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Record W3110887155 · doi:10.1088/1748-9326/abd214

High risk of growth cessation of planted larch under extreme drought

2020· article· en· W3110887155 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

VenueEnvironmental Research Letters · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversity of New Brunswick
FundersNational Key Research and Development Program of ChinaHebei Agricultural UniversityNational Natural Science Foundation of ChinaNatural Environment Research CouncilSight Research UKNational Science Foundation
KeywordsLarchAfforestationPrecipitationEnvironmental scienceDendrochronologyClimate changeAgroforestryGeographyBiologyEcology

Abstract

fetched live from OpenAlex

Abstract Larch trees are widely used in afforestation and timber plantations. Yet, little is known on how planted larch trees cope with increasing drought. We used a tree-ring network of 818 trees from 31 plantations spanning most of the distribution of Larix principis-rupprechtii to investigate how extreme drought influences larch radial growth in northern China. We found that summer drought, rather than temperature or precipitation, had the strongest relationship with radial growth throughout the region. Drought increased in frequency in recent decades, leaving a strong imprint on the radial growth of larch, particularly in dry sites. Across its distribution, radial growth in larch trees that experienced extreme droughts more frequently displayed lower resistance to drought, but higher recovery after it, suggesting these populations were better adapted to extreme droughts. Radial growth decreased with increasing drought, with particularly severe declines below a threshold Palmer Drought Severity Index (PDSI) value of −3 to −3.5. Extreme droughts (PDSI < −4.5) caused a reduction of 62% of radial growth and chronic drought events caused around 20% reduction in total radial growth compared with mean growth on the driest sites. Given that current climate projections for northern China indicate a strong increase in the frequency and severity of extreme drought, trees in large portions of the largest afforestation project in the world, particularly those in the drier edge, are likely to experience severe growth reductions in the future.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.058
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.258
Teacher spread0.204 · 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