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Record W2101776730 · doi:10.1093/forestry/cpr019

Balsam fir sawfly defoliation effects on survival and growth quantified from permanent plots and dendrochronology

2011· article· en· W2101776730 on OpenAlexafffundabout
Javed Iqbal, David A. MacLean, John A. Kershaw

Bibliographic record

VenueForestry An International Journal of Forest Research · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of New Brunswick
FundersAtlantic Canada Opportunities Agency
KeywordsAbies balsameaBalsamSawflySpruce budwormBiologyPEST analysisAgronomyBroodForestryTortricidaeHorticultureEcologyGeography

Abstract

fetched live from OpenAlex

Balsam fir sawfly (Neodiprion abietis (Harris)) has become a serious pest of young managed balsam fir (Abies balsamea (L.) Mill.) stands in western Newfoundland, Canada. During 1991–2008, a total area of 561 000 hectares was moderate to severely defoliated. We quantified impacts (growth and survival) using data from permanent sample plots (PSPs) and dendrochronology and related these impacts to defoliation severity determined from aerial defoliation data, in order to provide input into a Decision Support System. We analyzed 67 Newfoundland Forest Service PSPs, selected based on severity of defoliation (classes 1–6), stand age and management interventions (pre-commercially thinned vs natural) and measured before and after defoliation (1996–2008). We used Bayesian statistics to combine information from different sources, each having their own limitations and associated uncertainty. No mortality was observed in immature plots 12 years after defoliation, but survival was 54 per cent lower in mature defoliated than in non-defoliated plots. Plots in defoliation class 1 (1 year of moderate, 30–70 per cent, defoliation) showed 22 per cent cumulative growth reduction and complete recovery to pre-defoliation growth increment after 5 years. Plots in defoliation classes 2–6 (one to three consecutive years of severe, 71–100 per cent, defoliation) had mean cumulative growth reductions of 26–40 per cent and did not recover to pre-defoliation levels even 9 years after defoliation ceased. Natural and thinned plots responded similarly to defoliation severity. These results suggest that proactive control measures need to be implemented since impacts are severe, even with only 1 year of severe defoliation.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.501

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 communication0.0000.001
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 head0.046
GPT teacher head0.318
Teacher spread0.272 · 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

Citations6
Published2011
Admission routes3
Has abstractyes

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