers. Variation in stand productivity across the density gradient was not captured by Landsat-derived NDVI, but NDVI did capture annual variations in stand productivity. Our results suggest that the expected increases in tree density following fires at the TTE may effectively limit tree growth and that NDVI is unlikely to capture increasing productivity associated with changes in tree density.

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)0.007
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 score0.776
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.283
Teacher spread0.248 · 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

Citations22
Published2021
Admission routes1
Has abstractyes

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