MétaCan
Menu
Back to cohort
Record W2202265451 · doi:10.1139/cjfr-2014-0512

Towards silvicultural mitigation of the European ash (<i>Fraxinus excelsior</i>) dieback: the importance of acclimated trees in retention forestry

2015· article· en· W2202265451 on OpenAlexvenueno aff
Raul Rosenvald, Rein Drenkhan, Taavi Riit, Asko Lõhmus

Bibliographic record

VenueCanadian Journal of Forest Research · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
FundersEuropean Regional Development FundEuropean Commission
KeywordsFraxinusCrown (dentistry)ForestryTree healthBiologySilvicultureResistance (ecology)HorticultureAgroforestryBotanyAgronomyGeography

Abstract

fetched live from OpenAlex

The European ash (Fraxinus excelsior L.) dieback is an acute forest pathology problem caused by the invasive ascomycete Hymenoscyphus fraxineus (T. Kowalski) Baral, Queloz, Hosoya. There are no practical solutions yet, but selection for resistant genotypes and intensive care have been highlighted as options. Our aim was to assess the disease mitigation potential of silvicultural harvests, which influence stress levels in retained trees. We annually monitored 577 retention trees on Estonian cut areas for 13 years, including 9 years impacted by the dieback. Sixty-five percent of the trees survived and 15% retained healthy crown, despite all sampled trees being infected. The damage was smallest in the trees retained near precut edges. Former forest-interior trees that were left in central parts of the cut areas suffered high initial damage but smaller disease progression than trees near postcut edges. Tree size and secondary infection by Armillaria spp. were not related to disease progression, but rapid decline was observed in the region with the highest density of ash trees retained. Our results indicate a significant silvicultural potential for tree resistance. Ash trees tend to be healthiest in open conditions, which probably inhibit the pathogen and provide better resources for the tree. Location near precut edges is an important tree retention criterion, which can mitigate initial harvest-induced stress.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.482
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.044
GPT teacher head0.282
Teacher spread0.238 · 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

Citations28
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Forest ResearchSame topicForest Insect Ecology and ManagementFrench-language works237,207