MétaCan
Menu
Back to cohort
Record W2012146990 · doi:10.1139/x09-085

Assessing dendroecological methods to reconstruct defoliator outbreaks on <i>Nothofagus pumilio</i> in northwestern Patagonia, Argentina

2009· article· en· W2012146990 on OpenAlexvenueno aff
Juan Paritsis, Thomas T. Veblen, Thomas Kitzberger

Bibliographic record

VenueCanadian Journal of Forest Research · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsDendrochronologyNothofagusEcologyOutbreakBiologyGeographyArchaeology

Abstract

fetched live from OpenAlex

We examined the use of dendroecological techniques for detecting past defoliations caused by Ormiscodes amphimone Fabricius (Saturniidae) in Nothofagus pumilio (Poepp. et Endl.) Krasser forests in northwestern Patagonia. We evaluated the suitability of the conifer Austrocedrus chilensis (D. Don) Pic. Serm. et Bizarri as a nonhost climate control for reconstructing Ormiscodes outbreaks on N. pumilio. Additionally, we assessed the effectiveness of three alternative procedures to detect past outbreaks: the use of a regional host chronology (instead of the nonhost chronology), the detection of pointer years (i.e., extremely narrow tree rings caused by defoliation), and the use of a morphological tree-ring signature associated with defoliation. Although differences in tree-ring growth response to climate between N. pumilio and A. chilensis did not support the use of the latter species as a reliable climatic control in most of our study area, the alternative procedures were effective in detecting past defoliation events. Based on the performance of the methods assessed here, we designed and tested a protocol for reconstructing past Ormiscodes defoliations on N. pumilio stands. Our results reinforce the need to conduct explicit comparisons of growth responses to climatic variability for host and potential nonhost species on a site-specific basis as well as the advantages of using multiple independent methods to more accurately detect past insect outbreaks.

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)0.001
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 score0.647
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
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 head0.094
GPT teacher head0.385
Teacher spread0.291 · 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

Citations34
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Forest ResearchSame topicTree-ring climate responsesFrench-language works237,207